Spatial Distributions of Young Stars

NASA Astrophysics Data System (ADS)

Kraus, Adam L.; Hillenbrand, Lynne A.

2008-10-01

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

Sample size calculations for case-control studies

Cancer.gov

This R package can be used to calculate the required samples size for unconditional multivariate analyses of unmatched case-control studies. The sample sizes are for a scalar exposure effect, such as binary, ordinal or continuous exposures. The sample sizes can also be computed for scalar interaction effects. The analyses account for the effects of potential confounder variables that are also included in the multivariate logistic model.

Influence of management of variables, sampling zones and land units on LR analysis for landslide spatial prevision

NASA Astrophysics Data System (ADS)

Greco, R.; Sorriso-Valvo, M.

2013-09-01

Several authors, according to different methodological approaches, have employed logistic Regression (LR), a multivariate statistical analysis adopted to assess the spatial probability of landslide, even though its fundamental principles have remained unaltered. This study aims at assessing the influence of some of these methodological approaches on the performance of LR, through a series of sensitivity analyses developed over a test area of about 300 km2 in Calabria (southern Italy). In particular, four types of sampling (1 - the whole study area; 2 - transects running parallel to the general slope direction of the study area with a total surface of about 1/3 of the whole study area; 3 - buffers surrounding the phenomena with a 1/1 ratio between the stable and the unstable area; 4 - buffers surrounding the phenomena with a 1/2 ratio between the stable and the unstable area), two variable coding modes (1 - grouped variables; 2 - binary variables), and two types of elementary land (1 - cells units; 2 - slope units) units have been tested. The obtained results must be considered as statistically relevant in all cases (Aroc values > 70%), thus confirming the soundness of the LR analysis which maintains high predictive capacities notwithstanding the features of input data. As for the area under investigation, the best performing methodological choices are the following: (i) transects produced the best results (0 < P(y) ≤ 93.4%; Aroc = 79.5%); (ii) as for sampling modalities, binary variables (0 < P(y) ≤ 98.3%; Aroc = 80.7%) provide better performance than ordinated variables; (iii) as for the choice of elementary land units, slope units (0 < P(y) ≤ 100%; Aroc = 84.2%) have obtained better results than cells matrix.

Zonal wavefront sensing with enhanced spatial resolution.

PubMed

Pathak, Biswajit; Boruah, Bosanta R

2016-12-01

In this Letter, we introduce a scheme to enhance the spatial resolution of a zonal wavefront sensor. The zonal wavefront sensor comprises an array of binary gratings implemented by a ferroelectric spatial light modulator (FLCSLM) followed by a lens, in lieu of the array of lenses in the Shack-Hartmann wavefront sensor. We show that the fast response of the FLCSLM device facilitates quick display of several laterally shifted binary grating patterns, and the programmability of the device enables simultaneous capturing of each focal spot array. This eventually leads to a wavefront estimation with an enhanced spatial resolution without much sacrifice on the sensor frame rate, thus making the scheme suitable for high spatial resolution measurement of transient wavefronts. We present experimental and numerical simulation results to demonstrate the importance of the proposed wavefront sensing scheme.

Estimating neighborhood variability with a binary comparison matrix.

USGS Publications Warehouse

Murphy, D.L.

1985-01-01

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

Converting optical scanning holograms of real objects to binary Fourier holograms using an iterative direct binary search algorithm.

PubMed

Leportier, Thibault; Park, Min Chul; Kim, You Seok; Kim, Taegeun

2015-02-09

In this paper, we present a three-dimensional holographic imaging system. The proposed approach records a complex hologram of a real object using optical scanning holography, converts the complex form to binary data, and then reconstructs the recorded hologram using a spatial light modulator (SLM). The conversion from the recorded hologram to a binary hologram is achieved using a direct binary search algorithm. We present experimental results that verify the efficacy of our approach. To the best of our knowledge, this is the first time that a hologram of a real object has been reconstructed using a binary SLM.

GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update

PubMed Central

Peakall, Rod; Smouse, Peter E.

2012-01-01

Summary: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G′ST, G′′ST, Jost’s Dest and F′ST through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. Availability and implementation: GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. Contact: rod.peakall@anu.edu.au PMID:22820204

Detecting phase separation of freeze-dried binary amorphous systems using pair-wise distribution function and multivariate data analysis.

PubMed

Chieng, Norman; Trnka, Hjalte; Boetker, Johan; Pikal, Michael; Rantanen, Jukka; Grohganz, Holger

2013-09-15

The purpose of this study is to investigate the use of multivariate data analysis for powder X-ray diffraction-pair-wise distribution function (PXRD-PDF) data to detect phase separation in freeze-dried binary amorphous systems. Polymer-polymer and polymer-sugar binary systems at various ratios were freeze-dried. All samples were analyzed by PXRD, transformed to PDF and analyzed by principal component analysis (PCA). These results were validated by differential scanning calorimetry (DSC) through characterization of glass transition of the maximally freeze-concentrate solute (Tg'). Analysis of PXRD-PDF data using PCA provides a more clear 'miscible' or 'phase separated' interpretation through the distribution pattern of samples on a score plot presentation compared to residual plot method. In a phase separated system, samples were found to be evenly distributed around the theoretical PDF profile. For systems that were miscible, a clear deviation of samples away from the theoretical PDF profile was observed. Moreover, PCA analysis allows simultaneous analysis of replicate samples. Comparatively, the phase behavior analysis from PXRD-PDF-PCA method was in agreement with the DSC results. Overall, the combined PXRD-PDF-PCA approach improves the clarity of the PXRD-PDF results and can be used as an alternative explorative data analytical tool in detecting phase separation in freeze-dried binary amorphous systems. Copyright © 2013 Elsevier B.V. All rights reserved.

Self-declared stock ownership and association with positive trial outcome in randomized controlled trials with binary outcomes published in general medical journals: a cross-sectional study.

PubMed

Falk Delgado, Alberto; Falk Delgado, Anna

2017-07-26

Describe the prevalence and types of conflicts of interest (COI) in published randomized controlled trials (RCTs) in general medical journals with a binary primary outcome and assess the association between conflicts of interest and favorable outcome. Parallel-group RCTs with a binary primary outcome published in three general medical journals during 2013-2015 were identified. COI type, funding source, and outcome were extracted. Binomial logistic regression model was performed to assess association between COI and funding source with outcome. A total of 509 consecutive parallel-group RCTs were included in the study. COI was reported in 74% in mixed funded RCTs and in 99% in for-profit funded RCTs. Stock ownership was reported in none of the non-profit RCTs, in 7% of mixed funded RCTs, and in 50% of for-profit funded RCTs. Mixed-funded RCTs had employees from the funding company in 11% and for-profit RCTs in 76%. Multivariable logistic regression revealed that stock ownership in the funding company among any of the authors was associated with a favorable outcome (odds ratio = 3.53; 95% confidence interval = 1.59-7.86; p < 0.01). COI in for-profit funded RCTs is extensive, because the factors related to COI are not fully independent, a multivariable analysis should be cautiously interpreted. However, after multivariable adjustment only stock ownership from the funding company among authors is associated with a favorable outcome.

Accelerated defect visualization of microelectronic systems using binary search with fixed pitch-catch distance laser ultrasonic scanning

NASA Astrophysics Data System (ADS)

Park, Byeongjin; Sohn, Hoon

2018-04-01

The practicality of laser ultrasonic scanning is limited because scanning at a high spatial resolution demands a prohibitively long scanning time. Inspired by binary search, an accelerated defect visualization technique is developed to visualize defect with a reduced scanning time. The pitch-catch distance between the excitation point and the sensing point is also fixed during scanning to maintain a high signal-to-noise ratio of measured ultrasonic responses. The approximate defect boundary is identified by examining the interactions between ultrasonic waves and defect observed at the scanning points that are sparsely selected by a binary search algorithm. Here, a time-domain laser ultrasonic response is transformed into a spatial ultrasonic domain response using a basis pursuit approach so that the interactions between ultrasonic waves and defect can be better identified in the spatial ultrasonic domain. Then, the area inside the identified defect boundary is visualized as defect. The performance of the proposed defect visualization technique is validated through an experiment on a semiconductor chip. The proposed defect visualization technique accelerates the defect visualization process in three aspects: (1) The number of measurements that is necessary for defect visualization is dramatically reduced by a binary search algorithm; (2) The number of averaging that is necessary to achieve a high signal-to-noise ratio is reduced by maintaining the wave propagation distance short; and (3) With the proposed technique, defect can be identified with a lower spatial resolution than the spatial resolution required by full-field wave propagation imaging.

Spatial modeling of households' knowledge about arsenic pollution in Bangladesh.

PubMed

Sarker, M Mizanur Rahman

2012-04-01

Arsenic in drinking water is an important public health issue in Bangladesh, which is affected by households' knowledge about arsenic threats from their drinking water. In this study, spatial statistical models were used to investigate the determinants and spatial dependence of households' knowledge about arsenic risk. The binary join matrix/binary contiguity matrix and inverse distance spatial weight matrix techniques are used to capture spatial dependence in the data. This analysis extends the spatial model by allowing spatial dependence to vary across divisions and regions. A positive spatial correlation was found in households' knowledge across neighboring districts at district, divisional and regional levels, but the strength of this spatial correlation varies considerably by spatial weight. Literacy rate, daily wage rate of agricultural labor, arsenic status, and percentage of red mark tube well usage in districts were found to contribute positively and significantly to households' knowledge. These findings have policy implications both at regional and national levels in mitigating the present arsenic crisis and to ensure arsenic-free water in Bangladesh. Copyright © 2012 Elsevier Ltd. All rights reserved.

Gravitational-wave localization alone can probe origin of stellar-mass black hole mergers.

PubMed

Bartos, I; Haiman, Z; Marka, Z; Metzger, B D; Stone, N C; Marka, S

2017-10-10

The recent discovery of gravitational waves from stellar-mass binary black hole mergers by the Laser Interferometer Gravitational-wave Observatory opened the door to alternative probes of stellar and galactic evolution, cosmology and fundamental physics. Probing the origin of binary black hole mergers will be difficult due to the expected lack of electromagnetic emission and limited localization accuracy. Associations with rare host galaxy types-such as active galactic nuclei-can nevertheless be identified statistically through spatial correlation. Here we establish the feasibility of statistically proving the connection between binary black hole mergers and active galactic nuclei as hosts, even if only a sub-population of mergers originate from active galactic nuclei. Our results are the demonstration that the limited localization of gravitational waves, previously written off as not useful to distinguish progenitor channels, can in fact contribute key information, broadening the range of astrophysical questions probed by binary black hole observations.Binary black hole mergers have recently been observed through the detection of gravitational wave signatures. The authors demonstrate that their association with active galactic nuclei can be made through a statistical spatial correlation.

Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches

USGS Publications Warehouse

Selkowitz, David J.; Forster, Richard; Caldwell, Megan K.

2014-01-01

Remote sensing of snow-covered area (SCA) can be binary (indicating the presence/absence of snow cover at each pixel) or fractional (indicating the fraction of each pixel covered by snow). Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed) pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days and averaged 37 days. Our results suggest that mixed snow-covered snow-free pixels are common at the spatial resolutions imaged by both the Landsat and MODIS sensors. This highlights the additional information available from fractional SCA products and suggests fractional SCA can provide a major advantage for hydrological and climatological monitoring and modeling, particularly when accurate representation of the spatial distribution of snow cover is critical.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

Quantitative analysis of binary polymorphs mixtures of fusidic acid by diffuse reflectance FTIR spectroscopy, diffuse reflectance FT-NIR spectroscopy, Raman spectroscopy and multivariate calibration.

PubMed

Guo, Canyong; Luo, Xuefang; Zhou, Xiaohua; Shi, Beijia; Wang, Juanjuan; Zhao, Jinqi; Zhang, Xiaoxia

2017-06-05

Vibrational spectroscopic techniques such as infrared, near-infrared and Raman spectroscopy have become popular in detecting and quantifying polymorphism of pharmaceutics since they are fast and non-destructive. This study assessed the ability of three vibrational spectroscopy combined with multivariate analysis to quantify a low-content undesired polymorph within a binary polymorphic mixture. Partial least squares (PLS) regression and support vector machine (SVM) regression were employed to build quantitative models. Fusidic acid, a steroidal antibiotic, was used as the model compound. It was found that PLS regression performed slightly better than SVM regression in all the three spectroscopic techniques. Root mean square errors of prediction (RMSEP) were ranging from 0.48% to 1.17% for diffuse reflectance FTIR spectroscopy and 1.60-1.93% for diffuse reflectance FT-NIR spectroscopy and 1.62-2.31% for Raman spectroscopy. The results indicate that diffuse reflectance FTIR spectroscopy offers significant advantages in providing accurate measurement of polymorphic content in the fusidic acid binary mixtures, while Raman spectroscopy is the least accurate technique for quantitative analysis of polymorphs. Copyright © 2017 Elsevier B.V. All rights reserved.

PREDICTING APHASIA TYPE FROM BRAIN DAMAGE MEASURED WITH STRUCTURAL MRI

PubMed Central

Yourganov, Grigori; Smith, Kimberly G.; Fridriksson, Julius; Rorden, Chris

2015-01-01

Chronic aphasia is a common consequence of a left-hemisphere stroke. Since the early insights by Broca and Wernicke, studying the relationship between the loci of cortical damage and patterns of language impairment has been one of the concerns of aphasiology. We utilized multivariate classification in a cross-validation framework to predict the type of chronic aphasia from the spatial pattern of brain damage. Our sample consisted of 98 patients with five types of aphasia (Broca’s, Wernicke’s, global, conduction, and anomic), classified based on scores on the Western Aphasia Battery. Binary lesion maps were obtained from structural MRI scans (obtained at least 6 months poststroke, and within 2 days of behavioural assessment); after spatial normalization, the lesions were parcellated into a disjoint set of brain areas. The proportion of damage to the brain areas was used to classify patients’ aphasia type. To create this parcellation, we relied on five brain atlases; our classifier (support vector machine) could differentiate between different kinds of aphasia using any of the five parcellations. In our sample, the best classification accuracy was obtained when using a novel parcellation that combined two previously published brain atlases, with the first atlas providing the segmentation of grey matter, and the second atlas used to segment the white matter. For each aphasia type, we computed the relative importance of different brain areas for distinguishing it from other aphasia types; our findings were consistent with previously published reports of lesion locations implicated in different types of aphasia. Overall, our results revealed that automated multivariate classification could distinguish between aphasia types based on damage to atlas-defined brain areas. PMID:26465238

Predicting aphasia type from brain damage measured with structural MRI.

PubMed

Yourganov, Grigori; Smith, Kimberly G; Fridriksson, Julius; Rorden, Chris

2015-12-01

Chronic aphasia is a common consequence of a left-hemisphere stroke. Since the early insights by Broca and Wernicke, studying the relationship between the loci of cortical damage and patterns of language impairment has been one of the concerns of aphasiology. We utilized multivariate classification in a cross-validation framework to predict the type of chronic aphasia from the spatial pattern of brain damage. Our sample consisted of 98 patients with five types of aphasia (Broca's, Wernicke's, global, conduction, and anomic), classified based on scores on the Western Aphasia Battery (WAB). Binary lesion maps were obtained from structural MRI scans (obtained at least 6 months poststroke, and within 2 days of behavioural assessment); after spatial normalization, the lesions were parcellated into a disjoint set of brain areas. The proportion of damage to the brain areas was used to classify patients' aphasia type. To create this parcellation, we relied on five brain atlases; our classifier (support vector machine - SVM) could differentiate between different kinds of aphasia using any of the five parcellations. In our sample, the best classification accuracy was obtained when using a novel parcellation that combined two previously published brain atlases, with the first atlas providing the segmentation of grey matter, and the second atlas used to segment the white matter. For each aphasia type, we computed the relative importance of different brain areas for distinguishing it from other aphasia types; our findings were consistent with previously published reports of lesion locations implicated in different types of aphasia. Overall, our results revealed that automated multivariate classification could distinguish between aphasia types based on damage to atlas-defined brain areas. Copyright © 2015 Elsevier Ltd. All rights reserved.

Far-field phase contrast from orbiting objects: Characterizing progenitors of binary mergers

NASA Astrophysics Data System (ADS)

Matthias, P.; Hofmann, R.

2018-05-01

We propose an idea to determine the size of a binary, composed of two compact stars or black holes, its diffractive power, the distance between components, and the distance to an observer, in exploiting the emergence of intensity contrast by free-space propagation when the phase of coherent light from a very distant background source is affected by diffraction. We assume that this effect can be characterized by the projected real part of an effective refractive index n . Here we model the according two-dimensional exit phase-map by a superposition of two Gaussians. In the extreme far field, phase information is captured by scaling functions which are analyzed here. Both spatial and temporal scanning of the intensity contrast are discussed. While the former mode can be used, e.g., to determine the distance to the observer, the latter allows, e.g., one to measure the overall diffractive power of the binary in terms of the particular dependence of a scaling curve on the projected spatial separation between the binary's components. Both modes of observation may be of relevance in monitoring the progenitor dynamics of binary collapse using radio telescopes.

Accelerated damage visualization using binary search with fixed pitch-catch distance laser ultrasonic scanning

NASA Astrophysics Data System (ADS)

Park, Byeongjin; Sohn, Hoon

2017-07-01

Laser ultrasonic scanning, especially full-field wave propagation imaging, is attractive for damage visualization thanks to its noncontact nature, sensitivity to local damage, and high spatial resolution. However, its practicality is limited because scanning at a high spatial resolution demands a prohibitively long scanning time. Inspired by binary search, an accelerated damage visualization technique is developed to visualize damage with a reduced scanning time. The pitch-catch distance between the excitation point and the sensing point is also fixed during scanning to maintain a high signal-to-noise ratio (SNR) of measured ultrasonic responses. The approximate damage boundary is identified by examining the interactions between ultrasonic waves and damage observed at the scanning points that are sparsely selected by a binary search algorithm. Here, a time-domain laser ultrasonic response is transformed into a spatial ultrasonic domain response using a basis pursuit approach so that the interactions between ultrasonic waves and damage, such as reflections and transmissions, can be better identified in the spatial ultrasonic domain. Then, the area inside the identified damage boundary is visualized as damage. The performance of the proposed damage visualization technique is validated excusing a numerical simulation performed on an aluminum plate with a notch and experiments performed on an aluminum plate with a crack and a wind turbine blade with delamination. The proposed damage visualization technique accelerates the damage visualization process in three aspects: (1) the number of measurements that is necessary for damage visualization is dramatically reduced by a binary search algorithm; (2) the number of averaging that is necessary to achieve a high SNR is reduced by maintaining the wave propagation distance short; and (3) with the proposed technique, the same damage can be identified with a lower spatial resolution than the spatial resolution required by full-field wave propagation imaging.

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

USGS Publications Warehouse

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

2013-01-01

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

WIYN OPEN CLUSTER STUDY. XXXVI. SPECTROSCOPIC BINARY ORBITS IN NGC 188

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

Geller, Aaron M.; Mathieu, Robert D.; Harris, Hugh C.

2009-04-15

We present 98 spectroscopic binary orbits resulting from our ongoing radial velocity survey of the old (7 Gyr) open cluster NGC 188. All but 13 are high-probability cluster members based on both radial velocity and proper motion membership analyses. Fifteen of these member binaries are double lined. Our stellar sample spans a magnitude range of 10.8 {<=}V{<=} 16.5 (1.14-0.92 M {sub sun}) and extends spatially to 17 pc ({approx}13 core radii). All of our binary orbits have periods ranging from a few days to on the order of 10{sup 3} days, and thus are hard binaries that dynamically power themore » cluster. For each binary, we present the orbital solutions and place constraints on the component masses. Additionally, we discuss a few binaries of note from our sample, identifying a likely blue straggler-blue straggler binary system (7782), a double-lined binary with a secondary star which is underluminous for its mass (5080), two potential eclipsing binaries (4705 and 5762), and two binaries which are likely members of a quadruple system (5015a and 5015b)« less

Mapping spatial patterns with morphological image processing

Treesearch

Peter Vogt; Kurt H. Riitters; Christine Estreguil; Jacek Kozak; Timothy G. Wade; James D. Wickham

2006-01-01

We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the...

VizieR Online Data Catalog: Binary systems among nearby dwarfs searching (Khovritchev+, 2018)

NASA Astrophysics Data System (ADS)

Khovritchev, M. Yu.; Apetyan, A. A.; Roshchina, E. A.; Izmailov, I. S.; Bikulova, D. A.; Ershova, A. P.; Balyaev, I. A.; Kulikova, A. M.; Petjur, V. V.; Shumilov, A. A.; Oskina, K. I.; Maksimova, L. A.

2018-03-01

All results are collected in three tables: saturn1m-bc.dat, saturn1m-sdss-bc.dat and sdss-bc.dat. They have the same byte-by-byte description. The tables contain the estimates of spatial parameters of binaries (rho and d_m), relative ellipticity and asymmetry index. In addition, the positions, proper motions, photometric magnitudes, parallaxes and metallicities are presented. All stars listed in these tables are binary candidates. (3 data files).

Active Travel Behavior in a Border Region of Texas and New Mexico: Motivators, Deterrents, and Characteristics.

PubMed

Sener, Ipek N; Lee, Richard J

2017-08-01

Active travel has been linked with improved transportation and health outcomes, such as reduced traffic congestion and air pollution, improved mobility, accessibility, and equity, and increased physical and mental health. The purpose of this study was to better understand active travel characteristics, motivators, and deterrents in the El Paso, TX, region. A multimodal transportation survey brought together elements of transportation and health, with a focus on attitudinal characteristics. The analysis consisted of an initial descriptive analysis, spatial analysis, and multivariate binary and ordered-response models of walking and bicycling behavior. The motivators and deterrents of active travel differed for walkers, bicyclists, and noncyclists interested in bicycling. The link between active travel and life satisfaction was moderated by age, with a negative association for older travelers. This effect was stronger for bicycling than it was for walking. Based on the findings, several interventions to encourage walking and bicycling were suggested. These included infrastructure and built environment enhancements, workplace programs, and interventions targeting specific subpopulations.

Estimation of Subpixel Snow-Covered Area by Nonparametric Regression Splines

NASA Astrophysics Data System (ADS)

Kuter, S.; Akyürek, Z.; Weber, G.-W.

2016-10-01

Measurement of the areal extent of snow cover with high accuracy plays an important role in hydrological and climate modeling. Remotely-sensed data acquired by earth-observing satellites offer great advantages for timely monitoring of snow cover. However, the main obstacle is the tradeoff between temporal and spatial resolution of satellite imageries. Soft or subpixel classification of low or moderate resolution satellite images is a preferred technique to overcome this problem. The most frequently employed snow cover fraction methods applied on Moderate Resolution Imaging Spectroradiometer (MODIS) data have evolved from spectral unmixing and empirical Normalized Difference Snow Index (NDSI) methods to latest machine learning-based artificial neural networks (ANNs). This study demonstrates the implementation of subpixel snow-covered area estimation based on the state-of-the-art nonparametric spline regression method, namely, Multivariate Adaptive Regression Splines (MARS). MARS models were trained by using MODIS top of atmospheric reflectance values of bands 1-7 as predictor variables. Reference percentage snow cover maps were generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also employed to estimate the percentage snow-covered area on the same data set. The results indicated that the developed MARS model performed better than th

Resolving the Massive Binary Wind Interaction Of Eta Carinae with HST/STIS

NASA Technical Reports Server (NTRS)

Gull, Theodore; Nielsen, K.; Corcoran, M.; Hillier, J.; Madura, T.; Hamaguchi, K.; Kober, G.; Owocki, S.; Russell, C.; Okazaki, A.;

A comparison of data-driven groundwater vulnerability assessment methods

USGS Publications Warehouse

Sorichetta, Alessandro; Ballabio, Cristiano; Masetti, Marco; Robinson, Gilpin R.; Sterlacchini, Simone

2013-01-01

Increasing availability of geo-environmental data has promoted the use of statistical methods to assess groundwater vulnerability. Nitrate is a widespread anthropogenic contaminant in groundwater and its occurrence can be used to identify aquifer settings vulnerable to contamination. In this study, multivariate Weights of Evidence (WofE) and Logistic Regression (LR) methods, where the response variable is binary, were used to evaluate the role and importance of a number of explanatory variables associated with nitrate sources and occurrence in groundwater in the Milan District (central part of the Po Plain, Italy). The results of these models have been used to map the spatial variation of groundwater vulnerability to nitrate in the region, and we compare the similarities and differences of their spatial patterns and associated explanatory variables. We modify the standard WofE method used in previous groundwater vulnerability studies to a form analogous to that used in LR; this provides a framework to compare the results of both models and reduces the effect of sampling bias on the results of the standard WofE model. In addition, a nonlinear Generalized Additive Model has been used to extend the LR analysis. Both approaches improved discrimination of the standard WofE and LR models, as measured by the c-statistic. Groundwater vulnerability probability outputs, based on rank-order classification of the respective model results, were similar in spatial patterns and identified similar strong explanatory variables associated with nitrate source (population density as a proxy for sewage systems and septic sources) and nitrate occurrence (groundwater depth).

A density cusp of quiescent X-ray binaries in the central parsec of the Galaxy

NASA Astrophysics Data System (ADS)

Hailey, Charles J.; Mori, Kaya; Bauer, Franz E.; Berkowitz, Michael E.; Hong, Jaesub; Hord, Benjamin J.

2018-04-01

The existence of a ‘density cusp’—a localized increase in number—of stellar-mass black holes near a supermassive black hole is a fundamental prediction of galactic stellar dynamics. The best place to detect such a cusp is in the Galactic Centre, where the nearest supermassive black hole, Sagittarius A*, resides. As many as 20,000 black holes are predicted to settle into the central parsec of the Galaxy as a result of dynamical friction; however, so far no density cusp of black holes has been detected. Low-mass X-ray binary systems that contain a stellar-mass black hole are natural tracers of isolated black holes. Here we report observations of a dozen quiescent X-ray binaries in a density cusp within one parsec of Sagittarius A*. The lower-energy emission spectra that we observed in these binaries is distinct from the higher-energy spectra associated with the population of accreting white dwarfs that dominates the central eight parsecs of the Galaxy. The properties of these X-ray binaries, in particular their spatial distribution and luminosity function, suggest the existence of hundreds of binary systems in the central parsec of the Galaxy and many more isolated black holes. We cannot rule out a contribution to the observed emission from a population (of up to about one-half the number of X-ray binaries) of rotationally powered, millisecond pulsars. The spatial distribution of the binary systems is a relic of their formation history, either in the stellar disk around Sagittarius A* (ref. 7) or through in-fall from globular clusters, and constrains the number density of sources in the modelling of gravitational waves from massive stellar remnants, such as neutron stars and black holes.

A density cusp of quiescent X-ray binaries in the central parsec of the Galaxy.

PubMed

Hailey, Charles J; Mori, Kaya; Bauer, Franz E; Berkowitz, Michael E; Hong, Jaesub; Hord, Benjamin J

2018-04-04

The existence of a 'density cusp'-a localized increase in number-of stellar-mass black holes near a supermassive black hole is a fundamental prediction of galactic stellar dynamics. The best place to detect such a cusp is in the Galactic Centre, where the nearest supermassive black hole, Sagittarius A*, resides. As many as 20,000 black holes are predicted to settle into the central parsec of the Galaxy as a result of dynamical friction; however, so far no density cusp of black holes has been detected. Low-mass X-ray binary systems that contain a stellar-mass black hole are natural tracers of isolated black holes. Here we report observations of a dozen quiescent X-ray binaries in a density cusp within one parsec of Sagittarius A*. The lower-energy emission spectra that we observed in these binaries is distinct from the higher-energy spectra associated with the population of accreting white dwarfs that dominates the central eight parsecs of the Galaxy. The properties of these X-ray binaries, in particular their spatial distribution and luminosity function, suggest the existence of hundreds of binary systems in the central parsec of the Galaxy and many more isolated black holes. We cannot rule out a contribution to the observed emission from a population (of up to about one-half the number of X-ray binaries) of rotationally powered, millisecond pulsars. The spatial distribution of the binary systems is a relic of their formation history, either in the stellar disk around Sagittarius A* (ref. 7) or through in-fall from globular clusters, and constrains the number density of sources in the modelling of gravitational waves from massive stellar remnants, such as neutron stars and black holes.

Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed

USGS Publications Warehouse

Balk, Benjamin; Elder, Kelly

2000-01-01

We model the spatial distribution of snow across a mountain basin using an approach that combines binary decision tree and geostatistical techniques. In April 1997 and 1998, intensive snow surveys were conducted in the 6.9‐km2 Loch Vale watershed (LVWS), Rocky Mountain National Park, Colorado. Binary decision trees were used to model the large‐scale variations in snow depth, while the small‐scale variations were modeled through kriging interpolation methods. Binary decision trees related depth to the physically based independent variables of net solar radiation, elevation, slope, and vegetation cover type. These decision tree models explained 54–65% of the observed variance in the depth measurements. The tree‐based modeled depths were then subtracted from the measured depths, and the resulting residuals were spatially distributed across LVWS through kriging techniques. The kriged estimates of the residuals were added to the tree‐based modeled depths to produce a combined depth model. The combined depth estimates explained 60–85% of the variance in the measured depths. Snow densities were mapped across LVWS using regression analysis. Snow‐covered area was determined from high‐resolution aerial photographs. Combining the modeled depths and densities with a snow cover map produced estimates of the spatial distribution of snow water equivalence (SWE). This modeling approach offers improvement over previous methods of estimating SWE distribution in mountain basins.

Solidification of a binary mixture

NASA Technical Reports Server (NTRS)

Antar, B. N.

1982-01-01

The time dependent concentration and temperature profiles of a finite layer of a binary mixture are investigated during solidification. The coupled time dependent Stefan problem is solved numerically using an implicit finite differencing algorithm with the method of lines. Specifically, the temporal operator is approximated via an implicit finite difference operator resulting in a coupled set of ordinary differential equations for the spatial distribution of the temperature and concentration for each time. Since the resulting differential equations set form a boundary value problem with matching conditions at an unknown spatial point, the method of invariant imbedding is used for its solution.

Investigación observacional sobre el papel de las estrellas binarias en la ecología de cúmulos estelares

NASA Astrophysics Data System (ADS)

González, J. F.; Levato, H.; Grosso, M.

We present preliminary results of a long-term project devoted to the observational study of the binary star population in open clusters and its connection with the dynamical and evolutionary properties of the clusters. We report the discovery of 17 double-lined spectroscopic binaries, 30 radial velocity variables and about 30 suspected variables. In the 17 clusters of our sample the binary frequency ranges between 20 and 40 %, and reaches typically 60 % if all suspected binaries are included. We study the spatial distribution of the binary stars with respect to the cluster center and we discuss the statistical correlation of the mass-ratio distribution with the cluster age.

OGLE II Eclipsing Binaries In The LMC: Analysis With Class

NASA Astrophysics Data System (ADS)

Devinney, Edward J.; Prsa, A.; Guinan, E. F.; DeGeorge, M.

2011-01-01

The Eclipsing Binaries (EBs) via Artificial Intelligence (EBAI) Project is applying machine learning techniques to elucidate the nature of EBs. Previously, Prsa, et al. applied artificial neural networks (ANNs) trained on physically-realistic Wilson-Devinney models to solve the light curves of the 1882 detached EBs in the LMC discovered by the OGLE II Project (Wyrzykowski, et al.) fully automatically, bypassing the need for manually-derived starting solutions. A curious result is the non-monotonic distribution of the temperature ratio parameter T2/T1, featuring a subsidiary peak noted previously by Mazeh, et al. in an independent analysis using the EBOP EB solution code (Tamuz, et al.). To explore this and to gain a fuller understanding of the multivariate EBAI LMC observational plus solutions data, we have employed automatic clustering and advanced visualization (CAV) techniques. Clustering the OGLE II data aggregates objects that are similar with respect to many parameter dimensions. Measures of similarity for example, could include the multidimensional Euclidean Distance between data objects, although other measures may be appropriate. Applying clustering, we find good evidence that the T2/T1 subsidiary peak is due to evolved binaries, in support of Mazeh et al.'s speculation. Further, clustering suggests that the LMC detached EBs occupying the main sequence region belong to two distinct classes. Also identified as a separate cluster in the multivariate data are stars having a Period-I band relation. Derekas et al. had previously found a Period-K band relation for LMC EBs discovered by the MACHO Project (Alcock, et al.). We suggest such CAV techniques will prove increasingly useful for understanding the large, multivariate datasets increasingly being produced in astronomy. We are grateful for the support of this research from NSF/RUI Grant AST-05-75042 f.

Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets

USGS Publications Warehouse

Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.

2013-01-01

In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.

DEFINITION OF MULTIVARIATE GEOCHEMICAL ASSOCIATIONS WITH POLYMETALLIC MINERAL OCCURRENCES USING A SPATIALLY DEPENDENT CLUSTERING TECHNIQUE AND RASTERIZED STREAM SEDIMENT DATA - AN ALASKAN EXAMPLE.

USGS Publications Warehouse

Jenson, Susan K.; Trautwein, C.M.

1984-01-01

The application of an unsupervised, spatially dependent clustering technique (AMOEBA) to interpolated raster arrays of stream sediment data has been found to provide useful multivariate geochemical associations for modeling regional polymetallic resource potential. The technique is based on three assumptions regarding the compositional and spatial relationships of stream sediment data and their regional significance. These assumptions are: (1) compositionally separable classes exist and can be statistically distinguished; (2) the classification of multivariate data should minimize the pair probability of misclustering to establish useful compositional associations; and (3) a compositionally defined class represented by three or more contiguous cells within an array is a more important descriptor of a terrane than a class represented by spatial outliers.

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spatially filtered to enforce local consensus among neighboring pixels and the spatially filtered image is output.

Kilohertz binary phase modulator for pulsed laser sources using a digital micromirror device.

PubMed

Hoffmann, Maximilian; Papadopoulos, Ioannis N; Judkewitz, Benjamin

2018-01-01

The controlled modulation of an optical wavefront is required for aberration correction, digital phase conjugation, or patterned photostimulation. For most of these applications, it is desirable to control the wavefront modulation at the highest rates possible. The digital micromirror device (DMD) presents a cost-effective solution to achieve high-speed modulation and often exceeds the speed of the more conventional liquid crystal spatial light modulator but is inherently an amplitude modulator. Furthermore, spatial dispersion caused by DMD diffraction complicates its use with pulsed laser sources, such as those used in nonlinear microscopy. Here we introduce a DMD-based optical design that overcomes these limitations and achieves dispersion-free high-speed binary phase modulation. We show that this phase modulation can be used to switch through binary phase patterns at the rate of 20 kHz in two-photon excitation fluorescence applications.

Kilohertz binary phase modulator for pulsed laser sources using a digital micromirror device

NASA Astrophysics Data System (ADS)

Hoffmann, Maximilian; Papadopoulos, Ioannis N.; Judkewitz, Benjamin

2018-01-01

The controlled modulation of an optical wavefront is required for aberration correction, digital phase conjugation or patterned photostimulation. For most of these applications it is desirable to control the wavefront modulation at the highest rates possible. The digital micromirror device (DMD) presents a cost-effective solution to achieve high-speed modulation and often exceeds the speed of the more conventional liquid crystal spatial light modulator, but is inherently an amplitude modulator. Furthermore, spatial dispersion caused by DMD diffraction complicates its use with pulsed laser sources, such as those used in nonlinear microscopy. Here we introduce a DMD-based optical design that overcomes these limitations and achieves dispersion-free high-speed binary phase modulation. We show that this phase modulation can be used to switch through binary phase patterns at the rate of 20 kHz in two-photon excitation fluorescence applications.

High-throughput investigation of single and binary protein adsorption isotherms in anion exchange chromatography employing multivariate analysis.

PubMed

Field, Nicholas; Konstantinidis, Spyridon; Velayudhan, Ajoy

2017-08-11

The combination of multi-well plates and automated liquid handling is well suited to the rapid measurement of the adsorption isotherms of proteins. Here, single and binary adsorption isotherms are reported for BSA, ovalbumin and conalbumin on a strong anion exchanger over a range of pH and salt levels. The impact of the main experimental factors at play on the accuracy and precision of the adsorbed protein concentrations is quantified theoretically and experimentally. In addition to the standard measurement of liquid concentrations before and after adsorption, the amounts eluted from the wells are measured directly. This additional measurement corroborates the calculation based on liquid concentration data, and improves precision especially under conditions of weak or moderate interaction strength. The traditional measurement of multicomponent isotherms is limited by the speed of HPLC analysis; this analytical bottleneck is alleviated by careful multivariate analysis of UV spectra. Copyright © 2017. Published by Elsevier B.V.

The Nature of Double-peaked [O III] Active Galactic Nuclei

NASA Astrophysics Data System (ADS)

Fu, Hai; Yan, Lin; Myers, Adam D.; Stockton, Alan; Djorgovski, S. G.; Aldering, G.; Rich, Jeffrey A.

2012-01-01

Active galactic nuclei (AGNs) with double-peaked [O III] lines are suspected to be sub-kpc or kpc-scale binary AGNs. However, pure gas kinematics can produce the same double-peaked line profile in spatially integrated spectra. Here we combine integral-field spectroscopy and high-resolution imaging of 42 double-peaked [O III] AGNs from the Sloan Digital Sky Survey to investigate the constituents of the population. We find two binary AGNs where the line splitting is driven by the orbital motion of the merging nuclei. Such objects account for only ~2% of the double-peaked AGNs. Almost all (~98%) of the double-peaked AGNs were selected because of gas kinematics; and half of those show spatially resolved narrow-line regions that extend 4-20 kpc from the nuclei. Serendipitously, we find two spectrally unresolved binary AGNs where gas kinematics produced the double-peaked [O III] lines. The relatively frequent serendipitous discoveries indicate that only ~1% of binary AGNs would appear double-peaked in Sloan spectra and 2.2+2.5 -0.8% of all Sloan AGNs are binary AGNs. Therefore, the double-peaked sample does not offer much advantage over any other AGN samples in finding binary AGNs. The binary AGN fraction implies an elevated AGN duty cycle (8+8 -3%), suggesting galaxy interactions enhance nuclear accretion. We illustrate that integral-field spectroscopy is crucial for identifying binary AGNs: several objects previously classified as "binary AGNs" with long-slit spectra are most likely single AGNs with extended narrow-line regions (ENLRs). The formation of ENLRs driven by radiation pressure is also discussed. Some of the data presented herein were obtained at the W.M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

Combinatorial techniques to efficiently investigate and optimize organic thin film processing and properties.

PubMed

Wieberger, Florian; Kolb, Tristan; Neuber, Christian; Ober, Christopher K; Schmidt, Hans-Werner

2013-04-08

In this article we present several developed and improved combinatorial techniques to optimize processing conditions and material properties of organic thin films. The combinatorial approach allows investigations of multi-variable dependencies and is the perfect tool to investigate organic thin films regarding their high performance purposes. In this context we develop and establish the reliable preparation of gradients of material composition, temperature, exposure, and immersion time. Furthermore we demonstrate the smart application of combinations of composition and processing gradients to create combinatorial libraries. First a binary combinatorial library is created by applying two gradients perpendicular to each other. A third gradient is carried out in very small areas and arranged matrix-like over the entire binary combinatorial library resulting in a ternary combinatorial library. Ternary combinatorial libraries allow identifying precise trends for the optimization of multi-variable dependent processes which is demonstrated on the lithographic patterning process. Here we verify conclusively the strong interaction and thus the interdependency of variables in the preparation and properties of complex organic thin film systems. The established gradient preparation techniques are not limited to lithographic patterning. It is possible to utilize and transfer the reported combinatorial techniques to other multi-variable dependent processes and to investigate and optimize thin film layers and devices for optical, electro-optical, and electronic applications.

Dual-sensitivity profilometry with defocused projection of binary fringes.

PubMed

Garnica, G; Padilla, M; Servin, M

2017-10-01

A dual-sensitivity profilometry technique based on defocused projection of binary fringes is presented. Here, two sets of fringe patterns with a sinusoidal profile are produced by applying the same analog low-pass filter (projector defocusing) to binary fringes with a high- and low-frequency spatial carrier. The high-frequency fringes have a binary square-wave profile, while the low-frequency binary fringes are produced with error-diffusion dithering. The binary nature of the binary fringes removes the need for calibration of the projector's nonlinear gamma. Working with high-frequency carrier fringes, we obtain a high-quality wrapped phase. On the other hand, working with low-frequency carrier fringes we found a lower-quality, nonwrapped phase map. The nonwrapped estimation is used as stepping stone for dual-sensitivity temporal phase unwrapping, extending the applicability of the technique to discontinuous (piecewise continuous) surfaces. We are proposing a single defocusing level for faster high- and low-frequency fringe data acquisition. The proposed technique is validated with experimental results.

Multiwavelength Study of Powerful New Jet Activity in the Symbiotic Binary System R Aqr

NASA Astrophysics Data System (ADS)

Karovska, Margarita

2016-09-01

We propose to carry out coordinated high-spatial resolution Chandra ACIS-S and HST/WFC3 observations of R Aqr, a very active symbiotic interacting binary system. Our main goal is to study the physical characteristics of multi-scale components of the powerful jet; from near the central binary (within a few AU) to the jet-circumbinary material interaction region (2500 AU) and beyond , and especially of the recently discovered inner jet, to gain insight on early jet formation and propagation, such as jet kinematics and precession.

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy.

PubMed

Dankers, Frank; Wijsman, Robin; Troost, Esther G C; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L

2017-05-07

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy

NASA Astrophysics Data System (ADS)

Dankers, Frank; Wijsman, Robin; Troost, Esther G. C.; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L.

2017-05-01

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Experimental verification of multilevel spatial pattern generation from binary data page with four-step phase pattern (Conference Presentation)

NASA Astrophysics Data System (ADS)

Barada, Daisuke; Yatagai, Toyohiko

2016-09-01

Holographic memory is expected for cold storage because of the features of huge data capacity, high data transfer rate, and long life time. In holographic memory, a signal beam is modulated by a spatial light modulator according to data pages. The recording density is dependent on information amount per pixel in a data page. However, a binary spatial light modulator is used to realize high data transfer rate in general. In our previous study, an optical conversion method from binary data to multilevel data has been proposed. In this paper, the principle of the method is experimentally verified. In the proposed method, a data page consists of symbols with 2x2 pixels and a four-step phase mask is used. Then, the complex amplitudes of four pixels in a symbol become positive real, positive imaginary, negative real, and negative imaginary values, respectively. A square pixel pattern is spread by spatial frequency filtering with a square aperture in a Fourier plane. When the aperture size is too small, the complex amplitude of four pixels in a symbol is superposed and a symbol is regarded as a pixel with a complex number. In this work, a data page pattern with a four-step phase pattern was generated by using a computer-generated circular polarization hologram (CGCPH). The CGCPH was prepared by electron beam lithography. The page data pattern is Fourier transformed by a lens and spatially filtered by a variable rectangular aperture. The complex amplitude of the spatial filtered data page pattern was measured by digital holography and the principle was experimentally verified.

Dynamics of Volunteering in Older Europeans

ERIC Educational Resources Information Center

Hank, Karsten; Erlinghagen, Marcel

2010-01-01

Purpose: To investigate the dynamics of volunteering in the population aged 50 years or older across 11 Continental European countries. Design and Methods: Using longitudinal data from the first 2 waves of the Survey of Health, Ageing and Retirement in Europe, we run multivariate regressions on a set of binary-dependent variables indicating…

Phase Holograms In PMMA

NASA Technical Reports Server (NTRS)

Maker, Paul D.; Muller, Richard E.

1994-01-01

Complex, computer-generated phase holograms written in thin films of poly(methyl methacrylate) (PMMA) by process of electron-beam exposure followed by chemical development. Spatial variations of phase delay in holograms quasi-continuous, as distinquished from stepwise as in binary phase holograms made by integrated-circuit fabrication. Holograms more precise than binary holograms. Greater continuity and precision results in decreased scattering loss and increased imaging efficiency.

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Generation and characterization of a perfect vortex beam with a large topological charge through a digital micromirror device.

PubMed

Chen, Yue; Fang, Zhao-Xiang; Ren, Yu-Xuan; Gong, Lei; Lu, Rong-De

2015-09-20

Optical vortices are associated with a spatial phase singularity. Such a beam with a vortex is valuable in optical microscopy, hyper-entanglement, and optical levitation. In these applications, vortex beams with a perfect circle shape and a large topological charge are highly desirable. But the generation of perfect vortices with high topological charges is challenging. We present a novel method to create perfect vortex beams with large topological charges using a digital micromirror device (DMD) through binary amplitude modulation and a narrow Gaussian approximation. The DMD with binary holograms encoding both the spatial amplitude and the phase could generate fast switchable, reconfigurable optical vortex beams with significantly high quality and fidelity. With either the binary Lee hologram or the superpixel binary encoding technique, we were able to generate the corresponding hologram with high fidelity and create a perfect vortex with topological charge as large as 90. The physical properties of the perfect vortex beam produced were characterized through measurements of propagation dynamics and the focusing fields. The measurements show good consistency with the theoretical simulation. The perfect vortex beam produced satisfies high-demand utilization in optical manipulation and control, momentum transfer, quantum computing, and biophotonics.

Analysis of Binary Multivariate Longitudinal Data via 2-Dimensional Orbits: An Application to the Agincourt Health and Socio-Demographic Surveillance System in South Africa

PubMed Central

Visaya, Maria Vivien; Sherwell, David; Sartorius, Benn; Cromieres, Fabien

2015-01-01

We analyse demographic longitudinal survey data of South African (SA) and Mozambican (MOZ) rural households from the Agincourt Health and Socio-Demographic Surveillance System in South Africa. In particular, we determine whether absolute poverty status (APS) is associated with selected household variables pertaining to socio-economic determination, namely household head age, household size, cumulative death, adults to minor ratio, and influx. For comparative purposes, households are classified according to household head nationality (SA or MOZ) and APS (rich or poor). The longitudinal data of each of the four subpopulations (SA rich, SA poor, MOZ rich, and MOZ poor) is a five-dimensional space defined by binary variables (questions), subjects, and time. We use the orbit method to represent binary multivariate longitudinal data (BMLD) of each household as a two-dimensional orbit and to visualise dynamics and behaviour of the population. At each time step, a point (x, y) from the orbit of a household corresponds to the observation of the household, where x is a binary sequence of responses and y is an ordering of variables. The ordering of variables is dynamically rearranged such that clusters and holes associated to least and frequently changing variables in the state space respectively, are exposed. Analysis of orbits reveals information of change at both individual- and population-level, change patterns in the data, capacity of states in the state space, and density of state transitions in the orbits. Analysis of household orbits of the four subpopulations show association between (i) households headed by older adults and rich households, (ii) large household size and poor households, and (iii) households with more minors than adults and poor households. Our results are compared to other methods of BMLD analysis. PMID:25919116

A joint modeling and estimation method for multivariate longitudinal data with mixed types of responses to analyze physical activity data generated by accelerometers.

PubMed

Li, Haocheng; Zhang, Yukun; Carroll, Raymond J; Keadle, Sarah Kozey; Sampson, Joshua N; Matthews, Charles E

2017-11-10

A mixed effect model is proposed to jointly analyze multivariate longitudinal data with continuous, proportion, count, and binary responses. The association of the variables is modeled through the correlation of random effects. We use a quasi-likelihood type approximation for nonlinear variables and transform the proposed model into a multivariate linear mixed model framework for estimation and inference. Via an extension to the EM approach, an efficient algorithm is developed to fit the model. The method is applied to physical activity data, which uses a wearable accelerometer device to measure daily movement and energy expenditure information. Our approach is also evaluated by a simulation study. Copyright © 2017 John Wiley & Sons, Ltd.

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

PubMed Central

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

2013-01-01

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

Spatial compression algorithm for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R [Albuquerque, NM

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.

Theoretical Models of Protostellar Binary and Multiple Systems with AMR Simulations

NASA Astrophysics Data System (ADS)

Matsumoto, Tomoaki; Tokuda, Kazuki; Onishi, Toshikazu; Inutsuka, Shu-ichiro; Saigo, Kazuya; Takakuwa, Shigehisa

2017-05-01

We present theoretical models for protostellar binary and multiple systems based on the high-resolution numerical simulation with an adaptive mesh refinement (AMR) code, SFUMATO. The recent ALMA observations have revealed early phases of the binary and multiple star formation with high spatial resolutions. These observations should be compared with theoretical models with high spatial resolutions. We present two theoretical models for (1) a high density molecular cloud core, MC27/L1521F, and (2) a protobinary system, L1551 NE. For the model for MC27, we performed numerical simulations for gravitational collapse of a turbulent cloud core. The cloud core exhibits fragmentation during the collapse, and dynamical interaction between the fragments produces an arc-like structure, which is one of the prominent structures observed by ALMA. For the model for L1551 NE, we performed numerical simulations of gas accretion onto protobinary. The simulations exhibit asymmetry of a circumbinary disk. Such asymmetry has been also observed by ALMA in the circumbinary disk of L1551 NE.

Spatially variant morphological restoration and skeleton representation.

PubMed

Bouaynaya, Nidhal; Charif-Chefchaouni, Mohammed; Schonfeld, Dan

2006-11-01

The theory of spatially variant (SV) mathematical morphology is used to extend and analyze two important image processing applications: morphological image restoration and skeleton representation of binary images. For morphological image restoration, we propose the SV alternating sequential filters and SV median filters. We establish the relation of SV median filters to the basic SV morphological operators (i.e., SV erosions and SV dilations). For skeleton representation, we present a general framework for the SV morphological skeleton representation of binary images. We study the properties of the SV morphological skeleton representation and derive conditions for its invertibility. We also develop an algorithm for the implementation of the SV morphological skeleton representation of binary images. The latter algorithm is based on the optimal construction of the SV structuring element mapping designed to minimize the cardinality of the SV morphological skeleton representation. Experimental results show the dramatic improvement in the performance of the SV morphological restoration and SV morphological skeleton representation algorithms in comparison to their translation-invariant counterparts.

Towards constructing multi-bit binary adder based on Belousov-Zhabotinsky reaction

NASA Astrophysics Data System (ADS)

Zhang, Guo-Mao; Wong, Ieong; Chou, Meng-Ta; Zhao, Xin

2012-04-01

It has been proposed that the spatial excitable media can perform a wide range of computational operations, from image processing, to path planning, to logical and arithmetic computations. The realizations in the field of chemical logical and arithmetic computations are mainly concerned with single simple logical functions in experiments. In this study, based on Belousov-Zhabotinsky reaction, we performed simulations toward the realization of a more complex operation, the binary adder. Combining with some of the existing functional structures that have been verified experimentally, we designed a planar geometrical binary adder chemical device. Through numerical simulations, we first demonstrated that the device can implement the function of a single-bit full binary adder. Then we show that the binary adder units can be further extended in plane, and coupled together to realize a two-bit, or even multi-bit binary adder. The realization of chemical adders can guide the constructions of other sophisticated arithmetic functions, ultimately leading to the implementation of chemical computer and other intelligent systems.

Clustering of Multivariate Geostatistical Data

NASA Astrophysics Data System (ADS)

Fouedjio, Francky

2017-04-01

Multivariate data indexed by geographical coordinates have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations belonging to the same cluster have a certain degree of homogeneity while data locations in the different clusters have to be as different as possible. However, groups of data locations created through classical clustering techniques turn out to show poor spatial contiguity, a feature obviously inconvenient for many geoscience applications. In this work, we develop a clustering method that overcomes this problem by accounting the spatial dependence structure of data; thus reinforcing the spatial contiguity of resulting cluster. The capability of the proposed clustering method to provide spatially contiguous and meaningful clusters of data locations is assessed using both synthetic and real datasets. Keywords: clustering, geostatistics, spatial contiguity, spatial dependence.

Multi-epoch observations with high spatial resolution of multiple T Tauri systems

NASA Astrophysics Data System (ADS)

Csépány, Gergely; van den Ancker, Mario; Ábrahám, Péter; Köhler, Rainer; Brandner, Wolfgang; Hormuth, Felix; Hiss, Hector

2017-07-01

Context. In multiple pre-main-sequence systems the lifetime of circumstellar discs appears to be shorter than around single stars, and the actual dissipation process may depend on the binary parameters of the systems. Aims: We report high spatial resolution observations of multiple T Tauri systems at optical and infrared wavelengths. We determine whether the components are gravitationally bound and orbital motion is visible, derive orbital parameters, and investigate possible correlations between the binary parameters and disc states. Methods: We selected 18 T Tau multiple systems (16 binary and two triple systems, yielding 16 + 2 × 2 = 20 binary pairs) in the Taurus-Auriga star-forming region from a previous survey, with spectral types from K1 to M5 and separations from 0.22″ (31 AU) to 5.8″ (814 AU). We analysed data acquired in 2006-07 at Calar Alto using the AstraLux lucky imaging system, along with data from SPHERE and NACO at the VLT, and from the literature. Results: We found ten pairs to orbit each other, five pairs that may show orbital motion, and five likely common proper motion pairs. We found no obvious correlation between the stellar parameters and binary configuration. The 10 μm infra-red excess varies between 0.1 and 7.2 mag (similar to the distribution in single stars, where it is between 1.7 and 9.1), implying that the presence of the binary star does not greatly influence the emission from the inner disc. Conclusions: We have detected orbital motion in young T Tauri systems over a timescale of ≈ 20 yr. Further observations with even longer temporal baseline will provide crucial information on the dynamics of these young stellar systems.

Gravitational Wave Detection of Compact Binaries Through Multivariate Analysis

NASA Astrophysics Data System (ADS)

Atallah, Dany Victor; Dorrington, Iain; Sutton, Patrick

2017-01-01

The first detection of gravitational waves (GW), GW150914, as produced by a binary black hole merger, has ushered in the era of GW astronomy. The detection technique used to find GW150914 considered only a fraction of the information available describing the candidate event: mainly the detector signal to noise ratios and chi-squared values. In hopes of greatly increasing detection rates, we want to take advantage of all the information available about candidate events. We employ a technique called Multivariate Analysis (MVA) to improve LIGO sensitivity to GW signals. MVA techniques are efficient ways to scan high dimensional data spaces for signal/noise classification. Our goal is to use MVA to classify compact-object binary coalescence (CBC) events composed of any combination of black holes and neutron stars. CBC waveforms are modeled through numerical relativity. Templates of the modeled waveforms are used to search for CBCs and quantify candidate events. Different MVA pipelines are under investigation to look for CBC signals and un-modelled signals, with promising results. One such MVA pipeline used for the un-modelled search can theoretically analyze far more data than the MVA pipelines currently explored for CBCs, potentially making a more powerful classifier. In principle, this extra information could improve the sensitivity to GW signals. We will present the results from our efforts to adapt an MVA pipeline used in the un-modelled search to classify candidate events from the CBC search.

Arithmetic operations in optical computations using a modified trinary number system.

PubMed

Datta, A K; Basuray, A; Mukhopadhyay, S

1989-05-01

A modified trinary number (MTN) system is proposed in which any binary number can be expressed with the help of trinary digits (1, 0, 1 ). Arithmetic operations can be performed in parallel without the need for carry and borrow steps when binary digits are converted to the MTN system. An optical implementation of the proposed scheme that uses spatial light modulators and color-coded light signals is described.

Finding an appropriate equation to measure similarity between binary vectors: case studies on Indonesian and Japanese herbal medicines.

PubMed

Wijaya, Sony Hartono; Afendi, Farit Mochamad; Batubara, Irmanida; Darusman, Latifah K; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2016-12-07

The binary similarity and dissimilarity measures have critical roles in the processing of data consisting of binary vectors in various fields including bioinformatics and chemometrics. These metrics express the similarity and dissimilarity values between two binary vectors in terms of the positive matches, absence mismatches or negative matches. To our knowledge, there is no published work presenting a systematic way of finding an appropriate equation to measure binary similarity that performs well for certain data type or application. A proper method to select a suitable binary similarity or dissimilarity measure is needed to obtain better classification results. In this study, we proposed a novel approach to select binary similarity and dissimilarity measures. We collected 79 binary similarity and dissimilarity equations by extensive literature search and implemented those equations as an R package called bmeasures. We applied these metrics to quantify the similarity and dissimilarity between herbal medicine formulas belonging to the Indonesian Jamu and Japanese Kampo separately. We assessed the capability of binary equations to classify herbal medicine pairs into match and mismatch efficacies based on their similarity or dissimilarity coefficients using the Receiver Operating Characteristic (ROC) curve analysis. According to the area under the ROC curve results, we found Indonesian Jamu and Japanese Kampo datasets obtained different ranking of binary similarity and dissimilarity measures. Out of all the equations, the Forbes-2 similarity and the Variant of Correlation similarity measures are recommended for studying the relationship between Jamu formulas and Kampo formulas, respectively. The selection of binary similarity and dissimilarity measures for multivariate analysis is data dependent. The proposed method can be used to find the most suitable binary similarity and dissimilarity equation wisely for a particular data. Our finding suggests that all four types of matching quantities in the Operational Taxonomic Unit (OTU) table are important to calculate the similarity and dissimilarity coefficients between herbal medicine formulas. Also, the binary similarity and dissimilarity measures that include the negative match quantity d achieve better capability to separate herbal medicine pairs compared to equations that exclude d.

Shaping complex microwave fields in reverberating media with binary tunable metasurfaces

PubMed Central

Kaina, Nadège; Dupré, Matthieu; Lerosey, Geoffroy; Fink, Mathias

2014-01-01

In this article we propose to use electronically tunable metasurfaces as spatial microwave modulators. We demonstrate that like spatial light modulators, which have been recently proved to be ideal tools for controlling light propagation through multiple scattering media, spatial microwave modulators can efficiently shape in a passive way complex existing microwave fields in reverberating environments with a non-coherent energy feedback. Unlike in free space, we establish that a binary-only phase state tunable metasurface allows a very good control over the waves, owing to the random nature of the electromagnetic fields in these complex media. We prove in an everyday reverberating medium, that is, a typical office room, that a small spatial microwave modulator placed on the walls can passively increase the wireless transmission between two antennas by an order of magnitude, or on the contrary completely cancel it. Interestingly and contrary to free space, we show that this results in an isotropic shaped microwave field around the receiving antenna, which we attribute again to the reverberant nature of the propagation medium. We expect that spatial microwave modulators will be interesting tools for fundamental physics and will have applications in the field of wireless communications. PMID:25331498

Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models

NASA Astrophysics Data System (ADS)

Haslauer, C. P.; Bárdossy, A.

2017-12-01

A copula based multivariate framework allows more flexibility to describe different kind of dependences than what is possible using models relying on the confining assumption of symmetric Gaussian models: different quantiles can be modelled with a different degree of dependence; it will be demonstrated how this can be expected given process understanding. maximum likelihood based multivariate quantitative parameter estimation yields stable and reliable results; not only improved results in cross-validation based measures of uncertainty are obtained but also a more realistic spatial structure of uncertainty compared to second order models of dependence; as much information as is available is included in the parameter estimation: incorporation of censored measurements (e.g., below detection limit, or ones that are above the sensitive range of the measurement device) yield to more realistic spatial models; the proportion of true zeros can be jointly estimated with and distinguished from censored measurements which allow estimates about the age of a contaminant in the system; secondary information (categorical and on the rational scale) has been used to improve the estimation of the primary variable; These copula based multivariate statistical techniques are demonstrated based on hydraulic conductivity observations at the Borden (Canada) site, the MADE site (USA), and a large regional groundwater quality data-set in south-west Germany. Fields of spatially distributed K were simulated with identical marginal simulation, identical second order spatial moments, yet substantially differing solute transport characteristics when numerical tracer tests were performed. A statistical methodology is shown that allows the delineation of a boundary layer separating homogenous parts of a spatial data-set. The effects of this boundary layer (macro structure) and the spatial dependence of K (micro structure) on solute transport behaviour is shown.

Univariate and multivariate spatial models of health facility utilisation for childhood fevers in an area on the coast of Kenya.

PubMed

Ouma, Paul O; Agutu, Nathan O; Snow, Robert W; Noor, Abdisalan M

2017-09-18

Precise quantification of health service utilisation is important for the estimation of disease burden and allocation of health resources. Current approaches to mapping health facility utilisation rely on spatial accessibility alone as the predictor. However, other spatially varying social, demographic and economic factors may affect the use of health services. The exclusion of these factors can lead to the inaccurate estimation of health facility utilisation. Here, we compare the accuracy of a univariate spatial model, developed only from estimated travel time, to a multivariate model that also includes relevant social, demographic and economic factors. A theoretical surface of travel time to the nearest public health facility was developed. These were assigned to each child reported to have had fever in the Kenya demographic and health survey of 2014 (KDHS 2014). The relationship of child treatment seeking for fever with travel time, household and individual factors from the KDHS2014 were determined using multilevel mixed modelling. Bayesian information criterion (BIC) and likelihood ratio test (LRT) tests were carried out to measure how selected factors improve parsimony and goodness of fit of the time model. Using the mixed model, a univariate spatial model of health facility utilisation was fitted using travel time as the predictor. The mixed model was also used to compute a multivariate spatial model of utilisation, using travel time and modelled surfaces of selected household and individual factors as predictors. The univariate and multivariate spatial models were then compared using the receiver operating area under the curve (AUC) and a percent correct prediction (PCP) test. The best fitting multivariate model had travel time, household wealth index and number of children in household as the predictors. These factors reduced BIC of the time model from 4008 to 2959, a change which was confirmed by the LRT test. Although there was a high correlation of the two modelled probability surfaces (Adj R 2  = 88%), the multivariate model had better AUC compared to the univariate model; 0.83 versus 0.73 and PCP 0.61 versus 0.45 values. Our study shows that a model that uses travel time, as well as household and individual-level socio-demographic factors, results in a more accurate estimation of use of health facilities for the treatment of childhood fever, compared to one that relies on only travel time.

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

PubMed

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

2013-01-01

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

Self-assembly of Nano-rods in Photosensitive Phase Separation

NASA Astrophysics Data System (ADS)

Liu, Ya; Kuksenok, Olga; Maresov, Egor; Balazs, Anna

2012-02-01

Computer simulations reveal how photo-induced chemical reactions in polymeric mixtures can be exploited to create long-range order in materials whose features range from the sub-micron to the nanoscale. The process is initiated by shining a spatially uniform light on a photosensitive AB binary blend, which thereby undergoes both a reversible chemical reaction and phase separation. When a well-collimated, higher intensity light is rastered over the sample, the system forms defect-free, spatially periodic structures. We now build on this approach by introducing nanorods that have a preferential affinity for one the phases in a binary mixture. By rastering over the sample with the higher intensity light, we can create ordered arrays of rods within periodically ordered materials in essentially one processing step.

Young Binaries and Early Stellar Evolution

NASA Astrophysics Data System (ADS)

Brandner, Wolfgang

1996-07-01

Most main-sequence stars are members of binary or multiple systems. The same is true for pre-main-sequence (PMS) stars, as recent surveys have shown. Therefore studying star formation means to a large extent studying the formation of binary systems. Similarly, studying early stellar evolution primarily involves PMS binary systems. In this thesis I have studied the binary frequency among ROSAT selected T Tauri stars in the Chamaeleon T association and the Scorpius-Centaurus OB association, and the evolutionary status of Hα-selected PMS binaries in the T associations of Chamaeleon, Lupus, and ρ Ophiuchi. The direct imaging and spectroscopic observations in the optical have been carried out under subarcsec seeing conditions at the ESO New Technology Telescope (NTT) at La Silla. Furthermore, high-spatial resolution images of selected PMS stars in the near infrared were obtained with the ESO adaptive optics system COME-ON+/ADONIS. Among 195 T Tauri stars observed using direct imaging 31 binaries could be identified, 12 of them with subarcsec separation. Based on statistical arguments alone I conclude that almost all of them are indeed physical (i.e. gravitationally bound) binary or multiple systems. Using astrometric measurements of some binaries I showed that the components of these binaries are common proper motion pairs, very likely in a gravitationally bound orbit around each other. The overall binary frequency among T Tauri stars with a range of separations between 120 and 1800 AU is in agreement with the binary frequency observed among main-sequence stars in the solar neighbourhood. However, within individual regions the spatial distribution of binaries is non-uniform. In particular, in Upper Scorpius, weak-line T Tauri stars in the vicinity of early type stars seem to be almost devoid of multiple systems, whereas in another area in Upper Scorpius half of all weak-line T Tauri stars have a companion in a range of separation between 0.''7 and 3.''0. For a sample of 14 spatially resolved PMS binaries (separations 0.''6 to 1.prime'7) located in the above mentioned T associations both photometric and spectroscopic information has been analyzed. All binaries (originally unresolved) were identified as PMS stars based on their strong Hα emission and their association with dark clouds. Using the spectral A index, which measures the strength of the CaH band at 697.5nm relative to the nearby continuum as a luminosity class indicator, I showed that the classical T Tauri stars in the sample tend to be close to luminosity class V. Eight out of the 14 pairs could be placed on an H--R diagram. When comparing with theoretical PMS evolutionary tracks the individual components of all pairs appear to be coeval within the observational errors. This result is similar to Hartigan et al. (1994) who found two thirds of the wider pairs with separations from 400 AU to 6000 AU to be coeval. However, unlike Hartigan et al.'s finding for the wider pairs, I find no non-coeval pairs. One of the presumed binaries in our sample (ESO Hα 281) turned out to be a likely chance projection with the ``primary'' showing neither Hα emission nor Li absorption. Finally, using adaptive optics at the ESO 3.6m telescope, diffraction-limited JHK images of the region around the Herbig AeBe star NX Pup were obtained. The close companion (sep. 0.''128) to NX Pup -- originally discovered by HST -- was clearly resolved and its JHK magnitudes were determined. A third object at a separation of 7.''0 from NX Pup was identified as a classical T Tauri star so that NX Pup may in fact form a hierarchical triple system. I discuss the evolutionary status of these stars and derive estimates for their spectral types, luminosities, masses, and ages. My conclusions are that binarity is established very early in stellar evolution, that the orbital parameters of wide binaries (a >= 120AU) remain virtually unchanged during their PMS evolution, and that the components of the wide binaries were formed at the same time --- perhaps either through collisional fragmentation or fragmentation of rotating filaments. (Copies of the thesis (written in German) and related pre-/reprints are available from the author upon request.)

Spatial Dynamics and Determinants of County-Level Education Expenditure in China

ERIC Educational Resources Information Center

Gu, Jiafeng

2012-01-01

In this paper, a multivariate spatial autoregressive model of local public education expenditure determination with autoregressive disturbance is developed and estimated. The existence of spatial interdependence is tested using Moran's I statistic and Lagrange multiplier test statistics for both the spatial error and spatial lag models. The full…

An unconventional approach to ecosystem unit classification in western North Carolina, USA

Treesearch

W. Henry McNab; Sara A. Browning; Steven A. Simon; Penelope E. Fouts

1999-01-01

The authors used an unconventional combination of data transformation and multivariate analyses to reduce subjectivity in identification of ecosystem units in a mountainous region of western North Carolina, USA. Vegetative cover and environmental variables were measured on 79 stratified, randomly located, 0.1 ha sample plots in a 4000 ha watershed. Binary...

Electronic holography using binary phase modulation

NASA Astrophysics Data System (ADS)

Matoba, Osamu

2014-06-01

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

Binary Programming Models of Spatial Pattern Recognition: Applications in Remote Sensing Image Analysis

DTIC Science & Technology

1991-12-01

9 2.6.1 Multi-Shape Detection. .. .. .. .. .. .. ...... 9 Page 2.6.2 Line Segment Extraction and Re-Combination.. 9 2.6.3 Planimetric Feature... Extraction ............... 10 2.6.4 Line Segment Extraction From Statistical Texture Analysis .............................. 11 2.6.5 Edge Following as Graph...image after image, could benefit clue to the fact that major spatial characteristics of subregions could be extracted , and minor spatial changes could be

An information-based network approach for protein classification

PubMed Central

Wan, Xiaogeng; Zhao, Xin; Yau, Stephen S. T.

2017-01-01

Protein classification is one of the critical problems in bioinformatics. Early studies used geometric distances and polygenetic-tree to classify proteins. These methods use binary trees to present protein classification. In this paper, we propose a new protein classification method, whereby theories of information and networks are used to classify the multivariate relationships of proteins. In this study, protein universe is modeled as an undirected network, where proteins are classified according to their connections. Our method is unsupervised, multivariate, and alignment-free. It can be applied to the classification of both protein sequences and structures. Nine examples are used to demonstrate the efficiency of our new method. PMID:28350835

Predicting crash frequency for multi-vehicle collision types using multivariate Poisson-lognormal spatial model: A comparative analysis.

PubMed

Hosseinpour, Mehdi; Sahebi, Sina; Zamzuri, Zamira Hasanah; Yahaya, Ahmad Shukri; Ismail, Noriszura

2018-06-01

According to crash configuration and pre-crash conditions, traffic crashes are classified into different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear-end, and angle crashes, are more frequent than single-vehicle crashes, and most often result in serious consequences. From a methodological point of view, the majority of prior studies focused on multivehicle collisions have employed univariate count models to estimate crash counts separately by collision type. However, univariate models fail to account for correlations which may exist between different collision types. Among others, multivariate Poisson lognormal (MVPLN) model with spatial correlation is a promising multivariate specification because it not only allows for unobserved heterogeneity (extra-Poisson variation) and dependencies between collision types, but also spatial correlation between adjacent sites. However, the MVPLN spatial model has rarely been applied in previous research for simultaneously modelling crash counts by collision type. Therefore, this study aims at utilizing a MVPLN spatial model to estimate crash counts for four different multi-vehicle collision types, including head-on, rear-end, angle, and sideswipe collisions. To investigate the performance of the MVPLN spatial model, a two-stage model and a univariate Poisson lognormal model (UNPLN) spatial model were also developed in this study. Detailed information on roadway characteristics, traffic volume, and crash history were collected on 407 homogeneous segments from Malaysian federal roads. The results indicate that the MVPLN spatial model outperforms the other comparing models in terms of goodness-of-fit measures. The results also show that the inclusion of spatial heterogeneity in the multivariate model significantly improves the model fit, as indicated by the Deviance Information Criterion (DIC). The correlation between crash types is high and positive, implying that the occurrence of a specific collision type is highly associated with the occurrence of other crash types on the same road segment. These results support the utilization of the MVPLN spatial model when predicting crash counts by collision manner. In terms of contributing factors, the results show that distinct crash types are attributed to different subsets of explanatory variables. Copyright © 2018 Elsevier Ltd. All rights reserved.

Retrieving and Indexing Spatial Data in the Cloud Computing Environment

NASA Astrophysics Data System (ADS)

Wang, Yonggang; Wang, Sheng; Zhou, Daliang

In order to solve the drawbacks of spatial data storage in common Cloud Computing platform, we design and present a framework for retrieving, indexing, accessing and managing spatial data in the Cloud environment. An interoperable spatial data object model is provided based on the Simple Feature Coding Rules from the OGC such as Well Known Binary (WKB) and Well Known Text (WKT). And the classic spatial indexing algorithms like Quad-Tree and R-Tree are re-designed in the Cloud Computing environment. In the last we develop a prototype software based on Google App Engine to implement the proposed model.

Multivariate temporal dictionary learning for EEG.

PubMed

Barthélemy, Q; Gouy-Pailler, C; Isaac, Y; Souloumiac, A; Larue, A; Mars, J I

2013-04-30

This article addresses the issue of representing electroencephalographic (EEG) signals in an efficient way. While classical approaches use a fixed Gabor dictionary to analyze EEG signals, this article proposes a data-driven method to obtain an adapted dictionary. To reach an efficient dictionary learning, appropriate spatial and temporal modeling is required. Inter-channels links are taken into account in the spatial multivariate model, and shift-invariance is used for the temporal model. Multivariate learned kernels are informative (a few atoms code plentiful energy) and interpretable (the atoms can have a physiological meaning). Using real EEG data, the proposed method is shown to outperform the classical multichannel matching pursuit used with a Gabor dictionary, as measured by the representative power of the learned dictionary and its spatial flexibility. Moreover, dictionary learning can capture interpretable patterns: this ability is illustrated on real data, learning a P300 evoked potential. Copyright © 2013 Elsevier B.V. All rights reserved.

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values.

PubMed

Rasouli, Zolaikha; Ghavami, Raouf

2016-08-05

Vanillin (VA), vanillic acid (VAI) and syringaldehyde (SIA) are important food additives as flavor enhancers. The current study for the first time is devote to the application of partial least square (PLS-1), partial robust M-regression (PRM) and feed forward neural networks (FFNNs) as linear and nonlinear chemometric methods for the simultaneous detection of binary and ternary mixtures of VA, VAI and SIA using data extracted directly from UV-spectra with overlapped peaks of individual analytes. Under the optimum experimental conditions, for each compound a linear calibration was obtained in the concentration range of 0.61-20.99 [LOD=0.12], 0.67-23.19 [LOD=0.13] and 0.73-25.12 [LOD=0.15] μgmL(-1) for VA, VAI and SIA, respectively. Four calibration sets of standard samples were designed by combination of a full and fractional factorial designs with the use of the seven and three levels for each factor for binary and ternary mixtures, respectively. The results of this study reveal that both the methods of PLS-1 and PRM are similar in terms of predict ability each binary mixtures. The resolution of ternary mixture has been accomplished by FFNNs. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied for the description of spectra from the acid-base titration systems each individual compound, i.e. the resolution of the complex overlapping spectra as well as to interpret the extracted spectral and concentration profiles of any pure chemical species identified. Evolving factor analysis (EFA) and singular value decomposition (SVD) were used to distinguish the number of chemical species. Subsequently, their corresponding dissociation constants were derived. Finally, FFNNs has been used to detection active compounds in real and spiked water samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values

NASA Astrophysics Data System (ADS)

Rasouli, Zolaikha; Ghavami, Raouf

2016-08-01

Vanillin (VA), vanillic acid (VAI) and syringaldehyde (SIA) are important food additives as flavor enhancers. The current study for the first time is devote to the application of partial least square (PLS-1), partial robust M-regression (PRM) and feed forward neural networks (FFNNs) as linear and nonlinear chemometric methods for the simultaneous detection of binary and ternary mixtures of VA, VAI and SIA using data extracted directly from UV-spectra with overlapped peaks of individual analytes. Under the optimum experimental conditions, for each compound a linear calibration was obtained in the concentration range of 0.61-20.99 [LOD = 0.12], 0.67-23.19 [LOD = 0.13] and 0.73-25.12 [LOD = 0.15] μg mL- 1 for VA, VAI and SIA, respectively. Four calibration sets of standard samples were designed by combination of a full and fractional factorial designs with the use of the seven and three levels for each factor for binary and ternary mixtures, respectively. The results of this study reveal that both the methods of PLS-1 and PRM are similar in terms of predict ability each binary mixtures. The resolution of ternary mixture has been accomplished by FFNNs. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied for the description of spectra from the acid-base titration systems each individual compound, i.e. the resolution of the complex overlapping spectra as well as to interpret the extracted spectral and concentration profiles of any pure chemical species identified. Evolving factor analysis (EFA) and singular value decomposition (SVD) were used to distinguish the number of chemical species. Subsequently, their corresponding dissociation constants were derived. Finally, FFNNs has been used to detection active compounds in real and spiked water samples.

Exploiting Photo-induced Reactions in Polymer Blends to Create Hierarchically Ordered, Defect-free Materials

ScienceCinema

Balazs, Anna [University of Pittsburgh, Pittsburgh, Pennsylvania, United States

2017-12-09

Computer simulations reveal how photo-induced chemical reactions can be exploited to create long-range order in binary and ternary polymeric materials. The process is initiated by shining a spatially uniform light over a photosensitive AB binary blend, which undergoes both a reversible chemical reaction and phase separation. We then introduce a well-collimated, higher-intensity light source. Rastering this secondary light over the sample locally increases the reaction rate and causes formation of defect-free, spatially periodic structures. These binary structures resemble either the lamellar or hexagonal phases of microphase-separated di-block copolymers. We measure the regularity of the ordered structures as a function of the relative reaction rates for different values of the rastering speed and determine the optimal conditions for creating defect-free structures in the binary systems. We then add a non-reactive homo-polymer C, which is immiscible with both A and B. We show that this component migrates to regions that are illuminated by the secondary, higher-intensity light, allowing us to effectively write a pattern of C onto the AB film. Rastering over the ternary blend with this collimated light now leads to hierarchically ordered patterns of A, B, and C. The findings point to a facile, non-intrusive process for manufacturing high-quality polymeric devices in a low-cost, efficient manner.

PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

EPA Science Inventory

The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

HEPDOOP: High-Energy Physics Analysis using Hadoop

NASA Astrophysics Data System (ADS)

Bhimji, W.; Bristow, T.; Washbrook, A.

2014-06-01

We perform a LHC data analysis workflow using tools and data formats that are commonly used in the "Big Data" community outside High Energy Physics (HEP). These include Apache Avro for serialisation to binary files, Pig and Hadoop for mass data processing and Python Scikit-Learn for multi-variate analysis. Comparison is made with the same analysis performed with current HEP tools in ROOT.

Order information in verbal working memory shifts the subjective midpoint in both the line bisection and the landmark tasks.

PubMed

Antoine, Sophie; Ranzini, Mariagrazia; Gebuis, Titia; van Dijck, Jean-Philippe; Gevers, Wim

2017-10-01

A largely substantiated view in the domain of working memory is that the maintenance of serial order is achieved by generating associations of each item with an independent representation of its position, so-called position markers. Recent studies reported that the ordinal position of an item in verbal working memory interacts with spatial processing. This suggests that position markers might be spatial in nature. However, these interactions were so far observed in tasks implying a clear binary categorization of space (i.e., with left and right responses or targets). Such binary categorizations leave room for alternative interpretations, such as congruency between non-spatial categorical codes for ordinal position (e.g., begin and end) and spatial categorical codes for response (e.g., left and right). Here we discard this interpretation by providing evidence that this interaction can also be observed in a task that draws upon a continuous processing of space, the line bisection task. Specifically, bisections are modulated by ordinal position in verbal working memory, with lines bisected more towards the right after retrieving items from the end compared to the beginning of the memorized sequence. This supports the idea that position markers are intrinsically spatial in nature.

Multivariate classification with random forests for gravitational wave searches of black hole binary coalescence

NASA Astrophysics Data System (ADS)

Baker, Paul T.; Caudill, Sarah; Hodge, Kari A.; Talukder, Dipongkar; Capano, Collin; Cornish, Neil J.

2015-03-01

Searches for gravitational waves produced by coalescing black hole binaries with total masses ≳25 M⊙ use matched filtering with templates of short duration. Non-Gaussian noise bursts in gravitational wave detector data can mimic short signals and limit the sensitivity of these searches. Previous searches have relied on empirically designed statistics incorporating signal-to-noise ratio and signal-based vetoes to separate gravitational wave candidates from noise candidates. We report on sensitivity improvements achieved using a multivariate candidate ranking statistic derived from a supervised machine learning algorithm. We apply the random forest of bagged decision trees technique to two separate searches in the high mass (≳25 M⊙ ) parameter space. For a search which is sensitive to gravitational waves from the inspiral, merger, and ringdown of binary black holes with total mass between 25 M⊙ and 100 M⊙ , we find sensitive volume improvements as high as 70±13%-109±11% when compared to the previously used ranking statistic. For a ringdown-only search which is sensitive to gravitational waves from the resultant perturbed intermediate mass black hole with mass roughly between 10 M⊙ and 600 M⊙ , we find sensitive volume improvements as high as 61±4%-241±12% when compared to the previously used ranking statistic. We also report how sensitivity improvements can differ depending on mass regime, mass ratio, and available data quality information. Finally, we describe the techniques used to tune and train the random forest classifier that can be generalized to its use in other searches for gravitational waves.

Multifrequency synthesis and extraction using square wave projection patterns for quantitative tissue imaging.

PubMed

Nadeau, Kyle P; Rice, Tyler B; Durkin, Anthony J; Tromberg, Bruce J

2015-11-01

We present a method for spatial frequency domain data acquisition utilizing a multifrequency synthesis and extraction (MSE) method and binary square wave projection patterns. By illuminating a sample with square wave patterns, multiple spatial frequency components are simultaneously attenuated and can be extracted to determine optical property and depth information. Additionally, binary patterns are projected faster than sinusoids typically used in spatial frequency domain imaging (SFDI), allowing for short (millisecond or less) camera exposure times, and data acquisition speeds an order of magnitude or more greater than conventional SFDI. In cases where sensitivity to superficial layers or scattering is important, the fundamental component from higher frequency square wave patterns can be used. When probing deeper layers, the fundamental and harmonic components from lower frequency square wave patterns can be used. We compared optical property and depth penetration results extracted using square waves to those obtained using sinusoidal patterns on an in vivo human forearm and absorbing tube phantom, respectively. Absorption and reduced scattering coefficient values agree with conventional SFDI to within 1% using both high frequency (fundamental) and low frequency (fundamental and harmonic) spatial frequencies. Depth penetration reflectance values also agree to within 1% of conventional SFDI.

Multifrequency synthesis and extraction using square wave projection patterns for quantitative tissue imaging

PubMed Central

Nadeau, Kyle P.; Rice, Tyler B.; Durkin, Anthony J.; Tromberg, Bruce J.

2015-01-01

Abstract. We present a method for spatial frequency domain data acquisition utilizing a multifrequency synthesis and extraction (MSE) method and binary square wave projection patterns. By illuminating a sample with square wave patterns, multiple spatial frequency components are simultaneously attenuated and can be extracted to determine optical property and depth information. Additionally, binary patterns are projected faster than sinusoids typically used in spatial frequency domain imaging (SFDI), allowing for short (millisecond or less) camera exposure times, and data acquisition speeds an order of magnitude or more greater than conventional SFDI. In cases where sensitivity to superficial layers or scattering is important, the fundamental component from higher frequency square wave patterns can be used. When probing deeper layers, the fundamental and harmonic components from lower frequency square wave patterns can be used. We compared optical property and depth penetration results extracted using square waves to those obtained using sinusoidal patterns on an in vivo human forearm and absorbing tube phantom, respectively. Absorption and reduced scattering coefficient values agree with conventional SFDI to within 1% using both high frequency (fundamental) and low frequency (fundamental and harmonic) spatial frequencies. Depth penetration reflectance values also agree to within 1% of conventional SFDI. PMID:26524682

Rapid formation of supermassive black hole binaries in galaxy mergers with gas.

PubMed

Mayer, L; Kazantzidis, S; Madau, P; Colpi, M; Quinn, T; Wadsley, J

2007-06-29

Supermassive black holes (SMBHs) are a ubiquitous component of the nuclei of galaxies. It is normally assumed that after the merger of two massive galaxies, a SMBH binary will form, shrink because of stellar or gas dynamical processes, and ultimately coalesce by emitting a burst of gravitational waves. However, so far it has not been possible to show how two SMBHs bind during a galaxy merger with gas because of the difficulty of modeling a wide range of spatial scales. Here we report hydrodynamical simulations that track the formation of a SMBH binary down to scales of a few light years after the collision between two spiral galaxies. A massive, turbulent, nuclear gaseous disk arises as a result of the galaxy merger. The black holes form an eccentric binary in the disk in less than 1 million years as a result of the gravitational drag from the gas rather than from the stars.

Open cluster evolutions in binary system: How they dissolved

NASA Astrophysics Data System (ADS)

Priyatikanto, R.; Arifyanto, M. I.; Wulandari, H. R. T.

2014-03-01

Binarity among stellar clusters in galaxy is such a reality which has been realized for a long time, but still hides several questions and problems to be solved. Some of binary star clusters are formed by close encounter, but the others are formed together from similar womb. Some of them undergo separation process, while the others are in the middle of merger toward common future. The products of merger binary star cluster have typical characteristics which differ from solo clusters, especially in their spatial distribution and their stellar members kinematics. On the other hand, these merger products still have to face dissolving processes triggered by both internal and external factors. In this study, we performed N-body simulations of merger binary clusters with different initial conditions. After merging, these clusters dissolve with greater mass-loss rate because of their angular momentum. These rotating clusters also experience more deceleration caused by external tidal field.

Edge-Preserving Image Smoothing Constraint in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) of Hyperspectral Data.

PubMed

Hugelier, Siewert; Vitale, Raffaele; Ruckebusch, Cyril

2018-03-01

This article explores smoothing with edge-preserving properties as a spatial constraint for the resolution of hyperspectral images with multivariate curve resolution-alternating least squares (MCR-ALS). For each constrained component image (distribution map), irrelevant spatial details and noise are smoothed applying an L 1 - or L 0 -norm penalized least squares regression, highlighting in this way big changes in intensity of adjacent pixels. The feasibility of the constraint is demonstrated on three different case studies, in which the objects under investigation are spatially clearly defined, but have significant spectral overlap. This spectral overlap is detrimental for obtaining a good resolution and additional spatial information should be provided. The final results show that the spatial constraint enables better image (map) abstraction, artifact removal, and better interpretation of the results obtained, compared to a classical MCR-ALS analysis of hyperspectral images.

SAGE III L2 Monthly Cloud Presence Data (Binary)

Atmospheric Science Data Center

2016-06-14

... degrees South Spatial Resolution:  1 km vertical Temporal Coverage:  02/27/2002 - 12/31/2005 ... Parameters:  Cloud Amount/Frequency Cloud Height Cloud Vertical Distribution Order Data:  Search and ...

Prevalence and predictors of thyroid functional abnormalities in newly diagnosed AL amyloidosis.

PubMed

Muchtar, E; Dean, D S; Dispenzieri, A; Dingli, D; Buadi, F K; Lacy, M Q; Hayman, S R; Kapoor, P; Leung, N; Russell, S; Lust, J A; Lin, Yi; Warsame, R; Gonsalves, W; Kourelis, T V; Go, R S; Chakraborty, R; Zeldenrust, S; Kyle, R A; Rajkumar, S Vincent; Kumar, S K; Gertz, M A

2017-06-01

Data on the effect of systemic immunoglobulin light chain amyloidosis (AL amyloidosis) on thyroid function are limited. To assess the prevalence of hypothyroidism in AL amyloidosis patients and determine its predictors. 1142 newly diagnosed AL amyloidosis patients were grouped based on the thyroid-stimulating hormone (TSH) measurement at diagnosis: hypothyroid group (TSH above upper normal reference; >5 mIU L -1 ; n = 217, 19% of study participants) and euthyroid group (n = 925, 81%). Predictors for hypothyroidism were assessed in a binary multivariate model. Survival between groups was compared using the log-rank test and a multivariate analysis. Patients with hypothyroidism were older, more likely to present with renal and hepatic involvement and had a higher light chain burden compared to patients in the euthyroid group. Higher proteinuria in patients with renal involvement and lower albumin in patients with hepatic involvement were associated with hypothyroidism. In a binary logistic regression model, age ≥65 years, female sex, renal involvement, hepatic involvement, kappa light chain restriction and amiodarone use were independently associated with hypothyroidism. Ninety-three per cent of patients in the hypothyroid group with free thyroxine measurement had normal values, consistent with subclinical hypothyroidism. Patients in the hypothyroid group had a shorter survival compared to patients in the euthyroid group (4-year survival 36% vs 43%; P = 0.008), a difference that was maintained in a multivariate analysis. A significant proportion of patients with AL amyloidosis present with hypothyroidism, predominantly subclinical, which carries a survival disadvantage. Routine assessment of TSH in these patients is warranted. © 2017 The Association for the Publication of the Journal of Internal Medicine.

Analysis of the Conformally Flat Approximation for Binary Neutron Star Initial Conditions

DOE PAGES

Suh, In-Saeng; Mathews, Grant J.; Haywood, J. Reese; ...

2017-01-09

The spatially conformally flat approximation (CFA) is a viable method to deduce initial conditions for the subsequent evolution of binary neutron stars employing the full Einstein equations. Here in this paper, we analyze the viability of the CFA for the general relativistic hydrodynamic initial conditions of binary neutron stars. We illustrate the stability of the conformally flat condition on the hydrodynamics by numerically evolving ~100 quasicircular orbits. We illustrate the use of this approximation for orbiting neutron stars in the quasicircular orbit approximation to demonstrate the equation of state dependence of these initial conditions and how they might affect themore » emergent gravitational wave frequency as the stars approach the innermost stable circular orbit.« less

Local Multi-Grouped Binary Descriptor With Ring-Based Pooling Configuration and Optimization.

PubMed

Gao, Yongqiang; Huang, Weilin; Qiao, Yu

2015-12-01

Local binary descriptors are attracting increasingly attention due to their great advantages in computational speed, which are able to achieve real-time performance in numerous image/vision applications. Various methods have been proposed to learn data-dependent binary descriptors. However, most existing binary descriptors aim overly at computational simplicity at the expense of significant information loss which causes ambiguity in similarity measure using Hamming distance. In this paper, by considering multiple features might share complementary information, we present a novel local binary descriptor, referred as ring-based multi-grouped descriptor (RMGD), to successfully bridge the performance gap between current binary and floated-point descriptors. Our contributions are twofold. First, we introduce a new pooling configuration based on spatial ring-region sampling, allowing for involving binary tests on the full set of pairwise regions with different shapes, scales, and distances. This leads to a more meaningful description than the existing methods which normally apply a limited set of pooling configurations. Then, an extended Adaboost is proposed for an efficient bit selection by emphasizing high variance and low correlation, achieving a highly compact representation. Second, the RMGD is computed from multiple image properties where binary strings are extracted. We cast multi-grouped features integration as rankSVM or sparse support vector machine learning problem, so that different features can compensate strongly for each other, which is the key to discriminativeness and robustness. The performance of the RMGD was evaluated on a number of publicly available benchmarks, where the RMGD outperforms the state-of-the-art binary descriptors significantly.

Prevalence and determinants of cardiovascular disease risk factors among the residents of urban community housing projects in Malaysia.

PubMed

Amiri, Mohammadreza; Majid, Hazreen Abdul; Hairi, FarizahMohd; Thangiah, Nithiah; Bulgiba, Awang; Su, Tin Tin

2014-01-01

The objectives are to assess the prevalence and determinants of cardiovascular disease (CVD) risk factors among the residents of Community Housing Projects in metropolitan Kuala Lumpur, Malaysia. By using simple random sampling, we selected and surveyed 833 households which comprised of 3,722 individuals. Out of the 2,360 adults, 50.5% participated in blood sampling and anthropometric measurement sessions. Uni and bivariate data analysis and multivariate binary logistic regression were applied to identify demographic and socioeconomic determinants of the existence of having at least one CVD risk factor. As a Result, while obesity (54.8%), hypercholesterolemia (51.5%), and hypertension (39.3%) were the most common CVD risk factors among the low-income respondents, smoking (16.3%), diabetes mellitus (7.8%) and alcohol consumption (1.4%) were the least prevalent. Finally, the results from the multivariate binary logistic model illustrated that compared to the Malays, the Indians were 41% less likely to have at least one of the CVD risk factors (OR = 0.59; 95% CI: 0.37 - 0.93). In Conclusion, the low-income individuals were at higher risk of developing CVDs. Prospective policies addressing preventive actions and increased awareness focusing on low-income communities are highly recommended and to consider age, gender, ethnic backgrounds, and occupation classes.

Simulated single molecule microscopy with SMeagol.

PubMed

Lindén, Martin; Ćurić, Vladimir; Boucharin, Alexis; Fange, David; Elf, Johan

2016-08-01

SMeagol is a software tool to simulate highly realistic microscopy data based on spatial systems biology models, in order to facilitate development, validation and optimization of advanced analysis methods for live cell single molecule microscopy data. SMeagol runs on Matlab R2014 and later, and uses compiled binaries in C for reaction-diffusion simulations. Documentation, source code and binaries for Mac OS, Windows and Ubuntu Linux can be downloaded from http://smeagol.sourceforge.net johan.elf@icm.uu.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Binary logic based purely on Fresnel diffraction

NASA Astrophysics Data System (ADS)

Hamam, H.; de Bougrenet de La Tocnaye, J. L.

1995-09-01

Binary logic operations on two-dimensional data arrays are achieved by use of the self-imaging properties of Fresnel diffraction. The fields diffracted by periodic objects can be considered as the superimposition of weighted and shifted replicas of original objects. We show that a particular spatial organization of the input data can result in logical operations being performed on these data in the considered diffraction planes. Among various advantages, this approach is shown to allow the implementation of dual-track, nondissipative logical operators. Image algebra is presented as an experimental illustration of this principle.

Computer simulation of radiation damage in gallium arsenide

NASA Technical Reports Server (NTRS)

Stith, John J.; Davenport, James C.; Copeland, Randolph L.

1989-01-01

A version of the binary-collision simulation code MARLOWE was used to study the spatial characteristics of radiation damage in proton and electron irradiated gallium arsenide. Comparisons made with the experimental results proved to be encouraging.

A multiplexable TALE-based binary expression system for in vivo cellular interaction studies.

PubMed

Toegel, Markus; Azzam, Ghows; Lee, Eunice Y; Knapp, David J H F; Tan, Ying; Fa, Ming; Fulga, Tudor A

2017-11-21

Binary expression systems have revolutionised genetic research by enabling delivery of loss-of-function and gain-of-function transgenes with precise spatial-temporal resolution in vivo. However, at present, each existing platform relies on a defined exogenous transcription activator capable of binding a unique recognition sequence. Consequently, none of these technologies alone can be used to simultaneously target different tissues or cell types in the same organism. Here, we report a modular system based on programmable transcription activator-like effector (TALE) proteins, which enables parallel expression of multiple transgenes in spatially distinct tissues in vivo. Using endogenous enhancers coupled to TALE drivers, we demonstrate multiplexed orthogonal activation of several transgenes carrying cognate variable activating sequences (VAS) in distinct neighbouring cell types of the Drosophila central nervous system. Since the number of combinatorial TALE-VAS pairs is virtually unlimited, this platform provides an experimental framework for highly complex genetic manipulation studies in vivo.

Generation-3 programmable array microscope (PAM) with digital micro-mirror device (DMD)

NASA Astrophysics Data System (ADS)

De Beule, Pieter A. A.; de Vries, Anthony H. B.; Arndt-Jovin, Donna J.; Jovin, Thomas M.

2011-03-01

We report progress on the construction of an optical sectioning programmable array microscope (PAM) implemented with a digital micro-mirror device (DMD) spatial light modulator (SLM) utilized for both fluorescence illumination and detection. The introduction of binary intensity modulation at the focal plane of a microscope objective in a computer controlled pixilated mode allows the recovery of an optically sectioned image. Illumination patterns can be changed very quickly, in contrast to static Nipkow disk or aperture correlation implementations, thereby creating an optical system that can be optimized to the optical specimen in a convenient manner, e.g. for patterned photobleaching, photobleaching reduction, or spatial superresolution. We present a third generation (Gen-3) dual path PAM module incorporating the 25 kHz binary frame rate TI 1080p DMD and a newly developed optical system that offers diffraction limited imaging with compensation of tilt angle distortion.

Spherical hashing: binary code embedding with hyperspheres.

PubMed

Heo, Jae-Pil; Lee, Youngwoon; He, Junfeng; Chang, Shih-Fu; Yoon, Sung-Eui

2015-11-01

Many binary code embedding schemes have been actively studied recently, since they can provide efficient similarity search, and compact data representations suitable for handling large scale image databases. Existing binary code embedding techniques encode high-dimensional data by using hyperplane-based hashing functions. In this paper we propose a novel hypersphere-based hashing function, spherical hashing, to map more spatially coherent data points into a binary code compared to hyperplane-based hashing functions. We also propose a new binary code distance function, spherical Hamming distance, tailored for our hypersphere-based binary coding scheme, and design an efficient iterative optimization process to achieve both balanced partitioning for each hash function and independence between hashing functions. Furthermore, we generalize spherical hashing to support various similarity measures defined by kernel functions. Our extensive experiments show that our spherical hashing technique significantly outperforms state-of-the-art techniques based on hyperplanes across various benchmarks with sizes ranging from one to 75 million of GIST, BoW and VLAD descriptors. The performance gains are consistent and large, up to 100 percent improvements over the second best method among tested methods. These results confirm the unique merits of using hyperspheres to encode proximity regions in high-dimensional spaces. Finally, our method is intuitive and easy to implement.

Investigation of focusing and correcting aberrations with binary amplitude and polarization modulation

DOE PAGES

Fiala, Peter; Li, Yunqi; Dorrer, Christophe

2018-01-29

Here, we investigate the focusing and correcting wavefront aberration of an optical wave using binary amplitude and polarization modulation. Focusing is performed by selectively modulating the field in different zones of the pupil to obtain on-axis constructive interference at a given distance. The conventional Soret zone plate (binary amplitude profile) is expanded to a polarization Soret zone plate with twice the focusing efficiency. Binary pixelated devices that approximate the sinusoidal transmission profile of a Gabor zone plate by spatial dithering are also investigated with amplitude and polarization modulation. Wavefront aberrations are corrected by modulation of the field in the pupilmore » plane to prevent destructive interference in the focal plane of an ideal focusing element. Polarization modulation improves the efficiency obtained by amplitude-only modulation, with a gain that depends on the aberration. Experimental results obtained with Cr-on-glass devices for amplitude modulation and liquid crystal devices operating in the Mauguin condition for polarization modulation are in very good agreement with simulations.« less

A survey of the Local Group of galaxies for symbiotic binary stars - I. First detection of symbiotic stars in M33

NASA Astrophysics Data System (ADS)

Mikołajewska, Joanna; Shara, Michael M.; Caldwell, Nelson; Iłkiewicz, Krystian; Zurek, David

2017-02-01

We present and discuss initial selection criteria and first results in M33 from a systematic search for extragalactic symbiotic stars. We show that the presence of diffuse ionized gas (DIG) emission can significantly contaminate the spectra of symbiotic star candidates. This important effect forces upon us a more stringent working definition of an extragalactic symbiotic star. We report the first detections and spectroscopic characterization of 12 symbiotic binaries in M33. We found that four of our systems contain carbon-rich giants. In another two of them, the giant seems to be a Zr-enhanced MS star, while the remaining six objects host M-type giants. The high number ratio of C to M giants in these binaries is consistent with the low metallicity of M33. The spatial and radial velocity distributions of these new symbiotic binaries are consistent with a wide range of progenitor star ages.

Investigation of focusing and correcting aberrations with binary amplitude and polarization modulation

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

Fiala, Peter; Li, Yunqi; Dorrer, Christophe

Here, we investigate the focusing and correcting wavefront aberration of an optical wave using binary amplitude and polarization modulation. Focusing is performed by selectively modulating the field in different zones of the pupil to obtain on-axis constructive interference at a given distance. The conventional Soret zone plate (binary amplitude profile) is expanded to a polarization Soret zone plate with twice the focusing efficiency. Binary pixelated devices that approximate the sinusoidal transmission profile of a Gabor zone plate by spatial dithering are also investigated with amplitude and polarization modulation. Wavefront aberrations are corrected by modulation of the field in the pupilmore » plane to prevent destructive interference in the focal plane of an ideal focusing element. Polarization modulation improves the efficiency obtained by amplitude-only modulation, with a gain that depends on the aberration. Experimental results obtained with Cr-on-glass devices for amplitude modulation and liquid crystal devices operating in the Mauguin condition for polarization modulation are in very good agreement with simulations.« less

ISM DUST GRAINS AND N-BAND SPECTRAL VARIABILITY IN THE SPATIALLY RESOLVED SUBARCSECOND BINARY UY Aur

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

Skemer, Andrew J.; Close, Laird M.; Hinz, Philip M.

2010-03-10

The 10 {mu}m silicate feature is an essential diagnostic of dust-grain growth and planet formation in young circumstellar disks. The Spitzer Space Telescope has revolutionized the study of this feature, but due to its small (85 cm) aperture, it cannot spatially resolve small/medium-separation binaries ({approx}<3''; {approx}< 420 AU) at the distances of the nearest star-forming regions ({approx}140 pc). Large, 6-10 m ground-based telescopes with mid-infrared instruments can resolve these systems. In this paper, we spatially resolve the 0.''88 binary, UY Aur, with MMTAO/BLINC-MIRAC4 mid-infrared spectroscopy. We then compare our spectra to Spitzer/IRS (unresolved) spectroscopy, and resolved images from IRTF/MIRAC2, Keck/OSCIR,more » and Gemini/Michelle, which were taken over the past decade. We find that UY Aur A has extremely pristine, interstellar medium (ISM)-like grains and that UY Aur B has an unusually shaped silicate feature, which is probably the result of blended emission and absorption from foreground extinction in its disk. We also find evidence for variability in both UY Aur A and UY Aur B by comparing synthetic photometry from our spectra with resolved imaging from previous epochs. The photometric variability of UY Aur A could be an indication that the silicate emission itself is variable, as was recently found in EX Lupi. Otherwise, the thermal continuum is variable, and either the ISM-like dust has never evolved, or it is being replenished, perhaps by UY Aur's circumbinary disk.« less

Detecting spatial regimes in ecosystems

USGS Publications Warehouse

Sundstrom, Shana M.; Eason, Tarsha; Nelson, R. John; Angeler, David G.; Barichievy, Chris; Garmestani, Ahjond S.; Graham, Nicholas A.J.; Granholm, Dean; Gunderson, Lance; Knutson, Melinda; Nash, Kirsty L.; Spanbauer, Trisha; Stow, Craig A.; Allen, Craig R.

2017-01-01

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

NASA Astrophysics Data System (ADS)

Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

2002-12-01

The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

Linear multivariate evaluation models for spatial perception of soundscape.

PubMed

Deng, Zhiyong; Kang, Jian; Wang, Daiwei; Liu, Aili; Kang, Joe Zhengyu

2015-11-01

Soundscape is a sound environment that emphasizes the awareness of auditory perception and social or cultural understandings. The case of spatial perception is significant to soundscape. However, previous studies on the auditory spatial perception of the soundscape environment have been limited. Based on 21 native binaural-recorded soundscape samples and a set of auditory experiments for subjective spatial perception (SSP), a study of the analysis among semantic parameters, the inter-aural-cross-correlation coefficient (IACC), A-weighted-equal sound-pressure-level (L(eq)), dynamic (D), and SSP is introduced to verify the independent effect of each parameter and to re-determine some of their possible relationships. The results show that the more noisiness the audience perceived, the worse spatial awareness they received, while the closer and more directional the sound source image variations, dynamics, and numbers of sound sources in the soundscape are, the better the spatial awareness would be. Thus, the sensations of roughness, sound intensity, transient dynamic, and the values of Leq and IACC have a suitable range for better spatial perception. A better spatial awareness seems to promote the preference slightly for the audience. Finally, setting SSPs as functions of the semantic parameters and Leq-D-IACC, two linear multivariate evaluation models of subjective spatial perception are proposed.

4-D Imaging and Modeling of Eta Carinae's Inner Fossil Wind Structures

NASA Astrophysics Data System (ADS)

Madura, Thomas I.; Gull, Theodore; Teodoro, Mairan; Clementel, Nicola; Corcoran, Michael; Damineli, Augusto; Groh, Jose; Hamaguchi, Kenji; Hillier, D. John; Moffat, Anthony; Richardson, Noel; Weigelt, Gerd; Lindler, Don; Feggans, Keith

2017-11-01

Eta Carinae is the most massive active binary within 10,000 light-years and is famous for the largest non-terminal stellar explosion ever recorded. Observations reveal that the supermassive (~120 M⊙) binary, consisting of an LBV and either a WR or extreme O star, undergoes dramatic changes every 5.54 years due to the stars' very eccentric orbits (e ~ 0.9). Many of these changes are caused by a dynamic wind-wind collision region (WWCR) between the stars, plus expanding fossil WWCRs formed one, two, and three 5.54-year cycles ago. The fossil WWCRs can be spatially and spectrally resolved by the Hubble Space Telescope/Space Telescope Imaging Spectrograph (HST/STIS). Starting in June 2009, we used the HST/STIS to spatially map Eta Carinae's fossil WWCRs across one full orbit, following temporal changes in several forbidden emission lines (e.g. [Feiii] 4659 Å, [Feii] 4815 Å), creating detailed data cubes at multiple epochs. Multiple wind structures were imaged, revealing details about the binary's orbital motion, photoionization properties, and recent (~5 - 15 year) mass-loss history. These observations allow us to test 3-D hydrodynamical and radiative-transfer models of the interacting winds. Our observations and models strongly suggest that the wind and photoionization properties of Eta Carinae's binary have not changed substantially over the past several orbital cycles. They also provide a baseline for following future changes in Eta Carinae, essential for understanding the late-stage evolution of this nearby supernova progenitor. For more details, see Gull et al. (2016) and references therein.

Active Brownian motion tunable by light.

PubMed

Buttinoni, Ivo; Volpe, Giovanni; Kümmel, Felix; Volpe, Giorgio; Bechinger, Clemens

2012-07-18

Active Brownian particles are capable of taking up energy from their environment and converting it into directed motion; examples range from chemotactic cells and bacteria to artificial micro-swimmers. We have recently demonstrated that Janus particles, i.e. gold-capped colloidal spheres, suspended in a critical binary liquid mixture perform active Brownian motion when illuminated by light. In this paper, we investigate in more detail their swimming mechanism, leading to active Brownian motion. We show that the illumination-borne heating induces a local asymmetric demixing of the binary mixture, generating a spatial chemical concentration gradient which is responsible for the particle's self-diffusiophoretic motion. We study this effect as a function of the functionalization of the gold cap, the particle size and the illumination intensity: the functionalization determines what component of the binary mixture is preferentially adsorbed at the cap and the swimming direction (towards or away from the cap); the particle size determines the rotational diffusion and, therefore, the random reorientation of the particle; and the intensity tunes the strength of the heating and, therefore, of the motion. Finally, we harness this dependence of the swimming strength on the illumination intensity to investigate the behavior of a micro-swimmer in a spatial light gradient, where its swimming properties are space-dependent.

Spatial variability in intertidal macroalgal assemblages on the North Portuguese coast: consistence between species and functional group approaches

NASA Astrophysics Data System (ADS)

Veiga, P.; Rubal, M.; Vieira, R.; Arenas, F.; Sousa-Pinto, I.

2013-03-01

Natural assemblages are variable in space and time; therefore, quantification of their variability is imperative to identify relevant scales for investigating natural or anthropogenic processes shaping these assemblages. We studied the variability of intertidal macroalgal assemblages on the North Portuguese coast, considering three spatial scales (from metres to 10 s of kilometres) following a hierarchical design. We tested the hypotheses that (1) spatial pattern will be invariant at all the studied scales and (2) spatial variability of macroalgal assemblages obtained by using species will be consistent with that obtained using functional groups. This was done considering as univariate variables: total biomass and number of taxa as well as biomass of the most important species and functional groups and as multivariate variables the structure of macroalgal assemblages, both considering species and functional groups. Most of the univariate results confirmed the first hypothesis except for the total number of taxa and foliose macroalgae that showed significant variability at the scale of site and area, respectively. In contrast, when multivariate patterns were examined, the first hypothesis was rejected except at the scale of 10 s of kilometres. Both uni- and multivariate results indicated that variation was larger at the smallest scale, and thus, small-scale processes seem to have more effect on spatial variability patterns. Macroalgal assemblages, both considering species and functional groups as surrogate, showed consistent spatial patterns, and therefore, the second hypothesis was confirmed. Consequently, functional groups may be considered a reliable biological surrogate to study changes on macroalgal assemblages at least along the investigated Portuguese coastline.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

The Connection Between X-ray Binaries and Star Clusters in the Antennae

NASA Astrophysics Data System (ADS)

Rangelov, Blagoy; Chandar, R.; Prestwich, A.

2011-05-01

High Mass X-ray Binaries (HMXBs) are believed to form in massive, compact star clusters. However the correlation between these young binary star systems and properties of their parent clusters are still poorly known. We compare the locations of 82 X-ray binaries detected in the merging Antennae galaxies by Zezas et al. (2006) based on observations taken with the Chandra Space Telescope, with a catalog of optically selected star clusters presented recently by Whitmore et al. (2010) based on observations taken with the Hubble Space Telescope. We find 22 X-ray binaries coincident or nearly coincident with star clusters. The ages of the clusters were estimated by comparing their UBVIHα colors with predictions from stellar evolutionary models. We find that 14 of the 22 coincident sources (64%) are hosted by star clusters with ages of 6 Myr or less. At these very young ages, only stars initially more massive than M ≥ 30 Msun have evolved into compact remnants, almost certainly black holes. Therefore, these 14 sources are likely to be black hole binaries. Five of the XRBs are hosted by young clusters with ages τ 30-50 Myr, while three are hosted by intermediate age clusters with τ 100-300 Myr. We suggest that these older X-ray binaries likely have neutron stars as the compact object. We conclude that precision age-dating of star clusters, which are spatially coincident with XRBs in nearby star forming galaxies, is a powerful method of constraining the nature of the XRBs.

Binary Cepheids From High-Angular Resolution

NASA Astrophysics Data System (ADS)

Gallenne, A.; Mérand, A.; Kervella, P.

2015-12-01

Optical interferometry is the only technique giving access to milli-arcsecond (mas) spatial resolution. This is a powerful and unique tool to detect the close orbiting companions of Cepheids, and offers an unique opportunity to make progress in resolving the Cepheid mass discrepancy. Our goal in studying binary Cepheids is to measure the astrometric position of the high-contrast companion, and then combine them with spectroscopic measurements to derive the orbital elements, distances, and dynamical masses. In the course of this program, we developed a new tool, CANDID, to search for high-contrast companions and set detection limits from interferometric observations

An Interferometric Study of the Post-AGB Binary 89 Herculis. 1: Spatially Resolving the Continuum Circumstellar Environment at Optical and Near-IR Wavelengths with the VLTI, NPOI, IOTA, PTI, and the CHARA Array

DTIC Science & Technology

2013-01-01

evolution of binaries as well as the structure of circumstellar disks. Aims. A multiwavelength high angular resolution study of the prototypical object...optical to mid-IR wave- lengths. For YSOs this has led to the discovery of an empiri- cal size-luminosity relation (Millan-Gabet et al. 2001; Monnier...Millan-Gabet 2002), which in turn has led to the current paradigm (Dullemond & Monnier 2010) of a passive dusty disk with an optically thin cavity and the

Separate first- and second-order processing is supported by spatial summation estimates at the fovea and eccentrically.

PubMed

Sukumar, Subash; Waugh, Sarah J

2007-03-01

We estimated spatial summation areas for the detection of luminance-modulated (LM) and contrast-modulated (CM) blobs at the fovea, 2.5, 5 and 10 deg eccentrically. Gaussian profiles were added or multiplied to binary white noise to create LM and CM blob stimuli and these were used to psychophysically estimate detection thresholds and spatial summation areas. The results reveal significantly larger summation areas for detecting CM than LM blobs across eccentricity. These differences are comparable to receptive field size estimates made in V1 and V2. They support the notion that separate spatial processing occurs for the detection of LM and CM stimuli.

Subpixel Snow Cover Mapping from MODIS Data by Nonparametric Regression Splines

NASA Astrophysics Data System (ADS)

Akyurek, Z.; Kuter, S.; Weber, G. W.

2016-12-01

Spatial extent of snow cover is often considered as one of the key parameters in climatological, hydrological and ecological modeling due to its energy storage, high reflectance in the visible and NIR regions of the electromagnetic spectrum, significant heat capacity and insulating properties. A significant challenge in snow mapping by remote sensing (RS) is the trade-off between the temporal and spatial resolution of satellite imageries. In order to tackle this issue, machine learning-based subpixel snow mapping methods, like Artificial Neural Networks (ANNs), from low or moderate resolution images have been proposed. Multivariate Adaptive Regression Splines (MARS) is a nonparametric regression tool that can build flexible models for high dimensional and complex nonlinear data. Although MARS is not often employed in RS, it has various successful implementations such as estimation of vertical total electron content in ionosphere, atmospheric correction and classification of satellite images. This study is the first attempt in RS to evaluate the applicability of MARS for subpixel snow cover mapping from MODIS data. Total 16 MODIS-Landsat ETM+ image pairs taken over European Alps between March 2000 and April 2003 were used in the study. MODIS top-of-atmospheric reflectance, NDSI, NDVI and land cover classes were used as predictor variables. Cloud-covered, cloud shadow, water and bad-quality pixels were excluded from further analysis by a spatial mask. MARS models were trained and validated by using reference fractional snow cover (FSC) maps generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also developed. The mutual comparison of obtained MARS and ANN models was accomplished on independent test areas. The MARS model performed better than the ANN model with an average RMSE of 0.1288 over the independent test areas; whereas the average RMSE of the ANN model was 0.1500. MARS estimates for low FSC values (i.e., FSC<0.3) were better than that of ANN. Both ANN and MARS tended to overestimate medium FSC values (i.e., 0.30.7).

Ornaments Reveal Resistance of North European Cultures to the Spread of Farming

PubMed Central

Rigaud, Solange; d'Errico, Francesco; Vanhaeren, Marian

2015-01-01

The transition to farming is the process by which human groups switched from hunting and gathering wild resources to food production. Understanding how and to what extent the spreading of farming communities from the Near East had an impact on indigenous foraging populations in Europe has been the subject of lively debates for decades. Ethnographic and archaeological studies have shown that population replacement and admixture, trade, and long distance diffusion of cultural traits lead to detectable changes in symbolic codes expressed by associations of ornaments on the human body. Here we use personal ornaments to document changes in cultural geography during the Mesolithic-Neolithic transition. We submitted a binary matrix of 224 bead-types found at 212 European Mesolithic and 222 Early Neolithic stratigraphic units to a series of spatial and multivariate analyses. Our results reveal consistent diachronic and geographical trends in the use of personal ornaments during the Neolithisation. Adoption of novel bead-types combined with selective appropriation of old attires by incoming farmers is identified in Southern and Central Europe while cultural resistance leading to the nearly exclusive persistence of indigenous personal ornaments characterizes Northern Europe. We argue that this pattern reflects two distinct cultural trajectories with different potential for gene flow. PMID:25853888

Prevalence and determinants of cardiovascular disease risk factors among the residents of urban community housing projects in Malaysia

PubMed Central

2014-01-01

Objectives The objectives are to assess the prevalence and determinants of cardiovascular disease (CVD) risk factors among the residents of Community Housing Projects in metropolitan Kuala Lumpur, Malaysia. Method By using simple random sampling, we selected and surveyed 833 households which comprised of 3,722 individuals. Out of the 2,360 adults, 50.5% participated in blood sampling and anthropometric measurement sessions. Uni and bivariate data analysis and multivariate binary logistic regression were applied to identify demographic and socioeconomic determinants of the existence of having at least one CVD risk factor. Results As a Result, while obesity (54.8%), hypercholesterolemia (51.5%), and hypertension (39.3%) were the most common CVD risk factors among the low-income respondents, smoking (16.3%), diabetes mellitus (7.8%) and alcohol consumption (1.4%) were the least prevalent. Finally, the results from the multivariate binary logistic model illustrated that compared to the Malays, the Indians were 41% less likely to have at least one of the CVD risk factors (OR = 0.59; 95% CI: 0.37 - 0.93). Conclusion In Conclusion, the low-income individuals were at higher risk of developing CVDs. Prospective policies addressing preventive actions and increased awareness focusing on low-income communities are highly recommended and to consider age, gender, ethnic backgrounds, and occupation classes. PMID:25436515

Cerebrovascular risk factors for patients with cerebral watershed infarction: A case-control study based on computed tomography angiography in a population from Southwest China.

PubMed

Dong, Mei-Xue; Hu, Ling; Huang, Yuan-Jun; Xu, Xiao-Min; Liu, Yang; Wei, You-Dong

2017-07-01

To determine cerebrovascular risk factors for patients with cerebral watershed infarction (CWI) from Southwest China.Patients suffering from acute ischemic stroke were categorized into internal CWI (I-CWI), external CWI (E-CWI), or non-CWI (patients without CWI) groups. Clinical data were collected and degrees of steno-occlusion of all cerebral arteries were scored. Arteries associated with the circle of Willis were also assessed. Data were compared using Pearson chi-squared tests for categorical data and 1-way analysis of variance with Bonferroni post hoc tests for continuous data, as appropriate. Multivariate binary logistic regression analysis was performed to determine independent cerebrovascular risk factors for CWI.Compared with non-CWI, I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery, ipsilateral carotid artery, and contralateral middle cerebral artery. E-CWI showed no significant differences. All the 3 arteries were independent cerebrovascular risk factors for I-CWI confirmed by multivariate binary logistic regression analysis. I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery compared with E-CWI. No significant differences were found among arteries associated with the circle of Willis.The ipsilateral middle cerebral artery, carotid artery, and contralateral middle cerebral artery were independent cerebrovascular risk factors for I-CWI. No cerebrovascular risk factor was identified for E-CWI.

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

Beck, Tracy L.; Lubow, S. H.; Bary, Jeffrey S.

We present high spatial resolution maps of ro-vibrational molecular hydrogen emission from the environment of the GG Tau A binary component in the GG Tau quadruple system. The H{sub 2} v = 1-0 S(1) emission is spatially resolved and encompasses the inner binary, with emission detected at locations that should be dynamically cleared on several hundred year timescales. Extensions of H{sub 2} gas emission are seen to {approx}100 AU distances from the central stars. The v = 2-1 S(1) emission at 2.24 {mu}m is also detected at {approx}30 AU from the central stars, with a line ratio of 0.05 {+-}more » 0.01 with respect to the v = 1-0 S(1) emission. Assuming gas in LTE, this ratio corresponds to an emission environment at {approx}1700 K. We estimate that this temperature is too high for quiescent gas heated by X-ray or UV emission from the central stars. Surprisingly, we find that the brightest region of H{sub 2} emission arises from a spatial location that is exactly coincident with a recently revealed dust 'streamer' which seems to be transferring material from the outer circumbinary ring around GG Tau A into the inner region. As a result, we identify a new excitation mechanism for ro-vibrational H{sub 2} stimulation in the environment of young stars. The H{sub 2} in the GG Tau A system appears to be stimulated by mass accretion infall as material in the circumbinary ring accretes onto the system to replenish the inner circumstellar disks. We postulate that H{sub 2} stimulated by accretion infall could be present in other systems, particularly binaries and 'transition disk' systems which have dust-cleared gaps in their circumstellar environments.« less

ISM Dust Grains and N-band Spectral Variability in the Spatially Resolved Subarcsecond Binary UY Aur

NASA Astrophysics Data System (ADS)

Skemer, Andrew J.; Close, Laird M.; Hinz, Philip M.; Hoffmann, William F.; Greene, Thomas P.; Males, Jared R.; Beck, Tracy L.

2010-03-01

The 10 μm silicate feature is an essential diagnostic of dust-grain growth and planet formation in young circumstellar disks. The Spitzer Space Telescope has revolutionized the study of this feature, but due to its small (85 cm) aperture, it cannot spatially resolve small/medium-separation binaries (lsim3''; <~ 420 AU) at the distances of the nearest star-forming regions (~140 pc). Large, 6-10 m ground-based telescopes with mid-infrared instruments can resolve these systems. In this paper, we spatially resolve the 0farcs88 binary, UY Aur, with MMTAO/BLINC-MIRAC4 mid-infrared spectroscopy. We then compare our spectra to Spitzer/IRS (unresolved) spectroscopy, and resolved images from IRTF/MIRAC2, Keck/OSCIR, and Gemini/Michelle, which were taken over the past decade. We find that UY Aur A has extremely pristine, interstellar medium (ISM)-like grains and that UY Aur B has an unusually shaped silicate feature, which is probably the result of blended emission and absorption from foreground extinction in its disk. We also find evidence for variability in both UY Aur A and UY Aur B by comparing synthetic photometry from our spectra with resolved imaging from previous epochs. The photometric variability of UY Aur A could be an indication that the silicate emission itself is variable, as was recently found in EX Lupi. Otherwise, the thermal continuum is variable, and either the ISM-like dust has never evolved, or it is being replenished, perhaps by UY Aur's circumbinary disk. The observations reported here were partially obtained at the Infrared Telescope Facility, which is operated by the University of Hawaii under Cooperative Agreement no. NCC 5-538 with the National Aeronautics and Space Administration, Science Mission Directorate, Planetary Astronomy Program.

Multielement geochemistry identifies the spatial pattern of soil and sediment contamination in an urban parkland, Western Australia.

PubMed

Rate, Andrew W

2018-06-15

Urban environments are dynamic and highly heterogeneous, and multiple additions of potential contaminants are likely on timescales which are short relative to natural processes. The likely sources and location of soil or sediment contamination in urban environment should therefore be detectable using multielement geochemical composition combined with rigorously applied multivariate statistical techniques. Soil, wetland sediment, and street dust was sampled along intersecting transects in Robertson Park in metropolitan Perth, Western Australia. Samples were analysed for near-total concentrations of multiple elements (including Cd, Ce, Co, Cr, Cu, Fe, Gd, La, Mn, Nd, Ni, Pb, Y, and Zn), as well as pH, and electrical conductivity. Samples at some locations within Robertson Park had high concentrations of potentially toxic elements (Pb above Health Investigation Limits; As, Ba, Cu, Mn, Ni, Pb, V, and Zn above Ecological Investigation Limits). However, these concentrations carry low risk due to the main land use as recreational open space, the low proportion of samples exceeding guideline values, and a tendency for the highest concentrations to be located within the less accessible wetland basin. The different spatial distributions of different groups of contaminants was consistent with different inputs of contaminants related to changes in land use and technology over the history of the site. Multivariate statistical analyses reinforced the spatial information, with principal component analysis identifying geochemical associations of elements which were also spatially related. A multivariate linear discriminant model was able to discriminate samples into a-priori types, and could predict sample type with 84% accuracy based on multielement composition. The findings suggest substantial advantages of characterising a site using multielement and multivariate analyses, an approach which could benefit investigations of other sites of concern. Copyright © 2018 Elsevier B.V. All rights reserved.

Statistical inferences for data from studies conducted with an aggregated multivariate outcome-dependent sample design

PubMed Central

Lu, Tsui-Shan; Longnecker, Matthew P.; Zhou, Haibo

2016-01-01

Outcome-dependent sampling (ODS) scheme is a cost-effective sampling scheme where one observes the exposure with a probability that depends on the outcome. The well-known such design is the case-control design for binary response, the case-cohort design for the failure time data and the general ODS design for a continuous response. While substantial work has been done for the univariate response case, statistical inference and design for the ODS with multivariate cases remain under-developed. Motivated by the need in biological studies for taking the advantage of the available responses for subjects in a cluster, we propose a multivariate outcome dependent sampling (Multivariate-ODS) design that is based on a general selection of the continuous responses within a cluster. The proposed inference procedure for the Multivariate-ODS design is semiparametric where all the underlying distributions of covariates are modeled nonparametrically using the empirical likelihood methods. We show that the proposed estimator is consistent and developed the asymptotically normality properties. Simulation studies show that the proposed estimator is more efficient than the estimator obtained using only the simple-random-sample portion of the Multivariate-ODS or the estimator from a simple random sample with the same sample size. The Multivariate-ODS design together with the proposed estimator provides an approach to further improve study efficiency for a given fixed study budget. We illustrate the proposed design and estimator with an analysis of association of PCB exposure to hearing loss in children born to the Collaborative Perinatal Study. PMID:27966260

Mass-Luminosity Relations for Rapid and Slow Rotators.

NASA Astrophysics Data System (ADS)

Malkov, O. Yu.

2006-08-01

Comparing the radii of eclipsing binaries components and single stars we have found a noticeable difference between observational parameters of B0V-G0V components of eclipsing binaries and those of single stars of the corresponding spectral type. This difference was confirmed by re-analysing the results of independent investigations published in the literature. Larger radii and higher temperatures of A-F eclipsing binaries can be explained by synchronization of such stars in close systems that prevents them to rotate rapidly. So, we have found that the mass-luminosity relation based on eclipsing binary data cannot be used to derive the initial mass function of single stars. While our current knowledge of the empirical mass-luminosity relation for intermediate-mass (1.5 to 10 m[*]) stars is based exclusively on data from eclipsing binaries, knowledge of the mass-luminosity relation should come from dynamical mass determinations of visual binaries, combined with spatially resolved precise photometry. Then the initial mass function should be revised for m>1.5m[*]. Data were collected on fundamental parameters of stars with masses m > 1.5.m [*]). They are components of binaries with P > 15^d and consequently are not synchronised with the orbital periods and presumably are rapid rotators. These stars are believed to evolve similarly with single stars, so these data allow us to construct mass-luminosity and other relations that can more confidently be used for statistical and astrophysical investigations of single stars than so called standard relations, based on data on detached main-sequence double-lined short-period eclipsing binaries. Mass-luminosity, mass-temperature and mass-radius relations of single stars are presented, as well as their HR diagram.

Detecting spatial regimes in ecosystems | Science Inventory ...

EPA Pesticide Factsheets

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (US Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analysis such as nMDS (non-metric Multidimensional Scaling) and cluster analysis. We successfully detect spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. Use an information theory based method to identify ecological boundaries and compare our results to traditional early warning

A Spatially Constrained Multi-autoencoder Approach for Multivariate Geochemical Anomaly Recognition

NASA Astrophysics Data System (ADS)

Lirong, C.; Qingfeng, G.; Renguang, Z.; Yihui, X.

2017-12-01

Separating and recognizing geochemical anomalies from the geochemical background is one of the key tasks in geochemical exploration. Many methods have been developed, such as calculating the mean ±2 standard deviation, and fractal/multifractal models. In recent years, deep autoencoder, a deep learning approach, have been used for multivariate geochemical anomaly recognition. While being able to deal with the non-normal distributions of geochemical concentrations and the non-linear relationships among them, this self-supervised learning method does not take into account the spatial heterogeneity of geochemical background and the uncertainty induced by the randomly initialized weights of neurons, leading to ineffective recognition of weak anomalies. In this paper, we introduce a spatially constrained multi-autoencoder (SCMA) approach for multivariate geochemical anomaly recognition, which includes two steps: spatial partitioning and anomaly score computation. The first step divides the study area into multiple sub-regions to segregate the geochemical background, by grouping the geochemical samples through K-means clustering, spatial filtering, and spatial constraining rules. In the second step, for each sub-region, a group of autoencoder neural networks are constructed with an identical structure but different initial weights on neurons. Each autoencoder is trained using the geochemical samples within the corresponding sub-region to learn the sub-regional geochemical background. The best autoencoder of a group is chosen as the final model for the corresponding sub-region. The anomaly score at each location can then be calculated as the euclidean distance between the observed concentrations and reconstructed concentrations of geochemical elements.The experiments using the geochemical data and Fe deposits in the southwestern Fujian province of China showed that our SCMA approach greatly improved the recognition of weak anomalies, achieving the AUC of 0.89, compared with the AUC of 0.77 using a single deep autoencoder approach.

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

PubMed

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

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

Characterization Of Improved Binary Phase-Only Filters In A Real-Time Coherent Optical Correlation System

NASA Astrophysics Data System (ADS)

Flannery, D.; Keller, P.; Cartwright, S.; Loomis, J.

1987-06-01

Attractive correlation system performance potential is possible using magneto-optic spatial light modulators (SLM) to implement binary phase-only reference filters at high rates, provided the correlation performance of such reduced-information-content filters is adequate for the application. In the case studied here, the desired filter impulse response is a rectangular shape, which cannot be achieved with the usual binary phase-only filter formulation. The correlation application problem is described and techniques for synthesizing improved filter impulse response are considered. A compromise solution involves the cascading of a fixed amplitude-only weighting mask with the binary phase-only SLM. Based on simulations presented, this approach provides improved impulse responses and good correlation performance, while retaining the critical feature of real-time variations of the size, shape, and orientation of the rectangle by electronic programming of the phase pattern in the SLM. Simulations indicate that, for at least one very challenging input scene clutter situation, these filters provide higher correlation signal-to-noise than does "ideal" correlation, i.e. using a perfect rectangle filter response.

Neutron-Star Radius from a Population of Binary Neutron Star Mergers.

PubMed

Bose, Sukanta; Chakravarti, Kabir; Rezzolla, Luciano; Sathyaprakash, B S; Takami, Kentaro

2018-01-19

We show how gravitational-wave observations with advanced detectors of tens to several tens of neutron-star binaries can measure the neutron-star radius with an accuracy of several to a few percent, for mass and spatial distributions that are realistic, and with none of the sources located within 100 Mpc. We achieve such an accuracy by combining measurements of the total mass from the inspiral phase with those of the compactness from the postmerger oscillation frequencies. For estimating the measurement errors of these frequencies, we utilize analytical fits to postmerger numerical relativity waveforms in the time domain, obtained here for the first time, for four nuclear-physics equations of state and a couple of values for the mass. We further exploit quasiuniversal relations to derive errors in compactness from those frequencies. Measuring the average radius to well within 10% is possible for a sample of 100 binaries distributed uniformly in volume between 100 and 300 Mpc, so long as the equation of state is not too soft or the binaries are not too heavy. We also give error estimates for the Einstein Telescope.

Objective grading of facial paralysis using Local Binary Patterns in video processing.

PubMed

He, Shu; Soraghan, John J; O'Reilly, Brian F

2008-01-01

This paper presents a novel framework for objective measurement of facial paralysis in biomedial videos. The motion information in the horizontal and vertical directions and the appearance features on the apex frames are extracted based on the Local Binary Patterns (LBP) on the temporal-spatial domain in each facial region. These features are temporally and spatially enhanced by the application of block schemes. A multi-resolution extension of uniform LBP is proposed to efficiently combine the micro-patterns and large-scale patterns into a feature vector, which increases the algorithmic robustness and reduces noise effects while still retaining computational simplicity. The symmetry of facial movements is measured by the Resistor-Average Distance (RAD) between LBP features extracted from the two sides of the face. Support Vector Machine (SVM) is applied to provide quantitative evaluation of facial paralysis based on the House-Brackmann (H-B) Scale. The proposed method is validated by experiments with 197 subject videos, which demonstrates its accuracy and efficiency.

Discovery and characterization of 3000+ main-sequence binaries from APOGEE spectra

NASA Astrophysics Data System (ADS)

El-Badry, Kareem; Ting, Yuan-Sen; Rix, Hans-Walter; Quataert, Eliot; Weisz, Daniel R.; Cargile, Phillip; Conroy, Charlie; Hogg, David W.; Bergemann, Maria; Liu, Chao

2018-05-01

We develop a data-driven spectral model for identifying and characterizing spatially unresolved multiple-star systems and apply it to APOGEE DR13 spectra of main-sequence stars. Binaries and triples are identified as targets whose spectra can be significantly better fit by a superposition of two or three model spectra, drawn from the same isochrone, than any single-star model. From an initial sample of ˜20 000 main-sequence targets, we identify ˜2500 binaries in which both the primary and secondary stars contribute detectably to the spectrum, simultaneously fitting for the velocities and stellar parameters of both components. We additionally identify and fit ˜200 triple systems, as well as ˜700 velocity-variable systems in which the secondary does not contribute detectably to the spectrum. Our model simplifies the process of simultaneously fitting single- or multi-epoch spectra with composite models and does not depend on a velocity offset between the two components of a binary, making it sensitive to traditionally undetectable systems with periods of hundreds or thousands of years. In agreement with conventional expectations, almost all the spectrally identified binaries with measured parallaxes fall above the main sequence in the colour-magnitude diagram. We find excellent agreement between spectrally and dynamically inferred mass ratios for the ˜600 binaries in which a dynamical mass ratio can be measured from multi-epoch radial velocities. We obtain full orbital solutions for 64 systems, including 14 close binaries within hierarchical triples. We make available catalogues of stellar parameters, abundances, mass ratios, and orbital parameters.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

[Multivariate geostatistics and GIS-based approach to study the spatial distribution and sources of heavy metals in agricultural soil in the Pearl River Delta, China].

PubMed

Cai, Li-mei; Ma, Jin; Zhou, Yong-zhang; Huang, Lan-chun; Dou, Lei; Zhang, Cheng-bo; Fu, Shan-ming

2008-12-01

One hundred and eighteen surface soil samples were collected from the Dongguan City, and analyzed for concentration of Cu, Zn, Ni, Cr, Pb, Cd, As, Hg, pH and OM. The spatial distribution and sources of soil heavy metals were studied using multivariate geostatistical methods and GIS technique. The results indicated concentrations of Cu, Zn, Ni, Pb, Cd and Hg were beyond the soil background content in Guangdong province, and especially concentrations of Pb, Cd and Hg were greatly beyond the content. The results of factor analysis group Cu, Zn, Ni, Cr and As in Factor 1, Pb and Hg in Factor 2 and Cd in Factor 3. The spatial maps based on geostatistical analysis show definite association of Factor 1 with the soil parent material, Factor 2 was mainly affected by industries. The spatial distribution of Factor 3 was attributed to anthropogenic influence.

Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride.

PubMed

Katsarov, Plamen; Gergov, Georgi; Alin, Aylin; Pilicheva, Bissera; Al-Degs, Yahya; Simeonov, Vasil; Kassarova, Margarita

2018-03-01

The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms.

Impact of socioeconomic inequalities on geographic disparities in cancer incidence: comparison of methods for spatial disease mapping.

PubMed

Goungounga, Juste Aristide; Gaudart, Jean; Colonna, Marc; Giorgi, Roch

2016-10-12

The reliability of spatial statistics is often put into question because real spatial variations may not be found, especially in heterogeneous areas. Our objective was to compare empirically different cluster detection methods. We assessed their ability to find spatial clusters of cancer cases and evaluated the impact of the socioeconomic status (e.g., the Townsend index) on cancer incidence. Moran's I, the empirical Bayes index (EBI), and Potthoff-Whittinghill test were used to investigate the general clustering. The local cluster detection methods were: i) the spatial oblique decision tree (SpODT); ii) the spatial scan statistic of Kulldorff (SaTScan); and, iii) the hierarchical Bayesian spatial modeling (HBSM) in a univariate and multivariate setting. These methods were used with and without introducing the Townsend index of socioeconomic deprivation known to be related to the distribution of cancer incidence. Incidence data stemmed from the Cancer Registry of Isère and were limited to prostate, lung, colon-rectum, and bladder cancers diagnosed between 1999 and 2007 in men only. The study found a spatial heterogeneity (p < 0.01) and an autocorrelation for prostate (EBI = 0.02; p = 0.001), lung (EBI = 0.01; p = 0.019) and bladder (EBI = 0.007; p = 0.05) cancers. After introduction of the Townsend index, SaTScan failed in finding cancers clusters. This introduction changed the results obtained with the other methods. SpODT identified five spatial classes (p < 0.05): four in the Western and one in the Northern parts of the study area (standardized incidence ratios: 1.68, 1.39, 1.14, 1.12, and 1.16, respectively). In the univariate setting, the Bayesian smoothing method found the same clusters as the two other methods (RR >1.2). The multivariate HBSM found a spatial correlation between lung and bladder cancers (r = 0.6). In spatial analysis of cancer incidence, SpODT and HBSM may be used not only for cluster detection but also for searching for confounding or etiological factors in small areas. Moreover, the multivariate HBSM offers a flexible and meaningful modeling of spatial variations; it shows plausible previously unknown associations between various cancers.

Combined binary collision and continuum mechanics model applied to focused ion beam milling of a silicon membrane

NASA Astrophysics Data System (ADS)

Hobler, Gerhard

2015-06-01

Many experiments indicate the importance of stress and stress relaxation upon ion implantation. In this paper, a model is proposed that is capable of describing ballistic effects as well as stress relaxation by viscous flow. It combines atomistic binary collision simulation with continuum mechanics. The only parameters that enter the continuum model are the bulk modulus and the radiation-induced viscosity. The shear modulus can also be considered but shows only minor effects. A boundary-fitted grid is proposed that is usable both during the binary collision simulation and for the spatial discretization of the force balance equations. As an application, the milling of a slit into an amorphous silicon membrane with a 30 keV focused Ga beam is studied, which demonstrates the relevance of the new model compared to a more heuristic approach used in previous work.

Theory of Metastable State Relaxation in a Gravitational Field for Non-Critical Binary Systems with Non-Conserved Order Parameter

NASA Technical Reports Server (NTRS)

Izmailov, Alexander F.; Myerson, Allan S.

1993-01-01

A new mathematical ansatz is developed for solution of the time-dependent Ginzburg-Landau nonlinear partial differential equation describing metastable state relaxation in binary (solute+solvent) non-critical solutions with non-conserved scalar order parameter in presence of a gravitational field. It has been demonstrated analytically that in such systems metastability initiates heterogeneous solute redistribution which results in the formation of a non-equilibrium singly-periodic spatial solute structure in the new solute-rich phase. The critical radius of nucleation and the induction time in these systems are gravity-dependent. It has also been proved that metastable state relaxation in vertical columns of supersaturated non-critical binary solutions leads to formation of the solute concentration gradient. Analytical expression for this concentration gradient is found and analysed. It is concluded that gravity can initiate phase separation (nucleation or spinodal decomposition).

High efficiency x-ray nanofocusing by the blazed stacking of binary zone plates

NASA Astrophysics Data System (ADS)

Mohacsi, I.; Karvinen, P.; Vartiainen, I.; Diaz, A.; Somogyi, A.; Kewish, C. M.; Mercere, P.; David, C.

2013-09-01

The focusing efficiency of binary Fresnel zone plate lenses is fundamentally limited and higher efficiency requires a multi step lens profile. To overcome the manufacturing problems of high resolution and high efficiency multistep zone plates, we investigate the concept of stacking two different binary zone plates in each other's optical near-field. We use a coarse zone plate with π phase shift and a double density fine zone plate with π/2 phase shift to produce an effective 4- step profile. Using a compact experimental setup with piezo actuators for alignment, we demonstrated 47.1% focusing efficiency at 6.5 keV using a pair of 500 μm diameter and 200 nm smallest zone width. Furthermore, we present a spatially resolved characterization method using multiple diffraction orders to identify manufacturing errors, alignment errors and pattern distortions and their effect on diffraction efficiency.

A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.

PubMed

Schmidt, Christoph; Pester, Britta; Schmid-Hertel, Nicole; Witte, Herbert; Wismüller, Axel; Leistritz, Lutz

2016-01-01

Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.

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

PubMed

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

2009-10-01

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

Shaping Laguerre-Gaussian laser modes with binary gratings using a digital micromirror device.

PubMed

Lerner, Vitaly; Shwa, David; Drori, Yehonathan; Katz, Nadav

2012-12-01

Laguerre-Gaussian (LG) beams are used in many research fields, including microscopy, laser cavity modes, and optical tweezing. We developed a holographic method to generate pure LG modes (amplitude and phase) with a binary amplitude-only digital micromirror device (DMD) as an alternative to the commonly used phase-only spatial light modulator. The advantages of such a DMD include very high frame rates, low cost, and high damage thresholds. We have shown that the propagating shaped beams are self-similar and their phase fronts are of helical shape as demanded. We estimate the purity of the resultant beams to be above 94%.

Generation of atmospheric wavefronts using binary micromirror arrays.

PubMed

Anzuola, Esdras; Belmonte, Aniceto

2016-04-10

To simulate in the laboratory the influence that a turbulent atmosphere has on light beams, we introduce a practical method for generating atmospheric wavefront distortions that considers digital holographic reconstruction using a programmable binary micromirror array. We analyze the efficiency of the approach for different configurations of the micromirror array and experimentally demonstrate the benchtop technique. Though the mirrors on the digital array can only be positioned in one of two states, we show that the holographic technique can be used to devise a wide variety of atmospheric wavefront aberrations in a controllable and predictable way for a fraction of the cost of phase-only spatial light modulators.

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

Suh, In-Saeng; Mathews, Grant J.; Haywood, J. Reese

The spatially conformally flat approximation (CFA) is a viable method to deduce initial conditions for the subsequent evolution of binary neutron stars employing the full Einstein equations. Here in this paper, we analyze the viability of the CFA for the general relativistic hydrodynamic initial conditions of binary neutron stars. We illustrate the stability of the conformally flat condition on the hydrodynamics by numerically evolving ~100 quasicircular orbits. We illustrate the use of this approximation for orbiting neutron stars in the quasicircular orbit approximation to demonstrate the equation of state dependence of these initial conditions and how they might affect themore » emergent gravitational wave frequency as the stars approach the innermost stable circular orbit.« less

LSST Astroinformatics And Astrostatistics: Data-oriented Astronomical Research

NASA Astrophysics Data System (ADS)

Borne, Kirk D.; Stassun, K.; Brunner, R. J.; Djorgovski, S. G.; Graham, M.; Hakkila, J.; Mahabal, A.; Paegert, M.; Pesenson, M.; Ptak, A.; Scargle, J.; Informatics, LSST; Statistics Team

2011-01-01

The LSST Informatics and Statistics Science Collaboration (ISSC) focuses on research and scientific discovery challenges posed by the very large and complex data collection that LSST will generate. Application areas include astroinformatics, machine learning, data mining, astrostatistics, visualization, scientific data semantics, time series analysis, and advanced signal processing. Research problems to be addressed with these methodologies include transient event characterization and classification, rare class discovery, correlation mining, outlier/anomaly/surprise detection, improved estimators (e.g., for photometric redshift or early onset supernova classification), exploration of highly dimensional (multivariate) data catalogs, and more. We present sample science results from these data-oriented approaches to large-data astronomical research. We present results from LSST ISSC team members, including the EB (Eclipsing Binary) Factory, the environmental variations in the fundamental plane of elliptical galaxies, and outlier detection in multivariate catalogs.

The role of middle-class status in payday loan borrowing: a multivariate approach.

PubMed

Lim, Younghee; Bickham, Trey; Broussard, Julia; Dinecola, Cassie M; Gregory, Alethia; Weber, Brittany E

2014-10-01

Payday loans refer to small-dollar, high-interest, short-term loans usually extended to lower-income consumers. Despite much research to the contrary, the payday loan industry asserts that it primarily serves middle-class Americans. This article discusses the authors' investigation of the industry's claim, by analyzing data from a U.S. bankruptcy court serving a Southern district. Results of the multivariate binary logistic regression analysis showed that, controlling for various sociodemographic and economic variables, two middle-class indicators--home-ownership and annual income at or greater than the median income--are associated with a decreased likelihood of using payday loans. The article concludes with a discussion of the implications of the results for social work practice and advocacy in regard to financial capability, particularly asset development, income maintenance, and payday loan regulation.

Binary pseudo-random patterned structures for modulation transfer function calibration and resolution characterization of a full-field transmission soft x-ray microscope

DOE PAGES

Yashchuk, V. V.; Fischer, P. J.; Chan, E. R.; ...

2015-12-09

We present a modulation transfer function (MTF) calibration method based on binary pseudo-random (BPR) one-dimensional sequences and two-dimensional arrays as an effective method for spectral characterization in the spatial frequency domain of a broad variety of metrology instrumentation, including interferometric microscopes, scatterometers, phase shifting Fizeau interferometers, scanning and transmission electron microscopes, and at this time, x-ray microscopes. The inherent power spectral density of BPR gratings and arrays, which has a deterministic white-noise-like character, allows a direct determination of the MTF with a uniform sensitivity over the entire spatial frequency range and field of view of an instrument. We demonstrate themore » MTF calibration and resolution characterization over the full field of a transmission soft x-ray microscope using a BPR multilayer (ML) test sample with 2.8 nm fundamental layer thickness. We show that beyond providing a direct measurement of the microscope's MTF, tests with the BPRML sample can be used to fine tune the instrument's focal distance. Finally, our results confirm the universality of the method that makes it applicable to a large variety of metrology instrumentation with spatial wavelength bandwidths from a few nanometers to hundreds of millimeters.« less

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.

Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process.

PubMed

Ding, Mingtao; He, Lihan; Dunson, David; Carin, Lawrence

2012-12-01

A nonparametric Bayesian model is proposed for segmenting time-evolving multivariate spatial point process data. An inhomogeneous Poisson process is assumed, with a logistic stick-breaking process (LSBP) used to encourage piecewise-constant spatial Poisson intensities. The LSBP explicitly favors spatially contiguous segments, and infers the number of segments based on the observed data. The temporal dynamics of the segmentation and of the Poisson intensities are modeled with exponential correlation in time, implemented in the form of a first-order autoregressive model for uniformly sampled discrete data, and via a Gaussian process with an exponential kernel for general temporal sampling. We consider and compare two different inference techniques: a Markov chain Monte Carlo sampler, which has relatively high computational complexity; and an approximate and efficient variational Bayesian analysis. The model is demonstrated with a simulated example and a real example of space-time crime events in Cincinnati, Ohio, USA.

Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

NASA Astrophysics Data System (ADS)

Gu, Huaying; Liu, Zhixue; Weng, Yingliang

2017-04-01

The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

Sullivan, Thomas R; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its shortcomings, and so further research is needed to identify optimal approaches for relative risk estimation within the multiple imputation framework.

Statistical inferences for data from studies conducted with an aggregated multivariate outcome-dependent sample design.

PubMed

Lu, Tsui-Shan; Longnecker, Matthew P; Zhou, Haibo

2017-03-15

Outcome-dependent sampling (ODS) scheme is a cost-effective sampling scheme where one observes the exposure with a probability that depends on the outcome. The well-known such design is the case-control design for binary response, the case-cohort design for the failure time data, and the general ODS design for a continuous response. While substantial work has been carried out for the univariate response case, statistical inference and design for the ODS with multivariate cases remain under-developed. Motivated by the need in biological studies for taking the advantage of the available responses for subjects in a cluster, we propose a multivariate outcome-dependent sampling (multivariate-ODS) design that is based on a general selection of the continuous responses within a cluster. The proposed inference procedure for the multivariate-ODS design is semiparametric where all the underlying distributions of covariates are modeled nonparametrically using the empirical likelihood methods. We show that the proposed estimator is consistent and developed the asymptotically normality properties. Simulation studies show that the proposed estimator is more efficient than the estimator obtained using only the simple-random-sample portion of the multivariate-ODS or the estimator from a simple random sample with the same sample size. The multivariate-ODS design together with the proposed estimator provides an approach to further improve study efficiency for a given fixed study budget. We illustrate the proposed design and estimator with an analysis of association of polychlorinated biphenyl exposure to hearing loss in children born to the Collaborative Perinatal Study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Identifying Pleiotropic Genes in Genome-Wide Association Studies for Multivariate Phenotypes with Mixed Measurement Scales

PubMed Central

Williams, L. Keoki; Buu, Anne

2017-01-01

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies. PMID:28081206

Short gamma-ray bursts and gravitational-wave observations from eccentric compact binaries

NASA Astrophysics Data System (ADS)

Tan, Wei-Wei; Fan, Xi-Long; Wang, F. Y.

2018-03-01

Mergers of compact binaries, such as binary neutron stars (BNSs), neutron star-black hole binaries (NSBHs) and binary black holes (BBHs), are expected to be the best candidates for sources of gravitational waves (GWs) and the leading theoretical models for short gamma-ray bursts (SGRBs). Based on observations of SGRBs, we can derive the merger rates of these compact binaries and study stochastic GW backgrounds (SGWBs) or the co-detection rates of GWs associated with SGRBs (GW-SGRBs). Before that, however, the most important thing is to derive the GW spectrum from a single GW source. Usually, a GW spectrum from a circular-orbit binary is assumed. However, observations of the large spatial offsets of SGRBs from their host galaxies imply that SGRB progenitors may be formed by dynamical processes and will merge with residual eccentricities (er). The orbital eccentricity has an important effect on GW spectra and therefore on the SGWB and GW-SGRB co-detection rate. Our results show that the power spectra of SGWBs from eccentric compact binaries are greatly suppressed at low frequencies (e.g. f ≲ 1 Hz). In particular, SGWBs from binaries with high residual eccentricities (e.g. er ≳ 0.1 for BNSs) will be hard to detect (above the detection frequency of ˜ 100 Hz). Regarding the co-detection rates of GW-SGRB events, they could be ˜1.4 times higher than the circular case within some particular ranges of er (e.g. 0.01 ≲ er ≲ 0.1 for BBHs), but greatly reduced for high residual eccentricities (e.g. er > 0.1 for BNSs). In general, BBH progenitors produce 200 and 10 times higher GW-SGRB events than BNS and NSBH progenitors, respectively. Therefore, binaries with low residual eccentricities (e.g. 0.001 ≲ er ≲ 0.1) and high total masses will be easier to detect by Advanced LIGO (aLIGO). However, only a small fraction of BBHs can be SGRB progenitors (if they can produce SGRBs), because the predicted GW-SGRB event rate (60˜100 per year) is too high compared with recent observations, unless they merge with high residual eccentricities (e.g. er > 0.7).

The study of combining Latin Hypercube Sampling method and LU decomposition method (LULHS method) for constructing spatial random field

NASA Astrophysics Data System (ADS)

WANG, P. T.

2015-12-01

Groundwater modeling requires to assign hydrogeological properties to every numerical grid. Due to the lack of detailed information and the inherent spatial heterogeneity, geological properties can be treated as random variables. Hydrogeological property is assumed to be a multivariate distribution with spatial correlations. By sampling random numbers from a given statistical distribution and assigning a value to each grid, a random field for modeling can be completed. Therefore, statistics sampling plays an important role in the efficiency of modeling procedure. Latin Hypercube Sampling (LHS) is a stratified random sampling procedure that provides an efficient way to sample variables from their multivariate distributions. This study combines the the stratified random procedure from LHS and the simulation by using LU decomposition to form LULHS. Both conditional and unconditional simulations of LULHS were develpoed. The simulation efficiency and spatial correlation of LULHS are compared to the other three different simulation methods. The results show that for the conditional simulation and unconditional simulation, LULHS method is more efficient in terms of computational effort. Less realizations are required to achieve the required statistical accuracy and spatial correlation.

A High-Dimensional, Multivariate Copula Approach to Modeling Multivariate Agricultural Price Relationships and Tail Dependencies

Treesearch

Xuan Chi; Barry Goodwin

2012-01-01

Spatial and temporal relationships among agricultural prices have been an important topic of applied research for many years. Such research is used to investigate the performance of markets and to examine linkages up and down the marketing chain. This research has empirically evaluated price linkages by using correlation and regression models and, later, linear and...

On the potential for the Partial Triadic Analysis to grasp the spatio-temporal variability of groundwater hydrochemistry

NASA Astrophysics Data System (ADS)

Gourdol, L.; Hissler, C.; Pfister, L.

2012-04-01

The Luxembourg sandstone aquifer is of major relevance for the national supply of drinking water in Luxembourg. The city of Luxembourg (20% of the country's population) gets almost 2/3 of its drinking water from this aquifer. As a consequence, the study of both the groundwater hydrochemistry, as well as its spatial and temporal variations, are considered as of highest priority. Since 2005, a monitoring network has been implemented by the Water Department of Luxembourg City, with a view to a more sustainable management of this strategic water resource. The data collected to date forms a large and complex dataset, describing spatial and temporal variations of many hydrochemical parameters. The data treatment issue is tightly connected to this kind of water monitoring programs and complex databases. Standard multivariate statistical techniques, such as principal components analysis and hierarchical cluster analysis, have been widely used as unbiased methods for extracting meaningful information from groundwater quality data and are now classically used in many hydrogeological studies, in particular to characterize temporal or spatial hydrochemical variations induced by natural and anthropogenic factors. But these classical multivariate methods deal with two-way matrices, usually parameters/sites or parameters/time, while often the dataset resulting from qualitative water monitoring programs should be seen as a datacube parameters/sites/time. Three-way matrices, such as the one we propose here, are difficult to handle and to analyse by classical multivariate statistical tools and thus should be treated with approaches dealing with three-way data structures. One possible analysis approach consists in the use of partial triadic analysis (PTA). The PTA was previously used with success in many ecological studies but never to date in the domain of hydrogeology. Applied to the dataset of the Luxembourg Sandstone aquifer, the PTA appears as a new promising statistical instrument for hydrogeologists, in particular to characterize temporal and spatial hydrochemical variations induced by natural and anthropogenic factors. This new approach for groundwater management offers potential for 1) identifying a common multivariate spatial structure, 2) untapping the different hydrochemical patterns and explaining their controlling factors and 3) analysing the temporal variability of this structure and grasping hydrochemical changes.

Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations

PubMed Central

Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir

2004-01-01

Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586

On extreme events for non-spatial and spatial branching Brownian motions

NASA Astrophysics Data System (ADS)

Avan, Jean; Grosjean, Nicolas; Huillet, Thierry

2015-04-01

We study the impact of having a non-spatial branching mechanism with infinite variance on some parameters (height, width and first hitting time) of an underlying Bienaymé-Galton-Watson branching process. Aiming at providing a comparative study of the spread of an epidemics whose dynamics is given by the modulus of a branching Brownian motion (BBM) we then consider spatial branching processes in dimension d, not necessarily integer. The underlying branching mechanism is either a binary branching model or one presenting infinite variance. In particular we evaluate the chance p(x) of being hit if the epidemics started away at distance x. We compute the large x tail probabilities of this event, both when the branching mechanism is regular and when it exhibits very large fluctuations.

The surface-induced spatial-temporal structures in confined binary alloys

NASA Astrophysics Data System (ADS)

Krasnyuk, Igor B.; Taranets, Roman M.; Chugunova, Marina

2014-12-01

This paper examines surface-induced ordering in confined binary alloys. The hyperbolic initial boundary value problem (IBVP) is used to describe a scenario of spatiotemporal ordering in a disordered phase for concentration of one component of binary alloy and order parameter with non-linear dynamic boundary conditions. This hyperbolic model consists of two coupled second order differential equations for order parameter and concentration. It also takes into account effects of the “memory” on the ordering of atoms and their densities in the alloy. The boundary conditions characterize surface velocities of order parameter and concentration changing which is due to surface (super)cooling on walls confining the binary alloy. It is shown that for large times there are three classes of dynamic non-linear boundary conditions which lead to three different types of attractor’s elements for the IBVP. Namely, the elements of attractor are the limit periodic simple shock waves with fronts of “discontinuities” Γ. If Γ is finite, then the attractor contains spatiotemporal functions of relaxation type. If Γ is infinite and countable then we observe the functions of pre-turbulent type. If Γ is infinite and uncountable then we obtain the functions of turbulent type.

Kinematic Clues to OB Field Star Origins: Radial Velocities, Runaways, and Binaries

NASA Astrophysics Data System (ADS)

Januszewski, Helen; Castro, Norberto; Oey, Sally; Becker, Juliette; Kratter, Kaitlin M.; Mateo, Mario; Simón-Díaz, Sergio; Bjorkman, Jon E.; Bjorkman, Karen; Sigut, Aaron; Smullen, Rachel; M2FS Team

2018-01-01

Field OB stars are a crucial probe of star formation in extreme conditions. Properties of massive stars formed in relative isolation can distinguish between competing star formation theories, while the statistics of runaway stars allow an indirect test of the densest conditions in clusters. To address these questions, we have obtained multi-epoch, spectroscopic observations for a spatially complete sample of 48 OB field stars in the SMC Wing with the IMACS and M2FS multi-object spectrographs at the Magellan Telescopes. The observations span 3-6 epochs per star, with sampling frequency ranging from one day to about one year. From these spectra, we have calculated the radial velocities (RVs) and, in particular, the systemic velocities for binaries. Thus, we present the intrinsic RV distribution largely uncontaminated by binary motions. We estimate the runaway frequency, corresponding to the high velocity stars in our sample, and we also constrain the binary frequency. The binary frequency and fitted orbital parameters also place important constraints on star formation theories, as these properties drive the process of runaway ejection in clusters, and we discuss these properties as derived from our sample. This unique kinematic analysis of a high mass field star population thus provides a new look at the processes governing formation and interaction of stars in environments at extreme densities, from isolation to dense clusters.

Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

NASA Astrophysics Data System (ADS)

Gaitan, S.; ten Veldhuis, J. A. E.

2015-06-01

Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

Electromagnetic behavior of spatial terahertz wave modulators based on reconfigurable micromirror gratings in Littrow configuration.

PubMed

Kappa, Jan; Schmitt, Klemens M; Rahm, Marco

2017-08-21

Efficient, high speed spatial modulators with predictable performance are a key element in any coded aperture terahertz imaging system. For spectroscopy, the modulators must also provide a broad modulation frequency range. In this study, we numerically analyze the electromagnetic behavior of a dynamically reconfigurable spatial terahertz wave modulator based on a micromirror grating in Littrow configuration. We show that such a modulator can modulate terahertz radiation over a wide frequency range from 1.7 THz to beyond 3 THz at a modulation depth of more than 0.6. As a specific example, we numerically simulated coded aperture imaging of an object with binary transmissive properties and successfully reconstructed the image.

Discovery of Low-ionization Envelopes in the Planetary Nebula NGC 5189: Spatially-resolved Diagnostics from HST Observations

NASA Astrophysics Data System (ADS)

Danehkar, Ashkbiz; Karovska, Margarita; Maksym, Walter Peter; Montez, Rodolfo

2018-01-01

The planetary nebula NGC 5189 shows one of the most spectacular morphological structures among planetary nebulae with [WR]-type central stars. Using high-angular resolution HST/WFC3 imaging, we discovered inner, low-ionization structures within a region of 0.3 parsec × 0.2 parsec around the central binary system. We used Hα, [O III], and [S II] emission line images to construct line-ratio diagnostic maps, which allowed us to spatially resolve two distinct low-ionization envelopes within the inner, ionized gaseous environment, extending over a distance of 0.15 pc from the central binary. Both the low-ionization envelopes appear to be expanding along a NE to SW symmetric axis. The SW envelope appears smaller than its NE counterpart. Our diagnostic maps show that highly-ionized gas surrounds these low-ionization envelopes, which also include filamentary and clumpy structures. These envelopes could be a result of a powerful outburst from the central interacting binary, when one of the companions (now a [WR] star) was in its AGB evolutionary stage, with a strong mass-loss generating dense circumstellar shells. Dense material ejected from the progenitor AGB star is likely heated up as it propagates along a symmetric axis into the previously expelled low-density material. Our new diagnostic methodology is a powerful tool for high-angular resolution mapping of low-ionization structures in other planetary nebulae with complex structures possibly caused by past outbursts from their progenitors.

Multiwavelength Study of Powerful New Jet Activity in the Symbiotic System R AQR

NASA Astrophysics Data System (ADS)

Karovska, Margarita

2016-10-01

We propose to carry out coordinated high-spatial resolution Chandra ACIS-S and multiwavelength (UV-Optical) HST/WFC3 observations of R Aqr, a very active symbiotic interacting binary system. Our main goal is to study the physical characteristics of the multi-scale components of the powerful jet; from the vicinity of the central binary (within a few AU) to the jet-circumbinary material interaction region (2500 AU) and beyond, and especially of the recently discovered new component of the inner jet (likely due to recent ejection of material). Our main goal is to gain new insight on early jet formation and propagation, including jet kinematics and precession.

Theory of Metastable State Relaxation for Non-Critical Binary Systems with Non-Conserved Order Parameter

NASA Technical Reports Server (NTRS)

Izmailov, Alexander; Myerson, Allan S.

1993-01-01

A new mathematical ansatz for a solution of the time-dependent Ginzburg-Landau non-linear partial differential equation is developed for non-critical systems such as non-critical binary solutions (solute + solvent) described by the non-conserved scalar order parameter. It is demonstrated that in such systems metastability initiates heterogeneous solute redistribution which results in formation of the non-equilibrium singly-periodic spatial solute structure. It is found how the time-dependent period of this structure evolves in time. In addition, the critical radius r(sub c) for solute embryo of the new solute rich phase together with the metastable state lifetime t(sub c) are determined analytically and analyzed.

Differential Binary Encoding Method for Calibrating Image Sensors Based on IOFBs

PubMed Central

Fernández, Pedro R.; Lázaro-Galilea, José Luis; Gardel, Alfredo; Espinosa, Felipe; Bravo, Ignacio; Cano, Ángel

2012-01-01

Image transmission using incoherent optical fiber bundles (IOFBs) requires prior calibration to obtain the spatial in-out fiber correspondence necessary to reconstruct the image captured by the pseudo-sensor. This information is recorded in a Look-Up Table called the Reconstruction Table (RT), used later for reordering the fiber positions and reconstructing the original image. This paper presents a very fast method based on image-scanning using spaces encoded by a weighted binary code to obtain the in-out correspondence. The results demonstrate that this technique yields a remarkable reduction in processing time and the image reconstruction quality is very good compared to previous techniques based on spot or line scanning, for example. PMID:22666023

Searching for Binary Systems Among Nearby Dwarfs Based on Pulkovo Observations and SDSS Data

NASA Astrophysics Data System (ADS)

Khovrichev, M. Yu.; Apetyan, A. A.; Roshchina, E. A.; Izmailov, I. S.; Bikulova, D. A.; Ershova, A. P.; Balyaev, I. A.; Kulikova, A. M.; Petyur, V. V.; Shumilov, A. A.; Os'kina, K. I.; Maksimova, L. A.

2018-02-01

Our goal is to find previously unknown binary systems among low-mass dwarfs in the solar neighborhood and to test the search technique. The basic ideas are to reveal the images of stars with significant ellipticities and/or asymmetries compared to the background stars on CCD frames and to subsequently determine the spatial parameters of the binary system and the magnitude difference between its components. For its realization we have developed a method based on an image shapelet decomposition. All of the comparatively faint stars with large proper motions ( V >13 m , μ > 300 mas yr-1) for which the "duplicate source" flag in the Gaia DR1 catalogue is equal to one have been included in the list of objects for our study. As a result, we have selected 702 stars. To verify our results, we have performed additional observations of 65 stars from this list with the Pulkovo 1-m "Saturn" telescope (2016-2017). We have revealed a total of 138 binary candidates (nine of them from the "Saturn" telescope and SDSS data). Six program stars are known binaries. The images of the primaries of the comparatively wide pairs WDS 14519+5147, WDS 11371+6022, and WDS 15404+2500 are shown to be resolved into components; therefore, we can talk about the detection of triple systems. The angular separation ρ, position angle, and component magnitude difference Δ m have been estimated for almost all of the revealed binary systems. For most stars 1.5'' < ρ < 2.5'', while Δ m <1.5m.

Handling Different Spatial Resolutions in Image Fusion by Multivariate Curve Resolution-Alternating Least Squares for Incomplete Image Multisets.

PubMed

Piqueras, Sara; Bedia, Carmen; Beleites, Claudia; Krafft, Christoph; Popp, Jürgen; Maeder, Marcel; Tauler, Romà; de Juan, Anna

2018-06-05

Data fusion of different imaging techniques allows a comprehensive description of chemical and biological systems. Yet, joining images acquired with different spectroscopic platforms is complex because of the different sample orientation and image spatial resolution. Whereas matching sample orientation is often solved by performing suitable affine transformations of rotation, translation, and scaling among images, the main difficulty in image fusion is preserving the spatial detail of the highest spatial resolution image during multitechnique image analysis. In this work, a special variant of the unmixing algorithm Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) for incomplete multisets is proposed to provide a solution for this kind of problem. This algorithm allows analyzing simultaneously images collected with different spectroscopic platforms without losing spatial resolution and ensuring spatial coherence among the images treated. The incomplete multiset structure concatenates images of the two platforms at the lowest spatial resolution with the image acquired with the highest spatial resolution. As a result, the constituents of the sample analyzed are defined by a single set of distribution maps, common to all platforms used and with the highest spatial resolution, and their related extended spectral signatures, covering the signals provided by each of the fused techniques. We demonstrate the potential of the new variant of MCR-ALS for multitechnique analysis on three case studies: (i) a model example of MIR and Raman images of pharmaceutical mixture, (ii) FT-IR and Raman images of palatine tonsil tissue, and (iii) mass spectrometry and Raman images of bean tissue.

Quantitative analysis of facial paralysis using local binary patterns in biomedical videos.

PubMed

He, Shu; Soraghan, John J; O'Reilly, Brian F; Xing, Dongshan

2009-07-01

Facial paralysis is the loss of voluntary muscle movement of one side of the face. A quantitative, objective, and reliable assessment system would be an invaluable tool for clinicians treating patients with this condition. This paper presents a novel framework for objective measurement of facial paralysis. The motion information in the horizontal and vertical directions and the appearance features on the apex frames are extracted based on the local binary patterns (LBPs) on the temporal-spatial domain in each facial region. These features are temporally and spatially enhanced by the application of novel block processing schemes. A multiresolution extension of uniform LBP is proposed to efficiently combine the micropatterns and large-scale patterns into a feature vector. The symmetry of facial movements is measured by the resistor-average distance (RAD) between LBP features extracted from the two sides of the face. Support vector machine is applied to provide quantitative evaluation of facial paralysis based on the House-Brackmann (H-B) scale. The proposed method is validated by experiments with 197 subject videos, which demonstrates its accuracy and efficiency.

Population density estimated from locations of individuals on a passive detector array

USGS Publications Warehouse

Efford, Murray G.; Dawson, Deanna K.; Borchers, David L.

2009-01-01

The density of a closed population of animals occupying stable home ranges may be estimated from detections of individuals on an array of detectors, using newly developed methods for spatially explicit capture–recapture. Likelihood-based methods provide estimates for data from multi-catch traps or from devices that record presence without restricting animal movement ("proximity" detectors such as camera traps and hair snags). As originally proposed, these methods require multiple sampling intervals. We show that equally precise and unbiased estimates may be obtained from a single sampling interval, using only the spatial pattern of detections. This considerably extends the range of possible applications, and we illustrate the potential by estimating density from simulated detections of bird vocalizations on a microphone array. Acoustic detection can be defined as occurring when received signal strength exceeds a threshold. We suggest detection models for binary acoustic data, and for continuous data comprising measurements of all signals above the threshold. While binary data are often sufficient for density estimation, modeling signal strength improves precision when the microphone array is small.

Salience from the decision perspective: You know where it is before you know it is there.

PubMed

Zehetleitner, Michael; Müller, Hermann J

2010-12-31

In visual search for feature contrast ("odd-one-out") singletons, identical manipulations of salience, whether by varying target-distractor similarity or dimensional redundancy of target definition, had smaller effects on reaction times (RTs) for binary localization decisions than for yes/no detection decisions. According to formal models of binary decisions, identical differences in drift rates would yield larger RT differences for slow than for fast decisions. From this principle and the present findings, it follows that decisions on the presence of feature contrast singletons are slower than decisions on their location. This is at variance with two classes of standard models of visual search and object recognition that assume a serial cascade of first detection, then localization and identification of a target object, but also inconsistent with models assuming that as soon as a target is detected all its properties, spatial as well as non-spatial (e.g., its category), are available immediately. As an alternative, we propose a model of detection and localization tasks based on random walk processes, which can account for the present findings.

Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach

Treesearch

Michael S. Balshi; A. David McGuire; Paul Duffy; Mike Flannigan; John Walsh; Jerry Melillo

2009-01-01

We developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5o (latitude x longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was...

Modelling household finances: A Bayesian approach to a multivariate two-part model

PubMed Central

Brown, Sarah; Ghosh, Pulak; Su, Li; Taylor, Karl

2016-01-01

We contribute to the empirical literature on household finances by introducing a Bayesian multivariate two-part model, which has been developed to further our understanding of household finances. Our flexible approach allows for the potential interdependence between the holding of assets and liabilities at the household level and also encompasses a two-part process to allow for differences in the influences on asset or liability holding and on the respective amounts held. Furthermore, the framework is dynamic in order to allow for persistence in household finances over time. Our findings endorse the joint modelling approach and provide evidence supporting the importance of dynamics. In addition, we find that certain independent variables exert different influences on the binary and continuous parts of the model thereby highlighting the flexibility of our framework and revealing a detailed picture of the nature of household finances. PMID:27212801

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

Multivariate spatial analysis of a heavy rain event in a densely populated delta city

NASA Astrophysics Data System (ADS)

Gaitan, Santiago; ten Veldhuis, Marie-claire; Bruni, Guenda; van de Giesen, Nick

2014-05-01

Delta cities account for half of the world's population and host key infrastructure and services for the global economic growth. Due to the characteristic geography of delta areas, these cities face high vulnerability to extreme weather and pluvial flooding risks, that are expected to increase as climate change drives heavier rain events. Besides, delta cities are subjected to fast urban densification processes that progressively make them more vulnerable to pluvial flooding. Delta cities need to be adapted to better cope with this threat. The mechanism leading to damage after heavy rains is not completely understood. For instance, current research has shown that rain intensities and volumes can only partially explain the occurrence and localization of rain-related insurance claims (Spekkers et al., 2013). The goal of this paper is to provide further insights into spatial characteristics of the urban environment that can significantly be linked to pluvial-related flooding impacts. To that end, a study-case has been selected: on October 12 to 14 2013, a heavy rain event triggered pluvial floods in Rotterdam, a densely populated city which is undergoing multiple climate adaptation efforts and is located in the Meuse river Delta. While the average yearly precipitation in this city is around 800 mm, local rain gauge measurements ranged from aprox. 60 to 130 mm just during these three days. More than 600 citizens' telephonic complaints reported impacts related to rainfall. The registry of those complaints, which comprises around 300 calls made to the municipality and another 300 to the fire brigade, was made available for research. Other accessible information about this city includes a series of rainfall measurements with up to 1 min time-step at 7 different locations around the city, ground-based radar rainfall data (1 Km^2 spatial resolution and 5 min time-step), a digital elevation model (50 cm of horizontal resolution), a model of overland-flow paths, cadastral maps describing individual location and types of buildings, and maps on categorical socioeconomic statistics (1 Ha of spatial resolution). On the basis of the quality and availability of the mentioned information, spatial and temporal units of analysis will be discussed and defined. Aggregation of single occurrences for binary variables will be performed, while simple interpolations or averages will be used in case of continuous or categorical data. To determine spatial clustering within each variable, Nearest Neighbor Distance and Spatial Autocorrelation tests will be carried out. When appropriate, the Getis-Ord Gi* test will be used to identify single variable clusters. Finally, with the purpose of inferring possible associations between the available spatially distributed variables, a Mantel test will be applied to variables with a probed non-random spatial pattern. The results of this paper will allow to determine if the environmental characteristics described by the available data can provide additional explanation of the variability of rain-related damage in a delta city which is willing to become climate-proof.

New observations and new models of spin-orbit coupling in binary asteroids

NASA Astrophysics Data System (ADS)

Margot, Jean-Luc; Naidu, Shantanu

2015-08-01

The YORP-induced rotational fission hypothesis is the leading candidate for explaining the formation of binaries, triples, and pairs among small (<20 km) asteroids (e.g., Margot et al, Asteroids IV, subm., 2015). Various evolutionary paths following rotational fission have been suggested, but many important questions remain about the evolutionary mechanisms and timescales. We test hypotheses about the evolution of binary asteroids by obtaining precise descriptions of the orbits and components of binary systems with radar and by examining the system dynamics with detailed numerical simulations. Predictions for component spin states and orbital precession rates can then be compared to observables in our data sets or in other data sets to elucidate the states of various systems and their likely evolutionary paths.Accurate simulations require knowledge of the masses, shapes, and spin states of individual binary components. Because radar observations can provide exquisite data sets spanning days with spatial resolutions at the decameter level, we can invert for the component shapes and measure spin states. We can also solve for the mutual orbit by fitting the observed separations between components. In addition, the superb (10e-7--10e-8) fractional uncertainties in range allow us to measure the reflex motions directly, allowing masses of individual components to be determined.We use recently published observations of the binary 2000 DP107 (Naidu et al. AJ, subm., 2015) and that of other systems to simulate the dynamics of components in well-characterized binary systems (Naidu and Margot, AJ 149, 80, 2015). We model the coupled spin and orbital motions of two rigid, ellipsoidal bodies under the influence of their mutual gravitational potential. We use surface of section plots to map the possible spin configurations of the satellites. For asynchronous satellites, the analysis reveals large regions of phase space where the spin state of the satellite is chaotic. The presence of chaotic regions may substantially increase spin synchronization timescales, delay BYORP-type evolution, extend the lifetime of binaries, and explain the observed fraction of asynchronous binaries.

A mixed model framework for teratology studies.

PubMed

Braeken, Johan; Tuerlinckx, Francis

2009-10-01

A mixed model framework is presented to model the characteristic multivariate binary anomaly data as provided in some teratology studies. The key features of the model are the incorporation of covariate effects, a flexible random effects distribution by means of a finite mixture, and the application of copula functions to better account for the relation structure of the anomalies. The framework is motivated by data of the Boston Anticonvulsant Teratogenesis study and offers an integrated approach to investigate substantive questions, concerning general and anomaly-specific exposure effects of covariates, interrelations between anomalies, and objective diagnostic measurement.

Optimization techniques for integrating spatial data

USGS Publications Warehouse

Herzfeld, U.C.; Merriam, D.F.

1995-01-01

Two optimization techniques ta predict a spatial variable from any number of related spatial variables are presented. The applicability of the two different methods for petroleum-resource assessment is tested in a mature oil province of the Midcontinent (USA). The information on petroleum productivity, usually not directly accessible, is related indirectly to geological, geophysical, petrographical, and other observable data. This paper presents two approaches based on construction of a multivariate spatial model from the available data to determine a relationship for prediction. In the first approach, the variables are combined into a spatial model by an algebraic map-comparison/integration technique. Optimal weights for the map comparison function are determined by the Nelder-Mead downhill simplex algorithm in multidimensions. Geologic knowledge is necessary to provide a first guess of weights to start the automatization, because the solution is not unique. In the second approach, active set optimization for linear prediction of the target under positivity constraints is applied. Here, the procedure seems to select one variable from each data type (structure, isopachous, and petrophysical) eliminating data redundancy. Automating the determination of optimum combinations of different variables by applying optimization techniques is a valuable extension of the algebraic map-comparison/integration approach to analyzing spatial data. Because of the capability of handling multivariate data sets and partial retention of geographical information, the approaches can be useful in mineral-resource exploration. ?? 1995 International Association for Mathematical Geology.

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

PubMed

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.

Optical implementation of the synthetic discriminant function

NASA Astrophysics Data System (ADS)

Butler, S.; Riggins, J.

1984-10-01

Much attention is focused on the use of coherent optical pattern recognition (OPR) using matched spatial filters for robotics and intelligent systems. The OPR problem consists of three aspects -- information input, information processing, and information output. This paper discusses the information processing aspect which consists of choosing a filter to provide robust correlation with high efficiency. The filter should ideally be invariant to image shift, rotation and scale, provide a reasonable signal-to-noise (S/N) ratio and allow high throughput efficiency. The physical implementation of a spatial matched filter involves many choices. These include the use of conventional holograms or computer-generated holograms (CGH) and utilizing absorption or phase materials. Conventional holograms inherently modify the reference image by non-uniform emphasis of spatial frequencies. Proper use of film nonlinearity provides improved filter performance by emphasizing frequency ranges crucial to target discrimination. In the case of a CGH, the emphasis of the reference magnitude and phase can be controlled independently of the continuous tone or binary writing processes. This paper describes computer simulation and optical implementation of a geometrical shape and a Synthetic Discriminant Function (SDF) matched filter. The authors chose the binary Allebach-Keegan (AK) CGH algorithm to produce actual filters. The performances of these filters were measured to verify the simulation results. This paper provides a brief summary of the matched filter theory, the SDF, CGH algorithms, Phase-Only-Filtering, simulation procedures, and results.

The initial value problem as it relates to numerical relativity.

PubMed

Tichy, Wolfgang

2017-02-01

Spacetime is foliated by spatial hypersurfaces in the 3+1 split of general relativity. The initial value problem then consists of specifying initial data for all fields on one such a spatial hypersurface, such that the subsequent evolution forward in time is fully determined. On each hypersurface the 3-metric and extrinsic curvature describe the geometry. Together with matter fields such as fluid velocity, energy density and rest mass density, the 3-metric and extrinsic curvature then constitute the initial data. There is a lot of freedom in choosing such initial data. This freedom corresponds to the physical state of the system at the initial time. At the same time the initial data have to satisfy the Hamiltonian and momentum constraint equations of general relativity and can thus not be chosen completely freely. We discuss the conformal transverse traceless and conformal thin sandwich decompositions that are commonly used in the construction of constraint satisfying initial data. These decompositions allow us to specify certain free data that describe the physical nature of the system. The remaining metric fields are then determined by solving elliptic equations derived from the constraint equations. We describe initial data for single black holes and single neutron stars, and how we can use conformal decompositions to construct initial data for binaries made up of black holes or neutron stars. Orbiting binaries will emit gravitational radiation and thus lose energy. Since the emitted radiation tends to circularize the orbits over time, one can thus expect that the objects in a typical binary move on almost circular orbits with slowly shrinking radii. This leads us to the concept of quasi-equilibrium, which essentially assumes that time derivatives are negligible in corotating coordinates for binaries on almost circular orbits. We review how quasi-equilibrium assumptions can be used to make physically well motivated approximations that simplify the elliptic equations we have to solve.

The initial value problem as it relates to numerical relativity

NASA Astrophysics Data System (ADS)

Tichy, Wolfgang

2017-02-01

Spacetime is foliated by spatial hypersurfaces in the 3+1 split of general relativity. The initial value problem then consists of specifying initial data for all fields on one such a spatial hypersurface, such that the subsequent evolution forward in time is fully determined. On each hypersurface the 3-metric and extrinsic curvature describe the geometry. Together with matter fields such as fluid velocity, energy density and rest mass density, the 3-metric and extrinsic curvature then constitute the initial data. There is a lot of freedom in choosing such initial data. This freedom corresponds to the physical state of the system at the initial time. At the same time the initial data have to satisfy the Hamiltonian and momentum constraint equations of general relativity and can thus not be chosen completely freely. We discuss the conformal transverse traceless and conformal thin sandwich decompositions that are commonly used in the construction of constraint satisfying initial data. These decompositions allow us to specify certain free data that describe the physical nature of the system. The remaining metric fields are then determined by solving elliptic equations derived from the constraint equations. We describe initial data for single black holes and single neutron stars, and how we can use conformal decompositions to construct initial data for binaries made up of black holes or neutron stars. Orbiting binaries will emit gravitational radiation and thus lose energy. Since the emitted radiation tends to circularize the orbits over time, one can thus expect that the objects in a typical binary move on almost circular orbits with slowly shrinking radii. This leads us to the concept of quasi-equilibrium, which essentially assumes that time derivatives are negligible in corotating coordinates for binaries on almost circular orbits. We review how quasi-equilibrium assumptions can be used to make physically well motivated approximations that simplify the elliptic equations we have to solve.

Functional inverted Wishart for Bayesian multivariate spatial modeling with application to regional climatology model data.

PubMed

Duan, L L; Szczesniak, R D; Wang, X

2017-11-01

Modern environmental and climatological studies produce multiple outcomes at high spatial resolutions. Multivariate spatial modeling is an established means to quantify cross-correlation among outcomes. However, existing models typically suffer from poor computational efficiency and lack the flexibility to simultaneously estimate auto- and cross-covariance structures. In this article, we undertake a novel construction of covariance by utilizing spectral convolution and by imposing an inverted Wishart prior on the cross-correlation structure. The cross-correlation structure with this functional inverted Wishart prior flexibly accommodates not only positive but also weak or negative associations among outcomes while preserving spatial resolution. Furthermore, the proposed model is computationally efficient and produces easily interpretable results, including the individual autocovariances and full cross-correlation matrices, as well as a partial cross-correlation matrix reflecting the outcome correlation after excluding the effects caused by spatial convolution. The model is examined using simulated data sets under different scenarios. It is also applied to the data from the North American Regional Climate Change Assessment Program, examining long-term associations between surface outcomes for air temperature, pressure, humidity, and radiation, on the land area of the North American West Coast. Results and predictive performance are compared with findings from approaches using convolution only or coregionalization.

Functional inverted Wishart for Bayesian multivariate spatial modeling with application to regional climatology model data

PubMed Central

Duan, L. L.; Szczesniak, R. D.; Wang, X.

2018-01-01

Modern environmental and climatological studies produce multiple outcomes at high spatial resolutions. Multivariate spatial modeling is an established means to quantify cross-correlation among outcomes. However, existing models typically suffer from poor computational efficiency and lack the flexibility to simultaneously estimate auto- and cross-covariance structures. In this article, we undertake a novel construction of covariance by utilizing spectral convolution and by imposing an inverted Wishart prior on the cross-correlation structure. The cross-correlation structure with this functional inverted Wishart prior flexibly accommodates not only positive but also weak or negative associations among outcomes while preserving spatial resolution. Furthermore, the proposed model is computationally efficient and produces easily interpretable results, including the individual autocovariances and full cross-correlation matrices, as well as a partial cross-correlation matrix reflecting the outcome correlation after excluding the effects caused by spatial convolution. The model is examined using simulated data sets under different scenarios. It is also applied to the data from the North American Regional Climate Change Assessment Program, examining long-term associations between surface outcomes for air temperature, pressure, humidity, and radiation, on the land area of the North American West Coast. Results and predictive performance are compared with findings from approaches using convolution only or coregionalization. PMID:29576735

Multicollinearity in spatial genetics: separating the wheat from the chaff using commonality analyses.

PubMed

Prunier, J G; Colyn, M; Legendre, X; Nimon, K F; Flamand, M C

2015-01-01

Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent complexity of genetic variation in wildlife species and are the object of many methodological developments. However, multicollinearity among explanatory variables is a systemic issue in multivariate regression analyses and is likely to cause serious difficulties in properly interpreting results of direct gradient analyses, with the risk of erroneous conclusions, misdirected research and inefficient or counterproductive conservation measures. Using simulated data sets along with linear and logistic regressions on distance matrices, we illustrate how commonality analysis (CA), a detailed variance-partitioning procedure that was recently introduced in the field of ecology, can be used to deal with nonindependence among spatial predictors. By decomposing model fit indices into unique and common (or shared) variance components, CA allows identifying the location and magnitude of multicollinearity, revealing spurious correlations and thus thoroughly improving the interpretation of multivariate regressions. Despite a few inherent limitations, especially in the case of resistance model optimization, this review highlights the great potential of CA to account for complex multicollinearity patterns in spatial genetics and identifies future applications and lines of research. We strongly urge spatial geneticists to systematically investigate commonalities when performing direct gradient analyses. © 2014 John Wiley & Sons Ltd.

A Multivariate Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes

DOE PAGES

Kaufeld, Kimberly Ann; Fuentes, Montse; Reich, Brian J.; ...

2017-09-11

Evidence suggests that exposure to elevated concentrations of air pollution during pregnancy is associated with increased risks of birth defects and other adverse birth outcomes. While current regulations put limits on total PM2.5 concentrations, there are many speciated pollutants within this size class that likely have distinct effects on perinatal health. However, due to correlations between these speciated pollutants, it can be difficult to decipher their effects in a model for birth outcomes. To combat this difficulty, we develop a multivariate spatio-temporal Bayesian model for speciated particulate matter using dynamic spatial factors. These spatial factors can then be interpolated tomore » the pregnant women’s homes to be used to model birth defects. The birth defect model allows the impact of pollutants to vary across different weeks of the pregnancy in order to identify susceptible periods. Here, the proposed methodology is illustrated using pollutant monitoring data from the Environmental Protection Agency and birth records from the National Birth Defect Prevention Study.« less

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

DOE PAGES

Belianinov, Alex; Panchapakesan, G.; Lin, Wenzhi; ...

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 signaturemore » 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.« less

A Multivariate Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes

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

Kaufeld, Kimberly Ann; Fuentes, Montse; Reich, Brian J.

Evidence suggests that exposure to elevated concentrations of air pollution during pregnancy is associated with increased risks of birth defects and other adverse birth outcomes. While current regulations put limits on total PM2.5 concentrations, there are many speciated pollutants within this size class that likely have distinct effects on perinatal health. However, due to correlations between these speciated pollutants, it can be difficult to decipher their effects in a model for birth outcomes. To combat this difficulty, we develop a multivariate spatio-temporal Bayesian model for speciated particulate matter using dynamic spatial factors. These spatial factors can then be interpolated tomore » the pregnant women’s homes to be used to model birth defects. The birth defect model allows the impact of pollutants to vary across different weeks of the pregnancy in order to identify susceptible periods. Here, the proposed methodology is illustrated using pollutant monitoring data from the Environmental Protection Agency and birth records from the National Birth Defect Prevention Study.« less

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

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

Belianinov, Alex, E-mail: belianinova@ornl.gov; Ganesh, Panchapakesan; Lin, Wenzhi

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe{sub 0.55}Se{sub 0.45} (T{sub c} = 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 FeTe{sub 1−x}Se{sub x} structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified bymore » 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.« less

Note: Laser beam scanning using a ferroelectric liquid crystal spatial light modulator

NASA Astrophysics Data System (ADS)

Das, Abhijit; Boruah, Bosanta R.

2014-04-01

In this work we describe laser beam scanning using a ferroelectric liquid crystal spatial light modulator. Commercially available ferroelectric liquid crystal spatial light modulators are capable of displaying 85 colored images in 1 s using a time dithering technique. Each colored image, in fact, comprises 24 single bit (black and white) images displayed sequentially. We have used each single bit image to write a binary phase hologram. For a collimated laser beam incident on the hologram, one of the diffracted beams can be made to travel along a user defined direction. We have constructed a beam scanner employing the above arrangement and demonstrated its use to scan a single laser beam in a laser scanning optical sectioning microscope setup.

Determination of thiamine HCl and pyridoxine HCl in pharmaceutical preparations using UV-visible spectrophotometry and genetic algorithm based multivariate calibration methods.

PubMed

Ozdemir, Durmus; Dinc, Erdal

2004-07-01

Simultaneous determination of binary mixtures pyridoxine hydrochloride and thiamine hydrochloride in a vitamin combination using UV-visible spectrophotometry and classical least squares (CLS) and three newly developed genetic algorithm (GA) based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The sample data set contains the UV-visible spectra of 30 synthetic mixtures (8 to 40 microg/ml) of these vitamins and 10 tablets containing 250 mg from each vitamin. The spectra cover the range from 200 to 330 nm in 0.1 nm intervals. Several calibration models were built with the four methods for the two components. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) for the synthetic data were in the range of <0.01 and 0.43 microg/ml for all the four methods. The SEP values for the tablets were in the range of 2.91 and 11.51 mg/tablets. A comparison of genetic algorithm selected wavelengths for each component using GR method was also included.

Requiring collaboration: Hippocampal-prefrontal networks needed in spatial working memory and ageing. A multivariate analysis approach.

PubMed

Zancada-Menendez, C; Alvarez-Suarez, P; Sampedro-Piquero, P; Cuesta, M; Begega, A

2017-04-01

Ageing is characterized by a decline in the processes of retention and storage of spatial information. We have examined the behavioural performance of adult rats (3months old) and aged rats (18months old) in a spatial complex task (delayed match to sample). The spatial task was performed in the Morris water maze and consisted of three sessions per day over a period of three consecutive days. Each session consisted of two trials (one sample and retention) and inter-session intervals of 5min. Behavioural results showed that the spatial task was difficult for middle aged group. This worse execution could be associated with impairments of processing speed and spatial information retention. We examined the changes in the neuronal metabolic activity of different brain regions through cytochrome C oxidase histochemistry. Then, we performed MANOVA and Discriminant Function Analyses to determine the functional profile of the brain networks that are involved in the spatial learning of the adult and middle-aged groups. This multivariate analysis showed two principal functional networks that necessarily participate in this spatial learning. The first network was composed of the supramammillary nucleus, medial mammillary nucleus, CA3, and CA1. The second one included the anterior cingulate, prelimbic, and infralimbic areas of the prefrontal cortex, dentate gyrus, and amygdala complex (basolateral l and central subregions). There was a reduction in the hippocampal-supramammilar network in both learning groups, whilst there was an overactivation in the executive network, especially in the aged group. This response could be due to a higher requirement of the executive control in a complex spatial memory task in older animals. Copyright © 2017 Elsevier Inc. All rights reserved.

X-ray Binaries and the Galaxy Structure in Hard X-rays

NASA Astrophysics Data System (ADS)

Lutovinov, Alexander

The Galaxy structure in the hard X-ray energy band (¿20 keV) was studied using data of the INTEGRAL observatory. A deep and nearly uniform coverage of the galactic plane allowed to increase significantly the sensitivity of the survey and discover several dozens new galac-tic sources. The follow-up observations with XMM-Newton and CHANDRA observatories in X-rays and ground-based telescopes in optical and infrared wavebands gave us a possibility to determine optical counterparts and distances for number of new and already known faint sources. That, in turn, allowed us to build the spatial distribution of different classes of galactic X-ray binaries and obtain preliminary results of the structure of the further part of the Galaxy.

Face verification system for Android mobile devices using histogram based features

NASA Astrophysics Data System (ADS)

Sato, Sho; Kobayashi, Kazuhiro; Chen, Qiu

2016-07-01

This paper proposes a face verification system that runs on Android mobile devices. In this system, facial image is captured by a built-in camera on the Android device firstly, and then face detection is implemented using Haar-like features and AdaBoost learning algorithm. The proposed system verify the detected face using histogram based features, which are generated by binary Vector Quantization (VQ) histogram using DCT coefficients in low frequency domains, as well as Improved Local Binary Pattern (Improved LBP) histogram in spatial domain. Verification results with different type of histogram based features are first obtained separately and then combined by weighted averaging. We evaluate our proposed algorithm by using publicly available ORL database and facial images captured by an Android tablet.

On the Convection of a Binary Mixture in a Horizontal Layer Under High-frequency Vibrations

NASA Astrophysics Data System (ADS)

Smorodin, B. L.; Ishutov, S. M.; Myznikova, B. I.

2018-02-01

The convective instability and non-linear flows are considered in a horizontal, binary-mixture layer with negative Soret coupling, subjected to the high-frequency vibration whose axis is directed at an arbitrary angle to the layer boundaries. The limiting case of long-wave disturbances is studied using the perturbation method. The influence of the intensity and direction of vibration on the spatially-periodic traveling wave solution is analyzed. It is shown that the shift in the Rayleigh number range, in which the traveling wave regime exists, toward higher values is a response to a horizontal-to-vertical transition in the vibration axis orientation. The characteristics of amplitude- and phase-modulated traveling waves are obtained and discussed.

Edge-SIFT: discriminative binary descriptor for scalable partial-duplicate mobile search.

PubMed

Zhang, Shiliang; Tian, Qi; Lu, Ke; Huang, Qingming; Gao, Wen

2013-07-01

As the basis of large-scale partial duplicate visual search on mobile devices, image local descriptor is expected to be discriminative, efficient, and compact. Our study shows that the popularly used histogram-based descriptors, such as scale invariant feature transform (SIFT) are not optimal for this task. This is mainly because histogram representation is relatively expensive to compute on mobile platforms and loses significant spatial clues, which are important for improving discriminative power and matching near-duplicate image patches. To address these issues, we propose to extract a novel binary local descriptor named Edge-SIFT from the binary edge maps of scale- and orientation-normalized image patches. By preserving both locations and orientations of edges and compressing the sparse binary edge maps with a boosting strategy, the final Edge-SIFT shows strong discriminative power with compact representation. Furthermore, we propose a fast similarity measurement and an indexing framework with flexible online verification. Hence, the Edge-SIFT allows an accurate and efficient image search and is ideal for computation sensitive scenarios such as a mobile image search. Experiments on a large-scale dataset manifest that the Edge-SIFT shows superior retrieval accuracy to Oriented BRIEF (ORB) and is superior to SIFT in the aspects of retrieval precision, efficiency, compactness, and transmission cost.

Innocent Bystanders and Smoking Guns: Dwarf Carbon Stars

NASA Astrophysics Data System (ADS)

Green, Paul J.

2014-01-01

As far as we know, most carbon throughout the Universe is created and dispersed by AGB stars. So it was at first surprising to find that the carbon stars most prevalent in the Galaxy are in fact dwarfs. We suspect that dC stars are most likely innocent bystanders in post-mass transfer binaries, and may be predominantly metal-poor. Among 1200 C stars found in the SDSS (Green 2013), we confirm 724 dCs, of which a dozen are DA/dC stars in composite spectrum binaries, quadrupling the total sample of these "smoking guns" for AGB binary mass transfer. The dCs likely span absolute magnitudes M_i from about 6.5 to 10.5. G-type dC stars with weak CN and relatively blue colors are probably the most massive dCs still cool enough to show C_2 bands. Eleven very red C stars with strong red CN bands appear to be N-type AGB stars at large Galactocentric distances, one likely a new discovery in the dIrr galaxy Le A. Two such stars within 30arcmin of each other may trace a previously unidentified dwarf galaxy or tidal stream at ~40 kpc. We describe follow-up projects to study the spatial, kinematic, and binary properties of these C-enriched dwarfs.

Analyte species and concentration identification using differentially functionalized microcantilever arrays and artificial neural networks

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

Senesac, Larry R; Datskos, Panos G; Sepaniak, Michael J

2006-01-01

In the present work, we have performed analyte species and concentration identification using an array of ten differentially functionalized microcantilevers coupled with a back-propagation artificial neural network pattern recognition algorithm. The array consists of ten nanostructured silicon microcantilevers functionalized by polymeric and gas chromatography phases and macrocyclic receptors as spatially dense, differentially responding sensing layers for identification and quantitation of individual analyte(s) and their binary mixtures. The array response (i.e. cantilever bending) to analyte vapor was measured by an optical readout scheme and the responses were recorded for a selection of individual analytes as well as several binary mixtures. Anmore » artificial neural network (ANN) was designed and trained to recognize not only the individual analytes and binary mixtures, but also to determine the concentration of individual components in a mixture. To the best of our knowledge, ANNs have not been applied to microcantilever array responses previously to determine concentrations of individual analytes. The trained ANN correctly identified the eleven test analyte(s) as individual components, most with probabilities greater than 97%, whereas it did not misidentify an unknown (untrained) analyte. Demonstrated unique aspects of this work include an ability to measure binary mixtures and provide both qualitative (identification) and quantitative (concentration) information with array-ANN-based sensor methodologies.« less

Quantifying and mapping spatial variability in simulated forest plots

Treesearch

Gavin R. Corral; Harold E. Burkhart

2016-01-01

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

Geographic variation in forest composition and precipitation predict the synchrony of forest insect outbreaks

Treesearch

Kyle J. Haynes; Andrew M. Liebhold; Ottar N. Bjørnstad; Andrew J. Allstadt; Randall S. Morin

2018-01-01

Evaluating the causes of spatial synchrony in population dynamics in nature is notoriously difficult due to a lack of data and appropriate statistical methods. Here, we use a recently developed method, a multivariate extension of the local indicators of spatial autocorrelation statistic, to map geographic variation in the synchrony of gypsy moth outbreaks. Regression...

Variation in nutrient characteristics of surface soils from the Luquillo Experimental Forest of Puerto Rico: A multivariate perspective.

Treesearch

S. B. Cox; M. R. Willig; F. N. Scatena

2002-01-01

We assessed the effects of landscape features (vegetation type and topography), season, and spatial hierarchy on the nutrient content of surface soils in the Luquillo Experimental Forest (LEF) of Puerto Rico. Considerable spatial variation characterized the soils of the LEF, and differences between replicate sites within each combination of vegetation type (tabonuco vs...

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Multivariate Approaches for Simultaneous Determination of Avanafil and Dapoxetine by UV Chemometrics and HPLC-QbD in Binary Mixtures and Pharmaceutical Product.

PubMed

2016-04-07

Multivariate UV-spectrophotometric methods and Quality by Design (QbD) HPLC are described for concurrent estimation of avanafil (AV) and dapoxetine (DP) in the binary mixture and in the dosage form. Chemometric methods have been developed, including classical least-squares, principal component regression, partial least-squares, and multiway partial least-squares. Analytical figures of merit, such as sensitivity, selectivity, analytical sensitivity, LOD, and LOQ were determined. QbD consists of three steps, starting with the screening approach to determine the critical process parameter and response variables. This is followed by understanding of factors and levels, and lastly the application of a Box-Behnken design containing four critical factors that affect the method. From an Ishikawa diagram and a risk assessment tool, four main factors were selected for optimization. Design optimization, statistical calculation, and final-condition optimization of all the reactions were Carried out. Twenty-five experiments were done, and a quadratic model was used for all response variables. Desirability plot, surface plot, design space, and three-dimensional plots were calculated. In the optimized condition, HPLC separation was achieved on Phenomenex Gemini C18 column (250 × 4.6 mm, 5 μm) using acetonitrile-buffer (ammonium acetate buffer at pH 3.7 with acetic acid) as a mobile phase at flow rate of 0.7 mL/min. Quantification was done at 239 nm, and temperature was set at 20°C. The developed methods were validated and successfully applied for simultaneous determination of AV and DP in the dosage form.

Accreting binary population synthesis and feedback prescriptions

NASA Astrophysics Data System (ADS)

Fragos, Tassos

2016-04-01

Studies of extagalactic X-ray binary populations have shown that the characteristics of these populations depend strongly on the characteristics of the host galaxy's parent stellar population (e.g. star-formation history and metallicity). These dependencies not only make X-ray binaries promising for aiding in the measurement of galaxy properties themselves, but they also have important astrophysical and cosmological implications. For example, due to the relatively young stellar ages and primordial metallicities in the early Universe (z > 3), it is predicted that X-ray binaries were more luminous than today. The more energetic X-ray photons, because of their long mean-free paths, can escape the galaxies where they are produced, and interact at long distances with the intergalactic medium. This could result in a smoother spatial distribution of ionized regions, and more importantly in an overall warmer intergalactic medium. The energetic X-ray photons emitted from X-ray binaries dominate the X-ray radiation field over active galactic nuclei at z > 6 - 8, and hence Χ-ray binary feedback can be a non-negligible contributor to the heating and reionization of the inter-galactic medium in the early universe. The spectral energy distribution shape of the XRB emission does not change significantly with redshift, suggesting that the same XRB subpopulation, namely black-hole XRBs in the high-soft state, dominates the cumulative emission at all times. On the contrary, the normalization of the spectral energy distribution does evolve with redshift. To zeroth order, this evolution is driven by the cosmic star-formation rate evolution. However, the metallicity evolution of the universe and the mean stellar population age are two important factors that affect the X-ray emission from high-mass and low-mass XRBs, respectively. In this talk, I will review recent studies on the potential feedback from accreting binary populations in galactic and cosmological scales. Furthermore, I will discuss which are the next steps towards a more physically realisitc modelling of accreting compact object populations in the early Universe.

Spatial and spectral resolution of carbonaceous material from hematite (α-Fe2O3) using multivariate curve resolution-alternating least squares (MCR-ALS) with Raman microspectroscopic mapping: implications for the search for life on Mars.

PubMed

Smith, Joseph P; Smith, Frank C; Booksh, Karl S

2017-08-21

The search for evidence of extant or past life on Mars is a primary objective of both the upcoming Mars 2020 rover (NASA) and ExoMars 2020 rover (ESA/Roscosmos) missions. This search will involve the detection and identification of organic molecules and/or carbonaceous material within the Martian surface environment. For the first time on a mission to Mars, the scientific payload for each rover will include a Raman spectrometer, an instrument well-suited for this search. Hematite (α-Fe 2 O 3 ) is a widespread mineral on the Martian surface. The 2LO Raman band of hematite and the Raman D-band of carbonaceous material show spectral overlap, leading to the potential misidentification of hematite as carbonaceous material. Here we report the ability to spatially and spectrally differentiate carbonaceous material from hematite using multivariate curve resolution-alternating least squares (MCR-ALS) applied to Raman microspectroscopic mapping under both 532 nm and 785 nm excitation. For this study, a sample comprised of hematite, carbonaceous material, and substrate-adhesive epoxy in spatially distinct domains was constructed. Principal component analysis (PCA) reveals that both 532 nm and 785 nm excitation produce representative three-phase systems of hematite, carbonaceous material, and substrate-adhesive epoxy in the analyzed sample. MCR-ALS with Raman microspectroscopic mapping using both 532 nm and 785 nm excitation was able to resolve hematite, carbonaceous material, and substrate-adhesive epoxy by generating spatially-resolved chemical maps and corresponding Raman spectra of these spatially distinct chemical species. Moreover, MCR-ALS applied to the combinatorial data sets of 532 nm and 785 nm excitation, which contain hematite and carbonaceous material within the same locations, was able to resolve hematite, carbonaceous material, and substrate-adhesive epoxy. Using multivariate analysis with Raman microspectroscopic mapping, 785 nm excitation more effectively resolved hematite, carbonaceous material, and substrate-adhesive epoxy as compared to 532 nm excitation. To our knowledge, this is the first report of multivariate analysis methods, namely MCR-ALS, with Raman microspectroscopic mapping being employed to differentiate carbonaceous material from hematite. We have therefore provided an analytical methodology useful for the search for extant or past life on the surface of Mars.

Development and evaluation of a Hadamard transform imaging spectrometer and a Hadamard transform thermal imager

NASA Technical Reports Server (NTRS)

Harwit, M.; Swift, R.; Wattson, R.; Decker, J.; Paganetti, R.

1976-01-01

A spectrometric imager and a thermal imager, which achieve multiplexing by the use of binary optical encoding masks, were developed. The masks are based on orthogonal, pseudorandom digital codes derived from Hadamard matrices. Spatial and/or spectral data is obtained in the form of a Hadamard transform of the spatial and/or spectral scene; computer algorithms are then used to decode the data and reconstruct images of the original scene. The hardware, algorithms and processing/display facility are described. A number of spatial and spatial/spectral images are presented. The achievement of a signal-to-noise improvement due to the signal multiplexing was also demonstrated. An analysis of the results indicates both the situations for which the multiplex advantage may be gained, and the limitations of the technique. A number of potential applications of the spectrometric imager are discussed.

Unsupervised classification of multivariate geostatistical data: Two algorithms

NASA Astrophysics Data System (ADS)

Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques

2015-12-01

With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

Spectroscopic and Chemometric Analysis of Binary and Ternary Edible Oil Mixtures: Qualitative and Quantitative Study.

PubMed

Jović, Ozren; Smolić, Tomislav; Primožič, Ines; Hrenar, Tomica

2016-04-19

The aim of this study was to investigate the feasibility of FTIR-ATR spectroscopy coupled with the multivariate numerical methodology for qualitative and quantitative analysis of binary and ternary edible oil mixtures. Four pure oils (extra virgin olive oil, high oleic sunflower oil, rapeseed oil, and sunflower oil), as well as their 54 binary and 108 ternary mixtures, were analyzed using FTIR-ATR spectroscopy in combination with principal component and discriminant analysis, partial least-squares, and principal component regression. It was found that the composition of all 166 samples can be excellently represented using only the first three principal components describing 98.29% of total variance in the selected spectral range (3035-2989, 1170-1140, 1120-1100, 1093-1047, and 930-890 cm(-1)). Factor scores in 3D space spanned by these three principal components form a tetrahedral-like arrangement: pure oils being at the vertices, binary mixtures at the edges, and ternary mixtures on the faces of a tetrahedron. To confirm the validity of results, we applied several cross-validation methods. Quantitative analysis was performed by minimization of root-mean-square error of cross-validation values regarding the spectral range, derivative order, and choice of method (partial least-squares or principal component regression), which resulted in excellent predictions for test sets (R(2) > 0.99 in all cases). Additionally, experimentally more demanding gas chromatography analysis of fatty acid content was carried out for all specimens, confirming the results obtained by FTIR-ATR coupled with principal component analysis. However, FTIR-ATR provided a considerably better model for prediction of mixture composition than gas chromatography, especially for high oleic sunflower oil.

Real-time line matching from stereo images using a nonparametric transform of spatial relations and texture information

NASA Astrophysics Data System (ADS)

Park, Jonghee; Yoon, Kuk-Jin

2015-02-01

We propose a real-time line matching method for stereo systems. To achieve real-time performance while retaining a high level of matching precision, we first propose a nonparametric transform to represent the spatial relations between neighboring lines and nearby textures as a binary stream. Since the length of a line can vary across images, the matching costs between lines are computed within an overlap area (OA) based on the binary stream. The OA is determined for each line pair by employing the properties of a rectified image pair. Finally, the line correspondence is determined using a winner-takes-all method with a left-right consistency check. To reduce the computational time requirements further, we filter out unreliable matching candidates in advance based on their rectification properties. The performance of the proposed method was compared with state-of-the-art methods in terms of the computational time, matching precision, and recall. The proposed method required 47 ms to match lines from an image pair in the KITTI dataset with an average precision of 95%. We also verified the proposed method under image blur, illumination variation, and viewpoint changes.

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

DOE PAGES

Dorrer, C.; Hassett, J.

2017-01-23

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

1.5% root-mean-square flat-intensity laser beam formed using a binary-amplitude spatial light modulator.

PubMed

Liang, Jinyang; Kohn, Rudolph N; Becker, Michael F; Heinzen, Daniel J

2009-04-01

We demonstrate a digital micromirror device (DMD)-based optical system that converts a spatially noisy quasi-Gaussian to an eighth-order super-Lorentzian flat-top beam. We use an error-diffusion algorithm to design the binary pattern for the Texas Instruments DLP device. Following the DMD, a telescope with a pinhole low-pass filters the beam and scales it to the desired sized image. Experimental measurements show a 1% root-mean-square (RMS) flatness over a diameter of 0.28 mm in the center of the flat-top beam and better than 1.5% RMS flatness over its entire 1.43 mm diameter. The power conversion efficiency is 37%. We develop an alignment technique to ensure that the DMD pattern is correctly positioned on the incident beam. An interferometric measurement of the DMD surface flatness shows that phase uniformity is maintained in the output beam. Our approach is highly flexible and is able to produce not only flat-top beams with different parameters, but also any slowly varying target beam shape. It can be used to generate the homogeneous optical lattice required for Bose-Einstein condensate cold atom experiments.

High-Mass X-ray Binaries in hard X- rays

NASA Astrophysics Data System (ADS)

Lutovinov, Alexander

We present a review of the latest results of the all-sky survey, performed with the INTEGRAL observatory. The deep exposure spent by INTEGRAL in the Galactic plane region, as well as for nearby galaxies allowed us to obtain a flux limited sample for High Mass X-ray Binaries in the Local Galactic Group and measure their physical properties, like a luminosity function, spatial density distribution, etc. Particularly, it was determined the most accurate up to date spatial density distribution of HMXBs in the Galaxy and its correlation with the star formation rate distribution. Based on the measured value of the vertical distribution of HMXBs (a scale-height h~85 pc) we also estimated a kinematical age of HMXBs. Properties of the population of HMXBs are explained in the framework of the population synthesis model. Based on this model we argue that a flaring activity of so-called supergiant fast X-ray transients (SFXTs), the recently recognized sub-sample of HMXBs, is likely related with the magnetic arrest of their accretion. The resulted global characteristics of the HMXB population are used for predictions of sources number counts in sky surveys of future X-ray missions.

A Comparison of the Influences of Verbal-Successive and Spatial-Simultaneous Factors on Achieving Readers in Fourth and Fifth Grade: A Multivariate Correlational Study.

ERIC Educational Resources Information Center

Solan, Harold A.

1987-01-01

This study involving 38 normally achieving fourth and fifth grade children confirmed previous studies indicating that both spatial-simultaneous (in which perceived stimuli are totally available at one point in time) and verbal-successive (information is presented in serial order) cognitive processing are important in normal learning. (DB)

Automated artifact detection and removal for improved tensor estimation in motion-corrupted DTI data sets using the combination of local binary patterns and 2D partial least squares.

PubMed

Zhou, Zhenyu; Liu, Wei; Cui, Jiali; Wang, Xunheng; Arias, Diana; Wen, Ying; Bansal, Ravi; Hao, Xuejun; Wang, Zhishun; Peterson, Bradley S; Xu, Dongrong

2011-02-01

Signal variation in diffusion-weighted images (DWIs) is influenced both by thermal noise and by spatially and temporally varying artifacts, such as rigid-body motion and cardiac pulsation. Motion artifacts are particularly prevalent when scanning difficult patient populations, such as human infants. Although some motion during data acquisition can be corrected using image coregistration procedures, frequently individual DWIs are corrupted beyond repair by sudden, large amplitude motion either within or outside of the imaging plane. We propose a novel approach to identify and reject outlier images automatically using local binary patterns (LBP) and 2D partial least square (2D-PLS) to estimate diffusion tensors robustly. This method uses an enhanced LBP algorithm to extract texture features from a local texture feature of the image matrix from the DWI data. Because the images have been transformed to local texture matrices, we are able to extract discriminating information that identifies outliers in the data set by extending a traditional one-dimensional PLS algorithm to a two-dimension operator. The class-membership matrix in this 2D-PLS algorithm is adapted to process samples that are image matrix, and the membership matrix thus represents varying degrees of importance of local information within the images. We also derive the analytic form of the generalized inverse of the class-membership matrix. We show that this method can effectively extract local features from brain images obtained from a large sample of human infants to identify images that are outliers in their textural features, permitting their exclusion from further processing when estimating tensors using the DWIs. This technique is shown to be superior in performance when compared with visual inspection and other common methods to address motion-related artifacts in DWI data. This technique is applicable to correct motion artifact in other magnetic resonance imaging (MRI) techniques (e.g., the bootstrapping estimation) that use univariate or multivariate regression methods to fit MRI data to a pre-specified model. Copyright © 2011 Elsevier Inc. All rights reserved.

Lameness detection in dairy cattle: single predictor v. multivariate analysis of image-based posture processing and behaviour and performance sensing.

PubMed

Van Hertem, T; Bahr, C; Schlageter Tello, A; Viazzi, S; Steensels, M; Romanini, C E B; Lokhorst, C; Maltz, E; Halachmi, I; Berckmans, D

2016-09-01

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow behaviour and performance was measured with existing sensors that were already present at the farm. A prototype of three-dimensional-based video recording system was used to quantify automatically the back posture of a cow. For the single predictor comparisons, a receiver operating characteristics curve was made. For the multivariate detection models, logistic regression and generalized linear mixed models (GLMM) were developed. The best lameness classification model was obtained by the multi-sensor analysis (area under the receiver operating characteristics curve (AUC)=0.757±0.029), containing a combination of milk and milking variables, activity and gait and posture variables from videos. Second, the multivariate video-based system (AUC=0.732±0.011) performed better than the multivariate milk sensors (AUC=0.604±0.026) and the multivariate behaviour sensors (AUC=0.633±0.018). The video-based system performed better than the combined behaviour and performance-based detection model (AUC=0.669±0.028), indicating that it is worthwhile to consider a video-based lameness detection system, regardless the presence of other existing sensors in the farm. The results suggest that Θ2, the feature variable for the back curvature around the hip joints, with an AUC of 0.719 is the best single predictor variable for lameness detection based on locomotion scoring. In general, this study showed that the video-based back posture monitoring system is outperforming the behaviour and performance sensing techniques for locomotion scoring-based lameness detection. A GLMM with seven specific variables (walking speed, back posture measurement, daytime activity, milk yield, lactation stage, milk peak flow rate and milk peak conductivity) is the best combination of variables for lameness classification. The accuracy on four-level lameness classification was 60.3%. The accuracy improved to 79.8% for binary lameness classification. The binary GLMM obtained a sensitivity of 68.5% and a specificity of 87.6%, which both exceed the sensitivity (52.1%±4.7%) and specificity (83.2%±2.3%) of the multi-sensor logistic regression model. This shows that the repeated measures analysis in the GLMM, taking into account the individual history of the animal, outperforms the classification when thresholds based on herd level (a statistical population) are used.

Use of dirichlet distributions and orthogonal projection techniques for the fluctuation analysis of steady-state multivariate birth-death systems

NASA Astrophysics Data System (ADS)

Palombi, Filippo; Toti, Simona

2015-05-01

Approximate weak solutions of the Fokker-Planck equation represent a useful tool to analyze the equilibrium fluctuations of birth-death systems, as they provide a quantitative knowledge lying in between numerical simulations and exact analytic arguments. In this paper, we adapt the general mathematical formalism known as the Ritz-Galerkin method for partial differential equations to the Fokker-Planck equation with time-independent polynomial drift and diffusion coefficients on the simplex. Then, we show how the method works in two examples, namely the binary and multi-state voter models with zealots.

WIYN Open Cluster Study. XXXII. Stellar Radial Velocities in the Old Open Cluster NGC 188

NASA Astrophysics Data System (ADS)

Geller, Aaron M.; Mathieu, Robert D.; Harris, Hugh C.; McClure, Robert D.

2008-06-01

We present the results of our ongoing radial-velocity (RV) survey of the old (7 Gyr) open cluster NGC 188. Our WIYN 3.5 m data set spans a time baseline of 11 years, a magnitude range of 12 <= V <= 16.5 (1.18-0.94 M sun), and a 1° diameter region on the sky. With the addition of a Domain Astrophysical Observatory data set we extend our bright limit to V = 10.8 and, for some stars, extend our time baseline to 35 years. Our magnitude limits include solar-mass main-sequence stars, subgiants, giants, and blue stragglers (BSs), and our spatial coverage extends radially to 17 pc (~13 core radii). For the WIYN data we present a detailed description of our data reduction process and a thorough analysis of our measurement precision of 0.4 km s-1 for narrow-lined stars. We have measured radial velocities for 1046 stars in the direction of NGC 188, and have calculated RV membership probabilities for stars with >=3 measurements, finding 473 to be likely cluster members. We detect 124 velocity-variable cluster members, all of which are likely to be dynamically hard-binary stars. Using our single member stars, we find an average cluster radial velocity of -42.36 ± 0.04 km s-1. We use our precise RV and proper-motion membership data to greatly reduce field-star contamination in our cleaned color-magnitude diagram, from which we identify six stars of note that lie far from a standard single-star isochrone. We present a detailed study of the spatial distribution of cluster-member populations, and find the binaries to be centrally concentrated, providing evidence for the presence of mass segregation in NGC 188. We observe the BSs to populate a bimodal spatial distribution that is not centrally concentrated, suggesting that we may be observing two populations of BSs in NGC 188, including a centrally concentrated distribution as well as a halo population. Finally, we find NGC 188 to have a global RV dispersion of 0.64 ± 0.04 km s-1, which may be inflated by up to 0.23 km s-1 from unresolved binaries. When corrected for unresolved binaries, the NGC 188 RV dispersion has a nearly isothermal radial distribution. We use this mean-corrected velocity dispersion to derive a virial mass of 2300 ± 460 M sun .

Nonparametric statistical modeling of binary star separations

NASA Technical Reports Server (NTRS)

Heacox, William D.; Gathright, John

1994-01-01

We develop a comprehensive statistical model for the distribution of observed separations in binary star systems, in terms of distributions of orbital elements, projection effects, and distances to systems. We use this model to derive several diagnostics for estimating the completeness of imaging searches for stellar companions, and the underlying stellar multiplicities. In application to recent imaging searches for low-luminosity companions to nearby M dwarf stars, and for companions to young stars in nearby star-forming regions, our analyses reveal substantial uncertainty in estimates of stellar multiplicity. For binary stars with late-type dwarf companions, semimajor axes appear to be distributed approximately as a(exp -1) for values ranging from about one to several thousand astronomical units. About one-quarter of the companions to field F and G dwarf stars have semimajor axes less than 1 AU, and about 15% lie beyond 1000 AU. The geometric efficiency (fraction of companions imaged onto the detector) of imaging searches is nearly independent of distances to program stars and orbital eccentricities, and varies only slowly with detector spatial limitations.

The Chandra Delta Ori Large Project: Occultation Measurements of the Shocked Gas tn the Nearest Eclipsing O-Star Binary

NASA Technical Reports Server (NTRS)

Corcoran, Michael F.; Nichols, Joy; Naze, Yael; Rauw, Gregor; Pollock, Andrew; Moffat, Anthony; Richardson, Noel; Evans, Nancy; Hamaguchi, Kenji; Oskinova, Lida;

HESS J1844-030: A New Gamma-Ray Binary?

NASA Astrophysics Data System (ADS)

McCall, Hannah; Errando, Manel

2018-01-01

Gamma-ray binaries are comprised of a massive, main-sequence star orbiting a neutron star or black hole that generates bright gamma-ray emission. Only six of these systems have been discovered. Here we report on a candidate stellar-binary system associated with the unidentified gamma-ray source HESS J1844-030, whose detection was revealed in the H.E.S.S. galactic plane survey. Analysis of 60 ks of archival Chandra data and over 100 ks of XMM-Newton data reveal a spatially associated X-ray counterpart to this TeV-emitting source (E>1012 eV), CXO J1845-031. The X-ray spectra derived from these exposures yields column density absorption in the range nH = (0.4 - 0.7) x 1022 cm-2, which is below the total galactic value for that part of the sky, indicating that the source is galactic. The flux from CXO J1845-031 increases with a factor of up to 2.5 in a 60 day timescale, providing solid evidence for flux variability at a confidence level exceeding 7 standard deviations. The point-like nature of the source, the flux variability of the nearby X-ray counterpart, and the low column density absorption are all indicative of a binary system. Once confirmed, HESS J1844-030 would represent only the seventh known gamma-ray binary, providing valuable data to advance our understanding of the physics of pulsars and stellar winds and testing high-energy astrophysical processes at timescales not present in other classes of objects.

Boltzmann equations for a binary one-dimensional ideal gas.

PubMed

Boozer, A D

2011-09-01

We consider a time-reversal invariant dynamical model of a binary ideal gas of N molecules in one spatial dimension. By making time-asymmetric assumptions about the behavior of the gas, we derive Boltzmann and anti-Boltzmann equations that describe the evolution of the single-molecule velocity distribution functions for an ensemble of such systems. We show that for a special class of initial states of the ensemble one can obtain an exact expression for the N-molecule velocity distribution function, and we use this expression to rigorously prove that the time-asymmetric assumptions needed to derive the Boltzmann and anti-Boltzmann equations hold in the limit of large N. Our results clarify some subtle issues regarding the origin of the time asymmetry of Boltzmann's H theorem.

Enhanced Hα activity at periastron in the young and massive spectroscopic binary HD 200775

NASA Astrophysics Data System (ADS)

Benisty, M.; Perraut, K.; Mourard, D.; Stee, P.; Lima, G. H. R. A.; Le Bouquin, J. B.; Borges Fernandes, M.; Chesneau, O.; Nardetto, N.; Tallon-Bosc, I.; McAlister, H.; Ten Brummelaar, T.; Ridgway, S.; Sturmann, J.; Sturmann, L.; Turner, N.; Farrington, C.; Goldfinger, P. J.

2013-07-01

Context. Young close binaries clear central cavities in their surrounding circumbinary disk from which the stellar objects can still accrete material. This process takes place within the first astronomical unit and is still not well constrained because the observational evidence has been gathered, until now, only by means of spectroscopy. Theoretical models for T Tauri stars in close binaries predict a variability of the hydrogen emission lines attributable to periodic changes in the accretion rates as the secondary approaches periastron. Whether a similar scenario applies to more massive objects is unclear, and still needs to be proven observationally. Aims: The young object HD 200775 (MWC 361) is a massive spectroscopic binary (separation of ~15.9 mas, ~5.0 AU), with uncertain classification (early/late Be), that shows a strong and variable Hα emission. We aim to study the mechanisms that produce the Hα line at the AU-scale, and their dependence on binarity. Methods: Combining the radial velocity measurements and astrometric data available in the literature, we determined new orbital parameters and revised the distance to 320 ± 51 pc. With the VEGA instrument on the CHARA array, we spatially and spectrally resolved the Hα emission of HD 200775 on a scale of a few milliarcseconds, at low and medium spectral resolutions (R ~ 1600 and 5000). Our observations cover a single orbital period (~3.6 years). Spectra, spectral visibilities, and differential phases have been derived. A simple analytical model of a face-on Gaussian located along the binary axis was used to analyze the interferometric observables over the spectral range. Results: We observe that the Hα equivalent width varies with the orbital phase, and increases close to periastron, as expected from theoretical models that predict an increase of the mass transfer from the circumbinary disk to the primary disk. In addition, using spectral visibilities and differential phases, we find marginal variations of the typical extent of the Hα emission (at 1 to 2σ level) and location (at 1 to 5σ level). The spatial extent of the Hα emission, as probed by the Gaussian FWHM, is minimum at the ascending node (0.67 ± 0.20 mas, i.e., 0.22 ± 0.06 AU), and more than doubles at the periastron. In addition, the Gaussian photocenter is slightly displaced in the direction opposite to the secondary, ruling out the scenario in which all or most of the Hα emission is due to accretion onto the secondary. This favors a scenario in which the primary is responsible for the enhanced Hα activity at periastron. These findings, together with the wide Hα line profile, may be due to a non-spherical wind enhanced at periastron. Conclusions: For the first time in a system of this kind, we spatially resolve the Hα line and estimate that it is emitted in a region larger than the one usually inferred in accretion processes. The Hα line could be emitted in a stellar or disk-wind, enhanced at periastron as a result of gravitational perturbation, after a period of increased mass accretion rate. Our results suggest a strong connection between accretion and ejection in these massive objects, consistent with the predictions for lower-mass close binaries. Based on observations made with the VEGA/CHARA instrument.

Multivariate Analysis of Electron Detachment Dissociation and Infrared Multiphoton Dissociation Mass Spectra of Heparan Sulfate Tetrasaccharides Differing Only in Hexuronic acid Stereochemistry

NASA Astrophysics Data System (ADS)

Oh, Han Bin; Leach, Franklin E.; Arungundram, Sailaja; Al-Mafraji, Kanar; Venot, Andre; Boons, Geert-Jan; Amster, I. Jonathan

2011-03-01

The structural characterization of glycosaminoglycan (GAG) carbohydrates by mass spectrometry has been a long-standing analytical challenge due to the inherent heterogeneity of these biomolecules, specifically polydispersity, variability in sulfation, and hexuronic acid stereochemistry. Recent advances in tandem mass spectrometry methods employing threshold and electron-based ion activation have resulted in the ability to determine the location of the labile sulfate modification as well as assign the stereochemistry of hexuronic acid residues. To facilitate the analysis of complex electron detachment dissociation (EDD) spectra, principal component analysis (PCA) is employed to differentiate the hexuronic acid stereochemistry of four synthetic GAG epimers whose EDD spectra are nearly identical upon visual inspection. For comparison, PCA is also applied to infrared multiphoton dissociation spectra (IRMPD) of the examined epimers. To assess the applicability of multivariate methods in GAG mixture analysis, PCA is utilized to identify the relative content of two epimers in a binary mixture.

Central composite design with the help of multivariate curve resolution in loadability optimization of RP-HPLC to scale-up a binary mixture.

PubMed

Taheri, Mohammadreza; Moazeni-Pourasil, Roudabeh Sadat; Sheikh-Olia-Lavasani, Majid; Karami, Ahmad; Ghassempour, Alireza

2016-03-01

Chromatographic method development for preparative targets is a time-consuming and subjective process. This can be particularly problematic because of the use of valuable samples for isolation and the large consumption of solvents in preparative scale. These processes could be improved by using statistical computations to save time, solvent and experimental efforts. Thus, contributed by ESI-MS, after applying DryLab software to gain an overview of the most effective parameters in separation of synthesized celecoxib and its co-eluted compounds, design of experiment software that relies on multivariate modeling as a chemometric approach was used to predict the optimized touching-band overloading conditions by objective functions according to the relationship between selectivity and stationary phase properties. The loadability of the method was investigated on the analytical and semi-preparative scales, and the performance of this chemometric approach was approved by peak shapes beside recovery and purity of products. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Monte Carlo modeling of spatial coherence: free-space diffraction

PubMed Central

Fischer, David G.; Prahl, Scott A.; Duncan, Donald D.

2008-01-01

We present a Monte Carlo method for propagating partially coherent fields through complex deterministic optical systems. A Gaussian copula is used to synthesize a random source with an arbitrary spatial coherence function. Physical optics and Monte Carlo predictions of the first- and second-order statistics of the field are shown for coherent and partially coherent sources for free-space propagation, imaging using a binary Fresnel zone plate, and propagation through a limiting aperture. Excellent agreement between the physical optics and Monte Carlo predictions is demonstrated in all cases. Convergence criteria are presented for judging the quality of the Monte Carlo predictions. PMID:18830335

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

Novak, Erik; Trolinger, James D.; Lacey, Ian

This work reports on the development of a binary pseudo-random test sample optimized to calibrate the MTF of optical microscopes. The sample consists of a number of 1-D and 2-D patterns, with different minimum sizes of spatial artifacts from 300 nm to 2 microns. We describe the mathematical background, fabrication process, data acquisition and analysis procedure to return spatial frequency based instrument calibration. We show that the developed samples satisfy the characteristics of a test standard: functionality, ease of specification and fabrication, reproducibility, and low sensitivity to manufacturing error. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading ofmore » the abstract is permitted for personal use only.« less

Phase elements by means of a photolithographic system employing a spatial light modulator

NASA Astrophysics Data System (ADS)

Aubrecht, Ivo; Miler, Miroslav; Pala, Jan

2003-07-01

The system employs a spatial light modulator (SLM), between a pair of crossed polarizers, and an electronic shutter. Transmission of the SLM with the polarizers is controlled by graphical software that defines which pixels are fully transparent and which are fully opaque. While a particular binary graphics is on the SLM the electronic shutter allows light to pass for a certain time. The graphics is imaged, by an objective, onto a photoresist plate. A mercury lamp is used as a light source. The graphics changes after each exposition and the whole sequence of images determines the resultant surface-relief modulation.

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.

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.

High Resolution Studies of Mass Loss from Massive Binary Stars

NASA Astrophysics Data System (ADS)

Corcoran, Michael F.; Gull, Theodore R.; Hamaguchi, Kenji; Richardson, Noel; Madura, Thomas; Post Russell, Christopher Michael; Teodoro, Mairan; Nichols, Joy S.; Moffat, Anthony F. J.; Shenar, Tomer; Pablo, Herbert

2017-01-01

Mass loss from hot luminous single and binary stars has a significant, perhaps decisive, effect on their evolution. The combination of X-ray observations of hot shocked gas embedded in the stellar winds and high-resolution optical/UV spectra of the cooler mass in the outflow provides unique ways to study the unstable process by which massive stars lose mass both through continuous stellar winds and rare, impulsive, large-scale mass ejections. The ability to obtain coordinated observations with the Hubble Space Telescope Imaging Spectrograph (HST/STIS) and the Chandra High-Energy Transmission Grating Spectrometer (HETGS) and other X-ray observatories has allowed, for the first time, studies of resolved line emisssion over the temperature range of 104- 108K, and has provided observations to confront numerical dynamical models in three dimensions. Such observations advance our knowledge of mass-loss asymmetries, spatial and temporal variabilities, and the fundamental underlying physics of the hot shocked outflow, providing more realistic constraints on the amount of mass lost by different luminous stars in a variety of evolutionary stages. We discuss the impact that these joint observational studies have had on our understanding of dynamical mass outflows from massive stars, with particular emphasis on two important massive binaries, Delta Ori Aa, a linchpin of the mass luminosity relation for upper HRD main sequence stars, and the supermassive colliding wind binary Eta Carinae.

Part 2. Development of Enhanced Statistical Methods for Assessing Health Effects Associated with an Unknown Number of Major Sources of Multiple Air Pollutants.

PubMed

Park, Eun Sug; Symanski, Elaine; Han, Daikwon; Spiegelman, Clifford

2015-06-01

A major difficulty with assessing source-specific health effects is that source-specific exposures cannot be measured directly; rather, they need to be estimated by a source-apportionment method such as multivariate receptor modeling. The uncertainty in source apportionment (uncertainty in source-specific exposure estimates and model uncertainty due to the unknown number of sources and identifiability conditions) has been largely ignored in previous studies. Also, spatial dependence of multipollutant data collected from multiple monitoring sites has not yet been incorporated into multivariate receptor modeling. The objectives of this project are (1) to develop a multipollutant approach that incorporates both sources of uncertainty in source-apportionment into the assessment of source-specific health effects and (2) to develop enhanced multivariate receptor models that can account for spatial correlations in the multipollutant data collected from multiple sites. We employed a Bayesian hierarchical modeling framework consisting of multivariate receptor models, health-effects models, and a hierarchical model on latent source contributions. For the health model, we focused on the time-series design in this project. Each combination of number of sources and identifiability conditions (additional constraints on model parameters) defines a different model. We built a set of plausible models with extensive exploratory data analyses and with information from previous studies, and then computed posterior model probability to estimate model uncertainty. Parameter estimation and model uncertainty estimation were implemented simultaneously by Markov chain Monte Carlo (MCMC*) methods. We validated the methods using simulated data. We illustrated the methods using PM2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter) speciation data and mortality data from Phoenix, Arizona, and Houston, Texas. The Phoenix data included counts of cardiovascular deaths and daily PM2.5 speciation data from 1995-1997. The Houston data included respiratory mortality data and 24-hour PM2.5 speciation data sampled every six days from a region near the Houston Ship Channel in years 2002-2005. We also developed a Bayesian spatial multivariate receptor modeling approach that, while simultaneously dealing with the unknown number of sources and identifiability conditions, incorporated spatial correlations in the multipollutant data collected from multiple sites into the estimation of source profiles and contributions based on the discrete process convolution model for multivariate spatial processes. This new modeling approach was applied to 24-hour ambient air concentrations of 17 volatile organic compounds (VOCs) measured at nine monitoring sites in Harris County, Texas, during years 2000 to 2005. Simulation results indicated that our methods were accurate in identifying the true model and estimated parameters were close to the true values. The results from our methods agreed in general with previous studies on the source apportionment of the Phoenix data in terms of estimated source profiles and contributions. However, we had a greater number of statistically insignificant findings, which was likely a natural consequence of incorporating uncertainty in the estimated source contributions into the health-effects parameter estimation. For the Houston data, a model with five sources (that seemed to be Sulfate-Rich Secondary Aerosol, Motor Vehicles, Industrial Combustion, Soil/Crustal Matter, and Sea Salt) showed the highest posterior model probability among the candidate models considered when fitted simultaneously to the PM2.5 and mortality data. There was a statistically significant positive association between respiratory mortality and same-day PM2.5 concentrations attributed to one of the sources (probably industrial combustion). The Bayesian spatial multivariate receptor modeling approach applied to the VOC data led to a highest posterior model probability for a model with five sources (that seemed to be refinery, petrochemical production, gasoline evaporation, natural gas, and vehicular exhaust) among several candidate models, with the number of sources varying between three and seven and with different identifiability conditions. Our multipollutant approach assessing source-specific health effects is more advantageous than a single-pollutant approach in that it can estimate total health effects from multiple pollutants and can also identify emission sources that are responsible for adverse health effects. Our Bayesian approach can incorporate not only uncertainty in the estimated source contributions, but also model uncertainty that has not been addressed in previous studies on assessing source-specific health effects. The new Bayesian spatial multivariate receptor modeling approach enables predictions of source contributions at unmonitored sites, minimizing exposure misclassification and providing improved exposure estimates along with their uncertainty estimates, as well as accounting for uncertainty in the number of sources and identifiability conditions.

High-Density, High-Bandwidth, Multilevel Holographic Memory

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

2008-01-01

A proposed holographic memory system would be capable of storing data at unprecedentedly high density, and its data transfer performance in both reading and writing would be characterized by exceptionally high bandwidth. The capabilities of the proposed system would greatly exceed even those of a state-of-the art memory system, based on binary holograms (in which each pixel value represents 0 or 1), that can hold .1 terabyte of data and can support a reading or writing rate as high as 1 Gb/s. The storage capacity of the state-of-theart system cannot be increased without also increasing the volume and mass of the system. However, in principle, the storage capacity could be increased greatly, without significantly increasing the volume and mass, if multilevel holograms were used instead of binary holograms. For example, a 3-bit (8-level) hologram could store 8 terabytes, or an 8-bit (256-level) hologram could store 256 terabytes, in a system having little or no more size and mass than does the state-of-the-art 1-terabyte binary holographic memory. The proposed system would utilize multilevel holograms. The system would include lasers, imaging lenses and other beam-forming optics, a block photorefractive crystal wherein the holograms would be formed, and two multilevel spatial light modulators in the form of commercially available deformable-mirror-device spatial light modulators (DMDSLMs) made for use in high speed input conversion of data up to 12 bits. For readout, the system would also include two arrays of complementary metal oxide/semiconductor (CMOS) photodetectors matching the spatial light modulators. The system would further include a reference-beam sterring device (equivalent of a scanning mirror), containing no sliding parts, that could be either a liquid-crystal phased-array device or a microscopic mirror actuated by a high-speed microelectromechanical system. Time-multiplexing and the multilevel nature of the DMDSLM would be exploited to enable writing and reading of multilevel holograms. The DMDSLM would also enable transfer of data at a rate of 7.6 Gb/s or perhaps somewhat higher.

Affordable Care Act Qualified Health Plan Coverage: Association With Improved HIV Viral Suppression for AIDS Drug Assistance Program Clients in a Medicaid Nonexpansion State

PubMed Central

McManus, Kathleen A.; Rhodes, Anne; Bailey, Steven; Yerkes, Lauren; Engelhard, Carolyn L.; Ingersoll, Karen S.; Stukenborg, George J.; Dillingham, Rebecca

2016-01-01

Background. With the Patient Protection and Affordable Care Act, many state AIDS Drug Assistance Programs (ADAPs) shifted their healthcare delivery model from direct medication provision to purchasing qualified health plans (QHPs). The objective of this study was to characterize the demographic and healthcare delivery factors associated with Virginia ADAP clients' QHP enrollment and to assess the relationship between QHP coverage and human immunodeficiency virus (HIV) viral suppression. Methods. The cohort included persons living with HIV who were enrolled in the Virginia ADAP (n = 3933). Data were collected from 1 January 2013 through 31 December 2014. Multivariable binary logistic regression was conducted to assess for associations with QHP enrollment and between QHP coverage and viral load (VL) suppression. Results. In the cohort, 47.1% enrolled in QHPs, and enrollment varied significantly based on demographic and healthcare delivery factors. In multivariable binary logistic regression, controlling for time, age, sex, race/ethnicity, and region, factors significantly associated with achieving HIV viral suppression included QHP coverage (adjusted odds ratio, 1.346; 95% confidence interval, 1.041–1.740; P = .02), an initially undetectable VL (2.809; 2.174–3.636; P < .001), HIV rather than AIDS disease status (1.377; 1.049–1.808; P = .02), and HIV clinic (P < .001). Conclusions. QHP coverage was associated with viral suppression, an essential outcome for individuals and for public health. Promoting QHP coverage in clinics that provide care to persons living with HIV may offer a new opportunity to increase rates of viral suppression. PMID:27143661

Personality traits and coping styles explain anxiety in lung cancer patients to a greater extent than other factors.

PubMed

Shimizu, Ken; Nakaya, Naoki; Saito-Nakaya, Kumi; Akechi, Tatsuo; Ogawa, Asao; Fujisawa, Daisuke; Sone, Toshimasa; Yoshiuchi, Kazuhiro; Goto, Koichi; Iwasaki, Motoki; Tsugane, Shoichiro; Uchitomi, Yosuke

2015-05-01

Although various factors thought to be correlated with anxiety in cancer patients, relative importance of each factors were unknown. We tested our hypothesis that personality traits and coping styles explain anxiety in lung cancer patients to a greater extent than other factors. A total of 1334 consecutively recruited lung cancer patients were selected, and data on cancer-related variables, demographic characteristics, health behaviors, physical symptoms and psychological factors consisting of personality traits and coping styles were obtained. The participants were divided into groups with or without a significant anxiety using the Hospital Anxiety and Depression Scale-Anxiety, and a binary logistic regression analysis was used to identify factors correlated with significant anxiety using a multivariate model. Among the recruited patients, 440 (33.0%) had significant anxiety. The binary logistic regression analysis revealed a coefficient of determination (overall R(2)) of 39.0%, and the explanation for psychological factors was much higher (30.7%) than those for cancer-related variables (1.1%), demographic characteristics (2.1%), health behaviors (0.8%) and physical symptoms (4.3%). Four specific factors remained significant in a multivariate model. A neurotic personality trait, a coping style of helplessness/hopelessness, and a female sex were positively correlated with significant anxiety, while a coping style of fatalism was negatively correlated. Our hypothesis was supported, and anxiety was strongly linked with personality trait and coping style. As a clinical implication, the use of screening instruments to identify these factors and intervention for psychological crisis may be needed. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Spatial and temporal synchrony in reptile population dynamics in variable environments.

PubMed

Greenville, Aaron C; Wardle, Glenda M; Nguyen, Vuong; Dickman, Chris R

2016-10-01

Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22 years) from a large (8000 km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.

Geostatistics for spatial genetic structures: study of wild populations of perennial ryegrass.

PubMed

Monestiez, P; Goulard, M; Charmet, G

1994-04-01

Methods based on geostatistics were applied to quantitative traits of agricultural interest measured on a collection of 547 wild populations of perennial ryegrass in France. The mathematical background of these methods, which resembles spatial autocorrelation analysis, is briefly described. When a single variable is studied, the spatial structure analysis is similar to spatial autocorrelation analysis, and a spatial prediction method, called "kriging", gives a filtered map of the spatial pattern over all the sampled area. When complex interactions of agronomic traits with different evaluation sites define a multivariate structure for the spatial analysis, geostatistical methods allow the spatial variations to be broken down into two main spatial structures with ranges of 120 km and 300 km, respectively. The predicted maps that corresponded to each range were interpreted as a result of the isolation-by-distance model and as a consequence of selection by environmental factors. Practical collecting methodology for breeders may be derived from such spatial structures.

WIYN Open Cluster Study: Binary Orbits and Tidal Circularization in NGC 6819

NASA Astrophysics Data System (ADS)

Morscher, Meagan B.; Mathieu, R. D.; Kaeppler, S.; Hole, K. T.; Meibom, S.

2006-12-01

We are conducting a comprehensive stellar radial-velocity survey in NGC 6819, a rich, intermediate age ( 2.4 Gyr) open cluster with [Fe/H] -0.05. As of October 2006, we have obtained 7065 radial-velocity measurements of 1409 stars using the WIYN Hydra Multi-Object Spectrograph, with typical velocity measurement precisions of 0.4 km/s. Using an E/I criterion of 3, we have identified 282 velocity variables. In the past year we have expanded the number of final orbital solutions by 45 to a total of more than 80 solutions. In coeval stellar populations, circular binaries tend to have the shortest orbital periods, while longer period binaries show a distribution of non-zero eccentricities. The circularization of the shortest period orbits is the result of an exchange of stellar and orbital angular momentum due to tidal interactions. We defined a population’s tidal circularization period as the longest orbital period at which a binary of typical initial eccentricity has become circularized (e.g., has evolved to an eccentricity e = 0.01) over the lifetime of the cluster (Meibom & Mathieu, 2005, ApJ, 620, 970). We are studying the trend of increasing tidal circularization periods with population age. Preliminary results in NGC 6819 indicate a tidal circularization period of 7.5 days, which is consistent with this overall trend. We will recalculate the tidal circularization period in order to include the latest sample of orbital solutions. This comprehensive survey also allows us to investigate the relative spatial distributions of spectroscopic binaries and other constant-velocity cluster members of similar mass. We find the spectroscopic binaries to be more centrally concentrated at a statistically significant level, which we attribute to energy equipartition processes. MM was supported by REU NSF grant AST-0453442. RDM, SK, KTH, and SM were supported by NSF grant AST-0406615.

FIA data and species diversity—successes and failures using multivariate analysis techniques, spatial lag and error models and hot-spot analysis

Treesearch

Andrew J. Hartsell

2015-01-01

This study will investigate how global and local predictors differ with varying spatial scale in relation to species evenness and richness in the gulf coastal plain. Particularly, all-live trees >= one-inch d.b.h. Forest Inventory and Analysis (FIA) data was used as the basis for the study. Watersheds are defined by the USGS 12 digit hydrologic units. The...

Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.

PubMed

Lawson, A B; Carroll, R; Faes, C; Kirby, R S; Aregay, M; Watjou, K

2017-12-01

It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this paper, we propose a flexible class of multivariate spatio-temporal mixture models to fill this role. Further, these models offer flexibility with the potential for model selection as well as the ability to accommodate lifestyle, socio-economic, and physical environmental variables with spatial, temporal, or both structures. Here, we explore the capability of this approach via a large scale simulation study and examine a motivating data example involving three cancers in South Carolina. The results which are focused on four model variants suggest that all models possess the ability to recover simulation ground truth and display improved model fit over two baseline Knorr-Held spatio-temporal interaction model variants in a real data application.

Probing the X-ray Emission from the Massive Star Cluster Westerlund 2

NASA Astrophysics Data System (ADS)

Lopez, Laura

2017-09-01

We propose a 300 ks Chandra ACIS-I observation of the massive star cluster Westerlund 2 (Wd2). This region is teeming with high-energy emission from a variety of sources: colliding wind binaries, OB and Wolf-Rayet stars, two young pulsars, and an unidentified source of very high-energy (VHE) gamma-rays. Our Chandra program is designed to achieve several goals: 1) to take a complete census of Wd2 X-ray point sources and monitor variability; 2) to probe the conditions of the colliding winds in the binary WR 20a; 3) to search for an X-ray counterpart of the VHE gamma-rays; 4) to identify diffuse X-ray emission; 5) to compare results to other massive star clusters observed by Chandra. Only Chandra has the spatial resolution and sensitivity necessary for our proposed analyses.

Content based image retrieval using local binary pattern operator and data mining techniques.

PubMed

Vatamanu, Oana Astrid; Frandeş, Mirela; Lungeanu, Diana; Mihalaş, Gheorghe-Ioan

2015-01-01

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.

Reducing junk radiation and eccentricity in binary-black-hole initial data

NASA Astrophysics Data System (ADS)

Lovelace, Geoffrey; Pfeiffer, Harald; Brown, Duncan; Lindblom, Lee; Scheel, Mark; Kidder, Lawrence

2007-04-01

Numerical simulations of binary-black-hole (BBH) collisions require initial data that satisfy the Einstein constraint equations. Several well-known methods generate constraint-satisfying BBH data, but the commonly-used simplifying assumptions lead to undesirable effects. BBH data typically assume a conformally flat spatial metric; this leads to an initial pulse of unphysical ``junk'' gravitational radiation. Also, the initial radial velocity of the holes is often neglected; this can lead to significant eccentricity in the holes' trajectories. This talk will discuss efforts to reduce these effects by constructing and evolving generalizations of the BBH initial data of Cook and Pfeiffer (2004). By giving the holes a small radial velocity, the eccentricity can be greatly reduced (although the emitted waves are largely unaffected). The junk radiation for flat and non-flat conformal metrics will also be compared.

Binary zone-plate array for a parallel joint transform correlator applied to face recognition.

PubMed

Kodate, K; Hashimoto, A; Thapliya, R

1999-05-10

Taking advantage of small aberrations, high efficiency, and compactness, we developed a new, to our knowledge, design procedure for a binary zone-plate array (BZPA) and applied it to a parallel joint transform correlator for the recognition of the human face. Pairs of reference and unknown images of faces are displayed on a liquid-crystal spatial light modulator (SLM), Fourier transformed by the BZPA, intensity recorded on an optically addressable SLM, and inversely Fourier transformed to obtain correlation signals. Consideration of the bandwidth allows the relations among the channel number, the numerical aperture of the zone plates, and the pattern size to be determined. Experimentally a five-channel parallel correlator was implemented and tested successfully with a 100-person database. The design and the fabrication of a 20-channel BZPA for phonetic character recognition are also included.

Evaluation of AMOEBA: a spectral-spatial classification method

USGS Publications Warehouse

Jenson, Susan K.; Loveland, Thomas R.; Bryant, J.

1982-01-01

Muitispectral remotely sensed images have been treated as arbitrary multivariate spectral data for purposes of clustering and classifying. However, the spatial properties of image data can also be exploited. AMOEBA is a clustering and classification method that is based on a spatially derived model for image data. In an evaluation test, Landsat data were classified with both AMOEBA and a widely used spectral classifier. The test showed that irrigated crop types can be classified as accurately with the AMOEBA method as with the generally used spectral method ISOCLS; the AMOEBA method, however, requires less computer time.

Chandra Discovery of a Binary Active Galactic Nucleus in Mrk 739

NASA Astrophysics Data System (ADS)

Koss, Michael; Mushotzky, Richard; Treister, Ezequiel; Veilleux, Sylvain; Vasudevan, Ranjan; Miller, Neal; Sanders, D. B.; Schawinski, Kevin; Trippe, Margaret

2011-07-01

We have discovered a binary active galactic nucleus (AGN) in the galaxy Mrk 739 using Chandra and Swift BAT. We find two luminous (L 2-10 keV = 1.1 × 1043 and 1.0 × 1042 erg s-1), unresolved nuclei with a projected separation of 3.4 kpc (5farcs8 ± 0farcs1) coincident with two bulge components in the optical image. The western X-ray source (Mrk 739W) is highly variable (× 2.5) during the 4 hr Chandra observation and has a very hard spectrum consistent with an AGN. While the eastern component was already known to be an AGN based on the presence of broad optical recombination lines, Mrk 739W shows no evidence of being an AGN in optical, UV, and radio observations, suggesting the critical importance of high spatial resolution hard X-ray observations (>2 keV) in finding these binary AGNs. A high level of star formation combined with a very low L [O III]/L 2-10 keV ratio cause the AGN to be missed in optical observations. 12CO observations of the (3-2) and (2-1) lines indicate large amounts of molecular gas in the system that could be driven toward the black holes during the violent galaxy collision and be key to fueling the binary AGN. Mrk 739E has a high Eddington ratio of 0.71 and a small black hole (log M BH = 7.05 ± 0.3) consistent with an efficiently accreting AGN. Other than NGC 6240, this stands as the nearest case of a binary AGN discovered to date.

From empowerment to response-ability: rethinking socio-spatial, environmental justice, and nature-culture binaries in the context of STEM education

NASA Astrophysics Data System (ADS)

Kayumova, Shakhnoza; McGuire, Chad J.; Cardello, Suzanne

2018-04-01

In this conceptual paper, we draw upon the insights of Feminist Science Studies, in particular Karen Barad's concept of agential realism, as a critical analytical tool to re-think nature and culture binaries in dominant science knowledge-making practices and explanatory accounts, and their possible implications for science education in the context of socio-spatial and environmental injustices. Barad's framework proposes a relational and more expansive approach to justice, which takes into account consequential effects of nature-culture practices on humans, non-humans, and more than human vitalities. In efforts to understand potentialities of Barad's theory of agential realism, we situate our argument in the "story" of local children who encounter a bottle of cyanide in a former manufacturing building. The story takes place in a post-industrial urban city located in the U.S., caught up in an inverse relationship between the technological and scientific advances observed "globally" and the deteriorating environmental and living conditions experienced "locally" as the result of erstwhile industrial activity. Based on agential realist readings of the story and taking into consideration children's developing subjectivities, we argue that equity-oriented scholarship in science education might not be able to achieve justice devoid of understanding of the relatedness to plurality of life forms. We invite our readers to consider (re)configuring socio-spatial and environmental issues as an ethical response-ability that is constituted through relationships of care, recognition, openness, and responsiveness to vitalities of humans and nonhumans equally, one which cannot be conceptualized from a priori and distant calculations, but rather continuous entangled relations.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

Churchill, R. Michael

Apache Spark is explored as a tool for analyzing large data sets from the magnetic fusion simulation code XGCI. Implementation details of Apache Spark on the NERSC Edison supercomputer are discussed, including binary file reading, and parameter setup. Here, an unsupervised machine learning algorithm, k-means clustering, is applied to XGCI particle distribution function data, showing that highly turbulent spatial regions do not have common coherent structures, but rather broad, ring-like structures in velocity space.

Feasibility Study of Compressive Sensing Underwater Imaging Lidar

DTIC Science & Technology

2014-03-28

Texas Instruments Digital Micromirror Devices development system. In addition, through these studies, the deficiencies and/or areas of lack...device, such as the Digital Micromirror Device (DMD), to spatially modulate the laser source that illuminates the target plane. The same binary patterns...Digital Micromirror Device (DMD) Applications," Proc. of SPIE, 2003, 4985, 14-25. [8] T. E. Giddings and J. J. Shirron, "Numerical Simulation of the

Technical Report for the Period 1 October 1987 - 30 September 1989

DTIC Science & Technology

1990-03-01

low pass filter results. -dt dt specifies the sampling rate in seconds. -gin specifies .w file (binary waveform data) input. - gout specifies .w file...waves arriving at moderate incidence angles, * high signal-to-noise ratio (SNR). The following assumptions are made, for simplicity* * additive...spatially uncorrelated noise, * simple signal model, free of refraction and scattering effects. This study is limited to the case of a plane incident P

Physical vs. photolithographic patterning of plasma polymers: an investigation by ToF-SSIMS and multivariate analysis

PubMed Central

Mishra, Gautam; Easton, Christopher D.; McArthur, Sally L.

2009-01-01

Physical and photolithographic techniques are commonly used to create chemical patterns for a range of technologies including cell culture studies, bioarrays and other biomedical applications. In this paper, we describe the fabrication of chemical micropatterns from commonly used plasma polymers. Atomic force microcopy (AFM) imaging, Time-of-Flight Static Secondary Ion Mass Spectrometry (ToF-SSIMS) imaging and multivariate analysis have been employed to visualize the chemical boundaries created by these patterning techniques and assess the spatial and chemical resolution of the patterns. ToF-SSIMS analysis demonstrated that well defined chemical and spatial boundaries were obtained from photolithographic patterning, while the resolution of physical patterning via a transmission electron microscopy (TEM) grid varied depending on the properties of the plasma system including the substrate material. In general, physical masking allowed diffusion of the plasma species below the mask and bleeding of the surface chemistries. Multivariate analysis techniques including Principal Component Analysis (PCA) and Region of Interest (ROI) assessment were used to investigate the ToF-SSIMS images of a range of different plasma polymer patterns. In the most challenging case, where two strongly reacting polymers, allylamine and acrylic acid were deposited, PCA confirmed the fabrication of micropatterns with defined spatial resolution. ROI analysis allowed for the identification of an interface between the two plasma polymers for patterns fabricated using the photolithographic technique which has been previously overlooked. This study clearly demonstrated the versatility of photolithographic patterning for the production of multichemistry plasma polymer arrays and highlighted the need for complimentary characterization and analytical techniques during the fabrication plasma polymer micropatterns. PMID:19950941

Landscape controls on total and methyl Hg in the Upper Hudson River basin, New York, USA

USGS Publications Warehouse

Burns, Douglas A.; Riva-Murray, K.; Bradley, P.M.; Aiken, G.R.; Brigham, M.E.

2012-01-01

Approaches are needed to better predict spatial variation in riverine Hg concentrations across heterogeneous landscapes that include mountains, wetlands, and open waters. We applied multivariate linear regression to determine the landscape factors and chemical variables that best account for the spatial variation of total Hg (THg) and methyl Hg (MeHg) concentrations in 27 sub-basins across the 493 km2 upper Hudson River basin in the Adirondack Mountains of New York. THg concentrations varied by sixfold, and those of MeHg by 40-fold in synoptic samples collected at low-to-moderate flow, during spring and summer of 2006 and 2008. Bivariate linear regression relations of THg and MeHg concentrations with either percent wetland area or DOC concentrations were significant but could account for only about 1/3 of the variation in these Hg forms in summer. In contrast, multivariate linear regression relations that included metrics of (1) hydrogeomorphology, (2) riparian/wetland area, and (3) open water, explained about 66% to >90% of spatial variation in each Hg form in spring and summer samples. These metrics reflect the influence of basin morphometry and riparian soils on Hg source and transport, and the role of open water as a Hg sink. Multivariate models based solely on these landscape metrics generally accounted for as much or more of the variation in Hg concentrations than models based on chemical and physical metrics, and show great promise for identifying waters with expected high Hg concentrations in the Adirondack region and similar glaciated riverine ecosystems.

Factors Associated with the Emergence of Highly Pathogenic Avian Influenza A (H5N1) Poultry Outbreaks in China: Evidence from an Epidemiological Investigation in Ningxia, 2012.

PubMed

Liu, H; Zhou, X; Zhao, Y; Zheng, D; Wang, J; Wang, X; Castellan, D; Huang, B; Wang, Z; Soares Magalhães, R J

2017-06-01

In April 2012, highly pathogenic avian influenza virus of the H5N1 subtype (HPAIV H5N1) emerged in poultry layers in Ningxia. A retrospective case-control study was conducted to identify possible risk factors associated with the emergence of H5N1 infection and describe and quantify the spatial variation in H5N1 infection. A multivariable logistic regression model was used to identify risk factors significantly associated with the presence of infection; residual spatial variation in H5N1 risk unaccounted by the factors included in the multivariable model was investigated using a semivariogram. Our results indicate that HPAIV H5N1-infected farms were three times more likely to improperly dispose farm waste [adjusted OR = 0.37; 95% CI: 0.12-0.82] and five times more likely to have had visitors in their farm within the past month [adjusted OR = 5.47; 95% CI: 1.97-15.64] compared to H5N1-non-infected farms. The variables included in the final multivariable model accounted only 20% for the spatial clustering of H5N1 infection. The average size of a H5N1 cluster was 660 m. Bio-exclusion practices should be strengthened on poultry farms to prevent further emergence of H5N1 infection. For future poultry depopulation, operations should consider H5N1 disease clusters to be as large as 700 m. © 2015 Blackwell Verlag GmbH.

Phase-image-based content-addressable holographic data storage

NASA Astrophysics Data System (ADS)

John, Renu; Joseph, Joby; Singh, Kehar

2004-03-01

We propose and demonstrate the use of phase images for content-addressable holographic data storage. Use of binary phase-based data pages with 0 and π phase changes, produces uniform spectral distribution at the Fourier plane. The absence of strong DC component at the Fourier plane and more intensity of higher order spatial frequencies facilitate better recording of higher spatial frequencies, and improves the discrimination capability of the content-addressable memory. This improves the results of the associative recall in a holographic memory system, and can give low number of false hits even for small search arguments. The phase-modulated pixels also provide an opportunity of subtraction among data pixels leading to better discrimination between similar data pages.

Real-time optical correlator using computer-generated holographic filter on a liquid crystal light valve

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Yu, Jeffrey

1990-01-01

Limitations associated with the binary phase-only filter often used in optical correlators are presently circumvented in the writing of complex-valued data on a gray-scale spatial light modulator through the use of a computer-generated hologram (CGH) algorithm. The CGH encodes complex-valued data into nonnegative real CGH data in such a way that it may be encoded in any of the available gray-scale spatial light modulators. A CdS liquid-crystal light valve is used for the complex-valued CGH encoding; computer simulations and experimental results are compared, and the use of such a CGH filter as the synapse hologram in a holographic optical neural net is discussed.

Area variations in multiple morbidity using a life table methodology.

PubMed

Congdon, Peter

Analysis of healthy life expectancy is typically based on a binary distinction between health and ill-health. By contrast, this paper considers spatial modelling of disease free life expectancy taking account of the number of chronic conditions. Thus the analysis is based on population sub-groups with no disease, those with one disease only, and those with two or more diseases (multiple morbidity). Data on health status is accordingly modelled using a multinomial likelihood. The analysis uses data for 258 small areas in north London, and shows wide differences in the disease burden related to multiple morbidity. Strong associations between area socioeconomic deprivation and multiple morbidity are demonstrated, as well as strong spatial clustering.

Dynamic texture recognition using local binary patterns with an application to facial expressions.

PubMed

Zhao, Guoying; Pietikäinen, Matti

2007-06-01

Dynamic texture (DT) is an extension of texture to the temporal domain. Description and recognition of DTs have attracted growing attention. In this paper, a novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered. First, the textures are modeled with volume local binary patterns (VLBP), which are an extension of the LBP operator widely used in ordinary texture analysis, combining motion and appearance. To make the approach computationally simple and easy to extend, only the co-occurrences of the local binary patterns on three orthogonal planes (LBP-TOP) are then considered. A block-based method is also proposed to deal with specific dynamic events such as facial expressions in which local information and its spatial locations should also be taken into account. In experiments with two DT databases, DynTex and Massachusetts Institute of Technology (MIT), both the VLBP and LBP-TOP clearly outperformed the earlier approaches. The proposed block-based method was evaluated with the Cohn-Kanade facial expression database with excellent results. The advantages of our approach include local processing, robustness to monotonic gray-scale changes, and simple computation.

3D Modeling of Forbidden Line Emission in the Binary Wind Interaction Region of Eta Carinae

NASA Technical Reports Server (NTRS)

Madura, Thomas; Gull, T. R.; Owocki, S.; Okazaki, A. T.; Russell, C. M. P.

2010-01-01

We present recent work using three-dimensional (3D) Smoothed Particle Hydrodynamics (SPH) simulations to model the high ([Fe III], [Ar III], [Ne III] and [S III]) and low ([Fe II], [Ni II]) ionization forbidden emission lines observed in Eta Carinae using the HST/STIS. These structures are interpreted as the time-averaged, outer extensions of the primary wind and the wind-wind interaction region directly excited by the FUV of the hot companion star of this massive binary system. We discuss how analyzing the results of the 3D SPH simulations and synthetic slit spectra and comparing them to the spectra obtained with the HST/STIS helps us determine the absolute orientation of the binary orbit and helps remove the degeneracy inherent to models based solely on the observed RXTE X-ray light curve. A key point of this work is that spatially resolved observations like those with HST/STIS and comparison to 3D models are necessary to determine the alignment or misalignment of the orbital angular momentum axis with the Homunculus, or correspondingly, the alignment of the orbital plane with the Homunculus skirt.

Imprints of dynamical interactions on brown dwarf pairing statistics and kinematics

NASA Astrophysics Data System (ADS)

Sterzik, M. F.; Durisen, R. H.

2003-03-01

We present statistically robust predictions of brown dwarf properties arising from dynamical interactions during their early evolution in small clusters. Our conclusions are based on numerical calculations of the internal cluster dynamics as well as on Monte-Carlo models. Accounting for recent observational constraints on the sub-stellar mass function and initial properties in fragmenting star forming clumps, we derive multiplicity fractions, mass ratios, separation distributions, and velocity dispersions. We compare them with observations of brown dwarfs in the field and in young clusters. Observed brown dwarf companion fractions around 15 +/- 7% for very low-mass stars as reported recently by Close et al. (\\cite{CSFB03}) are consistent with certain dynamical decay models. A significantly smaller mean separation distribution for brown dwarf binaries than for binaries of late-type stars can be explained by similar specific energy at the time of cluster formation for all cluster masses. Due to their higher velocity dispersions, brown-dwarfs and low-mass single stars will undergo time-dependent spatial segregation from higher-mass stars and multiple systems. This will cause mass functions and binary statistics in star forming regions to vary with the age of the region and the volume sampled.

Reduced Carrier Recombination in PbS - CuInS2 Quantum Dot Solar Cells

PubMed Central

Sun, Zhenhua; Sitbon, Gary; Pons, Thomas; Bakulin, Artem A.; Chen, Zhuoying

2015-01-01

Energy loss due to carrier recombination is among the major factors limiting the performance of TiO2/PbS colloidal quantum dot (QD) heterojunction solar cells. In this work, enhanced photocurrent is achieved by incorporating another type of hole-transporting QDs, Zn-doped CuInS2 (Zn-CIS) QDs into the PbS QD matrix. Binary QD solar cells exhibit a reduced charge recombination associated with the spatial charge separation between these two types of QDs. A ~30% increase in short-circuit current density and a ~20% increase in power conversion efficiency are observed in binary QD solar cells compared to cells built from PbS QDs only. In agreement with the charge transfer process identified through ultrafast pump/probe spectroscopy between these two QD components, transient photovoltage characteristics of single-component and binary QDs solar cells reveal longer carrier recombination time constants associated with the incorporation of Zn-CIS QDs. This work presents a straightforward, solution-processed method based on the incorporation of another QDs in the PbS QD matrix to control the carrier dynamics in colloidal QD materials and enhance solar cell performance. PMID:26024021

Dynamical mass measurement of the young spectroscopic binary V343 Normae AaAb resolved with the Gemini Planet Imager

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

Nielsen, Eric L.; De Rosa, Robert J.; Wang, Jason

Here, we present new spatially resolved astrometry and photometry from the Gemini Planet Imager of the inner binary of the young multiple star system V343 Normae, which is a member of the β Pictoris (β Pic) moving group. V343 Normae comprises a K0 and mid-M star in a ~4.5 year orbit (AaAb) and a wide 10'' M5 companion (B). By combining these data with archival astrometry and radial velocities we fit the orbit and measure individual masses for both components ofmore » $${M}_{\\mathrm{Aa}}=1.10\\pm 0.10\\,{M}_{\\odot }$$ and $${M}_{\\mathrm{Ab}}=0.290\\pm 0.018\\,{M}_{\\odot }$$. Comparing to theoretical isochrones, we find good agreement for the measured masses and JHK band magnitudes of the two components consistent with the age of the β Pic moving group. We derive a model-dependent age for the β Pic moving group of 26 ± 3 Myr by combining our results for V343 Normae with literature measurements for GJ 3305, which is another group member with resolved binary components and dynamical masses.« less

Chandra Observations of the Eclipsing Wolf-Rayet Binary CQ CepOver a Full Orbital Cycle

NASA Astrophysics Data System (ADS)

Skinner, Steve L.; Guedel, Manuel; Schmutz, Werner; Zhekov, Svetozar

2018-06-01

We present results of Chandra X-ray observations and simultaneous optical light curves of the short-period (1.64 d) eclipsing WN6+O9 binary system CQ Cep obtained in 2013 and 2017 covering a full binary orbit. Our primary objective was to compare the observed X-ray properties with colliding wind shock theory, which predicts that the hottest shock plasma (T > 20 MK) will form on or near the line-of-centers between the stars. Thus, X-ray variability is expected during eclipses when the hottest plasma is occulted. The X-ray spectrum is strikingly similar to apparently single WN6 stars such as WR 134 and spectral lines reveal plasma over a broad range of temperatures T ~ 4 - 40 MK. Both primary and secondary optical eclipses were clearly detected and provide an accurate orbital period determination (P = 1.6412 d). The X-ray emission remained remarkably steady throughout the orbit and statistical tests give a low probability of variability. The lack of significant X-ray variabililty during eclipses indicates that the X-ray emission is not confined along the line-of-centers but is extended on larger spatial scales, contrary to colliding wind predictions.

A new phase encoding approach for a compact head-up display

NASA Astrophysics Data System (ADS)

Suszek, Jaroslaw; Makowski, Michal; Sypek, Maciej; Siemion, Andrzej; Kolodziejczyk, Andrzej; Bartosz, Andrzej

2008-12-01

The possibility of encoding multiple asymmetric symbols into a single thin binary Fourier hologram would have a practical application in the design of simple translucent holographic head-up displays. A Fourier hologram displays the encoded images at the infinity so this enables an observation without a time-consuming eye accommodation. Presenting a set of the most crucial signs for a driver in this way is desired, especially by older people with various eyesight disabilities. In this paper a method of holographic design is presented that assumes a combination of a spatial segmentation and carrier frequencies. It allows to achieve multiple reconstructed images selectable by the angle of the incident laser beam. In order to encode several binary symbols into a single Fourier hologram, the chessboard shaped segmentation function is used. An optimized sequence of phase encoding steps and a final direct phase binarization enables recording of asymmetric symbols into a binary hologram. The theoretical analysis is presented, verified numerically and confirmed in the optical experiment. We suggest and describe a practical and highly useful application of such holograms in an inexpensive HUD device for the use of the automotive industry. We present two alternative propositions of car viewing setups.

Dynamical mass measurement of the young spectroscopic binary V343 Normae AaAb resolved with the Gemini Planet Imager

DOE PAGES

Nielsen, Eric L.; De Rosa, Robert J.; Wang, Jason; ...

2016-11-22

Here, we present new spatially resolved astrometry and photometry from the Gemini Planet Imager of the inner binary of the young multiple star system V343 Normae, which is a member of the β Pictoris (β Pic) moving group. V343 Normae comprises a K0 and mid-M star in a ~4.5 year orbit (AaAb) and a wide 10'' M5 companion (B). By combining these data with archival astrometry and radial velocities we fit the orbit and measure individual masses for both components ofmore » $${M}_{\\mathrm{Aa}}=1.10\\pm 0.10\\,{M}_{\\odot }$$ and $${M}_{\\mathrm{Ab}}=0.290\\pm 0.018\\,{M}_{\\odot }$$. Comparing to theoretical isochrones, we find good agreement for the measured masses and JHK band magnitudes of the two components consistent with the age of the β Pic moving group. We derive a model-dependent age for the β Pic moving group of 26 ± 3 Myr by combining our results for V343 Normae with literature measurements for GJ 3305, which is another group member with resolved binary components and dynamical masses.« less

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R.

2007-10-16

A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

Depth and Medium-Scale Spatial Processes Influence Fish Assemblage Structure of Unconsolidated Habitats in a Subtropical Marine Park

PubMed Central

Schultz, Arthur L.; Malcolm, Hamish A.; Bucher, Daniel J.; Linklater, Michelle; Smith, Stephen D. A.

2014-01-01

Where biological datasets are spatially limited, abiotic surrogates have been advocated to inform objective planning for Marine Protected Areas. However, this approach assumes close correlation between abiotic and biotic patterns. The Solitary Islands Marine Park, northern NSW, Australia, currently uses a habitat classification system (HCS) to assist with planning, but this is based only on data for reefs. We used Baited Remote Underwater Videos (BRUVs) to survey fish assemblages of unconsolidated substrata at different depths, distances from shore, and across an along-shore spatial scale of 10 s of km (2 transects) to examine how well the HCS works for this dominant habitat. We used multivariate regression modelling to examine the importance of these, and other environmental factors (backscatter intensity, fine-scale bathymetric variation and rugosity), in structuring fish assemblages. There were significant differences in fish assemblages across depths, distance from shore, and over the medium spatial scale of the study: together, these factors generated the optimum model in multivariate regression. However, marginal tests suggested that backscatter intensity, which itself is a surrogate for sediment type and hardness, might also influence fish assemblages and needs further investigation. Species richness was significantly different across all factors: however, total MaxN only differed significantly between locations. This study demonstrates that the pre-existing abiotic HCS only partially represents the range of fish assemblages of unconsolidated habitats in the region. PMID:24824998

Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline

PubMed Central

Fan, Yong; Batmanghelich, Nematollah; Clark, Chris M.; Davatzikos, Christos

2010-01-01

Spatial patterns of brain atrophy in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) were measured via methods of computational neuroanatomy. These patterns were spatially complex and involved many brain regions. In addition to the hippocampus and the medial temporal lobe gray matter, a number of other regions displayed significant atrophy, including orbitofrontal and medial-prefrontal grey matter, cingulate (mainly posterior), insula, uncus, and temporal lobe white matter. Approximately 2/3 of the MCI group presented patterns of atrophy that overlapped with AD, whereas the remaining 1/3 overlapped with cognitively normal individuals, thereby indicating that some, but not all, MCI patients have significant and extensive brain atrophy in this cohort of MCI patients. Importantly, the group with AD-like patterns presented much higher rate of MMSE decline in follow-up visits; conversely, pattern classification provided relatively high classification accuracy (87%) of the individuals that presented relatively higher MMSE decline within a year from baseline. High-dimensional pattern classification, a nonlinear multivariate analysis, provided measures of structural abnormality that can potentially be useful for individual patient classification, as well as for predicting progression and examining multivariate relationships in group analyses. PMID:18053747

Multivariate analysis applied to the study of spatial distributions found in drug-eluting stent coatings by confocal Raman microscopy.

PubMed

Balss, Karin M; Long, Frederick H; Veselov, Vladimir; Orana, Argjenta; Akerman-Revis, Eugena; Papandreou, George; Maryanoff, Cynthia A

2008-07-01

Multivariate data analysis was applied to confocal Raman measurements on stents coated with the polymers and drug used in the CYPHER Sirolimus-eluting Coronary Stents. Partial least-squares (PLS) regression was used to establish three independent calibration curves for the coating constituents: sirolimus, poly(n-butyl methacrylate) [PBMA], and poly(ethylene-co-vinyl acetate) [PEVA]. The PLS calibrations were based on average spectra generated from each spatial location profiled. The PLS models were tested on six unknown stent samples to assess accuracy and precision. The wt % difference between PLS predictions and laboratory assay values for sirolimus was less than 1 wt % for the composite of the six unknowns, while the polymer models were estimated to be less than 0.5 wt % difference for the combined samples. The linearity and specificity of the three PLS models were also demonstrated with the three PLS models. In contrast to earlier univariate models, the PLS models achieved mass balance with better accuracy. This analysis was extended to evaluate the spatial distribution of the three constituents. Quantitative bitmap images of drug-eluting stent coatings are presented for the first time to assess the local distribution of components.

Dynamic fisheye grids for binary black hole simulations

NASA Astrophysics Data System (ADS)

Zilhão, Miguel; Noble, Scott C.

2014-03-01

We present a new warped gridding scheme adapted to simulating gas dynamics in binary black hole spacetimes. The grid concentrates grid points in the vicinity of each black hole to resolve the smaller scale structures there, and rarefies grid points away from each black hole to keep the overall problem size at a practical level. In this respect, our system can be thought of as a ‘double’ version of the fisheye coordinate system, used before in numerical relativity codes for evolving binary black holes. The gridding scheme is constructed as a mapping between a uniform coordinate system—in which the equations of motion are solved—to the distorted system representing the spatial locations of our grid points. Since we are motivated to eventually use this system for circumbinary disc calculations, we demonstrate how the distorted system can be constructed to asymptote to the typical spherical polar coordinate system, amenable to efficiently simulating orbiting gas flows about central objects with little numerical diffusion. We discuss its implementation in the Harm3d code, tailored to evolve the magnetohydrodynamics equations in curved spacetimes. We evaluate the performance of the system’s implementation in Harm3d with a series of tests, such as the advected magnetic field loop test, magnetized Bondi accretion, and evolutions of hydrodynamic discs about a single black hole and about a binary black hole. Like we have done with Harm3d, this gridding scheme can be implemented in other unigrid codes as a (possibly) simpler alternative to adaptive mesh refinement.

Establishing Extreme Dynamic Range with JWST: Decoding Smoke Signals in the Glare of a Wolf-Rayet Binary

NASA Astrophysics Data System (ADS)

Lau, Ryan; Hankins, M.; Kasliwal, M.; Sivaramakrishnan, A.; Thatte, D.

2017-11-01

Dust is a key ingredient in the formation of stars and planets. However, the dominant channels of dust production throughout cosmic time are still unclear. With its unprecedented sensitivity and spatial resolution in the mid-IR, the James Webb Space Telescope (JWST) is the ideal platform to address this issue by investigating the dust abundance, composition, and production rates of various dusty sources. In particular, colliding-wind Wolf-Rayet (WR) binaries are efficient dust producers in the local Universe, and likely existed in the earliest galaxies. To study these interesting objects, we propose JWST observations of the archetypal colliding-wind binary WR 140 to study its dust composition, abundance, and formation mechanisms. We will utilize two key JWST observing modes with the medium resolution spectrometer (MRS) on the Mid-Infrared Instrument (MIRI) and the Aperture Masking Interferometry (AMI) mode with the Near Infrared Imager and Slitless Spectrograph (NIRISS). Our proposed observations will yield high impact scientific results on the dust forming properties WR binaries, and establish a benchmark for key observing modes for imaging bright sources with faint extended emission. This will be valuable in various astrophysical contexts including mass-loss from evolved stars, dusty tori around active galactic nuclei, and protoplanetary disks. We are committed to designing and delivering science-enabling products for the JWST community that address technical issues such as bright source artifacts that will limit the maximum achievable image contrast.

Imaging accretion sources and circumbinary disks in young brown dwarfs

NASA Astrophysics Data System (ADS)

Reiners, Ansgar

2010-09-01

We propose to obtain deep WFC3/UVIS imaging observations of two accreting, nearby, young brown dwarf binaries. The first, 2M1207, is a brown dwarf with a planetary mass companion that became a benchmark in low-mass star formation and low-mass evolutionary models. The second, 2M0041, is a nearby young brown dwarf with clear evidence for accretion, but its space motion suggests a slightly higher age than the canonical accretion lifetime of 5-10 Myr. It has recently been discovered to be a binary and is likely to become a second benchmark object in this field. With narrow band images centered on the Halpha line that is indicative of accretion, we aim to determine the accretion ratio between the two components in each system. Halpha was observed in both systems but so far not spatially resolved. In particular, we want to search for accretion in the planetary mass companion of 2M1207. The evidence for accretion in 2M0041 and the possibility that it is in fact older than 10Myr suggests that the accretion lifetime is longer in brown dwarfs than in stars, and in particular that it is longer in brown dwarf binaries. Accretion could be sustained for a longer time if the accreting material is replenished by a circumbinary disk that might exist in both systems. We propose deep WFC/UVIS observations in the optical to search for circumbinary disks, similar to the famous disk around the binary TTauri system GG Tau.

The Orion Bullets: New GEMS MCAO images

NASA Astrophysics Data System (ADS)

Ginsburg, Adam; Bally, John; Youngblood, Allison

2013-07-01

The Orion A molecular cloud (OMC1) is the nearest site of massive star formation at a distance of 414 pc. The BN/KL region within it contains signs of a massive explosion triggered 500 years ago by decay of a non- hierarchical multiple system of massive stars. We present observations of the OMC1 core at high spatial resolution (<0.1") in narrow-band [Fe II] 1.64um and H2 S(1) 1-0 2.12um filters. The new data reveal compact (0.1" to 0.5") knots with unique excitation and chemical properties, unveiling new details about the three-dimensional structure of the explosion. Bright H2 emission from these compact, high proper-motion knots and compact [Fe II] features are consistent with scenario proposed by Bally et al. (2011) in which they are interpreted to be high density (n > 10^8 cm^{-3}) disk fragments launched from within a few AU of a massive star by a > three-body dynamical interaction that led to the ejection of the BN objects and the formation of a compact (separation < few AU) binary, most likely radio source I. The proper motions are as high as 400 km/s, hinting at the enormous energy unleashed in the explosion. The data also unveiled a population of obscured close binary systems. This new population will allow a comparison of embedded young binary systems with the older, un-obscured, visual binary population to test models of the evolution of multiplicity statistics in the Orion Nebula Cluster.

Stellar and Circumstellar Properties of the Pre-Main-Sequence Binary GV Tau from Infrared Spectroscopy

NASA Astrophysics Data System (ADS)

Doppmann, Greg W.; Najita, Joan R.; Carr, John S.

2008-09-01

We report spatially resolved spectroscopy of both components of the low-mass pre-main-sequence binary GV Tau. High-resolution spectroscopy in the K and L bands is used to characterize the stellar properties of the binary and to explore the nature of the circumstellar environment. We find that the southern component, GV Tau S, is a radial velocity variable, possibly as a result of an unseen low-mass companion. The strong warm gaseous HCN absorption reported previously by Gibb and coworkers toward GV Tau S was not present during the epoch of our observations. Instead, we detect warm (~500 K) molecular absorption with similar properties toward the northern infrared companion, GV Tau N. At the epoch of our observations, the absorbing gas toward GV Tau N was approximately at the radial velocity of the GV Tau molecular envelope, but it was redshifted with respect to the star by ~13 km s-1. One interpretation of our results is that GV Tau N is also a binary and that most of the warm molecular absorption arises in a circumbinary disk viewed close to edge-on. Data presented herein were obtained at the W. M. Keck Observatory from telescope time allocated to the National Aeronautics and Space Administration through the agency's scientific partnership with the California Institute of Technology and the University of California. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

X-ray Binaries in the Galaxy and the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Cowley, Anne P.

1993-05-01

For more than two decades astronomers have been aware that the most X-ray luminous stellar sources (L_x > 10(35) erg s(-1) ) are interacting binaries where one component is a neutron star or black hole. While other types of single and multiple stars are known X-ray sources, none compare in X-ray luminosity with the ``classical" X-ray binaries. In these systems X-ray emission results from accretion of material from a non-degenerate companion onto the compact star through several alternate mechanisms including Roche lobe overflow, stellar winds, or periastron effects in non-circular orbits. It has been recognized for many years that X-ray binaries divide into two broad groups, characterized primarily by the mass of the non-degenerate star: 1) massive X-ray binaries (MXRB), in which the optical primary is a bright, early-type star, and 2) low-mass X-ray binaries (LMXB), where a lower main-sequence or subgiant star is the mass donor. A broad variety of observational characteristics further subdivide these classes. In the Galaxy these two groups appear to be spatially and kinematically associated with the disk and the halo populations, respectively. A few dozen MXRB are known in the Galaxy. A great deal of information about their physical properties has been learned from observational study. Their optical primaries can be investigated by conventional techniques. Furthermore, most MXRB contain X-ray pulsars, allowing accurate determination of their orbital parameters. From these data masses have been determined for the neutron stars, all of which are ~ 1.4 Msun, within measurement errors. By contrast, the LMXB have been much more difficult to study. Although there are ~ 150 LMXB in the Galaxy, most are distant and faint, requiring use of large telescopes for their study. Their optical light is almost always dominated by an accretion disk, rather than the mass-losing star, making interpretation of their spectral and photometric properties difficult. Their often uncertain distances further complicate our understanding. Thus, although the galactic LMXB greatly outnumber the MXRB, they are much less well understood. The X-ray binaries in the Magellanic Clouds in many ways make an ideal laboratory because they are all at the same, known distance. However, at the present time only a handful of X-ray binaries are known with certainty in these galaxies -- 7 in the LMC and 1 in the SMC. Only 3 of the LMC sources are low-mass X-ray binaries, and their properties are quite different from ``typical" galactic LMXB. In this review we will outline the general properties of X-ray binaries and summarize what types of information we have learned from their study over a wide range of wavelengths. An overall comparison of the global properties of X-ray binaries in the Galaxy and the Magellanic Clouds will be given.

VISUAL DATA MINING IN ATMOSPHERIC SCIENCE DATA

EPA Science Inventory

This paper discusses the use of simple visual tools to explore multivariate spatially-referenced data. It describes interactive approaches such as linked brushing, and dynamic methods such as the grand tour. applied to studying the Comprehensive Ocean-Atmosphere Data Set (COADS)....

An Interactive Visual Analytics Framework for Multi-Field Data in a Geo-Spatial Context

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

Zhang, Zhiyuan; Tong, Xiaonan; McDonnell, Kevin T.

2013-04-01

Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a multi field visualization problem, where the geospace provides the expanse of the field. However, there is a limit on the amount of multivariate information that can be fit within a certain spatial location, and the use of linked multivari ate information displays has previously been devised to bridge this gap. In this paper we focus on the interactions in the geographical display, present an implementationmore » that uses Google Earth, and demonstrate it within a tightly linked parallel coordinates display. Several other visual representations, such as pie and bar charts are integrated into the Google Earth display and can be interactively manipulated. Further, we also demonstrate new brushing and visualization techniques for parallel coordinates, such as fixedwindow brushing and correlationenhanced display. We conceived our system with a team of climate researchers, who already made a few important discov eries using it. This demonstrates our system’s great potential to enable scientific discoveries, possibly also in oth er domains where data have a geospatial reference.« less

Spatial Elucidation of Spinal Cord Lipid- and Metabolite- Regulations in Amyotrophic Lateral Sclerosis

NASA Astrophysics Data System (ADS)

Hanrieder, Jörg; Ewing, Andrew G.

2014-06-01

Amyotrophic lateral sclerosis (ALS) is a devastating, rapidly progressing disease of the central nervous system that is characterized by motor neuron degeneration in the brain stem and the spinal cord. We employed time of flight secondary ion mass spectrometry (ToF-SIMS) to profile spatial lipid- and metabolite- regulations in post mortem human spinal cord tissue from ALS patients to investigate chemical markers of ALS pathogenesis. ToF-SIMS scans and multivariate analysis of image and spectral data were performed on thoracic human spinal cord sections. Multivariate statistics of the image data allowed delineation of anatomical regions of interest based on their chemical identity. Spectral data extracted from these regions were compared using two different approaches for multivariate statistics, for investigating ALS related lipid and metabolite changes. The results show a significant decrease for cholesterol, triglycerides, and vitamin E in the ventral horn of ALS samples, which is presumably a consequence of motor neuron degeneration. Conversely, the biogenic mediator lipid lysophosphatidylcholine and its fragments were increased in ALS ventral spinal cord, pointing towards neuroinflammatory mechanisms associated with neuronal cell death. ToF-SIMS imaging is a promising approach for chemical histology and pathology for investigating the subcellular mechanisms underlying motor neuron degeneration in amyotrophic lateral sclerosis.

Decoding complex flow-field patterns in visual working memory.

PubMed

Christophel, Thomas B; Haynes, John-Dylan

2014-05-01

There has been a long history of research on visual working memory. Whereas early studies have focused on the role of lateral prefrontal cortex in the storage of sensory information, this has been challenged by research in humans that has directly assessed the encoding of perceptual contents, pointing towards a role of visual and parietal regions during storage. In a previous study we used pattern classification to investigate the storage of complex visual color patterns across delay periods. This revealed coding of such contents in early visual and parietal brain regions. Here we aim to investigate whether the involvement of visual and parietal cortex is also observable for other types of complex, visuo-spatial pattern stimuli. Specifically, we used a combination of fMRI and multivariate classification to investigate the retention of complex flow-field stimuli defined by the spatial patterning of motion trajectories of random dots. Subjects were trained to memorize the precise spatial layout of these stimuli and to retain this information during an extended delay. We used a multivariate decoding approach to identify brain regions where spatial patterns of activity encoded the memorized stimuli. Content-specific memory signals were observable in motion sensitive visual area MT+ and in posterior parietal cortex that might encode spatial information in a modality independent manner. Interestingly, we also found information about the memorized visual stimulus in somatosensory cortex, suggesting a potential crossmodal contribution to memory. Our findings thus indicate that working memory storage of visual percepts might be distributed across unimodal, multimodal and even crossmodal brain regions. Copyright © 2014 Elsevier Inc. All rights reserved.

In-vivo detection of binary PKA network interactions upon activation of endogenous GPCRs

PubMed Central

Röck, Ruth; Bachmann, Verena; Bhang, Hyo-eun C; Malleshaiah, Mohan; Raffeiner, Philipp; Mayrhofer, Johanna E; Tschaikner, Philipp M; Bister, Klaus; Aanstad, Pia; Pomper, Martin G; Michnick, Stephen W; Stefan, Eduard

2015-01-01

Membrane receptor-sensed input signals affect and modulate intracellular protein-protein interactions (PPIs). Consequent changes occur to the compositions of protein complexes, protein localization and intermolecular binding affinities. Alterations of compartmentalized PPIs emanating from certain deregulated kinases are implicated in the manifestation of diseases such as cancer. Here we describe the application of a genetically encoded Protein-fragment Complementation Assay (PCA) based on the Renilla Luciferase (Rluc) enzyme to compare binary PPIs of the spatially and temporally controlled protein kinase A (PKA) network in diverse eukaryotic model systems. The simplicity and sensitivity of this cell-based reporter allows for real-time recordings of mutually exclusive PPIs of PKA upon activation of selected endogenous G protein-coupled receptors (GPCRs) in cancer cells, xenografts of mice, budding yeast, and zebrafish embryos. This extends the application spectrum of Rluc PCA for the quantification of PPI-based receptor-effector relationships in physiological and pathological model systems. PMID:26099953

Dynamics and universal scaling law in geometrically-controlled sessile drop evaporation

PubMed Central

Sáenz, P. J.; Wray, A. W.; Che, Z.; Matar, O. K.; Valluri, P.; Kim, J.; Sefiane, K.

2017-01-01

The evaporation of a liquid drop on a solid substrate is a remarkably common phenomenon. Yet, the complexity of the underlying mechanisms has constrained previous studies to spherically symmetric configurations. Here we investigate well-defined, non-spherical evaporating drops of pure liquids and binary mixtures. We deduce a universal scaling law for the evaporation rate valid for any shape and demonstrate that more curved regions lead to preferential localized depositions in particle-laden drops. Furthermore, geometry induces well-defined flow structures within the drop that change according to the driving mechanism. In the case of binary mixtures, geometry dictates the spatial segregation of the more volatile component as it is depleted. Our results suggest that the drop geometry can be exploited to prescribe the particle deposition and evaporative dynamics of pure drops and the mixing characteristics of multicomponent drops, which may be of interest to a wide range of industrial and scientific applications. PMID:28294114

Superlattices assembled through shape-induced directional binding

NASA Astrophysics Data System (ADS)

Lu, Fang; Yager, Kevin G.; Zhang, Yugang; Xin, Huolin; Gang, Oleg

2015-04-01

Organization of spherical particles into lattices is typically driven by packing considerations. Although the addition of directional binding can significantly broaden structural diversity, nanoscale implementation remains challenging. Here we investigate the assembly of clusters and lattices in which anisotropic polyhedral blocks coordinate isotropic spherical nanoparticles via shape-induced directional interactions facilitated by DNA recognition. We show that these polyhedral blocks--cubes and octahedrons--when mixed with spheres, promote the assembly of clusters with architecture determined by polyhedron symmetry. Moreover, three-dimensional binary superlattices are formed when DNA shells accommodate the shape disparity between nanoparticle interfaces. The crystallographic symmetry of assembled lattices is determined by the spatial symmetry of the block's facets, while structural order depends on DNA-tuned interactions and particle size ratio. The presented lattice assembly strategy, exploiting shape for defining the global structure and DNA-mediation locally, opens novel possibilities for by-design fabrication of binary lattices.

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

Lu, Fang; Yager, Kevin G.; Zhang, Yugang

Organization of spherical particles into lattices is typically driven by packing considerations. Although the addition of directional binding can significantly broaden structural diversity, nanoscale implementation remains challenging. Here we investigate the assembly of clusters and lattices in which anisotropic polyhedral blocks coordinate isotropic spherical nanoparticles via shape-induced directional interactions facilitated by DNA recognition. We show that these polyhedral blocks—cubes and octahedrons—when mixed with spheres, promote the assembly of clusters with architecture determined by polyhedron symmetry. Moreover, three-dimensional binary superlattices are formed when DNA shells accommodate the shape disparity between nanoparticle interfaces. The crystallographic symmetry of assembled lattices is determined bymore » the spatial symmetry of the block’s facets, while structural order depends on DNA-tuned interactions and particle size ratio. Lastly, the presented lattice assembly strategy, exploiting shape for defining the global structure and DNA-mediation locally, opens novel possibilities for by-design fabrication of binary lattices.« less

Superlattices assembled through shape-induced directional binding

DOE PAGES

Lu, Fang; Yager, Kevin G.; Zhang, Yugang; ...

2015-04-23

Organization of spherical particles into lattices is typically driven by packing considerations. Although the addition of directional binding can significantly broaden structural diversity, nanoscale implementation remains challenging. Here we investigate the assembly of clusters and lattices in which anisotropic polyhedral blocks coordinate isotropic spherical nanoparticles via shape-induced directional interactions facilitated by DNA recognition. We show that these polyhedral blocks—cubes and octahedrons—when mixed with spheres, promote the assembly of clusters with architecture determined by polyhedron symmetry. Moreover, three-dimensional binary superlattices are formed when DNA shells accommodate the shape disparity between nanoparticle interfaces. The crystallographic symmetry of assembled lattices is determined bymore » the spatial symmetry of the block’s facets, while structural order depends on DNA-tuned interactions and particle size ratio. Lastly, the presented lattice assembly strategy, exploiting shape for defining the global structure and DNA-mediation locally, opens novel possibilities for by-design fabrication of binary lattices.« less

Dimensional regularization of the IR divergences in the Fokker action of point-particle binaries at the fourth post-Newtonian order

NASA Astrophysics Data System (ADS)

Bernard, Laura; Blanchet, Luc; Bohé, Alejandro; Faye, Guillaume; Marsat, Sylvain

2017-11-01

The Fokker action of point-particle binaries at the fourth post-Newtonian (4PN) approximation of general relativity has been determined previously. However two ambiguity parameters associated with infrared (IR) divergencies of spatial integrals had to be introduced. These two parameters were fixed by comparison with gravitational self-force (GSF) calculations of the conserved energy and periastron advance for circular orbits in the test-mass limit. In the present paper together with a companion paper, we determine both these ambiguities from first principle, by means of dimensional regularization. Our computation is thus entirely defined within the dimensional regularization scheme, for treating at once the IR and ultra-violet (UV) divergencies. In particular, we obtain crucial contributions coming from the Einstein-Hilbert part of the action and from the nonlocal tail term in arbitrary dimensions, which resolve the ambiguities.

Dynamics and universal scaling law in geometrically-controlled sessile drop evaporation.

PubMed

Sáenz, P J; Wray, A W; Che, Z; Matar, O K; Valluri, P; Kim, J; Sefiane, K

2017-03-15

The evaporation of a liquid drop on a solid substrate is a remarkably common phenomenon. Yet, the complexity of the underlying mechanisms has constrained previous studies to spherically symmetric configurations. Here we investigate well-defined, non-spherical evaporating drops of pure liquids and binary mixtures. We deduce a universal scaling law for the evaporation rate valid for any shape and demonstrate that more curved regions lead to preferential localized depositions in particle-laden drops. Furthermore, geometry induces well-defined flow structures within the drop that change according to the driving mechanism. In the case of binary mixtures, geometry dictates the spatial segregation of the more volatile component as it is depleted. Our results suggest that the drop geometry can be exploited to prescribe the particle deposition and evaporative dynamics of pure drops and the mixing characteristics of multicomponent drops, which may be of interest to a wide range of industrial and scientific applications.

Primary radiation damage of an FeCr alloy under pressure: Atomistic simulation

NASA Astrophysics Data System (ADS)

Tikhonchev, M. Yu.; Svetukhin, V. V.

2017-05-01

The primary radiation damage of a binary FeCr alloy deformed by applied mechanical loading is studied by an atomistic molecular dynamics simulation. Loading is simulated by specifying an applied pressure of 0.25, 1.0, and 2.5 GPa of both signs. Hydrostatic and uniaxial loading is considered along the [001], [111], [112], and [210] directions. The influence of loading on the energy of point defect formation and the threshold atomic displacement energy in single-component bcc iron is investigated. The 10-keV atomic displacement cascades in a "random" binary Fe-9 at % Cr alloy are simulated at an initial temperature of 300 K. The number of the point defects generated in a cascade is estimated, and the clustering of point defects and the spatial orientation of interstitial configurations are analyzed. Our results agree with the results of other researchers and supplement them.

Socio-economic Correlates of Malnutrition among Married Women in Bangladesh.

PubMed

Mostafa Kamal, S M; Md Aynul, Islam

2010-12-01

This paper examines the prevalence and socio-economic correlates of malnutrition among ever married non-pregnant women of reproductive age of Bangladesh using a nationally representative weighted sample of 10,145. Body mass index was used to measure nutritional status. Both bivariate and multivariate statistical analyses were employed to assess the relationship between socio-economic characteristics and women's nutritional status. Overall, 28.5% of the women were found to be underweight. The fixed effect multivariate binary logistic regression analysis yielded significantly increased risk of underweight for the young, currently working, non-Muslim, rural residents, widowed, divorced or separated women. Significant wide variations of malnourishment prevailed in the administrative regions of the country. Wealth index and women's education were the most important determinants of underweight. The multivariate logistic regression analysis revealed that the risk of being underweight was almost seven times higher (OR=6.76, 95% CI=5.20-8.80) among women with no formal education as compared to those with higher education and the likelihood of underweight was significantly (p<0.001) 5.2 times (OR=5.23, 95% CI=4.51-6.07) in the poorest as compared to their richest counterparts. Poverty alleviation programmes should be strengthened targeting the poor. Effective policies, information and health education programmes for women are required to ensure adequate access to health services and for them to understand the components of a healthy diet.

Risk prediction for myocardial infarction via generalized functional regression models.

PubMed

Ieva, Francesca; Paganoni, Anna M

2016-08-01

In this paper, we propose a generalized functional linear regression model for a binary outcome indicating the presence/absence of a cardiac disease with multivariate functional data among the relevant predictors. In particular, the motivating aim is the analysis of electrocardiographic traces of patients whose pre-hospital electrocardiogram (ECG) has been sent to 118 Dispatch Center of Milan (the Italian free-toll number for emergencies) by life support personnel of the basic rescue units. The statistical analysis starts with a preprocessing of ECGs treated as multivariate functional data. The signals are reconstructed from noisy observations. The biological variability is then removed by a nonlinear registration procedure based on landmarks. Thus, in order to perform a data-driven dimensional reduction, a multivariate functional principal component analysis is carried out on the variance-covariance matrix of the reconstructed and registered ECGs and their first derivatives. We use the scores of the Principal Components decomposition as covariates in a generalized linear model to predict the presence of the disease in a new patient. Hence, a new semi-automatic diagnostic procedure is proposed to estimate the risk of infarction (in the case of interest, the probability of being affected by Left Bundle Brunch Block). The performance of this classification method is evaluated and compared with other methods proposed in literature. Finally, the robustness of the procedure is checked via leave-j-out techniques. © The Author(s) 2013.

Multivariate flood risk assessment: reinsurance perspective

NASA Astrophysics Data System (ADS)

Ghizzoni, Tatiana; Ellenrieder, Tobias

2013-04-01

For insurance and re-insurance purposes the knowledge of the spatial characteristics of fluvial flooding is fundamental. The probability of simultaneous flooding at different locations during one event and the associated severity and losses have to be estimated in order to assess premiums and for accumulation control (Probable Maximum Losses calculation). Therefore, the identification of a statistical model able to describe the multivariate joint distribution of flood events in multiple location is necessary. In this context, copulas can be viewed as alternative tools for dealing with multivariate simulations as they allow to formalize dependence structures of random vectors. An application of copula function for flood scenario generation is presented for Australia (Queensland, New South Wales and Victoria) where 100.000 possible flood scenarios covering approximately 15.000 years were simulated.

Comparative study of the efficiency of computed univariate and multivariate methods for the estimation of the binary mixture of clotrimazole and dexamethasone using two different spectral regions

NASA Astrophysics Data System (ADS)

Fayez, Yasmin Mohammed; Tawakkol, Shereen Mostafa; Fahmy, Nesma Mahmoud; Lotfy, Hayam Mahmoud; Shehata, Mostafa Abdel-Aty

2018-04-01

Three methods of analysis are conducted that need computational procedures by the Matlab® software. The first is the univariate mean centering method which eliminates the interfering signal of the one component at a selected wave length leaving the amplitude measured to represent the component of interest only. The other two multivariate methods named PLS and PCR depend on a large number of variables that lead to extraction of the maximum amount of information required to determine the component of interest in the presence of the other. Good accurate and precise results are obtained from the three methods for determining clotrimazole in the linearity range 1-12 μg/mL and 75-550 μg/mL with dexamethasone acetate 2-20 μg/mL in synthetic mixtures and pharmaceutical formulation using two different spectral regions 205-240 nm and 233-278 nm. The results obtained are compared statistically to each other and to the official methods.

A dependence modelling study of extreme rainfall in Madeira Island

NASA Astrophysics Data System (ADS)

Gouveia-Reis, Délia; Guerreiro Lopes, Luiz; Mendonça, Sandra

2016-08-01

The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.

Unmet/met need for contraception and self-reported abortion in Ghana.

PubMed

Amo-Adjei, Joshua; Darteh, Eugene K M

2017-10-01

Unmet need for contraception in several sub-Saharan African countries, including Ghana, remains high, with implications for unintended pregnancies and unsafe abortion, associated maternal morbidity and mortality. In this paper, we analysed for any associations between unmet/met need for contraception and the prevalence of abortion. The paper utilizes the 2014 Ghana Demographic Health Survey dataset. Applying descriptive statistics initially, and later, a binary logistic regression, we estimate two different models, taking into account, unmet/met need for contraception (Model 1) and a multivariable one comprising socioeconomic, spatial, cultural and demographic behaviour variables (Model 2) to test the associations between unmet/met need for contraception in Ghana. One-fourth (25%) of sampled women in 2014 had ever had an abortion. The bivariate results showed that women who reported "no unmet" considerably tended to report abortion more than the reference category - not married and no sex in the last 30days. The elevated odds among respondents who indicated "no unmet need" persisted even after controlling for all the relevant confounders. Relatedly, unlike women with an unmet need for spacing, women who desired to limit childbearing had a slightly higher tendency to report an abortion. The linkage between unmet need for contraception appears more complex, particularly when the connections are explored post-abortion. Thus, while an abortion episode is most likely due to unintended pregnancy, contraception may still not be used, after an abortion, probably because of failure, side effects or simply, a dislike for any method. Copyright © 2017 Elsevier B.V. All rights reserved.

Multivariate quantum memory as controllable delayed multi-port beamsplitter

NASA Astrophysics Data System (ADS)

Vetlugin, A. N.; Sokolov, I. V.

2016-03-01

The addressability of parallel spatially multimode quantum memory for light allows one to control independent collective spin waves within the same cold atomic ensemble. Generally speaking, there are transverse and longitudinal degrees of freedom of the memory that one can address by a proper choice of the pump (control) field spatial pattern. Here we concentrate on the mutual evolution and transformation of quantum states of the longitudinal modes of collective spin coherence in the cavity-based memory scheme. We assume that these modes are coherently controlled by the pump waves of the on-demand transverse profile, that is, by the superpositions of waves propagating in the directions close to orthogonal to the cavity axis. By the write-in, this allows one to couple a time sequence of the incoming quantized signals to a given set of superpositions of orthogonal spin waves. By the readout, one can retrieve quantum states of the collective spin waves that are controllable superpositions of the initial ones and are coupled on demand to the output signal sequence. In a general case, the memory is able to operate as a controllable delayed multi-port beamsplitter, capable of transformation of the delays, the durations and time shapes of signals in the sequence. We elaborate the theory of such light-matter interface for the spatially multivariate cavity-based off-resonant Raman-type quantum memory. Since, in order to speed up the manipulation of complex signals in multivariate memories, it might be of interest to store relatively short light pulses of a given time shape, we also address some issues of the cavity-based memory operation beyond the bad cavity limit.

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

NASA Astrophysics Data System (ADS)

Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun

2018-02-01

It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

Comparison of Multivariate Spatial Dependence Structures of DPIL and Flowmeter Hydraulic Conductivity Data Sets at the MADE Site

NASA Astrophysics Data System (ADS)

Xiao, B.; Haslauer, C. P.; Bohling, G. C.; Bárdossy, A.

2017-12-01

The spatial arrangement of hydraulic conductivity (K) determines water flow and solute transport behaviour in groundwater systems. This presentation demonstrates three advances over commonly used geostatistical methods by integrating measurements from novel measurement techniques and novel multivariate non-Gaussian dependence models: The spatial dependence structure of K was analysed using both data sets of K. Previously encountered similarities were confirmed in low-dimensional dependence. These similarities become less stringent and deviate more from symmetric Gaussian dependence in dimensions larger than two. Measurements of small and large K values are more uncertain than medium K values due to decreased sensitivity of the measurement devices at both ends of the K scale. Nevertheless, these measurements contain useful information that we include in the estimation of the marginal distribution and the spatial dependence structure as ``censored measurements'' that are estimated jointly without the common assumption of independence. The spatial dependence structure of the two data sets and their cross-covariances are used to infer the spatial dependence and the amount of the bias between the two data sets. By doing so, one spatial model for K is constructed that is used for simulation and that reflects the characteristics of both measurement techniques. The concept of the presented methodology is to use all available information for the estimation of a stochastic model of the primary parameter (K) at the highly heterogeneous Macrodispersion Experiment (MADE) site. The primary parameter has been measured by two independent measurement techniques whose sets of locations do not overlap. This site offers the unique opportunity of large quantities of measurements of K (31123 direct push injection logging based measurements and 2611 flowmeter based measurements). This improved dependence structure of K will be included into the estimated non-Gaussian dependence models and is expected to reproduce observed solute concentrations at the site better than existing dependence models of K.

Optimal sensor placement for spatial lattice structure based on genetic algorithms

NASA Astrophysics Data System (ADS)

Liu, Wei; Gao, Wei-cheng; Sun, Yi; Xu, Min-jian

2008-10-01

Optimal sensor placement technique plays a key role in structural health monitoring of spatial lattice structures. This paper considers the problem of locating sensors on a spatial lattice structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterized. Based on the criterion of optimal sensor placement for modal test, an improved genetic algorithm is introduced to find the optimal placement of sensors. The modal strain energy (MSE) and the modal assurance criterion (MAC) have been taken as the fitness function, respectively, so that three placement designs were produced. The decimal two-dimension array coding method instead of binary coding method is proposed to code the solution. Forced mutation operator is introduced when the identical genes appear via the crossover procedure. A computational simulation of a 12-bay plain truss model has been implemented to demonstrate the feasibility of the three optimal algorithms above. The obtained optimal sensor placements using the improved genetic algorithm are compared with those gained by exiting genetic algorithm using the binary coding method. Further the comparison criterion based on the mean square error between the finite element method (FEM) mode shapes and the Guyan expansion mode shapes identified by data-driven stochastic subspace identification (SSI-DATA) method are employed to demonstrate the advantage of the different fitness function. The results showed that some innovations in genetic algorithm proposed in this paper can enlarge the genes storage and improve the convergence of the algorithm. More importantly, the three optimal sensor placement methods can all provide the reliable results and identify the vibration characteristics of the 12-bay plain truss model accurately.

Opinion strength influences the spatial dynamics of opinion formation

PubMed Central

Baumgaertner, Bert O.; Tyson, Rebecca T.; Krone, Stephen M.

2016-01-01

Opinions are rarely binary; they can be held with different degrees of conviction, and this expanded attitude spectrum can affect the influence one opinion has on others. Our goal is to understand how different aspects of influence lead to recognizable spatio-temporal patterns of opinions and their strengths. To do this, we introduce a stochastic spatial agent-based model of opinion dynamics that includes a spectrum of opinion strengths and various possible rules for how the opinion strength of one individual affects the influence that this individual has on others. Through simulations, we find that even a small amount of amplification of opinion strength through interaction with like-minded neighbors can tip the scales in favor of polarization and deadlock. PMID:28529381

BOREAS Level-1B TIMS Imagery: At-sensor Radiance in BSQ Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Strub, Richard; Newcomer, Jeffrey A.; Chernobieff, Sonia

2000-01-01

The Boreal Ecosystem-Atmospheric Study (BOREAS) Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. For BOREAS, the Thermal Infrared Multispectral Scanner (TIMS) imagery, along with other aircraft images, was collected to provide spatially extensive information over the primary study areas. The Level-1b TIMS images cover the time periods of 16 to 20 Apr 1994 and 06 to 17 Sep 1994. The system calibrated images are stored in binary image format files. The TIMS images are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Electrode channel selection based on backtracking search optimization in motor imagery brain-computer interfaces.

PubMed

Dai, Shengfa; Wei, Qingguo

2017-01-01

Common spatial pattern algorithm is widely used to estimate spatial filters in motor imagery based brain-computer interfaces. However, use of a large number of channels will make common spatial pattern tend to over-fitting and the classification of electroencephalographic signals time-consuming. To overcome these problems, it is necessary to choose an optimal subset of the whole channels to save computational time and improve the classification accuracy. In this paper, a novel method named backtracking search optimization algorithm is proposed to automatically select the optimal channel set for common spatial pattern. Each individual in the population is a N-dimensional vector, with each component representing one channel. A population of binary codes generate randomly in the beginning, and then channels are selected according to the evolution of these codes. The number and positions of 1's in the code denote the number and positions of chosen channels. The objective function of backtracking search optimization algorithm is defined as the combination of classification error rate and relative number of channels. Experimental results suggest that higher classification accuracy can be achieved with much fewer channels compared to standard common spatial pattern with whole channels.

How Math Anxiety Relates to Number-Space Associations.

PubMed

Georges, Carrie; Hoffmann, Danielle; Schiltz, Christine

2016-01-01

Given the considerable prevalence of math anxiety, it is important to identify the factors contributing to it in order to improve mathematical learning. Research on math anxiety typically focusses on the effects of more complex arithmetic skills. Recent evidence, however, suggests that deficits in basic numerical processing and spatial skills also constitute potential risk factors of math anxiety. Given these observations, we determined whether math anxiety also depends on the quality of spatial-numerical associations. Behavioral evidence for a tight link between numerical and spatial representations is given by the SNARC (spatial-numerical association of response codes) effect, characterized by faster left-/right-sided responses for small/large digits respectively in binary classification tasks. We compared the strength of the SNARC effect between high and low math anxious individuals using the classical parity judgment task in addition to evaluating their spatial skills, arithmetic performance, working memory and inhibitory control. Greater math anxiety was significantly associated with stronger spatio-numerical interactions. This finding adds to the recent evidence supporting a link between math anxiety and basic numerical abilities and strengthens the idea that certain characteristics of low-level number processing such as stronger number-space associations constitute a potential risk factor of math anxiety.

How Math Anxiety Relates to Number–Space Associations

PubMed Central

Georges, Carrie; Hoffmann, Danielle; Schiltz, Christine

2016-01-01

Given the considerable prevalence of math anxiety, it is important to identify the factors contributing to it in order to improve mathematical learning. Research on math anxiety typically focusses on the effects of more complex arithmetic skills. Recent evidence, however, suggests that deficits in basic numerical processing and spatial skills also constitute potential risk factors of math anxiety. Given these observations, we determined whether math anxiety also depends on the quality of spatial-numerical associations. Behavioral evidence for a tight link between numerical and spatial representations is given by the SNARC (spatial-numerical association of response codes) effect, characterized by faster left-/right-sided responses for small/large digits respectively in binary classification tasks. We compared the strength of the SNARC effect between high and low math anxious individuals using the classical parity judgment task in addition to evaluating their spatial skills, arithmetic performance, working memory and inhibitory control. Greater math anxiety was significantly associated with stronger spatio-numerical interactions. This finding adds to the recent evidence supporting a link between math anxiety and basic numerical abilities and strengthens the idea that certain characteristics of low-level number processing such as stronger number–space associations constitute a potential risk factor of math anxiety. PMID:27683570

Probabilistic Model for Laser Damage to the Human Retina

DTIC Science & Technology

2012-03-01

the beam. Power density may be measured in radiant exposure, J cm2 , or by irradiance , W cm2 . In the experimental database used in this study and...to quan- tify a binary response, either lethal or non-lethal, within a population such as insects or rats. In directed energy research, probit...value of the normalized Arrhenius damage integral. In a one-dimensional simulation, the source term is determined as a spatially averaged irradiance (W

Speckle-learning-based object recognition through scattering media.

PubMed

Ando, Takamasa; Horisaki, Ryoichi; Tanida, Jun

2015-12-28

We experimentally demonstrated object recognition through scattering media based on direct machine learning of a number of speckle intensity images. In the experiments, speckle intensity images of amplitude or phase objects on a spatial light modulator between scattering plates were captured by a camera. We used the support vector machine for binary classification of the captured speckle intensity images of face and non-face data. The experimental results showed that speckles are sufficient for machine learning.

Iao: The New Adaptive Optics Visible Imaging and Photometric System for AEOS

DTIC Science & Technology

2008-09-01

observations of binary stars, asteroids and planets such as Mercury and Mars [2,3,4]. The Visible Imager is also used to take time resolved photometry ...role it takes high spatial resolution imagery of resolved targets. These targets are primarily low Earth orbiting satellites acquired for the...albedo pattern: Comparing the AEOS and TES data sets [5] D.T. Hall et al. 2007, Journal of Spacecraft and Rockets, 44, 910-919, Time - Resolved I-Band

Computer Generated Holography with Intensity-Graded Patterns

PubMed Central

Conti, Rossella; Assayag, Osnath; de Sars, Vincent; Guillon, Marc; Emiliani, Valentina

2016-01-01

Computer Generated Holography achieves patterned illumination at the sample plane through phase modulation of the laser beam at the objective back aperture. This is obtained by using liquid crystal-based spatial light modulators (LC-SLMs), which modulate the spatial phase of the incident laser beam. A variety of algorithms is employed to calculate the phase modulation masks addressed to the LC-SLM. These algorithms range from simple gratings-and-lenses to generate multiple diffraction-limited spots, to iterative Fourier-transform algorithms capable of generating arbitrary illumination shapes perfectly tailored on the base of the target contour. Applications for holographic light patterning include multi-trap optical tweezers, patterned voltage imaging and optical control of neuronal excitation using uncaging or optogenetics. These past implementations of computer generated holography used binary input profile to generate binary light distribution at the sample plane. Here we demonstrate that using graded input sources, enables generating intensity graded light patterns and extend the range of application of holographic light illumination. At first, we use intensity-graded holograms to compensate for LC-SLM position dependent diffraction efficiency or sample fluorescence inhomogeneity. Finally we show that intensity-graded holography can be used to equalize photo evoked currents from cells expressing different levels of chanelrhodopsin2 (ChR2), one of the most commonly used optogenetics light gated channels, taking into account the non-linear dependence of channel opening on incident light. PMID:27799896

Visualizing excipient composition and homogeneity of Compound Liquorice Tablets by near-infrared chemical imaging

NASA Astrophysics Data System (ADS)

Wu, Zhisheng; Tao, Ou; Cheng, Wei; Yu, Lu; Shi, Xinyuan; Qiao, Yanjiang

2012-02-01

This study demonstrated that near-infrared chemical imaging (NIR-CI) was a promising technology for visualizing the spatial distribution and homogeneity of Compound Liquorice Tablets. The starch distribution (indirectly, plant extraction) could be spatially determined using basic analysis of correlation between analytes (BACRA) method. The correlation coefficients between starch spectrum and spectrum of each sample were greater than 0.95. Depending on the accurate determination of starch distribution, a method to determine homogeneous distribution was proposed by histogram graph. The result demonstrated that starch distribution in sample 3 was relatively heterogeneous according to four statistical parameters. Furthermore, the agglomerates domain in each tablet was detected using score image layers of principal component analysis (PCA) method. Finally, a novel method named Standard Deviation of Macropixel Texture (SDMT) was introduced to detect agglomerates and heterogeneity based on binary image. Every binary image was divided into different sizes length of macropixel and the number of zero values in each macropixel was counted to calculate standard deviation. Additionally, a curve fitting graph was plotted on the relationship between standard deviation and the size length of macropixel. The result demonstrated the inter-tablet heterogeneity of both starch and total compounds distribution, simultaneously, the similarity of starch distribution and the inconsistency of total compounds distribution among intra-tablet were signified according to the value of slope and intercept parameters in the curve.

A Columnar Storage Strategy with Spatiotemporal Index for Big Climate Data

NASA Astrophysics Data System (ADS)

Hu, F.; Bowen, M. K.; Li, Z.; Schnase, J. L.; Duffy, D.; Lee, T. J.; Yang, C. P.

2015-12-01

Large collections of observational, reanalysis, and climate model output data may grow to as large as a 100 PB in the coming years, so climate dataset is in the Big Data domain, and various distributed computing frameworks have been utilized to address the challenges by big climate data analysis. However, due to the binary data format (NetCDF, HDF) with high spatial and temporal dimensions, the computing frameworks in Apache Hadoop ecosystem are not originally suited for big climate data. In order to make the computing frameworks in Hadoop ecosystem directly support big climate data, we propose a columnar storage format with spatiotemporal index to store climate data, which will support any project in the Apache Hadoop ecosystem (e.g. MapReduce, Spark, Hive, Impala). With this approach, the climate data will be transferred into binary Parquet data format, a columnar storage format, and spatial and temporal index will be built and attached into the end of Parquet files to enable real-time data query. Then such climate data in Parquet data format could be available to any computing frameworks in Hadoop ecosystem. The proposed approach is evaluated using the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. Experimental results show that this approach could efficiently overcome the gap between the big climate data and the distributed computing frameworks, and the spatiotemporal index could significantly accelerate data querying and processing.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

PubMed

Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

2014-07-21

Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately.

Quality issues in blue noise halftoning

NASA Astrophysics Data System (ADS)

Yu, Qing; Parker, Kevin J.

1998-01-01

The blue noise mask (BNM) is a halftone screen that produces unstructured visually pleasing dot patterns. The BNM combines the blue-noise characteristics of error diffusion and the simplicity of ordered dither. A BNM is constructed by designing a set of interdependent binary patterns for individual gray levels. In this paper, we investigate the quality issues in blue-noise binary pattern design and mask generation as well as in application to color reproduction. Using a global filtering technique and a local 'force' process for rearranging black and white pixels, we are able to generate a series of binary patterns, all representing a certain gray level, ranging from white-noise pattern to highly structured pattern. The quality of these individual patterns are studied in terms of low-frequency structure and graininess. Typically, the low-frequency structure (LF) is identified with a measurement of the energy around dc in the spatial frequency domain, while the graininess is quantified by a measurement of the average minimum distance (AMD) between minority dots as well as the kurtosis of the local kurtosis distribution (KLK) for minority pixels of the binary pattern. A set of partial BNMs are generated by using the different patterns as unique starting 'seeds.' In this way, we are able to study the quality of binary patterns over a range of gray levels. We observe that the optimality of a binary pattern for mask generation is related to its own quality mertirc values as well as the transition smoothness of those quality metric values over neighboring levels. Several schemes have been developed to apply blue-noise halftoning to color reproduction. Different schemes generate halftone patterns with different textures. In a previous paper, a human visual system (HVS) model was used to study the color halftone quality in terms of luminance and chrominance error in CIELAB color space. In this paper, a new series of psycho-visual experiments address the 'preferred' color rendering among four different blue noise halftoning schemes. The experimental results will be interpreted with respect to the proposed halftone quality metrics.

Do marginalized neighbourhoods have less healthy retail food environments? An analysis using Bayesian spatial latent factor and hurdle models.

PubMed

Luan, Hui; Minaker, Leia M; Law, Jane

2016-08-22

Findings of whether marginalized neighbourhoods have less healthy retail food environments (RFE) are mixed across countries, in part because inconsistent approaches have been used to characterize RFE 'healthfulness' and marginalization, and researchers have used non-spatial statistical methods to respond to this ultimately spatial issue. This study uses in-store features to categorize healthy and less healthy food outlets. Bayesian spatial hierarchical models are applied to explore the association between marginalization dimensions and RFE healthfulness (i.e., relative healthy food access that modelled via a probability distribution) at various geographical scales. Marginalization dimensions are derived from a spatial latent factor model. Zero-inflation occurring at the walkable-distance scale is accounted for with a spatial hurdle model. Neighbourhoods with higher residential instability, material deprivation, and population density are more likely to have access to healthy food outlets within a walkable distance from a binary 'have' or 'not have' access perspective. At the walkable distance scale however, materially deprived neighbourhoods are found to have less healthy RFE (lower relative healthy food access). Food intervention programs should be developed for striking the balance between healthy and less healthy food access in the study region as well as improving opportunities for residents to buy and consume foods consistent with dietary recommendations.

Wireless multi-level terahertz amplitude modulator using active metamaterial-based spatial light modulation.

PubMed

Rout, Saroj; Sonkusale, Sameer

2016-06-27

The ever increasing demand for bandwidth in wireless communication systems will inevitably lead to the extension of operating frequencies toward the terahertz (THz) band known as the 'THz gap'. Towards closing this gap, we present a multi-level amplitude shift keying (ASK) terahertz wireless communication system using terahertz spatial light modulators (SLM) instead of traditional voltage mode modulation, achieving higher spectral efficiency for high speed communication. The fundamental principle behind this higher efficiency is the conversion of a noisy voltage domain signal to a noise-free binary spatial pattern for effective amplitude modulation of a free-space THz carrier wave. Spatial modulation is achieved using an an active metamaterial array embedded with pseudomorphic high-electron mobility (pHEMT) designed in a consumer-grade galium-arsenide (GaAs) integrated circuit process which enables electronic control of its THz transmissivity. Each array is assembled as individually controllable tiles for transmissive terahertz spatial modulation. Using the experimental data from our metamaterial based modulator, we show that a four-level ASK digital communication system has two orders of magnitude improvement in symbol error rate (SER) for a degradation of 20 dB in transmit signal-to-noise ratio (SNR) using spatial light modulation compared to voltage controlled modulation.

Binaries in Transneptunian Resonances: Evidence for Slow Migration of Neptune?

NASA Technical Reports Server (NTRS)

Noll, Keith

2012-01-01

A distinguishing feature of trans neptunian objects (TNO) is the high fraction that arc binary. This is particularly true for the Cold Classicals (CC), objects in lowe and low i orbits concentrated between the 3:2 and 2: 1 mean-motion resonances. CCs have other physical markers: red colors, high albedos, and equal-mass binaries. The CCs appear to be a coherent and physically distinct population of planetesimals that has survived to the present with their physical properties relatively unaltered. Their spatial concentration between 39.4 and 47.7 AU has made identification of the CCs as a physical group possible. However, objects that started out as CCs arc almost certainly 1101 limited to this one dynamical niche. We can, therefore, use the measurable physical properties of CCs as tracers of Neptune-driven dynamical mixing in the Kuiper Belt. As Neptune migrated, its mean-motion resonances preceded it into the planetesimal disk. The efficiency of capture into mean motion resonances depends on the smoothness of Neptune's migration and the local population available to be captured. The two strongest resonances, the 3:2 at 39.4 AU and 2: 1 at 47.7 AU, straddle the core repository of the physically distinct CCs, providing a unique opportunity to test the details of Neptune's migration. Smooth migration should result in a measurable difference between the 3:2 and 2:1 with low inclination 2:1s having a red, binary population mirroring that of the CC itself while the 3:2 will be less contaminated. Alternative models with rapid migration would generate a more homogeneous result.

Radio emission in ultracool dwarfs: The nearby substellar triple system VHS 1256-1257

NASA Astrophysics Data System (ADS)

Guirado, J. C.; Azulay, R.; Gauza, B.; Pérez-Torres, M. A.; Rebolo, R.; Climent, J. B.; Zapatero Osorio, M. R.

2018-02-01

Aim. With the purpose of investigating the radio emission of new ultracool objects, we carried out a targeted search in the recently discovered system VHS J125601.92-125723.9 (hereafter VHS 1256-1257); this system is composed by an equal-mass M7.5 binary and a L7 low-mass substellar object located at only 15.8 pc. Methods: We observed in phase-reference mode the system VHS 1256-1257 with the Karl G. Jansky Very Large Array at X band and L band and with the European VLBI Network at L band in several epochs during 2015 and 2016. Results: We discovered radio emission at X band spatially coincident with the equal-mass M7.5 binary with a flux density of 60 μJy. We determined a spectral index α = ‑1.1 ± 0.3 between 8 and 12 GHz, suggesting that non-thermal, optically thin, synchrotron, or gyrosynchrotron radiation is responsible for the observed radio emission. Interestingly, no signal is seen at L band where we set a 3σ upper limit of 20 μJy. This might be explained by strong variability of the binary or self-absorption at this frequency. By adopting the latter scenario and gyrosynchrotron radiation, we constrain the turnover frequency to be in the interval 5-8.5 GHz, from which we infer the presence of kG-intense magnetic fields in the M7.5 binary. Our data impose a 3σ upper bound to the radio flux density of the L7 object of 9 μJy at 10 GHz.

Gamma-ray follow-up studies on η Carinae

DOE PAGES

Reitberger, K.; Reimer, O.; Reimer, A.; ...

2012-08-01

Observations of high-energy γ-rays recently revealed a persistent source in spatial coincidence with the binary system η Carinae. Since modulation of the observed γ-ray flux on orbital time scales has not been reported so far, an unambiguous identification was hitherto not possible. In particular, the observations made by the Fermi Large Area Telescope (LAT) posed additional questions regarding the actual emission scenario. Analyses show two energetically distinct components in the γ-ray spectrum, which are best described by an exponentially cutoff power-law function (CPL) at energies below 10 GeV and a power-law (PL) component dominant at higher energies. The increased exposuremore » in conjunction with the improved instrumental response functions of the LAT now allow us to perform a more detailed investigation of location, spectral shape, and flux time history of the observed γ-ray emission. Furthermore, we detect a weak but regular flux decrease over time. This can be understood and interpreted in a colliding-wind binary scenario for orbital modulation of the γ-ray emission. We find that the spectral shape of the γ-ray signal agrees with a single emitting particle population in combination with significant absorption by γ-γ pair production. We are able to report on the first unambiguous detection of GeV γ-ray emission from a colliding-wind massive star binary. By studying the correlation of the flux decrease with the orbital separation of the binary components allows us to predict the behaviour up to the next periastron passage in 2014.« less

Extreme isolation of WN3/O3 stars and implications for their evolutionary origin as the elusive stripped binaries

NASA Astrophysics Data System (ADS)

Smith, Nathan; Götberg, Ylva; de Mink, Selma E.

2018-03-01

Recent surveys of the Magellanic Clouds have revealed a subtype of Wolf-Rayet (WR) star with peculiar properties. WN3/O3 spectra exhibit both WR-like emission and O3 V-like absorption - but at lower luminosity than O3 V or WN stars. We examine the projected spatial distribution of WN3/O3 stars in the Large Magellanic Cloud as compared to O-type stars. Surprisingly, WN3/O3 stars are among the most isolated of all classes of massive stars; they have a distribution similar to red supergiants dominated by initial masses of 10-15 M⊙, and are far more dispersed than classical WR stars or luminous blue variables. Their lack of association with clusters of O-type stars suggests strongly that WN3/O3 stars are not the descendants of single massive stars (30 M⊙ or above). Instead, they are likely products of interacting binaries at lower initial mass (10-18 M⊙). Comparison with binary models suggests a probable origin with primaries in this mass range that were stripped of their H envelopes through non-conservative mass transfer by a low-mass secondary. We show that model spectra and positions on the Hertzsprung-Russell diagram for binary-stripped stars are consistent with WN3/O3 stars. Monitoring radial velocities with high-resolution spectra can test for low-mass companions or runaway velocities. With lower initial mass and environments that avoid very massive stars, the WN3/O3 stars fit expectations for progenitors of Type Ib and possibly Type Ibn supernovae.

The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality.

PubMed

Congdon, Peter

2011-01-01

Analysis of geographical patterns of suicide and psychiatric morbidity has demonstrated the impact of latent ecological variables (such as deprivation, rurality). Such latent variables may be derived by conventional multivariate techniques from sets of observed indices (for example, by principal components), by composite variable methods or by methods which explicitly consider the spatial framework of areas and, in particular, the spatial clustering of latent risks and outcomes. This article considers a latent random variable approach to explaining geographical contrasts in suicide in the US; and it develops a spatial structural equation model incorporating deprivation, social fragmentation and rurality. The approach allows for such latent spatial constructs to be correlated both within and between areas. Potential effects of area ethnic mix are also included. The model is applied to male and female suicide deaths over 2002–06 in 3142 US counties.

Punchets: nonlinear transport in Hamiltonian pump-ratchet hybrids

NASA Astrophysics Data System (ADS)

Dittrich, Thomas; Medina Sánchez, Nicolás

2018-02-01

‘Punchets’ are hybrids between ratchets and pumps, combining a spatially periodic static potential, typically asymmetric under space inversion, with a local driving that breaks time-reversal invariance, and are intended to model metal or semiconductor surfaces irradiated by a collimated laser beam. Their crucial feature is irregular driven scattering between asymptotic regions supporting periodic (as opposed to free) motion. With all binary spatio-temporal symmetries broken, scattering in punchets typically generates directed currents. We here study the underlying nonlinear transport mechanisms, from chaotic scattering to the parameter dependence of the currents, in three types of Hamiltonian models, (i) with spatially periodic potentials where only in the driven scattering region, spatial and temporal symmetries are broken, and (ii), spatially asymmetric (ratchet) potentials with a driving that only breaks time-reversal invariance. As more realistic models of laser-irradiated surfaces, we consider (iii), a driving in the form of a running wave confined to a compact region by a static envelope. In this case, the induced current can even run against the direction of wave propagation, drastically evidencing its nonlinear nature. Quantizing punchets is indicated as a viable research perspective.

Matched-filtering generalized phase contrast using LCoS pico-projectors for beam-forming.

PubMed

Bañas, Andrew; Palima, Darwin; Glückstad, Jesper

2012-04-23

We report on a new beam-forming system for generating high intensity programmable optical spikes using so-called matched-filtering Generalized Phase Contrast (mGPC) applying two consumer handheld pico-projectors. Such a system presents a low-cost alternative for optical trapping and manipulation, optical lattices and other beam-shaping applications usually implemented with high-end spatial light modulators. Portable pico-projectors based on liquid crystal on silicon (LCoS) devices are used as binary phase-only spatial light modulators by carefully setting the appropriate polarization of the laser illumination. The devices are subsequently placed into the object and Fourier plane of a standard 4f-setup according to the mGPC spatial filtering configuration. Having a reconfigurable spatial phase filter, instead of a fixed and fabricated one, allows the beam shaper to adapt to different input phase patterns suited for different requirements. Despite imperfections in these consumer pico-projectors, the mGPC approach tolerates phase aberrations that would have otherwise been hard to overcome by standard phase projection. © 2012 Optical Society of America

Obstructive urination problems after high-dose-rate brachytherapy boost treatment for prostate cancer are avoidable.

PubMed

Kragelj, Borut

2016-03-01

Aiming at improving treatment individualization in patients with prostate cancer treated with combination of external beam radiotherapy and high-dose-rate brachytherapy to boost the dose to prostate (HDRB-B), the objective was to evaluate factors that have potential impact on obstructive urination problems (OUP) after HDRB-B. In the follow-up study 88 patients consecutively treated with HDRB-B at the Institute of Oncology Ljubljana in the period 2006-2011 were included. The observed outcome was deterioration of OUP (DOUP) during the follow-up period longer than 1 year. Univariate and multivariate relationship analysis between DOUP and potential risk factors (treatment factors, patients' characteristics) was carried out by using binary logistic regression. ROC curve was constructed on predicted values and the area under the curve (AUC) calculated to assess the performance of the multivariate model. Analysis was carried out on 71 patients who completed 3 years of follow-up. DOUP was noted in 13/71 (18.3%) of them. The results of multivariate analysis showed statistically significant relationship between DOUP and anti-coagulation treatment (OR 4.86, 95% C.I. limits: 1.21-19.61, p = 0.026). Also minimal dose received by 90% of the urethra volume was close to statistical significance (OR = 1.23; 95% C.I. limits: 0.98-1.07, p = 0.099). The value of AUC was 0.755. The study emphasized the relationship between DOUP and anticoagulation treatment, and suggested the multivariate model with fair predictive performance. This model potentially enables a reduction of DOUP after HDRB-B. It supports the belief that further research should be focused on urethral sphincter as a critical structure for OUP.

Theoretical extension and experimental demonstration of spectral compression in second-harmonic generation by Fresnel-inspired binary phase shaping

NASA Astrophysics Data System (ADS)

Li, Baihong; Dong, Ruifang; Zhou, Conghua; Xiang, Xiao; Li, Yongfang; Zhang, Shougang

2018-05-01

Selective two-photon microscopy and high-precision nonlinear spectroscopy rely on efficient spectral compression at the desired frequency. Previously, a Fresnel-inspired binary phase shaping (FIBPS) method was theoretically proposed for spectral compression of two-photon absorption and second-harmonic generation (SHG) with a square-chirped pulse. Here, we theoretically show that the FIBPS can introduce a negative quadratic frequency phase (negative chirp) by analogy with the spatial-domain phase function of Fresnel zone plate. Thus, the previous theoretical model can be extended to the case where the pulse can be transformed limited and in any symmetrical spectral shape. As an example, we experimentally demonstrate spectral compression in SHG by FIBPS for a Gaussian transform-limited pulse and show good agreement with the theory. Given the fundamental pulse bandwidth, a narrower SHG bandwidth with relatively high intensity can be obtained by simply increasing the number of binary phases. The experimental results also verify that our method is superior to that proposed in [Phys. Rev. A 46, 2749 (1992), 10.1103/PhysRevA.46.2749]. This method will significantly facilitate the applications of selective two-photon microscopy and spectroscopy. Moreover, as it can introduce negative dispersion, hence it can also be generalized to other applications in the field of dispersion compensation.

Dynamics of ejecta from the binary asteroid Didymos, the target of the AIDA mission

NASA Astrophysics Data System (ADS)

Michel, Patrick; Yu, Yang; Schwartz, Stephen; Naidu, Shantanu; Benner, Lance

2016-04-01

The AIDA space mission, a collaborative effort between ESA and NASA, aims to characterize the near-Earth asteroid binary (65803) Didymos and to perform a kinetic impactor demonstration on the small moon of the binary system. Our study presents a multi-scale dynamical model of the ejecta cloud produced by a hypervelocity impact, which enables us to compute the ejecta properties at different spatial and time scales. This model is applied to the impact into the small moon of Didymos on October 2022 as considered by the AIDA mission. We model the process by including as much practical information as possible, e.g., the gravitational environment influenced by the non-spherical shapes of the bodies (based on the observed shape of the primary), the solar tides, and the solar radiation pressure. Our simulations show where and for how long the ejecta cloud evolves with time for the considered ejecta initial conditions. This information is used to assess the potential hazard to the ESA Asteroid Impact Mission (AIM) observing spacecraft and to determine the safest positions. This study is performed with support of the European Space Agency and in the framework of the NEOShield-2 project that has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 640351.

Near-Infrared Imaging Polarimetry of Inner Region of GG Tau A Disk

NASA Technical Reports Server (NTRS)

Yang, Yi; Hashimoto, Jun; Hayashi, Saeko S.; Tamura, Motohide; Mayama, Satoshi; Rafikov, Roman; Akiyama, Eiji; Carson, Joseph C.; Janson, Markus; Kwon, Jungmi;

Substellar Companions to weak-line TTauri Stars

NASA Astrophysics Data System (ADS)

Brandner, W.; Alcala, J. M.; Covino, E.; Frink, S.

1997-05-01

Weak-line TTauri stars, contrary to classical TTauri stars, no longer possess massive circumstellar disks. In weak-line TTauri stars, the circumstellar matter was either accreted onto the TTauri star or has been redistributed. Disk instabilities in the outer disk might result in the formation of brown dwarfs and giant planets. Based on photometric and spectroscopic studies of ROSAT sources, we have selected an initial sample of 200 weak-line TTauri stars in the Chamaeleon T association and the Scorpius Centaurus OB association. In the course of follow-up observations we identified visual and spectroscopic binary stars and excluded them from our final list, as the complex dynamics and gravitational interaction in binary systems might aggravate or even completely inhibit the formation of planets (depending on physical separation of the binary components and their mass-ratio). The membership of individual stars to the associations was established from proper motion studies and radial velocity surveys. Our final sample consists of 70 single weak-line TTauri stars. We have initiated a program to spatially RESOLVE young brown dwarfs and young giant planets as companions to single weak-line TTauri stars using adaptive optics at the ESO 3.6m telescope and HST/NICMOS. In this poster we describe the observing strategy and present first results of our adaptive optics observations.

Time-resolved Spectroscopy of RS CVn Binaries and dMe Flare Stars

NASA Astrophysics Data System (ADS)

Brown, Alexander

One of the most striking feature of the first two years of EUVE spectroscopy is the frequent occurrence of largescale coronal variability, in the form of stellar flares and slower changes in activity level due to rotational modulation and evolution of active regions. We propose EUVE observations of a set of RS CVn and dMe star binaries, most with short (< 2 days) periods, to investigate the coronal conditions and physical processes associated with this variability. EUVE flare outbursts have mostly been long duration events lasting many satellite orbits and been readily studied using time-resolved spectroscopy. Our targets are the dMe binaries YY Gem, CC Eri and Gliese 2123, and the RS CVn systems EI Eri, AR Psc, and TY Pyx. YY Gem and TY Pyx are eclipsing systems and Deep Survey photometry will be used to investigate the size of the coronal emitting regions. Situated 73 arcmin from YY Gem is Castor (Alpha Gem) another X-ray source that can be observed (and spatially resolved) simultaneously. We shall use the DS lightcurve to guide our time resolved spectral analysis. Changes in the coronal emission measure as a function of temperature and possibly changes in coronal density will be used to constrain magnetic loop models.

Multivariate ordination identifies vegetation types associated with spider conservation in brassica crops

PubMed Central

Saqib, Hafiz Sohaib Ahmed; You, Minsheng

2017-01-01

Conservation biological control emphasizes natural and other non-crop vegetation as a source of natural enemies to focal crops. There is an unmet need for better methods to identify the types of vegetation that are optimal to support specific natural enemies that may colonize the crops. Here we explore the commonality of the spider assemblage—considering abundance and diversity (H)—in brassica crops with that of adjacent non-crop and non-brassica crop vegetation. We employ spatial-based multivariate ordination approaches, hierarchical clustering and spatial eigenvector analysis. The small-scale mixed cropping and high disturbance frequency of southern Chinese vegetation farming offered a setting to test the role of alternate vegetation for spider conservation. Our findings indicate that spider families differ markedly in occurrence with respect to vegetation type. Grassy field margins, non-crop vegetation, taro and sweetpotato harbour spider morphospecies and functional groups that are also present in brassica crops. In contrast, pumpkin and litchi contain spiders not found in brassicas, and so may have little benefit for conservation biological control services for brassicas. Our findings also illustrate the utility of advanced statistical approaches for identifying spatial relationships between natural enemies and the land uses most likely to offer alternative habitats for conservation biological control efforts that generates testable hypotheses for future studies. PMID:29085741

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.

Spatial extremes modeling applied to extreme precipitation data in the state of Paraná

NASA Astrophysics Data System (ADS)

Olinda, R. A.; Blanchet, J.; dos Santos, C. A. C.; Ozaki, V. A.; Ribeiro, P. J., Jr.

2014-11-01

Most of the mathematical models developed for rare events are based on probabilistic models for extremes. Although the tools for statistical modeling of univariate and multivariate extremes are well developed, the extension of these tools to model spatial extremes includes an area of very active research nowadays. A natural approach to such a modeling is the theory of extreme spatial and the max-stable process, characterized by the extension of infinite dimensions of multivariate extreme value theory, and making it possible then to incorporate the existing correlation functions in geostatistics and therefore verify the extremal dependence by means of the extreme coefficient and the Madogram. This work describes the application of such processes in modeling the spatial maximum dependence of maximum monthly rainfall from the state of Paraná, based on historical series observed in weather stations. The proposed models consider the Euclidean space and a transformation referred to as space weather, which may explain the presence of directional effects resulting from synoptic weather patterns. This method is based on the theorem proposed for de Haan and on the models of Smith and Schlather. The isotropic and anisotropic behavior of these models is also verified via Monte Carlo simulation. Estimates are made through pairwise likelihood maximum and the models are compared using the Takeuchi Information Criterion. By modeling the dependence of spatial maxima, applied to maximum monthly rainfall data from the state of Paraná, it was possible to identify directional effects resulting from meteorological phenomena, which, in turn, are important for proper management of risks and environmental disasters in countries with its economy heavily dependent on agribusiness.

A novel principal component analysis for spatially misaligned multivariate air pollution data.

PubMed

Jandarov, Roman A; Sheppard, Lianne A; Sampson, Paul D; Szpiro, Adam A

2017-01-01

We propose novel methods for predictive (sparse) PCA with spatially misaligned data. These methods identify principal component loading vectors that explain as much variability in the observed data as possible, while also ensuring the corresponding principal component scores can be predicted accurately by means of spatial statistics at locations where air pollution measurements are not available. This will make it possible to identify important mixtures of air pollutants and to quantify their health effects in cohort studies, where currently available methods cannot be used. We demonstrate the utility of predictive (sparse) PCA in simulated data and apply the approach to annual averages of particulate matter speciation data from national Environmental Protection Agency (EPA) regulatory monitors.

Mapping and Modeling the Extended Winds of the Massive Interacting Binary, Eta Carinae

NASA Technical Reports Server (NTRS)

Gull, Ted

2010-01-01

The combination HST/STIS high spatial and moderate spectral resolutions have revealed the massive interacting wind structure of Eta Carinae by forbidden lines of singly and doubly ionized elements. Throughout the 5.54-year period, lines of Fe++, Ne++, Ar++, S++ and N+ reveal the interacting wind structures, near critical electron densities of 10(exp 5) to 3 x 10(exp 7)cu cm, photoionized by the hot secondary, Eta Car B, Lines of Fe+ and Ni+ trace the denser (>10(exp 7)cu cm. less-ionized (< 8 eV) primary wind of Eta Car A as it wraps around the interacting binary stars. For 5 years of the 5.54 year period, the FUV radiation from Eta Car B escapes the orbital region, ionizing the boundaries of the expanding wind structures. But for three to six months, Eta Car B plunges into the primary wind approaching to within 1 to 2 AU, leading to cutoff of FUV and X-ray fluxes. The interacting wind structure, resolved out to 0.8", drops io ionization and then rebuilds as Eta Car B emerges from the primary wind envelope. Solid Particle Hydrodynamical(SPH) models have been developed extending out to 2000 AU and adapted to include FUV radiation effects of the winds. In turn, synthetic spectroimages of selected forbidden lines have been constructed and compared to the spectroimages recorded by the HST/STIS throughout 1998.0 to 2004.3, extending across the 1998 and 2003.5 minima. By this method, we show that the orbital axis of the binary system must bc within 15 degrees of the Homunculus axis of symmetry and that periastron occurs with Eta Car B passing on the far side of Eta Car B. This result ties the current binary orbit with the bipolar ejection with intervening skirt and leads to implications that the binary system influenced the mass ejection of the l840s and the lesser ejection of the 1890s.

Piloting a 'spatial isolation' index: the built environment and sexual and drug use risks to sex workers.

PubMed

Deering, Kathleen N; Rusch, Melanie; Amram, Ofer; Chettiar, Jill; Nguyen, Paul; Feng, Cindy X; Shannon, Kate

2014-05-01

Employing innovative mapping and spatial analyses of individual and neighbourhood environment data, we examined the social, physical and structural features of overlapping street-based sex work and drug scenes and explored the utility of a 'spatial isolation index' in explaining exchanging sex for drugs and exchanging sex while high. Analyses drew on baseline interview and geographic data (January 2010-October 2011) from a large prospective cohort of street and off-street sex workers (SWs) in Metropolitan Vancouver and external publically-available, neighbourhood environment data. An index measuring 'spatial isolation' was developed from seven indicators measuring features of the built environment within 50m buffers (e.g., industrial or commercial zoning, lighting) surrounding sex work environments. Bivariate and multivariable logistic regression was used to examine associations between the two outcomes (exchanged sex for drugs; exchanged sex while high) and the index, as well as each individual indicator. Of 510 SWs, 328 worked in street-based/outdoor environments (e.g., streets, parks, alleys) and were included in the analyses. In multivariable analysis, increased spatial isolation surrounding street-based/outdoor SWs' main places of servicing clients as measured with the index was significantly associated with exchanging sex for drugs. Exchanging sex for drugs was also significantly positively associated with an indicator of the built environment suggesting greater spatial isolation (increased percent of parks) and negatively associated with those suggesting decreased spatial isolation (increased percent commercial areas, increased count of lighting, increased building footprint). Exchanging sex while high was negatively associated with increased percent of commercial zones but this association was removed when adjusting for police harassment. The results from our exploratory study highlight how built environment shapes risks within overlapping street-based sex work and drug scenes through the development of a novel index comprised of multiple indicators of the built environment available through publicly available data, This study informs the important role that spatially-oriented responses, such as safer-environment interventions, and structural responses, such as decriminalization of sex work can play in improving the health, safety and well-being of SWs. Copyright © 2013 Elsevier B.V. All rights reserved.

Piloting a ‘Spatial Isolation’ Index: The Built Environment and Sexual and Drug Use Risks to Sex Workers

PubMed Central

Deering, Kathleen N; Rusch, Melanie; Amram, Ofer; Chettiar, Jill; Nguyen, Paul; Feng, Cindy X; Shannon, Kate

2014-01-01

Background Employing innovative mapping and spatial analyses of individual and neighborhood environment data, we examined the social, physical and structural features of overlapping street-based sex work and drug scenes and explored the utility of a ‘spatial isolation index’ in explaining exchanging sex for drugs and exchanging sex while high. Methods Analyses drew on baseline interview and geographic data (Jan/10-Oct/11) from a large prospective cohort of street and off-street sex workers (SWs) in Metropolitan Vancouver and external publically-available, neighborhood environment data. An index measuring ‘spatial isolation’ was developed from seven indicators measuring features of the built environment within 50m buffers (e.g. industrial or commercial zoning, lighting) surrounding sex work environments. Bivariate and multivariable logistic regression was used to examine associations between the two outcomes (exchanged sex for drugs; exchanged sex while high) and the index, as well as each individual indicator. Results Of 510 SWs, 328 worked in street-based/outdoor environments (e.g. streets, parks, alleys) and were included in the analyses. In multivariable analysis, increased spatial isolation surrounding street-based/outdoor SWs’ main places of servicing clients as measured with the index was significantly associated with exchanging sex for drugs. Exchanging sex for drugs was also significantly positively associated with an indicator of the built environment suggesting greater spatial isolation (increased percent of parks) and negatively associated with those suggesting decreased spatial isolation (increased percent commercial areas, increased count of lighting, increased building footprint). Exchanging sex while high was negatively associated with increased percent of commercial zones but this association was removed when adjusting for police harassment. Conclusions The results from our exploratory study highlight how built environment shapes risks within overlapping street-based sex work and drug scenes through the development of a novel index comprised of multiple indicators of the built environment available through publicly available data, This study informs the important role that spatially-oriented responses, such as safer-environment interventions, and structural responses, such as decriminalization of sex work can play in improving the health, safety and well-being of SWs. PMID:24433813

Attention modulates spatial priority maps in the human occipital, parietal and frontal cortices

PubMed Central

Sprague, Thomas C.; Serences, John T.

2014-01-01

Computational theories propose that attention modulates the topographical landscape of spatial ‘priority’ maps in regions of visual cortex so that the location of an important object is associated with higher activation levels. While single-unit recording studies have demonstrated attention-related increases in the gain of neural responses and changes in the size of spatial receptive fields, the net effect of these modulations on the topography of region-level priority maps has not been investigated. Here, we used fMRI and a multivariate encoding model to reconstruct spatial representations of attended and ignored stimuli using activation patterns across entire visual areas. These reconstructed spatial representations reveal the influence of attention on the amplitude and size of stimulus representations within putative priority maps across the visual hierarchy. Our results suggest that attention increases the amplitude of stimulus representations in these spatial maps, particularly in higher visual areas, but does not substantively change their size. PMID:24212672

Modeling the Spatial and Temporal Variation of Monthly and Seasonal Precipitation on the Nevada Test Site and Vicinity, 1960-2006

USGS Publications Warehouse

Blainey, Joan B.; Webb, Robert H.; Magirl, Christopher S.

2007-01-01

The Nevada Test Site (NTS), located in the climatic transition zone between the Mojave and Great Basin Deserts, has a network of precipitation gages that is unusually dense for this region. This network measures monthly and seasonal variation in a landscape with diverse topography. Precipitation data from 125 climate stations on or near the NTS were used to spatially interpolate precipitation for each month during the period of 1960 through 2006 at high spatial resolution (30 m). The data were collected at climate stations using manual and/or automated techniques. The spatial interpolation method, applied to monthly accumulations of precipitation, is based on a distance-weighted multivariate regression between the amount of precipitation and the station location and elevation. This report summarizes the temporal and spatial characteristics of the available precipitation records for the period 1960 to 2006, examines the temporal and spatial variability of precipitation during the period of record, and discusses some extremes in seasonal precipitation on the NTS.

Multivariate Statistical Analysis: a tool for groundwater quality assessment in the hidrogeologic region of the Ring of Cenotes, Yucatan, Mexico.

NASA Astrophysics Data System (ADS)

Ye, M.; Pacheco Castro, R. B.; Pacheco Avila, J.; Cabrera Sansores, A.

2014-12-01

The karstic aquifer of Yucatan is a vulnerable and complex system. The first fifteen meters of this aquifer have been polluted, due to this the protection of this resource is important because is the only source of potable water of the entire State. Through the assessment of groundwater quality we can gain some knowledge about the main processes governing water chemistry as well as spatial patterns which are important to establish protection zones. In this work multivariate statistical techniques are used to assess the groundwater quality of the supply wells (30 to 40 meters deep) in the hidrogeologic region of the Ring of Cenotes, located in Yucatan, Mexico. Cluster analysis and principal component analysis are applied in groundwater chemistry data of the study area. Results of principal component analysis show that the main sources of variation in the data are due sea water intrusion and the interaction of the water with the carbonate rocks of the system and some pollution processes. The cluster analysis shows that the data can be divided in four clusters. The spatial distribution of the clusters seems to be random, but is consistent with sea water intrusion and pollution with nitrates. The overall results show that multivariate statistical analysis can be successfully applied in the groundwater quality assessment of this karstic aquifer.

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

PubMed

Duarte, João V; Ribeiro, Maria J; Violante, Inês R; Cunha, Gil; Silva, Eduardo; Castelo-Branco, Miguel

2014-01-01

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1. Copyright © 2012 Wiley Periodicals, Inc.

A mid-IR interferometric survey with MIDI/VLTI: resolving the second-generation protoplanetary disks around post-AGB binaries

NASA Astrophysics Data System (ADS)

Hillen, M.; Van Winckel, H.; Menu, J.; Manick, R.; Debosscher, J.; Min, M.; de Wit, W.-J.; Verhoelst, T.; Kamath, D.; Waters, L. B. F. M.

2017-03-01

Aims: We present a mid-IR interferometric survey of the circumstellar environment of a specific class of post-asymptotic giant branch (post-AGB) binaries. For this class the presence of a compact dusty disk has been postulated on the basis of various spatially unresolved measurements. The aim is to determine the angular extent of the N-band emission directly and to resolve the compact circumstellar structures. Methods: Our interferometric survey was performed with the MIDI instrument on the VLTI. In total 19 different systems were observed using variable baseline configurations. Combining all the visibilities at a single wavelength at 10.7 μm, we fitted two parametric models to the data: a uniform disk and a ring model mimicking a temperature gradient. We compared our observables of the whole sample, with synthetic data computed from a grid of radiative transfer models of passively irradiated disks in hydrostatic equilibrium. These models are computed with a Monte Carlo code that has been widely applied to describe the structure of protoplanetary disks around young stellar objects (YSO). Results: The spatially resolved observations show that the majority of our targets cluster closely together in the distance-independent size-colour diagram, and have extremely compact N-band emission regions. The typical uniform disk diameter of the N-band emission region is 40 mas, which corresponds to a typical brightness temperature of 400-600 K. The resolved objects display very similar characteristics in the interferometric observables and in the spectral energy distributions. Therefore, the physical properties of the disks around our targets must be similar. Our results are discussed in the light of recently published sample studies of YSOs to compare quantitatively the secondary discs around post-AGB stars to the ones around YSOs. Conclusions: Our high-angular-resolution survey further confirms the disk nature of the circumstellar structures present around wide post-AGB binaries. The grid of protoplanetary disk models covers very well the observed objects. Much like for young stars, the spatially resolved N-band emission region is determined by the hot inner rim of the disk. Continued comparisons between post-AGB and protoplanetary disks will help to understand grain growth and disk evolution processes, and to constrain planet formation theories. These second-generation disks are an important missing ingredient in binary evolution theory of intermediate-mass stars. Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programmes ID 073.A-9002, 073.A-9014, 073.D-0610, 075.D-0605, 077.D-0071, 078.D-0113, 079.D-0013, 080.D-0059, 081.D-0089, 082.D-0066, 083.D-0011, 083.D-0013, 084.D-0009, 093.D-0914, and 094.D-0778. Some observations were obtained in the framework of the Belgian Guaranteed Time allocation on VISA.

[Overload in the informal caregivers of patients with multiple comorbidities in an urban area].

PubMed

Álvarez-Tello, Margarita; Casado-Mejía, Rosa; Ortega-Calvo, Manuel; Ruiz-Arias, Esperanza

2012-01-01

The aim of the study was, to determine the profile of the family caregiver of patients with multiple pathologies, identify factors associated with overload, and construct predictive models using items from the Caregiver Strain Index (CSI). A cross-sectional study of caregivers of patients with multiple comorbidities who attended an urban health centre. Data were collected from health records and questionnaires (Barthel index, Pfeiffer index, and CSI). Statistical analysis was performed using measures of central tendency and dispersion, and by building multivariate models with binary logistic regression with the CSI items as predictors (program R version 2.14.0). The sample included 67 caregivers, with a mean age of 64.69 years (standard deviation=12.71, median 62 years), of whom 74.6% were women, 35.8% were wives, and 32.8% were daughters. The level of dependence of the patients cared for was total/severe in 77.6%, and moderate in 12% (Barthel), and 47.8% had some level of cognitive impairment (Pfeiffer). A CSI equal or greater than 7 was seen in 47.8% of caregivers, identifying life problems in more than 40% of them such as, restriction of social life, physical exertion, discomfort with change, bad behaviour, personal and family emotional changes, and sleep disturbances. Item 4 of the CSI, analysing the social restriction, was the one that showed a greater significance in the predictive multivariate model. Item 12 (economic burden) was the most significant with age in patients with cognitive impairment. Women tend to take the role of caregiver at an earlier age than men in the urban environment studied, and items from CSI showed that items 4 (social restrictions) and 12 (economic burden) have more significance in the predictive models constructed with Binary Logistic Regression. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Non-specific low back pain: occupational or lifestyle consequences?

PubMed

Stričević, Jadranka; Papež, Breda Jesenšek

2015-12-01

Nursing occupation was identified as a risk occupation for the development of low back pain (LBP). The aim of our study was to find out how much occupational factors influence the development of LBP in hospital nursing personnel. Non-experimental approach with a cross-sectional survey and statistical analysis. Nine hundred questionnaires were distributed among nursing personnel, 663 were returned and 659 (73.2 %) were considered for the analysis. Univariate and multivariate statistics for LBP risk was calculated by the binary logistic regression. The χ(2), influence factor, 95 % confidence interval and P value were calculated. Multivariate binary logistic regression was calculated by the Wald method to omit insignificant variables. Not performing exercises represented the highest risk for the development of LBP (OR 2.8, 95 % CI 1.7-4.4; p < 0.001). The second and third ranked risk factors were frequent manual lifting > 10 kg (OR 2.4, 95 % CI 1.5-3.8; p < 0.001) and duration of employment ≥ 19 years (OR 2.4, 95 % CI 1.6-3.7; p < 0.001). The fourth ranked risk factor was better physical condition by frequent recreation and sports, which reduced the risk for the development of LBP (OR 0.4, 95 % CI 0.3-0.7; p = 0.001). Work with the computer ≥ 2 h per day as last significant risk factor also reduced the risk for the development of LBP (OR 0.6, 95 % CI 0.4-0.1; p = 0.049). Risk factors for LBP established in our study (exercises, duration of employment, frequent manual lifting, recreation and sports and work with the computer) are not specifically linked to the working environment of the nursing personnel. Rather than focusing on mechanical causes and direct workload in the development of non-specific LBP, the complex approach to LBP including genetics, psychosocial environment, lifestyle and quality of life is coming more to the fore.

Predictive Risk Factors in the Development of Intraoperative Hyperkalemia in Adult Living Donor Liver Transplantation.

PubMed

Juang, S-E; Huang, C-E; Chen, C-L; Wang, C-H; Huang, C-J; Cheng, K-W; Wu, S-C; Shih, T-H; Yang, S-C; Wong, Z-W; Jawan, B; Lee, Y-E

2016-05-01

Hyperkalemia, defined as a serum potassium level higher than 5 mEq/L, is common in the liver transplantation setting. Severe hyperkalemia may induce fatal cardiac arrhythmias; therefore, it should be monitored and treated accordingly. The aim of the current retrospective study is to evaluate and indentify the predictive risk factors of hyperkalemia during living-donor liver transplantation (LDLT). Four hundred eighty-seven adult LDLT patients were included in the study. Intraoperative serum potassium levels were monitored at least five times during LDLT; patients with a potassium level higher than 5 mEq/L were included in group 1, and the others with normokalemia in group 2. Patients' categorical characteristics and intraoperative numeric variables with a P value <.1 were selected into a multiple binary logistic regression model. In multivariate analysis, a P value of <.05 is regarded as a risk factor in the development of hyperkalemia. Fifty-one of 487 (10.4%) patients had hyperkalemia with a serum potassium level higher than 5.0 mEq/L during LDLT. Predictive factors with P < .1 in univariate analysis (Table 1), such as anesthesia time, preoperative albumin level, Model for End-stage Liver Disease score, preoperative bilirubin level, amount of blood loss, red blood cell (RBC) and fresh frozen plasma transfused, 5% albumin administered, hemoglobin at the end of surgery, and the amount of furosemide used, were further analyzed by multivariate binary regression. Results show that the anesthesia time, preoperative serum albumin level, and RBC count are determinant risk factors in the development of the hyperkalemia in our LDLT serials. Prolonged anesthesia time, preoperative serum albumin level, and intraoperative RBC transfusion are three determinant factors in the development of intraoperative hyperkalemia, and close monitoring of serum potassium levels in patients with abovementioned risk factors are recommended. Copyright © 2016 Elsevier Inc. All rights reserved.

Method of identifying clusters representing statistical dependencies in multivariate data

NASA Technical Reports Server (NTRS)

Borucki, W. J.; Card, D. H.; Lyle, G. C.

1975-01-01

Approach is first to cluster and then to compute spatial boundaries for resulting clusters. Next step is to compute, from set of Monte Carlo samples obtained from scrambled data, estimates of probabilities of obtaining at least as many points within boundaries as were actually observed in original data.

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

USDA-ARS?s Scientific Manuscript database

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

Update and review of accuracy assessment techniques for remotely sensed data

NASA Technical Reports Server (NTRS)

Congalton, R. G.; Heinen, J. T.; Oderwald, R. G.

1983-01-01

Research performed in the accuracy assessment of remotely sensed data is updated and reviewed. The use of discrete multivariate analysis techniques for the assessment of error matrices, the use of computer simulation for assessing various sampling strategies, and an investigation of spatial autocorrelation techniques are examined.

Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown

EPA Science Inventory

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) hel...

Tools for automated acoustic monitoring within the R package monitoR

USGS Publications Warehouse

Katz, Jonathan; Hafner, Sasha D.; Donovan, Therese

2016-01-01

The R package monitoR contains tools for managing an acoustic-monitoring program including survey metadata, template creation and manipulation, automated detection and results management. These tools are scalable for use with small projects as well as larger long-term projects and those with expansive spatial extents. Here, we describe typical workflow when using the tools in monitoR. Typical workflow utilizes a generic sequence of functions, with the option for either binary point matching or spectrogram cross-correlation detectors.

Tight focusing of higher orders Laguerre-Gaussian modes

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

Savelyev, Dmitry A., E-mail: dmitrey.savelyev@yandex.ru; Khonina, Svetlana N.; Samara State Aerospace University, 34 Moskovskoye Shosse, Samara 443086

2016-04-13

The spatial redistribution of the contribution of different electric field components provides a decrease in the size of the central focal spot for higher orders Laguerre-Gaussian modes. It was shown that when sharply focusing laser beams with vortex or special binary phase plate, a sub-wavelength light localization of separate vector field components is possible for any polarization type. This fact should be considered for the interaction of laser radiation with materials selectively sensitive to lateral and longitudinal components of the electromagnetic field.

FINAL REPORT: Temporal and Spatial Distribution of Soil Moisture in Heterogeneous Vadose Zone with Moisture Barriers as Affected by Atmospheric Boundary Conditions

DTIC Science & Technology

2015-12-07

Wallen, B., K.M. Smits and S.E. Howington. Thermal conductivity of binary sand mixtures evaluated through the full range of saturation. Hydrology Days...and T.H. Illangasekare. 2011. Thermal conductivity of soils as affected by temperature, Proceedings from Hydrology Days. Colorado State University...is mixed with very fine soil). Although it is well known that the apparent thermal conductivity (λ) of partially wet soil is a function of water (θ

Relief diffracted elements recorded on absorbent photopolymers.

PubMed

Gallego, S; Márquez, A; Ortuño, M; Francés, J; Pascual, I; Beléndez, A

2012-05-07

Relief surface changes provide interesting possibilities for storing diffractive optical elements on photopolymers and are an important source of information for characterizing and understanding the material behavior. In this paper we use a 3-dimensional model, based on direct parameter measurements, for predicting the relief structures generated on without-coverplate photopolymers. We have analyzed different spatial frequency and recording intensity distributions such as binary and blazed periodic patterns. This model was successfully applied to different photopolymers with different values of monomer diffusion.

Zeroth-order phase-contrast technique.

PubMed

Pizolato, José Carlos; Cirino, Giuseppe Antonio; Gonçalves, Cristhiane; Neto, Luiz Gonçalves

2007-11-01

What we believe to be a new phase-contrast technique is proposed to recover intensity distributions from phase distributions modulated by spatial light modulators (SLMs) and binary diffractive optical elements (DOEs). The phase distribution is directly transformed into intensity distributions using a 4f optical correlator and an iris centered in the frequency plane as a spatial filter. No phase-changing plates or phase dielectric dots are used as a filter. This method allows the use of twisted nematic liquid-crystal televisions (LCTVs) operating in the real-time phase-mostly regime mode between 0 and p to generate high-intensity multiple beams for optical trap applications. It is also possible to use these LCTVs as input SLMs for optical correlators to obtain high-intensity Fourier transform distributions of input amplitude objects.

Laboratory demonstration of Stellar Intensity Interferometry using a software correlator

NASA Astrophysics Data System (ADS)

Matthews, Nolan; Kieda, David

2017-06-01

In this talk I will present measurements of the spatial coherence function of laboratory thermal (black-body) sources using Hanbury-Brown and Twiss interferometry with a digital off-line correlator. Correlations in the intensity fluctuations of a thermal source, such as a star, allow retrieval of the second order coherence function which can be used to perform high resolution imaging and source geometry characterization. We also demonstrate that intensity fluctuations between orthogonal polarization states are uncorrelated but can be used to reduce systematic noise. The work performed here can readily be applied to existing and future Imaging Air-Cherenkov telescopes to measure spatial properties of stellar sources. Some possible candidates for astronomy applications include close binary star systems, fast rotators, Cepheid variables, and potentially even exoplanet characterization.

Eta Carinae: Viewed from Multiple Vantage Points

NASA Technical Reports Server (NTRS)

Gull, Theodore

2007-01-01

The central source of Eta Carinae and its ejecta is a massive binary system buried within a massive interacting wind structure which envelops the two stars. However the hot, less massive companion blows a small cavity in the very massive primary wind, plus ionizes a portion of the massive wind just beyond the wind-wind boundary. We gain insight on this complex structure by examining the spatially-resolved Space Telescope Imaging Spectrograph (STIS) spectra of the central source (0.1") with the wind structure which extends out to nearly an arcsecond (2300AU) and the wind-blown boundaries, plus the ejecta of the Little Homunculus. Moreover, the spatially resolved Very Large Telescope/UltraViolet Echelle Spectrograph (VLT/UVES) stellar spectrum (one arcsecond) and spatially sampled spectra across the foreground lobe of the Homunculus provide us vantage points from different angles relative to line of sight. Examples of wind line profiles of Fe II, and the.highly excited [Fe III], [Ne III], [Ar III] and [S III)], plus other lines will be presented.

Coordinated temporal and spatial control of motor neuron and serotonergic neuron generation from a common pool of CNS progenitors.

PubMed

Pattyn, Alexandre; Vallstedt, Anna; Dias, José M; Samad, Omar Abdel; Krumlauf, Robb; Rijli, Filippo M; Brunet, Jean-Francois; Ericson, Johan

2003-03-15

Neural progenitor cells often produce distinct types of neurons in a specific order, but the determinants that control the sequential generation of distinct neuronal subclasses in the vertebrate CNS remain poorly defined. We examined the sequential generation of visceral motor neurons and serotonergic neurons from a common pool of neural progenitors located in the ventral hindbrain. We found that the temporal specification of these neurons varies along the anterior-posterior axis of the hindbrain, and that the timing of their generation critically depends on the integrated activities of Nkx- and Hox-class homeodomain proteins. A primary function of these proteins is to coordinate the spatial and temporal activation of the homeodomain protein Phox2b, which in turn acts as a binary switch in the selection of motor neuron or serotonergic neuronal fate. These findings assign new roles for Nkx, Hox, and Phox2 proteins in the control of temporal neuronal fate determination, and link spatial and temporal patterning of CNS neuronal fates.

Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases.

PubMed

Wendling, T; Jung, K; Callahan, A; Schuler, A; Shah, N H; Gallego, B

2018-06-03

There is growing interest in using routinely collected data from health care databases to study the safety and effectiveness of therapies in "real-world" conditions, as it can provide complementary evidence to that of randomized controlled trials. Causal inference from health care databases is challenging because the data are typically noisy, high dimensional, and most importantly, observational. It requires methods that can estimate heterogeneous treatment effects while controlling for confounding in high dimensions. Bayesian additive regression trees, causal forests, causal boosting, and causal multivariate adaptive regression splines are off-the-shelf methods that have shown good performance for estimation of heterogeneous treatment effects in observational studies of continuous outcomes. However, it is not clear how these methods would perform in health care database studies where outcomes are often binary and rare and data structures are complex. In this study, we evaluate these methods in simulation studies that recapitulate key characteristics of comparative effectiveness studies. We focus on the conditional average effect of a binary treatment on a binary outcome using the conditional risk difference as an estimand. To emulate health care database studies, we propose a simulation design where real covariate and treatment assignment data are used and only outcomes are simulated based on nonparametric models of the real outcomes. We apply this design to 4 published observational studies that used records from 2 major health care databases in the United States. Our results suggest that Bayesian additive regression trees and causal boosting consistently provide low bias in conditional risk difference estimates in the context of health care database studies. Copyright © 2018 John Wiley & Sons, Ltd.

Impact of high lipoprotein(a) levels on in-stent restenosis and long-term clinical outcomes of angina pectoris patients undergoing percutaneous coronary intervention with drug-eluting stents in Asian population.

PubMed

Park, Sang-Ho; Rha, Seung-Woon; Choi, Byoung-Geol; Park, Ji-Young; Jeon, Ung; Seo, Hong-Seog; Kim, Eung-Ju; Na, Jin-Oh; Choi, Cheol-Ung; Kim, Jin-Won; Lim, Hong-Euy; Park, Chang-Gyu; Oh, Dong-Joo

2015-06-01

Lipoprotein(a) (Lp(a)) is known to be associated with cardiovascular complications and atherothrombotic properties in general populations. However, it has not been examined whether Lp(a) levels are able to predict adverse cardiovascular outcomes in patients undergoing percutaneous coronary intervention (PCI) with drug-eluting stents (DES). A total of 595 consecutive patients with angina pectoris who underwent elective PCI with DES were enrolled from 2004 to 2010. The patients were divided into two groups according to the levels of Lp(a): Lp(a) < 50 mg/dL (n = 485 patients), and Lp(a) ≥ 50 mg/dL (n = 111 patients). The 6-9-month angiographic outcomes and 3-year cumulative major clinical outcomes were compared between the two groups. Binary restenosis occurred in 26 of 133 lesions (19.8%) in the high Lp(a) group and 43 of 550 lesions (7.9%) in the low Lp(a) group (P = 0.001). In multivariate analysis, the reference vessel diameter, low density lipoprotein cholesterol, total lesion length, and Lp(a) ≥ 50 mg/dL were predictors of binary restenosis. In the Cox proportional hazards regression analysis, Lp(a) > 50 mg/dL was significantly associated with the 3-year adverse clinical outcomes including any myocardial infarction, revascularization (target lesion revascularization (TLR) and target vessel revascularization (TVR)), TLR-major adverse cardiac events (MACEs), TVR-MACE, and All-MACEs. In our study, high Lp(a) level ≥ 50 mg/dL in angina pectoris patients undergoing elective PCI with DES was significantly associated with binary restenosis and 3-year adverse clinical outcomes in an Asian population. © 2015 Wiley Publishing Asia Pty Ltd.

Development and Validation of Chemometric Spectrophotometric Methods for Simultaneous Determination of Simvastatin and Nicotinic Acid in Binary Combinations.

PubMed

Alahmad, Shoeb; Elfatatry, Hamed M; Mabrouk, Mokhtar M; Hammad, Sherin F; Mansour, Fotouh R

2018-01-01

The development and introduction of combined therapy represent a challenge for analysis due to severe overlapping of their UV spectra in case of spectroscopy or the requirement of a long tedious and high cost separation technique in case of chromatography. Quality control laboratories have to develop and validate suitable analytical procedures in order to assay such multi component preparations. New spectrophotometric methods for the simultaneous determination of simvastatin (SIM) and nicotinic acid (NIA) in binary combinations were developed. These methods are based on chemometric treatment of data, the applied chemometric techniques are multivariate methods including classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS). In these techniques, the concentration data matrix were prepared by using the synthetic mixtures containing SIM and NIA dissolved in ethanol. The absorbance data matrix corresponding to the concentration data matrix was obtained by measuring the absorbance at 12 wavelengths in the range 216 - 240 nm at 2 nm intervals in the zero-order. The spectrophotometric procedures do not require any separation step. The accuracy, precision and the linearity ranges of the methods have been determined and validated by analyzing synthetic mixtures containing the studied drugs. Chemometric spectrophotometric methods have been developed in the present study for the simultaneous determination of simvastatin and nicotinic acid in their synthetic binary mixtures and in their mixtures with possible excipients present in tablet dosage form. The validation was performed successfully. The developed methods have been shown to be accurate, linear, precise, and so simple. The developed methods can be used routinely for the determination dosage form. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A time domain frequency-selective multivariate Granger causality approach.

PubMed

Leistritz, Lutz; Witte, Herbert

2016-08-01

The investigation of effective connectivity is one of the major topics in computational neuroscience to understand the interaction between spatially distributed neuronal units of the brain. Thus, a wide variety of methods has been developed during the last decades to investigate functional and effective connectivity in multivariate systems. Their spectrum ranges from model-based to model-free approaches with a clear separation into time and frequency range methods. We present in this simulation study a novel time domain approach based on Granger's principle of predictability, which allows frequency-selective considerations of directed interactions. It is based on a comparison of prediction errors of multivariate autoregressive models fitted to systematically modified time series. These modifications are based on signal decompositions, which enable a targeted cancellation of specific signal components with specific spectral properties. Depending on the embedded signal decomposition method, a frequency-selective or data-driven signal-adaptive Granger Causality Index may be derived.

Gas-water two-phase flow characterization with Electrical Resistance Tomography and Multivariate Multiscale Entropy analysis.

PubMed

Tan, Chao; Zhao, Jia; Dong, Feng

2015-03-01

Flow behavior characterization is important to understand gas-liquid two-phase flow mechanics and further establish its description model. An Electrical Resistance Tomography (ERT) provides information regarding flow conditions at different directions where the sensing electrodes implemented. We extracted the multivariate sample entropy (MSampEn) by treating ERT data as a multivariate time series. The dynamic experimental results indicate that the MSampEn is sensitive to complexity change of flow patterns including bubbly flow, stratified flow, plug flow and slug flow. MSampEn can characterize the flow behavior at different direction of two-phase flow, and reveal the transition between flow patterns when flow velocity changes. The proposed method is effective to analyze two-phase flow pattern transition by incorporating information of different scales and different spatial directions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

a Novel Approach to Veterinary Spatial Epidemiology: Dasymetric Refinement of the Swiss Dog Tumor Registry Data

NASA Astrophysics Data System (ADS)

Boo, G.; Fabrikant, S. I.; Leyk, S.

2015-08-01

In spatial epidemiology, disease incidence and demographic data are commonly summarized within larger regions such as administrative units because of privacy concerns. As a consequence, analyses using these aggregated data are subject to the Modifiable Areal Unit Problem (MAUP) as the geographical manifestation of ecological fallacy. In this study, we create small area disease estimates through dasymetric refinement, and investigate the effects on predictive epidemiological models. We perform a binary dasymetric refinement of municipality-aggregated dog tumor incidence counts in Switzerland for the year 2008 using residential land as a limiting ancillary variable. This refinement is expected to improve the quality of spatial data originally aggregated within arbitrary administrative units by deconstructing them into discontinuous subregions that better reflect the underlying population distribution. To shed light on effects of this refinement, we compare a predictive statistical model that uses unrefined administrative units with one that uses dasymetrically refined spatial units. Model diagnostics and spatial distributions of model residuals are assessed to evaluate the model performances in different regions. In particular, we explore changes in the spatial autocorrelation of the model residuals due to spatial refinement of the enumeration units in a selected mountainous region, where the rugged topography induces great shifts of the analytical units i.e., residential land. Such spatial data quality refinement results in a more realistic estimation of the population distribution within administrative units, and thus, in a more accurate modeling of dog tumor incidence patterns. Our results emphasize the benefits of implementing a dasymetric modeling framework in veterinary spatial epidemiology.

Spatial variation of pneumonia hospitalization risk in Twin Cities metro area, Minnesota.

PubMed

Iroh Tam, P Y; Krzyzanowski, B; Oakes, J M; Kne, L; Manson, S

2017-11-01

Fine resolution spatial variability in pneumonia hospitalization may identify correlates with socioeconomic, demographic and environmental factors. We performed a retrospective study within the Fairview Health System network of Minnesota. Patients 2 months of age and older hospitalized with pneumonia between 2011 and 2015 were geocoded to their census block group, and pneumonia hospitalization risk was analyzed in relation to socioeconomic, demographic and environmental factors. Spatial analyses were performed using Esri's ArcGIS software, and multivariate Poisson regression was used. Hospital encounters of 17 840 patients were included in the analysis. Multivariate Poisson regression identified several significant associations, including a 40% increased risk of pneumonia hospitalization among census block groups with large, compared with small, populations of ⩾65 years, a 56% increased risk among census block groups in the bottom (first) quartile of median household income compared to the top (fourth) quartile, a 44% higher risk in the fourth quartile of average nitrogen dioxide emissions compared with the first quartile, and a 47% higher risk in the fourth quartile of average annual solar insolation compared to the first quartile. After adjusting for income, moving from the first to the second quartile of the race/ethnic diversity index resulted in a 21% significantly increased risk of pneumonia hospitalization. In conclusion, the risk of pneumonia hospitalization at the census-block level is associated with age, income, race/ethnic diversity index, air quality, and solar insolation, and varies by region-specific factors. Identifying correlates using fine spatial analysis provides opportunities for targeted prevention and control.

Analysis of Mining Terrain Deformation Characteristics with Deformation Information System

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Milczarek, Wojciech; Grzempowski, Piotr

2014-05-01

Mapping and prediction of mining related deformations of the earth surface is an important measure for minimising threat to surface infrastructure, human population, the environment and safety of the mining operation itself arising from underground extraction of useful minerals. The number of methods and techniques used for monitoring and analysis of mining terrain deformations is wide and increasing with the development of geographical information technologies. These include for example: terrestrial geodetic measurements, global positioning systems, remote sensing, spatial interpolation, finite element method modelling, GIS based modelling, geological modelling, empirical modelling using the Knothe theory, artificial neural networks, fuzzy logic calculations and other. The aim of this paper is to introduce the concept of an integrated Deformation Information System (DIS) developed in geographic information systems environment for analysis and modelling of various spatial data related to mining activity and demonstrate its applications for mapping and visualising, as well as identifying possible mining terrain deformation areas with various spatial modelling methods. The DIS concept is based on connected modules that include: the spatial database - the core of the system, the spatial data collection module formed by: terrestrial, satellite and remote sensing measurements of the ground changes, the spatial data mining module for data discovery and extraction, the geological modelling module, the spatial data modeling module with data processing algorithms for spatio-temporal analysis and mapping of mining deformations and their characteristics (e.g. deformation parameters: tilt, curvature and horizontal strain), the multivariate spatial data classification module and the visualization module allowing two-dimensional interactive and static mapping and three-dimensional visualizations of mining ground characteristics. The Systems's functionality has been presented on the case study of a coal mining region in SW Poland where it has been applied to study characteristics and map mining induced ground deformations in a city in the last two decades of underground coal extraction and in the first decade after the end of mining. The mining subsidence area and its deformation parameters (tilt and curvature) have been calculated and the latter classified and mapped according to the Polish regulations. In addition possible areas of ground deformation have been indicated based on multivariate spatial data analysis of geological and mining operation characteristics with the geographically weighted regression method.

PAH Formation in O-rich Evolved Stars

NASA Astrophysics Data System (ADS)

Guzman-Ramirez, L.; Lagadec, E.; Jones, D.; Zijlstra, A. A.; Gesicki, K.

2015-08-01

Polycyclic aromatic hydrocarbons (PAHs) have been observed in O-rich planetary nebulae. This combination of oxygen-rich and carbon-rich material, known as dual-dust or mixed chemistry, is not expected to be seen around these objects. We recently proposed that PAHs could be formed from the photodissociation of CO in dense tori. Using VISIR/VLT, we spatially resolved the emission of the PAH bands and ionised emission from the [S IV] line, confirming the presence of dense central tori in all the observed O-rich objects. Furthermore, we show that for most of the objects, PAHs are located at the outer edge of these dense/compact tori, while the ionised material is mostly present in the inner parts, consistent with our hypothesis for the formation of PAHs in these systems. The presence of a dense torus has been strongly associated with the action of a central binary star and, as such, the rich chemistry seen in these regions may also be related to the formation of exoplanets in post-common-envelope binary systems.

Phase-field model for isothermal phase transitions in binary alloys

NASA Technical Reports Server (NTRS)

Wheeler, A. A.; Boettinger, W. J.; Mcfadden, G. B.

1992-01-01

A new phase field model is described which models isothermal phase transitions between ideal binary alloy solution phases. Equations are developed for the temporal and spatial variation of the phase field, which describes the identity of the phase, and of the composition. An asymptotic analysis, as the gradient energy coefficient of the phase field becomes small, was conducted. From the analysis, it is shown that the model recovers classical sharp interface models of this situation when the interfacial layers are thin, and they show how to relate the parameters appearing in the phase field model to material and growth parameters in real systems. Further, three stages of temporal evolution are identified: the first corresponding to interfacial genesis which occurs very rapidly; the second to interfacial motion controlled by the local energy difference across the interface and diffusion; the last taking place on a long time scale in which curvature effects are important and which correspond to Ostwald ripening. The results of the numerical calculations are presented.

Directional Solidification of a Binary Alloy into a Cellular Convective Flow: Localized Morphologies

NASA Technical Reports Server (NTRS)

Chen, Y.- J.; Davis, S. H.

1999-01-01

A steady, two dimensional cellular convection modifies the morphological instability of a binary alloy that undergoes directional solidification. When the convection wavelength is far longer than that of the morphological cells, the behavior of the moving front is described by a slow, spatial-temporal dynamics obtained through a multiple-scale analysis. The resulting system has a "parametric-excitation" structure in space, with complex parameters characterizing the interactions between flow, solute diffusion, and rejection. The convection stabilizes two dimensional disturbances oriented with the flow, but destabilizes three dimensional disturbances in general. When the flow is weak, the morphological instability behaves incommensurably to the flow wavelength, but becomes quantized and forced to fit into the flow-box as the flow gets stronger. At large flow magnitudes the instability is localized, confined in narrow envelopes with cells traveling with the flow. In this case the solutions are discrete eigenstates in an unbounded space. Their stability boundary and asymptotics are obtained by the WKB analysis.

Learning multivariate distributions by competitive assembly of marginals.

PubMed

Sánchez-Vega, Francisco; Younes, Laurent; Geman, Donald

2013-02-01

We present a new framework for learning high-dimensional multivariate probability distributions from estimated marginals. The approach is motivated by compositional models and Bayesian networks, and designed to adapt to small sample sizes. We start with a large, overlapping set of elementary statistical building blocks, or "primitives," which are low-dimensional marginal distributions learned from data. Each variable may appear in many primitives. Subsets of primitives are combined in a Lego-like fashion to construct a probabilistic graphical model; only a small fraction of the primitives will participate in any valid construction. Since primitives can be precomputed, parameter estimation and structure search are separated. Model complexity is controlled by strong biases; we adapt the primitives to the amount of training data and impose rules which restrict the merging of them into allowable compositions. The likelihood of the data decomposes into a sum of local gains, one for each primitive in the final structure. We focus on a specific subclass of networks which are binary forests. Structure optimization corresponds to an integer linear program and the maximizing composition can be computed for reasonably large numbers of variables. Performance is evaluated using both synthetic data and real datasets from natural language processing and computational biology.

Contribution made by multivariate curve resolution applied to gel permeation chromatography-Fourier transform infrared data for an in-depth characterization of styrene-butadiene rubber blends.

PubMed

Ruckebusch, C; Vilmin, F; Coste, N; Huvenne, J P

2008-07-01

We evaluate the contribution made by multivariate curve resolution-alternating least squares (MCR-ALS) for resolving gel permeation chromatography-Fourier transform infrared (GPC-FT-IR) data collected on butadiene rubber (BR) and styrene butadiene rubber (SBR) blends in order to access in-depth knowledge of polymers along the molecular weight distribution (MWD). In the BR-SBR case, individual polymers differ in chemical composition but share almost the same MWD. Principal component analysis (PCA) gives a general overview of the data structure and attests to the feasibility of modeling blends as a binary system. MCR-ALS is then performed. It allows resolving the chromatographic coelution and validates the chosen methodology. For SBR-SBR blends, the problem is more challenging since the individual elastomers present the same chemical composition. Rank deficiency is detected from the PCA data structure analysis. MCR-ALS is thus performed on column-wise augmented matrices. It brings very useful insight into the composition of the analyzed blends. In particular, a weak change in the composition of individual SBR in the MWD's lowest mass region is revealed.

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

PubMed Central

Broadaway, K. Alaine; Cutler, David J.; Duncan, Richard; Moore, Jacob L.; Ware, Erin B.; Jhun, Min A.; Bielak, Lawrence F.; Zhao, Wei; Smith, Jennifer A.; Peyser, Patricia A.; Kardia, Sharon L.R.; Ghosh, Debashis; Epstein, Michael P.

2016-01-01

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy. PMID:26942286

[Predictive factors of complications during CT-guided transthoracic biopsy].

PubMed

Fontaine-Delaruelle, C; Souquet, P-J; Gamondes, D; Pradat, E; de Leusse, A; Ferretti, G R; Couraud, S

2017-04-01

CT-guided transthoracic core-needle biopsy (TTNB) is frequently used for the diagnosis of lung nodules. The aim of this study is to describe TTNBs' complications and to investigate predictive factors of complications. All consecutive TTNBs performed in three centers between 2006 and 2012 were included. Binary logistic regression was used for multivariate analysis. Overall, 970 TTNBs were performed in 929 patients. The complication rate was 34% (life-threatening complication in 6%). The most frequent complications were pneumothorax (29% included 4% which required chest-tube) and hemoptysis (5%). The mortality rate was 0.1% (n=1). In multivariate analysis, predictive factor for a complication was small target size (AOR=0.984; 95% CI [0.976-0.992]; P<0.001). This predictive factor was also found for occurrence of life-threatening complication (AOR=0.982; [0.965-0.999]; P=0.037), of pneumothorax (AOR=0.987; [0.978-0.995]; P=0.002) and of hemoptysis (AOR=0.973; [0.951-0.997]; P=0.024). One complication occurred in one-third of TTNBs. The proportion of life-threatening complication was 6%. A small lesion size was predictive of complication occurrence. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer

PubMed Central

Kelly, P; Paulin, F; Lamont, D; Baker, L; Clearly, S; Exon, D; Thompson, A

2012-01-01

Background: The incidence of oesophageal adenocarcinoma is increasing worldwide but survival remains poor. Neoadjuvant chemotherapy can improve survival, but prognostic and predictive biomarkers are required. This study built upon preclinical approaches to identify prognostic plasma proteomic markers in oesophageal cancer. Methods: Plasma samples collected before and during the treatment of oesophageal cancer and non-cancer controls were analysed by surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) mass spectroscopy (MS). Protein peaks were identified by MS in tryptic digests of purified fractions. Associations between peak intensities obtained in the spectra and clinical endpoints (survival, disease-free survival) were tested by univariate (Fisher's exact test) and multivariate analysis (binary logistic regression). Results: Plasma protein peaks were identified that differed significantly (P<0.05, ANOVA) between the oesophageal cancer and control groups at baseline. Three peaks, confirmed as apolipoprotein A-I, serum amyloid A and transthyretin, in baseline (pre-treatment) samples were associated by univariate and multivariate analysis with disease-free survival and overall survival. Conclusion: Plasma proteins can be detected prior to treatment for oesophageal cancer that are associated with outcome and merit testing as prognostic and predictive markers of response to guide chemotherapy in oesophageal cancer. PMID:22294182

Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer.

PubMed

Kelly, P; Paulin, F; Lamont, D; Baker, L; Clearly, S; Exon, D; Thompson, A

2012-02-28

The incidence of oesophageal adenocarcinoma is increasing worldwide but survival remains poor. Neoadjuvant chemotherapy can improve survival, but prognostic and predictive biomarkers are required. This study built upon preclinical approaches to identify prognostic plasma proteomic markers in oesophageal cancer. Plasma samples collected before and during the treatment of oesophageal cancer and non-cancer controls were analysed by surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) mass spectroscopy (MS). Protein peaks were identified by MS in tryptic digests of purified fractions. Associations between peak intensities obtained in the spectra and clinical endpoints (survival, disease-free survival) were tested by univariate (Fisher's exact test) and multivariate analysis (binary logistic regression). Plasma protein peaks were identified that differed significantly (P<0.05, ANOVA) between the oesophageal cancer and control groups at baseline. Three peaks, confirmed as apolipoprotein A-I, serum amyloid A and transthyretin, in baseline (pre-treatment) samples were associated by univariate and multivariate analysis with disease-free survival and overall survival. Plasma proteins can be detected prior to treatment for oesophageal cancer that are associated with outcome and merit testing as prognostic and predictive markers of response to guide chemotherapy in oesophageal cancer.

X-ray Spectral Formation In High-mass X-ray Binaries: The Case Of Vela X-1

NASA Astrophysics Data System (ADS)

Akiyama, Shizuka; Mauche, C. W.; Liedahl, D. A.; Plewa, T.

2007-05-01

We are working to develop improved models of radiatively-driven mass flows in the presence of an X-ray source -- such as in X-ray binaries, cataclysmic variables, and active galactic nuclei -- in order to infer the physical properties that determine the X-ray spectra of such systems. The models integrate a three-dimensional time-dependent hydrodynamics capability (FLASH); a comprehensive and uniform set of atomic data, improved calculations of the line force multiplier that account for X-ray photoionization and non-LTE population kinetics, and X-ray emission-line models appropriate to X-ray photoionized plasmas (HULLAC); and a Monte Carlo radiation transport code that simulates Compton scattering and recombination cascades following photoionization. As a test bed, we have simulated a high-mass X-ray binary with parameters appropriate to Vela X-1. While the orbital and stellar parameters of this system are well constrained, the physics of X-ray spectral formation is less well understood because the canonical analytical wind velocity profile of OB stars does not account for the dynamical and radiative feedback effects due to the rotation of the system and to the irradiation of the stellar wind by X-rays from the neutron star. We discuss the dynamical wind structure of Vela X-1 as determined by the FLASH simulation, where in the binary the X-ray emission features originate, and how the spatial and spectral properties of the X-ray emission features are modified by Compton scattering, photoabsorption, and fluorescent emission. This work was performed under the auspices of the U.S. Department of Energy by University of California, Lawrence Livermore National Laboratory under Contract W-7405-Eng-48.

CONSTRAINING RELATIVISTIC BOW SHOCK PROPERTIES IN ROTATION-POWERED MILLISECOND PULSAR BINARIES.

PubMed

Wadiasingh, Zorawar; Harding, Alice K; Venter, Christo; Böttcher, Markus; Baring, Matthew G

2017-04-20

Multiwavelength followup of unidentified Fermi sources has vastly expanded the number of known galactic-field "black widow" and "redback" millisecond pulsar binaries. Focusing on their rotation-powered state, we interpret the radio to X-ray phenomenology in a consistent framework. We advocate the existence of two distinct modes differing in their intrabinary shock orientation, distinguished by the phase-centering of the double-peaked X-ray orbital modulation originating from mildly-relativistic Doppler boosting. By constructing a geometric model for radio eclipses, we constrain the shock geometry as functions of binary inclination and shock stand-off R 0 . We develop synthetic X-ray synchrotron orbital light curves and explore the model parameter space allowed by radio eclipse constraints applied on archetypal systems B1957+20 and J1023+0038. For B1957+20, from radio eclipses the stand-off is R 0 ~ 0.15-0.3 fraction of binary separation from the companion center, depending on the orbit inclination. Constructed X-ray light curves for B1957+20 using these values are qualitatively consistent with those observed, and we find occultation of the shock by the companion as a minor influence, demanding significant Doppler factors to yield double peaks. For J1023+0038, radio eclipses imply R 0 ≲ 0.4 while X-ray light curves suggest 0.1 ≲ R 0 ≲ 0.3 (from the pulsar). Degeneracies in the model parameter space encourage further development to include transport considerations. Generically, the spatial variation along the shock of the underlying electron power-law index should yield energy-dependence in the shape of light curves motivating future X-ray phase-resolved spectroscopic studies to probe the unknown physics of pulsar winds and relativistic shock acceleration therein.

Eta Carinae: An Astrophysical Laboratory to Study Conditions During the Transition Between a Pseudo-Supernova and a Supernova

NASA Astrophysics Data System (ADS)

McKinnon, Darren; Gull, T. R.; Madura, T.

2014-01-01

A major puzzle in the studies of supernovae is the pseudo-supernova, or the near-supernovae state. It has been found to precede, in timespans ranging from months to years, a number of recently-detected distant supernovae. One explanation of these systems is that a member of a massive binary underwent a near-supernova event shortly before the actual supernova phenomenon. Luckily, we have a nearby massive binary, Eta Carinae, that provides an astrophysical laboratory of a near-analog. The massive, highly-eccentric, colliding-wind binary star system survived a non-terminal stellar explosion in the 1800's, leaving behind the incredible bipolar, 10"x20" Homunculus nebula. Today, the interaction of the binary stellar winds 1") is resolvable by the Space Telescope Imaging Spectrograph (STIS) aboard the Hubble Space Telescope (HST). Using HST/STIS, several three-dimensional (3D) data cubes (2D spatial, 1D velocity) have been obtained at selected phases during Eta Carinae's 5.54-year orbital cycle. The data cubes were collected by mapping the central 1-2" at 0.05" intervals with a 52"x0.1" aperture. Selected forbidden lines, that form in the colliding wind regions, provide information on electron density of the shocked regions, the ionization by the hot secondary companion of the primary wind and how these regions change with orbital phase. By applying various analysis techniques to these data cubes, we can compare and measure temporal changes due to the interactions between the two massive winds. The observations, when compared to current 3D hydrodynamic models, provide insight on Eta Carinae's recent mass-loss history, important for determining the current and future states of this likely nearby supernova progenitor.

The twisted radio structure of PSO J334.2028+01.4075, still a supermassive binary black hole candidate

NASA Astrophysics Data System (ADS)

Mooley, K. P.; Wrobel, J. M.; Anderson, M. M.; Hallinan, G.

2018-01-01

Supermassive binary black holes (BBHs) on sub-parsec scales are prime targets for gravitational wave experiments. They also provide insights on close binary evolution and hierarchical structure formation. Sub-parsec BBHs cannot be spatially resolved but indirect methods can identify candidates. In 2015 Liu et al. reported an optical-continuum periodicity in the quasar PSO J334.2028+01.4075, with the estimated mass and rest-frame period suggesting an orbital separation of about 0.006 pc (0.7 μ arcsec). The persistence of the quasar's optical periodicity has recently been disfavoured over an extended baseline. However, if a radio jet is launched from a sub-parsec BBH, the binary's properties can influence the radio structure on larger scales. Here, we use the Very Long Baseline Array (VLBA) and Karl G. Jansky Very Large Array (VLA) to study the parsec- and kiloparsec-scale emission energized by the quasar's putative BBH. We find two VLBA components separated by 3.6 mas (30 pc), tentatively identifying one as the VLBA 'core' from which the other was ejected. The VLBA components contribute to a point-like, time-variable VLA source that is straddled by lobes spanning 8 arcsec (66 kpc). We classify PSO J334.2028+01.4075 as a lobe-dominated quasar, albeit with an atypically large twist of 39° between its elongation position angles on parsec- and kiloparsec-scales. By analogy with 3C 207, a well-studied lobe-dominated quasar with a similarly-rare twist, we speculate that PSO J334.2028+01.4075 could be ejecting jet components over an inner cone that traces a precessing jet in a BBH system.

CONSTRAINING RELATIVISTIC BOW SHOCK PROPERTIES IN ROTATION-POWERED MILLISECOND PULSAR BINARIES

PubMed Central

Wadiasingh, Zorawar; Harding, Alice K.; Venter, Christo; Böttcher, Markus; Baring, Matthew G.

2018-01-01

Multiwavelength followup of unidentified Fermi sources has vastly expanded the number of known galactic-field “black widow” and “redback” millisecond pulsar binaries. Focusing on their rotation-powered state, we interpret the radio to X-ray phenomenology in a consistent framework. We advocate the existence of two distinct modes differing in their intrabinary shock orientation, distinguished by the phase-centering of the double-peaked X-ray orbital modulation originating from mildly-relativistic Doppler boosting. By constructing a geometric model for radio eclipses, we constrain the shock geometry as functions of binary inclination and shock stand-off R0. We develop synthetic X-ray synchrotron orbital light curves and explore the model parameter space allowed by radio eclipse constraints applied on archetypal systems B1957+20 and J1023+0038. For B1957+20, from radio eclipses the stand-off is R0 ~ 0.15–0.3 fraction of binary separation from the companion center, depending on the orbit inclination. Constructed X-ray light curves for B1957+20 using these values are qualitatively consistent with those observed, and we find occultation of the shock by the companion as a minor influence, demanding significant Doppler factors to yield double peaks. For J1023+0038, radio eclipses imply R0 ≲ 0.4 while X-ray light curves suggest 0.1 ≲ R0 ≲ 0.3 (from the pulsar). Degeneracies in the model parameter space encourage further development to include transport considerations. Generically, the spatial variation along the shock of the underlying electron power-law index should yield energy-dependence in the shape of light curves motivating future X-ray phase-resolved spectroscopic studies to probe the unknown physics of pulsar winds and relativistic shock acceleration therein. PMID:29651167

Constraining Relativistic Bow Shock Properties in Rotation-Powered Millisecond Pulsar Binaries

NASA Technical Reports Server (NTRS)

Wadiasingh, Zorawar; Harding, Alice K.; Venter, Christo; Bottcher, Markus; Baring, Matthew G.

2017-01-01

Multiwavelength follow-up of unidentified Fermi sources has vastly expanded the number of known galactic-field "black widow" and "redback" millisecond pulsar binaries. Focusing on their rotation-powered state, we interpret the radio to X-ray phenomenology in a consistent framework. We advocate the existence of two distinct modes differing in their intrabinary shock orientation, distinguished by the phase-centering of the double-peaked X-ray orbital modulation originating from mildly-relativistic Doppler boosting. By constructing a geometric model for radio eclipses, we constrain the shock geometry as functions of binary inclination and shock stand-off R(sub 0). We develop synthetic X-ray synchrotron orbital light curves and explore the model parameter space allowed by radio eclipse constraints applied on archetypal systems B1957+20 and J1023+0038. For B1957+20, from radio eclipses the stand-off is R(sub 0) approximately 0:15 - 0:3 fraction of binary separation from the companion center, depending on the orbit inclination. Constructed X-ray light curves for B1957+20 using these values are qualitatively consistent with those observed, and we find occultation of the shock by the companion as a minor influence, demanding significant Doppler factors to yield double peaks. For J1023+0038, radio eclipses imply R(sub 0) is approximately less than 0:4 while X-ray light curves suggest 0:1 is approximately less than R(sub 0) is approximately less than 0:3 (from the pulsar). Degeneracies in the model parameter space encourage further development to include transport considerations. Generically, the spatial variation along the shock of the underlying electron power-law index should yield energy-dependence in the shape of light curves motivating future X-ray phase-resolved spectroscopic studies to probe the unknown physics of pulsar winds and relativistic shock acceleration therein.

Constraining Relativistic Bow Shock Properties in Rotation-powered Millisecond Pulsar Binaries

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

Wadiasingh, Zorawar; Venter, Christo; Böttcher, Markus

2017-04-20

Multiwavelength follow-up of unidentified Fermi sources has vastly expanded the number of known galactic-field “black widow” and “redback” millisecond pulsar binaries. Focusing on their rotation-powered state, we interpret the radio to X-ray phenomenology in a consistent framework. We advocate the existence of two distinct modes differing in their intrabinary shock orientation, distinguished by the phase centering of the double-peaked X-ray orbital modulation originating from mildly relativistic Doppler boosting. By constructing a geometric model for radio eclipses, we constrain the shock geometry as functions of binary inclination and shock standoff R {sub 0}. We develop synthetic X-ray synchrotron orbital light curvesmore » and explore the model parameter space allowed by radio eclipse constraints applied on archetypal systems B1957+20 and J1023+0038. For B1957+20, from radio eclipses the standoff is R {sub 0} ∼ 0.15–0.3 fraction of binary separation from the companion center, depending on the orbit inclination. Constructed X-ray light curves for B1957+20 using these values are qualitatively consistent with those observed, and we find occultation of the shock by the companion as a minor influence, demanding significant Doppler factors to yield double peaks. For J1023+0038, radio eclipses imply R {sub 0} ≲ 0.4, while X-ray light curves suggest 0.1 ≲ R {sub 0} ≲ 0.3 (from the pulsar). Degeneracies in the model parameter space encourage further development to include transport considerations. Generically, the spatial variation along the shock of the underlying electron power-law index should yield energy dependence in the shape of light curves, motivating future X-ray phase-resolved spectroscopic studies to probe the unknown physics of pulsar winds and relativistic shock acceleration therein.« less

Separating the Spectral Components of the Massive Triple Star System Delta Orionis

NASA Astrophysics Data System (ADS)

Gies, Douglas

2013-10-01

The multiple star system of delta Orionis represents one of the closest examples of a luminous O-star with a strong stellar wind, and it was the target of a recent multi-wavelength campaign to determine the source of the wind X-ray emission. It consists of aclose eclipsing binary with a more distant tertiary, and all the components are massive stars. Investigations of the radial velocity curves of the eclipsing system are made difficult by severe line blending with the spectral lines of the tertiary star, and the resulting mass estimates range by a factor of two. We propose that the solution to this problem is to isolate the flux of the tertiary through high angular resolutionspectroscopy with HST/STIS, and we show how a two visit program of ultraviolet and spatially resolved spectroscopy will provide us with the means to characterize the spectra of all three stars in the triple. This will allow us to reassess a large body of existing optical and UV spectroscopy and determine reliable radial velocity curves for the components in the close binary. By then fitting a new high precision light curve from MOST photometry, we will derive accurate masses, temperatures, radii, and projected rotational velocities for all the components. The inner binary also hasa measured apsidal period, and the new results will form a key test of models of interior structure. The analysis will also provide secure estimates for the geometry and size of the inner binary and the radius of the secondary, the parameters required to analyze the orbital phase variations and sites of origin of the wind X-ray emission documented in a recent Chandra/HETGS program.

Minimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection

USGS Publications Warehouse

Jarnevich, Catherine S.; Talbert, Marian; Morisette, Jeffrey T.; Aldridge, Cameron L.; Brown, Cynthia; Kumar, Sunil; Manier, Daniel; Talbert, Colin; Holcombe, Tracy R.

2017-01-01

Evaluating the conditions where a species can persist is an important question in ecology both to understand tolerances of organisms and to predict distributions across landscapes. Presence data combined with background or pseudo-absence locations are commonly used with species distribution modeling to develop these relationships. However, there is not a standard method to generate background or pseudo-absence locations, and method choice affects model outcomes. We evaluated combinations of both model algorithms (simple and complex generalized linear models, multivariate adaptive regression splines, Maxent, boosted regression trees, and random forest) and background methods (random, minimum convex polygon, and continuous and binary kernel density estimator (KDE)) to assess the sensitivity of model outcomes to choices made. We evaluated six questions related to model results, including five beyond the common comparison of model accuracy assessment metrics (biological interpretability of response curves, cross-validation robustness, independent data accuracy and robustness, and prediction consistency). For our case study with cheatgrass in the western US, random forest was least sensitive to background choice and the binary KDE method was least sensitive to model algorithm choice. While this outcome may not hold for other locations or species, the methods we used can be implemented to help determine appropriate methodologies for particular research questions.

Phase synchrony reveals organization in human atrial fibrillation

PubMed Central

Vidmar, David; Narayan, Sanjiv M.

2015-01-01

It remains unclear if human atrial fibrillation (AF) is spatially nonhierarchical or exhibits a hierarchy of organization sustained by sources. We utilize activation times obtained at discrete locations during AF to compute the phase synchrony between tissue regions, to examine underlying spatial dynamics throughout both atria. We construct a binary synchronization network and show that this network can accurately define regions of coherence in coarse-grained in silico data. Specifically, domains controlled by spiral waves exhibit regions of high phase synchrony. We then apply this analysis to clinical data from patients experiencing cardiac arrhythmias using multielectrode catheters to simultaneously record from a majority of both atria. We show that pharmaceutical intervention with ibutilide organizes activation by increasing the size of the synchronized domain in AF and quantify the increase in temporal organization when arrhythmia changes from fibrillation to tachycardia. Finally, in recordings from 24 patients in AF we show that the level of synchrony is spatially broad with some patients showing large spatially contiguous regions of synchronization, while in others synchrony is localized to small pockets. Using computer simulations, we show that this distribution is inconsistent with distributions obtained from simulations that mimic multiwavelet reentry but is consistent with mechanisms in which one or more spatially conserved spiral waves is surrounded by tissue in which activation is disorganized. PMID:26475585

Thermodynamically consistent Langevin dynamics with spatially correlated noise predicting frictionless regime and transient attraction effect

NASA Astrophysics Data System (ADS)

Majka, M.; Góra, P. F.

2016-10-01

While the origins of temporal correlations in Langevin dynamics have been thoroughly researched, the understanding of spatially correlated noise (SCN) is rather incomplete. In particular, very little is known about the relation between friction and SCN. In this article, starting from the microscopic, deterministic model, we derive the analytical formula for the spatial correlation function in the particle-bath interactions. This expression shows that SCN is the inherent component of binary mixtures, originating from the effective (entropic) interactions. Further, employing this spatial correlation function, we postulate the thermodynamically consistent Langevin equation driven by the Gaussian SCN and calculate the adequate fluctuation-dissipation relation. The thermodynamical consistency is achieved by introducing the spatially variant friction coefficient, which can be also derived analytically. This coefficient exhibits a number of intriguing properties, e.g., the singular behavior for certain types of interactions. Eventually, we apply this new theory to the system of two charged particles in the presence of counter-ions. Such particles interact via the screened-charge Yukawa potential and the inclusion of SCN leads to the emergence of the anomalous frictionless regime. In this regime the particles can experience active propulsion leading to the transient attraction effect. This effect suggests a nonequilibrium mechanism facilitating the molecular binding of the like-charged particles.

Rotating and Binary Stars in General Relativit

NASA Astrophysics Data System (ADS)

Shapiro, Stuart

The inspiral and coalescence of compact binary stars is one of the most challenging problems in theoretical astrophysics. Only recently have advances in numerical relativity made it possible to explore this topic in full general relativity (GR). The mergers of compact binaries have important consequences for the detection of gravitational waves. In addition, the coalescence of binary neutron stars (NSNSs) and binary black-hole neutron stars (BHNSs) may hold the key for resolving other astrophysical puzzles, such as the origin of short-hard gamma-ray bursts (GRBs). While simulations of these systems in full GR are now possible, only the most idealized treatments have been performed to date. More detailed physics, including magnetic fields, black hole spin, a realistic hot, nuclear equation of state and neutrino transport must be incorporated. Only then will we be able to identify reliably future sources that may be detected simultaneously in gravitational waves and as GRBs. Likewise, the coalescence of binary black holes (BHBHs) is now a solved problem in GR, but only in vacuum. Simulating the coalescence of BHBHs in the gaseous environments likely to be found in nearby galaxy cores or in merging galaxies is crucial to identifying an electromagnetic signal that might accompany the gravitational waves produced during the merger. The coalescence of a binary white dwarf-neutron star (WDNS) has only recently been treated in GR, but GR is necessary to explore tidal disruption scenarios in which the capture of WD debris by the NS may lead to catastrophic collapse. Alternatively, the NS may survive and the merger might result in the formation of pulsar planets. The stability of rotating neutron stars in these and other systems has not been fully explored in GR, and the final fate of unstable stars has not been determined in many cases, especially in the presence of magnetic fields and differential rotation. These systems will be probed observationally by current NASA instruments, such as HST, CHANDRA, SWIFT and FERMI, and by future NASA detectors, such as NuStar, ASTRO-H, GEMS, JWST, and, possibly, GEN-X and SGO (a Space-Based Gravitational-Wave Observatory). Treating all of these phenomena theoretically requires the same computational machinery: a fully relativistic code that simultaneously solves Einstein s equations for the gravitational field, Maxwell s equations for the electromagnetic field and the equations of relativistic magnetohydrodynamics for the plasma, all in three spatial dimensions plus time. Recent advances we have made in constructing such a code now make it possible for us to solve these fundamental, closely related computational problems, some for the first time.

Asteroid Satellites

NASA Astrophysics Data System (ADS)

Merline, W. J.

2001-11-01

Discovery and study of small satellites of asteroids or double asteroids can yield valuable information about the intrinsic properties of asteroids themselves and about their history and evolution. Determination of the orbits of these moons can provide precise masses of the primaries, and hence reliable estimates of the fundamental property of bulk density. This reveals much about the composition and structure of the primary and will allow us to make comparisons between, for example, asteroid taxonomic type and our inventory of meteorites. The nature and prevalence of these systems will also give clues as to the collisional environment in which they formed, and have further implications for the role of collisions in shaping our solar system. A decade ago, binary asteroids were more of a theoretical curiosity. In 1993, the Galileo spacecraft allowed the first undeniable detection of an asteroid moon, with the discovery of Dactyl, a small moon of Ida. Since that time, and particularly in the last year, the number of known binaries has risen dramatically. Previously odd-shaped and lobate near-Earth asteroids, observed by radar, have given way to signatures indicating, almost certainly, that at least four NEAs are binary systems. The tell-tale lightcurves of several other NEAs reveal a high likelihood of being double. Indications are that among the NEAs, there may be a binary frequency of several tens of percent. Among the main-belt asteroids, we now know of 6 confirmed binary systems, although their overall frequency is likely to be low, perhaps a few percent. The detections have largely come about because of significant advances in adaptive optics systems on large telescopes, which can now reduce the blurring of the Earth's atmosphere to compete with the spatial resolution of space-based imaging (which itself, via HST, is now contributing valuable observations). Most of these binary systems have similarities, but there are important exceptions. Searches among other dynamical populations such as the Trojans and KBOs are also proving fruitful. Similarities and differences among the detected systems are thus revealing important clues about the possible formation mechanisms. There are several theories seeking to explain the origin of these binary systems, all of them involving collisions of one type or another, either physical or gravitational. It is likely that several of the mechanisms will be required to explain the observations. Now that we have reliable techniques for detection, we have been rewarded with many examples of systems for study. This has in turn spurred new theoretical thinking and numerical simulations, the techniques for which have also improved substantially in recent years.

Temporal and spatial analysis of psittacosis in association with poultry farming in the Netherlands, 2000-2015.

PubMed

Hogerwerf, Lenny; Holstege, Manon M C; Benincà, Elisa; Dijkstra, Frederika; van der Hoek, Wim

2017-07-26

Human psittacosis is a highly under diagnosed zoonotic disease, commonly linked to psittacine birds. Psittacosis in birds, also known as avian chlamydiosis, is endemic in poultry, but the risk for people living close to poultry farms is unknown. Therefore, our study aimed to explore the temporal and spatial patterns of human psittacosis infections and identify possible associations with poultry farming in the Netherlands. We analysed data on 700 human cases of psittacosis notified between 01-01-2000 and 01-09-2015. First, we studied the temporal behaviour of psittacosis notifications by applying wavelet analysis. Then, to identify possible spatial patterns, we applied spatial cluster analysis. Finally, we investigated the possible spatial association between psittacosis notifications and data on the Dutch poultry sector at municipality level using a multivariable model. We found a large spatial cluster that covered a highly poultry-dense area but additional clusters were found in areas that had a low poultry density. There were marked geographical differences in the awareness of psittacosis and the amount and the type of laboratory diagnostics used for psittacosis, making it difficult to draw conclusions about the correlation between the large cluster and poultry density. The multivariable model showed that the presence of chicken processing plants and slaughter duck farms in a municipality was associated with a higher rate of human psittacosis notifications. The significance of the associations was influenced by the inclusion or exclusion of farm density in the model. Our temporal and spatial analyses showed weak associations between poultry-related variables and psittacosis notifications. Because of the low number of psittacosis notifications available for analysis, the power of our analysis was relative low. Because of the exploratory nature of this research, the associations found cannot be interpreted as evidence for airborne transmission of psittacosis from poultry to the general population. Further research is needed to determine the prevalence of C. psittaci in Dutch poultry. Also, efforts to promote PCR-based testing for C. psittaci and genotyping for source tracing are important to reduce the diagnostic deficit, and to provide better estimates of the human psittacosis burden, and the possible role of poultry.

New algorithm for detecting smaller retinal blood vessels in fundus images

NASA Astrophysics Data System (ADS)

LeAnder, Robert; Bidari, Praveen I.; Mohammed, Tauseef A.; Das, Moumita; Umbaugh, Scott E.

2010-03-01

About 4.1 million Americans suffer from diabetic retinopathy. To help automatically diagnose various stages of the disease, a new blood-vessel-segmentation algorithm based on spatial high-pass filtering was developed to automatically segment blood vessels, including the smaller ones, with low noise. Methods: Image database: Forty, 584 x 565-pixel images were collected from the DRIVE image database. Preprocessing: Green-band extraction was used to obtain better contrast, which facilitated better visualization of retinal blood vessels. A spatial highpass filter of mask-size 11 was applied. A histogram stretch was performed to enhance contrast. A median filter was applied to mitigate noise. At this point, the gray-scale image was converted to a binary image using a binary thresholding operation. Then, a NOT operation was performed by gray-level value inversion between 0 and 255. Postprocessing: The resulting image was AND-ed with its corresponding ring mask to remove the outer-ring (lens-edge) artifact. At this point, the above algorithm steps had extracted most of the major and minor vessels, with some intersections and bifurcations missing. Vessel segments were reintegrated using the Hough transform. Results: After applying the Hough transform, both the average peak SNR and the RMS error improved by 10%. Pratt's Figure of Merit (PFM) was decreased by 6%. Those averages were better than [1] by 10-30%. Conclusions: The new algorithm successfully preserved the details of smaller blood vessels and should prove successful as a segmentation step for automatically identifying diseases that affect retinal blood vessels.

Discrimination of isotrigon textures using the Rényi entropy of Allan variances.

PubMed

Gabarda, Salvador; Cristóbal, Gabriel

2008-09-01

We present a computational algorithm for isotrigon texture discrimination. The aim of this method consists in discriminating isotrigon textures against a binary random background. The extension of the method to the problem of multitexture discrimination is considered as well. The method relies on the fact that the information content of time or space-frequency representations of signals, including images, can be readily analyzed by means of generalized entropy measures. In such a scenario, the Rényi entropy appears as an effective tool, given that Rényi measures can be used to provide information about a local neighborhood within an image. Localization is essential for comparing images on a pixel-by-pixel basis. Discrimination is performed through a local Rényi entropy measurement applied on a spatially oriented 1-D pseudo-Wigner distribution (PWD) of the test image. The PWD is normalized so that it may be interpreted as a probability distribution. Prior to the calculation of the texture's PWD, a preprocessing filtering step replaces the original texture with its localized spatially oriented Allan variances. The anisotropic structure of the textures, as revealed by the Allan variances, turns out to be crucial later to attain a high discrimination by the extraction of Rényi entropy measures. The method has been empirically evaluated with a family of isotrigon textures embedded in a binary random background. The extension to the case of multiple isotrigon mosaics has also been considered. Discrimination results are compared with other existing methods.

Toward global crop type mapping using a hybrid machine learning approach and multi-sensor imagery

NASA Astrophysics Data System (ADS)

Wang, S.; Le Bras, S.; Azzari, G.; Lobell, D. B.

2017-12-01

Current global scale datasets on agricultural land use do not have sufficient spatial or temporal resolution to meet the needs of many applications. The recent rapid increase in public availability of fine- to moderate-resolution satellite imagery from Landsat OLI and Copernicus Sentinel-2 provides a unique opportunity to improve agricultural land use datasets. This project leverages these new satellite data streams, existing census data, and a novel training approach to develop global, annual maps that indicate the presence of (i) cropland and (ii) specific crops at a 20m resolution. Our machine learning methodology consists of two steps. The first is a supervised classifier trained with explicitly labelled data to distinguish between crop and non-crop pixels, creating a binary mask. For ground truth, we use labels collected by previous mapping efforts (e.g. IIASA's crowdsourced data (Fritz et al. 2015) and AFSIS's geosurvey data) in combination with new data collected manually. The crop pixels output by the binary mask are input to the second step: a semi-supervised clustering algorithm to resolve different crop types and generate a crop type map. We do not use field-level information on crop type to train the algorithm, making this approach scalable spatially and temporally. We instead incorporate size constraints on clusters based on aggregated agricultural land use statistics and other, more generalizable domain knowledge. We employ field-level data from the U.S., Southern Europe, and Eastern Africa to validate crop-to-cluster assignments.

JWST DD ERS Team Update: Decoding Smoke Signals from WR140 using NIRISS+AMI and MIRI/MRS

NASA Astrophysics Data System (ADS)

Lau, Ryan M.; Hankins, Matt; WR DustERS Team

2018-06-01

Dust is a key component of the interstellar medium and plays and important role in the formation of stars and planets. However, the dominant channels of dust production throughout cosmic time are uncertain. With its unprecedented sensitivity and spatial resolution in the mid-IR, the James Webb Space Telescope (JWST) is the ideal platform to address this issue by investigating the dust abundance, composition, and production rates of various dusty sources. In particular, colliding-wind Wolf-Rayet (WR) binaries are known to be efficient dust producers in the local Universe and likely existed in the earliest galaxies. In our Early Release Science (ERS) program, we will use JWST to observe the archetypal colliding-wind binary, WR 140, to study its dust composition, abundance, and formation mechanisms. We will utilize two key JWST observing modes with the medium-resolution spectrometer (MRS) on the Mid-Infrared Instrument (MIRI) and the Aperture Masking Interferometry (AMI) mode with the Near Infrared Imager and Slitless Spectrograph (NIRISS).Our planned observations will establish a benchmark for key observing modes for imaging bright sources with faint extended emission at high spatial resolutions. This will be valuable in various astrophysical contexts including mass-loss from evolved stars, dusty tori around active galactic nuclei, and protoplanetary disks. We are committed to delivering science-enabling products for the JWST community that include high-level pipeline tools to mitigate bright source artifacts and image reconstruction tools compatible with NIRISS+AMI data.

Spatial Statistical Model and Optimal Survey Design for Rapid Geophysical Characterization of UXO Sites

DTIC Science & Technology

2003-07-01

4, Gnanadesikan , 1977). An entity whose measured features fall into one of the regions is classified accordingly. For the approaches we discuss here... Gnanadesikan , R. 1977. Methods for Statistical Data Analysis of Multivariate Observations. John Wiley & Sons, New York. Hassig, N. L., O’Brien, R. F

An open source multivariate framework for n-tissue segmentation with evaluation on public data.

PubMed

Avants, Brian B; Tustison, Nicholas J; Wu, Jue; Cook, Philip A; Gee, James C

2011-12-01

We introduce Atropos, an ITK-based multivariate n-class open source segmentation algorithm distributed with ANTs ( http://www.picsl.upenn.edu/ANTs). The Bayesian formulation of the segmentation problem is solved using the Expectation Maximization (EM) algorithm with the modeling of the class intensities based on either parametric or non-parametric finite mixtures. Atropos is capable of incorporating spatial prior probability maps (sparse), prior label maps and/or Markov Random Field (MRF) modeling. Atropos has also been efficiently implemented to handle large quantities of possible labelings (in the experimental section, we use up to 69 classes) with a minimal memory footprint. This work describes the technical and implementation aspects of Atropos and evaluates its performance on two different ground-truth datasets. First, we use the BrainWeb dataset from Montreal Neurological Institute to evaluate three-tissue segmentation performance via (1) K-means segmentation without use of template data; (2) MRF segmentation with initialization by prior probability maps derived from a group template; (3) Prior-based segmentation with use of spatial prior probability maps derived from a group template. We also evaluate Atropos performance by using spatial priors to drive a 69-class EM segmentation problem derived from the Hammers atlas from University College London. These evaluation studies, combined with illustrative examples that exercise Atropos options, demonstrate both performance and wide applicability of this new platform-independent open source segmentation tool.

An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data

PubMed Central

Tustison, Nicholas J.; Wu, Jue; Cook, Philip A.; Gee, James C.

2012-01-01

We introduce Atropos, an ITK-based multivariate n-class open source segmentation algorithm distributed with ANTs (http://www.picsl.upenn.edu/ANTs). The Bayesian formulation of the segmentation problem is solved using the Expectation Maximization (EM) algorithm with the modeling of the class intensities based on either parametric or non-parametric finite mixtures. Atropos is capable of incorporating spatial prior probability maps (sparse), prior label maps and/or Markov Random Field (MRF) modeling. Atropos has also been efficiently implemented to handle large quantities of possible labelings (in the experimental section, we use up to 69 classes) with a minimal memory footprint. This work describes the technical and implementation aspects of Atropos and evaluates its performance on two different ground-truth datasets. First, we use the BrainWeb dataset from Montreal Neurological Institute to evaluate three-tissue segmentation performance via (1) K-means segmentation without use of template data; (2) MRF segmentation with initialization by prior probability maps derived from a group template; (3) Prior-based segmentation with use of spatial prior probability maps derived from a group template. We also evaluate Atropos performance by using spatial priors to drive a 69-class EM segmentation problem derived from the Hammers atlas from University College London. These evaluation studies, combined with illustrative examples that exercise Atropos options, demonstrate both performance and wide applicability of this new platform-independent open source segmentation tool. PMID:21373993

Assessment of the Spatial Distribution of Metal(Oid)s in Soils Around an Abandoned Pb-Smelter Plant

NASA Astrophysics Data System (ADS)

dos Santos, Nielson Machado; do Nascimento, Clístenes Williams Araújo; Matschullat, Jörg; de Olinda, Ricardo Alves

2017-03-01

Todos os Santos (All Saints) Bay area, NE-Brazil, is known for one of the most important cases of urban lead (Pb) contamination in the world. The main objective of this work was to assess and interpret the spatial distribution of As, Cd, Hg, Pb, and Zn in "background" soils of this environmentally impacted bay area, using a combination of geostatistical and multivariate analytical methods to distinguish between natural and anthropogenic sources of those metal(oid)s in soils. We collected 114 topsoil samples (0.0-0.2 m depth) from 38 sites. The median values for trace metal concentrations in soils (mg kg-1) followed the order Pb (33.9) > Zn (8.8) > As (1.2) > Cd (0.2) > Hg (0.07), clearly reflecting a Pb-contamination issue. Principal component analysis linked Cd, Pb, and Zn to the same factor (F1), chiefly corroborating their anthropogenic origin; yet, both Pb and Zn are also influenced by natural lithogenic sources. Arsenic and Hg concentrations (F2) are likely related to the natural component alone; their parent material (igneous-metamorphic rocks) seemingly confirm this hypothesis. The heterogeneity of sources and the complexity of the spatial distribution of metals in large areas such as the Todos os Santos Bay warrant, the importance of multivariate and geostatistical analyses in the interpretation of environmental data.

Spatial characterization of dissolved trace elements and heavy metals in the upper Han River (China) using multivariate statistical techniques.

PubMed

Li, Siyue; Zhang, Quanfa

2010-04-15

A data matrix (4032 observations), obtained during a 2-year monitoring period (2005-2006) from 42 sites in the upper Han River is subjected to various multivariate statistical techniques including cluster analysis, principal component analysis (PCA), factor analysis (FA), correlation analysis and analysis of variance to determine the spatial characterization of dissolved trace elements and heavy metals. Our results indicate that waters in the upper Han River are primarily polluted by Al, As, Cd, Pb, Sb and Se, and the potential pollutants include Ba, Cr, Hg, Mn and Ni. Spatial distribution of trace metals indicates the polluted sections mainly concentrate in the Danjiang, Danjiangkou Reservoir catchment and Hanzhong Plain, and the most contaminated river is in the Hanzhong Plain. Q-model clustering depends on geographical location of sampling sites and groups the 42 sampling sites into four clusters, i.e., Danjiang, Danjiangkou Reservoir region (lower catchment), upper catchment and one river in headwaters pertaining to water quality. The headwaters, Danjiang and lower catchment, and upper catchment correspond to very high polluted, moderate polluted and relatively low polluted regions, respectively. Additionally, PCA/FA and correlation analysis demonstrates that Al, Cd, Mn, Ni, Fe, Si and Sr are controlled by natural sources, whereas the other metals appear to be primarily controlled by anthropogenic origins though geogenic source contributing to them. 2009 Elsevier B.V. All rights reserved.

Spatial land-use inventory, modeling, and projection/Denver metropolitan area, with inputs from existing maps, airphotos, and LANDSAT imagery

NASA Technical Reports Server (NTRS)

Tom, C.; Miller, L. D.; Christenson, J. W.

1978-01-01

A landscape model was constructed with 34 land-use, physiographic, socioeconomic, and transportation maps. A simple Markov land-use trend model was constructed from observed rates of change and nonchange from photointerpreted 1963 and 1970 airphotos. Seven multivariate land-use projection models predicting 1970 spatial land-use changes achieved accuracies from 42 to 57 percent. A final modeling strategy was designed, which combines both Markov trend and multivariate spatial projection processes. Landsat-1 image preprocessing included geometric rectification/resampling, spectral-band, and band/insolation ratioing operations. A new, systematic grid-sampled point training-set approach proved to be useful when tested on the four orginal MSS bands, ten image bands and ratios, and all 48 image and map variables (less land use). Ten variable accuracy was raised over 15 percentage points from 38.4 to 53.9 percent, with the use of the 31 ancillary variables. A land-use classification map was produced with an optimal ten-channel subset of four image bands and six ancillary map variables. Point-by-point verification of 331,776 points against a 1972/1973 U.S. Geological Survey (UGSG) land-use map prepared with airphotos and the same classification scheme showed average first-, second-, and third-order accuracies of 76.3, 58.4, and 33.0 percent, respectively.

Dynamics of ejecta from a binary asteroid impact in the framework of the AIDA mission: a NEOShield-2 contribution

NASA Astrophysics Data System (ADS)

Yu, Y.; Schwartz, S. R.; Michel, P.; Benner, L. A. M.

2015-10-01

The dynamics of the ejecta cloud that results from a binary asteroid impact is one of the tasks of the NEOShield-2 project, funded by the European Commission in its program Horizon 2020. Results from such an investigation will have great relevance to the Phase-A study of the AIDA space mission, a collaborative effort between ESA and NASA, which aims to perform a kinetic impactor demonstration. Our study presents a multi-scale dynamical model of the ejecta cloud produced by a hypervelocity impact, which enables us to check the behaviors of the ejecta at different spatial and time scales. This model is applied to the impact into the small moon of the binary Near- Earth asteroid (65803) Didymos on October 2022 as considered by the AIDA mission. We attempt to model the process by including as much practical information as possible, e.g., the gravitational environment influenced by the non-spherical shapes of the bodies based on observed shape of the primary), the solar tides, and the solar radiation pressure. Our simulations show the general patterns of motion of the ejecta cloud, which we use to assess the potential hazard to an observing spacecraft. We also look into the grain-scale dynamics of the ejecta during this process, which has influence on the re-accumulation of particles orbiting in the vicinity.

Dumb-bell-shaped equilibrium figures for fiducial contact-binary asteroids and EKBOs

NASA Astrophysics Data System (ADS)

Descamps, Pascal

2015-01-01

In this work, we investigate the equilibrium figures of a dumb-bell-shaped sequence with which we are still not well acquainted. Studies have shown that these elongated and nonconvex figures may realistically replace the classic “Roche binary approximation” for modeling putative peanut-shaped or contact binary asteroids. The best-fit dumb-bell shapes, combined with the known rotational period of the objects, provide estimates of the bulk density of these objects. This new class of mathematical figures has been successfully tested on the observed light curves of three noteworthy small bodies: main-belt Asteroid 216 Kleopatra, Trojan Asteroid 624 Hektor and Edgeworth-Kuiper-belt object 2001 QG298. Using the direct observations of Kleopatra and Hektor obtained with high spatial resolution techniques and fitting the size of the dumb-bell-shaped solutions, we derived new physical characteristics in terms of equivalent radius, 62.5 ± 5 km and 92 ± 5 km, respectively, and bulk density, 4.4 ± 0.4 g cm-3 and 2.43 ± 0.35 g cm-3, respectively. In particular, the growing inadequacy of the radar shape model for interpreting any type of observations of Kleopatra (light curves, AO images, stellar occultations) in a satisfactory manner suggests that Kleopatra is more likely to be a dumb-bell-shaped object than a “dog-bone.”

Biophysical, infrastructural and social heterogeneities explain spatial distribution of waterborne gastrointestinal disease burden in Mexico City

NASA Astrophysics Data System (ADS)

Baeza, Andrés; Estrada-Barón, Alejandra; Serrano-Candela, Fidel; Bojórquez, Luis A.; Eakin, Hallie; Escalante, Ana E.

2018-06-01

Due to unplanned growth, large extension and limited resources, most megacities in the developing world are vulnerable to hydrological hazards and infectious diseases caused by waterborne pathogens. Here we aim to elucidate the extent of the relation between the spatial heterogeneity of physical and socio-economic factors associated with hydrological hazards (flooding and scarcity) and the spatial distribution of gastrointestinal disease in Mexico City, a megacity with more than 8 million people. We applied spatial statistics and multivariate regression analyses to high resolution records of gastrointestinal diseases during two time frames (2007–2009 and 2010–2014). Results show a pattern of significant association between water flooding events and disease incidence in the city center (lowlands). We also found that in the periphery (highlands), higher incidence is generally associated with household infrastructure deficiency. Our findings suggest the need for integrated and spatially tailored interventions by public works and public health agencies, aimed to manage socio-hydrological vulnerability in Mexico City.

High-rate synthetic aperture communications in shallow water.

PubMed

Song, H C; Hodgkiss, W S; Kuperman, W A; Akal, T; Stevenson, M

2009-12-01

Time reversal communication exploits spatial diversity to achieve spatial and temporal focusing in complex ocean environments. Spatial diversity can be provided easily by a vertical array in a waveguide. Alternatively, spatial diversity can be obtained from a virtual horizontal array generated by two elements, a transmitter and a receiver, due to relative motion between them, referred to as a synthetic aperture. This paper presents coherent synthetic aperture communication results from at-sea experiments conducted in two different frequency bands: (1) 2-4 kHz and (2) 8-20 kHz. Case (1) employs binary-phase shift-keying modulation, while case (2) involves up to eight-phase shift keying modulation with a data rate of 30 kbits/s divided by the number of transmissions (diversity) to be accumulated. The receiver utilizes time reversal diversity combining followed by a single channel equalizer, with frequent channel updates to accommodate the time-varying channel due to coupling of space and time in the presence of motion. Two to five consecutive transmissions from a source moving at 4 kts over 3-6 km range in shallow water are combined successfully after Doppler compensation, confirming the feasibility of coherent synthetic aperture communications using time reversal.

A multivariate ecogeographic analysis of macaque craniodental variation.

PubMed

Grunstra, Nicole D S; Mitteroecker, Philipp; Foley, Robert A

2018-06-01

To infer the ecogeographic conditions that underlie the evolutionary diversification of macaques, we investigated the within- and between-species relationships of craniodental dimensions, geography, and environment in extant macaque species. We studied evolutionary processes by contrasting macroevolutionary patterns, phylogeny, and within-species associations. Sixty-three linear measurements of the permanent dentition and skull along with data about climate, ecology (environment), and spatial geography were collected for 711 specimens of 12 macaque species and analyzed by a multivariate approach. Phylogenetic two-block partial least squares was used to identify patterns of covariance between craniodental and environmental variation. Phylogenetic reduced rank regression was employed to analyze spatial clines in morphological variation. Between-species associations consisted of two distinct multivariate patterns. The first represents overall craniodental size and is negatively associated with temperature and habitat, but positively with latitude. The second pattern shows an antero-posterior tooth size contrast related to diet, rainfall, and habitat productivity. After controlling for phylogeny, however, the latter dimension was diminished. Within-species analyses neither revealed significant association between morphology, environment, and geography, nor evidence of isolation by distance. We found evidence for environmental adaptation in macaque body and craniodental size, primarily driven by selection for thermoregulation. This pattern cannot be explained by the within-species pattern, indicating an evolved genetic basis for the between-species relationship. The dietary signal in relative tooth size, by contrast, can largely be explained by phylogeny. This cautions against adaptive interpretations of phenotype-environment associations when phylogeny is not explicitly modelled. © 2018 Wiley Periodicals, Inc.

Environmental Drivers of Benthic Flux Variation and Ecosystem Functioning in Salish Sea and Northeast Pacific Sediments.

PubMed

Belley, Rénald; Snelgrove, Paul V R; Archambault, Philippe; Juniper, S Kim

2016-01-01

The upwelling of deep waters from the oxygen minimum zone in the Northeast Pacific from the continental slope to the shelf and into the Salish Sea during spring and summer offers a unique opportunity to study ecosystem functioning in the form of benthic fluxes along natural gradients. Using the ROV ROPOS we collected sediment cores from 10 sites in May and July 2011, and September 2013 to perform shipboard incubations and flux measurements. Specifically, we measured benthic fluxes of oxygen and nutrients to evaluate potential environmental drivers of benthic flux variation and ecosystem functioning along natural gradients of temperature and bottom water dissolved oxygen concentrations. The range of temperature and dissolved oxygen encountered across our study sites allowed us to apply a suite of multivariate analyses rarely used in flux studies to identify bottom water temperature as the primary environmental driver of benthic flux variation and organic matter remineralization. Redundancy analysis revealed that bottom water characteristics (temperature and dissolved oxygen), quality of organic matter (chl a:phaeo and C:N ratios) and sediment characteristics (mean grain size and porosity) explained 51.5% of benthic flux variation. Multivariate analyses identified significant spatial and temporal variation in benthic fluxes, demonstrating key differences between the Northeast Pacific and Salish Sea. Moreover, Northeast Pacific slope fluxes were generally lower than shelf fluxes. Spatial and temporal variation in benthic fluxes in the Salish Sea were driven primarily by differences in temperature and quality of organic matter on the seafloor following phytoplankton blooms. These results demonstrate the utility of multivariate approaches in differentiating among potential drivers of seafloor ecosystem functioning, and indicate that current and future predictive models of organic matter remineralization and ecosystem functioning of soft-muddy shelf and slope seafloor habitats should consider bottom water temperature variation. Bottom temperature has important implications for estimates of seasonal and spatial benthic flux variation, benthic-pelagic coupling, and impacts of predicted ocean warming at high latitudes.

Functional overestimation due to spatial smoothing of fMRI data.

PubMed

Liu, Peng; Calhoun, Vince; Chen, Zikuan

2017-11-01

Pearson correlation (simply correlation) is a basic technique for neuroimage function analysis. It has been observed that the spatial smoothing may cause functional overestimation, which however remains a lack of complete understanding. Herein, we present a theoretical explanation from the perspective of correlation scale invariance. For a task-evoked spatiotemporal functional dataset, we can extract the functional spatial map by calculating the temporal correlations (tcorr) of voxel timecourses against the task timecourse. From the relationship between image noise level (changed through spatial smoothing) and the tcorr map calculation, we show that the spatial smoothing causes a noise reduction, which in turn smooths the tcorr map and leads to a spatial expansion on neuroactivity blob estimation. Through numerical simulations and subject experiments, we show that the spatial smoothing of fMRI data may overestimate activation spots in the correlation functional map. Our results suggest a small spatial smoothing (with a smoothing kernel with a full width at half maximum (FWHM) of no more than two voxels) on fMRI data processing for correlation-based functional mapping COMPARISON WITH EXISTING METHODS: In extreme noiselessness, the correlation of scale-invariance property defines a meaningless binary tcorr map. In reality, a functional activity blob in a tcorr map is shaped due to the spoilage of image noise on correlative responses. We may reduce data noise level by smoothing processing, which poses a smoothing effect on correlation. This logic allows us to understand the noise dependence and the smoothing effect of correlation-based fMRI data analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images

PubMed Central

Lahmiri, Salim; Boukadoum, Mounir

2013-01-01

A new methodology for automatic feature extraction from biomedical images and subsequent classification is presented. The approach exploits the spatial orientation of high-frequency textural features of the processed image as determined by a two-step process. First, the two-dimensional discrete wavelet transform (DWT) is applied to obtain the HH high-frequency subband image. Then, a Gabor filter bank is applied to the latter at different frequencies and spatial orientations to obtain new Gabor-filtered image whose entropy and uniformity are computed. Finally, the obtained statistics are fed to a support vector machine (SVM) binary classifier. The approach was validated on mammograms, retina, and brain magnetic resonance (MR) images. The obtained classification accuracies show better performance in comparison to common approaches that use only the DWT or Gabor filter banks for feature extraction. PMID:27006906

Beyond the Rayleigh instability limit for multicharged finite systems: From fission to Coulomb explosion

PubMed Central

Last, Isidore; Levy, Yaakov; Jortner, Joshua

2002-01-01

We address the stability of multicharged finite systems driven by Coulomb forces beyond the Rayleigh instability limit. Our exploration of the nuclear dynamics of heavily charged Morse clusters enabled us to vary the range of the pair potential and of the fissibility parameter, which results in distinct fragmentation patterns and in the angular distributions of the fragments. The Rayleigh instability limit separates between nearly binary (or tertiary) spatially unisotropic fission and spatially isotropic Coulomb explosion into a large number of small, ionic fragments. Implications are addressed for a broad spectrum of dynamics in chemical physics, radiation physics of ultracold gases, and biophysics, involving the fission of clusters and droplets, the realization of Coulomb explosion of molecular clusters, the isotropic expansion of optical molasses, and the Coulomb instability of “isolated” proteins. PMID:12093910

Multivariate Analysis and Modeling of Sediment Pollution Using Neural Network Models and Geostatistics

NASA Astrophysics Data System (ADS)

Golay, Jean; Kanevski, Mikhaïl

2013-04-01

The present research deals with the exploration and modeling of a complex dataset of 200 measurement points of sediment pollution by heavy metals in Lake Geneva. The fundamental idea was to use multivariate Artificial Neural Networks (ANN) along with geostatistical models and tools in order to improve the accuracy and the interpretability of data modeling. The results obtained with ANN were compared to those of traditional geostatistical algorithms like ordinary (co)kriging and (co)kriging with an external drift. Exploratory data analysis highlighted a great variety of relationships (i.e. linear, non-linear, independence) between the 11 variables of the dataset (i.e. Cadmium, Mercury, Zinc, Copper, Titanium, Chromium, Vanadium and Nickel as well as the spatial coordinates of the measurement points and their depth). Then, exploratory spatial data analysis (i.e. anisotropic variography, local spatial correlations and moving window statistics) was carried out. It was shown that the different phenomena to be modeled were characterized by high spatial anisotropies, complex spatial correlation structures and heteroscedasticity. A feature selection procedure based on General Regression Neural Networks (GRNN) was also applied to create subsets of variables enabling to improve the predictions during the modeling phase. The basic modeling was conducted using a Multilayer Perceptron (MLP) which is a workhorse of ANN. MLP models are robust and highly flexible tools which can incorporate in a nonlinear manner different kind of high-dimensional information. In the present research, the input layer was made of either two (spatial coordinates) or three neurons (when depth as auxiliary information could possibly capture an underlying trend) and the output layer was composed of one (univariate MLP) to eight neurons corresponding to the heavy metals of the dataset (multivariate MLP). MLP models with three input neurons can be referred to as Artificial Neural Networks with EXternal drift (ANNEX). Moreover, the exact number of output neurons and the selection of the corresponding variables were based on the subsets created during the exploratory phase. Concerning hidden layers, no restriction were made and multiple architectures were tested. For each MLP model, the quality of the modeling procedure was assessed by variograms: if the variogram of the residuals demonstrates pure nugget effect and if the level of the nugget exactly corresponds to the nugget value of the theoretical variogram of the corresponding variable, all the structured information has been correctly extracted without overfitting. Finally, it is worth mentioning that simple MLP models are not always able to remove all the spatial correlation structure from the data. In that case, Neural Network Residual Kriging (NNRK) can be carried out and risk assessment can be conducted with Neural Network Residual Simulations (NNRS). Finally, the results of the ANNEX models were compared to those of ordinary (co)kriging and (co)kriging with an external drift. It was shown that the ANNEX models performed better than traditional geostatistical algorithms when the relationship between the variable of interest and the auxiliary predictor was not linear. References Kanevski, M. and Maignan, M. (2004). Analysis and Modelling of Spatial Environmental Data. Lausanne: EPFL Press.

Learning Abilities and Disabilities: Generalist Genes, Specialist Environments.

PubMed

Kovas, Yulia; Plomin, Robert

2007-10-01

Twin studies comparing identical and fraternal twins consistently show substantial genetic influence on individual differences in learning abilities such as reading and mathematics, as well as in other cognitive abilities such as spatial ability and memory. Multivariate genetic research has shown that the same set of genes is largely responsible for genetic influence on these diverse cognitive areas. We call these "generalist genes." What differentiates these abilities is largely the environment, especially nonshared environments that make children growing up in the same family different from one another. These multivariate genetic findings of generalist genes and specialist environments have far-reaching implications for diagnosis and treatment of learning disabilities and for understanding the brain mechanisms that mediate these effects.

ALMA data suggest the presence of spiral structure in the inner wind of CW Leonis

NASA Astrophysics Data System (ADS)

Decin, L.; Richards, A. M. S.; Neufeld, D.; Steffen, W.; Melnick, G.; Lombaert, R.

2015-02-01

Context. Evolved low-mass stars lose a significant fraction of their mass through stellar winds. While the overall morphology of the stellar wind structure during the asymptotic giant branch (AGB) phase is thought to be roughly spherically symmetric, the morphology changes dramatically during the post-AGB and planetary nebula phase, during which bipolar and multi-polar structures are often observed. Aims: We aim to study the inner wind structure of the closest well-known AGB star CW Leo. Different diagnostics probing different geometrical scales have implied a non-homogeneous mass-loss process for this star: dust clumps are observed at milli-arcsec scale, a bipolar structure is seen at arcsecond-scale, and multi-concentric shells are detected beyond 1''. Methods: We present the first ALMA Cycle 0 band 9 data around 650 GHz (450 μm) tracing the inner wind of CW Leo. The full-resolution data have a spatial resolution of 0.̋42 × 0.̋24, allowing us to study the morpho-kinematical structure of CW Leo within ~6''. Results: We have detected 25 molecular emission lines in four spectral windows. The emission of all but one line is spatially resolved. The dust and molecular lines are centered around the continuum peak position, which is assumed to be dominated by stellar emission. The dust emission has an asymmetric distribution with a central peak flux density of ~2 Jy. The molecular emission lines trace different regions in the wind acceleration region and imply that the wind velocity increases rapidly from about 5 R⋆, almost reaching the terminal velocity at ~11 R⋆. The images prove that vibrational lines are excited close to the stellar surface and that SiO is a parent molecule. The channel maps for the brighter lines show a complex structure; specifically, for the 13CO J = 6-5 line, different arcs are detected within the first few arcseconds. The curved structure in the position-velocity (PV) map of the 13CO J = 6-5 line can be explained by a spiral structure in the inner wind of CW Leo, probably induced by a binary companion. From modelling the ALMA data, we deduce that the potential orbital axis for the binary system lies at a position angle of ~10-20° to the north-east and that the spiral structure is seen almost edge-on. We infer an orbital period of 55 yr and a binary separation of 25 au (or ~8.2 R⋆). We tentatively estimate that the companion is an unevolved low-mass main-sequence star. Conclusions: A scenario of a binary-induced spiral shell can explain the correlated structure seen in the ALMA PV images of CW Leo. Moreover, this scenario can also explain many other observational signatures seen at different spatial scales and in different wavelength regions, such as the bipolar structure and the almost concentric shells. ALMA data hence for the first time provide the crucial kinematical link between the dust clumps seen at milli-arcsecond scale and the almost concentric arcs seen at arcsecond scale. Appendix A is available in electronic form at http://www.aanda.org

Trinary optical logic processors using shadow casting with polarized light

NASA Astrophysics Data System (ADS)

Ghosh, Amal K.; Basuray, A.

1990-10-01

An optical implementation is proposed of the modified trinary number (MTN) system (Datta et al., 1989) in which any binary number can have arithmetic operations performed on it in parallel without the need for carry and borrow steps. The present method extends the lensless shadow-casting technique of Tanida and Ichioka (1983, 1985). Three kinds of spatial coding are used for encoding the trinary input states, whereas in the decoding plane three states are identified by no light and light with two orthogonal states of polarization.

The eclipsing binary star RZ Cas: accretion-driven variability of the multimode oscillation spectrum

NASA Astrophysics Data System (ADS)

Mkrtichian, D. E.; Lehmann, H.; Rodríguez, E.; Olson, E.; Kim, S.-L.; Kusakin, A. V.; Lee, J. W.; Youn, J.-H.; Kwon, S.-G.; López-González, M. J.; Janiashvili, E.; Tiwari, S. K.; Joshi, Santosh; Lampens, P.; Van Cauteren, P.; Glazunova, L.; Gamarova, A.; Grankin, K. N.; Rovithis-Livaniou, E.; Svoboda, P.; Uhlar, R.; Tsymbal, V.; Kokumbaeva, R.; Urushadze, T.; Kuratov, K.; Shin, H.-C.; Kang, Y.-W.; Soonthornthum, B.

2018-04-01

We analysed photometric time series of the active, semidetached Algol-type system RZ Cas obtained in 1999-2009, in order to search for seasonal and short-term variations in the oscillation spectrum of RZ Cas A. The orbital period shows ±1 s cyclic variations on time-scales of 6-9 years. We detected six low-degree p-mode oscillations with periods between 22.3 and 26.22 min and obtained safe mode identifications using the periodic spatial filter method. The amplitudes and frequencies of all modes vary.

Scale effects on information theory-based measures applied to streamflow patterns in two rural watersheds

NASA Astrophysics Data System (ADS)

Pan, Feng; Pachepsky, Yakov A.; Guber, Andrey K.; McPherson, Brian J.; Hill, Robert L.

2012-01-01

SummaryUnderstanding streamflow patterns in space and time is important for improving flood and drought forecasting, water resources management, and predictions of ecological changes. Objectives of this work include (a) to characterize the spatial and temporal patterns of streamflow using information theory-based measures at two thoroughly-monitored agricultural watersheds located in different hydroclimatic zones with similar land use, and (b) to elucidate and quantify temporal and spatial scale effects on those measures. We selected two USDA experimental watersheds to serve as case study examples, including the Little River experimental watershed (LREW) in Tifton, Georgia and the Sleepers River experimental watershed (SREW) in North Danville, Vermont. Both watersheds possess several nested sub-watersheds and more than 30 years of continuous data records of precipitation and streamflow. Information content measures (metric entropy and mean information gain) and complexity measures (effective measure complexity and fluctuation complexity) were computed based on the binary encoding of 5-year streamflow and precipitation time series data. We quantified patterns of streamflow using probabilities of joint or sequential appearances of the binary symbol sequences. Results of our analysis illustrate that information content measures of streamflow time series are much smaller than those for precipitation data, and the streamflow data also exhibit higher complexity, suggesting that the watersheds effectively act as filters of the precipitation information that leads to the observed additional complexity in streamflow measures. Correlation coefficients between the information-theory-based measures and time intervals are close to 0.9, demonstrating the significance of temporal scale effects on streamflow patterns. Moderate spatial scale effects on streamflow patterns are observed with absolute values of correlation coefficients between the measures and sub-watershed area varying from 0.2 to 0.6 in the two watersheds. We conclude that temporal effects must be evaluated and accounted for when the information theory-based methods are used for performance evaluation and comparison of hydrological models.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes

PubMed Central

2014-01-01

Background Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. Methods The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Results Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Conclusions Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately. PMID:25047164

The Assessment of Neurological Systems with Functional Imaging

ERIC Educational Resources Information Center

Eidelberg, David

2007-01-01

In recent years a number of multivariate approaches have been introduced to map neural systems in health and disease. In this review, we focus on spatial covariance methods applied to functional imaging data to identify patterns of regional activity associated with behavior. In the rest state, this form of network analysis can be used to detect…

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

PubMed Central

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

2005-01-01

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

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

NASA Astrophysics Data System (ADS)

Gulgundi, Mohammad Shahid; Shetty, Amba

2018-03-01

Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water.

Predicting drug court outcome among amphetamine-using participants.

PubMed

Wu, Lora J; Altshuler, Sandra J; Short, Robert A; Roll, John M

2012-06-01

Amphetamine use and abuse carry with it substantial social costs. Although there is a perception that amphetamine users are more difficult to treat than other substance users, drug courts have been used to effectively address drug-related crimes and hold the potential to lessen the impact of amphetamine abuse through efficacious treatment and rehabilitation. The objective of this study was to identify predictors of drug court outcome among amphetamine-using participants. A drug court database was obtained (N = 540) and amphetamine-using participants (n= 341) identified. Multivariate binary regression models run for the amphetamine-using participants identified being employed and being a parent as predictive of successful completion of the program, whereas being sanctioned to jail during the program was inversely related to program completion. Copyright © 2012 Elsevier Inc. All rights reserved.

Atomic-scale phase composition through multivariate statistical analysis of atom probe tomography data.

PubMed

Keenan, Michael R; Smentkowski, Vincent S; Ulfig, Robert M; Oltman, Edward; Larson, David J; Kelly, Thomas F

2011-06-01

We demonstrate for the first time that multivariate statistical analysis techniques can be applied to atom probe tomography data to estimate the chemical composition of a sample at the full spatial resolution of the atom probe in three dimensions. Whereas the raw atom probe data provide the specific identity of an atom at a precise location, the multivariate results can be interpreted in terms of the probabilities that an atom representing a particular chemical phase is situated there. When aggregated to the size scale of a single atom (∼0.2 nm), atom probe spectral-image datasets are huge and extremely sparse. In fact, the average spectrum will have somewhat less than one total count per spectrum due to imperfect detection efficiency. These conditions, under which the variance in the data is completely dominated by counting noise, test the limits of multivariate analysis, and an extensive discussion of how to extract the chemical information is presented. Efficient numerical approaches to performing principal component analysis (PCA) on these datasets, which may number hundreds of millions of individual spectra, are put forward, and it is shown that PCA can be computed in a few seconds on a typical laptop computer.

Southeast Atlantic Cloud Properties in a Multivariate Statistical Model - How Relevant is Air Mass History for Local Cloud Properties?

NASA Astrophysics Data System (ADS)

Fuchs, Julia; Cermak, Jan; Andersen, Hendrik

2017-04-01

This study aims at untangling the impacts of external dynamics and local conditions on cloud properties in the Southeast Atlantic (SEA) by combining satellite and reanalysis data using multivariate statistics. The understanding of clouds and their determinants at different scales is important for constraining the Earth's radiative budget, and thus prominent in climate-system research. In this study, SEA stratocumulus cloud properties are observed not only as the result of local environmental conditions but also as affected by external dynamics and spatial origins of air masses entering the study area. In order to assess to what extent cloud properties are impacted by aerosol concentration, air mass history, and meteorology, a multivariate approach is conducted using satellite observations of aerosol and cloud properties (MODIS, SEVIRI), information on aerosol species composition (MACC) and meteorological context (ERA-Interim reanalysis). To account for the often-neglected but important role of air mass origin, information on air mass history based on HYSPLIT modeling is included in the statistical model. This multivariate approach is intended to lead to a better understanding of the physical processes behind observed stratocumulus cloud properties in the SEA.

GSHR-Tree: a spatial index tree based on dynamic spatial slot and hash table in grid environments

NASA Astrophysics Data System (ADS)

Chen, Zhanlong; Wu, Xin-cai; Wu, Liang

2008-12-01

Computation Grids enable the coordinated sharing of large-scale distributed heterogeneous computing resources that can be used to solve computationally intensive problems in science, engineering, and commerce. Grid spatial applications are made possible by high-speed networks and a new generation of Grid middleware that resides between networks and traditional GIS applications. The integration of the multi-sources and heterogeneous spatial information and the management of the distributed spatial resources and the sharing and cooperative of the spatial data and Grid services are the key problems to resolve in the development of the Grid GIS. The performance of the spatial index mechanism is the key technology of the Grid GIS and spatial database affects the holistic performance of the GIS in Grid Environments. In order to improve the efficiency of parallel processing of a spatial mass data under the distributed parallel computing grid environment, this paper presents a new grid slot hash parallel spatial index GSHR-Tree structure established in the parallel spatial indexing mechanism. Based on the hash table and dynamic spatial slot, this paper has improved the structure of the classical parallel R tree index. The GSHR-Tree index makes full use of the good qualities of R-Tree and hash data structure. This paper has constructed a new parallel spatial index that can meet the needs of parallel grid computing about the magnanimous spatial data in the distributed network. This arithmetic splits space in to multi-slots by multiplying and reverting and maps these slots to sites in distributed and parallel system. Each sites constructs the spatial objects in its spatial slot into an R tree. On the basis of this tree structure, the index data was distributed among multiple nodes in the grid networks by using large node R-tree method. The unbalance during process can be quickly adjusted by means of a dynamical adjusting algorithm. This tree structure has considered the distributed operation, reduplication operation transfer operation of spatial index in the grid environment. The design of GSHR-Tree has ensured the performance of the load balance in the parallel computation. This tree structure is fit for the parallel process of the spatial information in the distributed network environments. Instead of spatial object's recursive comparison where original R tree has been used, the algorithm builds the spatial index by applying binary code operation in which computer runs more efficiently, and extended dynamic hash code for bit comparison. In GSHR-Tree, a new server is assigned to the network whenever a split of a full node is required. We describe a more flexible allocation protocol which copes with a temporary shortage of storage resources. It uses a distributed balanced binary spatial tree that scales with insertions to potentially any number of storage servers through splits of the overloaded ones. The application manipulates the GSHR-Tree structure from a node in the grid environment. The node addresses the tree through its image that the splits can make outdated. This may generate addressing errors, solved by the forwarding among the servers. In this paper, a spatial index data distribution algorithm that limits the number of servers has been proposed. We improve the storage utilization at the cost of additional messages. The structure of GSHR-Tree is believed that the scheme of this grid spatial index should fit the needs of new applications using endlessly larger sets of spatial data. Our proposal constitutes a flexible storage allocation method for a distributed spatial index. The insertion policy can be tuned dynamically to cope with periods of storage shortage. In such cases storage balancing should be favored for better space utilization, at the price of extra message exchanges between servers. This structure makes a compromise in the updating of the duplicated index and the transformation of the spatial index data. Meeting the needs of the grid computing, GSHRTree has a flexible structure in order to satisfy new needs in the future. The GSHR-Tree provides the R-tree capabilities for large spatial datasets stored over interconnected servers. The analysis, including the experiments, confirmed the efficiency of our design choices. The scheme should fit the needs of new applications of spatial data, using endlessly larger datasets. Using the system response time of the parallel processing of spatial scope query algorithm as the performance evaluation factor, According to the result of the simulated the experiments, GSHR-Tree is performed to prove the reasonable design and the high performance of the indexing structure that the paper presented.

Brain regions with abnormal network properties in severe epilepsy of Lennox-Gastaut phenotype: Multivariate analysis of task-free fMRI.

PubMed

Pedersen, Mangor; Curwood, Evan K; Archer, John S; Abbott, David F; Jackson, Graeme D

2015-11-01

Lennox-Gastaut syndrome, and the similar but less tightly defined Lennox-Gastaut phenotype, describe patients with severe epilepsy, generalized epileptic discharges, and variable intellectual disability. Our previous functional neuroimaging studies suggest that abnormal diffuse association network activity underlies the epileptic discharges of this clinical phenotype. Herein we use a data-driven multivariate approach to determine the spatial changes in local and global networks of patients with severe epilepsy of the Lennox-Gastaut phenotype. We studied 9 adult patients and 14 controls. In 20 min of task-free blood oxygen level-dependent functional magnetic resonance imaging data, two metrics of functional connectivity were studied: Regional homogeneity or local connectivity, a measure of concordance between each voxel to a focal cluster of adjacent voxels; and eigenvector centrality, a global connectivity estimate designed to detect important neural hubs. Multivariate pattern analysis of these data in a machine-learning framework was used to identify spatial features that classified disease subjects. Multivariate pattern analysis was 95.7% accurate in classifying subjects for both local and global connectivity measures (22/23 subjects correctly classified). Maximal discriminating features were the following: increased local connectivity in frontoinsular and intraparietal areas; increased global connectivity in posterior association areas; decreased local connectivity in sensory (visual and auditory) and medial frontal cortices; and decreased global connectivity in the cingulate cortex, striatum, hippocampus, and pons. Using a data-driven analysis method in task-free functional magnetic resonance imaging, we show increased connectivity in critical areas of association cortex and decreased connectivity in primary cortex. This supports previous findings of a critical role for these association cortical regions as a final common pathway in generating the Lennox-Gastaut phenotype. Abnormal function of these areas is likely to be important in explaining the intellectual problems characteristic of this disorder. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Quasar Astrophysics with the Space Interferometry Mission

NASA Technical Reports Server (NTRS)

Unwin, Stephen; Wehrle, Ann; Meier, David; Jones, Dayton; Piner, Glenn

2007-01-01

Optical astrometry of quasars and active galaxies can provide key information on the spatial distribution and variability of emission in compact nuclei. The Space Interferometry Mission (SIM PlanetQuest) will have the sensitivity to measure a significant number of quasar positions at the microarcsecond level. SIM will be very sensitive to astrometric shifts for objects as faint as V = 19. A variety of AGN phenomena are expected to be visible to SIM on these scales, including time and spectral dependence in position offsets between accretion disk and jet emission. These represent unique data on the spatial distribution and time dependence of quasar emission. It will also probe the use of quasar nuclei as fundamental astrometric references. Comparisons between the time-dependent optical photocenter position and VLBI radio images will provide further insight into the jet emission mechanism. Observations will be tailored to each specific target and science question. SIM will be able to distinguish spatially between jet and accretion disk emission; and it can observe the cores of galaxies potentially harboring binary supermassive black holes resulting from mergers.

Effects of spatial location and household wealth on health insurance subscription among women in Ghana.

PubMed

Kumi-Kyereme, Akwasi; Amo-Adjei, Joshua

2013-06-17

This study compares ownership of health insurance among Ghanaian women with respect to wealth status and spatial location. We explore the overarching research question by employing geographic and proxy means targeting through interactive analysis of wealth status and spatial issues. The paper draws on the 2008 Ghana Demographic and Health Survey. Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data. By wealth status, the likelihood of purchasing insurance was significantly higher among respondents from the middle, richer and richest households compared to the poorest (reference category) and these differences widened more profoundly in the Northern areas after interacting wealth with zone of residence. Among women at the bottom of household wealth (poorest and poorer), there were no statistically significant differences in insurance subscription in all the areas. The results underscore the relevance of geographic and proxy means targeting in identifying populations who may be need of special interventions as part of the efforts to increase enrolment as well as means of social protection against the vulnerable.

Coordinated temporal and spatial control of motor neuron and serotonergic neuron generation from a common pool of CNS progenitors

PubMed Central

Pattyn, Alexandre; Vallstedt, Anna; Dias, José M.; Samad, Omar Abdel; Krumlauf, Robb; Rijli, Filippo M.; Brunet, Jean-Francois; Ericson, Johan

2003-01-01

Neural progenitor cells often produce distinct types of neurons in a specific order, but the determinants that control the sequential generation of distinct neuronal subclasses in the vertebrate CNS remain poorly defined. We examined the sequential generation of visceral motor neurons and serotonergic neurons from a common pool of neural progenitors located in the ventral hindbrain. We found that the temporal specification of these neurons varies along the anterior-posterior axis of the hindbrain, and that the timing of their generation critically depends on the integrated activities of Nkx- and Hox-class homeodomain proteins. A primary function of these proteins is to coordinate the spatial and temporal activation of the homeodomain protein Phox2b, which in turn acts as a binary switch in the selection of motor neuron or serotonergic neuronal fate. These findings assign new roles for Nkx, Hox, and Phox2 proteins in the control of temporal neuronal fate determination, and link spatial and temporal patterning of CNS neuronal fates. PMID:12651891

Effects of spatial location and household wealth on health insurance subscription among women in Ghana

PubMed Central

2013-01-01

Background This study compares ownership of health insurance among Ghanaian women with respect to wealth status and spatial location. We explore the overarching research question by employing geographic and proxy means targeting through interactive analysis of wealth status and spatial issues. Methods The paper draws on the 2008 Ghana Demographic and Health Survey. Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data. Results By wealth status, the likelihood of purchasing insurance was significantly higher among respondents from the middle, richer and richest households compared to the poorest (reference category) and these differences widened more profoundly in the Northern areas after interacting wealth with zone of residence. Among women at the bottom of household wealth (poorest and poorer), there were no statistically significant differences in insurance subscription in all the areas. Conclusions The results underscore the relevance of geographic and proxy means targeting in identifying populations who may be need of special interventions as part of the efforts to increase enrolment as well as means of social protection against the vulnerable. PMID:23768255

EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation

PubMed Central

Amidi, Afshine; Megalooikonomou, Vasileios; Paragios, Nikos

2018-01-01

During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems. The size of the Protein Data Bank (PDB) has increased more than 15-fold since 1999, which enabled the expansion of models that aim at predicting enzymatic function via their amino acid composition. Amino acid sequence, however, is less conserved in nature than protein structure and therefore considered a less reliable predictor of protein function. This paper presents EnzyNet, a novel 3D convolutional neural networks classifier that predicts the Enzyme Commission number of enzymes based only on their voxel-based spatial structure. The spatial distribution of biochemical properties was also examined as complementary information. The two-layer architecture was investigated on a large dataset of 63,558 enzymes from the PDB and achieved an accuracy of 78.4% by exploiting only the binary representation of the protein shape. Code and datasets are available at https://github.com/shervinea/enzynet. PMID:29740518

EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation.

PubMed

Amidi, Afshine; Amidi, Shervine; Vlachakis, Dimitrios; Megalooikonomou, Vasileios; Paragios, Nikos; Zacharaki, Evangelia I

2018-01-01

During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems. The size of the Protein Data Bank (PDB) has increased more than 15-fold since 1999, which enabled the expansion of models that aim at predicting enzymatic function via their amino acid composition. Amino acid sequence, however, is less conserved in nature than protein structure and therefore considered a less reliable predictor of protein function. This paper presents EnzyNet, a novel 3D convolutional neural networks classifier that predicts the Enzyme Commission number of enzymes based only on their voxel-based spatial structure. The spatial distribution of biochemical properties was also examined as complementary information. The two-layer architecture was investigated on a large dataset of 63,558 enzymes from the PDB and achieved an accuracy of 78.4% by exploiting only the binary representation of the protein shape. Code and datasets are available at https://github.com/shervinea/enzynet.

The HTM Spatial Pooler-A Neocortical Algorithm for Online Sparse Distributed Coding.

PubMed

Cui, Yuwei; Ahmad, Subutai; Hawkins, Jeff

2017-01-01

Hierarchical temporal memory (HTM) provides a theoretical framework that models several key computational principles of the neocortex. In this paper, we analyze an important component of HTM, the HTM spatial pooler (SP). The SP models how neurons learn feedforward connections and form efficient representations of the input. It converts arbitrary binary input patterns into sparse distributed representations (SDRs) using a combination of competitive Hebbian learning rules and homeostatic excitability control. We describe a number of key properties of the SP, including fast adaptation to changing input statistics, improved noise robustness through learning, efficient use of cells, and robustness to cell death. In order to quantify these properties we develop a set of metrics that can be directly computed from the SP outputs. We show how the properties are met using these metrics and targeted artificial simulations. We then demonstrate the value of the SP in a complete end-to-end real-world HTM system. We discuss the relationship with neuroscience and previous studies of sparse coding. The HTM spatial pooler represents a neurally inspired algorithm for learning sparse representations from noisy data streams in an online fashion.

Defining critical habitats of threatened and endemic reef fishes with a multivariate approach.

PubMed

Purcell, Steven W; Clarke, K Robert; Rushworth, Kelvin; Dalton, Steven J

2014-12-01

Understanding critical habitats of threatened and endemic animals is essential for mitigating extinction risks, developing recovery plans, and siting reserves, but assessment methods are generally lacking. We evaluated critical habitats of 8 threatened or endemic fish species on coral and rocky reefs of subtropical eastern Australia, by measuring physical and substratum-type variables of habitats at fish sightings. We used nonmetric and metric multidimensional scaling (nMDS, mMDS), Analysis of similarities (ANOSIM), similarity percentages analysis (SIMPER), permutational analysis of multivariate dispersions (PERMDISP), and other multivariate tools to distinguish critical habitats. Niche breadth was widest for 2 endemic wrasses, and reef inclination was important for several species, often found in relatively deep microhabitats. Critical habitats of mainland reef species included small caves or habitat-forming hosts such as gorgonian corals and black coral trees. Hard corals appeared important for reef fishes at Lord Howe Island, and red algae for mainland reef fishes. A wide range of habitat variables are required to assess critical habitats owing to varied affinities of species to different habitat features. We advocate assessments of critical habitats matched to the spatial scale used by the animals and a combination of multivariate methods. Our multivariate approach furnishes a general template for assessing the critical habitats of species, understanding how these vary among species, and determining differences in the degree of habitat specificity. © 2014 Society for Conservation Biology.

Phenomapping of rangelands in South Africa using time series of RapidEye data

NASA Astrophysics Data System (ADS)

Parplies, André; Dubovyk, Olena; Tewes, Andreas; Mund, Jan-Peter; Schellberg, Jürgen

2016-12-01

Phenomapping is an approach which allows the derivation of spatial patterns of vegetation phenology and rangeland productivity based on time series of vegetation indices. In our study, we propose a new spatial mapping approach which combines phenometrics derived from high resolution (HR) satellite time series with spatial logistic regression modeling to discriminate land management systems in rangelands. From the RapidEye time series for selected rangelands in South Africa, we calculated bi-weekly noise reduced Normalized Difference Vegetation Index (NDVI) images. For the growing season of 2011⿿2012, we further derived principal phenology metrics such as start, end and length of growing season and related phenological variables such as amplitude, left derivative and small integral of the NDVI curve. We then mapped these phenometrics across two different tenure systems, communal and commercial, at the very detailed spatial resolution of 5 m. The result of a binary logistic regression (BLR) has shown that the amplitude and the left derivative of the NDVI curve were statistically significant. These indicators are useful to discriminate commercial from communal rangeland systems. We conclude that phenomapping combined with spatial modeling is a powerful tool that allows efficient aggregation of phenology and productivity metrics for spatially explicit analysis of the relationships of crop phenology with site conditions and management. This approach has particular potential for disaggregated and patchy environments such as in farming systems in semi-arid South Africa, where phenology varies considerably among and within years. Further, we see a strong perspective for phenomapping to support spatially explicit modelling of vegetation.

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

Linear, multivariable robust control with a mu perspective

NASA Technical Reports Server (NTRS)

Packard, Andy; Doyle, John; Balas, Gary

1993-01-01

The structured singular value is a linear algebra tool developed to study a particular class of matrix perturbation problems arising in robust feedback control of multivariable systems. These perturbations are called linear fractional, and are a natural way to model many types of uncertainty in linear systems, including state-space parameter uncertainty, multiplicative and additive unmodeled dynamics uncertainty, and coprime factor and gap metric uncertainty. The structured singular value theory provides a natural extension of classical SISO robustness measures and concepts to MIMO systems. The structured singular value analysis, coupled with approximate synthesis methods, make it possible to study the tradeoff between performance and uncertainty that occurs in all feedback systems. In MIMO systems, the complexity of the spatial interactions in the loop gains make it difficult to heuristically quantify the tradeoffs that must occur. This paper examines the role played by the structured singular value (and its computable bounds) in answering these questions, as well as its role in the general robust, multivariable control analysis and design problem.

Spatial correlation of the dynamic propensity of a glass-forming liquid

NASA Astrophysics Data System (ADS)

Razul, M. Shajahan G.; Matharoo, Gurpreet S.; Poole, Peter H.

2011-06-01

We present computer simulation results on the dynamic propensity (as defined by Widmer-Cooper et al 2004 Phys. Rev. Lett. 93 135701) in a Kob-Andersen binary Lennard-Jones liquid system consisting of 8788 particles. We compute the spatial correlation function for the dynamic propensity as a function of both the reduced temperature T, and the time scale on which the particle displacements are measured. For T <= 0.6, we find that non-zero correlations occur at the largest length scale accessible in our system. We also show that a cluster-size analysis of particles with extremal values of the dynamic propensity, as well as 3D visualizations, reveal spatially correlated regions that approach the size of our system as T decreases, consistently with the behavior of the spatial correlation function. Next, we define and examine the 'coordination propensity', the isoconfigurational average of the coordination number of the minority B particles around the majority A particles. We show that a significant correlation exists between the spatial fluctuations of the dynamic and coordination propensities. In addition, we find non-zero correlations of the coordination propensity occurring at the largest length scale accessible in our system for all T in the range 0.466 < T < 1.0. We discuss the implications of these results for understanding the length scales of dynamical heterogeneity in glass-forming liquids.

Usability and potential of geostatistics for spatial discrimination of multiple sclerosis lesion patterns.

PubMed

Marschallinger, Robert; Golaszewski, Stefan M; Kunz, Alexander B; Kronbichler, Martin; Ladurner, Gunther; Hofmann, Peter; Trinka, Eugen; McCoy, Mark; Kraus, Jörg

2014-01-01

In multiple sclerosis (MS) the individual disease courses are very heterogeneous among patients and biomarkers for setting the diagnosis and the estimation of the prognosis for individual patients would be very helpful. For this purpose, we are developing a multidisciplinary method and workflow for the quantitative, spatial, and spatiotemporal analysis and characterization of MS lesion patterns from MRI with geostatistics. We worked on a small data set involving three synthetic and three real-world MS lesion patterns, covering a wide range of possible MS lesion configurations. After brain normalization, MS lesions were extracted and the resulting binary 3-dimensional models of MS lesion patterns were subject to geostatistical indicator variography in three orthogonal directions. By applying geostatistical indicator variography, we were able to describe the 3-dimensional spatial structure of MS lesion patterns in a standardized manner. Fitting a model function to the empirical variograms, spatial characteristics of the MS lesion patterns could be expressed and quantified by two parameters. An orthogonal plot of these parameters enabled a well-arranged comparison of the involved MS lesion patterns. This method in development is a promising candidate to complement standard image-based statistics by incorporating spatial quantification. The work flow is generic and not limited to analyzing MS lesion patterns. It can be completely automated for the screening of radiological archives. Copyright © 2013 by the American Society of Neuroimaging.

A study on the use of Gumbel approximation with the Bernoulli spatial scan statistic.

PubMed

Read, S; Bath, P A; Willett, P; Maheswaran, R

2013-08-30

The Bernoulli version of the spatial scan statistic is a well established method of detecting localised spatial clusters in binary labelled point data, a typical application being the epidemiological case-control study. A recent study suggests the inferential accuracy of several versions of the spatial scan statistic (principally the Poisson version) can be improved, at little computational cost, by using the Gumbel distribution, a method now available in SaTScan(TM) (www.satscan.org). We study in detail the effect of this technique when applied to the Bernoulli version and demonstrate that it is highly effective, albeit with some increase in false alarm rates at certain significance thresholds. We explain how this increase is due to the discrete nature of the Bernoulli spatial scan statistic and demonstrate that it can affect even small p-values. Despite this, we argue that the Gumbel method is actually preferable for very small p-values. Furthermore, we extend previous research by running benchmark trials on 12 000 synthetic datasets, thus demonstrating that the overall detection capability of the Bernoulli version (i.e. ratio of power to false alarm rate) is not noticeably affected by the use of the Gumbel method. We also provide an example application of the Gumbel method using data on hospital admissions for chronic obstructive pulmonary disease. Copyright © 2013 John Wiley & Sons, Ltd.

The Role of Auxiliary Variables in Deterministic and Deterministic-Stochastic Spatial Models of Air Temperature in Poland

NASA Astrophysics Data System (ADS)

Szymanowski, Mariusz; Kryza, Maciej

2017-02-01

Our study examines the role of auxiliary variables in the process of spatial modelling and mapping of climatological elements, with air temperature in Poland used as an example. The multivariable algorithms are the most frequently applied for spatialization of air temperature, and their results in many studies are proved to be better in comparison to those obtained by various one-dimensional techniques. In most of the previous studies, two main strategies were used to perform multidimensional spatial interpolation of air temperature. First, it was accepted that all variables significantly correlated with air temperature should be incorporated into the model. Second, it was assumed that the more spatial variation of air temperature was deterministically explained, the better was the quality of spatial interpolation. The main goal of the paper was to examine both above-mentioned assumptions. The analysis was performed using data from 250 meteorological stations and for 69 air temperature cases aggregated on different levels: from daily means to 10-year annual mean. Two cases were considered for detailed analysis. The set of potential auxiliary variables covered 11 environmental predictors of air temperature. Another purpose of the study was to compare the results of interpolation given by various multivariable methods using the same set of explanatory variables. Two regression models: multiple linear (MLR) and geographically weighted (GWR) method, as well as their extensions to the regression-kriging form, MLRK and GWRK, respectively, were examined. Stepwise regression was used to select variables for the individual models and the cross-validation method was used to validate the results with a special attention paid to statistically significant improvement of the model using the mean absolute error (MAE) criterion. The main results of this study led to rejection of both assumptions considered. Usually, including more than two or three of the most significantly correlated auxiliary variables does not improve the quality of the spatial model. The effects of introduction of certain variables into the model were not climatologically justified and were seen on maps as unexpected and undesired artefacts. The results confirm, in accordance with previous studies, that in the case of air temperature distribution, the spatial process is non-stationary; thus, the local GWR model performs better than the global MLR if they are specified using the same set of auxiliary variables. If only GWR residuals are autocorrelated, the geographically weighted regression-kriging (GWRK) model seems to be optimal for air temperature spatial interpolation.

Occurrence and multivariate exploratory analysis of the natural radioactivity anomaly in the south coastal region of Kenya

NASA Astrophysics Data System (ADS)

Kaniu, M. I.; Angeyo, K. H.; Darby, I. G.

2018-05-01

Characterized by a variety of rock formations, namely alkaline, igneous and sedimentary that contain significant deposits of monazite and pyrochlore ores, the south coastal region of Kenya may be regarded as highly heterogeneous with regard to its geochemistry, mineralogy as well as geological morphology. The region is one of the several alkaline carbonatite complexes of Kenya that are associated with high natural background radiation and therefore radioactivity anomaly. However, this high background radiation (HBR) anomaly has hardly been systematically assessed and delineated with regard to the spatial, geological, geochemical as well as anthropogenic variability and co-dependencies. We conducted wide-ranging in-situ gamma-ray spectrometric measurements in this area. The goal of the study was to assess the radiation exposure as well as determine the underlying natural radioactivity levels in the region. In this paper we report the occurrence, exploratory analysis and modeling to assess the multivariate geo-dependence and spatial variability of the radioactivity and associated radiation exposure. Unsupervised principal component analysis and ternary plots were utilized in the study. It was observed that areas which exhibit HBR anomalies are located along the south coast paved road and in the Mrima-Kiruku complex. These areas showed a trend towards enhanced levels of 232Th and 238U and low 40K. The spatial variability of the radioactivity anomaly was found to be mainly constrained by anthropogenic activities, underlying geology and geochemical processes in the terrestrial environment.

An accelerated image matching technique for UAV orthoimage registration

NASA Astrophysics Data System (ADS)

Tsai, Chung-Hsien; Lin, Yu-Ching

2017-06-01

Using an Unmanned Aerial Vehicle (UAV) drone with an attached non-metric camera has become a popular low-cost approach for collecting geospatial data. A well-georeferenced orthoimage is a fundamental product for geomatics professionals. To achieve high positioning accuracy of orthoimages, precise sensor position and orientation data, or a number of ground control points (GCPs), are often required. Alternatively, image registration is a solution for improving the accuracy of a UAV orthoimage, as long as a historical reference image is available. This study proposes a registration scheme, including an Accelerated Binary Robust Invariant Scalable Keypoints (ABRISK) algorithm and spatial analysis of corresponding control points for image registration. To determine a match between two input images, feature descriptors from one image are compared with those from another image. A "Sorting Ring" is used to filter out uncorrected feature pairs as early as possible in the stage of matching feature points, to speed up the matching process. The results demonstrate that the proposed ABRISK approach outperforms the vector-based Scale Invariant Feature Transform (SIFT) approach where radiometric variations exist. ABRISK is 19.2 times and 312 times faster than SIFT for image sizes of 1000 × 1000 pixels and 4000 × 4000 pixels, respectively. ABRISK is 4.7 times faster than Binary Robust Invariant Scalable Keypoints (BRISK). Furthermore, the positional accuracy of the UAV orthoimage after applying the proposed image registration scheme is improved by an average of root mean square error (RMSE) of 2.58 m for six test orthoimages whose spatial resolutions vary from 6.7 cm to 10.7 cm.

Bayesian Scalar-on-Image Regression with Application to Association Between Intracranial DTI and Cognitive Outcomes

PubMed Central

Huang, Lei; Goldsmith, Jeff; Reiss, Philip T.; Reich, Daniel S.; Crainiceanu, Ciprian M.

2013-01-01

Diffusion tensor imaging (DTI) measures water diffusion within white matter, allowing for in vivo quantification of brain pathways. These pathways often subserve specific functions, and impairment of those functions is often associated with imaging abnormalities. As a method for predicting clinical disability from DTI images, we propose a hierarchical Bayesian “scalar-on-image” regression procedure. Our procedure introduces a latent binary map that estimates the locations of predictive voxels and penalizes the magnitude of effect sizes in these voxels, thereby resolving the ill-posed nature of the problem. By inducing a spatial prior structure, the procedure yields a sparse association map that also maintains spatial continuity of predictive regions. The method is demonstrated on a simulation study and on a study of association between fractional anisotropy and cognitive disability in a cross-sectional sample of 135 multiple sclerosis patients. PMID:23792220

Chandra/ACIS Observations of the 30 Doradus Star-Forming Complex

NASA Astrophysics Data System (ADS)

Townsley, Leisa; Broos, Patrick; Feigelson, Eric; Burrows, David; Chu, You-Hua; Garmire, Gordon; Griffiths, Richard; Maeda, Yoshitomo; Pavlov, George; Tsuboi, Yohko

2002-04-01

30 Doradus is the archetype giant extragalactic H II region, a massive star-forming complex in the Large Magellanic Cloud. We examine high-spatial-resolution X-ray images and spectra of the essential parts of 30 Doradus, obtained with the Advanced CCD Imaging Spectrometer (ACIS) aboard the Chandra X-ray Observatory. The central cluster of young high-mass stars, R136, is resolved at the arcsecond level, allowing spectral analysis of bright constituents; other OB/Wolf-Rayet binaries and multiple systems (e.g. R139, R140) are also detected. Spatially-resolved spectra are presented for N157B, the composite SNR containing a 16-msec pulsar. The spectrally soft superbubble structures seen by ROSAT are dramatically imaged by Chandra; we explore the spectral differences they exhibit. Taken together, the components of 30 Doradus give us an excellent microscopic view of high-energy phenomena seen on larger scales in more distant galaxies as starbursts and galactic winds.

High throughput dual-wavelength temperature distribution imaging via compressive imaging

NASA Astrophysics Data System (ADS)

Yao, Xu-Ri; Lan, Ruo-Ming; Liu, Xue-Feng; Zhu, Ge; Zheng, Fu; Yu, Wen-Kai; Zhai, Guang-Jie

2018-03-01

Thermal imaging is an essential tool in a wide variety of research areas. In this work we demonstrate high-throughput double-wavelength temperature distribution imaging using a modified single-pixel camera without the requirement of a beam splitter (BS). A digital micro-mirror device (DMD) is utilized to display binary masks and split the incident radiation, which eliminates the necessity of a BS. Because the spatial resolution is dictated by the DMD, this thermal imaging system has the advantage of perfect spatial registration between the two images, which limits the need for the pixel registration and fine adjustments. Two bucket detectors, which measures the total light intensity reflected from the DMD, are employed in this system and yield an improvement in the detection efficiency of the narrow-band radiation. A compressive imaging algorithm is utilized to achieve under-sampling recovery. A proof-of-principle experiment was presented to demonstrate the feasibility of this structure.

Spatial-dependence recurrence sample entropy

NASA Astrophysics Data System (ADS)

Pham, Tuan D.; Yan, Hong

2018-03-01

Measuring complexity in terms of the predictability of time series is a major area of research in science and engineering, and its applications are spreading throughout many scientific disciplines, where the analysis of physiological signals is perhaps the most widely reported in literature. Sample entropy is a popular measure for quantifying signal irregularity. However, the sample entropy does not take sequential information, which is inherently useful, into its calculation of sample similarity. Here, we develop a method that is based on the mathematical principle of the sample entropy and enables the capture of sequential information of a time series in the context of spatial dependence provided by the binary-level co-occurrence matrix of a recurrence plot. Experimental results on time-series data of the Lorenz system, physiological signals of gait maturation in healthy children, and gait dynamics in Huntington's disease show the potential of the proposed method.

Double-Referential Holography and Spatial Quadrature Amplitude Modulation

NASA Astrophysics Data System (ADS)

Zukeran, Keisuke; Okamoto, Atsushi; Takabayashi, Masanori; Shibukawa, Atsushi; Sato, Kunihiro; Tomita, Akihisa

2013-09-01

We proposed a double-referential holography (DRH) that allows phase-detection without external additional beams. In the DRH, phantom beams, prepared in the same optical path as signal beams and preliminary multiplexed in a recording medium along with the signal, are used to produce interference fringes on an imager for converting a phase into an intensity distribution. The DRH enables stable and high-accuracy phase detection independent of the fluctuations and vibrations of the optical system owing to medium shift and temperature variation. Besides, the collinear arrangement of the signal and phantom beams leads to the compactness of the optical data storage system. We conducted an experiment using binary phase modulation signals for verifying the DRH operation. In addition, 38-level spatial quadrature amplitude modulation signals were successfully reproduced with the DRH by numerical simulation. Furthermore, we verified that the distributed phase-shifting method moderates the dynamic range consumption for the exposure of phantom beams.

High Fidelity Simulation of Transcritical Liquid Jet in Crossflow

NASA Astrophysics Data System (ADS)

Li, Xiaoyi; Soteriou, Marios

2017-11-01

Transcritical injection of liquid fuel occurs in many practical applications such as diesel, rocket and gas turbine engines. In these applications, the liquid fuel, with a supercritical pressure and a subcritical temperature, is introduced into an environment where both the pressure and temperature exceeds the critical point of the fuel. The convoluted physics of the transition from subcritical to supercritical conditions poses great challenges for both experimental and numerical investigations. In this work, numerical simulation of a binary system of a subcritical liquid injecting into a supercritical gaseous crossflow is performed. The spatially varying fluid thermodynamic and transport properties are evaluated using established cubic equation of state and extended corresponding state principles with established mixing rules. To efficiently account for the large spatial gradients in property variations, an adaptive mesh refinement technique is employed. The transcritical simulation results are compared with the predictions from the traditional subcritical jet atomization simulations.

BOREAS Level-4c AVHRR-LAC Ten-Day Composite Images: Surface Parameters

NASA Technical Reports Server (NTRS)

Cihlar, Josef; Chen, Jing; Huang, Fengting; Nickeson, Jaime; Newcomer, Jeffrey A.; Hall, Forrest G. (Editor)

2000-01-01

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Manitoba Remote Sensing Center (MRSC) and BOREAS Information System (BORIS) personnel acquired, processed, and archived data from the Advanced Very High Resolution Radiometer (AVHRR) instruments on the NOAA-11 and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4c data are gridded, 10-day composites of surface parameters produced from sets of single-day images. Temporally, the 10-day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files. Note: Some of the data files on the BOREAS CD-ROMs have been compressed using the Gzip program.

BOREAS Level-2 MAS Surface Reflectance and Temperature Images in BSQ Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Newcomer, Jeffrey (Editor); Lobitz, Brad; Spanner, Michael; Strub, Richard; Lobitz, Brad

2000-01-01

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed aircraft data products they needed to compare and spatially extend point results. The MODIS Airborne Simulator (MAS) images, along with other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes biophysical parameter maps such as surface reflectance and temperature. Collection of the MAS images occurred over the study areas during the 1994 field campaigns. The level-2 MAS data cover the dates of 21-Jul-1994, 24-Jul-1994, 04-Aug-1994, and 08-Aug-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C130 navigation data in a MAS scan model. The data are provided in binary image format files.

BOREAS Level-4b AVHRR-LAC Ten-Day Composite Images: At-sensor Radiance

NASA Technical Reports Server (NTRS)

Cihlar, Josef; Chen, Jing; Nickerson, Jaime; Newcomer, Jeffrey A.; Huang, Feng-Ting; Hall, Forrest G. (Editor)

2000-01-01

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Manitoba Remote Sensing Center (MRSC) and BOREAS Information System (BORIS) personnel acquired, processed, and archived data from the Advanced Very High Resolution Radiometer (AVHRR) instruments on the National Oceanic and Atmospheric Administration (NOAA-11) and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4b data are gridded, 10-day composites of at-sensor radiance values produced from sets of single-day images. Temporally, the 10- day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files.

Strategies to optimize monitoring schemes of recreational waters from Salta, Argentina: a multivariate approach

PubMed Central

Gutiérrez-Cacciabue, Dolores; Teich, Ingrid; Poma, Hugo Ramiro; Cruz, Mercedes Cecilia; Balzarini, Mónica; Rajal, Verónica Beatriz

2014-01-01

Several recreational surface waters in Salta, Argentina, were selected to assess their quality. Seventy percent of the measurements exceeded at least one of the limits established by international legislation becoming unsuitable for their use. To interpret results of complex data, multivariate techniques were applied. Arenales River, due to the variability observed in the data, was divided in two: upstream and downstream representing low and high pollution sites, respectively; and Cluster Analysis supported that differentiation. Arenales River downstream and Campo Alegre Reservoir were the most different environments and Vaqueros and La Caldera Rivers were the most similar. Canonical Correlation Analysis allowed exploration of correlations between physicochemical and microbiological variables except in both parts of Arenales River, and Principal Component Analysis allowed finding relationships among the 9 measured variables in all aquatic environments. Variable’s loadings showed that Arenales River downstream was impacted by industrial and domestic activities, Arenales River upstream was affected by agricultural activities, Campo Alegre Reservoir was disturbed by anthropogenic and ecological effects, and La Caldera and Vaqueros Rivers were influenced by recreational activities. Discriminant Analysis allowed identification of subgroup of variables responsible for seasonal and spatial variations. Enterococcus, dissolved oxygen, conductivity, E. coli, pH, and fecal coliforms are sufficient to spatially describe the quality of the aquatic environments. Regarding seasonal variations, dissolved oxygen, conductivity, fecal coliforms, and pH can be used to describe water quality during dry season, while dissolved oxygen, conductivity, total coliforms, E. coli, and Enterococcus during wet season. Thus, the use of multivariate techniques allowed optimizing monitoring tasks and minimizing costs involved. PMID:25190636

A strategy for tissue self-organization that is robust to cellular heterogeneity and plasticity.

PubMed

Cerchiari, Alec E; Garbe, James C; Jee, Noel Y; Todhunter, Michael E; Broaders, Kyle E; Peehl, Donna M; Desai, Tejal A; LaBarge, Mark A; Thomson, Matthew; Gartner, Zev J

2015-02-17

Developing tissues contain motile populations of cells that can self-organize into spatially ordered tissues based on differences in their interfacial surface energies. However, it is unclear how self-organization by this mechanism remains robust when interfacial energies become heterogeneous in either time or space. The ducts and acini of the human mammary gland are prototypical heterogeneous and dynamic tissues comprising two concentrically arranged cell types. To investigate the consequences of cellular heterogeneity and plasticity on cell positioning in the mammary gland, we reconstituted its self-organization from aggregates of primary cells in vitro. We find that self-organization is dominated by the interfacial energy of the tissue-ECM boundary, rather than by differential homo- and heterotypic energies of cell-cell interaction. Surprisingly, interactions with the tissue-ECM boundary are binary, in that only one cell type interacts appreciably with the boundary. Using mathematical modeling and cell-type-specific knockdown of key regulators of cell-cell cohesion, we show that this strategy of self-organization is robust to severe perturbations affecting cell-cell contact formation. We also find that this mechanism of self-organization is conserved in the human prostate. Therefore, a binary interfacial interaction with the tissue boundary provides a flexible and generalizable strategy for forming and maintaining the structure of two-component tissues that exhibit abundant heterogeneity and plasticity. Our model also predicts that mutations affecting binary cell-ECM interactions are catastrophic and could contribute to loss of tissue architecture in diseases such as breast cancer.

Young Brown Dwarfs and Giant Planets as Companions to Weak-Line T Tauri Stars

NASA Astrophysics Data System (ADS)

Brandner, Wolfgang; Frink, Sabine; Kohler, Rainer; Kunkel, Michael

Weak-line T Tauri stars, contrary to classical T Tauri stars, no longer possess massive circumstellar disks. In weak-line T Tauri stars, the circumstellar matter was either accreted onto the T Tauri star or has been redistributed. Disk instabilities in the outer disk might result in the formation of brown dwarfs and giant planets. Based on photometric and spectroscopic studies of ROSAT sources, we have selected an initial sample of 200 weak-line T Tauri stars in the Chamaeleon T association and the Scorpius-Centaurus OB association. In the course of follow-up observations, we identified visual and spectroscopic binary stars and excluded them from our final list, as the complex dynamics and gravitational interaction in binary systems might aggravate or even completely inhibit the formation of planets (depending on physical separation of the binary components and their mass ratio). The membership of individual stars to the associations was established from proper motion studies and radial velocity surveys. Our final sample consists of 70 single weak-line T Tauri stars. We have initiated a program to spatially resolve young brown dwarfs and young giant planets as companions to single weak-line T Tauri stars using adaptive optics at the ESO 3.6 m telescope and HST/NICMOS. In this poster we describe the observing strategy and present first results of our adaptive optics observations. An update on the program status can be found at http://www.astro.uiuc.edu/~brandner/text/bd/bd.html

Binary black hole spacetimes with a helical Killing vector

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

Klein, Christian

Binary black hole spacetimes with a helical Killing vector, which are discussed as an approximation for the early stage of a binary system, are studied in a projection formalism. In this setting the four-dimensional Einstein equations are equivalent to a three-dimensional gravitational theory with a SL(2,R)/SO(1,1) sigma model as the material source. The sigma model is determined by a complex Ernst equation. 2+1 decompositions of the three-metric are used to establish the field equations on the orbit space of the Killing vector. The two Killing horizons of spherical topology which characterize the black holes, the cylinder of light where themore » Killing vector changes from timelike to spacelike, and infinity are singular points of the equations. The horizon and the light cylinder are shown to be regular singularities, i.e., the metric functions can be expanded in a formal power series in the vicinity. The behavior of the metric at spatial infinity is studied in terms of formal series solutions to the linearized Einstein equations. It is shown that the spacetime is not asymptotically flat in the strong sense to have a smooth null infinity under the assumption that the metric tends asymptotically to the Minkowski metric. In this case the metric functions have an oscillatory behavior in the radial coordinate in a nonaxisymmetric setting, the asymptotic multipoles are not defined. The asymptotic behavior of the Weyl tensor near infinity shows that there is no smooth null infinity.« less

Near-Infrared Keck Interferometer and IOTA Closure Phase Observations of Wolf-Rayet stars

NASA Astrophysics Data System (ADS)

Rajagopal, J.; Wallace, D.; Barry, R.; Richardson, L. J.; Traub, W.; Danchi, W. C.

We present first results from observations of a small sample of IR-bright Wolf-Rayet stars with the Keck Interferometer in the near-infrared, and with the IONIC beam three-telescope beam combiner at the Infrared and Optical Telescope Array (IOTA) observatory. The former results were obtained as part of shared-risk observations in commissioning the Keck Interferometer and form a subset of a high-resolution study of dust around Wolf-Rayet stars using multiple interferometers in progress in our group. The latter results are the first closure phase observations of these stars in the near-infrared in a separated telescope interferometer. Earlier aperture-masking observations with the Keck-I telescope provide strong evidence that dust-formation in late-type WC stars are a result of wind-wind collision in short-period binaries.Our program with the Keck interferometer seeks to further examine this paradigm at much higher resolution. We have spatially resolved the binary in the prototypical dusty WC type star WR 140. WR 137, another episodic dust-producing star, has been partially resolved for the first time, providing the first direct clue to its possible binary nature.We also include WN stars in our sample to investigate circumstellar dust in this other main sub-type of WRs. We have been unable to resolve any of these, indicating a lack of extended dust.Complementary observations using the MIDI instrument on the VLTI in the mid-infrared are presented in another contribution to this workshop.

Cloud-based computation for accelerating vegetation mapping and change detection at regional to national scales

Treesearch

Matthew J. Gregory; Zhiqiang Yang; David M. Bell; Warren B. Cohen; Sean Healey; Janet L. Ohmann; Heather M. Roberts

2015-01-01

Mapping vegetation and landscape change at fine spatial scales is needed to inform natural resource and conservation planning, but such maps are expensive and time-consuming to produce. For Landsat-based methodologies, mapping efforts are hampered by the daunting task of manipulating multivariate data for millions to billions of pixels. The advent of cloud-based...

Predictors of Study Success from a Teacher's Perspective of the Quality of the Built Environment

ERIC Educational Resources Information Center

Kok, Herman; Mobach, Mark; Omta, Onno

2015-01-01

The article aims to find predictors of study success from a teacher's perspective that relate to the built environment. The research is based on a national online survey among 1752 teachers at 18 Dutch Universities of Applied Sciences. Multivariate data analyses were used to test the hypothesis that the quality of spatial and functional aspects at…

VEMAP phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

Treesearch

Timothy G.F. Kittel; Nan. A. Rosenbloom; J.A. Royle; C. Daly; W.P. Gibson; H.H. Fisher; P. Thornton; D.N. Yates; S. Aulenbach; C. Kaufman; R. McKeown; Dominque Bachelet; David S. Schimel

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the...

Multivariate statistical techniques for the evaluation of surface water quality of the Himalayan foothills streams, Pakistan

NASA Astrophysics Data System (ADS)

Malik, Riffat Naseem; Hashmi, Muhammad Zaffar

2017-10-01

Himalayan foothills streams, Pakistan play an important role in living water supply and irrigation of farmlands; thus, the water quality is closely related to public health. Multivariate techniques were applied to check spatial and seasonal trends, and metals contamination sources of the Himalayan foothills streams, Pakistan. Grab surface water samples were collected from different sites (5-15 cm water depth) in pre-washed polyethylene containers. Fast Sequential Atomic Absorption Spectrophotometer (Varian FSAA-240) was used to measure the metals concentration. Concentrations of Ni, Cu, and Mn were high in pre-monsoon season than the post-monsoon season. Cluster analysis identified impaired, moderately impaired and least impaired clusters based on water parameters. Discriminant function analysis indicated spatial variability in water was due to temperature, electrical conductivity, nitrates, iron and lead whereas seasonal variations were correlated with 16 physicochemical parameters. Factor analysis identified municipal and poultry waste, automobile activities, surface runoff, and soil weathering as major sources of contamination. Levels of Mn, Cr, Fe, Pb, Cd, Zn and alkalinity were above the WHO and USEPA standards for surface water. The results of present study will help to higher authorities for the management of the Himalayan foothills streams.

Analysis of grating doublets for achromatic beam-splitting

PubMed Central

Pacheco, Shaun; Milster, Tom; Liang, Rongguang

2015-01-01

Achromatic beam-splitting grating doublets are designed for both continuous phase and binary phase gratings. By analyzing the sensitivity to lateral shifts between the two grating layers, it is shown that continuous-profile grating doublets are extremely difficult to fabricate. Achromatic grating doublets that have profiles with a constant first spatial derivative are significantly more resistant to lateral shifts between grating layers, where one design case showed a 17 times improvement in performance. Therefore, binary phase, multi-level phase, and blazed grating doublets perform significantly better than continuous phase grating doublets in the presence of a lateral shift between two grating layers. By studying the sensitivity to fabrication errors in the height of both grating layers, one grating layer height can be adjusted to maintain excellent performance over a large wavelength range if the other grating layer is fabricated incorrectly. It is shown in one design case that the performance of an achromatic Dammann grating doublet can be improved by a factor of 215 if the heights of the grating layers are chosen to minimize the performance change in the presence of fabrication errors. PMID:26368261

GeV Detection of HESS J0632+057

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

Li, Jian; Torres, Diego F.; Wilhelmi, Emma de Oña

2017-09-10

HESS J0632+057 is the only gamma-ray binary that has been detected at TeV energies, but not at GeV energies yet. Based on nearly nine years of Fermi Large Area Telescope (LAT) Pass 8 data, we report here on a deep search for the gamma-ray emission from HESS J0632+057 in the 0.1–300 GeV energy range. We find a previously unknown gamma-ray source, Fermi J0632.6+0548, spatially coincident with HESS J0632+057. The measured flux of Fermi J0632.6+0548 is consistent with the previous flux upper limit on HESS J0632+057 and shows variability that can be related to the HESS J0632+057 orbital phase. We proposemore » that Fermi J0632.6+0548 is the GeV counterpart of HESS J0632+057. Considering the Very High Energy spectrum of HESS J0632+057, a possible spectral turnover above 10 GeV may exist in Fermi J0632.6+0548, as appears to be common in other established gamma-ray binaries.« less

Efficient Data Mining for Local Binary Pattern in Texture Image Analysis

PubMed Central

Kwak, Jin Tae; Xu, Sheng; Wood, Bradford J.

2015-01-01

Local binary pattern (LBP) is a simple gray scale descriptor to characterize the local distribution of the grey levels in an image. Multi-resolution LBP and/or combinations of the LBPs have shown to be effective in texture image analysis. However, it is unclear what resolutions or combinations to choose for texture analysis. Examining all the possible cases is impractical and intractable due to the exponential growth in a feature space. This limits the accuracy and time- and space-efficiency of LBP. Here, we propose a data mining approach for LBP, which efficiently explores a high-dimensional feature space and finds a relatively smaller number of discriminative features. The features can be any combinations of LBPs. These may not be achievable with conventional approaches. Hence, our approach not only fully utilizes the capability of LBP but also maintains the low computational complexity. We incorporated three different descriptors (LBP, local contrast measure, and local directional derivative measure) with three spatial resolutions and evaluated our approach using two comprehensive texture databases. The results demonstrated the effectiveness and robustness of our approach to different experimental designs and texture images. PMID:25767332

Dynamical inversion of the energy landscape promotes non-equilibrium self-assembly of binary mixtures

DOE PAGES

Pestana, Luis Ruiz; Minnetian, Natalie; Lammers, Laura Nielsen; ...

2018-01-02

When driven out of equilibrium, many diverse systems can form complex spatial and dynamical patterns, even in the absence of attractive interactions. Using kinetic Monte Carlo simulations, we investigate the phase behavior of a binary system of particles of dissimilar size confined between semiflexible planar surfaces, in which the nanoconfinement introduces a non-local coupling between particles, which we model as an activation energy barrier to diffusion that decreases with the local fraction of the larger particle. The system autonomously reaches a cyclical non-equilibrium state characterized by the formation and dissolution of metastable micelle-like clusters with the small particles in themore » core and the large ones in the surrounding corona. The power spectrum of the fluctuations in the aggregation number exhibits 1/f noise reminiscent of self-organized critical systems. Finally, we suggest that the dynamical metastability of the micellar structures arises from an inversion of the energy landscape, in which the relaxation dynamics of one of the species induces a metastable phase for the other species.« less

Planetary nebulae: 20 years of Hubble inquiry

NASA Astrophysics Data System (ADS)

Balick, Bruce

2012-08-01

The Hubble Space Telescope has served the critical roles of microscope and movie camera in the past 20 years of research on planetary nebulae (``PNe''). We have glimpsed the details of the evolving structures of neutral and ionized post-AGB objects, built ingenious heuristic models that mimic these structures, and constrained most of the relevant physical processes with careful observations and interpretation. We have searched for close physical binary stars with spatial resolution ~50 AU at 1 AU, located jets emerging from the nucleus at speeds up to 2000 km s-1 and matched newly discovered molecular and X-ray emission regions to physical substructures in order to better understand how stellar winds and ionizing radiation interact to form the lovely symmetries that are observed. Ultraviolet spectra of CNO in PNe help to uncover how stars process deep inside AGB stars with unstable nuclear burning zones. HST broadband imaging has been at the forefront of uncovering surprisingly complex wind morphologies produced at the tip of the AGB, and has led to an increasing realization of the potentially vital roles of close binary stars and emerging magnetic fields in shaping stellar winds.

Fast precalculated triangular mesh algorithm for 3D binary computer-generated holograms.

PubMed

Yang, Fan; Kaczorowski, Andrzej; Wilkinson, Tim D

2014-12-10

A new method for constructing computer-generated holograms using a precalculated triangular mesh is presented. The speed of calculation can be increased dramatically by exploiting both the precalculated base triangle and GPU parallel computing. Unlike algorithms using point-based sources, this method can reconstruct a more vivid 3D object instead of a "hollow image." In addition, there is no need to do a fast Fourier transform for each 3D element every time. A ferroelectric liquid crystal spatial light modulator is used to display the binary hologram within our experiment and the hologram of a base right triangle is produced by utilizing just a one-step Fourier transform in the 2D case, which can be expanded to the 3D case by multiplying by a suitable Fresnel phase plane. All 3D holograms generated in this paper are based on Fresnel propagation; thus, the Fresnel plane is treated as a vital element in producing the hologram. A GeForce GTX 770 graphics card with 2 GB memory is used to achieve parallel computing.

Dynamical inversion of the energy landscape promotes non-equilibrium self-assembly of binary mixtures

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

Pestana, Luis Ruiz; Minnetian, Natalie; Lammers, Laura Nielsen

When driven out of equilibrium, many diverse systems can form complex spatial and dynamical patterns, even in the absence of attractive interactions. Using kinetic Monte Carlo simulations, we investigate the phase behavior of a binary system of particles of dissimilar size confined between semiflexible planar surfaces, in which the nanoconfinement introduces a non-local coupling between particles, which we model as an activation energy barrier to diffusion that decreases with the local fraction of the larger particle. The system autonomously reaches a cyclical non-equilibrium state characterized by the formation and dissolution of metastable micelle-like clusters with the small particles in themore » core and the large ones in the surrounding corona. The power spectrum of the fluctuations in the aggregation number exhibits 1/f noise reminiscent of self-organized critical systems. Finally, we suggest that the dynamical metastability of the micellar structures arises from an inversion of the energy landscape, in which the relaxation dynamics of one of the species induces a metastable phase for the other species.« less

A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

NASA Astrophysics Data System (ADS)

Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

2018-03-01

Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

Chemical Abundance Analysis of Moving Group W11450 (Latham 1)

NASA Astrophysics Data System (ADS)

O'Connell, Julia E.; Martens, Kylee; Frinchaboy, Peter M.

2016-12-01

We present elemental abundances for all seven stars in Moving Group W11450 (Latham 1) to determine if they may be chemically related. These stars appear to be both spatially and kinematically related, but no spectroscopic abundance analysis exists in literature. Abundances for eight elements were derived via equivalent width analyses of high-resolution (R ˜ 60,000), high-signal-to-noise ratio (< {{S}}/{{N}}> ˜ 100) spectra obtained with the Otto Struve 2.1 m telescope and the Sandiford Echelle Spectrograph at McDonald Observatory. The large star-to-star scatter in metallicity, -0.55 ≤ [Fe/H] ≤slant 0.06 dex (σ = 0.25), implies these stars were not produced from the same chemically homogeneous molecular cloud, and are therefore not part of a remnant or open cluster as previously proposed. Prior to this analysis, it was suggested that two stars in the group, W11449 and W11450, are possible wide binaries. The candidate wide binary pair show similar chemical abundance patterns with not only iron but with other elements analyzed in this study, suggesting the proposed connection between these two stars may be real.

Properties of the Closest Young Binaries. I. DF Tau’s Unequal Circumstellar Disk Evolution

NASA Astrophysics Data System (ADS)

Allen, T. S.; Prato, L.; Wright-Garba, N.; Schaefer, G.; Biddle, L. I.; Skiff, B.; Avilez, I.; Muzzio, R.; Simon, M.

2017-08-01

We present high-resolution, spatially resolved, near-infrared spectroscopy and imaging of the two components of DF Tau, a young, low-mass, visual binary in the Taurus star-forming region. With these data, we provide a more precise orbital solution for the system, determine component spectral types, radial velocity, veiling and v\\sin I values, and construct individual spectral energy distributions. We estimate the masses of both stars to be ˜ 0.6 {M}⊙ . We find markedly different circumstellar properties for DF Tau A and B: evidence for a disk, such as near-infrared excess and accretion signatures, is clearly present for the primary, while it is absent for the secondary. Additionally, the v\\sin I and rotation period measurements show that the secondary is rotating significantly more rapidly than the primary. We interpret these results in the framework of disk-locking and argue that DF Tau A is an example of disk-modulated rotation in a young system. The DF Tau system raises fundamental questions about our assumptions of universal disk formation and evolution.

A binary logistic regression model with complex sampling design of unmet need for family planning among all women aged (15-49) in Ethiopia.

PubMed

Workie, Demeke Lakew; Zike, Dereje Tesfaye; Fenta, Haile Mekonnen; Mekonnen, Mulusew Admasu

2017-09-01

Unintended pregnancy related to unmet need is a worldwide problem that affects societies. The main objective of this study was to identify the prevalence and determinants of unmet need for family planning among women aged (15-49) in Ethiopia. The Performance Monitoring and Accountability2020/Ethiopia was conducted in April 2016 at round-4 from 7494 women with two-stage-stratified sampling. Bi-variable and multi-variable binary logistic regression model with complex sampling design was fitted. The prevalence of unmet-need for family planning was 16.2% in Ethiopia. Women between the age range of 15-24 years were 2.266 times more likely to have unmet need family planning compared to above 35 years. Women who were currently married were about 8 times more likely to have unmet need family planning compared to never married women. Women who had no under-five child were 0.125 times less likely to have unmet need family planning compared to those who had more than two-under-5. The key determinants of unmet need family planning in Ethiopia were residence, age, marital-status, education, household members, birth-events and number of under-5 children. Thus the Government of Ethiopia would take immediate steps to address the causes of high unmet need for family planning among women.

Development of a simple binary response questionnaire to identify airflow obstruction in a smoking population in Argentina.

PubMed

Bergna, Miguel A; García, Gabriel R; Alchapar, Ramon; Altieri, Hector; Casas, Juan C Figueroa; Larrateguy, Luis; Nannini, Luis J; Pascansky, Daniel; Grabre, Pedro; Zabert, Gustavo; Miravitlles, Marc

2015-06-01

The CODE questionnaire (COPD detection questionnaire), a simple, binary response scale (yes/no), screening questionnaire, was developed for the identification of patients with chronic obstructive pulmonary disease (COPD). We conducted a survey of 468 subjects with a smoking history in 10 public hospitals in Argentina. Patients with a previous diagnosis of COPD, asthma and other respiratory illness were excluded. Items that measured conceptual domains in terms of characteristics of symptoms, smoking history and demographics data were considered. 96 (20.5%) subjects had a diagnosis of COPD according to the 2010 Global Initiative for Chronic Obstructive Lung Disease strategy document. The variables selected for the final questionnaire were based on univariate and multivariate analyses and clinical criteria. Finally, we selected the presence or absence of six variables (age ≥50 years, smoking history ≥30 pack-years, male sex, chronic cough, chronic phlegm and dyspnoea). Of patients without any of these six variables (0 points), none had COPD. The ability of the CODE questionnaire to discriminate between subjects with and without COPD was good (the area under the receiver operating characteristic curve was 0.75). Higher scores were associated with a greater probability of COPD. The CODE questionnaire is a brief, accurate questionnaire that can identify smoking individuals likely to have COPD. Copyright ©ERS 2015.

Characteristics of foodborne outbreaks in which use of analytical epidemiological studies contributed to identification of suspected vehicles, European Union, 2007 to 2011.

PubMed

Schlinkmann, K M; Razum, O; Werber, D

2017-04-01

Foodborne disease outbreaks (FBDOs) occur frequently in Europe. Employing analytical epidemiological study designs increases the likelihood of identifying the suspected vehicle(s), but these studies are rarely applied in FBDO investigations. We used multivariable binary logistic regression analysis to identify characteristics of investigated FBDOs reported to the European Food Safety Authority (2007-2011) that were associated with analytical epidemiological evidence (compared to evidence from microbiological investigations/descriptive epidemiology only). The analysis was restricted to FBDO investigations, where the evidence for the suspected vehicle was considered 'strong', i.e. convincing. The presence of analytical epidemiological evidence was reported in 2012 (50%) of these 4038 outbreaks. In multivariable analysis, increasing outbreak size, number of hospitalizations, causative (i.e. aetiological) agent (whether identified and, if so, which one), and the setting in which these outbreaks occurred (e.g. geographically dispersed outbreaks) were independently associated with presence of analytical evidence. The number of investigations with reported analytical epidemiological evidence was unexpectedly high, likely indicating the need for quality assurance within the European Union foodborne outbreak reporting system, and warranting cautious interpretation of our findings. This first analysis of evidence implicating a food vehicle in FBDOs may help to inform public health authorities on when to use analytical epidemiological study designs.

Prospects of second generation artificial intelligence tools in calibration of chemical sensors.

PubMed

Braibanti, Antonio; Rao, Rupenaguntla Sambasiva; Ramam, Veluri Anantha; Rao, Gollapalli Nageswara; Rao, Vaddadi Venkata Panakala

2005-05-01

Multivariate data driven calibration models with neural networks (NNs) are developed for binary (Cu++ and Ca++) and quaternary (K+, Ca++, NO3- and Cl-) ion-selective electrode (ISE) data. The response profiles of ISEs with concentrations are non-linear and sub-Nernstian. This task represents function approximation of multi-variate, multi-response, correlated, non-linear data with unknown noise structure i.e. multi-component calibration/prediction in chemometric parlance. Radial distribution function (RBF) and Fuzzy-ARTMAP-NN models implemented in the software packages, TRAJAN and Professional II, are employed for the calibration. The optimum NN models reported are based on residuals in concentration space. Being a data driven information technology, NN does not require a model, prior- or posterior- distribution of data or noise structure. Missing information, spikes or newer trends in different concentration ranges can be modeled through novelty detection. Two simulated data sets generated from mathematical functions are modeled as a function of number of data points and network parameters like number of neurons and nearest neighbors. The success of RBF and Fuzzy-ARTMAP-NNs to develop adequate calibration models for experimental data and function approximation models for more complex simulated data sets ensures AI2 (artificial intelligence, 2nd generation) as a promising technology in quantitation.

Analysis of longitudinal multivariate outcome data from couples cohort studies: application to HPV transmission dynamics

PubMed Central

Kong, Xiangrong; Wang, Mei-Cheng; Gray, Ronald

2014-01-01

We consider a specific situation of correlated data where multiple outcomes are repeatedly measured on each member of a couple. Such multivariate longitudinal data from couples may exhibit multi-faceted correlations which can be further complicated if there are polygamous partnerships. An example is data from cohort studies on human papillomavirus (HPV) transmission dynamics in heterosexual couples. HPV is a common sexually transmitted disease with 14 known oncogenic types causing anogenital cancers. The binary outcomes on the multiple types measured in couples over time may introduce inter-type, intra-couple, and temporal correlations. Simple analysis using generalized estimating equations or random effects models lacks interpretability and cannot fully utilize the available information. We developed a hybrid modeling strategy using Markov transition models together with pairwise composite likelihood for analyzing such data. The method can be used to identify risk factors associated with HPV transmission and persistence, estimate difference in risks between male-to-female and female-to-male HPV transmission, compare type-specific transmission risks within couples, and characterize the inter-type and intra-couple associations. Applying the method to HPV couple data collected in a Ugandan male circumcision (MC) trial, we assessed the effect of MC and the role of gender on risks of HPV transmission and persistence. PMID:26195849

Defining an additivity framework for mixture research in inducible whole-cell biosensors

NASA Astrophysics Data System (ADS)

Martin-Betancor, K.; Ritz, C.; Fernández-Piñas, F.; Leganés, F.; Rodea-Palomares, I.

2015-11-01

A novel additivity framework for mixture effect modelling in the context of whole cell inducible biosensors has been mathematically developed and implemented in R. The proposed method is a multivariate extension of the effective dose (EDp) concept. Specifically, the extension accounts for differential maximal effects among analytes and response inhibition beyond the maximum permissive concentrations. This allows a multivariate extension of Loewe additivity, enabling direct application in a biphasic dose-response framework. The proposed additivity definition was validated, and its applicability illustrated by studying the response of the cyanobacterial biosensor Synechococcus elongatus PCC 7942 pBG2120 to binary mixtures of Zn, Cu, Cd, Ag, Co and Hg. The novel method allowed by the first time to model complete dose-response profiles of an inducible whole cell biosensor to mixtures. In addition, the approach also allowed identification and quantification of departures from additivity (interactions) among analytes. The biosensor was found to respond in a near additive way to heavy metal mixtures except when Hg, Co and Ag were present, in which case strong interactions occurred. The method is a useful contribution for the whole cell biosensors discipline and related areas allowing to perform appropriate assessment of mixture effects in non-monotonic dose-response frameworks

Simultaneous chemometric determination of pyridoxine hydrochloride and isoniazid in tablets by multivariate regression methods.

PubMed

Dinç, Erdal; Ustündağ, Ozgür; Baleanu, Dumitru

2010-08-01

The sole use of pyridoxine hydrochloride during treatment of tuberculosis gives rise to pyridoxine deficiency. Therefore, a combination of pyridoxine hydrochloride and isoniazid is used in pharmaceutical dosage form in tuberculosis treatment to reduce this side effect. In this study, two chemometric methods, partial least squares (PLS) and principal component regression (PCR), were applied to the simultaneous determination of pyridoxine (PYR) and isoniazid (ISO) in their tablets. A concentration training set comprising binary mixtures of PYR and ISO consisting of 20 different combinations were randomly prepared in 0.1 M HCl. Both multivariate calibration models were constructed using the relationships between the concentration data set (concentration data matrix) and absorbance data matrix in the spectral region 200-330 nm. The accuracy and the precision of the proposed chemometric methods were validated by analyzing synthetic mixtures containing the investigated drugs. The recovery results obtained by applying PCR and PLS calibrations to the artificial mixtures were found between 100.0 and 100.7%. Satisfactory results obtained by applying the PLS and PCR methods to both artificial and commercial samples were obtained. The results obtained in this manuscript strongly encourage us to use them for the quality control and the routine analysis of the marketing tablets containing PYR and ISO drugs. Copyright © 2010 John Wiley & Sons, Ltd.

Characterizing the Associative Content of Brain Structures Involved in Habitual and Goal-Directed Actions in Humans: A Multivariate fMRI Study

PubMed Central

Liljeholm, Mimi; Zika, Ondrej; O'Doherty, John P.

2015-01-01

While there is accumulating evidence for the existence of distinct neural systems supporting goal-directed and habitual action selection in the mammalian brain, much less is known about the nature of the information being processed in these different brain regions. Associative learning theory predicts that brain systems involved in habitual control, such as the dorsolateral striatum, should contain stimulus and response information only, but not outcome information, while regions involved in goal-directed action, such as ventromedial and dorsolateral prefrontal cortex and dorsomedial striatum, should be involved in processing information about outcomes as well as stimuli and responses. To test this prediction, human participants underwent fMRI while engaging in a binary choice task designed to enable the separate identification of these different representations with a multivariate classification analysis approach. Consistent with our predictions, the dorsolateral striatum contained information about responses but not outcomes at the time of an initial stimulus, while the regions implicated in goal-directed action selection contained information about both responses and outcomes. These findings suggest that differential contributions of these regions to habitual and goal-directed behavioral control may depend in part on basic differences in the type of information that these regions have access to at the time of decision making. PMID:25740507

Multivariate analysis, mass balance techniques, and statistical tests as tools in igneous petrology: application to the Sierra de las Cruces volcanic range (Mexican Volcanic Belt).

PubMed

Velasco-Tapia, Fernando

2014-01-01

Magmatic processes have usually been identified and evaluated using qualitative or semiquantitative geochemical or isotopic tools based on a restricted number of variables. However, a more complete and quantitative view could be reached applying multivariate analysis, mass balance techniques, and statistical tests. As an example, in this work a statistical and quantitative scheme is applied to analyze the geochemical features for the Sierra de las Cruces (SC) volcanic range (Mexican Volcanic Belt). In this locality, the volcanic activity (3.7 to 0.5 Ma) was dominantly dacitic, but the presence of spheroidal andesitic enclaves and/or diverse disequilibrium features in majority of lavas confirms the operation of magma mixing/mingling. New discriminant-function-based multidimensional diagrams were used to discriminate tectonic setting. Statistical tests of discordancy and significance were applied to evaluate the influence of the subducting Cocos plate, which seems to be rather negligible for the SC magmas in relation to several major and trace elements. A cluster analysis following Ward's linkage rule was carried out to classify the SC volcanic rocks geochemical groups. Finally, two mass-balance schemes were applied for the quantitative evaluation of the proportion of the end-member components (dacitic and andesitic magmas) in the comingled lavas (binary mixtures).

Chemometric methods for the simultaneous determination of some water-soluble vitamins.

PubMed

Mohamed, Abdel-Maaboud I; Mohamed, Horria A; Mohamed, Niveen A; El-Zahery, Marwa R

2011-01-01

Two spectrophotometric methods, derivative and multivariate methods, were applied for the determination of binary, ternary, and quaternary mixtures of the water-soluble vitamins thiamine HCI (I), pyridoxine HCI (II), riboflavin (III), and cyanocobalamin (IV). The first method is divided into first derivative and first derivative of ratio spectra methods, and the second into classical least squares and principal components regression methods. Both methods are based on spectrophotometric measurements of the studied vitamins in 0.1 M HCl solution in the range of 200-500 nm for all components. The linear calibration curves were obtained from 2.5-90 microg/mL, and the correlation coefficients ranged from 0.9991 to 0.9999. These methods were applied for the analysis of the following mixtures: (I) and (II); (I), (II), and (III); (I), (II), and (IV); and (I), (II), (III), and (IV). The described methods were successfully applied for the determination of vitamin combinations in synthetic mixtures and dosage forms from different manufacturers. The recovery ranged from 96.1 +/- 1.2 to 101.2 +/- 1.0% for derivative methods and 97.0 +/- 0.5 to 101.9 +/- 1.3% for multivariate methods. The results of the developed methods were compared with those of reported methods, and gave good accuracy and precision.

Evaluating MODIS snow products for modelling snowmelt runoff: Case study of the Rio Grande headwaters

NASA Astrophysics Data System (ADS)

Steele, Caitriana; Dialesandro, John; James, Darren; Elias, Emile; Rango, Albert; Bleiweiss, Max

2017-12-01

Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM) and in other models for simulating discharge from snowmelt. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM +) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and may not always provide sufficient cloud-free dates. The coarser spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) offers better temporal resolution and in cloudy years, MODIS data offer the best alternative for mapping snow cover when finer spatial resolution data are unavailable. However, MODIS' coarse spatial resolution (500 m) can obscure fine spatial patterning in snow cover and some MODIS products are not sensitive to end-of-season snow cover. In this study, we aimed to test MODIS snow products for use in simulating snowmelt runoff from smaller headwater basins by a) comparing maps of TM and MODIS-based SCA and b) determining how SRM streamflow simulations are changed by the different estimates of seasonal snow depletion. We compared gridded MODIS snow products (Collection 5 MOD10A1 fractional and binary SCA; SCA derived from Collection 6 MOD10A1 Normalised Difference Snow Index (NDSI) Snow Cover), and the MODIS Snow Covered-Area and Grain size retrieval (MODSCAG) canopy-corrected fractional SCA (SCAMG), with reference SCA maps (SCAREF) generated from binary classification of TM imagery. SCAMG showed strong agreement with SCAREF; excluding true negatives (where both methods agreed no snow was present) the median percent difference between SCAREF and SCAMG ranged between -2.4% and 4.7%. We simulated runoff for each of the four study years using SRM populated with and calibrated for snow depletion curves derived from SCAREF. We then substituted in each of the MODIS-derived depletion curves. With efficiency coefficients ranging between 0.73 and 0.93, SRM simulation results from the SCAMG runs yielded the best results of all the MODIS products and only slightly underestimated discharge volume (between 7 and 11% of measured annual discharge). SRM simulations that used SCA derived from Collection 6 NDSI Snow Cover also yielded promising results, with efficiency coefficients ranging between 0.73 and 0.91. In conclusion, we recommend that when simulating snowmelt runoff from small basins (<4000 km2) with SRM, we recommend that users select either canopy-corrected MODSCAG or create their own site-specific products from the Collection 6 MOD10A1 NDSI.

Learning Abilities and Disabilities: Generalist Genes, Specialist Environments

PubMed Central

Kovas, Yulia; Plomin, Robert

2007-01-01

Twin studies comparing identical and fraternal twins consistently show substantial genetic influence on individual differences in learning abilities such as reading and mathematics, as well as in other cognitive abilities such as spatial ability and memory. Multivariate genetic research has shown that the same set of genes is largely responsible for genetic influence on these diverse cognitive areas. We call these “generalist genes.” What differentiates these abilities is largely the environment, especially nonshared environments that make children growing up in the same family different from one another. These multivariate genetic findings of generalist genes and specialist environments have far-reaching implications for diagnosis and treatment of learning disabilities and for understanding the brain mechanisms that mediate these effects. PMID:20351764

Stability of binary and ternary model oil-field particle suspensions: a multivariate analysis approach.

PubMed

Dudásová, Dorota; Rune Flåten, Geir; Sjöblom, Johan; Øye, Gisle

2009-09-15

The transmission profiles of one- to three-component particle suspension mixtures were analyzed by multivariate methods such as principal component analysis (PCA) and partial least-squares regression (PLS). The particles mimic the solids present in oil-field-produced water. Kaolin and silica represent solids of reservoir origin, whereas FeS is the product of bacterial metabolic activities, and Fe(3)O(4) corrosion product (e.g., from pipelines). All particles were coated with crude oil surface active components to imitate particles in real systems. The effects of different variables (concentration, temperature, and coating) on the suspension stability were studied with Turbiscan LAb(Expert). The transmission profiles over 75 min represent the overall water quality, while the transmission during the first 15.5 min gives information for suspension behavior during a representative time period for the hold time in the separator. The behavior of the mixed particle suspensions was compared to that of the single particle suspensions and models describing the systems were built. The findings are summarized as follows: silica seems to dominate the mixture properties in the binary suspensions toward enhanced separation. For 75 min, temperature and concentration are the most significant, while for 15.5 min, concentration is the only significant variable. Models for prediction of transmission spectra from run parameters as well as particle type from transmission profiles (inverse calibration) give a reasonable description of the relationships. In ternary particle mixtures, silica is not dominant and for 75 min, the significant variables for mixture (temperature and coating) are more similar to single kaolin and FeS/Fe(3)O(4). On the other hand, for 15.5 min, the coating is the most significant and this is similar to one for silica (at 15.5 min). The model for prediction of transmission spectra from run parameters gives good estimates of the transmission profiles. Although the model for prediction of particle type from transmission parameters is able to predict some particles, further improvement is required before all particles are consistently correctly classified. Cross-validation was done for both models and estimation errors are reported.

Sociodemographic profile and predictors of outpatient clinic attendance among HIV-positive patients initiating antiretroviral therapy in Selangor, Malaysia.

PubMed

Abdulrahman, Surajudeen Abiola; Rampal, Lekhraj; Othman, Norlijah; Ibrahim, Faisal; Hayati, Kadir Shahar; Radhakrishnan, Anuradha P

2017-01-01

Inconsistent literature evidence suggests that sociodemographic, economic, and system- and patient-related factors are associated with clinic attendance among the HIV-positive population receiving antiretroviral therapy (ART) around the world. We examined the factors that predict outpatient clinic attendance among a cohort of HIV-positive patients initiating ART in Selangor, Malaysia. This cross-sectional study analyzed secondary data on outpatient clinic attendance and sociodemographic, economic, psychosocial, and patient-related factors among 242 adult Malaysian patients initiating ART in Selangor, Malaysia. Study cohort was enrolled in a parent randomized controlled trial (RCT) in Hospital Sungai Buloh Malaysia between January and December 2014, during which peer counseling, medication, and clinic appointment reminders were provided to the intervention group through short message service (SMS) and telephone calls for 24 consecutive weeks. Data on outpatient clinic attendance were extracted from the hospital electronic medical records system, while other patient-level data were extracted from pre-validated Adult AIDS Clinical Trial Group (AACTG) adherence questionnaires in which primary data were collected. Outpatient clinic attendance was categorized into binary outcome - regular attendee and defaulter categories - based on the number of missed scheduled outpatient clinic appointments within a 6-month period. Multivariate regression models were fitted to examine predictors of outpatient clinic attendance using SPSS version 22 and R software. A total of 224 (93%) patients who completed 6-month assessment were included in the model. Out of those, 42 (18.7%) defaulted scheduled clinic attendance at least once. Missed appointments were significantly more prevalent among females (n=10, 37.0%), rural residents (n=10, 38.5%), and bisexual respondents (n=8, 47.1%). Multivariate binary logistic regression analysis showed that Indian ethnicity (adjusted odds ratio [AOR] =0.235; 95% CI [0.063-0.869]; P =0.030) and heterosexual orientation (AOR =4.199; 95% CI [1.040-16.957]; P =0.044) were significant predictors of outpatient clinic attendance among HIV-positive patients receiving ART in Malaysia. Ethnicity and sexual orientation of Malaysian patients may play a significant role in their level of adherence to scheduled clinic appointments. These factors should be considered during collaborative adherence strategy planning at ART initiation.

Spatial estimation from remotely sensed data via empirical Bayes models

NASA Technical Reports Server (NTRS)

Hill, J. R.; Hinkley, D. V.; Kostal, H.; Morris, C. N.

1984-01-01

Multichannel satellite image data, available as LANDSAT imagery, are recorded as a multivariate time series (four channels, multiple passovers) in two spatial dimensions. The application of parametric empirical Bayes theory to classification of, and estimating the probability of, each crop type at each of a large number of pixels is considered. This theory involves both the probability distribution of imagery data, conditional on crop types, and the prior spatial distribution of crop types. For the latter Markov models indexed by estimable parameters are used. A broad outline of the general theory reveals several questions for further research. Some detailed results are given for the special case of two crop types when only a line transect is analyzed. Finally, the estimation of an underlying continuous process on the lattice is discussed which would be applicable to such quantities as crop yield.

The genetic and environmental aetiology of spatial, mathematics and general anxiety

PubMed Central

Malanchini, Margherita; Rimfeld, Kaili; Shakeshaft, Nicholas G.; Rodic, Maja; Schofield, Kerry; Selzam, Saskia; Dale, Philip S.; Petrill, Stephen A.; Kovas, Yulia

2017-01-01

Individuals differ in their level of general anxiety as well as in their level of anxiety towards specific activities, such as mathematics and spatial tasks. Both specific anxieties correlate moderately with general anxiety, but the aetiology of their association remains unexplored. Moreover, the factor structure of spatial anxiety is to date unknown. The present study investigated the factor structure of spatial anxiety, its aetiology, and the origins of its association with general and mathematics anxiety in a sample of 1,464 19-21-year-old twin pairs from the UK representative Twins Early Development Study. Participants reported their general, mathematics and spatial anxiety as part of an online battery of tests. We found that spatial anxiety is a multifactorial construct, including two components: navigation anxiety and rotation/visualization anxiety. All anxiety measures were moderately heritable (30% to 41%), and non-shared environmental factors explained the remaining variance. Multivariate genetic analysis showed that, although some genetic and environmental factors contributed to all anxiety measures, a substantial portion of genetic and non-shared environmental influences were specific to each anxiety construct. This suggests that anxiety is a multifactorial construct phenotypically and aetiologically, highlighting the importance of studying anxiety within specific contexts. PMID:28220830

The genetic and environmental aetiology of spatial, mathematics and general anxiety.

PubMed

Malanchini, Margherita; Rimfeld, Kaili; Shakeshaft, Nicholas G; Rodic, Maja; Schofield, Kerry; Selzam, Saskia; Dale, Philip S; Petrill, Stephen A; Kovas, Yulia

2017-02-21

Individuals differ in their level of general anxiety as well as in their level of anxiety towards specific activities, such as mathematics and spatial tasks. Both specific anxieties correlate moderately with general anxiety, but the aetiology of their association remains unexplored. Moreover, the factor structure of spatial anxiety is to date unknown. The present study investigated the factor structure of spatial anxiety, its aetiology, and the origins of its association with general and mathematics anxiety in a sample of 1,464 19-21-year-old twin pairs from the UK representative Twins Early Development Study. Participants reported their general, mathematics and spatial anxiety as part of an online battery of tests. We found that spatial anxiety is a multifactorial construct, including two components: navigation anxiety and rotation/visualization anxiety. All anxiety measures were moderately heritable (30% to 41%), and non-shared environmental factors explained the remaining variance. Multivariate genetic analysis showed that, although some genetic and environmental factors contributed to all anxiety measures, a substantial portion of genetic and non-shared environmental influences were specific to each anxiety construct. This suggests that anxiety is a multifactorial construct phenotypically and aetiologically, highlighting the importance of studying anxiety within specific contexts.