Characterization and Prediction of the SPI Background

NASA Technical Reports Server (NTRS)

Teegarden, B. J.; Jean, P.; Knodlseder, J.; Skinner, G. K.; Weidenspointer, G.

2003-01-01

The INTEGRAL Spectrometer, like most gamma-ray instruments, is background dominated. Signal-to-background ratios of a few percent are typical. The background is primarily due to interactions of cosmic rays in the instrument and spacecraft. It characteristically varies by +/- 5% on time scales of days. This variation is caused mainly by fluctuations in the interplanetary magnetic field that modulates the cosmic ray intensity. To achieve the maximum performance from SPI it is essential to have a high quality model of this background that can predict its value to a fraction of a percent. In this poster we characterize the background and its variability, explore various models, and evaluate the accuracy of their predictions.

Effect of Background Pressure on the Plasma Oscillation Characteristics of the HiVHAc Hall Thruster

NASA Technical Reports Server (NTRS)

Huang, Wensheng; Kamhawi, Hani; Lobbia, Robert B.; Brown, Daniel L.

2014-01-01

During a component compatibility test of the NASA HiVHAc Hall thruster, a number of plasma diagnostics were implemented to study the effect of varying facility background pressure on thruster operation. These diagnostics characterized the thruster performance, the plume, and the plasma oscillations in the thruster. Thruster performance and plume characteristics as functions of background pressure were previously published. This paper focuses on changes in the plasma oscillation characteristics with changing background pressure. The diagnostics used to study plasma oscillations include a high-speed camera and a set of high-speed Langmuir probes. The results show a rise in the oscillation frequency of the "breathing" mode with rising background pressure, which is hypothesized to be due to a shortening acceleration/ionization zone. An attempt is made to apply a simplified ingestion model to the data. The combined results are used to estimate the maximum acceptable background pressure for performance and wear testing.

Statistical Modeling of Natural Backgrounds in Hyperspectral LWIR Data

DTIC Science & Technology

2016-09-06

extremely important for studying performance trades. First, we study the validity of this model using real hyperspectral data, and compare the relative...difficult to validate any statistical model created for a target of interest. However, since background measurements are plentiful, it is reasonable to...Golden, S., Less, D., Jin, X., and Rynes, P., “ Modeling and analysis of LWIR signature variability associated with 3d and BRDF effects,” 98400P (May 2016

Linear model for fast background subtraction in oligonucleotide microarrays.

PubMed

Kroll, K Myriam; Barkema, Gerard T; Carlon, Enrico

2009-11-16

One important preprocessing step in the analysis of microarray data is background subtraction. In high-density oligonucleotide arrays this is recognized as a crucial step for the global performance of the data analysis from raw intensities to expression values. We propose here an algorithm for background estimation based on a model in which the cost function is quadratic in a set of fitting parameters such that minimization can be performed through linear algebra. The model incorporates two effects: 1) Correlated intensities between neighboring features in the chip and 2) sequence-dependent affinities for non-specific hybridization fitted by an extended nearest-neighbor model. The algorithm has been tested on 360 GeneChips from publicly available data of recent expression experiments. The algorithm is fast and accurate. Strong correlations between the fitted values for different experiments as well as between the free-energy parameters and their counterparts in aqueous solution indicate that the model captures a significant part of the underlying physical chemistry.

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

Archer, Daniel E.; Hornback, Donald Eric; Johnson, Jeffrey O.

This report summarizes the findings of a two year effort to systematically assess neutron and gamma backgrounds relevant to operational modeling and detection technology implementation. The first year effort focused on reviewing the origins of background sources and their impact on measured rates in operational scenarios of interest. The second year has focused on the assessment of detector and algorithm performance as they pertain to operational requirements against the various background sources and background levels.

Non-local gravity and comparison with observational datasets. II. Updated results and Bayesian model comparison with ΛCDM

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

Dirian, Yves; Foffa, Stefano; Kunz, Martin

We present a comprehensive and updated comparison with cosmological observations of two non-local modifications of gravity previously introduced by our group, the so called RR and RT models. We implement the background evolution and the cosmological perturbations of the models in a modified Boltzmann code, using CLASS. We then test the non-local models against the Planck 2015 TT, TE, EE and Cosmic Microwave Background (CMB) lensing data, isotropic and anisotropic Baryonic Acoustic Oscillations (BAO) data, JLA supernovae, H {sub 0} measurements and growth rate data, and we perform Bayesian parameter estimation. We then compare the RR, RT and ΛCDM models,more » using the Savage-Dickey method. We find that the RT model and ΛCDM perform equally well, while the performance of the RR model with respect to ΛCDM depends on whether or not we include a prior on H {sub 0} based on local measurements.« less

Salient object detection based on discriminative boundary and multiple cues integration

NASA Astrophysics Data System (ADS)

Jiang, Qingzhu; Wu, Zemin; Tian, Chang; Liu, Tao; Zeng, Mingyong; Hu, Lei

2016-01-01

In recent years, many saliency models have achieved good performance by taking the image boundary as the background prior. However, if all boundaries of an image are equally and artificially selected as background, misjudgment may happen when the object touches the boundary. We propose an algorithm called weighted contrast optimization based on discriminative boundary (wCODB). First, a background estimation model is reliably constructed through discriminating each boundary via Hausdorff distance. Second, the background-only weighted contrast is improved by fore-background weighted contrast, which is optimized through weight-adjustable optimization framework. Then to objectively estimate the quality of a saliency map, a simple but effective metric called spatial distribution of saliency map and mean saliency in covered window ratio (MSR) is designed. Finally, in order to further promote the detection result using MSR as the weight, we propose a saliency fusion framework to integrate three other cues-uniqueness, distribution, and coherence from three representative methods into our wCODB model. Extensive experiments on six public datasets demonstrate that our wCODB performs favorably against most of the methods based on boundary, and the integrated result outperforms all state-of-the-art methods.

Predicting performance: relative importance of students' background and past performance.

PubMed

Stegers-Jager, Karen M; Themmen, Axel P N; Cohen-Schotanus, Janke; Steyerberg, Ewout W

2015-09-01

Despite evidence for the predictive value of both pre-admission characteristics and past performance at medical school, their relative contribution to predicting medical school performance has not been thoroughly investigated. This study was designed to determine the relative importance of pre-admission characteristics and past performance in medical school in predicting student performance in pre-clinical and clinical training. This longitudinal prospective study followed six cohorts of students admitted to a Dutch, 6-year, undergraduate medical course during 2002-2007 (n = 2357). Four prediction models were developed using multivariate logistic regression analysis. Main outcome measures were 'Year 1 course completion within 1 year' (models 1a, 1b), 'Pre-clinical course completion within 4 years' (model 2) and 'Achievement of at least three of five clerkship grades of ≥ 8.0' (model 3). Pre-admission characteristics (models 1a, 1b, 2, 3) and past performance at medical school (models 1b, 2, 3) were included as predictor variables. In model 1a - including pre-admission characteristics only - the strongest predictor for Year 1 course completion was pre-university grade point average (GPA). Success factors were 'selected by admission testing' and 'age > 21 years'; risk factors were 'Surinamese/Antillean background', 'foreign pre-university degree', 'doctor parent' and male gender. In model 1b, number of attempts and GPA at 4 months were the strongest predictors for Year 1 course completion, and male gender remained a risk factor. Year 1 GPA was the strongest predictor for pre-clinical course completion, whereas being male or aged 19-21 years were risk factors. Pre-clinical course GPA positively predicted clinical performance, whereas being non-Dutch or a first-generation university student were important risk factors for lower clinical grades. Nagelkerke's R(2) ranged from 0.16 to 0.62. This study not only confirms the importance of past performance as a predictor of future performance in pre-clinical training, but also reveals the importance of a student's background as a predictor in clinical training. These findings have important practical implications for selection and support during medical school. © 2015 John Wiley & Sons Ltd.

Equity in the Turkish Education System: A Multilevel Analysis of Social Background Influences on the Mathematics Performance of 15-Year-Old Students

ERIC Educational Resources Information Center

Özdemir, Caner

2016-01-01

This paper aims to discover the level of equity in the Turkish education system using maths outcomes of 15-year-old students in the Programme for International Student Assessment (PISA) exam. In order to do that, associations between various social background variables and student performance are analysed via multilevel models. Female pupils,…

[Symptoms, disease models and treatment experiences of patients in psychosomatic rehabilitation with and without a history of migration].

PubMed

Gruner, Andrea; Oster, Jörg; Müller, Gottfried; von Wietersheim, Jörn

2012-01-01

Previous studies have shown that psychosomatic rehabilitation treatments were less successful for patients with a migration background. These findings should be explored further with the help of interviews. The main aim of this study was to compare patients with and without a migration background with regards to social-demographic variables, disease model, symptoms, and the course and result of a psychosomatic rehabilitation treatment. 75 patients with and 75 without a migration background were analysed. Half-structured interviews were carried out at admission, discharge and three months after discharge from treatment. Patients with a migration background were "sicker" at the beginning of the rehabilitation. Especially men with a migration background benefit less from the treatment and often did not feel "at the right place" in the psychosomatic rehabilitation. Patients with a migration background have a more negative view of their work performance than patients without a migration background. Patient with a migration background should receive more information about psychosomatic disease models and different treatment methods prior to their rehabilitation therapy.

Comparison of model and human observer performance in FFDM, DBT, and synthetic mammography

NASA Astrophysics Data System (ADS)

Ikejimba, Lynda; Glick, Stephen J.; Samei, Ehsan; Lo, Joseph Y.

2016-03-01

Reader studies are important in assessing breast imaging systems. The purpose of this work was to assess task-based performance of full field digital mammography (FFDM), digital breast tomosynthesis (DBT), and synthetic mammography (SM) using different phantom types, and to determine an accurate observer model for human readers. Images were acquired on a Hologic Selenia Dimensions system with a uniform and anthropomorphic phantom. A contrast detail insert of small, low-contrast disks was created using an inkjet printer with iodine-doped ink and inserted in the phantoms. The disks varied in diameter from 210 to 630 μm, and in contrast from 1.1% contrast to 2.2% in regular increments. Human and model observers performed a 4-alternative forced choice experiment. The models were a non-prewhitening matched filter with eye model (NPWE) and a channelized Hotelling observer with either Gabor channels (Gabor-CHO) or Laguerre-Gauss channels (LG-CHO). With the given phantoms, reader scores were higher in FFDM and DBT than SM. The structure in the phantom background had a bigger impact on outcome for DBT than for FFDM or SM. All three model observers showed good correlation with humans in the uniform background, with ρ between 0.89 and 0.93. However, in the structured background, only the CHOs had high correlation, with ρ=0.92 for Gabor-CHO, 0.90 for LG-CHO, and 0.77 for NPWE. Because results of any analysis can depend on the phantom structure, conclusions of modality performance may need to be taken in the context of an appropriate model observer and a realistic phantom.

Modelling a C-Band Space Surveillance Radar using Systems Tool Kit

DTIC Science & Technology

2013-02-01

directly) or ‘Calculate’ by selecting to use: Earth, Sun, Atmosphere, Rain, Clouds & Fog, Tropo Scintillation, and/or Cosmic Background noise in the...OVERVIEW OF THE RADAR.......................................................................................... 2 2.1 Background ...performance described in previous work [1]. UNCLASSIFIED 1 UNCLASSIFIED DSTO-TN-1164 2. Overview of the Radar 2.1 Background The AN/FPQ-14 is a

A biological hierarchical model based underwater moving object detection.

PubMed

Shen, Jie; Fan, Tanghuai; Tang, Min; Zhang, Qian; Sun, Zhen; Huang, Fengchen

2014-01-01

Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results.

A Biological Hierarchical Model Based Underwater Moving Object Detection

PubMed Central

Shen, Jie; Fan, Tanghuai; Tang, Min; Zhang, Qian; Sun, Zhen; Huang, Fengchen

2014-01-01

Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results. PMID:25140194

Visual signal detection in structured backgrounds. II. Effects of contrast gain control, background variations, and white noise

NASA Technical Reports Server (NTRS)

Eckstein, M. P.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.

Digital filtering and model updating methods for improving the robustness of near-infrared multivariate calibrations.

PubMed

Kramer, Kirsten E; Small, Gary W

2009-02-01

Fourier transform near-infrared (NIR) transmission spectra are used for quantitative analysis of glucose for 17 sets of prediction data sampled as much as six months outside the timeframe of the corresponding calibration data. Aqueous samples containing physiological levels of glucose in a matrix of bovine serum albumin and triacetin are used to simulate clinical samples such as blood plasma. Background spectra of a single analyte-free matrix sample acquired during the instrumental warm-up period on the prediction day are used for calibration updating and for determining the optimal frequency response of a preprocessing infinite impulse response time-domain digital filter. By tuning the filter and the calibration model to the specific instrumental response associated with the prediction day, the calibration model is given enhanced ability to operate over time. This methodology is demonstrated in conjunction with partial least squares calibration models built with a spectral range of 4700-4300 cm(-1). By using a subset of the background spectra to evaluate the prediction performance of the updated model, projections can be made regarding the success of subsequent glucose predictions. If a threshold standard error of prediction (SEP) of 1.5 mM is used to establish successful model performance with the glucose samples, the corresponding threshold for the SEP of the background spectra is found to be 1.3 mM. For calibration updating in conjunction with digital filtering, SEP values of all 17 prediction sets collected over 3-178 days displaced from the calibration data are below 1.5 mM. In addition, the diagnostic based on the background spectra correctly assesses the prediction performance in 16 of the 17 cases.

A neural model of border-ownership from kinetic occlusion.

PubMed

Layton, Oliver W; Yazdanbakhsh, Arash

2015-01-01

Camouflaged animals that have very similar textures to their surroundings are difficult to detect when stationary. However, when an animal moves, humans readily see a figure at a different depth than the background. How do humans perceive a figure breaking camouflage, even though the texture of the figure and its background may be statistically identical in luminance? We present a model that demonstrates how the primate visual system performs figure-ground segregation in extreme cases of breaking camouflage based on motion alone. Border-ownership signals develop as an emergent property in model V2 units whose receptive fields are nearby kinetically defined borders that separate the figure and background. Model simulations support border-ownership as a general mechanism by which the visual system performs figure-ground segregation, despite whether figure-ground boundaries are defined by luminance or motion contrast. The gradient of motion- and luminance-related border-ownership signals explains the perceived depth ordering of the foreground and background surfaces. Our model predicts that V2 neurons, which are sensitive to kinetic edges, are selective to border-ownership (magnocellular B cells). A distinct population of model V2 neurons is selective to border-ownership in figures defined by luminance contrast (parvocellular B cells). B cells in model V2 receive feedback from neurons in V4 and MT with larger receptive fields to bias border-ownership signals toward the figure. We predict that neurons in V4 and MT sensitive to kinetically defined figures play a crucial role in determining whether the foreground surface accretes, deletes, or produces a shearing motion with respect to the background. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting the performance of linear optical detectors in free space laser communication links

NASA Astrophysics Data System (ADS)

Farrell, Thomas C.

2018-05-01

While the fundamental performance limit for optical communications is set by the quantum nature of light, in practical systems background light, dark current, and thermal noise of the electronics also degrade performance. In this paper, we derive a set of equations predicting the performance of PIN diodes and linear mode avalanche photo diodes (APDs) in the presence of such noise sources. Electrons generated by signal, background, and dark current shot noise are well modeled in PIN diodes as Poissonian statistical processes. In APDs, on the other hand, the amplifying effects of the device result in statistics that are distinctly non-Poissonian. Thermal noise is well modeled as Gaussian. In this paper, we appeal to the central limit theorem and treat both the variability of the signal and the sum of noise sources as Gaussian. Comparison against Monte-Carlo simulation of PIN diode performance (where we do model shot noise with draws from a Poissonian distribution) validates the legitimacy of this approximation. On-off keying, M-ary pulse position, and binary differential phase shift keying modulation are modeled. We conclude with examples showing how the equations may be used in a link budget to estimate the performance of optical links using linear receivers.

Regional and global modeling estimates of policy relevant background ozone over the United States

NASA Astrophysics Data System (ADS)

Emery, Christopher; Jung, Jaegun; Downey, Nicole; Johnson, Jeremiah; Jimenez, Michele; Yarwood, Greg; Morris, Ralph

2012-02-01

Policy Relevant Background (PRB) ozone, as defined by the US Environmental Protection Agency (EPA), refers to ozone concentrations that would occur in the absence of all North American anthropogenic emissions. PRB enters into the calculation of health risk benefits, and as the US ozone standard approaches background levels, PRB is increasingly important in determining the feasibility and cost of compliance. As PRB is a hypothetical construct, modeling is a necessary tool. Since 2006 EPA has relied on global modeling to establish PRB for their regulatory analyses. Recent assessments with higher resolution global models exhibit improved agreement with remote observations and modest upward shifts in PRB estimates. This paper shifts the paradigm to a regional model (CAMx) run at 12 km resolution, for which North American boundary conditions were provided by a low-resolution version of the GEOS-Chem global model. We conducted a comprehensive model inter-comparison, from which we elucidate differences in predictive performance against ozone observations and differences in temporal and spatial background variability over the US. In general, CAMx performed better in replicating observations at remote monitoring sites, and performance remained better at higher concentrations. While spring and summer mean PRB predicted by GEOS-Chem ranged 20-45 ppb, CAMx predicted PRB ranged 25-50 ppb and reached well over 60 ppb in the west due to event-oriented phenomena such as stratospheric intrusion and wildfires. CAMx showed a higher correlation between modeled PRB and total observed ozone, which is significant for health risk assessments. A case study during April 2006 suggests that stratospheric exchange of ozone is underestimated in both models on an event basis. We conclude that wildfires, lightning NO x and stratospheric intrusions contribute a significant level of uncertainty in estimating PRB, and that PRB will require careful consideration in the ozone standard setting process.

Source apportionment of PM2.5 at the Lin'an regional background site in China with three receptor models

NASA Astrophysics Data System (ADS)

Deng, Junjun; Zhang, Yanru; Qiu, Yuqing; Zhang, Hongliang; Du, Wenjiao; Xu, Lingling; Hong, Youwei; Chen, Yanting; Chen, Jinsheng

2018-04-01

Source apportionment of fine particulate matter (PM2.5) were conducted at the Lin'an Regional Atmospheric Background Station (LA) in the Yangtze River Delta (YRD) region in China from July 2014 to April 2015 with three receptor models including principal component analysis combining multiple linear regression (PCA-MLR), UNMIX and Positive Matrix Factorization (PMF). The model performance, source identification and source contribution of the three models were analyzed and inter-compared. Source apportionment of PM2.5 was also conducted with the receptor models. Good correlations between the reconstructed and measured concentrations of PM2.5 and its major chemical species were obtained for all models. PMF resolved almost all masses of PM2.5, while PCA-MLR and UNMIX explained about 80%. Five, four and seven sources were identified by PCA-MLR, UNMIX and PMF, respectively. Combustion, secondary source, marine source, dust and industrial activities were identified by all the three receptor models. Combustion source and secondary source were the major sources, and totally contributed over 60% to PM2.5. The PMF model had a better performance on separating the different combustion sources. These findings improve the understanding of PM2.5 sources in background region.

Vehicle license plate recognition in dense fog based on improved atmospheric scattering model

NASA Astrophysics Data System (ADS)

Tang, Chunming; Lin, Jun; Chen, Chunkai; Dong, Yancheng

2018-04-01

An effective method based on improved atmospheric scattering model is proposed in this paper to handle the problem of the vehicle license plate location and recognition in dense fog. Dense fog detection is performed firstly by the top-hat transformation and the vertical edge detection, and the moving vehicle image is separated from the traffic video image. After the vehicle image is decomposed into two layers: structure and texture layers, the glow layer is separated from the structure layer to get the background layer. Followed by performing the mean-pooling and the bicubic interpolation algorithm, the atmospheric light map of the background layer can be predicted, meanwhile the transmission of the background layer is estimated through the grayed glow layer, whose gray value is altered by linear mapping. Then, according to the improved atmospheric scattering model, the final restored image can be obtained by fusing the restored background layer and the optimized texture layer. License plate location is performed secondly by a series of morphological operations, connected domain analysis and various validations. Characters extraction is achieved according to the projection. Finally, an offline trained pattern classifier of hybrid discriminative restricted boltzmann machines (HDRBM) is applied to recognize the characters. Experimental results on thorough data sets are reported to demonstrate that the proposed method can achieve high recognition accuracy and works robustly in the dense fog traffic environment during 24h or one day.

Low contrast detection in abdominal CT: comparing single-slice and multi-slice tasks

NASA Astrophysics Data System (ADS)

Ba, Alexandre; Racine, Damien; Viry, Anaïs.; Verdun, Francis R.; Schmidt, Sabine; Bochud, François O.

2017-03-01

Image quality assessment is crucial for the optimization of computed tomography (CT) protocols. Human and mathematical model observers are increasingly used for the detection of low contrast signal in abdominal CT, but are frequently limited to the use of a single image slice. Another limitation is that most of them only consider the detection of a signal embedded in a uniform background phantom. The purpose of this paper was to test if human observer performance is significantly different in CT images read in single or multiple slice modes and if these differences are the same for anatomical and uniform clinical images. We investigated detection performance and scrolling trends of human observers of a simulated liver lesion embedded in anatomical and uniform CT backgrounds. Results show that observers don't take significantly benefit of additional information provided in multi-slice reading mode. Regarding the background, performances are moderately higher for uniform than for anatomical images. Our results suggest that for low contrast detection in abdominal CT, the use of multi-slice model observers would probably only add a marginal benefit. On the other hand, the quality of a CT image is more accurately estimated with clinical anatomical backgrounds.

Simbol-X Background Minimization: Mirror Spacecraft Passive Shielding Trade-off Study

NASA Astrophysics Data System (ADS)

Fioretti, V.; Malaguti, G.; Bulgarelli, A.; Palumbo, G. G. C.; Ferri, A.; Attinà, P.

2009-05-01

The present work shows a quantitative trade-off analysis of the Simbol-X Mirror Spacecraft (MSC) passive shielding, in the phase space of the various parameters: mass budget, dimension, geometry and composition. A simplified physical (and geometrical) model of the sky screen, implemented by means of a GEANT4 simulation, has been developed to perform a performance-driven mass optimization and evaluate the residual background level on Simbol-X focal plane.

Psychophysical and perceptual performance in a simulated-scotoma model of human eye injury

NASA Astrophysics Data System (ADS)

Brandeis, R.; Egoz, I.; Peri, D.; Sapiens, N.; Turetz, J.

2008-02-01

Macular scotomas, affecting visual functioning, characterize many eye and neurological diseases like AMD, diabetes mellitus, multiple sclerosis, and macular hole. In this work, foveal visual field defects were modeled, and their effects were evaluated on spatial contrast sensitivity and a task of stimulus detection and aiming. The modeled occluding scotomas, of different size, were superimposed on the stimuli presented on the computer display, and were stabilized on the retina using a mono Purkinje Eye-Tracker. Spatial contrast sensitivity was evaluated using square-wave grating stimuli, whose contrast thresholds were measured using the method of constant stimuli with "catch trials". The detection task consisted of a triple conjunctive visual search display of: size (in visual angle), contrast and background (simple, low-level features vs. complex, high-level features). Search/aiming accuracy as well as R.T. measures used for performance evaluation. Artificially generated scotomas suppressed spatial contrast sensitivity in a size dependent manner, similar to previous studies. Deprivation effect was dependent on spatial frequency, consistent with retinal inhomogeneity models. Stimulus detection time was slowed in complex background search situation more than in simple background. Detection speed was dependent on scotoma size and size of stimulus. In contrast, visually guided aiming was more sensitive to scotoma effect in simple background search situation than in complex background. Both stimulus aiming R.T. and accuracy (precision targeting) were impaired, as a function of scotoma size and size of stimulus. The data can be explained by models distinguishing between saliency-based, parallel and serial search processes, guiding visual attention, which are supported by underlying retinal as well as neural mechanisms.

Development and application of diurnal thermal modeling for camouflage, concealment, and deception

NASA Astrophysics Data System (ADS)

Rodgers, Mark L. B.

2000-07-01

The art of camouflage is to make a military asset appear to be part of the natural environment: its background. In order to predict the likely performance of countermeasures in attaining this goal it is necessary to model the signatures of targets, backgrounds and the effect of countermeasures. A library of diurnal thermal models has been constructed covering a range of backgrounds from vegetated and non- vegetated surfaces to snow cover. These models, originally developed for Western Europe, have been validated successfully for theatres of operation from the arctic to the desert. This paper will show the basis for and development of physically based models for the diurnal thermal behavior both of these backgrounds and for major passive countermeasures: camouflage nets and continuous textile materials. The countermeasures set up significant challenges for the thermal modeler with their low but non-zero thermal inertial and the extent to which they influence local aerodynamic behavior. These challenges have been met and the necessary extensive validation has shown the ability of the models to predict successfully the behavior of in-service countermeasures.

Image Discrimination Models Predict Object Detection in Natural Backgrounds

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Rohaly, A. M.; Watson, Andrew B.; Null, Cynthia H. (Technical Monitor)

1994-01-01

Object detection involves looking for one of a large set of object sub-images in a large set of background images. Image discrimination models only predict the probability that an observer will detect a difference between two images. In a recent study based on only six different images, we found that discrimination models can predict the relative detectability of objects in those images, suggesting that these simpler models may be useful in some object detection applications. Here we replicate this result using a new, larger set of images. Fifteen images of a vehicle in an other-wise natural setting were altered to remove the vehicle and mixed with the original image in a proportion chosen to make the target neither perfectly recognizable nor unrecognizable. The target was also rotated about a vertical axis through its center and mixed with the background. Sixteen observers rated these 30 target images and the 15 background-only images for the presence of a vehicle. The likelihoods of the observer responses were computed from a Thurstone scaling model with the assumption that the detectabilities are proportional to the predictions of an image discrimination model. Three image discrimination models were used: a cortex transform model, a single channel model with a contrast sensitivity function filter, and the Root-Mean-Square (RMS) difference of the digital target and background-only images. As in the previous study, the cortex transform model performed best; the RMS difference predictor was second best; and last, but still a reasonable predictor, was the single channel model. Image discrimination models can predict the relative detectabilities of objects in natural backgrounds.

Sensor performance and weather effects modeling for intelligent transportation systems (ITS) applications

NASA Astrophysics Data System (ADS)

Everson, Jeffrey H.; Kopala, Edward W.; Lazofson, Laurence E.; Choe, Howard C.; Pomerleau, Dean A.

1995-01-01

Optical sensors are used for several ITS applications, including lateral control of vehicles, traffic sign recognition, car following, autonomous vehicle navigation, and obstacle detection. This paper treats the performance assessment of a sensor/image processor used as part of an on-board countermeasure system to prevent single vehicle roadway departure crashes. Sufficient image contrast between objects of interest and backgrounds is an essential factor influencing overall system performance. Contrast is determined by material properties affecting reflected/radiated intensities, as well as weather and visibility conditions. This paper discusses the modeling of these parameters and characterizes the contrast performance effects due to reduced visibility. The analysis process first involves generation of inherent road/off- road contrasts, followed by weather effects as a contrast modification. The sensor is modeled as a charge coupled device (CCD), with variable parameters. The results of the sensor/weather modeling are used to predict the performance on an in-vehicle warning system under various levels of adverse weather. Software employed in this effort was previously developed for the U.S. Air Force Wright Laboratory to determine target/background detection and recognition ranges for different sensor systems operating under various mission scenarios.

Listen to the Noise: Noise Is Beneficial for Cognitive Performance in ADHD

ERIC Educational Resources Information Center

Soderlund, Goran; Sikstrom, Sverker; Smart, Andrew

2007-01-01

Background: Noise is typically conceived of as being detrimental to cognitive performance. However, given the mechanism of stochastic resonance, a certain amount of noise can benefit performance. We investigate cognitive performance in noisy environments in relation to a neurocomputational model of attention deficit hyperactivity disorder (ADHD)…

Radiofrequency ablation: importance of background tissue electrical conductivity--an agar phantom and computer modeling study.

PubMed

Solazzo, Stephanie A; Liu, Zhengjun; Lobo, S Melvyn; Ahmed, Muneeb; Hines-Peralta, Andrew U; Lenkinski, Robert E; Goldberg, S Nahum

2005-08-01

To determine whether radiofrequency (RF)-induced heating can be correlated with background electrical conductivity in a controlled experimental phantom environment mimicking different background tissue electrical conductivities and to determine the potential electrical and physical basis for such a correlation by using computer modeling. The effect of background tissue electrical conductivity on RF-induced heating was studied in a controlled system of 80 two-compartment agar phantoms (with inner wells of 0.3%, 1.0%, or 36.0% NaCl) with background conductivity that varied from 0.6% to 5.0% NaCl. Mathematical modeling of the relationship between electrical conductivity and temperatures 2 cm from the electrode (T2cm) was performed. Next, computer simulation of RF heating by using two-dimensional finite-element analysis (ETherm) was performed with parameters selected to approximate the agar phantoms. Resultant heating, in terms of both the T2cm and the distance of defined thermal isotherms from the electrode surface, was calculated and compared with the phantom data. Additionally, electrical and thermal profiles were determined by using the computer modeling data and correlated by using linear regression analysis. For each inner compartment NaCl concentration, a negative exponential relationship was established between increased background NaCl concentration and the T2cm (R2= 0.64-0.78). Similar negative exponential relationships (r2 > 0.97%) were observed for the computer modeling. Correlation values (R2) between the computer and experimental data were 0.9, 0.9, and 0.55 for the 0.3%, 1.0%, and 36.0% inner NaCl concentrations, respectively. Plotting of the electrical field generated around the RF electrode identified the potential for a dramatic local change in electrical field distribution (ie, a second electrical peak ["E-peak"]) occurring at the interface between the two compartments of varied electrical background conductivity. Linear correlations between the E-peak and heating at T2cm (R2= 0.98-1.00) and the 50 degrees C isotherm (R2= 0.99-1.00) were established. These results demonstrate the strong relationship between background tissue conductivity and RF heating and further explain electrical phenomena that occur in a two-compartment system.

A salient region detection model combining background distribution measure for indoor robots.

PubMed

Li, Na; Xu, Hui; Wang, Zhenhua; Sun, Lining; Chen, Guodong

2017-01-01

Vision system plays an important role in the field of indoor robot. Saliency detection methods, capturing regions that are perceived as important, are used to improve the performance of visual perception system. Most of state-of-the-art methods for saliency detection, performing outstandingly in natural images, cannot work in complicated indoor environment. Therefore, we propose a new method comprised of graph-based RGB-D segmentation, primary saliency measure, background distribution measure, and combination. Besides, region roundness is proposed to describe the compactness of a region to measure background distribution more robustly. To validate the proposed approach, eleven influential methods are compared on the DSD and ECSSD dataset. Moreover, we build a mobile robot platform for application in an actual environment, and design three different kinds of experimental constructions that are different viewpoints, illumination variations and partial occlusions. Experimental results demonstrate that our model outperforms existing methods and is useful for indoor mobile robots.

Object Detection in Natural Backgrounds Predicted by Discrimination Performance and Models

NASA Technical Reports Server (NTRS)

Ahumada, A. J., Jr.; Watson, A. B.; Rohaly, A. M.; Null, Cynthia H. (Technical Monitor)

1995-01-01

In object detection, an observer looks for an object class member in a set of backgrounds. In discrimination, an observer tries to distinguish two images. Discrimination models predict the probability that an observer detects a difference between two images. We compare object detection and image discrimination with the same stimuli by: (1) making stimulus pairs of the same background with and without the target object and (2) either giving many consecutive trials with the same background (discrimination) or intermixing the stimuli (object detection). Six images of a vehicle in a natural setting were altered to remove the vehicle and mixed with the original image in various proportions. Detection observers rated the images for vehicle presence. Discrimination observers rated the images for any difference from the background image. Estimated detectabilities of the vehicles were found by maximizing the likelihood of a Thurstone category scaling model. The pattern of estimated detectabilities is similar for discrimination and object detection, and is accurately predicted by a Cortex Transform discrimination model. Predictions of a Contrast- Sensitivity- Function filter model and a Root-Mean-Square difference metric based on the digital image values are less accurate. The discrimination detectabilities averaged about twice those of object detection.

JUNO Photovoltaic Power at Jupiter

NASA Technical Reports Server (NTRS)

Dawson, Stephen F.; Stella, Paul; McAlpine, William; Smith, Brian

2012-01-01

This paper summarizes the Juno modeling team work on predicting the Juno solar array performance at critical mission points including Juno Orbit Insertion (JOI) and End of Mission (EOM). This report consists of background on Juno solar array design, a summary of power estimates, an explanation of the modeling approach used by Aerospace, a detailed discussion of loss factors and performance predictions, a thermal analysis, and a review of risks to solar array performance

Supervised variational model with statistical inference and its application in medical image segmentation.

PubMed

Li, Changyang; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Yin, Yong; Dagan Feng, David

2015-01-01

Automated and general medical image segmentation can be challenging because the foreground and the background may have complicated and overlapping density distributions in medical imaging. Conventional region-based level set algorithms often assume piecewise constant or piecewise smooth for segments, which are implausible for general medical image segmentation. Furthermore, low contrast and noise make identification of the boundaries between foreground and background difficult for edge-based level set algorithms. Thus, to address these problems, we suggest a supervised variational level set segmentation model to harness the statistical region energy functional with a weighted probability approximation. Our approach models the region density distributions by using the mixture-of-mixtures Gaussian model to better approximate real intensity distributions and distinguish statistical intensity differences between foreground and background. The region-based statistical model in our algorithm can intuitively provide better performance on noisy images. We constructed a weighted probability map on graphs to incorporate spatial indications from user input with a contextual constraint based on the minimization of contextual graphs energy functional. We measured the performance of our approach on ten noisy synthetic images and 58 medical datasets with heterogeneous intensities and ill-defined boundaries and compared our technique to the Chan-Vese region-based level set model, the geodesic active contour model with distance regularization, and the random walker model. Our method consistently achieved the highest Dice similarity coefficient when compared to the other methods.

Teacher Effects, Value-Added Models, and Accountability

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2014-01-01

Background: In the last decade, the effects of teachers on student performance (typically manifested as state-wide standardized tests) have been re-examined using statistical models that are known as value-added models. These statistical models aim to compute the unique contribution of the teachers in promoting student achievement gains from grade…

Chromatographic background drift correction coupled with parallel factor analysis to resolve coelution problems in three-dimensional chromatographic data: quantification of eleven antibiotics in tap water samples by high-performance liquid chromatography coupled with a diode array detector.

PubMed

Yu, Yong-Jie; Wu, Hai-Long; Fu, Hai-Yan; Zhao, Juan; Li, Yuan-Na; Li, Shu-Fang; Kang, Chao; Yu, Ru-Qin

2013-08-09

Chromatographic background drift correction has been an important field of research in chromatographic analysis. In the present work, orthogonal spectral space projection for background drift correction of three-dimensional chromatographic data was described in detail and combined with parallel factor analysis (PARAFAC) to resolve overlapped chromatographic peaks and obtain the second-order advantage. This strategy was verified by simulated chromatographic data and afforded significant improvement in quantitative results. Finally, this strategy was successfully utilized to quantify eleven antibiotics in tap water samples. Compared with the traditional methodology of introducing excessive factors for the PARAFAC model to eliminate the effect of background drift, clear improvement in the quantitative performance of PARAFAC was observed after background drift correction by orthogonal spectral space projection. Copyright © 2013 Elsevier B.V. All rights reserved.

Generalization of the normal-exponential model: exploration of a more accurate parametrisation for the signal distribution on Illumina BeadArrays.

PubMed

Plancade, Sandra; Rozenholc, Yves; Lund, Eiliv

2012-12-11

Illumina BeadArray technology includes non specific negative control features that allow a precise estimation of the background noise. As an alternative to the background subtraction proposed in BeadStudio which leads to an important loss of information by generating negative values, a background correction method modeling the observed intensities as the sum of the exponentially distributed signal and normally distributed noise has been developed. Nevertheless, Wang and Ye (2012) display a kernel-based estimator of the signal distribution on Illumina BeadArrays and suggest that a gamma distribution would represent a better modeling of the signal density. Hence, the normal-exponential modeling may not be appropriate for Illumina data and background corrections derived from this model may lead to wrong estimation. We propose a more flexible modeling based on a gamma distributed signal and a normal distributed background noise and develop the associated background correction, implemented in the R-package NormalGamma. Our model proves to be markedly more accurate to model Illumina BeadArrays: on the one hand, it is shown on two types of Illumina BeadChips that this model offers a more correct fit of the observed intensities. On the other hand, the comparison of the operating characteristics of several background correction procedures on spike-in and on normal-gamma simulated data shows high similarities, reinforcing the validation of the normal-gamma modeling. The performance of the background corrections based on the normal-gamma and normal-exponential models are compared on two dilution data sets, through testing procedures which represent various experimental designs. Surprisingly, we observe that the implementation of a more accurate parametrisation in the model-based background correction does not increase the sensitivity. These results may be explained by the operating characteristics of the estimators: the normal-gamma background correction offers an improvement in terms of bias, but at the cost of a loss in precision. This paper addresses the lack of fit of the usual normal-exponential model by proposing a more flexible parametrisation of the signal distribution as well as the associated background correction. This new model proves to be considerably more accurate for Illumina microarrays, but the improvement in terms of modeling does not lead to a higher sensitivity in differential analysis. Nevertheless, this realistic modeling makes way for future investigations, in particular to examine the characteristics of pre-processing strategies.

Infrared maritime target detection using a probabilistic single Gaussian model of sea clutter in Fourier domain

NASA Astrophysics Data System (ADS)

Zhou, Anran; Xie, Weixin; Pei, Jihong; Chen, Yapei

2018-02-01

For ship targets detection in cluttered infrared image sequences, a robust detection method, based on the probabilistic single Gaussian model of sea background in Fourier domain, is put forward. The amplitude spectrum sequences at each frequency point of the pure seawater images in Fourier domain, being more stable than the gray value sequences of each background pixel in the spatial domain, are regarded as a Gaussian model. Next, a probability weighted matrix is built based on the stability of the pure seawater's total energy spectrum in the row direction, to make the Gaussian model more accurate. Then, the foreground frequency points are separated from the background frequency points by the model. Finally, the false-alarm points are removed utilizing ships' shape features. The performance of the proposed method is tested by visual and quantitative comparisons with others.

Incorporating signal-dependent noise for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Morman, Christopher J.; Meola, Joseph

2015-05-01

The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.

Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals

NASA Technical Reports Server (NTRS)

Thompson, David R.; Mandrake, Lukas; Green, Robert O.

2013-01-01

Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.

Fingerprint Liveness Detection in the Presence of Capable Intruders.

PubMed

Sequeira, Ana F; Cardoso, Jaime S

2015-06-19

Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the use of a previously known material. This assumption has led to the use of supervised techniques to estimate the performance of the methods, using both live and spoof samples to train the predictive models and evaluate each type of fake samples individually. Additionally, the background was often included in the sample representation, completely distorting the decision process. Therefore, we propose that an automatic segmentation step should be performed to isolate the fingerprint from the background and truly decide on the liveness of the fingerprint and not on the characteristics of the background. Also, we argue that one cannot aim to model the fake samples completely since the material used by the intruder is unknown beforehand. We approach the design by modeling the distribution of the live samples and predicting as fake the samples very unlikely according to that model. Our experiments compare the performance of the supervised approaches with the semi-supervised ones that rely solely on the live samples. The results obtained differ from the ones obtained by the more standard approaches which reinforces our conviction that the results in the literature are misleadingly estimating the true vulnerability of the biometric system.

Fingerprint Liveness Detection in the Presence of Capable Intruders

PubMed Central

Sequeira, Ana F.; Cardoso, Jaime S.

2015-01-01

Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the use of a previously known material. This assumption has led to the use of supervised techniques to estimate the performance of the methods, using both live and spoof samples to train the predictive models and evaluate each type of fake samples individually. Additionally, the background was often included in the sample representation, completely distorting the decision process. Therefore, we propose that an automatic segmentation step should be performed to isolate the fingerprint from the background and truly decide on the liveness of the fingerprint and not on the characteristics of the background. Also, we argue that one cannot aim to model the fake samples completely since the material used by the intruder is unknown beforehand. We approach the design by modeling the distribution of the live samples and predicting as fake the samples very unlikely according to that model. Our experiments compare the performance of the supervised approaches with the semi-supervised ones that rely solely on the live samples. The results obtained differ from the ones obtained by the more standard approaches which reinforces our conviction that the results in the literature are misleadingly estimating the true vulnerability of the biometric system. PMID:26102491

A flexible framework for process-based hydraulic and water quality modeling of stormwater green infrastructure performance

EPA Science Inventory

Background Models that allow for design considerations of green infrastructure (GI) practices to control stormwater runoff and associated contaminants have received considerable attention in recent years. While popular, generally, the GI models are relatively simplistic. However,...

Modeling haplotype block variation using Markov chains.

PubMed

Greenspan, G; Geiger, D

2006-04-01

Models of background variation in genomic regions form the basis of linkage disequilibrium mapping methods. In this work we analyze a background model that groups SNPs into haplotype blocks and represents the dependencies between blocks by a Markov chain. We develop an error measure to compare the performance of this model against the common model that assumes that blocks are independent. By examining data from the International Haplotype Mapping project, we show how the Markov model over haplotype blocks is most accurate when representing blocks in strong linkage disequilibrium. This contrasts with the independent model, which is rendered less accurate by linkage disequilibrium. We provide a theoretical explanation for this surprising property of the Markov model and relate its behavior to allele diversity.

Modeling Haplotype Block Variation Using Markov Chains

PubMed Central

Greenspan, G.; Geiger, D.

2006-01-01

Models of background variation in genomic regions form the basis of linkage disequilibrium mapping methods. In this work we analyze a background model that groups SNPs into haplotype blocks and represents the dependencies between blocks by a Markov chain. We develop an error measure to compare the performance of this model against the common model that assumes that blocks are independent. By examining data from the International Haplotype Mapping project, we show how the Markov model over haplotype blocks is most accurate when representing blocks in strong linkage disequilibrium. This contrasts with the independent model, which is rendered less accurate by linkage disequilibrium. We provide a theoretical explanation for this surprising property of the Markov model and relate its behavior to allele diversity. PMID:16361244

FPGA implementation for real-time background subtraction based on Horprasert model.

PubMed

Rodriguez-Gomez, Rafael; Fernandez-Sanchez, Enrique J; Diaz, Javier; Ros, Eduardo

2012-01-01

Background subtraction is considered the first processing stage in video surveillance systems, and consists of determining objects in movement in a scene captured by a static camera. It is an intensive task with a high computational cost. This work proposes an embedded novel architecture on FPGA which is able to extract the background on resource-limited environments and offers low degradation (produced because of the hardware-friendly model modification). In addition, the original model is extended in order to detect shadows and improve the quality of the segmentation of the moving objects. We have analyzed the resource consumption and performance in Spartan3 Xilinx FPGAs and compared to others works available on the literature, showing that the current architecture is a good trade-off in terms of accuracy, performance and resources utilization. With less than a 65% of the resources utilization of a XC3SD3400 Spartan-3A low-cost family FPGA, the system achieves a frequency of 66.5 MHz reaching 32.8 fps with resolution 1,024 × 1,024 pixels, and an estimated power consumption of 5.76 W.

FPGA Implementation for Real-Time Background Subtraction Based on Horprasert Model

PubMed Central

Rodriguez-Gomez, Rafael; Fernandez-Sanchez, Enrique J.; Diaz, Javier; Ros, Eduardo

2012-01-01

Background subtraction is considered the first processing stage in video surveillance systems, and consists of determining objects in movement in a scene captured by a static camera. It is an intensive task with a high computational cost. This work proposes an embedded novel architecture on FPGA which is able to extract the background on resource-limited environments and offers low degradation (produced because of the hardware-friendly model modification). In addition, the original model is extended in order to detect shadows and improve the quality of the segmentation of the moving objects. We have analyzed the resource consumption and performance in Spartan3 Xilinx FPGAs and compared to others works available on the literature, showing that the current architecture is a good trade-off in terms of accuracy, performance and resources utilization. With less than a 65% of the resources utilization of a XC3SD3400 Spartan-3A low-cost family FPGA, the system achieves a frequency of 66.5 MHz reaching 32.8 fps with resolution 1,024 × 1,024 pixels, and an estimated power consumption of 5.76 W. PMID:22368487

Dynamics, Heat Transport, Spectral Composition and Acoustic Signatures of Mesoscale Variability in the Ocean

DTIC Science & Technology

2013-12-01

Eastward background flow EOS Equation of state GDEM Generalized Digital Environmental Model GRB Growth Rate Balance model HPCMP High Performance...the Naval Research Lab (NRL) Generalized Digital Environmental Model ( GDEM ). This provides a realistic and detailed profile for a known turbulent

Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

PubMed

Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

2014-02-01

The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

Aircraft vulnerability analysis by modeling and simulation

NASA Astrophysics Data System (ADS)

Willers, Cornelius J.; Willers, Maria S.; de Waal, Alta

2014-10-01

Infrared missiles pose a significant threat to civilian and military aviation. ManPADS missiles are especially dangerous in the hands of rogue and undisciplined forces. Yet, not all the launched missiles hit their targets; the miss being either attributable to misuse of the weapon or to missile performance restrictions. This paper analyses some of the factors affecting aircraft vulnerability and demonstrates a structured analysis of the risk and aircraft vulnerability problem. The aircraft-missile engagement is a complex series of events, many of which are only partially understood. Aircraft and missile designers focus on the optimal design and performance of their respective systems, often testing only in a limited set of scenarios. Most missiles react to the contrast intensity, but the variability of the background is rarely considered. Finally, the vulnerability of the aircraft depends jointly on the missile's performance and the doctrine governing the missile's launch. These factors are considered in a holistic investigation. The view direction, altitude, time of day, sun position, latitude/longitude and terrain determine the background against which the aircraft is observed. Especially high gradients in sky radiance occur around the sun and on the horizon. This paper considers uncluttered background scenes (uniform terrain and clear sky) and presents examples of background radiance at all view angles across a sphere around the sensor. A detailed geometrical and spatially distributed radiometric model is used to model the aircraft. This model provides the signature at all possible view angles across the sphere around the aircraft. The signature is determined in absolute terms (no background) and in contrast terms (with background). It is shown that the background significantly affects the contrast signature as observed by the missile sensor. A simplified missile model is constructed by defining the thrust and mass profiles, maximum seeker tracking rate, maximum guidance acceleration and seeker sensitivity. For the purpose of this investigation the aircraft is equipped with conventional pyrotechnic decoy flares and the missile has no counter-countermeasure means (security restrictions on open publication). This complete simulation is used to calculate the missile miss distance, when the missile is launched from different locations around the aircraft. The miss distance data is then graphically presented showing miss distance (aircraft vulnerability) as a function of launch direction and range. The aircraft vulnerability graph accounts for aircraft and missile characteristics, but does not account for missile deployment doctrine. A Bayesian network is constructed to fuse the doctrinal rules with the aircraft vulnerability data. The Bayesian network now provides the capability to evaluate the combined risk of missile launch and aircraft vulnerability. It is shown in this paper that it is indeed possible to predict the aircraft vulnerability to missile attack in a comprehensive modelling and a holistic process. By using the appropriate real-world models, this approach is used to evaluate the effectiveness of specific countermeasure techniques against specific missile threats. The use of a Bayesian network provides the means to fuse simulated performance data with more abstract doctrinal rules to provide a realistic assessment of the aircraft vulnerability.

Adaptive nonlinear control for autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Black, William S.

We present the background and motivation for ground vehicle autonomy, and focus on uses for space-exploration. Using a simple design example of an autonomous ground vehicle we derive the equations of motion. After providing the mathematical background for nonlinear systems and control we present two common methods for exactly linearizing nonlinear systems, feedback linearization and backstepping. We use these in combination with three adaptive control methods: model reference adaptive control, adaptive sliding mode control, and extremum-seeking model reference adaptive control. We show the performances of each combination through several simulation results. We then consider disturbances in the system, and design nonlinear disturbance observers for both single-input-single-output and multi-input-multi-output systems. Finally, we show the performance of these observers with simulation results.

Exploring the Black Box: An Analysis of Work Group Diversity, Conflict, and Performance.

ERIC Educational Resources Information Center

Pelled, Lisa Hope; Eisenhardt, Kathleen M.; Xin, Katherine R.

1999-01-01

Tests an integrative model of the relationships among diversity, conflict, and performance, using a sample of 45 electronics-industry worker teams. Functional background diversity drives task conflict; multiple types of diversity drive emotional conflict. Task conflict affects task performance more favorably than does emotional conflict. (102…

Use of model calibration to achieve high accuracy in analysis of computer networks

DOEpatents

Frogner, Bjorn; Guarro, Sergio; Scharf, Guy

2004-05-11

A system and method are provided for creating a network performance prediction model, and calibrating the prediction model, through application of network load statistical analyses. The method includes characterizing the measured load on the network, which may include background load data obtained over time, and may further include directed load data representative of a transaction-level event. Probabilistic representations of load data are derived to characterize the statistical persistence of the network performance variability and to determine delays throughout the network. The probabilistic representations are applied to the network performance prediction model to adapt the model for accurate prediction of network performance. Certain embodiments of the method and system may be used for analysis of the performance of a distributed application characterized as data packet streams.

Target detection using the background model from the topological anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Dorado Munoz, Leidy P.; Messinger, David W.; Ziemann, Amanda K.

2013-05-01

The Topological Anomaly Detection (TAD) algorithm has been used as an anomaly detector in hyperspectral and multispectral images. TAD is an algorithm based on graph theory that constructs a topological model of the background in a scene, and computes an anomalousness ranking for all of the pixels in the image with respect to the background in order to identify pixels with uncommon or strange spectral signatures. The pixels that are modeled as background are clustered into groups or connected components, which could be representative of spectral signatures of materials present in the background. Therefore, the idea of using the background components given by TAD in target detection is explored in this paper. In this way, these connected components are characterized in three different approaches, where the mean signature and endmembers for each component are calculated and used as background basis vectors in Orthogonal Subspace Projection (OSP) and Adaptive Subspace Detector (ASD). Likewise, the covariance matrix of those connected components is estimated and used in detectors: Constrained Energy Minimization (CEM) and Adaptive Coherence Estimator (ACE). The performance of these approaches and the different detectors is compared with a global approach, where the background characterization is derived directly from the image. Experiments and results using self-test data set provided as part of the RIT blind test target detection project are shown.

Effect of Background Pressure on the Plasma Oscillation Characteristics of the HiVHAc Hall Thruster

NASA Technical Reports Server (NTRS)

Huang, Wensheng; Kamhawi, Hani; Lobbia, Robert B.; Brown, Daniel L.

2014-01-01

During a component compatibility test of the NASA HiVHAc Hall thruster, a high-speed camera and a set of high-speed Langmuir probes were implemented to study the effect of varying facility background pressure on thruster operation. The results show a rise in the oscillation frequency of the breathing mode with rising background pressure, which is hypothesized to be due to a shortening accelerationionization zone. An attempt is made to apply a simplified ingestion model to the data. The combined results are used to estimate the maximum acceptable background pressure for performance and wear testing.

Chandra ACIS-I particle background: an analytical model

NASA Astrophysics Data System (ADS)

Bartalucci, I.; Mazzotta, P.; Bourdin, H.; Vikhlinin, A.

2014-06-01

Aims: Imaging and spectroscopy of X-ray extended sources require a proper characterisation of a spatially unresolved background signal. This background includes sky and instrumental components, each of which are characterised by its proper spatial and spectral behaviour. While the X-ray sky background has been extensively studied in previous work, here we analyse and model the instrumental background of the ACIS-I detector on board the Chandra X-ray observatory in very faint mode. Methods: Caused by interaction of highly energetic particles with the detector, the ACIS-I instrumental background is spectrally characterised by the superimposition of several fluorescence emission lines onto a continuum. To isolate its flux from any sky component, we fitted an analytical model of the continuum to observations performed in very faint mode with the detector in the stowed position shielded from the sky, and gathered over the eight-year period starting in 2001. The remaining emission lines were fitted to blank-sky observations of the same period. We found 11 emission lines. Analysing the spatial variation of the amplitude, energy and width of these lines has further allowed us to infer that three lines of these are presumably due to an energy correction artefact produced in the frame store. Results: We provide an analytical model that predicts the instrumental background with a precision of 2% in the continuum and 5% in the lines. We use this model to measure the flux of the unresolved cosmic X-ray background in the Chandra deep field south. We obtain a flux of 10.2+0.5-0.4 × 10-13 erg cm-2 deg-2 s-1 for the [1-2] keV band and (3.8 ± 0.2) × 10-12 erg cm-2 deg-2 s-1 for the [2-8] keV band.

Cultural models of self and social class disparities at organizational gateways and pathways.

PubMed

Townsend, Sarah Sm; Truong, Mindy

2017-12-01

Attaining a college degree has traditionally been assumed to be key to upward social and professional mobility. However, college graduates from working-class backgrounds achieve less career success in professional, white-collar workplaces compared to those from middle-class backgrounds. Using a cultural models approach, we examine how the independent cultural beliefs and practices promoted by professional organizations disadvantage people from working-class backgrounds, who espouse interdependent beliefs and practices. Our review illustrates how this disadvantage can manifest in two ways. First, despite relative equality in objective qualifications, it can occur at organizational gateways (e.g., interview and hiring decisions). Second, even after people from working-class backgrounds gain access to an organization, it can occur along organizational pathways (e.g., performance evaluations and assignment to high-profile tasks). Copyright © 2017. Published by Elsevier Ltd.

Wavelet analysis techniques applied to removing varying spectroscopic background in calibration model for pear sugar content

NASA Astrophysics Data System (ADS)

Liu, Yande; Ying, Yibin; Lu, Huishan; Fu, Xiaping

2005-11-01

A new method is proposed to eliminate the varying background and noise simultaneously for multivariate calibration of Fourier transform near infrared (FT-NIR) spectral signals. An ideal spectrum signal prototype was constructed based on the FT-NIR spectrum of fruit sugar content measurement. The performances of wavelet based threshold de-noising approaches via different combinations of wavelet base functions were compared. Three families of wavelet base function (Daubechies, Symlets and Coiflets) were applied to estimate the performance of those wavelet bases and threshold selection rules by a series of experiments. The experimental results show that the best de-noising performance is reached via the combinations of Daubechies 4 or Symlet 4 wavelet base function. Based on the optimization parameter, wavelet regression models for sugar content of pear were also developed and result in a smaller prediction error than a traditional Partial Least Squares Regression (PLSR) mode.

Estimating background-subtracted fluorescence transients in calcium imaging experiments: a quantitative approach.

PubMed

Joucla, Sébastien; Franconville, Romain; Pippow, Andreas; Kloppenburg, Peter; Pouzat, Christophe

2013-08-01

Calcium imaging has become a routine technique in neuroscience for subcellular to network level investigations. The fast progresses in the development of new indicators and imaging techniques call for dedicated reliable analysis methods. In particular, efficient and quantitative background fluorescence subtraction routines would be beneficial to most of the calcium imaging research field. A background-subtracted fluorescence transients estimation method that does not require any independent background measurement is therefore developed. This method is based on a fluorescence model fitted to single-trial data using a classical nonlinear regression approach. The model includes an appropriate probabilistic description of the acquisition system's noise leading to accurate confidence intervals on all quantities of interest (background fluorescence, normalized background-subtracted fluorescence time course) when background fluorescence is homogeneous. An automatic procedure detecting background inhomogeneities inside the region of interest is also developed and is shown to be efficient on simulated data. The implementation and performances of the proposed method on experimental recordings from the mouse hypothalamus are presented in details. This method, which applies to both single-cell and bulk-stained tissues recordings, should help improving the statistical comparison of fluorescence calcium signals between experiments and studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Parametric models to relate spike train and LFP dynamics with neural information processing.

PubMed

Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

2012-01-01

Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial-by-trial behavioral performance than existing models of neural information processing. Our results highlight the utility of the unified modeling framework for characterizing spike-LFP recordings obtained during behavioral performance.

Robust foreground detection: a fusion of masked grey world, probabilistic gradient information and extended conditional random field approach.

PubMed

Zulkifley, Mohd Asyraf; Moran, Bill; Rawlinson, David

2012-01-01

Foreground detection has been used extensively in many applications such as people counting, traffic monitoring and face recognition. However, most of the existing detectors can only work under limited conditions. This happens because of the inability of the detector to distinguish foreground and background pixels, especially in complex situations. Our aim is to improve the robustness of foreground detection under sudden and gradual illumination change, colour similarity issue, moving background and shadow noise. Since it is hard to achieve robustness using a single model, we have combined several methods into an integrated system. The masked grey world algorithm is introduced to handle sudden illumination change. Colour co-occurrence modelling is then fused with the probabilistic edge-based background modelling. Colour co-occurrence modelling is good in filtering moving background and robust to gradual illumination change, while an edge-based modelling is used for solving a colour similarity problem. Finally, an extended conditional random field approach is used to filter out shadow and afterimage noise. Simulation results show that our algorithm performs better compared to the existing methods, which makes it suitable for higher-level applications.

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

Akerib, DS; Alsum, S; Araújo, HM

The LUX experiment has performed searches for dark matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived frommore » $${1.4}\\times 10^{4}\\;\\mathrm{kg\\,days}$$ of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.« less

Calibration, event reconstruction, data analysis, and limit calculation for the LUX dark matter experiment

NASA Astrophysics Data System (ADS)

Akerib, D. S.; Alsum, S.; Araújo, H. M.; Bai, X.; Bailey, A. J.; Balajthy, J.; Beltrame, P.; Bernard, E. P.; Bernstein, A.; Biesiadzinski, T. P.; Boulton, E. M.; Brás, P.; Byram, D.; Cahn, S. B.; Carmona-Benitez, M. C.; Chan, C.; Currie, A.; Cutter, J. E.; Davison, T. J. R.; Dobi, A.; Dobson, J. E. Y.; Druszkiewicz, E.; Edwards, B. N.; Faham, C. H.; Fallon, S. R.; Fan, A.; Fiorucci, S.; Gaitskell, R. J.; Gehman, V. M.; Genovesi, J.; Ghag, C.; Gilchriese, M. G. D.; Hall, C. R.; Hanhardt, M.; Haselschwardt, S. J.; Hertel, S. A.; Hogan, D. P.; Horn, M.; Huang, D. Q.; Ignarra, C. M.; Jacobsen, R. G.; Ji, W.; Kamdin, K.; Kazkaz, K.; Khaitan, D.; Knoche, R.; Larsen, N. A.; Lee, C.; Lenardo, B. G.; Lesko, K. T.; Lindote, A.; Lopes, M. I.; Manalaysay, A.; Mannino, R. L.; Marzioni, M. F.; McKinsey, D. N.; Mei, D.-M.; Mock, J.; Moongweluwan, M.; Morad, J. A.; Murphy, A. St. J.; Nehrkorn, C.; Nelson, H. N.; Neves, F.; O'Sullivan, K.; Oliver-Mallory, K. C.; Palladino, K. J.; Pease, E. K.; Reichhart, L.; Rhyne, C.; Shaw, S.; Shutt, T. A.; Silva, C.; Solmaz, M.; Solovov, V. N.; Sorensen, P.; Sumner, T. J.; Szydagis, M.; Taylor, D. J.; Taylor, W. C.; Tennyson, B. P.; Terman, P. A.; Tiedt, D. R.; To, W. H.; Tripathi, M.; Tvrznikova, L.; Uvarov, S.; Velan, V.; Verbus, J. R.; Webb, R. C.; White, J. T.; Whitis, T. J.; Witherell, M. S.; Wolfs, F. L. H.; Xu, J.; Yazdani, K.; Young, S. K.; Zhang, C.; LUX Collaboration

2018-05-01

The LUX experiment has performed searches for dark-matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived from 1.4 ×104 kg days of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.

Investigation of micromixing by acoustically oscillated sharp-edges

PubMed Central

Nama, Nitesh; Huang, Po-Hsun; Huang, Tony Jun; Costanzo, Francesco

2016-01-01

Recently, acoustically oscillated sharp-edges have been utilized to achieve rapid and homogeneous mixing in microchannels. Here, we present a numerical model to investigate acoustic mixing inside a sharp-edge-based micromixer in the presence of a background flow. We extend our previously reported numerical model to include the mixing phenomena by using perturbation analysis and the Generalized Lagrangian Mean (GLM) theory in conjunction with the convection-diffusion equation. We divide the flow variables into zeroth-order, first-order, and second-order variables. This results in three sets of equations representing the background flow, acoustic response, and the time-averaged streaming flow, respectively. These equations are then solved successively to obtain the mean Lagrangian velocity which is combined with the convection-diffusion equation to predict the concentration profile. We validate our numerical model via a comparison of the numerical results with the experimentally obtained values of the mixing index for different flow rates. Further, we employ our model to study the effect of the applied input power and the background flow on the mixing performance of the sharp-edge-based micromixer. We also suggest potential design changes to the previously reported sharp-edge-based micromixer to improve its performance. Finally, we investigate the generation of a tunable concentration gradient by a linear arrangement of the sharp-edge structures inside the microchannel. PMID:27158292

Investigation of micromixing by acoustically oscillated sharp-edges.

PubMed

Nama, Nitesh; Huang, Po-Hsun; Huang, Tony Jun; Costanzo, Francesco

2016-03-01

Recently, acoustically oscillated sharp-edges have been utilized to achieve rapid and homogeneous mixing in microchannels. Here, we present a numerical model to investigate acoustic mixing inside a sharp-edge-based micromixer in the presence of a background flow. We extend our previously reported numerical model to include the mixing phenomena by using perturbation analysis and the Generalized Lagrangian Mean (GLM) theory in conjunction with the convection-diffusion equation. We divide the flow variables into zeroth-order, first-order, and second-order variables. This results in three sets of equations representing the background flow, acoustic response, and the time-averaged streaming flow, respectively. These equations are then solved successively to obtain the mean Lagrangian velocity which is combined with the convection-diffusion equation to predict the concentration profile. We validate our numerical model via a comparison of the numerical results with the experimentally obtained values of the mixing index for different flow rates. Further, we employ our model to study the effect of the applied input power and the background flow on the mixing performance of the sharp-edge-based micromixer. We also suggest potential design changes to the previously reported sharp-edge-based micromixer to improve its performance. Finally, we investigate the generation of a tunable concentration gradient by a linear arrangement of the sharp-edge structures inside the microchannel.

Spatiotemporal models for the simulation of infrared backgrounds

NASA Astrophysics Data System (ADS)

Wilkes, Don M.; Cadzow, James A.; Peters, R. Alan, II; Li, Xingkang

1992-09-01

It is highly desirable for designers of automatic target recognizers (ATRs) to be able to test their algorithms on targets superimposed on a wide variety of background imagery. Background imagery in the infrared spectrum is expensive to gather from real sources, consequently, there is a need for accurate models for producing synthetic IR background imagery. We have developed a model for such imagery that will do the following: Given a real, infrared background image, generate another image, distinctly different from the one given, that has the same general visual characteristics as well as the first and second-order statistics of the original image. The proposed model consists of a finite impulse response (FIR) kernel convolved with an excitation function, and histogram modification applied to the final solution. A procedure for deriving the FIR kernel using a signal enhancement algorithm has been developed, and the histogram modification step is a simple memoryless nonlinear mapping that imposes the first order statistics of the original image onto the synthetic one, thus the overall model is a linear system cascaded with a memoryless nonlinearity. It has been found that the excitation function relates to the placement of features in the image, the FIR kernel controls the sharpness of the edges and the global spectrum of the image, and the histogram controls the basic coloration of the image. A drawback to this method of simulating IR backgrounds is that a database of actual background images must be collected in order to produce accurate FIR and histogram models. If this database must include images of all types of backgrounds obtained at all times of the day and all times of the year, the size of the database would be prohibitive. In this paper we propose improvements to the model described above that enable time-dependent modeling of the IR background. This approach can greatly reduce the number of actual IR backgrounds that are required to produce a sufficiently accurate mathematical model for synthesizing a similar IR background for different times of the day. Original and synthetic IR backgrounds will be presented. Previous research in simulating IR backgrounds was performed by Strenzwilk, et al., Botkin, et al., and Rapp. The most recent work of Strenzwilk, et al. was based on the use of one-dimensional ARMA models for synthesizing the images. Their results were able to retain the global statistical and spectral behavior of the original image, but the synthetic image was not visually very similar to the original. The research presented in this paper is the result of an attempt to improve upon their results, and represents a significant improvement in quality over previously obtained results.

Man-Machine Communication in Remote Manipulation: Task-Oriented Supervisory Command Language (TOSC).

DTIC Science & Technology

1980-03-01

ORIENTED SUPERVISORY CONTROL SYSTEM METHODOLOGY 3-1 3.1 Overview 3-1 3.2 Background 3-3 3.2.1 General 3-3 3.2.2 Preliminary Principles of Command Language...Design 3-4 3.2.3 Preliminary Principles of Feedback Display Design 3-9 3.3 Man-Machine Communication Models 3-12 3.3.1 Background 3-12 3.3.2 Adapted...and feedback mode. The work ends with the presentation of a performance prediction model and a set of principles and guidelines, applicable to the

Issues and progress in determining background ozone and particle concentrations

NASA Astrophysics Data System (ADS)

Pinto, J. P.

2011-12-01

Exposure to ambient ozone is associated with a variety of health outcomes ranging from mild breathing discomfort to mortality. For the purpose of health risk and policy assessments EPA evaluates the anthropogenic increase in ozone above background concentrations and has defined the North American (NA) background concentration of O3 as that which would occur in the U.S. in the absence of anthropogenic emissions of precursors in the U.S., Canada, and Mexico. Monthly average NA background ozone has been used to evaluate health risks, but EPA and state air quality managers must also estimate day specific ozone background levels for high ozone episodes as part of urban scale photochemical modeling efforts to support ozone regulatory programs. The background concentration of O3 is of more concern than other air pollutants because it typically represents a much larger fraction of observed O3 than do the backgrounds of other criteria pollutants (particulate matter (PM), CO, NO2, SO2). NA background cannot be determined directly from ambient monitoring data because of the influence of NA precursor emissions on formation of ozone within NA. Instead, estimates of NA background O3 have been based on GEOS-Chem using simulations in which NA anthropogenic precursor emissions are zeroed out. Thus, modeled NA background O3 includes contributions from natural sources of precursors (including CH4, NMVOCs, NOx, and CO) everywhere in the world, anthropogenic sources of precursors outside of NA, and downward transport of O3 from the stratosphere. Although monitoring data cannot determine NA background directly, measurements by satellites, aircraft, ozonesondes and surface monitors have proved to be highly useful for identifying sources of background O3 and for evaluating the performance of the GEOS-Chem model. Model simulated NA background concentrations are strong functions of location and season with large inter-day variability and with values increasing with elevation and higher in spring than in summer, and tend to be highest in the Intermountain West during spring. Estimates of annual average NA and other background definitions that have been considered will be presented. Issues associated with modeling background concentrations for both health-risk assessments and for episodic regulatory air quality programs will be discussed, and proposals for new atmospheric measurements and model improvements needed to quantify more accurately background contributions to ozone will also be presented. The views expressed are those of the author and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

Cuckoos vs. top predators as prime bioindicators of biodiversity in disturbed environments.

PubMed

Morelli, Federico; Mousseau, Timothy A; Møller, Anders Pape

2017-10-01

We studied the abundance of the common cuckoo Cuculus canorus L. little cuckoo Cuculus poliocephalus L. and Asian cuckoo Cuculus saturatus L. and avian top predators as indicators of bird species richness (surrogate of biodiversity) in disturbed environments caused by radioactive contamination in Chernobyl, Ukraine and Fukushima, Japan, comparing their efficiency as indicators of local biodiversity hotspots. Bird species richness and birds abundance were quantified in each sample site during the breeding seasons between 2006 and 2015 and the level of background radiation was measured at every site. The correlation between number of cuckoos, top predators, land use composition and level of background radiation with bird species richness as response variable were examined using Generalized Linear Mixed Models. The strength of correlation between species richness and abundance and the covariates obtained from the model outputs were used as measure of the efficiency of each predictor, as well as the AIC of each model. Background radiation was negatively correlated with bird species richness and bird abundance in both countries, while number of top predators and cuckoos were both positively correlated with bird species richness and abundance. However, model with number of cuckoos was more performant than model with number of avian top predators. These differences in performance supports the hypothesis that cuckoos are a largely superior bioindicator than top predators. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evolution of cosmic string networks

NASA Technical Reports Server (NTRS)

Albrecht, Andreas; Turok, Neil

1989-01-01

A discussion of the evolution and observable consequences of a network of cosmic strings is given. A simple model for the evolution of the string network is presented, and related to the statistical mechanics of string networks. The model predicts the long string density throughout the history of the universe from a single parameter, which researchers calculate in radiation era simulations. The statistical mechanics arguments indicate a particular thermal form for the spectrum of loops chopped off the network. Detailed numerical simulations of string networks in expanding backgrounds are performed to test the model. Consequences for large scale structure, the microwave and gravity wave backgrounds, nucleosynthesis and gravitational lensing are calculated.

Analysis for signal-to-noise ratio of hyper-spectral imaging FTIR interferometer

NASA Astrophysics Data System (ADS)

Li, Xun-niu; Zheng, Wei-jian; Lei, Zheng-gang; Wang, Hai-yang; Fu, Yan-peng

2013-08-01

Signal-to-noise Ratio of hyper-spectral imaging FTIR interferometer system plays a decisive role on the performance of the instrument. It is necessary to analyze them in the development process. Based on the simplified target/background model, the energy transfer model of the LWIR hyper-spectral imaging interferometer has been discussed. The noise equivalent spectral radiance (NESR) and its influencing factors of the interferometer system was analyzed, and the signal-to-noise（SNR） was calculated by using the properties of NESR and incident radiance. In a typical application environment, using standard atmospheric model of USA(1976 COESA) as a background, and set a reasonable target/background temperature difference, and take Michelson spatial modulation Fourier Transform interferometer as an example, the paper had calculated the NESR and the SNR of the interferometer system which using the commercially LWIR cooled FPA and UFPA detector. The system noise sources of the instrument were also analyzed in the paper. The results of those analyses can be used to optimize and pre-estimate the performance of the interferometer system, and analysis the applicable conditions of use different detectors. It has important guiding significance for the LWIR interferometer spectrometer design.

Modelling difficulties in abstract thinking in psychosis: the importance of socio-developmental background.

PubMed

Berg, A O; Melle, I; Zuber, V; Simonsen, C; Nerhus, M; Ueland, T; Andreassen, O A; Sundet, K; Vaskinn, A

2017-01-01

Abstract thinking is important in modern understanding of neurocognitive abilities, and a symptom of thought disorder in psychosis. In patients with psychosis, we assessed if socio-developmental background influences abstract thinking, and the association with executive functioning and clinical psychosis symptoms. Participants (n = 174) had a diagnosis of psychotic or bipolar disorder, were 17-65 years, intelligence quotient (IQ) > 70, fluent in a Scandinavian language, and their full primary education in Norway. Immigrants (N = 58) were matched (1:2) with participants without a history of migration (N = 116). All participants completed a neurocognitive and clinical assessment. Socio-developmental background was operationalised as human developmental index (HDI) of country of birth, at year of birth. Structural equation modelling was used to assess the model with best fit. The model with best fit, χ 2  = 96.591, df = 33, p < .001, confirmed a significant indirect effect of HDI scores on abstract thinking through executive functioning, but not through clinical psychosis symptoms. This study found that socio-developmental background influences abstract thinking in psychosis by indirect effect through executive functioning. We should take into account socio-developmental background in the interpretation of neurocognitive performance in patients with psychosis, and prioritise cognitive remediation in treatment of immigrant patients.

Slowing of Femtosecond Laser-Generated Nanoparticles in a Background Gas

DOE PAGES

Rouleau, Christopher M.; Puretzky, Alexander A.; Geohegan, David B.

2014-11-25

The slowing of Pt nanoparticles in argon background gas was characterized by Rayleigh scattering imaging using a plume of nanoparticles generated by femtosecond laser through thin film ablation (fs-TTFA) of 20 nanometers-thick Pt films. The ablation was performed at threshold laser energy fluences for complete film removal to provide a well-defined plume consisting almost entirely of nanoparticles traveling with a narrow velocity distribution, providing a unique system to unambiguously characterize the slowing of nanoparticles during interaction with background gases. Nanoparticles of ~200 nm diameter were found to decelerate in background Ar gas with pressures less than 50 Torr in goodmore » agreement with a linear drag model in the Epstein regime. Based on this model, the stopping distance of small nanoparticles in the plume was predicted and tested by particle collection in an off-axis geometry, and size distribution analysis by transmission electron microscopy. These results permit a basis to interpret nanoparticle propagation through background gases in laser ablation plumes that contain mixed components.« less

Modeling the performance of direct-detection Doppler lidar systems including cloud and solar background variability.

PubMed

McGill, M J; Hart, W D; McKay, J A; Spinhirne, J D

1999-10-20

Previous modeling of the performance of spaceborne direct-detection Doppler lidar systems assumed extremely idealized atmospheric models. Here we develop a technique for modeling the performance of these systems in a more realistic atmosphere, based on actual airborne lidar observations. The resulting atmospheric model contains cloud and aerosol variability that is absent in other simulations of spaceborne Doppler lidar instruments. To produce a realistic simulation of daytime performance, we include solar radiance values that are based on actual measurements and are allowed to vary as the viewing scene changes. Simulations are performed for two types of direct-detection Doppler lidar system: the double-edge and the multichannel techniques. Both systems were optimized to measure winds from Rayleigh backscatter at 355 nm. Simulations show that the measurement uncertainty during daytime is degraded by only approximately 10-20% compared with nighttime performance, provided that a proper solar filter is included in the instrument design.

Task-based lens design with application to digital mammography

NASA Astrophysics Data System (ADS)

Chen, Liying; Barrett, Harrison H.

2005-01-01

Recent advances in model observers that predict human perceptual performance now make it possible to optimize medical imaging systems for human task performance. We illustrate the procedure by considering the design of a lens for use in an optically coupled digital mammography system. The channelized Hotelling observer is used to model human performance, and the channels chosen are differences of Gaussians. The task performed by the model observer is detection of a lesion at a random but known location in a clustered lumpy background mimicking breast tissue. The entire system is simulated with a Monte Carlo application according to physics principles, and the main system component under study is the imaging lens that couples a fluorescent screen to a CCD detector. The signal-to-noise ratio (SNR) of the channelized Hotelling observer is used to quantify this detectability of the simulated lesion (signal) on the simulated mammographic background. Plots of channelized Hotelling SNR versus signal location for various lens apertures, various working distances, and various focusing places are presented. These plots thus illustrate the trade-off between coupling efficiency and blur in a task-based manner. In this way, the channelized Hotelling SNR is used as a merit function for lens design.

Task-based lens design, with application to digital mammography

NASA Astrophysics Data System (ADS)

Chen, Liying

Recent advances in model observers that predict human perceptual performance now make it possible to optimize medical imaging systems for human task performance. We illustrate the procedure by considering the design of a lens for use in an optically coupled digital mammography system. The channelized Hotelling observer is used to model human performance, and the channels chosen are differences of Gaussians (DOGs). The task performed by the model observer is detection of a lesion at a random but known location in a clustered lumpy background mimicking breast tissue. The entire system is simulated with a Monte Carlo application according to the physics principles, and the main system component under study is the imaging lens that couples a fluorescent screen to a CCD detector. The SNR of the channelized Hotelling observer is used to quantify the detectability of the simulated lesion (signal) upon the simulated mammographic background. In this work, plots of channelized Hotelling SNR vs. signal location for various lens apertures, various working distances, and various focusing places are shown. These plots thus illustrate the trade-off between coupling efficiency and blur in a task-based manner. In this way, the channelized Hotelling SNR is used as a merit function for lens design.

Grating scattering BRDF and imaging performances: A test survey performed in the frame of the flex mission

NASA Astrophysics Data System (ADS)

Harnisch, Bernd; Deep, Atul; Vink, Ramon; Coatantiec, Claude

2017-11-01

Key components in optical spectrometers are the gratings. Their influence on the overall infield straylight of the spectrometer depends not only on the technology used for grating fabrication but also on the potential existence of ghost images caused by irregularities of the grating constant. For the straylight analysis of spectrometer no general Bidirectional Reflectance Distribution Function (BRDF) model of gratings exist, as it does for optically smooth surfaces. These models are needed for the determination of spectrometer straylight background and for the calculation of spectrometer out of band rejection performances. Within the frame of the Fluorescence Earth Explorer mission (FLEX), gratings manufactured using different technologies have been investigated in terms of straylight background and imaging performance in the used diffraction order. The gratings which have been investigated cover a lithographically written grating, a volume Bragg grating, two holographic gratings and an off-the-shelf ruled grating. In this paper we present a survey of the measured bidirectional reflectance/transmittance distribution function and the determination of an equivalent surface micro-roughness of the gratings, describing the scattering of the grating around the diffraction order. This is specifically needed for the straylight modeling of the spectrometer.

Technical Manual for the SAM Physical Trough Model

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

Wagner, M. J.; Gilman, P.

2011-06-01

NREL, in conjunction with Sandia National Lab and the U.S Department of Energy, developed the System Advisor Model (SAM) analysis tool for renewable energy system performance and economic analysis. This paper documents the technical background and engineering formulation for one of SAM's two parabolic trough system models in SAM. The Physical Trough model calculates performance relationships based on physical first principles where possible, allowing the modeler to predict electricity production for a wider range of component geometries than is possible in the Empirical Trough model. This document describes the major parabolic trough plant subsystems in detail including the solar field,more » power block, thermal storage, piping, auxiliary heating, and control systems. This model makes use of both existing subsystem performance modeling approaches, and new approaches developed specifically for SAM.« less

Accurate object tracking system by integrating texture and depth cues

NASA Astrophysics Data System (ADS)

Chen, Ju-Chin; Lin, Yu-Hang

2016-03-01

A robust object tracking system that is invariant to object appearance variations and background clutter is proposed. Multiple instance learning with a boosting algorithm is applied to select discriminant texture information between the object and background data. Additionally, depth information, which is important to distinguish the object from a complicated background, is integrated. We propose two depth-based models that can compensate texture information to cope with both appearance variants and background clutter. Moreover, in order to reduce the risk of drifting problem increased for the textureless depth templates, an update mechanism is proposed to select more precise tracking results to avoid incorrect model updates. In the experiments, the robustness of the proposed system is evaluated and quantitative results are provided for performance analysis. Experimental results show that the proposed system can provide the best success rate and has more accurate tracking results than other well-known algorithms.

Putting Growth and Value-Added Models on the Map: A National Overview

ERIC Educational Resources Information Center

Collins, Clarin; Amrein-Beardsley, Audrey

2014-01-01

Background: Within the last few years, the focus on educational accountability has shifted from holding students responsible for their own performance to holding those shown to impact student performance responsible--students' teachers. Encouraged and financially incentivized by federal programs, states are becoming ever more reliant on…

Interactions of Task and Subject Variables among Continuous Performance Tests

ERIC Educational Resources Information Center

Denney, Colin B.; Rapport, Mark D.; Chung, Kyong-Mee

2005-01-01

Background: Contemporary models of working memory suggest that target paradigm (TP) and target density (TD) should interact as influences on error rates derived from continuous performance tests (CPTs). The present study evaluated this hypothesis empirically in a typically developing, ethnically diverse sample of children. The extent to which…

Variability and Spectral Studies of Luminous Seyfert 1 Galaxy Fairall 9. Search for the Reflection Component is a Quasar: RXTE and ASCA Observation of a Nearby Radio-Quiet Quasar MR 2251-178

NASA Technical Reports Server (NTRS)

Leighly, Karen M.

1999-01-01

Monitoring observations with interval of 3 days using RXTE (X Ray Timing Explorer) of the luminous Seyfert 1 galaxy Fairall 9 were performed for one year. The purpose of the observations were to study the variability of Fairall 9 and compare the results with those from the radio-loud object 3C 390.3. The data has been received and analysis is underway, using the new background model. An observation of the quasar MR 2251-178 was made in order to determine whether or not it has a reflection component. Older background models gave an unacceptable subtraction and analysis is underway using the new background model. The observation of NGC 6300 showed that the X-ray spectrum from this Seyfert 2 galaxy appears to be dominated by Compton reflection.

Evaluating the Performance Improvement Preferences of Disability Service Managers: An Exploratory Study Using Gilbert's Behavior Engineering Model

ERIC Educational Resources Information Center

Wooderson, John R.; Cuskelly, Monica; Meyer, Kim A.

2017-01-01

Background: Front-line managers play an important role in managing the performance of staff working in services for people with intellectual disability, but little is known about the practices they prefer to use to improve staff performance and whether these align with what research has shown to be effective. Method: This study comprised two…

Processor core for real time background identification of HD video based on OpenCV Gaussian mixture model algorithm

NASA Astrophysics Data System (ADS)

Genovese, Mariangela; Napoli, Ettore

2013-05-01

The identification of moving objects is a fundamental step in computer vision processing chains. The development of low cost and lightweight smart cameras steadily increases the request of efficient and high performance circuits able to process high definition video in real time. The paper proposes two processor cores aimed to perform the real time background identification on High Definition (HD, 1920 1080 pixel) video streams. The implemented algorithm is the OpenCV version of the Gaussian Mixture Model (GMM), an high performance probabilistic algorithm for the segmentation of the background that is however computationally intensive and impossible to implement on general purpose CPU with the constraint of real time processing. In the proposed paper, the equations of the OpenCV GMM algorithm are optimized in such a way that a lightweight and low power implementation of the algorithm is obtained. The reported performances are also the result of the use of state of the art truncated binary multipliers and ROM compression techniques for the implementation of the non-linear functions. The first circuit has commercial FPGA devices as a target and provides speed and logic resource occupation that overcome previously proposed implementations. The second circuit is oriented to an ASIC (UMC-90nm) standard cell implementation. Both implementations are able to process more than 60 frames per second in 1080p format, a frame rate compatible with HD television.

Numerical Modeling of the Hall Thruster Discharge

DTIC Science & Technology

2005-04-01

This collection of seven previously published papers performed under Grant No. FA8655-04-1-3003 provide the background for the development of a new version of the HPHall hybrid code (HPHallv.2) for the numerical modeling of Hall Thruster discharge and new insights on discharge physics obtained during the development.

Unpacking the Inequality among Turkish Schools: Findings from PISA 2006

ERIC Educational Resources Information Center

Alacaci, Cengiz; Erbas, Ayhan Kursat

2010-01-01

The study investigates the effects of certain school characteristics on students' mathematics performances in Turkey in the PISA 2006 while controlling for family background and demographic characteristics. Three models of Hierarchical Linear Modeling (HLM) are constructed. The results reveal that 55% of the variance is attributable to…

A refined methodology for modeling volume quantification performance in CT

NASA Astrophysics Data System (ADS)

Chen, Baiyu; Wilson, Joshua; Samei, Ehsan

2014-03-01

The utility of CT lung nodule volume quantification technique depends on the precision of the quantification. To enable the evaluation of quantification precision, we previously developed a mathematical model that related precision to image resolution and noise properties in uniform backgrounds in terms of an estimability index (e'). The e' was shown to predict empirical precision across 54 imaging and reconstruction protocols, but with different correlation qualities for FBP and iterative reconstruction (IR) due to the non-linearity of IR impacted by anatomical structure. To better account for the non-linearity of IR, this study aimed to refine the noise characterization of the model in the presence of textured backgrounds. Repeated scans of an anthropomorphic lung phantom were acquired. Subtracted images were used to measure the image quantum noise, which was then used to adjust the noise component of the e' calculation measured from a uniform region. In addition to the model refinement, the validation of the model was further extended to 2 nodule sizes (5 and 10 mm) and 2 segmentation algorithms. Results showed that the magnitude of IR's quantum noise was significantly higher in structured backgrounds than in uniform backgrounds (ASiR, 30-50%; MBIR, 100-200%). With the refined model, the correlation between e' values and empirical precision no longer depended on reconstruction algorithm. In conclusion, the model with refined noise characterization relfected the nonlinearity of iterative reconstruction in structured background, and further showed successful prediction of quantification precision across a variety of nodule sizes, dose levels, slice thickness, reconstruction algorithms, and segmentation software.

COUPLING OF CORONAL AND HELIOSPHERIC MAGNETOHYDRODYNAMIC MODELS: SOLUTION COMPARISONS AND VERIFICATION

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

Merkin, V. G.; Lionello, R.; Linker, J.

2016-11-01

Two well-established magnetohydrodynamic (MHD) codes are coupled to model the solar corona and the inner heliosphere. The corona is simulated using the MHD algorithm outside a sphere (MAS) model. The Lyon–Fedder–Mobarry (LFM) model is used in the heliosphere. The interface between the models is placed in a spherical shell above the critical point and allows both models to work in either a rotating or an inertial frame. Numerical tests are presented examining the coupled model solutions from 20 to 50 solar radii. The heliospheric simulations are run with both LFM and the MAS extension into the heliosphere, and use themore » same polytropic coronal MAS solutions as the inner boundary condition. The coronal simulations are performed for idealized magnetic configurations, with an out-of-equilibrium flux rope inserted into an axisymmetric background, with and without including the solar rotation. The temporal evolution at the inner boundary of the LFM and MAS solutions is shown to be nearly identical, as are the steady-state background solutions, prior to the insertion of the flux rope. However, after the coronal mass ejection has propagated through the significant portion of the simulation domain, the heliospheric solutions diverge. Additional simulations with different resolution are then performed and show that the MAS heliospheric solutions approach those of LFM when run with progressively higher resolution. Following these detailed tests, a more realistic simulation driven by the thermodynamic coronal MAS is presented, which includes solar rotation and an azimuthally asymmetric background and extends to the Earth’s orbit.« less

Detecting spatial memory deficits beyond blindness in tg2576 Alzheimer mice.

PubMed

Yassine, Nour; Lazaris, Anelise; Dorner-Ciossek, Cornelia; Després, Olivier; Meyer, Laurence; Maitre, Michel; Mensah-Nyagan, Ayikoe Guy; Cassel, Jean-Christophe; Mathis, Chantal

2013-03-01

The retinal degeneration Pde6b(rd1) (rd) mutation can be a major pitfall in behavioral studies using tg2576 mice bred on a B6:SJL genetic background, 1 of the most widely used models of Alzheimer's disease. After a pilot study in wild type mice, performance of 8- and 16-month-old tg2576 mice were assessed in several behavioral tasks with the challenge of selecting 1 or more task(s) showing robust memory deficits on this genetic background. Water maze acquisition was impossible in rd homozygotes, whereas Y-maze alternation, object recognition, and olfactory discrimination were unaffected by both the transgene and the rd mutation. Spatial memory retention of 8- and 16-month-old tg2576 mice, however, was dramatically affected independently of the rd mutation when mice had to recognize a spatial configuration of objects or to perform the Barnes maze. Thus, the latter tasks appear extremely useful to evaluate spatial memory deficits and to test cognitive therapies in tg2576 mice and other mouse models bred on a background susceptible to visual impairment. Copyright © 2013 Elsevier Inc. All rights reserved.

Evaluation of Multiclass Model Observers in PET LROC Studies

NASA Astrophysics Data System (ADS)

Gifford, H. C.; Kinahan, P. E.; Lartizien, C.; King, M. A.

2007-02-01

A localization ROC (LROC) study was conducted to evaluate nonprewhitening matched-filter (NPW) and channelized NPW (CNPW) versions of a multiclass model observer as predictors of human tumor-detection performance with PET images. Target localization is explicitly performed by these model observers. Tumors were placed in the liver, lungs, and background soft tissue of a mathematical phantom, and the data simulation modeled a full-3D acquisition mode. Reconstructions were performed with the FORE+AWOSEM algorithm. The LROC study measured observer performance with 2D images consisting of either coronal, sagittal, or transverse views of the same set of cases. Versions of the CNPW observer based on two previously published difference-of-Gaussian channel models demonstrated good quantitative agreement with human observers. One interpretation of these results treats the CNPW observer as a channelized Hotelling observer with implicit internal noise

Modeling spatiotemporal covariance for magnetoencephalography or electroencephalography source analysis.

PubMed

Plis, Sergey M; George, J S; Jun, S C; Paré-Blagoev, J; Ranken, D M; Wood, C C; Schmidt, D M

2007-01-01

We propose a new model to approximate spatiotemporal noise covariance for use in neural electromagnetic source analysis, which better captures temporal variability in background activity. As with other existing formalisms, our model employs a Kronecker product of matrices representing temporal and spatial covariance. In our model, spatial components are allowed to have differing temporal covariances. Variability is represented as a series of Kronecker products of spatial component covariances and corresponding temporal covariances. Unlike previous attempts to model covariance through a sum of Kronecker products, our model is designed to have a computationally manageable inverse. Despite increased descriptive power, inversion of the model is fast, making it useful in source analysis. We have explored two versions of the model. One is estimated based on the assumption that spatial components of background noise have uncorrelated time courses. Another version, which gives closer approximation, is based on the assumption that time courses are statistically independent. The accuracy of the structural approximation is compared to an existing model, based on a single Kronecker product, using both Frobenius norm of the difference between spatiotemporal sample covariance and a model, and scatter plots. Performance of ours and previous models is compared in source analysis of a large number of single dipole problems with simulated time courses and with background from authentic magnetoencephalography data.

Malaysian adolescent students' needs for enhancing thinking skills, counteracting risk factors and demonstrating academic resilience

PubMed Central

Kuldas, Seffetullah; Hashim, Shahabuddin; Ismail, Hairul Nizam

2015-01-01

The adolescence period of life comes along with changes and challenges in terms of physical and cognitive development. In this hectic period, many adolescents may suffer more from various risk factors such as low socioeconomic status, substance abuse, sexual abuse and teenage pregnancy. Findings indicate that such disadvantaged backgrounds of Malaysian adolescent students lead to failure or underachievement in their academic performance. This narrative review scrutinises how some of these students are able to demonstrate academic resilience, which is satisfactory performance in cognitive or academic tasks in spite of their disadvantaged backgrounds. The review stresses the need for developing a caregiving relationship model for at-risk adolescent students in Malaysia. Such a model would allow educators to meet the students' needs for enhancing thinking skills, counteracting risk factors and demonstrating academic resilience. PMID:25663734

A Meta-Analysis of Adult-Rated Child Personality and Academic Performance in Primary Education

ERIC Educational Resources Information Center

Poropat, Arthur E.

2014-01-01

Background: Personality is reliably associated with academic performance, but personality measurement in primary education can be problematic. Young children find it difficult to accurately self-rate personality, and dominant models of adult personality may be inappropriate for children. Aims: This meta-analysis was conducted to determine the…

Going for the gold. Models of agency in Japanese and American contexts.

PubMed

Markus, Hazel Rose; Uchida, Yukiko; Omoregie, Heather; Townsend, Sarah S M; Kitayama, Shinobu

2006-02-01

Two studies examined how Olympic performance is explained in American and Japanese contexts. Study 1, an analysis of media coverage of the 2000 and 2002 Olympics, shows that in both Japanese and American contexts, performance is construed mainly in terms of the actions of persons. However, Japanese and American accounts differ in their explanations of the nature and source of intentional agency, that is, in their models of agency. In Japanese contexts, agency is construed as conjoint and simultaneously implicates athletes' personal attributes (both positive and negative), background, and social and emotional experience. In American contexts, agency is construed as disjoint, separate from athletes' background or social and emotional experience; performance is explained primarily through positive personal characteristics and features of the competition. Study 2, in which participants chose information to be included in an athlete's description, confirms these findings. Differences in the construction of agency are reflected in and fostered by common cultural products (e.g., television accounts).

FNAS/summer faculty fellowship research continuation program. Task 6: Integrated model development for liquid fueled rocket propulsion systems. Task 9: Aspects of model-based rocket engine condition monitoring and control

NASA Technical Reports Server (NTRS)

Santi, L. Michael; Helmicki, Arthur J.

1993-01-01

The objective of Phase I of this research effort was to develop an advanced mathematical-empirical model of SSME steady-state performance. Task 6 of Phase I is to develop component specific modification strategy for baseline case influence coefficient matrices. This report describes the background of SSME performance characteristics and provides a description of the control variable basis of three different gains models. The procedure used to establish influence coefficients for each of these three models is also described. Gains model analysis results are compared to Rocketdyne's power balance model (PBM).

Wavelet Analysis Used for Spectral Background Removal in the Determination of Glucose from Near-Infrared Single-Beam Spectra

PubMed Central

Wan, Boyong; Small, Gary W.

2010-01-01

Wavelet analysis is developed as a preprocessing tool for use in removing background information from near-infrared (near-IR) single-beam spectra before the construction of multivariate calibration models. Three data sets collected with three different near-IR spectrometers are investigated that involve the determination of physiological levels of glucose (1-30 mM) in a simulated biological matrix containing alanine, ascorbate, lactate, triacetin, and urea in phosphate buffer. A factorial design is employed to optimize the specific wavelet function used and the level of decomposition applied, in addition to the spectral range and number of latent variables associated with a partial least-squares calibration model. The prediction performance of the computed models is studied with separate data acquired after the collection of the calibration spectra. This evaluation includes one data set collected over a period of more than six months. Preprocessing with wavelet analysis is also compared to the calculation of second-derivative spectra. Over the three data sets evaluated, wavelet analysis is observed to produce better-performing calibration models, with improvements in concentration predictions on the order of 30% being realized relative to models based on either second-derivative spectra or spectra preprocessed with simple additive and multiplicative scaling correction. This methodology allows the construction of stable calibrations directly with single-beam spectra, thereby eliminating the need for the collection of a separate background or reference spectrum. PMID:21035604

Wavelet analysis used for spectral background removal in the determination of glucose from near-infrared single-beam spectra.

PubMed

Wan, Boyong; Small, Gary W

2010-11-29

Wavelet analysis is developed as a preprocessing tool for use in removing background information from near-infrared (near-IR) single-beam spectra before the construction of multivariate calibration models. Three data sets collected with three different near-IR spectrometers are investigated that involve the determination of physiological levels of glucose (1-30 mM) in a simulated biological matrix containing alanine, ascorbate, lactate, triacetin, and urea in phosphate buffer. A factorial design is employed to optimize the specific wavelet function used and the level of decomposition applied, in addition to the spectral range and number of latent variables associated with a partial least-squares calibration model. The prediction performance of the computed models is studied with separate data acquired after the collection of the calibration spectra. This evaluation includes one data set collected over a period of more than 6 months. Preprocessing with wavelet analysis is also compared to the calculation of second-derivative spectra. Over the three data sets evaluated, wavelet analysis is observed to produce better-performing calibration models, with improvements in concentration predictions on the order of 30% being realized relative to models based on either second-derivative spectra or spectra preprocessed with simple additive and multiplicative scaling correction. This methodology allows the construction of stable calibrations directly with single-beam spectra, thereby eliminating the need for the collection of a separate background or reference spectrum. Copyright © 2010 Elsevier B.V. All rights reserved.

Calibration, event reconstruction, data analysis and limits calculation for the LUX dark matter experiment

DOE PAGES

Akerib, DS; Alsum, S; Araújo, HM; ...

2018-01-05

The LUX experiment has performed searches for dark matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived frommore » $${1.4}\\times 10^{4}\\;\\mathrm{kg\\,days}$$ of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.« less

Calibration, event reconstruction, data analysis, and limit calculation for the LUX dark matter experiment

DOE PAGES

Akerib, D. S.; Alsum, S.; Araújo, H. M.; ...

2018-05-31

Here, the LUX experiment has performed searches for dark matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived frommore » $${1.4}\\times 10^{4}\\;\\mathrm{kg\\,days}$$ of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.« less

Calibration, event reconstruction, data analysis, and limit calculation for the LUX dark matter experiment

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

Akerib, D. S.; Alsum, S.; Araújo, H. M.

Here, the LUX experiment has performed searches for dark matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived frommore » $${1.4}\\times 10^{4}\\;\\mathrm{kg\\,days}$$ of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.« less

CXBN: a blueprint for an improved measurement of the cosmological x-ray background

NASA Astrophysics Data System (ADS)

Simms, Lance M.; Jernigan, J. G.; Malphrus, Benjamin K.; McNeil, Roger; Brown, Kevin Z.; Rose, Tyler G.; Lim, Hyoung S.; Anderson, Steven; Kruth, Jeffrey A.; Doty, John P.; Wampler-Doty, Matthew; Cominsky, Lynn R.; Prasad, Kamal S.; Thomas, Eric T.; Combs, Michael S.; Kroll, Robert T.; Cahall, Benjamin J.; Turba, Tyler T.; Molton, Brandon L.; Powell, Margaret M.; Fitzpatrick, Jonathan F.; Graves, Daniel C.; Gaalema, Stephen D.; Sun, Shunming

2012-10-01

A precise measurement of the Cosmic X-ray Background (CXB) is crucial for constraining models of the evolution and composition of the universe. While several large, expensive satellites have measured the CXB as a secondary mission, there is still disagreement about normalization of its spectrum. The Cosmic X-ray Background NanoSat (CXBN) is a small, low-cost satellite whose primary goal is to measure the CXB over its two-year lifetime. Benefiting from a low instrument-induced background due to its small mass and size, CXBN will use a novel, pixelated Cadmium Zinc Telluride (CZT) detector with energy resolution < 1 keV over the range 1-60 keV to measure the CXBN with unprecedented accuracy. This paper describes CXBN and its science payload, including the GEANT4 model that has been used to predict overall performance and the backgrounds from secondary particles in Low Earth Orbit. It also addresses the strategy for scanning the sky and calibrating the data, and presents the expected results over the two-year mission lifetime.

Binocular combination of luminance profiles

PubMed Central

Ding, Jian; Levi, Dennis M.

2017-01-01

We develop and test a new two-dimensional model for binocular combination of the two eyes' luminance profiles. For first-order stimuli, the model assumes that one eye's luminance profile first goes through a luminance compressor, receives gain-control and gain-enhancement from the other eye, and then linearly combines the other eye's output profile. For second-order stimuli, rectification is added in the signal path of the model before the binocular combination site. Both the total contrast and luminance energies, weighted sums over both the space and spatial-frequency domains, were used in the interocular gain-control, while only the total contrast energy was used in the interocular gain-enhancement. To challenge the model, we performed a binocular brightness matching experiment over a large range of background and target luminances. The target stimulus was a dichoptic disc with a sharp edge that has an increment or decrement luminance from its background. The disk's interocular luminance ratio varied from trial to trial. To refine the model we tested three luminance compressors, five nested binocular combination models (including the Ding–Sperling and the DSKL models), and examined the presence or absence of total luminance energy in the model. We found that (1) installing a luminance compressor, either a logarithmic luminance function or luminance gain-control, (2) including both contrast and luminance energies, and (3) adding interocular gain-enhancement (the DSKL model) to a combined model significantly improved its performance. The combined model provides a systematic account of binocular luminance summation over a large range of luminance input levels. It gives a unified explanation of Fechner's paradox observed on a dark background, and a winner-take-all phenomenon observed on a light background. To further test the model, we conducted two additional experiments: luminance summation of discs with asymmetric contour information (Experiment 2), similar to Levelt (1965) and binocular combination of second-order contrast-modulated gratings (Experiment 3). We used the model obtained in Experiment 1 to predict the results of Experiments 2 and 3 and the results of our previous studies. Model simulations further refined the contrast space weight and contrast sensitivity functions that are installed in the model, and provide a reasonable account for rebalancing of imbalanced binocular vision by reducing the mean luminance in the dominant eye. PMID:29098293

Simulation of PEP-II Accelerator Backgrounds Using TURTLE

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

Barlow, R.J.; Fieguth, T.; /SLAC

2006-02-15

We present studies of accelerator-induced backgrounds in the BaBar detector at the SLAC B-Factory, carried out using LPTURTLE, a modified version of the DECAY TURTLE simulation package. Lost-particle backgrounds in PEP-II are dominated by a combination of beam-gas bremstrahlung, beam-gas Coulomb scattering, radiative-Bhabha events and beam-beam blow-up. The radiation damage and detector occupancy caused by the associated electromagnetic shower debris can limit the usable luminosity. In order to understand and mitigate such backgrounds, we have performed a full program of beam-gas and luminosity-background simulations, that include the effects of the detector solenoidal field, detailed modeling of limiting apertures in bothmore » collider rings, and optimization of the betatron collimation scheme in the presence of large transverse tails.« less

Example-Based Learning: Effects of Model Expertise in Relation to Student Expertise

ERIC Educational Resources Information Center

Boekhout, Paul; van Gog, Tamara; van de Wiel, Margje W. J.; Gerards-Last, Dorien; Geraets, Jacques

2010-01-01

Background: Worked examples are very effective for novice learners. They typically present a written-out ideal (didactical) solution for learners to study. Aims: This study used worked examples of patient history taking in physiotherapy that presented a "non"-didactical solution (i.e., based on actual performance). The effects of model expertise…

Measuring Learning Progressions Using Bayesian Modeling in Complex Assessments

ERIC Educational Resources Information Center

Rutstein, Daisy Wise

2012-01-01

This research examines issues regarding model estimation and robustness in the use of Bayesian Inference Networks (BINs) for measuring Learning Progressions (LPs). It provides background information on LPs and how they might be used in practice. Two simulation studies are performed, along with real data examples. The first study examines the case…

Appreciative Inquiry: A Model for Organizational Development and Performance Improvement in Student Affairs

ERIC Educational Resources Information Center

Elleven, Russell K.

2007-01-01

The article examines a relatively new tool to increase the effectiveness of organizations and people. The recent development and background of Appreciative Inquiry (AI) is reviewed. Basic assumptions of the model are discussed. Implications for departments and divisions of student affairs are analyzed. Finally, suggested readings and workshop…

B-spline based image tracking by detection

NASA Astrophysics Data System (ADS)

Balaji, Bhashyam; Sithiravel, Rajiv; Damini, Anthony; Kirubarajan, Thiagalingam; Rajan, Sreeraman

2016-05-01

Visual image tracking involves the estimation of the motion of any desired targets in a surveillance region using a sequence of images. A standard method of isolating moving targets in image tracking uses background subtraction. The standard background subtraction method is often impacted by irrelevant information in the images, which can lead to poor performance in image-based target tracking. In this paper, a B-Spline based image tracking is implemented. The novel method models the background and foreground using the B-Spline method followed by a tracking-by-detection algorithm. The effectiveness of the proposed algorithm is demonstrated.

Evaluation of a Revised Interplanetary Shock Prediction Model: 1D CESE-HD-2 Solar-Wind Model

NASA Astrophysics Data System (ADS)

Zhang, Y.; Du, A. M.; Du, D.; Sun, W.

2014-08-01

We modified the one-dimensional conservation element and solution element (CESE) hydrodynamic (HD) model into a new version [ 1D CESE-HD-2], by considering the direction of the shock propagation. The real-time performance of the 1D CESE-HD-2 model during Solar Cycle 23 (February 1997 - December 2006) is investigated and compared with those of the Shock Time of Arrival Model ( STOA), the Interplanetary-Shock-Propagation Model ( ISPM), and the Hakamada-Akasofu-Fry version 2 ( HAFv.2). Of the total of 584 flare events, 173 occurred during the rising phase, 166 events during the maximum phase, and 245 events during the declining phase. The statistical results show that the success rates of the predictions by the 1D CESE-HD-2 model for the rising, maximum, declining, and composite periods are 64 %, 62 %, 57 %, and 61 %, respectively, with a hit window of ± 24 hours. The results demonstrate that the 1D CESE-HD-2 model shows the highest success rates when the background solar-wind speed is relatively fast. Thus, when the background solar-wind speed at the time of shock initiation is enhanced, the forecasts will provide potential values to the customers. A high value (27.08) of χ 2 and low p-value (< 0.0001) for the 1D CESE-HD-2 model give considerable confidence for real-time forecasts by using this new model. Furthermore, the effects of various shock characteristics (initial speed, shock duration, background solar wind, longitude, etc.) and background solar wind on the forecast are also investigated statistically.

Correlation between model observers in uniform background and human observers in patient liver background for a low-contrast detection task in CT

NASA Astrophysics Data System (ADS)

Gong, Hao; Yu, Lifeng; Leng, Shuai; Dilger, Samantha; Zhou, Wei; Ren, Liqiang; McCollough, Cynthia H.

2018-03-01

Channelized Hotelling observer (CHO) has demonstrated strong correlation with human observer (HO) in both single-slice viewing mode and multi-slice viewing mode in low-contrast detection tasks with uniform background. However, it remains unknown if the simplest single-slice CHO in uniform background can be used to predict human observer performance in more realistic tasks that involve patient anatomical background and multi-slice viewing mode. In this study, we aim to investigate the correlation between CHO in a uniform water background and human observer performance at a multi-slice viewing mode on patient liver background for a low-contrast lesion detection task. The human observer study was performed on CT images from 7 abdominal CT exams. A noise insertion tool was employed to synthesize CT scans at two additional dose levels. A validated lesion insertion tool was used to numerically insert metastatic liver lesions of various sizes and contrasts into both phantom and patient images. We selected 12 conditions out of 72 possible experimental conditions to evaluate the correlation at various radiation doses, lesion sizes, lesion contrasts and reconstruction algorithms. CHO with both single and multi-slice viewing modes were strongly correlated with HO. The corresponding Pearson's correlation coefficient was 0.982 (with 95% confidence interval (CI) [0.936, 0.995]) and 0.989 (with 95% CI of [0.960, 0.997]) in multi-slice and single-slice viewing modes, respectively. Therefore, this study demonstrated the potential to use the simplest single-slice CHO to assess image quality for more realistic clinically relevant CT detection tasks.

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

Rouleau, Christopher M.; Puretzky, Alexander A.; Geohegan, David B.

The slowing of Pt nanoparticles in argon background gas was characterized by Rayleigh scattering imaging using a plume of nanoparticles generated by femtosecond laser through thin film ablation (fs-TTFA) of 20 nanometers-thick Pt films. The ablation was performed at threshold laser energy fluences for complete film removal to provide a well-defined plume consisting almost entirely of nanoparticles traveling with a narrow velocity distribution, providing a unique system to unambiguously characterize the slowing of nanoparticles during interaction with background gases. Nanoparticles of ~200 nm diameter were found to decelerate in background Ar gas with pressures less than 50 Torr in goodmore » agreement with a linear drag model in the Epstein regime. Based on this model, the stopping distance of small nanoparticles in the plume was predicted and tested by particle collection in an off-axis geometry, and size distribution analysis by transmission electron microscopy. These results permit a basis to interpret nanoparticle propagation through background gases in laser ablation plumes that contain mixed components.« less

Academically Buoyant Students Are Less Anxious about and Perform Better in High-Stakes Examinations

ERIC Educational Resources Information Center

Putwain, David W.; Daly, Anthony L.; Chamberlain, Suzanne; Sadreddini, Shireen

2015-01-01

Background: Prior research has shown that test anxiety is negatively related to academic buoyancy, but it is not known whether test anxiety is an antecedent or outcome of academic buoyancy. Furthermore, it is not known whether academic buoyancy is related to performance on high-stakes examinations. Aims: To test a model specifying reciprocal…

Effect of Background Pressure on the Performance and Plume of the HiVHAc Hall Thruster

NASA Technical Reports Server (NTRS)

Huang, Wensheng; Kamhawi, Hani; Haag, Thomas

2013-01-01

During the Single String Integration Test of the NASA HiVHAc Hall thruster, a number of plasma diagnostics were implemented to study the effect of varying facility background pressure on thruster operation. These diagnostics include thrust stand, Faraday probe, ExB probe, and retarding potential analyzer. The test results indicated a rise in thrust and discharge current with background pressure. There was also a decrease in ion energy per charge, an increase in multiply-charged species production, a decrease in plume divergence, and a decrease in ion beam current with increasing background pressure. A simplified ingestion model was applied to determine the maximum acceptable background pressure for thrust measurement. The maximum acceptable ingestion percentage was found to be around 1%. Examination of the diagnostics results suggest the ionization and acceleration zones of the thruster were shifting upstream with increasing background pressure.

The inception of pulsed discharges in air: simulations in background fields above and below breakdown

NASA Astrophysics Data System (ADS)

Sun, Anbang; Teunissen, Jannis; Ebert, Ute

2014-11-01

We investigate discharge inception in air, in uniform background electric fields above and below the breakdown threshold. We perform 3D particle simulations that include a natural level of background ionization in the form of positive and \\text{O}2- ions. In background fields below breakdown, we use a strongly ionized seed of electrons and positive ions to enhance the field locally. In the region of enhanced field, we observe the growth of positive streamers, as in previous simulations with 2D plasma fluid models. The inclusion of background ionization has little effect in this case. When the background field is above the breakdown threshold, the situation is very different. Electrons can then detach from \\text{O}2- and start ionization avalanches in the whole volume. These avalanches together create one extended discharge, in contrast to the ‘double-headed’ streamers found in many fluid simulations.

Assessment of the MPACT Resonance Data Generation Procedure

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

Kim, Kang Seog; Williams, Mark L.

Currently, heterogeneous models are being used to generate resonance self-shielded cross-section tables as a function of background cross sections for important nuclides such as 235U and 238U by performing the CENTRM (Continuous Energy Transport Model) slowing down calculation with the MOC (Method of Characteristics) spatial discretization and ESSM (Embedded Self-Shielding Method) calculations to obtain background cross sections. And then the resonance self-shielded cross section tables are converted into subgroup data which are to be used in estimating problem-dependent self-shielded cross sections in MPACT (Michigan Parallel Characteristics Transport Code). Although this procedure has been developed and thus resonance data have beenmore » generated and validated by benchmark calculations, assessment has never been performed to review if the resonance data are properly generated by the procedure and utilized in MPACT. This study focuses on assessing the procedure and a proper use in MPACT.« less

Do semantic contextual cues facilitate transfer learning from video in toddlers?

PubMed Central

Zimmermann, Laura; Moser, Alecia; Grenell, Amanda; Dickerson, Kelly; Yao, Qianwen; Gerhardstein, Peter; Barr, Rachel

2015-01-01

Young children typically demonstrate a transfer deficit, learning less from video than live presentations. Semantically meaningful context has been demonstrated to enhance learning in young children. We examined the effect of a semantically meaningful context on toddlers’ imitation performance. Two- and 2.5-year-olds participated in a puzzle imitation task to examine learning from either a live or televised model. The model demonstrated how to assemble a three-piece puzzle to make a fish or a boat, with the puzzle demonstration occurring against a semantically meaningful background context (ocean) or a yellow background (no context). Participants in the video condition performed significantly worse than participants in the live condition, demonstrating the typical transfer deficit effect. While the context helped improve overall levels of imitation, especially for the boat puzzle, only individual differences in the ability to self-generate a stimulus label were associated with a reduction in the transfer deficit. PMID:26029131

Ultrasound Shear Wave Simulation of Breast Tumor Using Nonlinear Tissue Elasticity

PubMed Central

Park, Dae Woo

2016-01-01

Shear wave elasticity imaging (SWEI) can assess the elasticity of tissues, but the shear modulus estimated in SWEI is often less sensitive to a subtle change of the stiffness that produces only small mechanical contrast to the background tissues. Because most soft tissues exhibit mechanical nonlinearity that differs in tissue types, mechanical contrast can be enhanced if the tissues are compressed. In this study, a finite element- (FE-) based simulation was performed for a breast tissue model, which consists of a circular (D: 10 mm, hard) tumor and surrounding tissue (soft). The SWEI was performed with 0% to 30% compression of the breast tissue model. The shear modulus of the tumor exhibited noticeably high nonlinearity compared to soft background tissue above 10% overall applied compression. As a result, the elastic modulus contrast of the tumor to the surrounding tissue was increased from 0.46 at 0% compression to 1.45 at 30% compression. PMID:27293476

The effects of iterative reconstruction in CT on low-contrast liver lesion volumetry: a phantom study

NASA Astrophysics Data System (ADS)

Li, Qin; Berman, Benjamin P.; Schumacher, Justin; Liang, Yongguang; Gavrielides, Marios A.; Yang, Hao; Zhao, Binsheng; Petrick, Nicholas

2017-03-01

Tumor volume measured from computed tomography images is considered a biomarker for disease progression or treatment response. The estimation of the tumor volume depends on the imaging system parameters selected, as well as lesion characteristics. In this study, we examined how different image reconstruction methods affect the measurement of lesions in an anthropomorphic liver phantom with a non-uniform background. Iterative statistics-based and model-based reconstructions, as well as filtered back-projection, were evaluated and compared in this study. Statistics-based and filtered back-projection yielded similar estimation performance, while model-based yielded higher precision but lower accuracy in the case of small lesions. Iterative reconstructions exhibited higher signal-to-noise ratio but slightly lower contrast of the lesion relative to the background. A better understanding of lesion volumetry performance as a function of acquisition parameters and lesion characteristics can lead to its incorporation as a routine sizing tool.

Do semantic contextual cues facilitate transfer learning from video in toddlers?

PubMed

Zimmermann, Laura; Moser, Alecia; Grenell, Amanda; Dickerson, Kelly; Yao, Qianwen; Gerhardstein, Peter; Barr, Rachel

2015-01-01

Young children typically demonstrate a transfer deficit, learning less from video than live presentations. Semantically meaningful context has been demonstrated to enhance learning in young children. We examined the effect of a semantically meaningful context on toddlers' imitation performance. Two- and 2.5-year-olds participated in a puzzle imitation task to examine learning from either a live or televised model. The model demonstrated how to assemble a three-piece puzzle to make a fish or a boat, with the puzzle demonstration occurring against a semantically meaningful background context (ocean) or a yellow background (no context). Participants in the video condition performed significantly worse than participants in the live condition, demonstrating the typical transfer deficit effect. While the context helped improve overall levels of imitation, especially for the boat puzzle, only individual differences in the ability to self-generate a stimulus label were associated with a reduction in the transfer deficit.

Salient Object Detection via Structured Matrix Decomposition.

PubMed

Peng, Houwen; Li, Bing; Ling, Haibin; Hu, Weiming; Xiong, Weihua; Maybank, Stephen J

2016-05-04

Low-rank recovery models have shown potential for salient object detection, where a matrix is decomposed into a low-rank matrix representing image background and a sparse matrix identifying salient objects. Two deficiencies, however, still exist. First, previous work typically assumes the elements in the sparse matrix are mutually independent, ignoring the spatial and pattern relations of image regions. Second, when the low-rank and sparse matrices are relatively coherent, e.g., when there are similarities between the salient objects and background or when the background is complicated, it is difficult for previous models to disentangle them. To address these problems, we propose a novel structured matrix decomposition model with two structural regularizations: (1) a tree-structured sparsity-inducing regularization that captures the image structure and enforces patches from the same object to have similar saliency values, and (2) a Laplacian regularization that enlarges the gaps between salient objects and the background in feature space. Furthermore, high-level priors are integrated to guide the matrix decomposition and boost the detection. We evaluate our model for salient object detection on five challenging datasets including single object, multiple objects and complex scene images, and show competitive results as compared with 24 state-of-the-art methods in terms of seven performance metrics.

Multispectral infrared target detection: phenomenology and modeling

NASA Astrophysics Data System (ADS)

Cederquist, Jack N.; Rogne, Timothy J.; Schwartz, Craig R.

1993-10-01

Many targets of interest provide only very small signature differences from the clutter background. The ability to detect these small difference targets should be improved by using data which is diverse in space, time, wavelength or some other observable. Target materials often differ from background materials in the variation of their reflectance or emittance with wavelength. A multispectral sensor is therefore considered as a means to improve detection of small signal targets. If this sensor operates in the thermal infrared, it will not need solar illumination and will be useful at night as well as during the day. An understanding of the phenomenology of the spectral properties of materials and an ability to model and simulate target and clutter signatures is needed to understand potential target detection performance from multispectral infrared sensor data. Spectral variations in material emittance are due to vibrational energy transitions in molecular bonds. The spectral emittances of many materials of interest have been measured. Examples are vegetation, soil, construction and road materials, and paints. A multispectral infrared signature model has been developed which includes target and background temperature and emissivity, sky, sun, cloud and background irradiance, multiple reflection effects, path radiance, and atmospheric attenuation. This model can be used to predict multispectral infrared signatures for small signal targets.

Comparison of linear, skewed-linear, and proportional hazard models for the analysis of lambing interval in Ripollesa ewes.

PubMed

Casellas, J; Bach, R

2012-06-01

Lambing interval is a relevant reproductive indicator for sheep populations under continuous mating systems, although there is a shortage of selection programs accounting for this trait in the sheep industry. Both the historical assumption of small genetic background and its unorthodox distribution pattern have limited its implementation as a breeding objective. In this manuscript, statistical performances of 3 alternative parametrizations [i.e., symmetric Gaussian mixed linear (GML) model, skew-Gaussian mixed linear (SGML) model, and piecewise Weibull proportional hazard (PWPH) model] have been compared to elucidate the preferred methodology to handle lambing interval data. More specifically, flock-by-flock analyses were performed on 31,986 lambing interval records (257.3 ± 0.2 d) from 6 purebred Ripollesa flocks. Model performances were compared in terms of deviance information criterion (DIC) and Bayes factor (BF). For all flocks, PWPH models were clearly preferred; they generated a reduction of 1,900 or more DIC units and provided BF estimates larger than 100 (i.e., PWPH models against linear models). These differences were reduced when comparing PWPH models with different number of change points for the baseline hazard function. In 4 flocks, only 2 change points were required to minimize the DIC, whereas 4 and 6 change points were needed for the 2 remaining flocks. These differences demonstrated a remarkable degree of heterogeneity across sheep flocks that must be properly accounted for in genetic evaluation models to avoid statistical biases and suboptimal genetic trends. Within this context, all 6 Ripollesa flocks revealed substantial genetic background for lambing interval with heritabilities ranging between 0.13 and 0.19. This study provides the first evidence of the suitability of PWPH models for lambing interval analysis, clearly discarding previous parametrizations focused on mixed linear models.

Design Specifications for the Advanced Instructional Design Advisor (AIDA). Volume 1

DTIC Science & Technology

1992-01-01

research; (3) Describe the knowledge base sufficient to support the varieties of knowledge to be represented in the AIDA model ; (4) Document the...feasibility of continuing the development of the AIDA model . 2.3 Background In Phase I of the AIDA project (Task 0006), (1) the AIDA concept was defined...the AIDA Model A paper-based demonstration of the AIDA instructional design model was performed by using the model to develop a minimal application

Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update.

PubMed

Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

2016-04-15

Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the "good" models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm.

Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update

PubMed Central

Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

2016-01-01

Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the “good” models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm. PMID:27092505

78 FR 54835 - Air Quality Implementation Plan; Alabama; Attainment Plan for the Troy Area 2008 Lead...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-06

... input options commensurate with the Regulatory Modeling Guidance. Perform current and post control.... Table 2--Post-Control Modeling Results \\4\\ Sanders lead facility Max 3-mth Background Total Year maximum...\\ (Facility MET data). The post-control analysis resulted in a predicted impact of 0.15 [mu]g/m\\3\\ (NWS MET...

The Significance of Trust in the Political System and Motivation for Pupils' Learning Progress in Politics Lessons

ERIC Educational Resources Information Center

Landwehr, Barbara; Weisseno, Georg

2016-01-01

Very little research has been conducted on the contribution of political education to learning progress in Germany. Hence, there is a need for intervention studies measuring performance against the theoretical background of a political competence model. This model comprises three constructs: subject knowledge, motivation and attitudes. According…

Development and Application of a Multi-Modal Task Analysis to Support Intelligent Tutoring of Complex Skills

ERIC Educational Resources Information Center

Skinner, Anna; Diller, David; Kumar, Rohit; Cannon-Bowers, Jan; Smith, Roger; Tanaka, Alyssa; Julian, Danielle; Perez, Ray

2018-01-01

Background: Contemporary work in the design and development of intelligent training systems employs task analysis (TA) methods for gathering knowledge that is subsequently encoded into task models. These task models form the basis of intelligent interpretation of student performance within education and training systems. Also referred to as expert…

ForCent model development and testing using the Enriched Background Isotope Study experiment

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

Parton, W.J.; Hanson, P. J.; Swanston, C.

The ForCent forest ecosystem model was developed by making major revisions to the DayCent model including: (1) adding a humus organic pool, (2) incorporating a detailed root growth model, and (3) including plant phenological growth patterns. Observed plant production and soil respiration data from 1993 to 2000 were used to demonstrate that the ForCent model could accurately simulate ecosystem carbon dynamics for the Oak Ridge National Laboratory deciduous forest. A comparison of ForCent versus observed soil pool {sup 14}C signature ({Delta} {sup 14}C) data from the Enriched Background Isotope Study {sup 14}C experiment (1999-2006) shows that the model correctly simulatesmore » the temporal dynamics of the {sup 14}C label as it moved from the surface litter and roots into the mineral soil organic matter pools. ForCent model validation was performed by comparing the observed Enriched Background Isotope Study experimental data with simulated live and dead root biomass {Delta} {sup 14}C data, and with soil respiration {Delta} {sup 14}C (mineral soil, humus layer, leaf litter layer, and total soil respiration) data. Results show that the model correctly simulates the impact of the Enriched Background Isotope Study {sup 14}C experimental treatments on soil respiration {Delta} {sup 14}C values for the different soil organic matter pools. Model results suggest that a two-pool root growth model correctly represents root carbon dynamics and inputs to the soil. The model fitting process and sensitivity analysis exposed uncertainty in our estimates of the fraction of mineral soil in the slow and passive pools, dissolved organic carbon flux out of the litter layer into the mineral soil, and mixing of the humus layer into the mineral soil layer.« less

ForCent Model Development and Testing using the Enriched Background Isotope Study (EBIS) Experiment

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

Parton, William; Hanson, Paul J; Swanston, Chris

The ForCent forest ecosystem model was developed by making major revisions to the DayCent model including: (1) adding a humus organic pool, (2) incorporating a detailed root growth model, and (3) including plant phenological growth patterns. Observed plant production and soil respiration data from 1993 to 2000 were used to demonstrate that the ForCent model could accurately simulate ecosystem carbon dynamics for the Oak Ridge National Laboratory deciduous forest. A comparison of ForCent versus observed soil pool 14C signature (? 14C) data from the Enriched Background Isotope Study 14C experiment (1999-2006) shows that the model correctly simulates the temporal dynamicsmore » of the 14C label as it moved from the surface litter and roots into the mineral soil organic matter pools. ForCent model validation was performed by comparing the observed Enriched Background Isotope Study experimental data with simulated live and dead root biomass ? 14C data, and with soil respiration ? 14C (mineral soil, humus layer, leaf litter layer, and total soil respiration) data. Results show that the model correctly simulates the impact of the Enriched Background Isotope Study 14C experimental treatments on soil respiration ? 14C values for the different soil organic matter pools. Model results suggest that a two-pool root growth model correctly represents root carbon dynamics and inputs to the soil. The model fitting process and sensitivity analysis exposed uncertainty in our estimates of the fraction of mineral soil in the slow and passive pools, dissolved organic carbon flux out of the litter layer into the mineral soil, and mixing of the humus layer into the mineral soil layer.« less

Performance measurement of PSF modeling reconstruction (True X) on Siemens Biograph TruePoint TrueV PET/CT.

PubMed

Lee, Young Sub; Kim, Jin Su; Kim, Kyeong Min; Kang, Joo Hyun; Lim, Sang Moo; Kim, Hee-Joung

2014-05-01

The Siemens Biograph TruePoint TrueV (B-TPTV) positron emission tomography (PET) scanner performs 3D PET reconstruction using a system matrix with point spread function (PSF) modeling (called the True X reconstruction). PET resolution was dramatically improved with the True X method. In this study, we assessed the spatial resolution and image quality on a B-TPTV PET scanner. In addition, we assessed the feasibility of animal imaging with a B-TPTV PET and compared it with a microPET R4 scanner. Spatial resolution was measured at center and at 8 cm offset from the center in transverse plane with warm background activity. True X, ordered subset expectation maximization (OSEM) without PSF modeling, and filtered back-projection (FBP) reconstruction methods were used. Percent contrast (% contrast) and percent background variability (% BV) were assessed according to NEMA NU2-2007. The recovery coefficient (RC), non-uniformity, spill-over ratio (SOR), and PET imaging of the Micro Deluxe Phantom were assessed to compare image quality of B-TPTV PET with that of the microPET R4. When True X reconstruction was used, spatial resolution was <3.65 mm with warm background activity. % contrast and % BV with True X reconstruction were higher than those with the OSEM reconstruction algorithm without PSF modeling. In addition, the RC with True X reconstruction was higher than that with the FBP method and the OSEM without PSF modeling method on the microPET R4. The non-uniformity with True X reconstruction was higher than that with FBP and OSEM without PSF modeling on microPET R4. SOR with True X reconstruction was better than that with FBP or OSEM without PSF modeling on the microPET R4. This study assessed the performance of the True X reconstruction. Spatial resolution with True X reconstruction was improved by 45 % and its % contrast was significantly improved compared to those with the conventional OSEM without PSF modeling reconstruction algorithm. The noise level was higher than that with the other reconstruction algorithm. Therefore, True X reconstruction should be used with caution when quantifying PET data.

Generalized background error covariance matrix model (GEN_BE v2.0)

NASA Astrophysics Data System (ADS)

Descombes, G.; Auligné, T.; Vandenberghe, F.; Barker, D. M.; Barré, J.

2015-03-01

The specification of state background error statistics is a key component of data assimilation since it affects the impact observations will have on the analysis. In the variational data assimilation approach, applied in geophysical sciences, the dimensions of the background error covariance matrix (B) are usually too large to be explicitly determined and B needs to be modeled. Recent efforts to include new variables in the analysis such as cloud parameters and chemical species have required the development of the code to GENerate the Background Errors (GEN_BE) version 2.0 for the Weather Research and Forecasting (WRF) community model. GEN_BE allows for a simpler, flexible, robust, and community-oriented framework that gathers methods used by some meteorological operational centers and researchers. We present the advantages of this new design for the data assimilation community by performing benchmarks of different modeling of B and showing some of the new features in data assimilation test cases. As data assimilation for clouds remains a challenge, we present a multivariate approach that includes hydrometeors in the control variables and new correlated errors. In addition, the GEN_BE v2.0 code is employed to diagnose error parameter statistics for chemical species, which shows that it is a tool flexible enough to implement new control variables. While the generation of the background errors statistics code was first developed for atmospheric research, the new version (GEN_BE v2.0) can be easily applied to other domains of science and chosen to diagnose and model B. Initially developed for variational data assimilation, the model of the B matrix may be useful for variational ensemble hybrid methods as well.

Model-based video segmentation for vision-augmented interactive games

NASA Astrophysics Data System (ADS)

Liu, Lurng-Kuo

2000-04-01

This paper presents an architecture and algorithms for model based video object segmentation and its applications to vision augmented interactive game. We are especially interested in real time low cost vision based applications that can be implemented in software in a PC. We use different models for background and a player object. The object segmentation algorithm is performed in two different levels: pixel level and object level. At pixel level, the segmentation algorithm is formulated as a maximizing a posteriori probability (MAP) problem. The statistical likelihood of each pixel is calculated and used in the MAP problem. Object level segmentation is used to improve segmentation quality by utilizing the information about the spatial and temporal extent of the object. The concept of an active region, which is defined based on motion histogram and trajectory prediction, is introduced to indicate the possibility of a video object region for both background and foreground modeling. It also reduces the overall computation complexity. In contrast with other applications, the proposed video object segmentation system is able to create background and foreground models on the fly even without introductory background frames. Furthermore, we apply different rate of self-tuning on the scene model so that the system can adapt to the environment when there is a scene change. We applied the proposed video object segmentation algorithms to several prototype virtual interactive games. In our prototype vision augmented interactive games, a player can immerse himself/herself inside a game and can virtually interact with other animated characters in a real time manner without being constrained by helmets, gloves, special sensing devices, or background environment. The potential applications of the proposed algorithms including human computer gesture interface and object based video coding such as MPEG-4 video coding.

Performance evaluation and modeling of a conformal filter (CF) based real-time standoff hazardous material detection sensor

NASA Astrophysics Data System (ADS)

Nelson, Matthew P.; Tazik, Shawna K.; Bangalore, Arjun S.; Treado, Patrick J.; Klem, Ethan; Temple, Dorota

2017-05-01

Hyperspectral imaging (HSI) systems can provide detection and identification of a variety of targets in the presence of complex backgrounds. However, current generation sensors are typically large, costly to field, do not usually operate in real time and have limited sensitivity and specificity. Despite these shortcomings, HSI-based intelligence has proven to be a valuable tool, thus resulting in increased demand for this type of technology. By moving the next generation of HSI technology into a more adaptive configuration, and a smaller and more cost effective form factor, HSI technologies can help maintain a competitive advantage for the U.S. armed forces as well as local, state and federal law enforcement agencies. Operating near the physical limits of HSI system capability is often necessary and very challenging, but is often enabled by rigorous modeling of detection performance. Specific performance envelopes we consistently strive to improve include: operating under low signal to background conditions; at higher and higher frame rates; and under less than ideal motion control scenarios. An adaptable, low cost, low footprint, standoff sensor architecture we have been maturing includes the use of conformal liquid crystal tunable filters (LCTFs). These Conformal Filters (CFs) are electro-optically tunable, multivariate HSI spectrometers that, when combined with Dual Polarization (DP) optics, produce optimized spectral passbands on demand, which can readily be reconfigured, to discriminate targets from complex backgrounds in real-time. With DARPA support, ChemImage Sensor Systems (CISS™) in collaboration with Research Triangle Institute (RTI) International are developing a novel, real-time, adaptable, compressive sensing short-wave infrared (SWIR) hyperspectral imaging technology called the Reconfigurable Conformal Imaging Sensor (RCIS) based on DP-CF technology. RCIS will address many shortcomings of current generation systems and offer improvements in operational agility and detection performance, while addressing sensor weight, form factor and cost needs. This paper discusses recent test and performance modeling results of a RCIS breadboard apparatus.

Understanding Uncertainties and Biases in Jet Quenching in High-Energy Nucleus-Nucleus Collisions

NASA Astrophysics Data System (ADS)

Heinz, Matthias

2017-09-01

Jets are the collimated streams of particles resulting from hard scattering in the initial state of high-energy collisions. In heavy-ion collisions, jets interact with the quark-gluon plasma (QGP) before freezeout, providing a probe into the internal structure and properties of the QGP. In order to study jets, background must be subtracted from the measured event, potentially introducing a bias. We aim to understand quantify this subtraction bias. PYTHIA, a library to simulate pure jet events, is used to simulate a model for a signature with one pure jet (a photon) and one quenched jet, where all quenched particle momenta are reduced by the same fraction. Background for the event is simulated using multiplicity values generated by the TRENTO initial state model of heavy-ion collisions fed into a thermal model from which to sample particle types and a 3-dimensional Boltzmann distribution from which to sample particle momenta. Data from the simulated events is used to train a statistical model, which computes a posterior distribution of the quench factor for a data set. The model was tested first on pure jet events and later on full events including the background. This model will allow for a quantitative determination of biases induced by various methods of background subtraction. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Structural models used in real-time biosurveillance outbreak detection and outbreak curve isolation from noisy background morbidity levels

PubMed Central

Cheng, Karen Elizabeth; Crary, David J; Ray, Jaideep; Safta, Cosmin

2013-01-01

Objective We discuss the use of structural models for the analysis of biosurveillance related data. Methods and results Using a combination of real and simulated data, we have constructed a data set that represents a plausible time series resulting from surveillance of a large scale bioterrorist anthrax attack in Miami. We discuss the performance of anomaly detection with structural models for these data using receiver operating characteristic (ROC) and activity monitoring operating characteristic (AMOC) analysis. In addition, we show that these techniques provide a method for predicting the level of the outbreak valid for approximately 2 weeks, post-alarm. Conclusions Structural models provide an effective tool for the analysis of biosurveillance data, in particular for time series with noisy, non-stationary background and missing data. PMID:23037798

Statistics for the Relative Detectability of Chemicals in Weak Gaseous Plumes in LWIR Hyperspectral Imagery

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

Metoyer, Candace N.; Walsh, Stephen J.; Tardiff, Mark F.

2008-10-30

The detection and identification of weak gaseous plumes using thermal imaging data is complicated by many factors. These include variability due to atmosphere, ground and plume temperature, and background clutter. This paper presents an analysis of one formulation of the physics-based model that describes the at-sensor observed radiance. The motivating question for the analyses performed in this paper is as follows. Given a set of backgrounds, is there a way to predict the background over which the probability of detecting a given chemical will be the highest? Two statistics were developed to address this question. These statistics incorporate data frommore » the long-wave infrared band to predict the background over which chemical detectability will be the highest. These statistics can be computed prior to data collection. As a preliminary exploration into the predictive ability of these statistics, analyses were performed on synthetic hyperspectral images. Each image contained one chemical (either carbon tetrachloride or ammonia) spread across six distinct background types. The statistics were used to generate predictions for the background ranks. Then, the predicted ranks were compared to the empirical ranks obtained from the analyses of the synthetic images. For the simplified images under consideration, the predicted and empirical ranks showed a promising amount of agreement. One statistic accurately predicted the best and worst background for detection in all of the images. Future work may include explorations of more complicated plume ingredients, background types, and noise structures.« less

Enhanced terahertz imaging system performance analysis and design tool for concealed weapon identification

NASA Astrophysics Data System (ADS)

Murrill, Steven R.; Franck, Charmaine C.; Espinola, Richard L.; Petkie, Douglas T.; De Lucia, Frank C.; Jacobs, Eddie L.

2011-11-01

The U.S. Army Research Laboratory (ARL) and the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD) have developed a terahertz-band imaging system performance model/tool for detection and identification of concealed weaponry. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, and for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security & Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). This paper will provide a comprehensive review of an enhanced, user-friendly, Windows-executable, terahertz-band imaging system performance analysis and design tool that now includes additional features such as a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures. This newly enhanced THz imaging system design tool is an extension of the advanced THz imaging system performance model that was developed under the Defense Advanced Research Project Agency's (DARPA) Terahertz Imaging Focal-Plane Technology (TIFT) program. This paper will also provide example system component (active-illumination source and detector) trade-study analyses using the new features of this user-friendly THz imaging system performance analysis and design tool.

Formaldehyde Production From Isoprene Oxidation Across NOx Regimes

NASA Technical Reports Server (NTRS)

Wolfe, G. M.; Kaiser, J.; Hanisco, T. F.; Keutsch, F. N.; de Gouw, J. A.; Gilman, J. B.; Graus, M.; Hatch, C. D.; Holloway, J.; Horowitz, L. W.;

Formaldehyde production from isoprene oxidation across NOx regimes

PubMed Central

Wolfe, G. M.; Kaiser, J.; Hanisco, T. F.; Keutsch, F. N.; de Gouw, J. A.; Gilman, J. B.; Graus, M.; Hatch, C. D.; Holloway, J.; Horowitz, L. W.; Lee, B. H.; Lerner, B. M.; Lopez-Hilifiker, F.; Mao, J.; Marvin, M. R.; Peischl, J.; Pollack, I. B.; Roberts, J. M.; Ryerson, T. B.; Thornton, J. A.; Veres, P. R.; Warneke, C.

2018-01-01

The chemical link between isoprene and formaldehyde (HCHO) is a strong, non-linear function of NOx (= NO + NO2). This relationship is a linchpin for top-down isoprene emission inventory verification from orbital HCHO column observations. It is also a benchmark for overall photochemical mechanism performance with regard to VOC oxidation. Using a comprehensive suite of airborne in situ observations over the Southeast U.S., we quantify HCHO production across the urban-rural spectrum. Analysis of isoprene and its major first-generation oxidation products allows us to define both a “prompt” yield of HCHO (molecules of HCHO produced per molecule of freshly-emitted isoprene) and the background HCHO mixing ratio (from oxidation of longer-lived hydrocarbons). Over the range of observed NOx values (roughly 0.1 – 2 ppbv), the prompt yield increases by a factor of 3 (from 0.3 to 0.9 ppbv ppbv−1), while background HCHO increases by a factor of 2 (from 1.6 to 3.3 ppbv). We apply the same method to evaluate the performance of both a global chemical transport model (AM3) and a measurement-constrained 0-D steady state box model. Both models reproduce the NOx dependence of the prompt HCHO yield, illustrating that models with updated isoprene oxidation mechanisms can adequately capture the link between HCHO and recent isoprene emissions. On the other hand, both models under-estimate background HCHO mixing ratios, suggesting missing HCHO precursors, inadequate representation of later-generation isoprene degradation and/or under-estimated hydroxyl radical concentrations. Detailed process rates from the box model simulation demonstrate a 3-fold increase in HCHO production across the range of observed NOx values, driven by a 100% increase in OH and a 40% increase in branching of organic peroxy radical reactions to produce HCHO. PMID:29619046

Formaldehyde production from isoprene oxidation across NOx regimes.

PubMed

Wolfe, G M; Kaiser, J; Hanisco, T F; Keutsch, F N; de Gouw, J A; Gilman, J B; Graus, M; Hatch, C D; Holloway, J; Horowitz, L W; Lee, B H; Lerner, B M; Lopez-Hilifiker, F; Mao, J; Marvin, M R; Peischl, J; Pollack, I B; Roberts, J M; Ryerson, T B; Thornton, J A; Veres, P R; Warneke, C

2016-01-01

The chemical link between isoprene and formaldehyde (HCHO) is a strong, non-linear function of NO x (= NO + NO 2 ). This relationship is a linchpin for top-down isoprene emission inventory verification from orbital HCHO column observations. It is also a benchmark for overall photochemical mechanism performance with regard to VOC oxidation. Using a comprehensive suite of airborne in situ observations over the Southeast U.S., we quantify HCHO production across the urban-rural spectrum. Analysis of isoprene and its major first-generation oxidation products allows us to define both a "prompt" yield of HCHO (molecules of HCHO produced per molecule of freshly-emitted isoprene) and the background HCHO mixing ratio (from oxidation of longer-lived hydrocarbons). Over the range of observed NO x values (roughly 0.1 - 2 ppbv), the prompt yield increases by a factor of 3 (from 0.3 to 0.9 ppbv ppbv -1 ), while background HCHO increases by a factor of 2 (from 1.6 to 3.3 ppbv). We apply the same method to evaluate the performance of both a global chemical transport model (AM3) and a measurement-constrained 0-D steady state box model. Both models reproduce the NO x dependence of the prompt HCHO yield, illustrating that models with updated isoprene oxidation mechanisms can adequately capture the link between HCHO and recent isoprene emissions. On the other hand, both models under-estimate background HCHO mixing ratios, suggesting missing HCHO precursors, inadequate representation of later-generation isoprene degradation and/or under-estimated hydroxyl radical concentrations. Detailed process rates from the box model simulation demonstrate a 3-fold increase in HCHO production across the range of observed NO x values, driven by a 100% increase in OH and a 40% increase in branching of organic peroxy radical reactions to produce HCHO.

Path loss modeling and performance trade-off study for short-range non-line-of-sight ultraviolet communications.

PubMed

Chen, Gang; Xu, Zhengyuan; Ding, Haipeng; Sadler, Brian

2009-03-02

We consider outdoor non-line-of-sight deep ultraviolet (UV) solar blind communications at ranges up to 100 m, with different transmitter and receiver geometries. We propose an empirical channel path loss model, and fit the model based on extensive measurements. We observe range-dependent power decay with a power exponent that varies from 0.4 to 2.4 with varying geometry. We compare with the single scattering model, and show that the single scattering assumption leads to a model that is not accurate for small apex angles. Our model is then used to study fundamental communication system performance trade-offs among transmitted optical power, range, link geometry, data rate, and bit error rate. Both weak and strong solar background radiation scenarios are considered to bound detection performance. These results provide guidelines to system design.

Demographic faultlines: a meta-analysis of the literature.

PubMed

Thatcher, Sherry M B; Patel, Pankaj C

2011-11-01

We propose and test a theoretical model focusing on antecedents and consequences of demographic faultlines. We also posit contingencies that affect overall team dynamics in the context of demographic faultlines, such as the study setting and performance measurement. Using meta-analysis structural equation modeling with a final data set consisting of 311 data points (i.e., k [predictor-criterion relationships]), from 39 studies that were obtained from 36 papers with a total sample size of 24,388 individuals in 4,366 teams, we found that sex and racial diversity increased demographic faultline strength more than did diversity on the attributes of functional background, educational background, age, and tenure. Demographic faultline strength was found to increase task and relationship conflict as well as decrease team cohesion. Furthermore, although demographic faultline strength decreased both team satisfaction and team performance, there was a stronger decrease in team performance than in team satisfaction. The strength of these relationships increased when the study was conducted in the lab rather than in the field. We describe the theoretical and practical implications of these findings for advancing the study of faultlines. (c) 2011 APA, all rights reserved.

Investigation of the hard x-ray background in backlit pinhole imagers.

PubMed

Fein, J R; Peebles, J L; Keiter, P A; Holloway, J P; Klein, S R; Kuranz, C C; Manuel, M J-E; Drake, R P

2014-11-01

Hard x-rays from laser-produced hot electrons (>10 keV) in backlit pinhole imagers can give rise to a background signal that decreases signal dynamic range in radiographs. Consequently, significant uncertainties are introduced to the measured optical depth of imaged plasmas. Past experiments have demonstrated that hard x-rays are produced when hot electrons interact with the high-Z pinhole substrate used to collimate the softer He-α x-ray source. Results are presented from recent experiments performed on the OMEGA-60 laser to further study the production of hard x-rays in the pinhole substrate and how these x-rays contribute to the background signal in radiographs. Radiographic image plates measured hard x-rays from pinhole imagers with Mo, Sn, and Ta pinhole substrates. The variation in background signal between pinhole substrates provides evidence that much of this background comes from x-rays produced in the pinhole substrate itself. A Monte Carlo electron transport code was used to model x-ray production from hot electrons interacting in the pinhole substrate, as well as to model measurements of x-rays from the irradiated side of the targets, recorded by a bremsstrahlung x-ray spectrometer. Inconsistencies in inferred hot electron distributions between the different pinhole substrate materials demonstrate that additional sources of hot electrons beyond those modeled may produce hard x-rays in the pinhole substrate.

Investigation of the hard x-ray background in backlit pinhole imagers

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

Fein, J. R., E-mail: jrfein@umich.edu; Holloway, J. P.; Peebles, J. L.

Hard x-rays from laser-produced hot electrons (>10 keV) in backlit pinhole imagers can give rise to a background signal that decreases signal dynamic range in radiographs. Consequently, significant uncertainties are introduced to the measured optical depth of imaged plasmas. Past experiments have demonstrated that hard x-rays are produced when hot electrons interact with the high-Z pinhole substrate used to collimate the softer He-α x-ray source. Results are presented from recent experiments performed on the OMEGA-60 laser to further study the production of hard x-rays in the pinhole substrate and how these x-rays contribute to the background signal in radiographs. Radiographicmore » image plates measured hard x-rays from pinhole imagers with Mo, Sn, and Ta pinhole substrates. The variation in background signal between pinhole substrates provides evidence that much of this background comes from x-rays produced in the pinhole substrate itself. A Monte Carlo electron transport code was used to model x-ray production from hot electrons interacting in the pinhole substrate, as well as to model measurements of x-rays from the irradiated side of the targets, recorded by a bremsstrahlung x-ray spectrometer. Inconsistencies in inferred hot electron distributions between the different pinhole substrate materials demonstrate that additional sources of hot electrons beyond those modeled may produce hard x-rays in the pinhole substrate.« less

Integration of Irma tactical scene generator into directed-energy weapon system simulation

NASA Astrophysics Data System (ADS)

Owens, Monte A.; Cole, Madison B., III; Laine, Mark R.

2003-08-01

Integrated high-fidelity physics-based simulations that include engagement models, image generation, electro-optical hardware models and control system algorithms have previously been developed by Boeing-SVS for various tracking and pointing systems. These simulations, however, had always used images with featureless or random backgrounds and simple target geometries. With the requirement to engage tactical ground targets in the presence of cluttered backgrounds, a new type of scene generation tool was required to fully evaluate system performance in this challenging environment. To answer this need, Irma was integrated into the existing suite of Boeing-SVS simulation tools, allowing scene generation capabilities with unprecedented realism. Irma is a US Air Force research tool used for high-resolution rendering and prediction of target and background signatures. The MATLAB/Simulink-based simulation achieves closed-loop tracking by running track algorithms on the Irma-generated images, processing the track errors through optical control algorithms, and moving simulated electro-optical elements. The geometry of these elements determines the sensor orientation with respect to the Irma database containing the three-dimensional background and target models. This orientation is dynamically passed to Irma through a Simulink S-function to generate the next image. This integrated simulation provides a test-bed for development and evaluation of tracking and control algorithms against representative images including complex background environments and realistic targets calibrated using field measurements.

Infrared images target detection based on background modeling in the discrete cosine domain

NASA Astrophysics Data System (ADS)

Ye, Han; Pei, Jihong

2018-02-01

Background modeling is the critical technology to detect the moving target for video surveillance. Most background modeling techniques are aimed at land monitoring and operated in the spatial domain. A background establishment becomes difficult when the scene is a complex fluctuating sea surface. In this paper, the background stability and separability between target are analyzed deeply in the discrete cosine transform (DCT) domain, on this basis, we propose a background modeling method. The proposed method models each frequency point as a single Gaussian model to represent background, and the target is extracted by suppressing the background coefficients. Experimental results show that our approach can establish an accurate background model for seawater, and the detection results outperform other background modeling methods in the spatial domain.

Comparison of low-contrast detectability between two CT reconstruction algorithms using voxel-based 3D printed textured phantoms.

PubMed

Solomon, Justin; Ba, Alexandre; Bochud, François; Samei, Ehsan

2016-12-01

To use novel voxel-based 3D printed textured phantoms in order to compare low-contrast detectability between two reconstruction algorithms, FBP (filtered-backprojection) and SAFIRE (sinogram affirmed iterative reconstruction) and determine what impact background texture (i.e., anatomical noise) has on estimating the dose reduction potential of SAFIRE. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find CLB textures that were reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, four cylindrical phantoms (Textures A-C and uniform, 165 mm in diameter, and 30 mm height) were designed, each containing 20 low-contrast spherical signals (6 mm diameter at nominal contrast levels of ∼3.2, 5.2, 7.2, 10, and 14 HU with four repeats per signal). The phantoms were voxelized and input into a commercial multimaterial 3D printer (Object Connex 350), with custom software for voxel-based printing (using principles of digital dithering). Images of the textured phantoms and a corresponding uniform phantom were acquired at six radiation dose levels (SOMATOM Flash, Siemens Healthcare) and observer model detection performance (detectability index of a multislice channelized Hotelling observer) was estimated for each condition (5 contrasts × 6 doses × 2 reconstructions × 4 backgrounds = 240 total conditions). A multivariate generalized regression analysis was performed (linear terms, no interactions, random error term, log link function) to assess whether dose, reconstruction algorithm, signal contrast, and background type have statistically significant effects on detectability. Also, fitted curves of detectability (averaged across contrast levels) as a function of dose were constructed for each reconstruction algorithm and background texture. FBP and SAFIRE were compared for each background type to determine the improvement in detectability at a given dose, and the reduced dose at which SAFIRE had equivalent performance compared to FBP at 100% dose. Detectability increased with increasing radiation dose (P = 2.7 × 10 -59 ) and contrast level (P = 2.2 × 10 -86 ) and was higher in the uniform phantom compared to the textured phantoms (P = 6.9 × 10 -51 ). Overall, SAFIRE had higher d' compared to FBP (P = 0.02). The estimated dose reduction potential of SAFIRE was found to be 8%, 10%, 27%, and 8% for Texture-A, Texture-B, Texture-C and uniform phantoms. In all background types, detectability was higher with SAFIRE compared to FBP. However, the relative improvement observed from SAFIRE was highly dependent on the complexity of the background texture. Iterative algorithms such as SAFIRE should be assessed in the most realistic context possible.

Airborne Particulate Threat Assessment

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

Patrick Treado; Oksana Klueva; Jeffrey Beckstead

Aerosol threat detection requires the ability to discern between threat agents and ambient background particulate matter (PM) encountered in the environment. To date, Raman imaging technology has been demonstrated as an effective strategy for the assessment of threat agents in the presence of specific, complex backgrounds. Expanding our understanding of the composition of ambient particulate matter background will improve the overall performance of Raman Chemical Imaging (RCI) detection strategies for the autonomous detection of airborne chemical and biological hazards. Improving RCI detection performance is strategic due to its potential to become a widely exploited detection approach by several U.S. governmentmore » agencies. To improve the understanding of the ambient PM background with subsequent improvement in Raman threat detection capability, ChemImage undertook the Airborne Particulate Threat Assessment (APTA) Project in 2005-2008 through a collaborative effort with the National Energy Technology Laboratory (NETL), under cooperative agreement number DE-FC26-05NT42594. During Phase 1 of the program, a novel PM classification based on molecular composition was developed based on a comprehensive review of the scientific literature. In addition, testing protocols were developed for ambient PM characterization. A signature database was developed based on a variety of microanalytical techniques, including scanning electron microscopy, FT-IR microspectroscopy, optical microscopy, fluorescence and Raman chemical imaging techniques. An automated particle integrated collector and detector (APICD) prototype was developed for automated collection, deposition and detection of biothreat agents in background PM. During Phase 2 of the program, ChemImage continued to refine the understanding of ambient background composition. Additionally, ChemImage enhanced the APICD to provide improved autonomy, sensitivity and specificity. Deliverables included a Final Report detailing our findings and APICD Gen II subsystems for automated collection, deposition and detection of ambient particulate matter. Key findings from the APTA Program include: Ambient biological PM taxonomy; Demonstration of key subsystems needed for autonomous bioaerosol detection; System design; Efficient electrostatic collection; Automated bioagent recognition; Raman analysis performance validating Td<9 sec; Efficient collection surface regeneration; and Development of a quantitative bioaerosol defection model. The objective of the APTA program was to advance the state of our knowledge of ambient background PM composition. Operation of an automated aerosol detection system was enhanced by a more accurate assessment of background variability, especially for sensitive and specific sensing strategies like Raman detection that are background-limited in performance. Based on this improved knowledge of background, the overall threat detection performance of Raman sensors was improved.« less

Training Professionals to Implement a Group Model for Alleviating Loneliness among Older People--10-Year Follow-Up Study

ERIC Educational Resources Information Center

Jansson, Anu H.; Savikko, Niina M.; Pitkälä, Kaisu H.

2018-01-01

Background and objectives: Although randomized controlled trials (RCTs) have been performed to alleviate loneliness among older people, little is known about how they have been implemented, or whether they are effective in real life. Our RCT-based model, "Circle of Friends" (CoF) proved to be effective in improving the wellbeing, health…

LENSED: a code for the forward reconstruction of lenses and sources from strong lensing observations

NASA Astrophysics Data System (ADS)

Tessore, Nicolas; Bellagamba, Fabio; Metcalf, R. Benton

2016-12-01

Robust modelling of strong lensing systems is fundamental to exploit the information they contain about the distribution of matter in galaxies and clusters. In this work, we present LENSED, a new code which performs forward parametric modelling of strong lenses. LENSED takes advantage of a massively parallel ray-tracing kernel to perform the necessary calculations on a modern graphics processing unit (GPU). This makes the precise rendering of the background lensed sources much faster, and allows the simultaneous optimization of tens of parameters for the selected model. With a single run, the code is able to obtain the full posterior probability distribution for the lens light, the mass distribution and the background source at the same time. LENSED is first tested on mock images which reproduce realistic space-based observations of lensing systems. In this way, we show that it is able to recover unbiased estimates of the lens parameters, even when the sources do not follow exactly the assumed model. Then, we apply it to a subsample of the Sloan Lens ACS Survey lenses, in order to demonstrate its use on real data. The results generally agree with the literature, and highlight the flexibility and robustness of the algorithm.

Beyond the audiogram: application of models of auditory fitness for duty to assess communication in the real world.

PubMed

Dubno, Judy R

2018-05-01

This manuscript provides a Commentary on a paper published in the current issue of the International Journal of Audiology and the companion paper published in Ear and Hearing by Soli et al. These papers report background, rationale and results of a novel modelling approach to assess "auditory fitness for duty," or an individual's ability to perform hearing-critical tasks related to their job, based on their likelihood of effective speech communication in the listening environment in which the task is performed.

Design, fabrication, and implementation of voxel-based 3D printed textured phantoms for task-based image quality assessment in CT

NASA Astrophysics Data System (ADS)

Solomon, Justin; Ba, Alexandre; Diao, Andrew; Lo, Joseph; Bier, Elianna; Bochud, François; Gehm, Michael; Samei, Ehsan

2016-03-01

In x-ray computed tomography (CT), task-based image quality studies are typically performed using uniform background phantoms with low-contrast signals. Such studies may have limited clinical relevancy for modern non-linear CT systems due to possible influence of background texture on image quality. The purpose of this study was to design and implement anatomically informed textured phantoms for task-based assessment of low-contrast detection. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find the CLB parameters that were most reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, a cylinder phantom (165 mm in diameter and 30 mm height) was designed, containing 20 low-contrast spherical signals (6 mm in diameter at targeted contrast levels of ~3.2, 5.2, 7.2, 10, and 14 HU, 4 repeats per signal). The phantom was voxelized and input into a commercial multi-material 3D printer (Object Connex 350), with custom software for voxel-based printing. Using principles of digital half-toning and dithering, the 3D printer was programmed to distribute two base materials (VeroWhite and TangoPlus, nominal voxel size of 42x84x30 microns) to achieve the targeted spatial distribution of x-ray attenuation properties. The phantom was used for task-based image quality assessment of a clinically available iterative reconstruction algorithm (Sinogram Affirmed Iterative Reconstruction, SAFIRE) using a channelized Hotelling observer paradigm. Images of the textured phantom and a corresponding uniform phantom were acquired at six dose levels and observer model performance was estimated for each condition (5 contrasts x 6 doses x 2 reconstructions x 2 backgrounds = 120 total conditions). Based on the observer model results, the dose reduction potential of SAFIRE was computed and compared between the uniform and textured phantom. The dose reduction potential of SAFIRE was found to be 23% based on the uniform phantom and 17% based on the textured phantom. This discrepancy demonstrates the need to consider background texture when assessing non-linear reconstruction algorithms.

Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

PubMed

de Gennaro, Gianluigi; Trizio, Livia; Di Gilio, Alessia; Pey, Jorge; Pérez, Noemi; Cusack, Michael; Alastuey, Andrés; Querol, Xavier

2013-10-01

An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies. © 2013 Elsevier B.V. All rights reserved.

Generalized Background Error covariance matrix model (GEN_BE v2.0)

NASA Astrophysics Data System (ADS)

Descombes, G.; Auligné, T.; Vandenberghe, F.; Barker, D. M.

2014-07-01

The specification of state background error statistics is a key component of data assimilation since it affects the impact observations will have on the analysis. In the variational data assimilation approach, applied in geophysical sciences, the dimensions of the background error covariance matrix (B) are usually too large to be explicitly determined and B needs to be modeled. Recent efforts to include new variables in the analysis such as cloud parameters and chemical species have required the development of the code to GENerate the Background Errors (GEN_BE) version 2.0 for the Weather Research and Forecasting (WRF) community model to allow for a simpler, flexible, robust, and community-oriented framework that gathers methods used by meteorological operational centers and researchers. We present the advantages of this new design for the data assimilation community by performing benchmarks and showing some of the new features on data assimilation test cases. As data assimilation for clouds remains a challenge, we present a multivariate approach that includes hydrometeors in the control variables and new correlated errors. In addition, the GEN_BE v2.0 code is employed to diagnose error parameter statistics for chemical species, which shows that it is a tool flexible enough to involve new control variables. While the generation of the background errors statistics code has been first developed for atmospheric research, the new version (GEN_BE v2.0) can be easily extended to other domains of science and be chosen as a testbed for diagnostic and new modeling of B. Initially developed for variational data assimilation, the model of the B matrix may be useful for variational ensemble hybrid methods as well.

Robotic and endoscopic transoral thyroidectomy: feasibility and description of the technique in the cadaveric model

PubMed Central

Kahramangil, Bora; Mohsin, Khuzema; Alzahrani, Hassan; Bu Ali, Daniah; Tausif, Syed; Kang, Sang-Wook; Kandil, Emad

2017-01-01

Background Numerous new approaches have been described over the years to improve the cosmetic outcomes of thyroid surgery. Transoral approach is a new technique that aims to achieve superior cosmetic outcomes by concealing the incision in the oral cavity. Methods Transoral thyroidectomy through vestibular approach was performed in two institutions on cadaveric models. Procedure was performed endoscopically in one institution, while the robotic technique was utilized at the other. Results Transoral thyroidectomy was successfully performed at both institutions with robotic and endoscopic techniques. All vital structures were identified and preserved. Conclusions Transoral thyroidectomy has been performed in animal and cadaveric models, as well as in some clinical studies. Our initial experience indicates the feasibility of this approach. More clinical studies are required to elucidate its full utility. PMID:29302476

Online Homework Put to the Test: A Report on the Impact of Two Online Learning Systems on Student Performance in General Chemistry

ERIC Educational Resources Information Center

Eichler, Jack F.; Peeples, Junelyn

2013-01-01

Two different online homework systems were administered to students in a first-quarter general chemistry course. This study used a multiple regression model to control for the students' academic and socioeconomic background, and it was found that students who completed the online homework activities performed significantly better on a common…

Complete Hard X-Ray Surveys, AGN Luminosity Functions and the X-Ray Background

NASA Technical Reports Server (NTRS)

Tueller, Jack

2011-01-01

AGN are believed to make up most of the Cosmic X-Ray Background (CXB) above a few keV, but this background cannot be fully resolved at energies less than 10 keV due to absorption. The Swift/BAT and INTEGRAL missions are performing the first complete hard x-ray surveys with minimal bias due to absorption. The most recent results for both missions will be presented. Although the fraction of the CXB resolved by these surveys is small, it is possible to derive unbiased number counts and luminosity functions for AGN in the local universe. The survey energy range from 15-150 keV contains the important reflection and cutoff spectral features dominate the shape of the AGN contribution to the CXB. Average spectral characteristics of survey detected AGN will be presented and compared with model distributions. The numbers of hard x-ray blazars detected in these surveys are finally sufficient to estimate this important component's contribution the cosmic background. Constraints on CXB models and their significance will be discussed.

Advances in remote sensing of forest background reflectance with MODIS BRDF data across Europe

NASA Astrophysics Data System (ADS)

Pisek, Jan; Alikas, Krista; Lukeš, Petr; Lundin, Lars; Kobler, Johannes; Santos-Reis, Margarida; Chen, Jing

2017-04-01

Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. However, systematic reflectance data covering different site types are almost missing. This presentation will focus on the validation of background reflectance retrievals using MODIS bidirectional reflectance distribution function (BRDF) data against in-situ understory reflectance measurements covering a diverse set of long-term ecological research (LTER) sites distributed along a wide latitudinal and elevational gradient across Europe: protected coniferous blueberry forest in Sweden, karst forest system in Austria, floodplain broadleaf forest and coniferous forest in the Czech Republic, and Mediterranean agro-sylvo-pastoral woodlands in Portugal. The multi-angle remote sensing data-based methodology was originally developed for the forest background signal retrieval in a boreal region. Here its performance will be tested across diverse forest conditions and moments during the growing season, which is a necessary step before conducting extensive mapping over forested areas. The results can be also used as an input for improved modeling of local carbon and energy fluxes.

Figure-Ground Segmentation Using Factor Graphs

PubMed Central

Shen, Huiying; Coughlan, James; Ivanchenko, Volodymyr

2009-01-01

Foreground-background segmentation has recently been applied [26,12] to the detection and segmentation of specific objects or structures of interest from the background as an efficient alternative to techniques such as deformable templates [27]. We introduce a graphical model (i.e. Markov random field)-based formulation of structure-specific figure-ground segmentation based on simple geometric features extracted from an image, such as local configurations of linear features, that are characteristic of the desired figure structure. Our formulation is novel in that it is based on factor graphs, which are graphical models that encode interactions among arbitrary numbers of random variables. The ability of factor graphs to express interactions higher than pairwise order (the highest order encountered in most graphical models used in computer vision) is useful for modeling a variety of pattern recognition problems. In particular, we show how this property makes factor graphs a natural framework for performing grouping and segmentation, and demonstrate that the factor graph framework emerges naturally from a simple maximum entropy model of figure-ground segmentation. We cast our approach in a learning framework, in which the contributions of multiple grouping cues are learned from training data, and apply our framework to the problem of finding printed text in natural scenes. Experimental results are described, including a performance analysis that demonstrates the feasibility of the approach. PMID:20160994

Study of solid state photomultiplier

NASA Technical Reports Server (NTRS)

Hays, K. M.; Laviolette, R. A.

1987-01-01

Available solid state photomultiplier (SSPM) detectors were tested under low-background, low temperature conditions to determine the conditions producing optimal sensitivity in a space-based astronomy system such as a liquid cooled helium telescope in orbit. Detector temperatures varied between 6 and 9 K, with background flux ranging from 10 to the 13th power to less than 10 to the 6th power photons/square cm-s. Measured parameters included quantum efficiency, noise, dark current, and spectral response. Experimental data were reduced, analyzed, and combined with existing data to build the SSPM data base included herein. The results were compared to analytical models of SSPM performance where appropriate models existed. Analytical models presented here were developed to be as consistent with the data base as practicable. Significant differences between the theory and data are described. Some models were developed or updated as a result of this study.

Fitting cosmic microwave background data with cosmic strings and inflation.

PubMed

Bevis, Neil; Hindmarsh, Mark; Kunz, Martin; Urrestilla, Jon

2008-01-18

We perform a multiparameter likelihood analysis to compare measurements of the cosmic microwave background (CMB) power spectra with predictions from models involving cosmic strings. Adding strings to the standard case of a primordial spectrum with power-law tilt ns, we find a 2sigma detection of strings: f10=0.11+/-0.05, where f10 is the fractional contribution made by strings in the temperature power spectrum (at l=10). CMB data give moderate preference to the model ns=1 with cosmic strings over the standard zero-strings model with variable tilt. When additional non-CMB data are incorporated, the two models become on a par. With variable ns and these extra data, we find that f10<0.11, which corresponds to Gmicro<0.7x10(-6) (where micro is the string tension and G is the gravitational constant).

Formaldehyde Production from Isoprene Oxidation Across NOx Regimes

NASA Technical Reports Server (NTRS)

Wolfe, G. M.; Kaiser, J.; Hanisco, T. F.; Keutsch, F. N.; de Gouw, J. A.; Gilman, J. B.; Graus, M.; Hatch, C. D.; Holloway, J.; Horowitz, L. W.;

(Biased) Grading of Students' Performance: Students' Names, Performance Level, and Implicit Attitudes.

PubMed

Bonefeld, Meike; Dickhäuser, Oliver

2018-01-01

Biases in pre-service teachers' evaluations of students' performance may arise due to stereotypes (e.g., the assumption that students with a migrant background have lower potential). This study examines the effects of a migrant background, performance level, and implicit attitudes toward individuals with a migrant background on performance assessment (assigned grades and number of errors counted in a dictation). Pre-service teachers ( N = 203) graded the performance of a student who appeared to have a migrant background statistically significantly worse than that of a student without a migrant background. The differences were more pronounced when the performance level was low and when the pre-service teachers held relatively positive implicit attitudes toward individuals with a migrant background. Interestingly, only performance level had an effect on the number of counted errors. Our results support the assumption that pre-service teachers exhibit bias when grading students with a migrant background in a third-grade level dictation assignment.

(Biased) Grading of Students’ Performance: Students’ Names, Performance Level, and Implicit Attitudes

PubMed Central

Bonefeld, Meike; Dickhäuser, Oliver

2018-01-01

Biases in pre-service teachers’ evaluations of students’ performance may arise due to stereotypes (e.g., the assumption that students with a migrant background have lower potential). This study examines the effects of a migrant background, performance level, and implicit attitudes toward individuals with a migrant background on performance assessment (assigned grades and number of errors counted in a dictation). Pre-service teachers (N = 203) graded the performance of a student who appeared to have a migrant background statistically significantly worse than that of a student without a migrant background. The differences were more pronounced when the performance level was low and when the pre-service teachers held relatively positive implicit attitudes toward individuals with a migrant background. Interestingly, only performance level had an effect on the number of counted errors. Our results support the assumption that pre-service teachers exhibit bias when grading students with a migrant background in a third-grade level dictation assignment. PMID:29867618

Estimating representative background PM2.5 concentration in heavily polluted areas using baseline separation technique and chemical mass balance model

NASA Astrophysics Data System (ADS)

Gao, Shuang; Yang, Wen; Zhang, Hui; Sun, Yanling; Mao, Jian; Ma, Zhenxing; Cong, Zhiyuan; Zhang, Xian; Tian, Shasha; Azzi, Merched; Chen, Li; Bai, Zhipeng

2018-02-01

The determination of background concentration of PM2.5 is important to understand the contribution of local emission sources to total PM2.5 concentration. The purpose of this study was to exam the performance of baseline separation techniques to estimate PM2.5 background concentration. Five separation methods, which included recursive digital filters (Lyne-Hollick, one-parameter algorithm, and Boughton two-parameter algorithm), sliding interval and smoothed minima, were applied to one-year PM2.5 time-series data in two heavily polluted cities, Tianjin and Jinan. To obtain the proper filter parameters and recession constants for the separation techniques, we conducted regression analysis at a background site during the emission reduction period enforced by the Government for the 2014 Asia-Pacific Economic Cooperation (APEC) meeting in Beijing. Background concentrations in Tianjin and Jinan were then estimated by applying the determined filter parameters and recession constants. The chemical mass balance (CMB) model was also applied to ascertain the effectiveness of the new approach. Our results showed that the contribution of background PM concentration to ambient pollution was at a comparable level to the contribution obtained from the previous study. The best performance was achieved using the Boughton two-parameter algorithm. The background concentrations were estimated at (27 ± 2) μg/m3 for the whole year, (34 ± 4) μg/m3 for the heating period (winter), (21 ± 2) μg/m3 for the non-heating period (summer), and (25 ± 2) μg/m3 for the sandstorm period in Tianjin. The corresponding values in Jinan were (30 ± 3) μg/m3, (40 ± 4) μg/m3, (24 ± 5) μg/m3, and (26 ± 2) μg/m3, respectively. The study revealed that these baseline separation techniques are valid for estimating levels of PM2.5 air pollution, and that our proposed method has great potential for estimating the background level of other air pollutants.

COSMIC INFRARED BACKGROUND FLUCTUATIONS AND ZODIACAL LIGHT

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

Arendt, Richard G.; Kashlinsky, A.; Moseley, S. H.

We performed a specific observational test to measure the effect that the zodiacal light can have on measurements of the spatial fluctuations of the near-IR background. Previous estimates of possible fluctuations caused by zodiacal light have often been extrapolated from observations of the thermal emission at longer wavelengths and low angular resolution or from IRAC observations of high-latitude fields where zodiacal light is faint and not strongly varying with time. The new observations analyzed here target the COSMOS field at low ecliptic latitude where the zodiacal light intensity varies by factors of ∼2 over the range of solar elongations atmore » which the field can be observed. We find that the white-noise component of the spatial power spectrum of the background is correlated with the modeled zodiacal light intensity. Roughly half of the measured white noise is correlated with the zodiacal light, but a more detailed interpretation of the white noise is hampered by systematic uncertainties that are evident in the zodiacal light model. At large angular scales (≳100″) where excess power above the white noise is observed, we find no correlation of the power with the modeled intensity of the zodiacal light. This test clearly indicates that the large-scale power in the infrared background is not being caused by the zodiacal light.« less

Probabilistic fusion of stereo with color and contrast for bilayer segmentation.

PubMed

Kolmogorov, Vladimir; Criminisi, Antonio; Blake, Andrew; Cross, Geoffrey; Rother, Carsten

2006-09-01

This paper describes models and algorithms for the real-time segmentation of foreground from background layers in stereo video sequences. Automatic separation of layers from color/contrast or from stereo alone is known to be error-prone. Here, color, contrast, and stereo matching information are fused to infer layers accurately and efficiently. The first algorithm, Layered Dynamic Programming (LDP), solves stereo in an extended six-state space that represents both foreground/background layers and occluded regions. The stereo-match likelihood is then fused with a contrast-sensitive color model that is learned on-the-fly and stereo disparities are obtained by dynamic programming. The second algorithm, Layered Graph Cut (LGC), does not directly solve stereo. Instead, the stereo match likelihood is marginalized over disparities to evaluate foreground and background hypotheses and then fused with a contrast-sensitive color model like the one used in LDP. Segmentation is solved efficiently by ternary graph cut. Both algorithms are evaluated with respect to ground truth data and found to have similar performance, substantially better than either stereo or color/ contrast alone. However, their characteristics with respect to computational efficiency are rather different. The algorithms are demonstrated in the application of background substitution and shown to give good quality composite video output.

Cosmic Infrared Background Fluctuations and Zodiacal Light

NASA Astrophysics Data System (ADS)

Arendt, Richard G.; Kashlinsky, A.; Moseley, S. H.; Mather, J.

2016-06-01

We performed a specific observational test to measure the effect that the zodiacal light can have on measurements of the spatial fluctuations of the near-IR background. Previous estimates of possible fluctuations caused by zodiacal light have often been extrapolated from observations of the thermal emission at longer wavelengths and low angular resolution or from IRAC observations of high-latitude fields where zodiacal light is faint and not strongly varying with time. The new observations analyzed here target the COSMOS field at low ecliptic latitude where the zodiacal light intensity varies by factors of ˜2 over the range of solar elongations at which the field can be observed. We find that the white-noise component of the spatial power spectrum of the background is correlated with the modeled zodiacal light intensity. Roughly half of the measured white noise is correlated with the zodiacal light, but a more detailed interpretation of the white noise is hampered by systematic uncertainties that are evident in the zodiacal light model. At large angular scales (≳100″) where excess power above the white noise is observed, we find no correlation of the power with the modeled intensity of the zodiacal light. This test clearly indicates that the large-scale power in the infrared background is not being caused by the zodiacal light.

Discoveries far from the lamppost with matrix elements and ranking

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

Debnath, Dipsikha; Gainer, James S.; Matchev, Konstantin T.

2015-04-01

The prevalence of null results in searches for new physics at the LHC motivates the effort to make these searches as model-independent as possible. We describe procedures for adapting the Matrix Element Method for situations where the signal hypothesis is not known a priori. We also present general and intuitive approaches for performing analyses and presenting results, which involve the flattening of background distributions using likelihood information. The first flattening method involves ranking events by background matrix element, the second involves quantile binning with respect to likelihood (and other) variables, and the third method involves reweighting histograms by the inversemore » of the background distribution.« less

Gate modulation of proton transport in a nanopore.

PubMed

Mei, Lanju; Yeh, Li-Hsien; Qian, Shizhi

2016-03-14

Proton transport in confined spaces plays a crucial role in many biological processes as well as in modern technological applications, such as fuel cells. To achieve active control of proton conductance, we investigate for the first time the gate modulation of proton transport in a pH-regulated nanopore by a multi-ion model. The model takes into account surface protonation/deprotonation reactions, surface curvature, electroosmotic flow, Stern layer, and electric double layer overlap. The proposed model is validated by good agreement with the existing experimental data on nanopore conductance with and without a gate voltage. The results show that the modulation of proton transport in a nanopore depends on the concentration of the background salt and solution pH. Without background salt, the gated nanopore exhibits an interesting ambipolar conductance behavior when pH is close to the isoelectric point of the dielectric pore material, and the net ionic and proton conductance can be actively regulated with a gate voltage as low as 1 V. The higher the background salt concentration, the lower is the performance of the gate control on the proton transport.

Sixth Graders Investigate Models and Designs through Teacher-Directed and Student-Centered Inquiry Lessons: Effects on Performance and Attitudes

ERIC Educational Resources Information Center

Olsen, Benjamin D.; Rule, Audrey C.

2016-01-01

Science inquiry has been found to be effective with students from diverse backgrounds and varied academic abilities. This study compared student learning, enjoyment, motivation, perceived understanding, and creativity during a science unit on Models and Designs for 38 sixth grade students (20 male, 18 female; 1 Black, 1 Hispanic and 36 White). The…

A Constraints-Led Perspective to Understanding Skill Acquisition and Game Play: A Basis for Integration of Motor Learning Theory and Physical Education Praxis?

ERIC Educational Resources Information Center

Renshaw, Ian; Chow, Jia Yi; Davids, Keith; Hammond, John

2010-01-01

Background: In order to design appropriate environments for performance and learning of movement skills, physical educators need a sound theoretical model of the learner and of processes of learning. In physical education, this type of modelling informs the organisation of learning environments and effective and efficient use of practice time. An…

Achromatic half-wave plate for submillimeter instruments in cosmic microwave background astronomy: experimental characterization.

PubMed

Pisano, Giampaolo; Savini, Giorgio; Ade, Peter A R; Haynes, Vic; Gear, Walter K

2006-09-20

An achromatic half-wave plate (HWP) to be used in millimeter cosmic microwave background (CMB) polarization experiments has been designed, manufactured, and tested. The design is based on the 5-plates Pancharatnam recipe and it works in the frequency range 85-185 GHz. A model has been used to predict the transmission, reflection, absorption, and phase shift as a function of frequency. The HWP has been tested by using coherent radiation from a back-wave oscillator to investigate its modulation efficiency and with incoherent radiation from a polarizing Fourier transform spectrometer (FTS) to explore its frequency behavior. The FTS measurements have been fitted with an optical performance model which is in excellent agreement with the data. A detailed analysis of the data also allows a precise determination of the HWP fast and slow axes in the frequency band of operation. A list of the HWP performance characteristics is reported including estimates of its cross polarization.

Bounds on isocurvature perturbations from cosmic microwave background and large scale structure data.

PubMed

Crotty, Patrick; García-Bellido, Juan; Lesgourgues, Julien; Riazuelo, Alain

2003-10-24

We obtain very stringent bounds on the possible cold dark matter, baryon, and neutrino isocurvature contributions to the primordial fluctuations in the Universe, using recent cosmic microwave background and large scale structure data. Neglecting the possible effects of spatial curvature, tensor perturbations, and reionization, we perform a Bayesian likelihood analysis with nine free parameters, and find that the amplitude of the isocurvature component cannot be larger than about 31% for the cold dark matter mode, 91% for the baryon mode, 76% for the neutrino density mode, and 60% for the neutrino velocity mode, at 2sigma, for uncorrelated models. For correlated adiabatic and isocurvature components, the fraction could be slightly larger. However, the cross-correlation coefficient is strongly constrained, and maximally correlated/anticorrelated models are disfavored. This puts strong bounds on the curvaton model.

Segregation analysis of urothelial cell carcinoma.

PubMed

Aben, Katja K H; Baglietto, Laura; Baffoe-Bonnie, Agnes; Coebergh, Jan-Willem W; Bailey-Wilson, Joan E; Trink, Barry; Verbeek, André L M; Schoenberg, Mark P; Alfred Witjes, J; Kiemeney, Lambertus A

2006-07-01

A family history of urothelial cell carcinoma (UCC) confers an almost two-fold increased risk of developing UCC. It is unknown whether (part of) this aggregation of UCC has a Mendelian background. We performed complex segregation analyses on 1193 families ascertained through a proband with UCC of the bladder, ureter, renal pelvis or urethra, who were newly diagnosed between January 1, 1995 and December 31, 1997 and registered by two population-based cancer registries in the southeastern part of the Netherlands. Data were reported on 10 738 first-degree relatives by postal questionnaire; 101 of these relatives had UCC. All reported occurrences of UCC were verified (if possible) using medical records. Analyses were performed with the S.A.G.E. segregation package. Five restricted models (Mendelian dominant, Mendelian recessive, Mendelian co-dominant, 'no major gene' model and environmental model) were tested against the general unrestricted model. Sex and smoking status were incorporated as covariates. Strong evidence of Mendelian inheritance of UCC through a single major gene was not found in these 1 193 families. However, since none of the Mendelian models could be rejected, an inherited subtype of UCC cannot be excluded. A major gene may segregate in some families but this effect may have been masked in a background of high sporadic incidence. The 'no major gene' (or sporadic) model appeared to be the most parsimonious one to describe the occurrence of UCC in these families.

Advances in Experiment Design for High Performance Aircraft

NASA Technical Reports Server (NTRS)

Morelli, Engene A.

1998-01-01

A general overview and summary of recent advances in experiment design for high performance aircraft is presented, along with results from flight tests. General theoretical background is included, with some discussion of various approaches to maneuver design. Flight test examples from the F-18 High Alpha Research Vehicle (HARV) are used to illustrate applications of the theory. Input forms are compared using Cramer-Rao bounds for the standard errors of estimated model parameters. Directions for future research in experiment design for high performance aircraft are identified.

Characteristics of Quasi-Biennial Oscillation simulation in the Meteorological Research Institute earth system model

NASA Astrophysics Data System (ADS)

Yoshida, K.; Naoe, H.

2016-12-01

Whether climate models drive Quasi-Biennial Oscillation (QBO) appropriately is important to assess QBO impact on climate change such as global warming and solar related variation. However, there were few models generating QBO in the Coupled Model Intercomparison Project Phase 5 (CMIP5). This study focuses on dynamical structure of the QBO and its sensitivity to background wind pattern and model configuration. We present preliminary results of experiments designed by "Towards Improving the QBO in Global Climate Models (QBOi)", which is derived from the Stratosphere-troposphere processes and their role in climate (SPARC), in the Meteorological Research Institute earth system model, MRI-ESM2. The simulations were performed in present-day climate condition, repeated annual cycle condition with various CO2 level and sea surface temperatures, and QBO hindcast. In the present climate simulation, zonal wind in the equatorial stratosphere generally exhibits realistic behavior of the QBO. Equatorial zonal wind variability associated with QBO is overestimated in upper stratosphere and underestimated in lower stratosphere. In the MRI-ESM2, the QBO behavior is mainly driven by gravity wave drag parametrization (GWDP) introduced in Hines (1997). Comparing to reanalyses, shortage of resolved wave forcing is found especially in equatorial lower stratosphere. These discrepancies can be attributed to difference in wave forcing, background wind pattern and model configuration. We intend to show results of additional sensitivity experiments to examine how model configuration and background wind pattern affect resolved wave source, wave propagation characteristics, and QBO behavior.

Habilitation thesis on STT and Higgs searches in WH production (in FRENCH)

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

Sonnenschein, Lars

The detector of the D0 experiment at the proton anti-proton collider Tevatron in Run II is discussed in detail. The performance of the collider and the experiment is presented. Standard model Higgs searches with integrated luminosities between 260 pb -1 and 950 pb -1 and their combination are performed. No deviation from SM background expectation has been observed. Sensitivity prospects at the Tevatron are shown.

Background for protective action recommendations: accidental radioactive contamination of food and animal feeds. Final report

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

Shleien, B.; Schmidt, G.D.; Chiacchierini, R.P.

This report provides background material for the development of FDA's Protective Action Recommendations: Accidental Radioactive Contamination of Food and Animal Feeds. The rationale, dosimetric and agricultural transport models for the Protective Action Guides are presented, along with information on dietary intake. In addition, the document contains a discussion of field methods of analysis of radionuclides deposited on the ground or contained in milk and herbage. Various protective actions are described and evaluated, and a cost-effectiveness analysis for the recommendations performed.

Evaluation of model-based versus non-parametric monaural noise-reduction approaches for hearing aids.

PubMed

Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker

2012-08-01

Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.

Imprints of spherical nontrivial topologies on the cosmic microwave background.

PubMed

Niarchou, Anastasia; Jaffe, Andrew

2007-08-24

The apparent low power in the cosmic microwave background (CMB) temperature anisotropy power spectrum derived from the Wilkinson Microwave Anisotropy Probe motivated us to consider the possibility of a nontrivial topology. We focus on simple spherical multiconnected manifolds and discuss their implications for the CMB in terms of the power spectrum, maps, and the correlation matrix. We perform a Bayesian model comparison against the fiducial best-fit cold dark matter model with a cosmological constant based both on the power spectrum and the correlation matrix to assess their statistical significance. We find that the first-year power spectrum shows a slight preference for the truncated cube space, but the three-year data show no evidence for any of these spaces.

Motivation and Self-Regulated Learning Influences on Middle School Mathematics Achievement

ERIC Educational Resources Information Center

Cleary, Timothy J.; Kitsantas, Anastasia

2017-01-01

The primary purpose of the current study was to use structural equation modeling to examine the relations among background variables (socioeconomic status, prior mathematics achievement), motivation variables (self-efficacy, task interest, school connectedness), self-regulated learning (SRL) behaviors, and performance in middle school mathematics…

Slave systems in verbal short-term memory

PubMed Central

Caplan, David; Waters, Gloria; Howard, David

2013-01-01

Background The model of performance in short-term memory (STM) tasks that has been most influential in cognitive neuropsychological work on deficits of STM is the “working memory” model mainly associated with the work of Alan Baddeley and his colleagues. Aim This paper reviews the model. We examine the development of this theory in studies that account for STM performances in normal (non-brain-damaged) individuals, and then review the application of this theory to neuropsychological cases and specifications, modifications, and extensions of the theory that have been suggested on the basis of these cases. Our approach is to identify the major phenomena that have been discussed and to examine selected papers dealing with those phenomena in some detail. Main Contribution The main contribution is a review of the WM model that includes both normative and neuropsychological data. Conclusions We conclude that the WM model has many inconsistencies and empirical inadequacies, and that cognitive neuropsychologists might benefit from considering other models when they attempt to describe and explain patients’ performances on STM tasks. PMID:24347786

Multilevel latent class casemix modelling: a novel approach to accommodate patient casemix

PubMed Central

2011-01-01

Background Using routinely collected patient data we explore the utility of multilevel latent class (MLLC) models to adjust for patient casemix and rank Trust performance. We contrast this with ranks derived from Trust standardised mortality ratios (SMRs). Methods Patients with colorectal cancer diagnosed between 1998 and 2004 and resident in Northern and Yorkshire regions were identified from the cancer registry database (n = 24,640). Patient age, sex, stage-at-diagnosis (Dukes), and Trust of diagnosis/treatment were extracted. Socioeconomic background was derived using the Townsend Index. Outcome was survival at 3 years after diagnosis. MLLC-modelled and SMR-generated Trust ranks were compared. Results Patients were assigned to two classes of similar size: one with reasonable prognosis (63.0% died within 3 years), and one with better prognosis (39.3% died within 3 years). In patient class one, all patients diagnosed at stage B or C died within 3 years; in patient class two, all patients diagnosed at stage A, B or C survived. Trusts were assigned two classes with 51.3% and 53.2% of patients respectively dying within 3 years. Differences in the ranked Trust performance between the MLLC model and SMRs were all within estimated 95% CIs. Conclusions A novel approach to casemix adjustment is illustrated, ranking Trust performance whilst facilitating the evaluation of factors associated with the patient journey (e.g. treatments) and factors associated with the processes of healthcare delivery (e.g. delays). Further research can demonstrate the value of modelling patient pathways and evaluating healthcare processes across provider institutions. PMID:21362172

Adaptive regularization network based neural modeling paradigm for nonlinear adaptive estimation of cerebral evoked potentials.

PubMed

Zhang, Jian-Hua; Böhme, Johann F

2007-11-01

In this paper we report an adaptive regularization network (ARN) approach to realizing fast blind separation of cerebral evoked potentials (EPs) from background electroencephalogram (EEG) activity with no need to make any explicit assumption on the statistical (or deterministic) signal model. The ARNs are proposed to construct nonlinear EEG and EP signal models. A novel adaptive regularization training (ART) algorithm is proposed to improve the generalization performance of the ARN. Two adaptive neural modeling methods based on the ARN are developed and their implementation and performance analysis are also presented. The computer experiments using simulated and measured visual evoked potential (VEP) data have shown that the proposed ARN modeling paradigm yields computationally efficient and more accurate VEP signal estimation owing to its intrinsic model-free and nonlinear processing characteristics.

Connectionist Models and Parallelism in High Level Vision.

DTIC Science & Technology

1985-01-01

GRANT NUMBER(s) Jerome A. Feldman N00014-82-K-0193 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENt. PROJECT, TASK Computer Science...Connectionist Models 2.1 Background and Overviev % Computer science is just beginning to look seriously at parallel computation : it may turn out that...the chair. The program includes intermediate level networks that compute more complex joints and ones that compute parallelograms in the image. These

Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model

PubMed Central

Eum, Hyukmin; Yoon, Changyong; Lee, Heejin; Park, Mignon

2015-01-01

In this paper, we propose a new method for spotting and recognizing continuous human actions using a vision sensor. The method is comprised of depth-MHI-HOG (DMH), action modeling, action spotting, and recognition. First, to effectively separate the foreground from background, we propose a method called DMH. It includes a standard structure for segmenting images and extracting features by using depth information, MHI, and HOG. Second, action modeling is performed to model various actions using extracted features. The modeling of actions is performed by creating sequences of actions through k-means clustering; these sequences constitute HMM input. Third, a method of action spotting is proposed to filter meaningless actions from continuous actions and to identify precise start and end points of actions. By employing the spotter model, the proposed method improves action recognition performance. Finally, the proposed method recognizes actions based on start and end points. We evaluate recognition performance by employing the proposed method to obtain and compare probabilities by applying input sequences in action models and the spotter model. Through various experiments, we demonstrate that the proposed method is efficient for recognizing continuous human actions in real environments. PMID:25742172

Non-stationary background intensity and Caribbean seismic events

NASA Astrophysics Data System (ADS)

Valmy, Larissa; Vaillant, Jean

2014-05-01

We consider seismic risk calculation based on models with non-stationary background intensity. The aim is to improve predictive strategies in the framework of seismic risk assessment from models describing at best the seismic activity in the Caribbean arc. Appropriate statistical methods are required for analyzing the volumes of data collected. The focus is on calculating earthquakes occurrences probability and analyzing spatiotemporal evolution of these probabilities. The main modeling tool is the point process theory in order to take into account past history prior to a given date. Thus, the seismic event conditional intensity is expressed by means of the background intensity and the self exciting component. This intensity can be interpreted as the expected event rate per time and / or surface unit. The most popular intensity model in seismology is the ETAS (Epidemic Type Aftershock Sequence) model introduced and then generalized by Ogata [2, 3]. We extended this model and performed a comparison of different probability density functions for the triggered event times [4]. We illustrate our model by considering the CDSA (Centre de Données Sismiques des Antilles) catalog [1] which contains more than 7000 seismic events occurred in the Lesser Antilles arc. Statistical tools for testing the background intensity stationarity and for dynamical segmentation are presented. [1] Bengoubou-Valérius M., Bazin S., Bertil D., Beauducel F. and Bosson A. (2008). CDSA: a new seismological data center for the French Lesser Antilles, Seismol. Res. Lett., 79 (1), 90-102. [2] Ogata Y. (1998). Space-time point-process models for earthquake occurrences, Annals of the Institute of Statistical Mathematics, 50 (2), 379-402. [3] Ogata, Y. (2011). Significant improvements of the space-time ETAS model for forecasting of accurate baseline seismicity, Earth, Planets and Space, 63 (3), 217-229. [4] Valmy L. and Vaillant J. (2013). Statistical models in seismology: Lesser Antilles arc case, Bull. Soc. géol. France, 2013, 184 (1), 61-67.

Marine atmospheric effects on electro-optical systems performance

NASA Astrophysics Data System (ADS)

Richter, Juergen H.; Hughes, Herbert G.

1990-09-01

For the past twelve years, a coordinated tri-service effort has been underway in the United States Department of Defense to provide an atmospheric effects assessment capability for existing and planned electro-optical (E0) systems. This paper reviews the exploratory development effort in the US Navy. A key responsibility for the Navy was the development of marine aerosol models. An initial model, the Navy Aerosol Model (NAN), was developed, tested, and transitioned into LOWTRAN 6. A more comprehensive model, the Navy Oceanic Vertical Aerosol Model (NOVAM), has been formulated and is presently undergoing comprehensive evaluation and testing. Marine aerosols and their extinction properties are only one important factor in EO systems performance assessment. For many EO systems applications, an accurate knowledge of marine background radiances is required in addition to considering the effects of the intervening atmosphere. Accordingly, a capability was developed to estimate the apparent sea surface radiance for different sea states and meteorological conditions. Also, an empirical relationship was developed which directly relates apparent mean sea temperature to calculated mean sky temperature. In situ measurements of relevant environmental parameters are essential for real-time EO systems performance assessment. Direct measurement of slant path extinction would be most desirable. This motivated a careful investigation of lidar (light detection and ranging) techniques including improvements to single-ended lidar profile inversion algorithms and development of new lidar techniques such as double-ended and dual-angle configurations. It was concluded that single-ended, single frequency lidars can not be used to infer slant path extinction with an accuracy necessary to make meaningful performance assessments. Other lidar configurations may find limited application in model validation and research efforts. No technique has emerged yet which could be considered ready for shipboard implementation. A shipboard real-time performance assessment system was developed and named PREOS (Performance and Range for EO Systems). PREOS has been incorporated into the Navy's Tactical Environmental Support System (TESS). The present version of PREOS is a first step in accomplishing the complex task of real-time systems performance assessment. Improved target and background models are under development and will be incorporated into TESS when tested and validated. A reliable assessment capability can be used to develop Tactical Decision Aids (TDAs). TDAs permit optimum selection or combination of sensors and estimation of a ship's own vulnerability against hostile systems.

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

Benetti, Micol; Alcaniz, Jailson S.; Landau, Susana J., E-mail: micolbenetti@on.br, E-mail: slandau@df.uba.ar, E-mail: alcaniz@on.br

The hypothesis of the self-induced collapse of the inflaton wave function was proposed as responsible for the emergence of inhomogeneity and anisotropy at all scales. This proposal was studied within an almost de Sitter space-time approximation for the background, which led to a perfect scale-invariant power spectrum, and also for a quasi-de Sitter background, which allows to distinguish departures from the standard approach due to the inclusion of the collapse hypothesis. In this work we perform a Bayesian model comparison for two different choices of the self-induced collapse in a full quasi-de Sitter expansion scenario. In particular, we analyze themore » possibility of detecting the imprint of these collapse schemes at low multipoles of the anisotropy temperature power spectrum of the Cosmic Microwave Background (CMB) using the most recent data provided by the Planck Collaboration. Our results show that one of the two collapse schemes analyzed provides the same Bayesian evidence of the minimal standard cosmological model ΛCDM, while the other scenario is weakly disfavoured with respect to the standard cosmology.« less

Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Waltenberger, W.; Wulz, C.-E.; Dvornikov, O.; Makarenko, V.; Zykunov, V.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Heracleous, N.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Sharma, A.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Bakhshiansohi, H.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Nuttens, C.; Piotrzkowski, K.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Micanovic, S.; Sudic, L.; Susa, T.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Tsiakkouri, D.; Finger, M.; Finger, M.; Carrera Jarrin, E.; El-khateeb, E.; Elgammal, S.; Mohamed, A.; Calpas, B.; Kadastik, M.; Murumaa, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sabes, D.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schomakers, C.; Schulz, J.; Verlage, T.; Weber, H.; Zhukov, V.; Albert, A.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; Hoehle, F.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Müller, T.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Seitz, C.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Poehlsen, J.; Sander, C.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baur, S.; Baus, C.; Berger, J.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Fink, S.; Friese, R.; Giffels, M.; Gilbert, A.; Goldenzweig, P.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Katkov, I.; Kudella, S.; Lobelle Pardo, P.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Filipovic, N.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Bahinipati, S.; Choudhury, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Malhotra, S.; Naimuddin, M.; Nishu, N.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, R.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Kole, G.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhowmik, S.; Dewanjee, R. K.; Ganguly, S.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Rane, A.; Sharma, S.; Behnamian, H.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Fahim, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Chiorboli, M.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Lo Vetere, M.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Nardo, G.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; D'imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Finco, L.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, S.; Lee, S. W.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Kim, H.; Brochero Cifuentes, J. A.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, B.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Lee, H.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Choi, M.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Goh, J.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Komaragiri, J. R.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Magaña Villalba, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Carpinteyro, S.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Di Francesco, A.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Rodrigues Antunes, J.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Vischia, P.; Alexakhin, V.; Belotelov, I.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Chtchipounov, L.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Murzin, V.; Oreshkin, V.; Sulimov, V.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Bylinkin, A.; Chistov, R.; Danilov, M.; Rusinov, V.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Rusakov, S. V.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Perfilov, M.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Blinov, V.; Skovpen, Y.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Barrio Luna, M.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Suárez Andrés, I.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Castiñeiras De Saa, J. R.; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Bloch, P.; Bocci, A.; Bonato, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Di Marco, E.; Dobson, M.; Dorney, B.; du Pree, T.; Duggan, D.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Fartoukh, S.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Girone, M.; Glege, F.; Gulhan, D.; Gundacker, S.; Guthoff, M.; Hammer, J.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kieseler, J.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Kousouris, K.; Krammer, M.; Lange, C.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Merlin, J. A.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Ruan, M.; Sakulin, H.; Sauvan, J. B.; Schäfer, C.; Schwick, C.; Seidel, M.; Sharma, A.; Silva, P.; Sphicas, P.; Steggemann, J.; Stoye, M.; Takahashi, Y.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lecomte, P.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Yang, Y.; Zucchetta, A.; Candelise, V.; Chang, Y. H.; Chen, C. W.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Pozdnyakov, A.; Tong, H. Y. S.; Wu, J. Y.; Yu, S. S.; Kumar, Arun; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Tzeng, Y. M.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Eskut, E.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Tali, B.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Bilmis, S.; Isildak, B.; Karapinar, G.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, E. A.; Yetkin, T.; Cakir, A.; Cankocak, K.; Sen, S.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Burton, D.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Nash, J.; Nikitenko, A.; Pela, J.; Penning, B.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Seez, C.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leslie, D.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Berry, E.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Jesus, O.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Breto, G.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Bravo, C.; Cousins, R.; Everaerts, P.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Saltzberg, D.; Schnaible, C.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Si, W.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Holzner, A.; Klein, D.; Krutelyov, V.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mullin, S. D.; Ovcharova, A.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Apresyan, A.; Bendavid, J.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Lawhorn, J. M.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Azzolini, V.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bein, S.; Diamond, B.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Santra, A.; Weinberg, M.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Jung, K.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Turner, P.; Varelas, N.; Wang, H.; Wu, Z.; Zakaria, M.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Osherson, M.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Bruner, C.; Castle, J.; Forthomme, L.; Kenny, R. P., III; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Apyan, A.; Barbieri, R.; Baty, A.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; Tatar, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bartek, R.; Bloom, K.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Malta Rodrigues, A.; Meier, F.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Hahn, K. A.; Kubik, A.; Kumar, A.; Low, J. F.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Hughes, R.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Mc Donald, J.; Medvedeva, T.; Mei, K.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Miller, D. H.; Neumeister, N.; Schulte, J. F.; Shi, X.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Agapitos, A.; Chou, J. P.; Contreras-Campana, E.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Nash, K.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; De Guio, F.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Sturdy, J.; Belknap, D. A.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

2017-05-01

A search for heavy resonances decaying to a Higgs boson and a vector boson is presented. The analysis is performed using data samples collected in 2015 by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to integrated luminosities of 2.2-2.5 fb-1. The search is performed in channels in which the vector boson decays into leptonic final states (Z → νν, W → ℓν, and Z → ℓℓ, with ℓ = e , μ), while the Higgs boson decays to collimated b quark pairs detected as a single massive jet. The discriminating power of a jet mass requirement and a b jet tagging algorithm are exploited to suppress the standard model backgrounds. The event yields observed in data are consistent with the background expectation. In the context of a theoretical model with a heavy vector triplet, a resonance with mass less than 2 TeV is excluded at 95% confidence level. The results are also interpreted in terms of limits on the parameters of the model, improving on the reach of previous searches.

Solar Research | NREL

Science.gov Websites

the System Advisor Model (SAM) PV engineering PV performance reliability and safety Solar resource Research Photo of a city landscape with a sun in the background. Solar energy research at NREL includes photovoltaics, concentrating solar power, solar grid and systems integration, and market research

Inviting Parents to the Middle: A Proactive Stance for Improving Student Performance.

ERIC Educational Resources Information Center

Peel, Henry A.; Foster, Elizabeth S.

1993-01-01

Explores the challenge of keeping parents involved in their children's education beyond the elementary school years. Suggests the invitational model as proactive approach for keeping parents involved in the lives of their children, particularly during the transition years of middle school education. As background, discusses nature of…

Cognitive Processes in University Learning: A Developmental Framework Using Structural Equation Modelling

ERIC Educational Resources Information Center

Phan, Huy P.

2011-01-01

Background: Both achievement goals and study processing strategies theories have been shown to contribute to the prediction of students' academic performance. Existing research studies (Fenollar, Roman, & Cuestas, 2007; Liem, Lau, & Nie, 2008; Simons, Dewitte, & Lens, 2004) amalgamating these two theoretical orientations in different causal models…

Professional Standards for Physical Education Teachers' Professional Development: Technologies for Performance?

ERIC Educational Resources Information Center

Macdonald, Doune; Mitchell, Jane; Mayer, Diane

2006-01-01

Background: The widespread and diverse models of professional standards for teaching raise questions with respect to the need to provide teachers with a pathway for continuing professional development balanced with the public nature of surveillance and accountability that may accompany standards. Ways of understanding technologies of power in…

Learning Management System with Prediction Model and Course-Content Recommendation Module

ERIC Educational Resources Information Center

Evale, Digna S.

2017-01-01

Aim/Purpose: This study is an attempt to enhance the existing learning management systems today through the integration of technology, particularly with educational data mining and recommendation systems. Background: It utilized five-year historical data to find patterns for predicting student performance in Java Programming to generate…

Psychometric Structure of a Comprehensive Objective Structured Clinical Examination: A Factor Analytic Approach

ERIC Educational Resources Information Center

Volkan, Kevin; Simon, Steven R.; Baker, Harley; Todres, I. David

2004-01-01

Problem Statement and Background: While the psychometric properties of Objective Structured Clinical Examinations (OSCEs) have been studied, their latent structures have not been well characterized. This study examines a factor analytic model of a comprehensive OSCE and addresses implications for measurement of clinical performance. Methods: An…

A corpus of full-text journal articles is a robust evaluation tool for revealing differences in performance of biomedical natural language processing tools

PubMed Central

2012-01-01

Background We introduce the linguistic annotation of a corpus of 97 full-text biomedical publications, known as the Colorado Richly Annotated Full Text (CRAFT) corpus. We further assess the performance of existing tools for performing sentence splitting, tokenization, syntactic parsing, and named entity recognition on this corpus. Results Many biomedical natural language processing systems demonstrated large differences between their previously published results and their performance on the CRAFT corpus when tested with the publicly available models or rule sets. Trainable systems differed widely with respect to their ability to build high-performing models based on this data. Conclusions The finding that some systems were able to train high-performing models based on this corpus is additional evidence, beyond high inter-annotator agreement, that the quality of the CRAFT corpus is high. The overall poor performance of various systems indicates that considerable work needs to be done to enable natural language processing systems to work well when the input is full-text journal articles. The CRAFT corpus provides a valuable resource to the biomedical natural language processing community for evaluation and training of new models for biomedical full text publications. PMID:22901054

Research on Bayes matting algorithm based on Gaussian mixture model

NASA Astrophysics Data System (ADS)

Quan, Wei; Jiang, Shan; Han, Cheng; Zhang, Chao; Jiang, Zhengang

2015-12-01

The digital matting problem is a classical problem of imaging. It aims at separating non-rectangular foreground objects from a background image, and compositing with a new background image. Accurate matting determines the quality of the compositing image. A Bayesian matting Algorithm Based on Gaussian Mixture Model is proposed to solve this matting problem. Firstly, the traditional Bayesian framework is improved by introducing Gaussian mixture model. Then, a weighting factor is added in order to suppress the noises of the compositing images. Finally, the effect is further improved by regulating the user's input. This algorithm is applied to matting jobs of classical images. The results are compared to the traditional Bayesian method. It is shown that our algorithm has better performance in detail such as hair. Our algorithm eliminates the noise well. And it is very effectively in dealing with the kind of work, such as interested objects with intricate boundaries.

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

An enhanced MMW and SMMW/THz imaging system performance prediction and analysis tool for concealed weapon detection and pilotage obstacle avoidance

NASA Astrophysics Data System (ADS)

Murrill, Steven R.; Jacobs, Eddie L.; Franck, Charmaine C.; Petkie, Douglas T.; De Lucia, Frank C.

2015-10-01

The U.S. Army Research Laboratory (ARL) has continued to develop and enhance a millimeter-wave (MMW) and submillimeter- wave (SMMW)/terahertz (THz)-band imaging system performance prediction and analysis tool for both the detection and identification of concealed weaponry, and for pilotage obstacle avoidance. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security and Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). Further development of this tool that includes a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures was reported on at the 2011 SPIE Europe Security and Defence Symposium (Prague). This paper provides a comprehensive review of a newly enhanced MMW and SMMW/THz imaging system analysis and design tool that now includes an improved noise sub-model for more accurate and reliable performance predictions, the capability to account for postcapture image contrast enhancement, and the capability to account for concealment material backscatter with active-illumination- based systems. Present plans for additional expansion of the model's predictive capabilities are also outlined.

Upper Limits on the Stochastic Gravitational-Wave Background from Advanced LIGO's First Observing Run

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Beer, C.; Bejger, M.; Belahcene, I.; Belgin, M.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Biscoveanu, A. S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Campbell, W.; Canepa, M.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Cheeseboro, B. D.; Chen, H. Y.; Chen, Y.; Cheng, H.-P.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M.; Conti, L.; Cooper, S. J.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, E.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Daw, E. J.; Day, B.; Day, R.; De, S.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Devenson, J.; Devine, R. C.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Essick, R. C.; Etienne, Z.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Fernández Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fong, H.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kelley, D. B.; Kennedy, R.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, Whansun; Kim, W.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kirchhoff, R.; Kissel, J. S.; Klein, B.; Kleybolte, L.; Klimenko, S.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Liu, J.; Lockerbie, N. A.; Lombardi, A. L.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lovelace, G.; Lück, H.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGrath, C.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, A.; Miller, B. B.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muniz, E. A. M.; Murray, P. G.; Mytidis, A.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nelemans, G.; Nelson, T. J. N.; Neri, M.; Nery, M.; Neunzert, A.; Newport, J. M.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Rhoades, E.; Ricci, F.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sandberg, V.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheuer, J.; Schlassa, S.; Schmidt, E.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Setyawati, Y.; Shaddock, D. A.; Shaffer, T. J.; Shahriar, M. S.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stevenson, S. P.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tao, D.; Tápai, M.; Taracchini, A.; Taylor, R.; Theeg, T.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Tippens, T.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tomlinson, C.; Tonelli, M.; Tornasi, Z.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tse, M.; Tso, R.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Worden, J.; Wright, J. L.; Wu, D. S.; Wu, G.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, Hang; Yu, Haocun; Yvert, M.; ZadroŻny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S. J.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2017-03-01

A wide variety of astrophysical and cosmological sources are expected to contribute to a stochastic gravitational-wave background. Following the observations of GW150914 and GW151226, the rate and mass of coalescing binary black holes appear to be greater than many previous expectations. As a result, the stochastic background from unresolved compact binary coalescences is expected to be particularly loud. We perform a search for the isotropic stochastic gravitational-wave background using data from Advanced Laser Interferometer Gravitational Wave Observatory's (aLIGO) first observing run. The data display no evidence of a stochastic gravitational-wave signal. We constrain the dimensionless energy density of gravitational waves to be Ω0<1.7 ×10-7 with 95% confidence, assuming a flat energy density spectrum in the most sensitive part of the LIGO band (20-86 Hz). This is a factor of ˜33 times more sensitive than previous measurements. We also constrain arbitrary power-law spectra. Finally, we investigate the implications of this search for the background of binary black holes using an astrophysical model for the background.

Upper Limits on the Stochastic Gravitational-Wave Background from Advanced LIGO's First Observing Run.

PubMed

Abbott, B P; Abbott, R; Abbott, T D; Abernathy, M R; Acernese, F; Ackley, K; Adams, C; Adams, T; Addesso, P; Adhikari, R X; Adya, V B; Affeldt, C; Agathos, M; Agatsuma, K; Aggarwal, N; Aguiar, O D; Aiello, L; Ain, A; Ajith, P; Allen, B; Allocca, A; Altin, P A; Ananyeva, A; Anderson, S B; Anderson, W G; Appert, S; Arai, K; Araya, M C; Areeda, J S; Arnaud, N; Arun, K G; Ascenzi, S; Ashton, G; Ast, M; Aston, S M; Astone, P; Aufmuth, P; Aulbert, C; Avila-Alvarez, A; Babak, S; Bacon, P; Bader, M K M; Baker, P T; Baldaccini, F; Ballardin, G; Ballmer, S W; Barayoga, J C; Barclay, S E; Barish, B C; Barker, D; Barone, F; Barr, B; Barsotti, L; Barsuglia, M; Barta, D; Bartlett, J; Bartos, I; Bassiri, R; Basti, A; Batch, J C; Baune, C; Bavigadda, V; Bazzan, M; Beer, C; Bejger, M; Belahcene, I; Belgin, M; Bell, A S; Berger, B K; Bergmann, G; Berry, C P L; Bersanetti, D; Bertolini, A; Betzwieser, J; Bhagwat, S; Bhandare, R; Bilenko, I A; Billingsley, G; Billman, C R; Birch, J; Birney, R; Birnholtz, O; Biscans, S; Biscoveanu, A S; Bisht, A; Bitossi, M; Biwer, C; Bizouard, M A; Blackburn, J K; Blackman, J; Blair, C D; Blair, D G; Blair, R M; Bloemen, S; Bock, O; Boer, M; Bogaert, G; Bohe, A; Bondu, F; Bonnand, R; Boom, B A; Bork, R; Boschi, V; Bose, S; Bouffanais, Y; Bozzi, A; Bradaschia, C; Brady, P R; Braginsky, V B; Branchesi, M; Brau, J E; Briant, T; Brillet, A; Brinkmann, M; Brisson, V; Brockill, P; Broida, J E; Brooks, A F; Brown, D A; Brown, D D; Brown, N M; Brunett, S; Buchanan, C C; Buikema, A; Bulik, T; Bulten, H J; Buonanno, A; Buskulic, D; Buy, C; Byer, R L; Cabero, M; Cadonati, L; Cagnoli, G; Cahillane, C; Calderón Bustillo, J; Callister, T A; Calloni, E; Camp, J B; Campbell, W; Canepa, M; Cannon, K C; Cao, H; Cao, J; Capano, C D; Capocasa, E; Carbognani, F; Caride, S; Casanueva Diaz, J; Casentini, C; Caudill, S; Cavaglià, M; Cavalier, F; Cavalieri, R; Cella, G; Cepeda, C B; Cerboni Baiardi, L; Cerretani, G; Cesarini, E; Chamberlin, S J; Chan, M; Chao, S; Charlton, P; Chassande-Mottin, E; Cheeseboro, B D; Chen, H Y; Chen, Y; Cheng, H-P; Chincarini, A; Chiummo, A; Chmiel, T; Cho, H S; Cho, M; Chow, J H; Christensen, N; Chu, Q; Chua, A J K; Chua, S; Chung, S; Ciani, G; Clara, F; Clark, J A; Cleva, F; Cocchieri, C; Coccia, E; Cohadon, P-F; Colla, A; Collette, C G; Cominsky, L; Constancio, M; Conti, L; Cooper, S J; Corbitt, T R; Cornish, N; Corsi, A; Cortese, S; Costa, C A; Coughlin, E; Coughlin, M W; Coughlin, S B; Coulon, J-P; Countryman, S T; Couvares, P; Covas, P B; Cowan, E E; Coward, D M; Cowart, M J; Coyne, D C; Coyne, R; Creighton, J D E; Creighton, T D; Cripe, J; Crowder, S G; Cullen, T J; Cumming, A; Cunningham, L; Cuoco, E; Dal Canton, T; Danilishin, S L; D'Antonio, S; Danzmann, K; Dasgupta, A; Da Silva Costa, C F; Dattilo, V; Dave, I; Davier, M; Davies, G S; Davis, D; Daw, E J; Day, B; Day, R; De, S; DeBra, D; Debreczeni, G; Degallaix, J; De Laurentis, M; Deléglise, S; Del Pozzo, W; Denker, T; Dent, T; Dergachev, V; De Rosa, R; DeRosa, R T; DeSalvo, R; Devenson, J; Devine, R C; Dhurandhar, S; Díaz, M C; Di Fiore, L; Di Giovanni, M; Di Girolamo, T; Di Lieto, A; Di Pace, S; Di Palma, I; Di Virgilio, A; Doctor, Z; Dolique, V; Donovan, F; Dooley, K L; Doravari, S; Dorrington, I; Douglas, R; Dovale Álvarez, M; Downes, T P; Drago, M; Drever, R W P; Driggers, J C; Du, Z; Ducrot, M; Dwyer, S E; Edo, T B; Edwards, M C; Effler, A; Eggenstein, H-B; Ehrens, P; Eichholz, J; Eikenberry, S S; Essick, R C; Etienne, Z; Etzel, T; Evans, M; Evans, T M; Everett, R; Factourovich, M; Fafone, V; Fair, H; Fairhurst, S; Fan, X; Farinon, S; Farr, B; Farr, W M; Fauchon-Jones, E J; Favata, M; Fays, M; Fehrmann, H; Fejer, M M; Fernández Galiana, A; Ferrante, I; Ferreira, E C; Ferrini, F; Fidecaro, F; Fiori, I; Fiorucci, D; Fisher, R P; Flaminio, R; Fletcher, M; Fong, H; Forsyth, S S; Fournier, J-D; Frasca, S; Frasconi, F; Frei, Z; Freise, A; Frey, R; Frey, V; Fries, E M; Fritschel, P; Frolov, V V; Fulda, P; Fyffe, M; Gabbard, H; Gadre, B U; Gaebel, S M; Gair, J R; Gammaitoni, L; Gaonkar, S G; Garufi, F; Gaur, G; Gayathri, V; Gehrels, N; Gemme, G; Genin, E; Gennai, A; George, J; Gergely, L; Germain, V; Ghonge, S; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S; Giaime, J A; Giardina, K D; Giazotto, A; Gill, K; Glaefke, A; Goetz, E; Goetz, R; Gondan, L; González, G; Gonzalez Castro, J M; Gopakumar, A; Gorodetsky, M L; Gossan, S E; Gosselin, M; Gouaty, R; Grado, A; Graef, C; Granata, M; Grant, A; Gras, S; Gray, C; Greco, G; Green, A C; Groot, P; Grote, H; Grunewald, S; Guidi, G M; Guo, X; Gupta, A; Gupta, M K; Gushwa, K E; Gustafson, E K; Gustafson, R; Hacker, J J; Hall, B R; Hall, E D; Hammond, G; Haney, M; Hanke, M M; Hanks, J; Hanna, C; Hannam, M D; Hanson, J; Hardwick, T; Harms, J; Harry, G M; Harry, I W; Hart, M J; Hartman, M T; Haster, C-J; Haughian, K; Healy, J; Heidmann, A; Heintze, M C; Heitmann, H; Hello, P; Hemming, G; Hendry, M; Heng, I S; Hennig, J; Henry, J; Heptonstall, A W; Heurs, M; Hild, S; Hoak, D; Hofman, D; Holt, K; Holz, D E; Hopkins, P; Hough, J; Houston, E A; Howell, E J; Hu, Y M; Huerta, E A; Huet, D; Hughey, B; Husa, S; Huttner, S H; Huynh-Dinh, T; Indik, N; Ingram, D R; Inta, R; Isa, H N; Isac, J-M; Isi, M; Isogai, T; Iyer, B R; Izumi, K; Jacqmin, T; Jani, K; Jaranowski, P; Jawahar, S; Jiménez-Forteza, F; Johnson, W W; Jones, D I; Jones, R; Jonker, R J G; Ju, L; Junker, J; Kalaghatgi, C V; Kalogera, V; Kandhasamy, S; Kang, G; Kanner, J B; Karki, S; Karvinen, K S; Kasprzack, M; Katsavounidis, E; Katzman, W; Kaufer, S; Kaur, T; Kawabe, K; Kéfélian, F; Keitel, D; Kelley, D B; Kennedy, R; Key, J S; Khalili, F Y; Khan, I; Khan, S; Khan, Z; Khazanov, E A; Kijbunchoo, N; Kim, Chunglee; Kim, J C; Kim, Whansun; Kim, W; Kim, Y-M; Kimbrell, S J; King, E J; King, P J; Kirchhoff, R; Kissel, J S; Klein, B; Kleybolte, L; Klimenko, S; Koch, P; Koehlenbeck, S M; Koley, S; Kondrashov, V; Kontos, A; Korobko, M; Korth, W Z; Kowalska, I; Kozak, D B; Krämer, C; Kringel, V; Królak, A; Kuehn, G; Kumar, P; Kumar, R; Kuo, L; Kutynia, A; Lackey, B D; Landry, M; Lang, R N; Lange, J; Lantz, B; Lanza, R K; Lartaux-Vollard, A; Lasky, P D; Laxen, M; Lazzarini, A; Lazzaro, C; Leaci, P; Leavey, S; Lebigot, E O; Lee, C H; Lee, H K; Lee, H M; Lee, K; Lehmann, J; Lenon, A; Leonardi, M; Leong, J R; Leroy, N; Letendre, N; Levin, Y; Li, T G F; Libson, A; Littenberg, T B; Liu, J; Lockerbie, N A; Lombardi, A L; London, L T; Lord, J E; Lorenzini, M; Loriette, V; Lormand, M; Losurdo, G; Lough, J D; Lovelace, G; Lück, H; Lundgren, A P; Lynch, R; Ma, Y; Macfoy, S; Machenschalk, B; MacInnis, M; Macleod, D M; Magaña-Sandoval, F; Majorana, E; Maksimovic, I; Malvezzi, V; Man, N; Mandic, V; Mangano, V; Mansell, G L; Manske, M; Mantovani, M; Marchesoni, F; Marion, F; Márka, S; Márka, Z; Markosyan, A S; Maros, E; Martelli, F; Martellini, L; Martin, I W; Martynov, D V; Mason, K; Masserot, A; Massinger, T J; Masso-Reid, M; Mastrogiovanni, S; Matas, A; Matichard, F; Matone, L; Mavalvala, N; Mazumder, N; McCarthy, R; McClelland, D E; McCormick, S; McGrath, C; McGuire, S C; McIntyre, G; McIver, J; McManus, D J; McRae, T; McWilliams, S T; Meacher, D; Meadors, G D; Meidam, J; Melatos, A; Mendell, G; Mendoza-Gandara, D; Mercer, R A; Merilh, E L; Merzougui, M; Meshkov, S; Messenger, C; Messick, C; Metzdorff, R; Meyers, P M; Mezzani, F; Miao, H; Michel, C; Middleton, H; Mikhailov, E E; Milano, L; Miller, A L; Miller, A; Miller, B B; Miller, J; Millhouse, M; Minenkov, Y; Ming, J; Mirshekari, S; Mishra, C; Mitra, S; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Moggi, A; Mohan, M; Mohapatra, S R P; Montani, M; Moore, B C; Moore, C J; Moraru, D; Moreno, G; Morriss, S R; Mours, B; Mow-Lowry, C M; Mueller, G; Muir, A W; Mukherjee, Arunava; Mukherjee, D; Mukherjee, S; Mukund, N; Mullavey, A; Munch, J; Muniz, E A M; Murray, P G; Mytidis, A; Napier, K; Nardecchia, I; Naticchioni, L; Nelemans, G; Nelson, T J N; Neri, M; Nery, M; Neunzert, A; Newport, J M; Newton, G; Nguyen, T T; Nielsen, A B; Nissanke, S; Nitz, A; Noack, A; Nocera, F; Nolting, D; Normandin, M E N; Nuttall, L K; Oberling, J; Ochsner, E; Oelker, E; Ogin, G H; Oh, J J; Oh, S H; Ohme, F; Oliver, M; Oppermann, P; Oram, Richard J; O'Reilly, B; O'Shaughnessy, R; Ottaway, D J; Overmier, H; Owen, B J; Pace, A E; Page, J; Pai, A; Pai, S A; Palamos, J R; Palashov, O; Palomba, C; Pal-Singh, A; Pan, H; Pankow, C; Pannarale, F; Pant, B C; Paoletti, F; Paoli, A; Papa, M A; Paris, H R; Parker, W; Pascucci, D; Pasqualetti, A; Passaquieti, R; Passuello, D; Patricelli, B; Pearlstone, B L; Pedraza, M; Pedurand, R; Pekowsky, L; Pele, A; Penn, S; Perez, C J; Perreca, A; Perri, L M; Pfeiffer, H P; Phelps, M; Piccinni, O J; Pichot, M; Piergiovanni, F; Pierro, V; Pillant, G; Pinard, L; Pinto, I M; Pitkin, M; Poe, M; Poggiani, R; Popolizio, P; Post, A; Powell, J; Prasad, J; Pratt, J W W; Predoi, V; Prestegard, T; Prijatelj, M; Principe, M; Privitera, S; Prodi, G A; Prokhorov, L G; Puncken, O; Punturo, M; Puppo, P; Pürrer, M; Qi, H; Qin, J; Qiu, S; Quetschke, V; Quintero, E A; Quitzow-James, R; Raab, F J; Rabeling, D S; Radkins, H; Raffai, P; Raja, S; Rajan, C; Rakhmanov, M; Rapagnani, P; Raymond, V; Razzano, M; Re, V; Read, J; Regimbau, T; Rei, L; Reid, S; Reitze, D H; Rew, H; Reyes, S D; Rhoades, E; Ricci, F; Riles, K; Rizzo, M; Robertson, N A; Robie, R; Robinet, F; Rocchi, A; Rolland, L; Rollins, J G; Roma, V J; Romano, J D; Romano, R; Romie, J H; Rosińska, D; Rowan, S; Rüdiger, A; Ruggi, P; Ryan, K; Sachdev, S; Sadecki, T; Sadeghian, L; Sakellariadou, M; Salconi, L; Saleem, M; Salemi, F; Samajdar, A; Sammut, L; Sampson, L M; Sanchez, E J; Sandberg, V; Sanders, J R; Sassolas, B; Sathyaprakash, B S; Saulson, P R; Sauter, O; Savage, R L; Sawadsky, A; Schale, P; Scheuer, J; Schlassa, S; Schmidt, E; Schmidt, J; Schmidt, P; Schnabel, R; Schofield, R M S; Schönbeck, A; Schreiber, E; Schuette, D; Schutz, B F; Schwalbe, S G; Scott, J; Scott, S M; Sellers, D; Sengupta, A S; Sentenac, D; Sequino, V; Sergeev, A; Setyawati, Y; Shaddock, D A; Shaffer, T J; Shahriar, M S; Shapiro, B; Shawhan, P; Sheperd, A; Shoemaker, D H; Shoemaker, D M; Siellez, K; Siemens, X; Sieniawska, M; Sigg, D; Silva, A D; Singer, A; Singer, L P; Singh, A; Singh, R; Singhal, A; Sintes, A M; Slagmolen, B J J; Smith, B; Smith, J R; Smith, R J E; Son, E J; Sorazu, B; Sorrentino, F; Souradeep, T; Spencer, A P; Srivastava, A K; Staley, A; Steinke, M; Steinlechner, J; Steinlechner, S; Steinmeyer, D; Stephens, B C; Stevenson, S P; Stone, R; Strain, K A; Straniero, N; Stratta, G; Strigin, S E; Sturani, R; Stuver, A L; Summerscales, T Z; Sun, L; Sunil, S; Sutton, P J; Swinkels, B L; Szczepańczyk, M J; Tacca, M; Talukder, D; Tanner, D B; Tao, D; Tápai, M; Taracchini, A; Taylor, R; Theeg, T; Thomas, E G; Thomas, M; Thomas, P; Thorne, K A; Thrane, E; Tippens, T; Tiwari, S; Tiwari, V; Tokmakov, K V; Toland, K; Tomlinson, C; Tonelli, M; Tornasi, Z; Torrie, C I; Töyrä, D; Travasso, F; Traylor, G; Trifirò, D; Trinastic, J; Tringali, M C; Trozzo, L; Tse, M; Tso, R; Turconi, M; Tuyenbayev, D; Ugolini, D; Unnikrishnan, C S; Urban, A L; Usman, S A; Vahlbruch, H; Vajente, G; Valdes, G; van Bakel, N; van Beuzekom, M; van den Brand, J F J; Van Den Broeck, C; Vander-Hyde, D C; van der Schaaf, L; van Heijningen, J V; van Veggel, A A; Vardaro, M; Varma, V; Vass, S; Vasúth, M; Vecchio, A; Vedovato, G; Veitch, J; Veitch, P J; Venkateswara, K; Venugopalan, G; Verkindt, D; Vetrano, F; Viceré, A; Viets, A D; Vinciguerra, S; Vine, D J; Vinet, J-Y; Vitale, S; Vo, T; Vocca, H; Vorvick, C; Voss, D V; Vousden, W D; Vyatchanin, S P; Wade, A R; Wade, L E; Wade, M; Walker, M; Wallace, L; Walsh, S; Wang, G; Wang, H; Wang, M; Wang, Y; Ward, R L; Warner, J; Was, M; Watchi, J; Weaver, B; Wei, L-W; Weinert, M; Weinstein, A J; Weiss, R; Wen, L; Weßels, P; Westphal, T; Wette, K; Whelan, J T; Whiting, B F; Whittle, C; Williams, D; Williams, R D; Williamson, A R; Willis, J L; Willke, B; Wimmer, M H; Winkler, W; Wipf, C C; Wittel, H; Woan, G; Woehler, J; Worden, J; Wright, J L; Wu, D S; Wu, G; Yam, W; Yamamoto, H; Yancey, C C; Yap, M J; Yu, Hang; Yu, Haocun; Yvert, M; Zadrożny, A; Zangrando, L; Zanolin, M; Zendri, J-P; Zevin, M; Zhang, L; Zhang, M; Zhang, T; Zhang, Y; Zhao, C; Zhou, M; Zhou, Z; Zhu, S J; Zhu, X J; Zucker, M E; Zweizig, J

2017-03-24

A wide variety of astrophysical and cosmological sources are expected to contribute to a stochastic gravitational-wave background. Following the observations of GW150914 and GW151226, the rate and mass of coalescing binary black holes appear to be greater than many previous expectations. As a result, the stochastic background from unresolved compact binary coalescences is expected to be particularly loud. We perform a search for the isotropic stochastic gravitational-wave background using data from Advanced Laser Interferometer Gravitational Wave Observatory's (aLIGO) first observing run. The data display no evidence of a stochastic gravitational-wave signal. We constrain the dimensionless energy density of gravitational waves to be Ω_{0}<1.7×10^{-7} with 95% confidence, assuming a flat energy density spectrum in the most sensitive part of the LIGO band (20-86 Hz). This is a factor of ∼33 times more sensitive than previous measurements. We also constrain arbitrary power-law spectra. Finally, we investigate the implications of this search for the background of binary black holes using an astrophysical model for the background.

Cosmic Infrared Background Fluctuations and Zodiacal Light

NASA Technical Reports Server (NTRS)

Arendt, Richard G.; Kashlinsky, A.; Moseley, S. H.; Mather, J.

2017-01-01

We performed a specific observational test to measure the effect that the zodiacal light can have on measurements of the spatial fluctuations of the near-IR (near-infrared)background. Previous estimates of possible fluctuations caused by zodiacal light have often been extrapolated from observations of the thermal emission at longer wavelengths and low angular resolution or from IRAC (Infrared Array Camera) observations of high-latitude fields where zodiacal light is faint and not strongly varying with time. The new observations analyzed here target the COSMOS (Cosmic Evolution Survey) field at low ecliptic latitude where the zodiacal light intensity varies by factors of approximately 2 over the range of solar elongations at which the field can be observed. We find that the white-noise component of the spatial power spectrum of the background is correlated with the modeled zodiacal light intensity. Roughly half of the measured white noise is correlated with the zodiacal light, but a more detailed interpretation of the white noise is hampered by systematic uncertainties that are evident in the zodiacal light model. At large angular scales (greater than or approximately equal to 100 arcseconds) where excess power above the white noise is observed, we find no correlation of the power with the modeled intensity of the zodiacal light. This test clearly indicates that the large-scale power in the infrared background is not being caused by the zodiacal light.

Gamma-Ray Background Variability in Mobile Detectors

NASA Astrophysics Data System (ADS)

Aucott, Timothy John

Gamma-ray background radiation significantly reduces detection sensitivity when searching for radioactive sources in the field, such as in wide-area searches for homeland security applications. Mobile detector systems in particular must contend with a variable background that is not necessarily known or even measurable a priori. This work will present measurements of the spatial and temporal variability of the background, with the goal of merging gamma-ray detection, spectroscopy, and imaging with contextual information--a "nuclear street view" of the ubiquitous background radiation. The gamma-ray background originates from a variety of sources, both natural and anthropogenic. The dominant sources in the field are the primordial isotopes potassium-40, uranium-238, and thorium-232, as well as their decay daughters. In addition to the natural background, many artificially-created isotopes are used for industrial or medical purposes, and contamination from fission products can be found in many environments. Regardless of origin, these backgrounds will reduce detection sensitivity by adding both statistical as well as systematic uncertainty. In particular, large detector arrays will be limited by the systematic uncertainty in the background and will suffer from a high rate of false alarms. The goal of this work is to provide a comprehensive characterization of the gamma-ray background and its variability in order to improve detection sensitivity and evaluate the performance of mobile detectors in the field. Large quantities of data are measured in order to study their performance at very low false alarm rates. Two different approaches, spectroscopy and imaging, are compared in a controlled study in the presence of this measured background. Furthermore, there is additional information that can be gained by correlating the gamma-ray data with contextual data streams (such as cameras and global positioning systems) in order to reduce the variability in the background. This is accomplished by making many hours of background measurements with a truck-mounted system, which utilizes high-purity germanium detectors for spectroscopy and sodium iodide detectors for coded aperture imaging. This system also utilizes various peripheral sensors, such as panoramic cameras, laser ranging systems, global positioning systems, and a weather station to provide context for the gamma-ray data. About three hundred hours of data were taken in the San Francisco Bay Area, covering a wide variety of environments that might be encountered in operational scenarios. These measurements were used in a source injection study to evaluate the sensitivity of different algorithms (imaging and spectroscopy) and hardware (sodium iodide and high-purity germanium detectors). These measurements confirm that background distributions in large, mobile detector systems are dominated by systematic, not statistical variations, and both spectroscopy and imaging were found to substantially reduce this variability. Spectroscopy performed better than the coded aperture for the given scintillator array (one square meter of sodium iodide) for a variety of sources and geometries. By modeling the statistical and systematic uncertainties of the background, the data can be sampled to simulate the performance of a detector array of arbitrary size and resolution. With a larger array or lower resolution detectors, however imaging was better able to compensate for background variability.

Effects of Background Music on Objective and Subjective Performance Measures in an Auditory BCI.

PubMed

Zhou, Sijie; Allison, Brendan Z; Kübler, Andrea; Cichocki, Andrzej; Wang, Xingyu; Jin, Jing

2016-01-01

Several studies have explored brain computer interface (BCI) systems based on auditory stimuli, which could help patients with visual impairments. Usability and user satisfaction are important considerations in any BCI. Although background music can influence emotion and performance in other task environments, and many users may wish to listen to music while using a BCI, auditory, and other BCIs are typically studied without background music. Some work has explored the possibility of using polyphonic music in auditory BCI systems. However, this approach requires users with good musical skills, and has not been explored in online experiments. Our hypothesis was that an auditory BCI with background music would be preferred by subjects over a similar BCI without background music, without any difference in BCI performance. We introduce a simple paradigm (which does not require musical skill) using percussion instrument sound stimuli and background music, and evaluated it in both offline and online experiments. The result showed that subjects preferred the auditory BCI with background music. Different performance measures did not reveal any significant performance effect when comparing background music vs. no background. Since the addition of background music does not impair BCI performance but is preferred by users, auditory (and perhaps other) BCIs should consider including it. Our study also indicates that auditory BCIs can be effective even if the auditory channel is simultaneously otherwise engaged.

Fluorescence background subtraction technique for hybrid fluorescence molecular tomography/x-ray computed tomography imaging of a mouse model of early stage lung cancer.

PubMed

Ale, Angelique; Ermolayev, Vladimir; Deliolanis, Nikolaos C; Ntziachristos, Vasilis

2013-05-01

The ability to visualize early stage lung cancer is important in the study of biomarkers and targeting agents that could lead to earlier diagnosis. The recent development of hybrid free-space 360-deg fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) imaging yields a superior optical imaging modality for three-dimensional small animal fluorescence imaging over stand-alone optical systems. Imaging accuracy was improved by using XCT information in the fluorescence reconstruction method. Despite this progress, the detection sensitivity of targeted fluorescence agents remains limited by nonspecific background accumulation of the fluorochrome employed, which complicates early detection of murine cancers. Therefore we examine whether x-ray CT information and bulk fluorescence detection can be combined to increase detection sensitivity. Correspondingly, we research the performance of a data-driven fluorescence background estimator employed for subtraction of background fluorescence from acquisition data. Using mice containing known fluorochromes ex vivo, we demonstrate the reduction of background signals from reconstructed images and sensitivity improvements. Finally, by applying the method to in vivo data from K-ras transgenic mice developing lung cancer, we find small tumors at an early stage compared with reconstructions performed using raw data. We conclude with the benefits of employing fluorescence subtraction in hybrid FMT-XCT for early detection studies.

MGGPOD: a Monte Carlo Suite for Modeling Instrumental Line and Continuum Backgrounds in Gamma-Ray Astronomy

NASA Technical Reports Server (NTRS)

Weidenspointner, G.; Harris, M. J.; Sturner, S.; Teegarden, B. J.; Ferguson, C.

2004-01-01

Intense and complex instrumental backgrounds, against which the much smaller signals from celestial sources have to be discerned, are a notorious problem for low and intermediate energy gamma-ray astronomy (approximately 50 keV - 10 MeV). Therefore a detailed qualitative and quantitative understanding of instrumental line and continuum backgrounds is crucial for most stages of gamma-ray astronomy missions, ranging from the design and development of new instrumentation through performance prediction to data reduction. We have developed MGGPOD, a user-friendly suite of Monte Carlo codes built around the widely used GEANT (Version 3.21) package, to simulate ab initio the physical processes relevant for the production of instrumental backgrounds. These include the build-up and delayed decay of radioactive isotopes as well as the prompt de-excitation of excited nuclei, both of which give rise to a plethora of instrumental gamma-ray background lines in addition t o continuum backgrounds. The MGGPOD package and documentation are publicly available for download. We demonstrate the capabilities of the MGGPOD suite by modeling high resolution gamma-ray spectra recorded by the Transient Gamma-Ray Spectrometer (TGRS) on board Wind during 1995. The TGRS is a Ge spectrometer operating in the 40 keV to 8 MeV range. Due to its fine energy resolution, these spectra reveal the complex instrumental background in formidable detail, particularly the many prompt and delayed gamma-ray lines. We evaluate the successes and failures of the MGGPOD package in reproducing TGRS data, and provide identifications for the numerous instrumental lines.

Stability of Early EEG Background Patterns After Pediatric Cardiac Arrest.

PubMed

Abend, Nicholas S; Xiao, Rui; Kessler, Sudha Kilaru; Topjian, Alexis A

2018-05-01

We aimed to determine whether EEG background characteristics remain stable across discrete time periods during the acute period after resuscitation from pediatric cardiac arrest. Children resuscitated from cardiac arrest underwent continuous conventional EEG monitoring. The EEG was scored in 12-hour epochs for up to 72 hours after return of circulation by an electroencephalographer using a Background Category with 4 levels (normal, slow-disorganized, discontinuous/burst-suppression, or attenuated-featureless) or 2 levels (normal/slow-disorganized or discontinuous/burst-suppression/attenuated-featureless). Survival analyses and mixed-effects ordinal logistic regression models evaluated whether the EEG remained stable across epochs. EEG monitoring was performed in 89 consecutive children. When EEG was assessed as the 4-level Background Category, 30% of subjects changed category over time. Based on initial Background Category, one quarter of the subjects changed EEG category by 24 hours if the initial EEG was attenuated-featureless, by 36 hours if the initial EEG was discontinuous or burst-suppression, by 48 hours if the initial EEG was slow-disorganized, and never if the initial EEG was normal. However, regression modeling for the 4-level Background Category indicated that the EEG did not change over time (odds ratio = 1.06, 95% confidence interval = 0.96-1.17, P = 0.26). Similarly, when EEG was assessed as the 2-level Background Category, 8% of subjects changed EEG category over time. However, regression modeling for the 2-level category indicated that the EEG did not change over time (odds ratio = 1.02, 95% confidence interval = 0.91-1.13, P = 0.75). The EEG Background Category changes over time whether analyzed as 4 levels (30% of subjects) or 2 levels (8% of subjects), although regression analyses indicated that no significant changes occurred over time for the full cohort. These data indicate that the Background Category is often stable during the acute 72 hours after pediatric cardiac arrest and thus may be a useful EEG assessment metric in future studies, but that some subjects do have EEG changes over time and therefore serial EEG assessments may be informative.

Predicting medical students' intentions to take up rural practice after graduation.

PubMed

Jones, Michael; Humphreys, John; Prideaux, David

2009-10-01

Using a novel longitudinal tracking project, this study develops and evaluates the performance of a predictive model and index of rural medical practice intention based on the characteristics of incoming medical students. Medical school entry survey data were obtained from the Medical Schools Outcome Database (MSOD) project implemented in all Australian and New Zealand medical schools and coordinated through Medical Deans Australia and New Zealand, the representative body for the Deans of 18 Australian and two New Zealand medical schools and faculties. The medical school commencement survey collects data on students' education and family background, including rural upbringing, personal circumstances and scholarships, and on their practice intentions in terms of location and specialty. The MSOD will also allow tracking of medical graduates after graduation. Logistic regression modelling was used to develop a predictive model of rural practice intention. Split-sample validation was used to gain some insight into the stability of performance of the model. Response rates to the MSOD survey exceeded 90% on average. The model findings confirm and extend previous research examining the association of medical student characteristics with intention to take up rural medical practice. The statistically significant independent factors in the model included students' rural backgrounds, financial arrangements and intentions regarding specialist versus generalist practice upon graduation. Model performance was good, with an area under the receiver-operator characteristics curve of 0.86, and reproducible, with an area in a validation sample of 0.83. The model and related index provide important insights into individual factors associated with rural practice intention among students commencing medical studies. The model can also provide a means for optimising the use of scarce medical programme resources, thereby helping to improve the supply of rural medical practitioners. This study illustrates the power and potential of a robust, consistent, systematic longitudinal tracking project.

Levels of naturally occurring gamma radiation measured in British homes and their prediction in particular residences.

PubMed

Kendall, G M; Wakeford, R; Athanson, M; Vincent, T J; Carter, E J; McColl, N P; Little, M P

2016-03-01

Gamma radiation from natural sources (including directly ionising cosmic rays) is an important component of background radiation. In the present paper, indoor measurements of naturally occurring gamma rays that were undertaken as part of the UK Childhood Cancer Study are summarised, and it is shown that these are broadly compatible with an earlier UK National Survey. The distribution of indoor gamma-ray dose rates in Great Britain is approximately normal with mean 96 nGy/h and standard deviation 23 nGy/h. Directly ionising cosmic rays contribute about one-third of the total. The expanded dataset allows a more detailed description than previously of indoor gamma-ray exposures and in particular their geographical variation. Various strategies for predicting indoor natural background gamma-ray dose rates were explored. In the first of these, a geostatistical model was fitted, which assumes an underlying geologically determined spatial variation, superimposed on which is a Gaussian stochastic process with Matérn correlation structure that models the observed tendency of dose rates in neighbouring houses to correlate. In the second approach, a number of dose-rate interpolation measures were first derived, based on averages over geologically or administratively defined areas or using distance-weighted averages of measurements at nearest-neighbour points. Linear regression was then used to derive an optimal linear combination of these interpolation measures. The predictive performances of the two models were compared via cross-validation, using a randomly selected 70 % of the data to fit the models and the remaining 30 % to test them. The mean square error (MSE) of the linear-regression model was lower than that of the Gaussian-Matérn model (MSE 378 and 411, respectively). The predictive performance of the two candidate models was also evaluated via simulation; the OLS model performs significantly better than the Gaussian-Matérn model.

Data-driven modeling of background and mine-related acidity and metals in river basins

USGS Publications Warehouse

Friedel, Michael J

2013-01-01

A novel application of self-organizing map (SOM) and multivariate statistical techniques is used to model the nonlinear interaction among basin mineral-resources, mining activity, and surface-water quality. First, the SOM is trained using sparse measurements from 228 sample sites in the Animas River Basin, Colorado. The model performance is validated by comparing stochastic predictions of basin-alteration assemblages and mining activity at 104 independent sites. The SOM correctly predicts (>98%) the predominant type of basin hydrothermal alteration and presence (or absence) of mining activity. Second, application of the Davies–Bouldin criteria to k-means clustering of SOM neurons identified ten unique environmental groups. Median statistics of these groups define a nonlinear water-quality response along the spatiotemporal hydrothermal alteration-mining gradient. These results reveal that it is possible to differentiate among the continuum between inputs of background and mine-related acidity and metals, and it provides a basis for future research and empirical model development.

Simulation of atmospheric and terrestrial background signatures for detection and tracking scenarios

NASA Astrophysics Data System (ADS)

Schweitzer, Caroline; Stein, Karin

2015-10-01

In the fields of early warning, one is depending on reliable image exploitation: Only if the applied detection and tracking algorithms work efficiently, the threat approach alert can be given fast enough to ensure an automatic initiation of the countermeasure. In order to evaluate the performance of those algorithms for a certain electro-optical (EO) sensor system, test sequences need to be created as realistic and comprehensive as possible. Since both, background and target signature, depend on the environmental conditions, a detailed knowledge of the meteorology and climatology is necessary. Trials for measuring these environmental characteristics serve as a solid basis, but might only constitute the conditions during a rather short period of time. To represent the entire variation of meteorology and climatology that the future system will be exposed to, the application of comprehensive atmospheric modelling tools is essential. This paper gives an introduction of the atmospheric modelling tools that are currently used at Fraunhofer IOSB to simulate spectral background signatures in the infrared (IR) range. It is also demonstrated, how those signatures are affected by changing atmospheric and climatic conditions. In conclusion - and with a special focus on the modelling of different cloud types - sources of error and limits are discussed.

Evidence for the associated production of a W boson and a top quark at ATLAS

NASA Astrophysics Data System (ADS)

Koll, James

This thesis discusses a search for the Standard Model single top Wt-channel process. An analysis has been performed searching for the Wt-channel process using 4.7 fb-1 of integrated luminosity collected with the ATLAS detector at the Large Hadron Collider. A boosted decision tree is trained using machine learning techniques to increase the separation between signal and background. A profile likelihood fit is used to measure the cross-section of the Wt-channel process at sigma(pp → Wt + X) = 16.8 +/-2.9 (stat) +/- 4.9(syst) pb, consistent with the Standard Model prediction. This fit is also used to generate pseudoexperiments to calculate the significance, finding an observed (expected) 3.3 sigma (3.4 sigma) excess over background.

The active muon shield in the SHiP experiment

NASA Astrophysics Data System (ADS)

Akmete, A.; Alexandrov, A.; Anokhina, A.; Aoki, S.; Atkin, E.; Azorskiy, N.; Back, J. J.; Bagulya, A.; Baranov, A.; Barker, G. J.; Bay, A.; Bayliss, V.; Bencivenni, G.; Berdnikov, A. Y.; Berdnikov, Y. A.; Bertani, M.; Betancourt, C.; Bezshyiko, I.; Bezshyyko, O.; Bick, D.; Bieschke, S.; Blanco, A.; Boehm, J.; Bogomilov, M.; Bondarenko, K.; Bonivento, W. M.; Boyarsky, A.; Brenner, R.; Breton, D.; Brundler, R.; Bruschi, M.; Büscher, V.; Buonaura, A.; Buontempo, S.; Cadeddu, S.; Calcaterra, A.; Campanelli, M.; Chauveau, J.; Chepurnov, A.; Chernyavsky, M.; Choi, K.-Y.; Chumakov, A.; Ciambrone, P.; Dallavalle, G. M.; D'Ambrosio, N.; D'Appollonio, G.; De Lellis, G.; De Roeck, A.; De Serio, M.; Dedenko, L.; Di Crescenzo, A.; Di Marco, N.; Dib, C.; Dijkstra, H.; Dmitrenko, V.; Domenici, D.; Donskov, S.; Dubreuil, A.; Ebert, J.; Enik, T.; Etenko, A.; Fabbri, F.; Fabbri, L.; Fedin, O.; Fedorova, G.; Felici, G.; Ferro-Luzzi, M.; Fini, R. A.; Fonte, P.; Franco, C.; Fukuda, T.; Galati, G.; Gavrilov, G.; Gerlach, S.; Golinka-Bezshyyko, L.; Golubkov, D.; Golutvin, A.; Gorbunov, D.; Gorbunov, S.; Gorkavenko, V.; Gornushkin, Y.; Gorshenkov, M.; Grachev, V.; Graverini, E.; Grichine, V.; Guler, A. M.; Guz, Yu.; Hagner, C.; Hakobyan, H.; van Herwijnen, E.; Hollnagel, A.; Hosseini, B.; Hushchyn, M.; Iaselli, G.; Iuliano, A.; Jacobsson, R.; Jonker, M.; Kadenko, I.; Kamiscioglu, C.; Kamiscioglu, M.; Khabibullin, M.; Khaustov, G.; Khotyantsev, A.; Kim, S. H.; Kim, V.; Kim, Y. G.; Kitagawa, N.; Ko, J.-W.; Kodama, K.; Kolesnikov, A.; Kolev, D. I.; Kolosov, V.; Komatsu, M.; Konovalova, N.; Korkmaz, M. A.; Korol, I.; Korol'ko, I.; Korzenev, A.; Kovalenko, S.; Krasilnikova, I.; Krivova, K.; Kudenko, Y.; Kurochka, V.; Kuznetsova, E.; Lacker, H. M.; Lai, A.; Lanfranchi, G.; Lantwin, O.; Lauria, A.; Lebbolo, H.; Lee, K. Y.; Lévy, J.-M.; Lopes, L.; Lyubovitskij, V.; Maalmi, J.; Magnan, A.; Maleev, V.; Malinin, A.; Mefodev, A.; Mermod, P.; Mikado, S.; Mikhaylov, Yu.; Milstead, D. A.; Mineev, O.; Montanari, A.; Montesi, M. C.; Morishima, K.; Movchan, S.; Naganawa, N.; Nakamura, M.; Nakano, T.; Novikov, A.; Obinyakov, B.; Ogawa, S.; Okateva, N.; Owen, P. H.; Paoloni, A.; Park, B. D.; Paparella, L.; Pastore, A.; Patel, M.; Pereyma, D.; Petrenko, D.; Petridis, K.; Podgrudkov, D.; Poliakov, V.; Polukhina, N.; Prokudin, M.; Prota, A.; Rademakers, A.; Ratnikov, F.; Rawlings, T.; Razeti, M.; Redi, F.; Ricciardi, S.; Roganova, T.; Rogozhnikov, A.; Rokujo, H.; Rosa, G.; Rovelli, T.; Ruchayskiy, O.; Ruf, T.; Samoylenko, V.; Saputi, A.; Sato, O.; Savchenko, E. S.; Schmidt-Parzefall, W.; Serra, N.; Shakin, A.; Shaposhnikov, M.; Shatalov, P.; Shchedrina, T.; Shchutska, L.; Shevchenko, V.; Shibuya, H.; Shustov, A.; Silverstein, S. B.; Simone, S.; Skorokhvatov, M.; Smirnov, S.; Sohn, J. Y.; Sokolenko, A.; Starkov, N.; Storaci, B.; Strolin, P.; Takahashi, S.; Timiryasov, I.; Tioukov, V.; Tosi, N.; Treille, D.; Tsenov, R.; Ulin, S.; Ustyuzhanin, A.; Uteshev, Z.; Vankova-Kirilova, G.; Vannucci, F.; Venkova, P.; Vilchinski, S.; Villa, M.; Vlasik, K.; Volkov, A.; Voronkov, R.; Wanke, R.; Woo, J.-K.; Wurm, M.; Xella, S.; Yilmaz, D.; Yilmazer, A. U.; Yoon, C. S.; Zaytsev, Yu.

2017-05-01

The SHiP experiment is designed to search for very weakly interacting particles beyond the Standard Model which are produced in a 400 GeV/c proton beam dump at the CERN SPS. An essential task for the experiment is to keep the Standard Model background level to less than 0.1 event after 2× 1020 protons on target. In the beam dump, around 1011 muons will be produced per second. The muon rate in the spectrometer has to be reduced by at least four orders of magnitude to avoid muon-induced combinatorial background. A novel active muon shield is used to magnetically deflect the muons out of the acceptance of the spectrometer. This paper describes the basic principle of such a shield, its optimization and its performance.

The effect of observing novice and expert performance on acquisition of surgical skills on a robotic platform

PubMed Central

Harris, David J.; Vine, Samuel J.; Wilson, Mark R.; McGrath, John S.; LeBel, Marie-Eve

2017-01-01

Background Observational learning plays an important role in surgical skills training, following the traditional model of learning from expertise. Recent findings have, however, highlighted the benefit of observing not only expert performance but also error-strewn performance. The aim of this study was to determine which model (novice vs. expert) would lead to the greatest benefits when learning robotically assisted surgical skills. Methods 120 medical students with no prior experience of robotically-assisted surgery completed a ring-carrying training task on three occasions; baseline, post-intervention and at one-week follow-up. The observation intervention consisted of a video model performing the ring-carrying task, with participants randomly assigned to view an expert model, a novice model, a mixed expert/novice model or no observation (control group). Participants were assessed for task performance and surgical instrument control. Results There were significant group differences post-intervention, with expert and novice observation groups outperforming the control group, but there were no clear group differences at a retention test one week later. There was no difference in performance between the expert-observing and error-observing groups. Conclusions Similar benefits were found when observing the traditional expert model or the error-strewn model, suggesting that viewing poor performance may be as beneficial as viewing expertise in the early acquisition of robotic surgical skills. Further work is required to understand, then inform, the optimal curriculum design when utilising observational learning in surgical training. PMID:29141046

Influence of background noise on the performance in the odor sensitivity task: effects of noise type and extraversion.

PubMed

Seo, Han-Seok; Hähner, Antje; Gudziol, Volker; Scheibe, Mandy; Hummel, Thomas

2012-10-01

Recent research demonstrated that background noise relative to silence impaired subjects' performance in a cognitively driven odor discrimination test. The current study aimed to investigate whether the background noise can also modulate performance in an odor sensitivity task that is less cognitively loaded. Previous studies have shown that the effect of background noise on task performance can be different in relation to degree of extraversion and/or type of noise. Accordingly, we wanted to examine whether the influence of background noise on the odor sensitivity task can be altered as a function of the type of background noise (i.e., nonverbal vs. verbal noise) and the degree of extraversion (i.e., introvert vs. extrovert group). Subjects were asked to conduct an odor sensitivity task in the presence of either nonverbal noise (e.g., party sound) or verbal noise (e.g., audio book), or silence. Overall, the subjects' mean performance in the odor sensitivity task was not significantly different across three auditory conditions. However, with regard to the odor sensitivity task, a significant interaction emerged between the type of background noise and the degree of extraversion. Specifically, verbal noise relative to silence significantly impaired or improved the performance of the odor sensitivity task in the introvert or extrovert group, respectively; the differential effect of introversion/extraversion was not observed in the nonverbal noise-induced task performance. In conclusion, our findings provide new empirical evidence that type of background noise and degree of extraversion play an important role in modulating the effect of background noise on subjects' performance in an odor sensitivity task.

The BioMedical Admissions Test for medical student selection: issues of fairness and bias.

PubMed

Emery, Joanne L; Bell, John F; Vidal Rodeiro, Carmen L

2011-01-01

The BioMedical Admissions Test (BMAT) forms part of the undergraduate medical admission process at the University of Cambridge. The fairness of admissions tests is an important issue. Aims were to investigate the relationships between applicants' background variables and BMAT scores, whether they were offered a place or rejected and, for those admitted, performance on the first year course examinations. Multilevel regression models were employed with data from three combined applicant cohorts. Admission rates for different groups were investigated with and without controlling for BMAT performance. The fairness of the BMAT was investigated by determining, for those admitted, whether scores predicted examination performance equitably. Despite some differences in applicants' BMAT performance (e.g. by school type and gender), BMAT scores predicted mean examination marks equitably for all background variables considered. The probability of achieving a 1st class examination result, however, was slightly under-predicted for those admitted from schools and colleges entering relatively few applicants. Not all differences in admission rates were accounted for by BMAT performance. However, the test constitutes only one part of a compensatory admission system in which other factors, such as interview performance, are important considerations. Results are in support of the equity of the BMAT.

Development of a clean optical telescope

NASA Technical Reports Server (NTRS)

Brown, R. A.

1983-01-01

Particulate contamination on astronomical mirrors degrades performance in two ways: by information loss by extinction of light; and background and noise from scattering, especially forward or Fraunhofer scattering. These effects were not generally understood, and an ambitious pilot program was outlined to measure particulate effects on telescope optical performance; develop prophylactic and cleaning procedures suitable for groundbased observatories; investigate by computational modelling the effects on telescopes in space; and communicate the results and concerns within the astronomical community.

Current status of the Double Chooz experiment

NASA Astrophysics Data System (ADS)

Haser, J.; Double Chooz Collaboration

2016-04-01

The Double Chooz reactor antineutrino experiment aims for a precision measurement of the neutrino mixing angle θ13. Located at the Chooz nuclear power plant in France, it observes an energy dependent deficit in the electron antineutrino spectrum, currently with one detector filled with gadolinium-loaded liquid scintillator at a baseline of 1.05 km. The Double Chooz analysis utilizes different approaches to extract θ13: A combined rate and spectral shape fit as well as a background-model-independent analysis based on reactor power variations are performed, giving consistent results. Among the recent reactor-based oscillation experiments with comparable baseline it was the only one to observe reactor shutdown phases, during which all reactors are turned off. These enabled to measure the backgrounds solely, allowing to crosscheck the background models used in the oscillation analysis. At present an improved analysis was put forward with twice as much data statistics collected compared to the last publication. Revised selection criteria and background studies enhance the signal to background ratio while a decrease in the corresponding uncertainties is achieved. Along with an improved energy calibration the overall systematic uncertainty on θ13 is reduced, preparing for a two detector analysis. The new analysis obtains from 467.90 live days with 66.5 GW-ton-years of exposure (reactor power × detector mass × live time) a value of sin2 ⁡ 2θ13 =0.090-0.029+0.032(stat + syst).

Motor performance of tongue with a computer-integrated system under different levels of background physical exertion

PubMed Central

Huo, Xueliang; Johnson-Long, Ashley N.; Ghovanloo, Maysam; Shinohara, Minoru

2015-01-01

The purpose of this study was to compare the motor performance of tongue, using Tongue Drive System, to hand operation for relatively complex tasks under different levels of background physical exertion. Thirteen young able-bodied adults performed tasks that tested the accuracy and variability in tracking a sinusoidal waveform, and the performance in playing two video games that require accurate and rapid movements with cognitive processing using tongue and hand under two levels of background physical exertion. Results show additional background physical activity did not influence rapid and accurate displacement motor performance, but compromised the slow waveform tracking and shooting performances in both hand and tongue. Slow waveform tracking performance by the tongue was compromised with an additional motor or cognitive task, but with an additional motor task only for the hand. Practitioner Summary We investigated the influence of task complexity and background physical exertion on the motor performance of tongue and hand. Results indicate the task performance degrades with an additional concurrent task or physical exertion due to the limited attentional resources available for handling both the motor task and background exertion. PMID:24003900

de Sitter limit analysis for dark energy and modified gravity models

NASA Astrophysics Data System (ADS)

De Felice, Antonio; Frusciante, Noemi; Papadomanolakis, Georgios

2017-07-01

The effective field theory of dark energy and modified gravity is supposed to well describe, at low energies, the behavior of the gravity modifications due to one extra scalar degree of freedom. The usual curvature perturbation is very useful when studying the conditions for the avoidance of ghost instabilities as well as the positivity of the squared speeds of propagation for both the scalar and tensor modes, or the Stückelberg field performs perfectly when investigating the evolution of linear perturbations. We show that the viable parameter space identified by requiring no-ghost instabilities and positive squared speeds of propagation does not change by performing a field redefinition, while the requirement of the avoidance of tachyonic instability might instead be different. Therefore, we find it interesting to associate to the general modified gravity theory described in the effective field theory framework, a perturbation field which will inherit all of the properties of the theory. In the present paper we address the following questions: (1) how can we define such a field? and (2) what is the mass of such a field as the background approaches a final de Sitter state? We define a gauge-invariant quantity which identifies the density of the dark energy perturbation field valid for any background. We derive the mass associated to the gauge-invariant dark energy field on a de Sitter background, which we retain to be still a good approximation also at very low redshift (z ≃0 ). On this background we also investigate the value of the speed of propagation and we find that there exist classes of theories which admit a nonvanishing speed of propagation, even in the Horndeski model, for which a zero speed of sound has previously been found in the literature. We finally apply our results to specific well-known models.

Who reports high company performance? A quantitative study of Chinese listed companies in the energy industry.

PubMed

Guo, Daoyan; Chen, Hong; Long, Ruyin

2016-01-01

In the increasingly competitive environment, top managers' background characteristics are undoubtedly vital factors for company performance. This study examines whether the performance of Chinese listed companies in the energy industry differs with respect to top managers' background characteristics and explores the exact distribution interval of top managers' background characteristics when company performance reaches the highest level. The initial sample was collected from the CSMAR database (2005-2014) for listed companies in the energy industry. After removing the outlier and missing data, the final number of observations was determined as 780. Descriptive statistics were used to investigate the present distribution of top managers' background characteristics, factor analysis was used to determine the dimensions of company performance, and one-way ANOVA was used to analyze the differences in company performance and its dimensions with respect to top managers' background characteristics. The findings show that both the age and length of service of top managers present an increasing trend over the years of the study period, whereas the educational level shows no significant changes. The performance of listed companies has three dimensions: profit performance, growth performance, and operating performance. Companies behave differently with regard to their top managers' background characteristics; when the top manager is 40-45 years old, with a doctoral degree and above, and in the 2nd-3rd year of his service period, his company will achieve a higher level of performance. This study contributes to the growing literature on company performance in the Chinese energy industry by demonstrating the differences in the performance of Chinese listed companies in the energy industry with regard to top managers' background characteristics, and reaching conclusions on the optimum distribution interval of top managers' background characteristics when company performance reaches the highest level. This study also provides a valuable reference for organizational reform and performance enhancement, which are urgent problems for the Chinese energy industry.

Comparing Dichotomous and Trichotomous Approaches to Achievement Goal Theory: An Example Using Motivational Regulations as Outcome Variables

ERIC Educational Resources Information Center

Barkoukis, Vassilis; Ntoumanis, Nikos; Nikitaras, Nikitas

2007-01-01

Background: It is commonly assumed that there is conceptual equivalence between the task and ego achievement goals proposed by Nicholl's (1989) dichotomous achievement goal theory (Nicholls, 1989), and the mastery and performance approach goals advanced by Elliot's (1997) trichotomous hierarchical model of approach and avoidance achievement…

Lead-Free vs Tin-Lead Reliability of Advanced Electronic Assemblies

NASA Technical Reports Server (NTRS)

Ghaffarian, Reza

2005-01-01

This presentation will provide the technical background and specific information published in literature related to reliability test, analyses, modeling, and associated issues for lead-free solder package assemblies in comparison to their tin-lead solder alloys. It also presents current understanding of lead-free thermal cycle test performance in support.

ERPs Associated with Monitoring and Evaluation of Monetary Reward and Punishment in Children with ADHD

ERIC Educational Resources Information Center

van Meel, Catharina S.; Heslenfeld, Dirk J.; Oosterlaan, Jaap; Luman, Marjolein; Sergeant, Joseph A.

2011-01-01

Background: Several models of attention-deficit hyperactivity disorder (ADHD) propose abnormalities in the response to behavioural contingencies. Using event-related potentials (ERPs), the present study investigated the monitoring and subsequent evaluation of performance feedback resulting in either reward or punishment in children with ADHD (N =…

Higgs field and cosmological parameters in the fractal quantum system

NASA Astrophysics Data System (ADS)

Abramov, Valeriy

2017-10-01

For the fractal model of the Universe the relations of cosmological parameters and the Higgs field are established. Estimates of the critical density, the expansion and speed-up parameters of the Universe (the Hubble constant and the cosmological redshift); temperature and anisotropy of the cosmic microwave background radiation were performed.

The Use of Longitudinal Analysis to Identify More and Less Effective Schools.

ERIC Educational Resources Information Center

Goldberg, Zandra S.; Spartz, James L.

Three longitudinal studies of student achievement test data were conducted to examine the extent to which the variation in student achievement can be explained by differences in student background (including socioeconomic and prior achievement data) and school resources. This model assumes that achievement test performance may be predicted by…

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

Carena, Marcela; Liu, Zhen

Heavy scalar and pseudoscalar resonance searches through themore » $$gg\\rightarrow S\\rightarrow t\\bar t$$ process are challenging due to the peculiar behavior of the large interference effects with the standard model $$t\\bar t$$ background. Such effects generate non-trivial lineshapes from additional relative phases between the signal and background amplitudes. We provide the analytic expressions for the differential cross sections to understand the interference effects in the heavy scalar signal lineshapes. We extend our study to the case of CP-violation and further consider the effect of bottom quarks in the production and decay processes. We also evaluate the contributions from additional particles to the gluon fusion production process, such as stops and vector-like quarks, that could lead to significant changes in the behavior of the signal lineshapes. Taking into account the large interference effects, we perform lineshape searches at the LHC and discuss the importance of the systematic uncertainties and smearing effects. Lastly, we present projected sensitivities for two LHC performance scenarios to probe the $$gg\\rightarrow S \\rightarrow t\\bar t$$ channel in various models.« less

Development of classification models to detect Salmonella Enteritidis and Salmonella Typhimurium found in poultry carcass rinses by visible-near infrared hyperspectral imaging

NASA Astrophysics Data System (ADS)

Seo, Young Wook; Yoon, Seung Chul; Park, Bosoon; Hinton, Arthur; Windham, William R.; Lawrence, Kurt C.

2013-05-01

Salmonella is a major cause of foodborne disease outbreaks resulting from the consumption of contaminated food products in the United States. This paper reports the development of a hyperspectral imaging technique for detecting and differentiating two of the most common Salmonella serotypes, Salmonella Enteritidis (SE) and Salmonella Typhimurium (ST), from background microflora that are often found in poultry carcass rinse. Presumptive positive screening of colonies with a traditional direct plating method is a labor intensive and time consuming task. Thus, this paper is concerned with the detection of differences in spectral characteristics among the pure SE, ST, and background microflora grown on brilliant green sulfa (BGS) and xylose lysine tergitol 4 (XLT4) agar media with a spread plating technique. Visible near-infrared hyperspectral imaging, providing the spectral and spatial information unique to each microorganism, was utilized to differentiate SE and ST from the background microflora. A total of 10 classification models, including five machine learning algorithms, each without and with principal component analysis (PCA), were validated and compared to find the best model in classification accuracy. The five machine learning (classification) algorithms used in this study were Mahalanobis distance (MD), k-nearest neighbor (kNN), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and support vector machine (SVM). The average classification accuracy of all 10 models on a calibration (or training) set of the pure cultures on BGS agar plates was 98% (Kappa coefficient = 0.95) in determining the presence of SE and/or ST although it was difficult to differentiate between SE and ST. The average classification accuracy of all 10 models on a training set for ST detection on XLT4 agar was over 99% (Kappa coefficient = 0.99) although SE colonies on XLT4 agar were difficult to differentiate from background microflora. The average classification accuracy of all 10 models on a validation set of chicken carcass rinses spiked with SE or ST and incubated on BGS agar plates was 94.45% and 83.73%, without and with PCA for classification, respectively. The best performing classification model on the validation set was QDA without PCA by achieving the classification accuracy of 98.65% (Kappa coefficient=0.98). The overall best performing classification model regardless of using PCA was MD with the classification accuracy of 94.84% (Kappa coefficient=0.88) on the validation set.

Investigation of the Effects of Facility Background Pressure on the Performance and Voltage-Current Characteristics of the High Voltage Hall Accelerator

NASA Technical Reports Server (NTRS)

Kamhawi, Hani; Huang, Wensheng; Haag, Thomas; Spektor, Rostislav

2014-01-01

The National Aeronautics and Space Administration (NASA) Science Mission Directorate In-Space Propulsion Technology office is sponsoring NASA Glenn Research Center to develop a 4 kW-class Hall thruster propulsion system for implementation in NASA science missions. A study was conducted to assess the impact of varying the facility background pressure on the High Voltage Hall Accelerator (HiVHAc) thruster performance and voltage-current characteristics. This present study evaluated the HiVHAc thruster performance in the lowest attainable background pressure condition at NASA GRC Vacuum Facility 5 to best simulate space-like conditions. Additional tests were performed at selected thruster operating conditions to investigate and elucidate the underlying physics that change during thruster operation at elevated facility background pressure. Tests were performed at background pressure conditions that are three and ten times higher than the lowest realized background pressure. Results indicated that the thruster discharge specific impulse and efficiency increased with elevated facility background pressure. The voltage-current profiles indicated a narrower stable operating region with increased background pressure. Experimental observations of the thruster operation indicated that increasing the facility background pressure shifted the ionization and acceleration zones upstream towards the thrusters anode. Future tests of the HiVHAc thruster are planned at background pressure conditions that are expected to be two to three times lower than what was achieved during this test campaign. These tests will not only assess the impact of reduced facility background pressure on thruster performance, voltage-current characteristics, and plume properties; but will also attempt to quantify the magnitude of the ionization.

Investigation of the Effects of Facility Background Pressure on the Performance and Voltage-Current Characteristics of the High Voltage Hall Accelerator

NASA Technical Reports Server (NTRS)

Kamhawi, Hani; Huang, Wensheng; Haag, Thomas; Spektor, Rostislav

2014-01-01

The National Aeronautics and Space Administration (NASA) Science Mission Directorate In-Space Propulsion Technology office is sponsoring NASA Glenn Research Center to develop a 4 kW-class Hall thruster propulsion system for implementation in NASA science missions. A study was conducted to assess the impact of varying the facility background pressure on the High Voltage Hall Accelerator (HiVHAc) thruster performance and voltage-current characteristics. This present study evaluated the HiVHAc thruster performance in the lowest attainable background pressure condition at NASA GRC Vacuum Facility 5 to best simulate space-like conditions. Additional tests were performed at selected thruster operating conditions to investigate and elucidate the underlying physics that change during thruster operation at elevated facility background pressure. Tests were performed at background pressure conditions that are three and ten times higher than the lowest realized background pressure. Results indicated that the thruster discharge specific impulse and efficiency increased with elevated facility background pressure. The voltage-current profiles indicated a narrower stable operating region with increased background pressure. Experimental observations of the thruster operation indicated that increasing the facility background pressure shifted the ionization and acceleration zones upstream towards the thruster's anode. Future tests of the HiVHAc thruster are planned at background pressure conditions that are expected to be two to three times lower than what was achieved during this test campaign. These tests will not only assess the impact of reduced facility background pressure on thruster performance, voltage-current characteristics, and plume properties; but will also attempt to quantify the magnitude of the ionization and acceleration zones upstream shifting as a function of increased background pressure.

An efficient background modeling approach based on vehicle detection

NASA Astrophysics Data System (ADS)

Wang, Jia-yan; Song, Li-mei; Xi, Jiang-tao; Guo, Qing-hua

2015-10-01

The existing Gaussian Mixture Model(GMM) which is widely used in vehicle detection suffers inefficiency in detecting foreground image during the model phase, because it needs quite a long time to blend the shadows in the background. In order to overcome this problem, an improved method is proposed in this paper. First of all, each frame is divided into several areas(A, B, C and D), Where area A, B, C and D are decided by the frequency and the scale of the vehicle access. For each area, different new learning rate including weight, mean and variance is applied to accelerate the elimination of shadows. At the same time, the measure of adaptive change for Gaussian distribution is taken to decrease the total number of distributions and save memory space effectively. With this method, different threshold value and different number of Gaussian distribution are adopted for different areas. The results show that the speed of learning and the accuracy of the model using our proposed algorithm surpass the traditional GMM. Probably to the 50th frame, interference with the vehicle has been eliminated basically, and the model number only 35% to 43% of the standard, the processing speed for every frame approximately has a 20% increase than the standard. The proposed algorithm has good performance in terms of elimination of shadow and processing speed for vehicle detection, it can promote the development of intelligent transportation, which is very meaningful to the other Background modeling methods.

Interevent times in a new alarm-based earthquake forecasting model

NASA Astrophysics Data System (ADS)

Talbi, Abdelhak; Nanjo, Kazuyoshi; Zhuang, Jiancang; Satake, Kenji; Hamdache, Mohamed

2013-09-01

This study introduces a new earthquake forecasting model that uses the moment ratio (MR) of the first to second order moments of earthquake interevent times as a precursory alarm index to forecast large earthquake events. This MR model is based on the idea that the MR is associated with anomalous long-term changes in background seismicity prior to large earthquake events. In a given region, the MR statistic is defined as the inverse of the index of dispersion or Fano factor, with MR values (or scores) providing a biased estimate of the relative regional frequency of background events, here termed the background fraction. To test the forecasting performance of this proposed MR model, a composite Japan-wide earthquake catalogue for the years between 679 and 2012 was compiled using the Japan Meteorological Agency catalogue for the period between 1923 and 2012, and the Utsu historical seismicity records between 679 and 1922. MR values were estimated by sampling interevent times from events with magnitude M ≥ 6 using an earthquake random sampling (ERS) algorithm developed during previous research. Three retrospective tests of M ≥ 7 target earthquakes were undertaken to evaluate the long-, intermediate- and short-term performance of MR forecasting, using mainly Molchan diagrams and optimal spatial maps obtained by minimizing forecasting error defined by miss and alarm rate addition. This testing indicates that the MR forecasting technique performs well at long-, intermediate- and short-term. The MR maps produced during long-term testing indicate significant alarm levels before 15 of the 18 shallow earthquakes within the testing region during the past two decades, with an alarm region covering about 20 per cent (alarm rate) of the testing region. The number of shallow events missed by forecasting was reduced by about 60 per cent after using the MR method instead of the relative intensity (RI) forecasting method. At short term, our model succeeded in forecasting the occurrence region of the 2011 Mw 9.0 Tohoku earthquake, whereas the RI method did not. Cases where a period of quiescent seismicity occurred before the target event often lead to low MR scores, meaning that the target event was not predicted and indicating that our model could be further improved by taking into account quiescent periods in the alarm strategy.

High-Operating Temperature HgCdTe: A Vision for the Near Future

NASA Astrophysics Data System (ADS)

Lee, D.; Carmody, M.; Piquette, E.; Dreiske, P.; Chen, A.; Yulius, A.; Edwall, D.; Bhargava, S.; Zandian, M.; Tennant, W. E.

2016-09-01

We review recent advances in the HgCdTe material quality and detector performance achieved at Teledyne using molecular beam epitaxy growth and the double-layer planar hetero-junction (DLPH) detector architecture. By using an un-doped, fully depleted absorber, Teledyne's DLPH architecture can be extended for use in high operating temperatures and other applications. We assess the potential achievable performance for long wavelength infrared (LWIR) hetero-junction p-lightly-doped n or p-intrinsic- n (p-i-n) detectors based on recently reported results for 10.7 μm cutoff 1 K × 1 K focal plane arrays (FPAs) tested at temperatures down to 30 K. Variable temperature dark current measurements show that any Shockley-Read-Hall currents in the depletion region of these devices have lifetimes that are reproducibly greater than 100 ms. Under the assumption of comparable lifetimes at higher temperatures, it is predicted that fully-depleted background radiation-limited performance can be expected for 10- μm cutoff detectors from room temperature to well below liquid nitrogen temperatures, with room-temperature dark current nearly 400 times lower than predicted by Rule 07. The hetero-junction p-i-n diode is shown to have numerous other significant potential advantages including minimal or no passivation requirements for pBn-like processing, low 1/ f noise, compatibility with small pixel pitch while maintaining high modulation transfer function, low crosstalk and good quantum efficiency. By appropriate design of the FPA dewar shielding, analysis shows that dark current can theoretically be further reduced below the thermal equilibrium radiative limit. Modeling shows that background radiation-limited LWIR HgCdTe operating with f/1 optics has the potential to operate within √2 of background-limited performance at 215 K. By reducing the background radiation by 2/3 using novel shielding methods, operation with a single-stage thermo-electric-cooler may be possible. If the background radiation can be reduced by 90%, then room-temperature operation is possible.

Construction of a model for predicting creatinine clearance in Japanese patients treated with Cisplatin therapy.

PubMed

Yajima, Airi; Uesawa, Yoshihiro; Ogawa, Chiaki; Yatabe, Megumi; Kondo, Naoki; Saito, Shinichiro; Suzuki, Yoshihiko; Atsuda, Kouichiro; Kagaya, Hajime

2015-05-01

There exist various useful predictive models, such as the Cockcroft-Gault model, for estimating creatinine clearance (CLcr). However, the prediction of renal function is difficult in patients with cancer treated with cisplatin. Therefore, we attempted to construct a new model for predicting CLcr in such patients. Japanese patients with head and neck cancer who had received cisplatin-based chemotherapy were used as subjects. A multiple regression equation was constructed as a model for predicting CLcr values based on background and laboratory data. A model for predicting CLcr, which included body surface area, serum creatinine and albumin, was constructed. The model exhibited good performance prior to cisplatin therapy. In addition, it performed better than previously reported models after cisplatin therapy. The predictive model constructed in the present study displayed excellent potential and was useful for estimating the renal function of patients treated with cisplatin therapy. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Integrating the Advanced Human Eye Model (AHEM) and optical instrument models to model complete visual optical systems inclusive of the typical or atypical eye

NASA Astrophysics Data System (ADS)

Donnelly, William J., III

2012-06-01

PURPOSE: To present a commercially available optical modeling software tool to assist the development of optical instrumentation and systems that utilize and/or integrate with the human eye. METHODS: A commercially available flexible eye modeling system is presented, the Advanced Human Eye Model (AHEM). AHEM is a module that the engineer can use to perform rapid development and test scenarios on systems that integrate with the eye. Methods include merging modeled systems initially developed outside of AHEM and performing a series of wizard-type operations that relieve the user from requiring an optometric or ophthalmic background to produce a complete eye inclusive system. Scenarios consist of retinal imaging of targets and sources through integrated systems. Uses include, but are not limited to, optimization, telescopes, microscopes, spectacles, contact and intraocular lenses, ocular aberrations, cataract simulation and scattering, and twin eye model (binocular) systems. RESULTS: Metrics, graphical data, and exportable CAD geometry are generated from the various modeling scenarios.

BEATBOX v1.0: Background Error Analysis Testbed with Box Models

NASA Astrophysics Data System (ADS)

Knote, Christoph; Barré, Jérôme; Eckl, Max

2018-02-01

The Background Error Analysis Testbed (BEATBOX) is a new data assimilation framework for box models. Based on the BOX Model eXtension (BOXMOX) to the Kinetic Pre-Processor (KPP), this framework allows users to conduct performance evaluations of data assimilation experiments, sensitivity analyses, and detailed chemical scheme diagnostics from an observation simulation system experiment (OSSE) point of view. The BEATBOX framework incorporates an observation simulator and a data assimilation system with the possibility of choosing ensemble, adjoint, or combined sensitivities. A user-friendly, Python-based interface allows for the tuning of many parameters for atmospheric chemistry and data assimilation research as well as for educational purposes, for example observation error, model covariances, ensemble size, perturbation distribution in the initial conditions, and so on. In this work, the testbed is described and two case studies are presented to illustrate the design of a typical OSSE experiment, data assimilation experiments, a sensitivity analysis, and a method for diagnosing model errors. BEATBOX is released as an open source tool for the atmospheric chemistry and data assimilation communities.

Wavelet-based compression of M-FISH images.

PubMed

Hua, Jianping; Xiong, Zixiang; Wu, Qiang; Castleman, Kenneth R

2005-05-01

Multiplex fluorescence in situ hybridization (M-FISH) is a recently developed technology that enables multi-color chromosome karyotyping for molecular cytogenetic analysis. Each M-FISH image set consists of a number of aligned images of the same chromosome specimen captured at different optical wavelength. This paper presents embedded M-FISH image coding (EMIC), where the foreground objects/chromosomes and the background objects/images are coded separately. We first apply critically sampled integer wavelet transforms to both the foreground and the background. We then use object-based bit-plane coding to compress each object and generate separate embedded bitstreams that allow continuous lossy-to-lossless compression of the foreground and the background. For efficient arithmetic coding of bit planes, we propose a method of designing an optimal context model that specifically exploits the statistical characteristics of M-FISH images in the wavelet domain. Our experiments show that EMIC achieves nearly twice as much compression as Lempel-Ziv-Welch coding. EMIC also performs much better than JPEG-LS and JPEG-2000 for lossless coding. The lossy performance of EMIC is significantly better than that of coding each M-FISH image with JPEG-2000.

Efficiency of the human observer detecting random signals in random backgrounds

PubMed Central

Park, Subok; Clarkson, Eric; Kupinski, Matthew A.; Barrett, Harrison H.

2008-01-01

The efficiencies of the human observer and the channelized-Hotelling observer relative to the ideal observer for signal-detection tasks are discussed. Both signal-known-exactly (SKE) tasks and signal-known-statistically (SKS) tasks are considered. Signal location is uncertain for the SKS tasks, and lumpy backgrounds are used for background uncertainty in both cases. Markov chain Monte Carlo methods are employed to determine ideal-observer performance on the detection tasks. Psychophysical studies are conducted to compute human-observer performance on the same tasks. Efficiency is computed as the squared ratio of the detectabilities of the observer of interest to the ideal observer. Human efficiencies are approximately 2.1% and 24%, respectively, for the SKE and SKS tasks. The results imply that human observers are not affected as much as the ideal observer by signal-location uncertainty even though the ideal observer outperforms the human observer for both tasks. Three different simplified pinhole imaging systems are simulated, and the humans and the model observers rank the systems in the same order for both the SKE and the SKS tasks. PMID:15669610

An incremental knowledge assimilation system (IKAS) for mine detection

NASA Astrophysics Data System (ADS)

Porway, Jake; Raju, Chaitanya; Varadarajan, Karthik Mahesh; Nguyen, Hieu; Yadegar, Joseph

2010-04-01

In this paper we present an adaptive incremental learning system for underwater mine detection and classification that utilizes statistical models of seabed texture and an adaptive nearest-neighbor classifier to identify varied underwater targets in many different environments. The first stage of processing uses our Background Adaptive ANomaly detector (BAAN), which identifies statistically likely target regions using Gabor filter responses over the image. Using this information, BAAN classifies the background type and updates its detection using background-specific parameters. To perform classification, a Fully Adaptive Nearest Neighbor (FAAN) determines the best label for each detection. FAAN uses an extremely fast version of Nearest Neighbor to find the most likely label for the target. The classifier perpetually assimilates new and relevant information into its existing knowledge database in an incremental fashion, allowing improved classification accuracy and capturing concept drift in the target classes. Experiments show that the system achieves >90% classification accuracy on underwater mine detection tasks performed on synthesized datasets provided by the Office of Naval Research. We have also demonstrated that the system can incrementally improve its detection accuracy by constantly learning from new samples.

Activation of the maternal caregiving system by childhood fever – a qualitative study of the experiences made by mothers with a German or a Turkish background in the care of their children

PubMed Central

2013-01-01

Background Childhood fever represents a frequent cause to consult a primary care physician. “Fever phobia” describes a fearful and irrational view of fever shared by many parents with different cultural backgrounds. The study aims to explain the experiences of mothers of children having a fever and to analyze the role of the mothers’ cultural background with regard to their experiences by comparing the accounts of mothers with a German with those from a Turkish background. Disease and context specific knowledge about the influence of culture can be important for effective counselling. Methods We applied a qualitative approach using in-depth interviews with 11 mothers with a Turkish and 9 with a German background living in Germany. The interviews were conducted at the participants´ homes from May to October 2008. Data was audio-recorded and transcribed verbatim. Grounded Theory was used as a framing methodology including open, axial and selective coding. Analysis was performed in a group with members of different professional and cultural backgrounds. Results Mothers experienced their child’s fever not merely as elevated temperature but as a potentially dangerous event. A deeply rooted urge to protect the child from harm was central to all participants’ experience. The caregiving system model offers a good theoretical foundation to explain the findings as it incorporates the unique relational quality of care giving mothers to their children. The cultural background represents an important context variable influencing the explanatory models and strategies of dealing with fever. The identified culturally influenced concepts sometimes match and sometimes conflict with medical knowledge. Conclusion By applying the caregiving system model which is a part of attachment theory (Bowlby) maternal actions can be understood as an understandable attempt to protect the child from harm. The mothers´ decisions what to do when a child has a fever can be culturally influenced. This may lead either to a frequent use of services or to an underestimation of the child’s state of health. The mothers´ caring role and emotional state should be acknowledged; her concerns, explanatory models and strategies should be elicited and taken seriously in order to maintain a trustful relationship, provide effective counselling and thereby insuring optimal care for the children. PMID:23506372

Non-Destructive Evaluation of the Leaf Nitrogen Concentration by In-Field Visible/Near-Infrared Spectroscopy in Pear Orchards.

PubMed

Wang, Jie; Shen, Changwei; Liu, Na; Jin, Xin; Fan, Xueshan; Dong, Caixia; Xu, Yangchun

2017-03-08

Non-destructive and timely determination of leaf nitrogen (N) concentration is urgently needed for N management in pear orchards. A two-year field experiment was conducted in a commercial pear orchard with five N application rates: 0 (N0), 165 (N1), 330 (N2), 660 (N3), and 990 (N4) kg·N·ha -1 . The mid-portion leaves on the year's shoot were selected for the spectral measurement first and then N concentration determination in the laboratory at 50 and 80 days after full bloom (DAB). Three methods of in-field spectral measurement (25° bare fibre under solar conditions, black background attached to plant probe, and white background attached to plant probe) were compared. We also investigated the modelling performances of four chemometric techniques (principal components regression, PCR; partial least squares regression, PLSR; stepwise multiple linear regression, SMLR; and back propagation neural network, BPNN) and three vegetation indices (difference spectral index, normalized difference spectral index, and ratio spectral index). Due to the low correlation of reflectance obtained by the 25° field of view method, all of the modelling was performed on two spectral datasets-both acquired by a plant probe. Results showed that the best modelling and prediction accuracy were found in the model established by PLSR and spectra measured with a black background. The randomly-separated subsets of calibration ( n = 1000) and validation ( n = 420) of this model resulted in high R² values of 0.86 and 0.85, respectively, as well as a low mean relative error (<6%). Furthermore, a higher coefficient of determination between the leaf N concentration and fruit yield was found at 50 DAB samplings in both 2015 (R² = 0.77) and 2014 (R² = 0.59). Thus, the leaf N concentration was suggested to be determined at 50 DAB by visible/near-infrared spectroscopy and the threshold should be 24-27 g/kg.

Improving Transferability of Introduced Species’ Distribution Models: New Tools to Forecast the Spread of a Highly Invasive Seaweed

PubMed Central

Verbruggen, Heroen; Tyberghein, Lennert; Belton, Gareth S.; Mineur, Frederic; Jueterbock, Alexander; Hoarau, Galice; Gurgel, C. Frederico D.; De Clerck, Olivier

2013-01-01

The utility of species distribution models for applications in invasion and global change biology is critically dependent on their transferability between regions or points in time, respectively. We introduce two methods that aim to improve the transferability of presence-only models: density-based occurrence thinning and performance-based predictor selection. We evaluate the effect of these methods along with the impact of the choice of model complexity and geographic background on the transferability of a species distribution model between geographic regions. Our multifactorial experiment focuses on the notorious invasive seaweed Caulerpacylindracea (previously Caulerpa racemosa var. cylindracea ) and uses Maxent, a commonly used presence-only modeling technique. We show that model transferability is markedly improved by appropriate predictor selection, with occurrence thinning, model complexity and background choice having relatively minor effects. The data shows that, if available, occurrence records from the native and invaded regions should be combined as this leads to models with high predictive power while reducing the sensitivity to choices made in the modeling process. The inferred distribution model of Caulerpacylindracea shows the potential for this species to further spread along the coasts of Western Europe, western Africa and the south coast of Australia. PMID:23950789

Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition

NASA Astrophysics Data System (ADS)

Kesrarat, Darun; Patanavijit, Vorapoj

2017-02-01

In optical flow for motion allocation, the efficient result in Motion Vector (MV) is an important issue. Several noisy conditions may cause the unreliable result in optical flow algorithms. We discover that many classical optical flows algorithms perform better result under noisy condition when combined with modern optimized model. This paper introduces effective robust models of optical flow by using Robust high reliability spatial based optical flow algorithms using the adaptive Lorentzian norm influence function in computation on simple spatial temporal optical flows algorithm. Experiment on our proposed models confirm better noise tolerance in optical flow's MV under noisy condition when they are applied over simple spatial temporal optical flow algorithms as a filtering model in simple frame-to-frame correlation technique. We illustrate the performance of our models by performing an experiment on several typical sequences with differences in movement speed of foreground and background where the experiment sequences are contaminated by the additive white Gaussian noise (AWGN) at different noise decibels (dB). This paper shows very high effectiveness of noise tolerance models that they are indicated by peak signal to noise ratio (PSNR).

Linear and non-linear perturbations in dark energy models

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

Escamilla-Rivera, Celia; Casarini, Luciano; Fabris, Júlio C.

2016-11-01

In this work we discuss observational aspects of three time-dependent parameterisations of the dark energy equation of state w ( z ). In order to determine the dynamics associated with these models, we calculate their background evolution and perturbations in a scalar field representation. After performing a complete treatment of linear perturbations, we also show that the non-linear contribution of the selected w ( z ) parameterisations to the matter power spectra is almost the same for all scales, with no significant difference from the predictions of the standard ΛCDM model.

Effects of Socio-Economic Background Factors on Typewriting Speed and Accuracy.

ERIC Educational Resources Information Center

Erickson, Lawrence W.

The socioeconomic backgrounds of typewriting students as such backgrounds affect typewriting performance is evaluated in this research. There is convincing evidence that socioeconomic factors play a significant role in affecting typewriting performance. Students from low socioeconomic backgrounds are almost always associated with the poorest…

Staggered-grid finite-difference acoustic modeling with the Time-Domain Atmospheric Acoustic Propagation Suite (TDAAPS).

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

Aldridge, David Franklin; Collier, Sandra L.; Marlin, David H.

2005-05-01

This document is intended to serve as a users guide for the time-domain atmospheric acoustic propagation suite (TDAAPS) program developed as part of the Department of Defense High-Performance Modernization Office (HPCMP) Common High-Performance Computing Scalable Software Initiative (CHSSI). TDAAPS performs staggered-grid finite-difference modeling of the acoustic velocity-pressure system with the incorporation of spatially inhomogeneous winds. Wherever practical the control structure of the codes are written in C++ using an object oriented design. Sections of code where a large number of calculations are required are written in C or F77 in order to enable better compiler optimization of these sections. Themore » TDAAPS program conforms to a UNIX style calling interface. Most of the actions of the codes are controlled by adding flags to the invoking command line. This document presents a large number of examples and provides new users with the necessary background to perform acoustic modeling with TDAAPS.« less

A study of nuclear recoil backgrounds in dark matter detectors

NASA Astrophysics Data System (ADS)

Westerdale, Shawn S.

Despite the great success of the Standard Model of particle physics, a preponderance of astrophysical evidence suggests that it cannot explain most of the matter in the universe. This so-called dark matter has eluded direct detection, though many theoretical extensions to the Standard Model predict the existence of particles with a mass on the 1-1000 GeV scale that interact only via the weak nuclear force. Particles in this class are referred to as Weakly Interacting Massive Particles (WIMPs), and their high masses and low scattering cross sections make them viable dark matter candidates. The rarity of WIMP-nucleus interactions makes them challenging to detect: any background can mask the signal they produce. Background rejection is therefore a major problem in dark matter detection. Many experiments greatly reduce their backgrounds by employing techniques to reject electron recoils. However, nuclear recoil backgrounds, which produce signals similar to what we expect from WIMPs, remain problematic. There are two primary sources of such backgrounds: surface backgrounds and neutron recoils. Surface backgrounds result from radioactivity on the inner surfaces of the detector sending recoiling nuclei into the detector. These backgrounds can be removed with fiducial cuts, at some cost to the experiment's exposure. In this dissertation we briefly discuss a novel technique for rejecting these events based on signals they make in the wavelength shifter coating on the inner surfaces of some detectors. Neutron recoils result from neutrons scattering off of nuclei in the detector. These backgrounds may produce a signal identical to what we expect from WIMPs and are extensively discussed here. We additionally present a new tool for calculating (alpha, n) yields in various materials. We introduce the concept of a neutron veto system designed to shield against, measure, and provide an anti-coincidence veto signal for background neutrons. We discuss the research and development that informed the design of the DarkSide-50 boron-loaded liquid scintillator neutron veto. We describe the specific implementation of this veto system in DarkSide-50, including a description of its performance, and show that it can reject neutrons with a high enough efficiency to allow DarkSide-50 to run background-free for three years.

Motif finding in DNA sequences based on skipping nonconserved positions in background Markov chains.

PubMed

Zhao, Xiaoyan; Sze, Sing-Hoi

2011-05-01

One strategy to identify transcription factor binding sites is through motif finding in upstream DNA sequences of potentially co-regulated genes. Despite extensive efforts, none of the existing algorithms perform very well. We consider a string representation that allows arbitrary ignored positions within the nonconserved portion of single motifs, and use O(2(l)) Markov chains to model the background distributions of motifs of length l while skipping these positions within each Markov chain. By focusing initially on positions that have fixed nucleotides to define core occurrences, we develop an algorithm to identify motifs of moderate lengths. We compare the performance of our algorithm to other motif finding algorithms on a few benchmark data sets, and show that significant improvement in accuracy can be obtained when the sites are sufficiently conserved within a given sample, while comparable performance is obtained when the site conservation rate is low. A software program (PosMotif ) and detailed results are available online at http://faculty.cse.tamu.edu/shsze/posmotif.

Nonuniform Changes in the Distribution of Visual Attention from Visual Complexity and Action: A Driving Simulation Study.

PubMed

Park, George D; Reed, Catherine L

2015-02-01

Researchers acknowledge the interplay between action and attention, but typically consider action as a response to successful attentional selection or the correlation of performance on separate action and attention tasks. We investigated how concurrent action with spatial monitoring affects the distribution of attention across the visual field. We embedded a functional field of view (FFOV) paradigm with concurrent central object recognition and peripheral target localization tasks in a simulated driving environment. Peripheral targets varied across 20-60 deg eccentricity at 11 radial spokes. Three conditions assessed the effects of visual complexity and concurrent action on the size and shape of the FFOV: (1) with no background, (2) with driving background, and (3) with driving background and vehicle steering. The addition of visual complexity slowed task performance and reduced the FFOV size but did not change the baseline shape. In contrast, the addition of steering produced not only shrinkage of the FFOV, but also changes in the FFOV shape. Nonuniform performance decrements occurred in proximal regions used for the central task and for steering, independent of interference from context elements. Multifocal attention models should consider the role of action and account for nonhomogeneities in the distribution of attention. © 2015 SAGE Publications.

Effects of mild cognitive impairment on emotional scene memory

PubMed Central

Waring, J.D.; Dimsdale-Zucker, H.R.; Flannery, S.; Budson, A.E.; Kensinger, E.A.

2017-01-01

Young and older adults experience benefits in attention and memory for emotional compared to neutral information, but this memory benefit is greatly diminished in Alzheimer’s disease (AD). Little is known about whether this impairment arises early or late in the time course between healthy aging and AD. This study compared memory for positive, negative, and neutral items with neutral backgrounds between patients with mild cognitive impairment (MCI) and healthy older adults. We also used a divided attention condition in older adults as a possible model for the deficits observed in MCI patients. Results showed a similar pattern of selective memory for emotional items while forgetting their backgrounds in older adults and MCI patients, but MCI patients had poorer memory overall. Dividing attention during encoding disproportionately reduced memory for backgrounds (versus items) relative to a full attention condition. Participants performing in the lower half on the divided attention task qualitatively and quantitatively mirrored the results in MCI patients. Exploratory analyses comparing lower- and higher-performing MCI patients showed that only higher-performing MCI patients had the characteristic scene memory pattern observed in healthy older adults. Together, these results suggest that the effects of emotion on memory are relatively well preserved for patients with MCI, although emotional memory patterns may start to be altered once memory deficits become more pronounced. PMID:28089697

Sensitivity analysis of a data assimilation technique for hindcasting and forecasting hydrodynamics of a complex coastal water body

NASA Astrophysics Data System (ADS)

Ren, Lei; Hartnett, Michael

2017-02-01

Accurate forecasting of coastal surface currents is of great economic importance due to marine activities such as marine renewable energy and fish farms in coastal regions in recent twenty years. Advanced oceanographic observation systems such as satellites and radars can provide many parameters of interest, such as surface currents and waves, with fine spatial resolution in near real time. To enhance modelling capability, data assimilation (DA) techniques which combine the available measurements with the hydrodynamic models have been used since the 1990s in oceanography. Assimilating measurements into hydrodynamic models makes the original model background states follow the observation trajectory, then uses it to provide more accurate forecasting information. Galway Bay is an open, wind dominated water body on which two coastal radars are deployed. An efficient and easy to implement sequential DA algorithm named Optimal Interpolation (OI) was used to blend radar surface current data into a three-dimensional Environmental Fluid Dynamics Code (EFDC) model. Two empirical parameters, horizontal correlation length and DA cycle length (CL), are inherent within OI. No guidance has previously been published regarding selection of appropriate values of these parameters or how sensitive OI DA is to variations in their values. Detailed sensitivity analysis has been performed on both of these parameters and results presented. Appropriate value of DA CL was examined and determined on producing the minimum Root-Mean-Square-Error (RMSE) between radar data and model background states. Analysis was performed to evaluate assimilation index (AI) of using an OI DA algorithm in the model. AI of the half-day forecasting mean vectors' directions was over 50% in the best assimilation model. The ability of using OI to improve model forecasts was also assessed and is reported upon.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

PubMed

Zhang, J; Feng, J-Y; Ni, Y-L; Wen, Y-J; Niu, Y; Tamba, C L; Yue, C; Song, Q; Zhang, Y-M

2017-06-01

Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.

Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

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

Khachatryan, Vardan

A search for heavy resonances decaying to a Higgs boson and a vector boson is presented. The analysis is performed using data samples collected in 2015 by the CMS experiment at the LHC in proton–proton collisions at a center-of-mass energy of 13 TeV, corresponding to integrated luminosities of 2.2–2.5 fb –1. The search is performed in channels in which the vector boson decays into leptonic final states (Z→νν, W→ℓν, and Z→ℓℓ, with ℓ=e,μ), while the Higgs boson decays to collimated b quark pairs detected as a single massive jet. The discriminating power of a jet mass requirement and a bmore » jet tagging algorithm are exploited to suppress the standard model backgrounds. The event yields observed in data are consistent with the background expectation. In the context of a theoretical model with a heavy vector triplet, a resonance with mass less than 2 TeV is excluded at 95% confidence level. Finally, the results are also interpreted in terms of limits on the parameters of the model, improving on the reach of previous searches.« less

Wavelet-Bayesian inference of cosmic strings embedded in the cosmic microwave background

NASA Astrophysics Data System (ADS)

McEwen, J. D.; Feeney, S. M.; Peiris, H. V.; Wiaux, Y.; Ringeval, C.; Bouchet, F. R.

2017-12-01

Cosmic strings are a well-motivated extension to the standard cosmological model and could induce a subdominant component in the anisotropies of the cosmic microwave background (CMB), in addition to the standard inflationary component. The detection of strings, while observationally challenging, would provide a direct probe of physics at very high-energy scales. We develop a framework for cosmic string inference from observations of the CMB made over the celestial sphere, performing a Bayesian analysis in wavelet space where the string-induced CMB component has distinct statistical properties to the standard inflationary component. Our wavelet-Bayesian framework provides a principled approach to compute the posterior distribution of the string tension Gμ and the Bayesian evidence ratio comparing the string model to the standard inflationary model. Furthermore, we present a technique to recover an estimate of any string-induced CMB map embedded in observational data. Using Planck-like simulations, we demonstrate the application of our framework and evaluate its performance. The method is sensitive to Gμ ∼ 5 × 10-7 for Nambu-Goto string simulations that include an integrated Sachs-Wolfe contribution only and do not include any recombination effects, before any parameters of the analysis are optimized. The sensitivity of the method compares favourably with other techniques applied to the same simulations.

Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

DOE PAGES

Khachatryan, Vardan

2017-02-22

A search for heavy resonances decaying to a Higgs boson and a vector boson is presented. The analysis is performed using data samples collected in 2015 by the CMS experiment at the LHC in proton–proton collisions at a center-of-mass energy of 13 TeV, corresponding to integrated luminosities of 2.2–2.5 fb –1. The search is performed in channels in which the vector boson decays into leptonic final states (Z→νν, W→ℓν, and Z→ℓℓ, with ℓ=e,μ), while the Higgs boson decays to collimated b quark pairs detected as a single massive jet. The discriminating power of a jet mass requirement and a bmore » jet tagging algorithm are exploited to suppress the standard model backgrounds. The event yields observed in data are consistent with the background expectation. In the context of a theoretical model with a heavy vector triplet, a resonance with mass less than 2 TeV is excluded at 95% confidence level. Finally, the results are also interpreted in terms of limits on the parameters of the model, improving on the reach of previous searches.« less

An integrated physiology model to study regional lung damage effects and the physiologic response

PubMed Central

2014-01-01

Background This work expands upon a previously developed exercise dynamic physiology model (DPM) with the addition of an anatomic pulmonary system in order to quantify the impact of lung damage on oxygen transport and physical performance decrement. Methods A pulmonary model is derived with an anatomic structure based on morphometric measurements, accounting for heterogeneous ventilation and perfusion observed experimentally. The model is incorporated into an existing exercise physiology model; the combined system is validated using human exercise data. Pulmonary damage from blast, blunt trauma, and chemical injury is quantified in the model based on lung fluid infiltration (edema) which reduces oxygen delivery to the blood. The pulmonary damage component is derived and calibrated based on published animal experiments; scaling laws are used to predict the human response to lung injury in terms of physical performance decrement. Results The augmented dynamic physiology model (DPM) accurately predicted the human response to hypoxia, altitude, and exercise observed experimentally. The pulmonary damage parameters (shunt and diffusing capacity reduction) were fit to experimental animal data obtained in blast, blunt trauma, and chemical damage studies which link lung damage to lung weight change; the model is able to predict the reduced oxygen delivery in damage conditions. The model accurately estimates physical performance reduction with pulmonary damage. Conclusions We have developed a physiologically-based mathematical model to predict performance decrement endpoints in the presence of thoracic damage; simulations can be extended to estimate human performance and escape in extreme situations. PMID:25044032

Comparison of analytical models for zonal flow generation in ion-temperature-gradient mode turbulence

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

Anderson, J.; Miki, K.; Uzawa, K.

2006-11-30

During the past years the understanding of the multi scale interaction problems have increased significantly. However, at present there exists a flora of different analytical models for investigating multi scale interactions and hardly any specific comparisons have been performed among these models. In this work two different models for the generation of zonal flows from ion-temperature-gradient (ITG) background turbulence are discussed and compared. The methods used are the coherent mode coupling model and the wave kinetic equation model (WKE). It is shown that the two models give qualitatively the same results even though the assumption on the spectral difference ismore » used in the (WKE) approach.« less

Imaging Analysis of the Hard X-Ray Telescope ProtoEXIST2 and New Techniques for High-Resolution Coded-Aperture Telescopes

NASA Technical Reports Server (NTRS)

Hong, Jaesub; Allen, Branden; Grindlay, Jonathan; Barthelmy, Scott D.

2016-01-01

Wide-field (greater than or approximately equal to 100 degrees squared) hard X-ray coded-aperture telescopes with high angular resolution (greater than or approximately equal to 2 minutes) will enable a wide range of time domain astrophysics. For instance, transient sources such as gamma-ray bursts can be precisely localized without the assistance of secondary focusing X-ray telescopes to enable rapid followup studies. On the other hand, high angular resolution in coded-aperture imaging introduces a new challenge in handling the systematic uncertainty: the average photon count per pixel is often too small to establish a proper background pattern or model the systematic uncertainty in a timescale where the model remains invariant. We introduce two new techniques to improve detection sensitivity, which are designed for, but not limited to, a high-resolution coded-aperture system: a self-background modeling scheme which utilizes continuous scan or dithering operations, and a Poisson-statistics based probabilistic approach to evaluate the significance of source detection without subtraction in handling the background. We illustrate these new imaging analysis techniques in high resolution coded-aperture telescope using the data acquired by the wide-field hard X-ray telescope ProtoEXIST2 during a high-altitude balloon flight in fall 2012. We review the imaging sensitivity of ProtoEXIST2 during the flight, and demonstrate the performance of the new techniques using our balloon flight data in comparison with a simulated ideal Poisson background.

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

Gorham, P. W.; Allison, P.; Hebert, C. L.

We report initial results of the first flight of the Antarctic Impulsive Transient Antenna (ANITA-1) 2006-2007 Long Duration Balloon flight, which searched for evidence of a diffuse flux of cosmic neutrinos above energies of E{sub {nu}}{approx_equal}3x10{sup 18} eV. ANITA-1 flew for 35 days looking for radio impulses due to the Askaryan effect in neutrino-induced electromagnetic showers within the Antarctic ice sheets. We report here on our initial analysis, which was performed as a blind search of the data. No neutrino candidates are seen, with no detected physics background. We set model-independent limits based on this result. Upper limits derived frommore » our analysis rule out the highest cosmogenic neutrino models. In a background horizontal-polarization channel, we also detect six events consistent with radio impulses from ultrahigh energy extensive air showers.« less

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

Gorham, P.W.; Allison, P.; /Hawaii U.

We report initial results of the first flight of the Antarctic Impulsive Transient Antenna (ANITA-1) 2006-2007 Long Duration Balloon flight, which searched for evidence of a diffuse flux of cosmic neutrinos above energies of E{sub v} = 3 x 10{sup 18} eV. ANITA-1 flew for 35 days looking for radio impulses due to the Askaryan effect in neutrino-induced electromagnetic showers within the Antarctic ice sheets. We report here on our initial analysis, which was performed as a blind search of the data. No neutrino candidates are seen, with no detected physics background. We set model-independent limits based on this result.more » Upper limits derived from our analysis rule out the highest cosmogenic neutrino models. In a background horizontal-polarization channel, we also detect six events consistent with radio impulses from ultrahigh energy extensive air showers.« less

Prioritizing Public- Private Partnership Models for Public Hospitals of Iran Based on Performance Indicators

PubMed Central

Gholamzadeh Nikjoo, Raana; Jabbari Beyrami, Hossein; Jannati, Ali; Asghari Jaafarabadi, Mohammad

2012-01-01

Background: The present study was conducted to scrutinize Public- Private Partnership (PPP) models in public hospitals of different countries based on performance indicators in order to se-lect appropriated models for Iran hospitals. Methods: In this mixed (quantitative-qualitative) study, systematic review and expert panel has been done to identify varied models of PPP as well as performance indicators. In the second step we prioritized performance indicator and PPP models based on selected performance indicators by Analytical Hierarchy process (AHP) technique. The data were analyzed by Excel 2007 and Expert Choice11 software’s. Results: In quality – effectiveness area, indicators like the rate of hospital infections (100%), hospital accidents prevalence rate (73%), pure rate of hospital mortality (63%), patient satisfaction percentage (53%), in accessibility equity area indicators such as average inpatient waiting time (100%) and average outpatient waiting time (74%), and in financial – efficiency area, indicators including average length of stay (100%), bed occupation ratio (99%), specific income to total cost ratio (97%) have been chosen to be the most key performance indicators. In the pri¬oritization of the PPP models clinical outsourcing, management, privatization, BOO (build, own, operate) and non-clinical outsourcing models, achieved high priority for various performance in¬dicator areas. Conclusion: This study had been provided the most common PPP options in the field of public hospitals and had gathered suitable evidences from experts for choosing appropriate PPP option for public hospitals. Effect of private sector presence in public hospital performance, based on which PPP options undertaken, will be different. PMID:24688942

Growth curve analyses of the relationship between early maternal age and children's mathematics and reading performance.

PubMed

Torres, D Diego

2015-03-01

Regarding the methods used to examine the early maternal age-child academic outcomes relationship, the extant literature has tended to examine change using statistical analyses that fail to appreciate that individuals vary in their rates of growth. Of the one study I have been able to find that employs a true growth model to estimate this relationship, the authors only controlled for characteristics of the maternal household after family formation; confounding background factors of mothers that might select them into early childbearing, a possible source of bias, were ignored. The authors' findings nonetheless suggested an inverse relationship between early maternal age, i.e., a first birth between the ages of 13 and 17, and Canadian adolescents' mean math performance at age 10. Early maternal age was not related to the linear slope of age. To elucidate whether the early maternal age-child academic outcomes association, treated in a growth context, is consistent with this finding, the present study built on it using US data and explored children's mathematics and reading trajectories from age 5 on. Its unique contribution is that it further explicitly controlled for maternal background factors and employed a three-level growth model with repeated measures of children nested within their mothers. Though the strength of the relationship varied between mean initial academic performance and mean academic growth, results confirmed that early maternal age was negatively related to children's mathematics and reading achievement, net of post-teen first birth child-specific and maternal household factors. Once maternal background factors were included, there was no statistically significant relationship between early maternal age and either children's mean initial mathematics and reading scores or their mean mathematics and reading growth. Copyright © 2014 Elsevier Inc. All rights reserved.

Application of seemingly unrelated regression in medical data with intermittently observed time-dependent covariates.

PubMed

Keshavarzi, Sareh; Ayatollahi, Seyyed Mohammad Taghi; Zare, Najaf; Pakfetrat, Maryam

2012-01-01

BACKGROUND. In many studies with longitudinal data, time-dependent covariates can only be measured intermittently (not at all observation times), and this presents difficulties for standard statistical analyses. This situation is common in medical studies, and methods that deal with this challenge would be useful. METHODS. In this study, we performed the seemingly unrelated regression (SUR) based models, with respect to each observation time in longitudinal data with intermittently observed time-dependent covariates and further compared these models with mixed-effect regression models (MRMs) under three classic imputation procedures. Simulation studies were performed to compare the sample size properties of the estimated coefficients for different modeling choices. RESULTS. In general, the proposed models in the presence of intermittently observed time-dependent covariates showed a good performance. However, when we considered only the observed values of the covariate without any imputations, the resulted biases were greater. The performances of the proposed SUR-based models in comparison with MRM using classic imputation methods were nearly similar with approximately equal amounts of bias and MSE. CONCLUSION. The simulation study suggests that the SUR-based models work as efficiently as MRM in the case of intermittently observed time-dependent covariates. Thus, it can be used as an alternative to MRM.

Performance Testing of a Trace Contaminant Control Subassembly for the International Space Station

NASA Technical Reports Server (NTRS)

Perry, J. L.; Curtis, R. E.; Alexandre, K. L.; Ruggiero, L. L.; Shtessel, N.

1998-01-01

As part of the International Space Station (ISS) Trace Contaminant Control Subassembly (TCCS) development, a performance test has been conducted to provide reference data for flight verification analyses. This test, which used the U.S. Habitation Module (U.S. Hab) TCCS as the test article, was designed to add to the existing database on TCCS performance. Included in this database are results obtained during ISS development testing; testing of functionally similar TCCS prototype units; and bench scale testing of activated charcoal, oxidation catalyst, and granular lithium hydroxide (LiOH). The present database has served as the basis for the development and validation of a computerized TCCS process simulation model. This model serves as the primary means for verifying the ISS TCCS performance. In order to mitigate risk associated with this verification approach, the U.S. Hab TCCS performance test provides an additional set of data which serve to anchor both the process model and previously-obtained development test data to flight hardware performance. The following discussion provides relevant background followed by a summary of the test hardware, objectives, requirements, and facilities. Facility and test article performance during the test is summarized, test results are presented, and the TCCS's performance relative to past test experience is discussed. Performance predictions made with the TCCS process model are compared with the U.S. Hab TCCS test results to demonstrate its validation.

Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations . Part II; Sensitivity Tests and Results

NASA Technical Reports Server (NTRS)

da Silva, Arlindo M.; Norris, Peter M.

2013-01-01

Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

Influence of temperature fluctuations on infrared limb radiance: a new simulation code

NASA Astrophysics Data System (ADS)

Rialland, Valérie; Chervet, Patrick

2006-08-01

Airborne infrared limb-viewing detectors may be used as surveillance sensors in order to detect dim military targets. These systems' performances are limited by the inhomogeneous background in the sensor field of view which impacts strongly on target detection probability. This background clutter, which results from small-scale fluctuations of temperature, density or pressure must therefore be analyzed and modeled. Few existing codes are able to model atmospheric structures and their impact on limb-observed radiance. SAMM-2 (SHARC-4 and MODTRAN4 Merged), the Air Force Research Laboratory (AFRL) background radiance code can be used to in order to predict the radiance fluctuation as a result of a normalized temperature fluctuation, as a function of the line-of-sight. Various realizations of cluttered backgrounds can then be computed, based on these transfer functions and on a stochastic temperature field. The existing SIG (SHARC Image Generator) code was designed to compute the cluttered background which would be observed from a space-based sensor. Unfortunately, this code was not able to compute accurate scenes as seen by an airborne sensor especially for lines-of-sight close to the horizon. Recently, we developed a new code called BRUTE3D and adapted to our configuration. This approach is based on a method originally developed in the SIG model. This BRUTE3D code makes use of a three-dimensional grid of temperature fluctuations and of the SAMM-2 transfer functions to synthesize an image of radiance fluctuations according to sensor characteristics. This paper details the working principles of the code and presents some output results. The effects of the small-scale temperature fluctuations on infrared limb radiance as seen by an airborne sensor are highlighted.

Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling.

PubMed

Mainali, Kumar P; Warren, Dan L; Dhileepan, Kunjithapatham; McConnachie, Andrew; Strathie, Lorraine; Hassan, Gul; Karki, Debendra; Shrestha, Bharat B; Parmesan, Camille

2015-12-01

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium. However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. © 2015 John Wiley & Sons Ltd.

The Impact of Background Radio and Television on High School Students' Homework Performance.

ERIC Educational Resources Information Center

Pool, Marina M.; Koolstra, Cees M.; van der Voort, Tom H. A.

2003-01-01

Examines the impact of background media on Dutch students' performance and time spent on paper-and-pencil and memorization homework assignments. Notes that doing homework combined with watching a soap opera interfered with students' performance on both types of assignments. Indicates that music in the background left homework performance…

Kindergarten Students' Qualitative Responses to Different Instructional Strategies during the Horizontal Jump

ERIC Educational Resources Information Center

Weimar, Wendi H.; Martin, Ellen H.; Wall, Sarah J.

2011-01-01

Background: The teaching strategies of modeling and the use of cue words are employed by both experienced and inexperienced teachers. While these strategies have received some attention in the literature, the effectiveness of these strategies in terms of the resultant change in the quality or kinematics of the motor skill performance has been…

Overview of Management Theory

DTIC Science & Technology

1991-02-01

theory orients command leadership for the enormous task of managing organizations in our environment fraught with volatility, uncertainty...performance and organizational ethics. A THEORY OF MANAGEMENT BACKGROUND BASIC MANAGEMENT BEHAVIORAL Definitions FUNCTIONS ASPECTS History Planning Leadership ...the best way to manage in their theory of managerial leadership . To them, the 9,9 position on their model, "is acknowledged by managers as the

Developing and Evaluating Gamifying Learning System by Using Flow-Based Model

ERIC Educational Resources Information Center

Su, Chung-Ho; Hsaio, Kai-Chong

2015-01-01

Game-based learning is an effective learning method, whose performance depends on the quality of the educational game. Due to versatile game environments with complex backgrounds, evaluations are not easy to implement. Consequently, it is difficult for educators to determine to what degree a game may be qualified. This study proposes a novel,…

Incidental Learning Speeds Visual Search by Lowering Response Thresholds, Not by Improving Efficiency: Evidence from Eye Movements

ERIC Educational Resources Information Center

Hout, Michael C.; Goldinger, Stephen D.

2012-01-01

When observers search for a target object, they incidentally learn the identities and locations of "background" objects in the same display. This learning can facilitate search performance, eliciting faster reaction times for repeated displays. Despite these findings, visual search has been successfully modeled using architectures that maintain no…

School Performance, Status Relations, and the Structure of Sentiment: Bringing the Teacher Back In.

ERIC Educational Resources Information Center

Alexander, Karl L; And Others

1987-01-01

Teachers' social origins influence their reactions to students. Low-status and minority students experience difficulties in the classrooms of high-status teachers. Outcomes of these relationships are that the students are seen as less mature and less is expected of them. A model of teacher-pupil background congruence is proposed. (Author/VM)

Efficiency in Vocational Rehabilitation Program Service Delivery: The Impact of Socioeconomic Context

ERIC Educational Resources Information Center

Gere, Bryan O.; Burnett, Royce D.; Flowers, Carl R.; Akaaboune, Ouadie

2017-01-01

Background: State-federal (VR) program efficiency is the focus of empirical research because of increases in the magnitude and types of program requests, possibly funding cuts and class for models to more appropriately measure and evaluate performance. Objective: The purpose of this study was to examine the impact socioeconomic diversity has on…

Race, Poverty and SAT Scores: Modeling the Influences of Family Income on Black and White High School Students' SAT Performance

ERIC Educational Resources Information Center

Dixon-Roman, Ezekiel J.; Everson, Howard T.; McArdle, John J.

2013-01-01

Background: Educational policy makers and test critics often assert that standardized test scores are strongly influenced by factors beyond individual differences in academic achievement such as family income and wealth. Unfortunately, few empirical studies consider the simultaneous and related influences of family income, parental education, and…

Using multi-trait and random regression models to identify genetic variation in tolerance of pigs to Porcine Reproductive and Respiratory Syndrome virus

USDA-ARS?s Scientific Manuscript database

Background A host can adopt two response strategies to infection: resistance (reduce pathogen load) and tolerance (minimize impact of infection on performance). Both strategies may be under genetic control and could thus be targeted for genetic improvement. Although there is evidence in support of a...

Search for production of an $$\\Upsilon$$(1S) meson in association with a W or Z boson using the full 1.96 TeV $$p\\bar{p}$$ collision data set at CDF

DOE PAGES

Aaltonen, T.

2015-03-17

Production of the Υ(1S) meson in association with a vector boson is a rare process in the standard model with a cross section predicted to be below the sensitivity of the Tevatron. Observation of this process could signify contributions not described by the standard model or reveal limitations with the current nonrelativistic quantum-chromodynamic models used to calculate the cross section. We perform a search for this process using the full Run II data set collected by the CDF II detector corresponding to an integrated luminosity of 9.4 fb -1. Our search considers the Υ→μμ decay and the decay of themore » W and Z bosons into muons and electrons. Furthermore, in these purely leptonic decay channels, we observe one ΥW candidate with an expected background of 1.2±0.5 events, and one ΥZcandidate with an expected background of 0.1±0.1 events. Both observations are consistent with the predicted background contributions. The resulting upper limits on the cross section for Υ+W/Zproduction are the most sensitive reported from a single experiment and place restrictions on potential contributions from non-standard-model physics.« less

Lesion detection performance of cone beam CT images with anatomical background noise: single-slice vs. multi-slice human and model observer study

NASA Astrophysics Data System (ADS)

Han, Minah; Jang, Hanjoo; Baek, Jongduk

2018-03-01

We investigate lesion detectability and its trends for different noise structures in single-slice and multislice CBCT images with anatomical background noise. Anatomical background noise is modeled using a power law spectrum of breast anatomy. Spherical signal with a 2 mm diameter is used for modeling a lesion. CT projection data are acquired by the forward projection and reconstructed by the Feldkamp-Davis-Kress algorithm. To generate different noise structures, two types of reconstruction filters (Hanning and Ram-Lak weighted ramp filters) are used in the reconstruction, and the transverse and longitudinal planes of reconstructed volume are used for detectability evaluation. To evaluate single-slice images, the central slice, which contains the maximum signal energy, is used. To evaluate multislice images, central nine slices are used. Detectability is evaluated using human and model observer studies. For model observer, channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels are used. For all noise structures, detectability by a human observer is higher for multislice images than single-slice images, and the degree of detectability increase in multislice images depends on the noise structure. Variation in detectability for different noise structures is reduced in multislice images, but detectability trends are not much different between single-slice and multislice images. The CHO with D-DOG channels predicts detectability by a human observer well for both single-slice and multislice images.

PCA-based approach for subtracting thermal background emission in high-contrast imaging data

NASA Astrophysics Data System (ADS)

Hunziker, S.; Quanz, S. P.; Amara, A.; Meyer, M. R.

2018-03-01

Aims.Ground-based observations at thermal infrared wavelengths suffer from large background radiation due to the sky, telescope and warm surfaces in the instrument. This significantly limits the sensitivity of ground-based observations at wavelengths longer than 3 μm. The main purpose of this work is to analyse this background emission in infrared high-contrast imaging data as illustrative of the problem, show how it can be modelled and subtracted and demonstrate that it can improve the detection of faint sources, such as exoplanets. Methods: We used principal component analysis (PCA) to model and subtract the thermal background emission in three archival high-contrast angular differential imaging datasets in the M' and L' filter. We used an M' dataset of β Pic to describe in detail how the algorithm works and explain how it can be applied. The results of the background subtraction are compared to the results from a conventional mean background subtraction scheme applied to the same dataset. Finally, both methods for background subtraction are compared by performing complete data reductions. We analysed the results from the M' dataset of HD 100546 only qualitatively. For the M' band dataset of β Pic and the L' band dataset of HD 169142, which was obtained with an angular groove phase mask vortex vector coronagraph, we also calculated and analysed the achieved signal-to-noise ratio (S/N). Results: We show that applying PCA is an effective way to remove spatially and temporarily varying thermal background emission down to close to the background limit. The procedure also proves to be very successful at reconstructing the background that is hidden behind the point spread function. In the complete data reductions, we find at least qualitative improvements for HD 100546 and HD 169142, however, we fail to find a significant increase in S/N of β Pic b. We discuss these findings and argue that in particular datasets with strongly varying observing conditions or infrequently sampled sky background will benefit from the new approach.

Asian American women in science, engineering, and mathematics: Background contextual and college environment influences on self-efficacy and academic achievement

NASA Astrophysics Data System (ADS)

Vogt, Kristen E.

2005-07-01

The purpose of this research study was to examine, for undergraduate women of various Asian American ethnic backgrounds, the influence of background contextual and college environment factors on their sense of academic self-efficacy and achievement in science, technology, engineering, and mathematics (STEM) majors. Social cognitive career theory and its critiques provided a theoretical foundation for relationships from past performance, socioeconomic status, acculturation, and college environment variables (compositional diversity, racial climate, gendered climate, academic peer support), to academic self-efficacy and achievement. Data were collected through an online survey. Instrumentation included the scales of Language, Identity, and Behavioral Acculturation; Gender Discrimination; Faculty and Classroom Behavior; Interactions with Peers; and Academic Milestones Self-efficacy. The participants were 228 Asian American undergraduate women in STEM at a large public, doctoral research extensive university on the east coast; the response rate was 51%. In three MANOVAs for nine social cognitive career variables, four ethnic groups (East, South, Southeast, and Multi-ethnic Asian American) significantly differed only on socioeconomic status. In path analysis, the initial model was not a good fit and was rejected. The model was respecified through statistical and theoretical evaluation, tested in exploratory analysis, and considered a good fit. The respecified model explained 36% of semester GPA (achievement) and 28% of academic self-efficacy. The academic achievement of Asian American women in STEM was related to past performance, background contextual factors, academic self-efficacy, academic peer support, and gendered climate. The strongest direct influence on achievement was academic self-efficacy followed by past performance. The total effect of Asian acculturation on achievement was negative and the total effect of American acculturation on achievement was not significant; academic self-efficacy mediated these complex relationships. The total effects of racial and gendered compositional diversity and racial climate on both academic self-efficacy and achievement were not significant. Students in majors with more female peers reported less academic peer support. In this study, when culturally specific variables embellished social cognitive career theory, the theory exhibited cultural validity for undergraduate Asian American women in STEM. The nature of the relationships among culturally specific variables and college environment variables, however, requires further study.

Spectrophotometric Analysis of Pigments: A Critical Assessment of a High-Throughput Method for Analysis of Algal Pigment Mixtures by Spectral Deconvolution

PubMed Central

Thrane, Jan-Erik; Kyle, Marcia; Striebel, Maren; Haande, Sigrid; Grung, Merete; Rohrlack, Thomas; Andersen, Tom

2015-01-01

The Gauss-peak spectra (GPS) method represents individual pigment spectra as weighted sums of Gaussian functions, and uses these to model absorbance spectra of phytoplankton pigment mixtures. We here present several improvements for this type of methodology, including adaptation to plate reader technology and efficient model fitting by open source software. We use a one-step modeling of both pigment absorption and background attenuation with non-negative least squares, following a one-time instrument-specific calibration. The fitted background is shown to be higher than a solvent blank, with features reflecting contributions from both scatter and non-pigment absorption. We assessed pigment aliasing due to absorption spectra similarity by Monte Carlo simulation, and used this information to select a robust set of identifiable pigments that are also expected to be common in natural samples. To test the method’s performance, we analyzed absorbance spectra of pigment extracts from sediment cores, 75 natural lake samples, and four phytoplankton cultures, and compared the estimated pigment concentrations with concentrations obtained using high performance liquid chromatography (HPLC). The deviance between observed and fitted spectra was generally very low, indicating that measured spectra could successfully be reconstructed as weighted sums of pigment and background components. Concentrations of total chlorophylls and total carotenoids could accurately be estimated for both sediment and lake samples, but individual pigment concentrations (especially carotenoids) proved difficult to resolve due to similarity between their absorbance spectra. In general, our modified-GPS method provides an improvement of the GPS method that is a fast, inexpensive, and high-throughput alternative for screening of pigment composition in samples of phytoplankton material. PMID:26359659

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results

PubMed Central

Norris, Peter M.; da Silva, Arlindo M.

2018-01-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational–Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state. PMID:29618848

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 2: Sensitivity Tests and Results

NASA Technical Reports Server (NTRS)

Norris, Peter M.; da Silva, Arlindo M.

2016-01-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results.

PubMed

Norris, Peter M; da Silva, Arlindo M

2016-07-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.

Background Error Correlation Modeling with Diffusion Operators

DTIC Science & Technology

2013-01-01

RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) 07-10-2013 Book Chapter Background Error Correlation Modeling with Diffusion Operators...normalization Unclassified Unclassified Unclassified UU 27 Max Yaremchuk (228) 688-5259 Reset Chapter 8 Background error correlation modeling with diffusion ...field, then a structure like this simulates enhanced diffusive transport of model errors in the regions of strong cur- rents on the background of

Quantum gravitational contributions to the cosmic microwave background anisotropy spectrum.

PubMed

Kiefer, Claus; Krämer, Manuel

2012-01-13

We derive the primordial power spectrum of density fluctuations in the framework of quantum cosmology. For this purpose we perform a Born-Oppenheimer approximation to the Wheeler-DeWitt equation for an inflationary universe with a scalar field. In this way, we first recover the scale-invariant power spectrum that is found as an approximation in the simplest inflationary models. We then obtain quantum gravitational corrections to this spectrum and discuss whether they lead to measurable signatures in the cosmic microwave background anisotropy spectrum. The nonobservation so far of such corrections translates into an upper bound on the energy scale of inflation.

The role of family social background and inheritance in later life volunteering: Evidence from SHARE-Israel

PubMed Central

Youssim, Iaroslav; Hank, Karsten; Litwin, Howard

2014-01-01

Building on a tripartite model of capitals necessary to perform productive activities and on work suggesting that cumulative (dis-) advantage processes are important mechanisms for life-course inequalities, our study set out to investigate the potential role of family social background and inheritance in later-life volunteering. We hypothesized that older individuals who inherited work-relevant economic and cultural capitals from their family of origin are more likely to be engaged in voluntary activities than their counterparts with a less advantageous family social background. Our main findings from the analysis of a representative sample of community-dwelling Israelis aged 50 and over provide strong support for this hypothesis: the likelihood to volunteer is significantly higher among those who received substantial financial transfers from their family of origin (‘inherited economic capital’) and among those having a ‘white collar’ parental background (‘inherited cultural capital’). We conclude with perspectives for future research. PMID:25651548

The role of family social background and inheritance in later life volunteering: evidence from SHARE-Israel.

PubMed

Youssim, Iaroslav; Hank, Karsten; Litwin, Howard

2015-01-01

Building on a tripartite model of capitals necessary to perform productive activities and on work suggesting that cumulative (dis-)advantage processes are important mechanisms for life course inequalities, our study set out to investigate the potential role of family social background and inheritance in later life volunteering. We hypothesized that older individuals who inherited work-relevant economic and cultural capitals from their family of origin are more likely to be engaged in voluntary activities than their counterparts with a less advantageous family social background. Our main findings from the analysis of a representative sample of community-dwelling Israelis aged 50 and over provide strong support for this hypothesis: the likelihood to volunteer is significantly higher among those who received substantial financial transfers from their family of origin ("inherited economic capital") and among those having a "white collar" parental background ("inherited cultural capital"). We conclude with perspectives for future research. © The Author(s) 2014.

LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

NASA Technical Reports Server (NTRS)

Smith, James A.

1992-01-01

The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI < 1.0) with varying soil reflectance backgrounds is particularly difficult. Standard multiple regression methods applied to canopies within a single homogeneous soil type yield good results but perform unacceptably when applied across soil boundaries, resulting in absolute percentage errors of >1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

A Flexible Cosmic Ultraviolet Background Model

NASA Astrophysics Data System (ADS)

McQuinn, Matthew

2016-10-01

HST studies of the IGM, of the CGM, and of reionization-era galaxies are all aided by ionizing background models, which are a critical input in modeling the ionization state of diffuse, 10^4 K gas. The ionization state in turn enables the determination of densities and sizes of absorbing clouds and, when applied to the Ly-a forest, the global ionizing emissivity of sources. Unfortunately, studies that use these background models have no way of gauging the amount of uncertainty in the adopted model other than to recompute their results using previous background models with outdated observational inputs. As of yet there has been no systematic study of uncertainties in the background model and there unfortunately is no publicly available ultraviolet background code. A public code would enable users to update the calculation with the latest observational constraints, and it would allow users to experiment with varying the background model's assumptions regarding emissions and absorptions. We propose to develop a publicly available ionizing background code and, as an initial application, quantify the level of uncertainty in the ionizing background spectrum across cosmic time. As the background model improves, so does our understanding of (1) the sources that dominate ionizing emissions across cosmic time and (2) the properties of diffuse gas in the circumgalactic medium, the WHIM, and the Ly-a forest. HST is the primary telescope for studying both the highest redshift galaxies and low-redshift diffuse gas. The proposed program would benefit HST studies of the Universe at z 0 all the way up to z = 10, including of high-z galaxies observed in the HST Frontier Fields.

The MAJORANA DEMONSTRATOR for 0νββ: Current Status and Future Plans

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

Green, M. P.; Abgrall, N.; Aguayo, Estanislao

2015-03-24

The Majorana Demonstrator will search for neutrinoless-double-beta decay in 76Ge, while establishing the feasibility of a future tonne-scale germanium-based neutrinoless-double-beta decay experiment, and performing searches for new physics beyond the Standard Model. The experiment, currently under construction at the Sanford Underground Research Facility in Lead, SD, will consist of a pair of modular high-purity germanium detector arrays housed inside of a compact copper, lead, and polyethylene shield. Through a combination of strict materials qualifications and assay, low-background design, and powerful background rejection techniques, the Demonstrator aims to achieve a background rate in the neutrinoless-double-beta decay region of interest (ROI) ofmore » no more than 3cnts/(ROI-t-y). The current status of the Demonstrator is discussed, as are plans for its completion.« less

Parameter estimation for the exponential-normal convolution model for background correction of affymetrix GeneChip data.

PubMed

McGee, Monnie; Chen, Zhongxue

2006-01-01

There are many methods of correcting microarray data for non-biological sources of error. Authors routinely supply software or code so that interested analysts can implement their methods. Even with a thorough reading of associated references, it is not always clear how requisite parts of the method are calculated in the software packages. However, it is important to have an understanding of such details, as this understanding is necessary for proper use of the output, or for implementing extensions to the model. In this paper, the calculation of parameter estimates used in Robust Multichip Average (RMA), a popular preprocessing algorithm for Affymetrix GeneChip brand microarrays, is elucidated. The background correction method for RMA assumes that the perfect match (PM) intensities observed result from a convolution of the true signal, assumed to be exponentially distributed, and a background noise component, assumed to have a normal distribution. A conditional expectation is calculated to estimate signal. Estimates of the mean and variance of the normal distribution and the rate parameter of the exponential distribution are needed to calculate this expectation. Simulation studies show that the current estimates are flawed; therefore, new ones are suggested. We examine the performance of preprocessing under the exponential-normal convolution model using several different methods to estimate the parameters.

Cardiac Teratogenicity in Mouse Maternal Phenylketonuria: Defining phenotype parameters and genetic background influences

PubMed Central

Seagraves, Nikki J.; McBride, Kim L.

2012-01-01

Maternal phenylketonuria (MPKU) is a syndrome including cardiovascular malformations (CVMs), microcephaly, intellectual impairment, and small for gestational age, caused by in-utero exposure to elevated serum phenylalanine (Phe) due to PKU in the mother. It is becoming a public health concern as more women with PKU reach child bearing age. Although a mouse model of PKU, BTBR Pahenu2, has been available for 20 years, it has not been well utilized for studying MPKU. We used this model to delineate critical parameters in Phe cardiovascular teratogenicity and study the effect of genetic background. Dosing and timing experiments were performed with the BTBR Pahenu2 mouse. A dose response curve was noted, with CVM rates at maternal serum Phe levels <360 μM (control), 360 – 600 μM (low), 600 – 900 μM (mid), and >900μM (high) of 11.86%, 16.67%, 30.86%, and 46.67% respectively. A variety of CVMs were noted on the BTBR background, including double outlet right ventricle (DORV), aortic arch artery (AAA)abnormalities, and ventricular septal defects (VSDs). Timed exposure experiments identified a teratogenic window from embryonic day 8.5-13.5, with higher rates of conotruncal and valve defects occurring in early exposure time and persistent truncus arteriosus (PTA) and aortic arch branching abnormalities occurring with late exposure. Compared to the BTBR strain, N10+ Pahenu2 congenics on the C3H/HeJ background had higher rates of CVMs in general and propensity to left ventricular outflow tract (LVOT) malformations, while the C57B/L6 background had similar CVM rates but predominately AAA abnormalities. We have delineated key parameters of Phe cardiovascular teratogenicity, demonstrated the utility of this MPKU model on different mouse strains, and shown how genetic background profoundly affects the phenotype. PMID:22951387

RenderView: physics-based multi- and hyperspectral rendering using measured background panoramics

NASA Astrophysics Data System (ADS)

Talcott, Denise M.; Brown, Wade W.; Thomas, David J.

2003-09-01

As part of the survivability engineering process it is necessary to accurately model and visualize the vehicle signatures in multi- or hyperspectral bands of interest. The signature at a given wavelength is a function of the surface optical properties, reflection of the background and, in the thermal region, the emission of thermal radiation. Currently, it is difficult to obtain and utilize background models that are of sufficient fidelity when compared with the vehicle models. In addition, the background models create an additional layer of uncertainty in estimating the vehicles signature. Therefore, to meet exacting rendering requirements we have developed RenderView, which incorporates the full bidirectional reflectance distribution function (BRDF). Instead of using a modeled background we have incorporated a measured calibrated background panoramic image to provide the high fidelity background interaction. Uncertainty in the background signature is reduced to the error in the measurement which is considerably smaller than the uncertainty inherent in a modeled background. RenderView utilizes a number of different descriptions of the BRDF, including the Sandford-Robertson. In addition, it provides complete conservation of energy with off axis sampling. A description of RenderView will be presented along with a methodology developed for collecting background panoramics. Examples of the RenderView output and the background panoramics will be presented along with our approach to handling the solar irradiance problem.

Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing.

PubMed

Fredrikson, Matthew; Lantz, Eric; Jha, Somesh; Lin, Simon; Page, David; Ristenpart, Thomas

2014-08-01

We initiate the study of privacy in pharmacogenetics, wherein machine learning models are used to guide medical treatments based on a patient's genotype and background. Performing an in-depth case study on privacy in personalized warfarin dosing, we show that suggested models carry privacy risks, in particular because attackers can perform what we call model inversion : an attacker, given the model and some demographic information about a patient, can predict the patient's genetic markers. As differential privacy (DP) is an oft-proposed solution for medical settings such as this, we evaluate its effectiveness for building private versions of pharmacogenetic models. We show that DP mechanisms prevent our model inversion attacks when the privacy budget is carefully selected . We go on to analyze the impact on utility by performing simulated clinical trials with DP dosing models. We find that for privacy budgets effective at preventing attacks, patients would be exposed to increased risk of stroke, bleeding events, and mortality . We conclude that current DP mechanisms do not simultaneously improve genomic privacy while retaining desirable clinical efficacy, highlighting the need for new mechanisms that should be evaluated in situ using the general methodology introduced by our work.

Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing

PubMed Central

Fredrikson, Matthew; Lantz, Eric; Jha, Somesh; Lin, Simon; Page, David; Ristenpart, Thomas

2014-01-01

We initiate the study of privacy in pharmacogenetics, wherein machine learning models are used to guide medical treatments based on a patient’s genotype and background. Performing an in-depth case study on privacy in personalized warfarin dosing, we show that suggested models carry privacy risks, in particular because attackers can perform what we call model inversion: an attacker, given the model and some demographic information about a patient, can predict the patient’s genetic markers. As differential privacy (DP) is an oft-proposed solution for medical settings such as this, we evaluate its effectiveness for building private versions of pharmacogenetic models. We show that DP mechanisms prevent our model inversion attacks when the privacy budget is carefully selected. We go on to analyze the impact on utility by performing simulated clinical trials with DP dosing models. We find that for privacy budgets effective at preventing attacks, patients would be exposed to increased risk of stroke, bleeding events, and mortality. We conclude that current DP mechanisms do not simultaneously improve genomic privacy while retaining desirable clinical efficacy, highlighting the need for new mechanisms that should be evaluated in situ using the general methodology introduced by our work. PMID:27077138

Performance and Facility Background Pressure Characterization Tests of NASAs 12.5-kW Hall Effect Rocket with Magnetic Shielding Thruster

NASA Technical Reports Server (NTRS)

Kamhawi, Hani; Huang, Wensheng; Haag, Thomas; Shastry, Rohit; Thomas, Robert; Yim, John; Herman, Daniel; Williams, George; Myers, James; Hofer, Richard;

High dimensional biological data retrieval optimization with NoSQL technology

PubMed Central

2014-01-01

Background High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. Results In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. Conclusions The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating tranSMART's implementation to a more scalable solution for Big Data. PMID:25435347

37 CFR 253.4 - Performance of musical compositions by PBS, NPR and other public broadcasting entities engaged in...

Code of Federal Regulations, 2014 CFR

2014-07-01

... performance of such a work as background or theme music in a PBS program: 2003-2007 $56.81 (3) For performance... such a work as background or theme music in a program of a station of PBS: 2003-2007 $4.04 (5) For the... a work as background or theme music in an NPR program: 2003-2007 $5.51 (7) For the performance of...

Modeling the influence of Chevron alignment sign on young male driver performance: A driving simulator study.

PubMed

Wu, Yiping; Zhao, Xiaohua; Chen, Chen; He, Jiayuan; Rong, Jian; Ma, Jianming

2016-10-01

In China, the Chevron alignment sign on highways is a vertical rectangle with a white arrow and border on a blue background, which differs from its counterpart in other countries. Moreover, little research has been devoted to the effectiveness of China's Chevron signs; there is still no practical method to quantitatively describe the impact of Chevron signs on driver performance in roadway curves. In this paper, a driving simulator experiment collected data on the driving performance of 30 young male drivers as they navigated on 29 different horizontal curves under different conditions (presence of Chevron signs, curve radius and curve direction). To address the heterogeneity issue in the data, three models were estimated and tested: a pooled data linear regression model, a fixed effects model, and a random effects model. According to the Hausman Test and Akaike Information Criterion (AIC), the random effects model offers the best fit. The current study explores the relationship between driver performance (i.e., vehicle speed and lane position) and horizontal curves with respect to the horizontal curvature, presence of Chevron signs, and curve direction. This study lays a foundation for developing procedures and guidelines that would allow more uniform and efficient deployment of Chevron signs on China's highways. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China

PubMed Central

Wu, Wei; Guo, Junqiao; An, Shuyi; Guan, Peng; Ren, Yangwu; Xia, Linzi; Zhou, Baosen

2015-01-01

Background Cases of hemorrhagic fever with renal syndrome (HFRS) are widely distributed in eastern Asia, especially in China, Russia, and Korea. It is proved to be a difficult task to eliminate HFRS completely because of the diverse animal reservoirs and effects of global warming. Reliable forecasting is useful for the prevention and control of HFRS. Methods Two hybrid models, one composed of nonlinear autoregressive neural network (NARNN) and autoregressive integrated moving average (ARIMA) the other composed of generalized regression neural network (GRNN) and ARIMA were constructed to predict the incidence of HFRS in the future one year. Performances of the two hybrid models were compared with ARIMA model. Results The ARIMA, ARIMA-NARNN ARIMA-GRNN model fitted and predicted the seasonal fluctuation well. Among the three models, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA-NARNN hybrid model was the lowest both in modeling stage and forecasting stage. As for the ARIMA-GRNN hybrid model, the MSE, MAE and MAPE of modeling performance and the MSE and MAE of forecasting performance were less than the ARIMA model, but the MAPE of forecasting performance did not improve. Conclusion Developing and applying the ARIMA-NARNN hybrid model is an effective method to make us better understand the epidemic characteristics of HFRS and could be helpful to the prevention and control of HFRS. PMID:26270814

Activation of the maternal caregiving system by childhood fever--a qualitative study of the experiences made by mothers with a German or a Turkish background in the care of their children.

PubMed

Langer, Thorsten; Pfeifer, Miriam; Soenmez, Aynur; Kalitzkus, Vera; Wilm, Stefan; Schnepp, Wilfried

2013-03-18

Childhood fever represents a frequent cause to consult a primary care physician. "Fever phobia" describes a fearful and irrational view of fever shared by many parents with different cultural backgrounds. The study aims to explain the experiences of mothers of children having a fever and to analyze the role of the mothers' cultural background with regard to their experiences by comparing the accounts of mothers with a German with those from a Turkish background. Disease and context specific knowledge about the influence of culture can be important for effective counselling. We applied a qualitative approach using in-depth interviews with 11 mothers with a Turkish and 9 with a German background living in Germany. The interviews were conducted at the participants' homes from May to October 2008. Data was audio-recorded and transcribed verbatim. Grounded Theory was used as a framing methodology including open, axial and selective coding. Analysis was performed in a group with members of different professional and cultural backgrounds. Mothers experienced their child's fever not merely as elevated temperature but as a potentially dangerous event. A deeply rooted urge to protect the child from harm was central to all participants' experience. The caregiving system model offers a good theoretical foundation to explain the findings as it incorporates the unique relational quality of care giving mothers to their children. The cultural background represents an important context variable influencing the explanatory models and strategies of dealing with fever. The identified culturally influenced concepts sometimes match and sometimes conflict with medical knowledge. By applying the caregiving system model which is a part of attachment theory (Bowlby) maternal actions can be understood as an understandable attempt to protect the child from harm. The mothers' decisions what to do when a child has a fever can be culturally influenced. This may lead either to a frequent use of services or to an underestimation of the child's state of health. The mothers' caring role and emotional state should be acknowledged; her concerns, explanatory models and strategies should be elicited and taken seriously in order to maintain a trustful relationship, provide effective counselling and thereby insuring optimal care for the children.

An evaluation of 1D loss model collections for the off-design performance prediction of automotive turbocharger compressors

NASA Astrophysics Data System (ADS)

Harley, P.; Spence, S.; Early, J.; Filsinger, D.; Dietrich, M.

2013-12-01

Single-zone modelling is used to assess different collections of impeller 1D loss models. Three collections of loss models have been identified in literature, and the background to each of these collections is discussed. Each collection is evaluated using three modern automotive turbocharger style centrifugal compressors; comparisons of performance for each of the collections are made. An empirical data set taken from standard hot gas stand tests for each turbocharger is used as a baseline for comparison. Compressor range is predicted in this study; impeller diffusion ratio is shown to be a useful method of predicting compressor surge in 1D, and choke is predicted using basic compressible flow theory. The compressor designer can use this as a guide to identify the most compatible collection of losses for turbocharger compressor design applications. The analysis indicates the most appropriate collection for the design of automotive turbocharger centrifugal compressors.

Applications of the line-of-response probability density function resolution model in PET list mode reconstruction.

PubMed

Jian, Y; Yao, R; Mulnix, T; Jin, X; Carson, R E

2015-01-07

Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners-the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7 mm to 1.9 mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [(11)C]AFM rats imaged on the HRRT and [(11)C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods.

Applications of the line-of-response probability density function resolution model in PET list mode reconstruction

PubMed Central

Jian, Y; Yao, R; Mulnix, T; Jin, X; Carson, R E

2016-01-01

Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners - the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7 mm to 1.9 mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [11C]AFM rats imaged on the HRRT and [11C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods. PMID:25490063

Development of a new type of germanium detector for dark matter searches

NASA Astrophysics Data System (ADS)

Wei, Wenzhao

Monte Carlo simulation is an important tool used to develop a better understanding of important physical processes. This thesis describes three Monte Carlo simulations used to understand germanium detector response to low energy nuclear recoils and radiogenic backgrounds for direct dark matter searches. The first simulation is the verification of Barker-Mei model, a theoretical model for calculating the ionization efficiency for germanium detector for the energy range of 1 - 100 keV. Utilizing the shape analysis, a bin-to-bin comparison between simulation and experimental data was performed for verifying the accuracy of the Barker-Mei model. A percentage difference within 4% was achieved between data and simulation, which showed the validity of the Barker-Mei model. The second simulation is the study of a new type of germanium detector for n/gamma discrimination at 77 K with plasma time difference in pulse shape. Due to the poor time resolution, conventional P-type Point Contact (PPC) and coaxial germanium detectors are not capable of discriminating nuclear recoils from electron recoils. In this thesis, a new idea of using great detector granularity and plasma time difference in pulse shape to discriminate nuclear recoils from electron recoils with planar germanium detectors in strings was discussed. The anticipated sensitivity of this new detector array is shown for detecting dark matter. The last simulation is a study of a new type of germanium-detector array serving as a PMT screening facility for ultra-low background dark matter experiments using noble liquid xenon as detector material such LUX/LZ and XENON100/XENON1T. A well-shaped germanium detector array and a PMT were simulated to study the detector response to the signal and background for a better understanding of the radiogenic gamma rays from PMTs. The detector efficiency and other detector performance were presented in this work.

Evaluation of internal noise methods for Hotelling observers

NASA Astrophysics Data System (ADS)

Zhang, Yani; Pham, Binh T.; Eckstein, Miguel P.

2005-04-01

Including internal noise in computer model observers to degrade model observer performance to human levels is a common method to allow for quantitatively comparisons of human and model performance. In this paper, we studied two different types of methods for injecting internal noise to Hotelling model observers. The first method adds internal noise to the output of the individual channels: a) Independent non-uniform channel noise, b) Independent uniform channel noise. The second method adds internal noise to the decision variable arising from the combination of channel responses: a) internal noise standard deviation proportional to decision variable's standard deviation due to the external noise, b) internal noise standard deviation proportional to decision variable's variance caused by the external noise. We tested the square window Hotelling observer (HO), channelized Hotelling observer (CHO), and Laguerre-Gauss Hotelling observer (LGHO). The studied task was detection of a filling defect of varying size/shape in one of four simulated arterial segment locations with real x-ray angiography backgrounds. Results show that the internal noise method that leads to the best prediction of human performance differs across the studied models observers. The CHO model best predicts human observer performance with the channel internal noise. The HO and LGHO best predict human observer performance with the decision variable internal noise. These results might help explain why previous studies have found different results on the ability of each Hotelling model to predict human performance. Finally, the present results might guide researchers with the choice of method to include internal noise into their Hotelling models.

SAR image classification based on CNN in real and simulation datasets

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-04-01

Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

Hawkes process model with a time-dependent background rate and its application to high-frequency financial data.

PubMed

Omi, Takahiro; Hirata, Yoshito; Aihara, Kazuyuki

2017-07-01

A Hawkes process model with a time-varying background rate is developed for analyzing the high-frequency financial data. In our model, the logarithm of the background rate is modeled by a linear model with a relatively large number of variable-width basis functions, and the parameters are estimated by a Bayesian method. Our model can capture not only the slow time variation, such as in the intraday seasonality, but also the rapid one, which follows a macroeconomic news announcement. By analyzing the tick data of the Nikkei 225 mini, we find that (i) our model is better fitted to the data than the Hawkes models with a constant background rate or a slowly varying background rate, which have been commonly used in the field of quantitative finance; (ii) the improvement in the goodness-of-fit to the data by our model is significant especially for sessions where considerable fluctuation of the background rate is present; and (iii) our model is statistically consistent with the data. The branching ratio, which quantifies the level of the endogeneity of markets, estimated by our model is 0.41, suggesting the relative importance of exogenous factors in the market dynamics. We also demonstrate that it is critically important to appropriately model the time-dependent background rate for the branching ratio estimation.

Hawkes process model with a time-dependent background rate and its application to high-frequency financial data

NASA Astrophysics Data System (ADS)

Omi, Takahiro; Hirata, Yoshito; Aihara, Kazuyuki

2017-07-01

A Hawkes process model with a time-varying background rate is developed for analyzing the high-frequency financial data. In our model, the logarithm of the background rate is modeled by a linear model with a relatively large number of variable-width basis functions, and the parameters are estimated by a Bayesian method. Our model can capture not only the slow time variation, such as in the intraday seasonality, but also the rapid one, which follows a macroeconomic news announcement. By analyzing the tick data of the Nikkei 225 mini, we find that (i) our model is better fitted to the data than the Hawkes models with a constant background rate or a slowly varying background rate, which have been commonly used in the field of quantitative finance; (ii) the improvement in the goodness-of-fit to the data by our model is significant especially for sessions where considerable fluctuation of the background rate is present; and (iii) our model is statistically consistent with the data. The branching ratio, which quantifies the level of the endogeneity of markets, estimated by our model is 0.41, suggesting the relative importance of exogenous factors in the market dynamics. We also demonstrate that it is critically important to appropriately model the time-dependent background rate for the branching ratio estimation.

Robust pedestrian detection and tracking from a moving vehicle

NASA Astrophysics Data System (ADS)

Tuong, Nguyen Xuan; Müller, Thomas; Knoll, Alois

2011-01-01

In this paper, we address the problem of multi-person detection, tracking and distance estimation in a complex scenario using multi-cameras. Specifically, we are interested in a vision system for supporting the driver in avoiding any unwanted collision with the pedestrian. We propose an approach using Histograms of Oriented Gradients (HOG) to detect pedestrians on static images and a particle filter as a robust tracking technique to follow targets from frame to frame. Because the depth map requires expensive computation, we extract depth information of targets using Direct Linear Transformation (DLT) to reconstruct 3D-coordinates of correspondent points found by running Speeded Up Robust Features (SURF) on two input images. Using the particle filter the proposed tracker can efficiently handle target occlusions in a simple background environment. However, to achieve reliable performance in complex scenarios with frequent target occlusions and complex cluttered background, results from the detection module are integrated to create feedback and recover the tracker from tracking failures due to the complexity of the environment and target appearance model variability. The proposed approach is evaluated on different data sets both in a simple background scenario and a cluttered background environment. The result shows that, by integrating detector and tracker, a reliable and stable performance is possible even if occlusion occurs frequently in highly complex environment. A vision-based collision avoidance system for an intelligent car, as a result, can be achieved.

A Buyer Behaviour Framework for the Development and Design of Software Agents in E-Commerce.

ERIC Educational Resources Information Center

Sproule, Susan; Archer, Norm

2000-01-01

Software agents are computer programs that run in the background and perform tasks autonomously as delegated by the user. This paper blends models from marketing research and findings from the field of decision support systems to build a framework for the design of software agents to support in e-commerce buying applications. (Contains 35…

Object-Oriented Software Model for Battlefield Signal Transmission and Sensing

DTIC Science & Technology

2009-12-01

21 Platform positioning and problem viability ...........................................................................23 7 Environmental ...The graphic on the title page of this report was created by Dr. Dale R. Hill (ERDC-CRREL). The authors thank Dr. George G. Koenig of ERDC-CRREL’s...Background The performance and utility of battlefield and homeland security sensors depends on many complex factors, both environmental and mission

The Application of the Theory of Planned Behaviour to Diet in Carers of People with an Intellectual Disability

ERIC Educational Resources Information Center

Jenkins, Catherine M.; McKenzie, Karen

2011-01-01

Background: The utility of the theory of planned behaviour (TPB) in predicting the intentions of care staff to encourage healthy eating behaviour in those they supported was examined. Method: A quantitative, within-participant, questionnaire based design was used with 112 carers to assess the performance of two TPB models. The first contained the…

Good Beginnings Are Not the Measure of Success: Using an Outcomes Logic Model to Track the Progress of the Irish Integrative Learning Project

ERIC Educational Resources Information Center

Ryan, C. Anthony; Higgs, Bettie; Kilcommins, Shane

2009-01-01

Background: The resources, needs and implementation activities of educational projects are often straightforward to document, especially if objectives are clear. However, developing appropriate metrics and indicators of outcomes and performance is not only challenging but is often overlooked in the excitement of project design and implementation.…

Thresholds of Knowledge Development in Complex Problem Solving: A Multiple-Case Study of Advanced Learners' Cognitive Processes

ERIC Educational Resources Information Center

Bogard, Treavor; Liu, Min; Chiang, Yueh-hui Vanessa

2013-01-01

This multiple-case study examined how advanced learners solved a complex problem, focusing on how their frequency and application of cognitive processes contributed to differences in performance outcomes, and developing a mental model of a problem. Fifteen graduate students with backgrounds related to the problem context participated in the study.…

Promoting Lifelong Physical Activity and High Level Performance: Realising an Achievable Aim for Physical Education

ERIC Educational Resources Information Center

MacNamara, Aine; Collins, Dave; Bailey, Richard; Toms, Martin; Ford, Paul; Pearce, Gemma

2011-01-01

Background: Even though all school-aged children in most countries experience some form of curricular physical education many do not maintain a lifelong involvement in sport or physical activity. From a theoretical perspective, the development models that dominate sport are limited by their staged and linear approaches to development (e.g. Cote's…

An empirical evaluation of two-stage species tree inference strategies using a multilocus dataset from North American pines

Treesearch

Michael DeGiorgio; John Syring; Andrew J. Eckert; Aaron Liston; Richard Cronn; David B. Neale; Noah A. Rosenberg

2014-01-01

Background: As it becomes increasingly possible to obtain DNA sequences of orthologous genes from diverse sets of taxa, species trees are frequently being inferred from multilocus data. However, the behavior of many methods for performing this inference has remained largely unexplored. Some methods have been proven to be consistent given certain evolutionary models,...

The Effects of Student Demographics and School Resources on California School Performance Gain: A Fixed Effects Panel Model

ERIC Educational Resources Information Center

Wu, Mei-Jiun

2013-01-01

Background/Context: Recently emerged with the implementation of the California's Public Schools Accountability Act of 1999 and the NCLB Act of 2001 is an increase in the number of education production function studies estimating the relationship between educational inputs and APIs. While the majority of past research on California school…

The Evolution of Student-Coach's Pedagogical Content Knowledge in a Combined Use of Sport Education and the Step-Game-Approach Model

ERIC Educational Resources Information Center

Araújo, Rui Manuel Flores; Hastie, Peter Andrew; de Assunção Bessa Pereira, Cristiana Helena; Mesquita, Isabel Maria Ribeiro

2017-01-01

Background: One of the essential elements within Sport Education is the inclusion of student roles and responsibilities. While previous research has examined students' performance in officiating tasks, the examination of student-coaches' pedagogical content knowledge (PCK) within peer-assisted tasks of Sport Education has been scarce. Indeed, the…

Challenges and opportunities for heavy scalar searches in the tt¯ channel at the LHC

DOE PAGES

Carena, Marcela; Liu, Zhen

2016-11-25

Heavy scalar and pseudoscalar resonance searches through themore » $$gg\\rightarrow S\\rightarrow t\\bar t$$ process are challenging due to the peculiar behavior of the large interference effects with the standard model $$t\\bar t$$ background. Such effects generate non-trivial lineshapes from additional relative phases between the signal and background amplitudes. We provide the analytic expressions for the differential cross sections to understand the interference effects in the heavy scalar signal lineshapes. We extend our study to the case of CP-violation and further consider the effect of bottom quarks in the production and decay processes. We also evaluate the contributions from additional particles to the gluon fusion production process, such as stops and vector-like quarks, that could lead to significant changes in the behavior of the signal lineshapes. Taking into account the large interference effects, we perform lineshape searches at the LHC and discuss the importance of the systematic uncertainties and smearing effects. Lastly, we present projected sensitivities for two LHC performance scenarios to probe the $$gg\\rightarrow S \\rightarrow t\\bar t$$ channel in various models.« less

Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation.

PubMed

Zana, F; Klein, J C

2001-01-01

This paper presents an algorithm based on mathematical morphology and curvature evaluation for the detection of vessel-like patterns in a noisy environment. Such patterns are very common in medical images. Vessel detection is interesting for the computation of parameters related to blood flow. Its tree-like geometry makes it a usable feature for registration between images that can be of a different nature. In order to define vessel-like patterns, segmentation is performed with respect to a precise model. We define a vessel as a bright pattern, piece-wise connected, and locally linear, mathematical morphology is very well adapted to this description, however other patterns fit such a morphological description. In order to differentiate vessels from analogous background patterns, a cross-curvature evaluation is performed. They are separated out as they have a specific Gaussian-like profile whose curvature varies smoothly along the vessel. The detection algorithm that derives directly from this modeling is based on four steps: (1) noise reduction; (2) linear pattern with Gaussian-like profile improvement; (3) cross-curvature evaluation; (4) linear filtering. We present its theoretical background and illustrate it on real images of various natures, then evaluate its robustness and its accuracy with respect to noise.

Incorporating User Input in Template-Based Segmentation

PubMed Central

Vidal, Camille; Beggs, Dale; Younes, Laurent; Jain, Sanjay K.; Jedynak, Bruno

2015-01-01

We present a simple and elegant method to incorporate user input in a template-based segmentation method for diseased organs. The user provides a partial segmentation of the organ of interest, which is used to guide the template towards its target. The user also highlights some elements of the background that should be excluded from the final segmentation. We derive by likelihood maximization a registration algorithm from a simple statistical image model in which the user labels are modeled as Bernoulli random variables. The resulting registration algorithm minimizes the sum of square differences between the binary template and the user labels, while preventing the template from shrinking, and penalizing for the inclusion of background elements into the final segmentation. We assess the performance of the proposed algorithm on synthetic images in which the amount of user annotation is controlled. We demonstrate our algorithm on the segmentation of the lungs of Mycobacterium tuberculosis infected mice from μCT images. PMID:26146532

Subject design and factors affecting achievement in mathematics for biomedical science

NASA Astrophysics Data System (ADS)

Carnie, Steven; Morphett, Anthony

2017-01-01

Reports such as Bio2010 emphasize the importance of integrating mathematical modelling skills into undergraduate biology and life science programmes, to ensure students have the skills and knowledge needed for biological research in the twenty-first century. One way to do this is by developing a dedicated mathematics subject to teach modelling and mathematical concepts in biological contexts. We describe such a subject at a research-intensive Australian university, and discuss the considerations informing its design. We also present an investigation into the effect of mathematical and biological background, prior mathematical achievement, and gender, on student achievement in the subject. The investigation shows that several factors known to predict performance in standard calculus subjects apply also to specialized discipline-specific mathematics subjects, and give some insight into the relative importance of mathematical versus biological background for a biology-focused mathematics subject.

A novel star extraction method based on modified water flow model

NASA Astrophysics Data System (ADS)

Zhang, Hao; Niu, Yanxiong; Lu, Jiazhen; Ouyang, Zibiao; Yang, Yanqiang

2017-11-01

Star extraction is the essential procedure for attitude measurement of star sensor. The great challenge for star extraction is to segment star area exactly from various noise and background. In this paper, a novel star extraction method based on Modified Water Flow Model(MWFM) is proposed. The star image is regarded as a 3D terrain. The morphology is adopted for noise elimination and Tentative Star Area(TSA) selection. Star area can be extracted through adaptive water flowing within TSAs. This method can achieve accurate star extraction with improved efficiency under complex conditions such as loud noise and uneven backgrounds. Several groups of different types of star images are processed using proposed method. Comparisons with existing methods are conducted. Experimental results show that MWFM performs excellently under different imaging conditions. The star extraction rate is better than 95%. The star centroid accuracy is better than 0.075 pixels. The time-consumption is also significantly reduced.

Infrared dim small target segmentation method based on ALI-PCNN model

NASA Astrophysics Data System (ADS)

Zhao, Shangnan; Song, Yong; Zhao, Yufei; Li, Yun; Li, Xu; Jiang, Yurong; Li, Lin

2017-10-01

Pulse Coupled Neural Network (PCNN) is improved by Adaptive Lateral Inhibition (ALI), while a method of infrared (IR) dim small target segmentation based on ALI-PCNN model is proposed in this paper. Firstly, the feeding input signal is modulated by lateral inhibition network to suppress background. Then, the linking input is modulated by ALI, and linking weight matrix is generated adaptively by calculating ALI coefficient of each pixel. Finally, the binary image is generated through the nonlinear modulation and the pulse generator in PCNN. The experimental results show that the segmentation effect as well as the values of contrast across region and uniformity across region of the proposed method are better than the OTSU method, maximum entropy method, the methods based on conventional PCNN and visual attention, and the proposed method has excellent performance in extracting IR dim small target from complex background.

The Hard X-ray Imager (HXI) for the ASTRO-H Mission

NASA Astrophysics Data System (ADS)

Sato, Goro; Kokubun, Motohide; Nakazawa, Kazuhiro; Enoto, Teruaki; Fukazawa, Yasushi; Harayama, Atsushi; Hayashi, Katsuhiro; Kataoka, Jun; Katsuta, Junichiro; Kawaharada, Madoka; Laurent, Philippe; Lebrun, François; Limousin, Olivier; Makishima, Kazuo; Mizuno, Tsunefumi; Mori, Kunishiro; Nakamori, Takeshi; Noda, Hirofumi; Odaka, Hirokazu; Ohno, Masanori; Ohta, Masayuki; Saito, Shinya; Sato, Rie; Tajima, Hiroyasu; Takahashi, Hiromitsu; Takahashi, Tadayuki; Takeda, Shinichiro; Terada, Yukikatsu; Uchiyama, Hideki; Uchiyama, Yasunobu; Watanabe, Shin; Yamaoka, Kazutaka; Yatsu, Yoichi; Yuasa, Takayuki

2014-07-01

The 6th Japanese X-ray satellite, ASTRO-H, is scheduled for launch in 2015. The hard X-ray focusing imaging system will observe astronomical objects with the sensitivity for detecting point sources with a brightness of 1/100,000 times fainter than the Crab nebula at > 10 keV. The Hard X-ray Imager (HXI) is a focal plane detector 12 m below the hard X-ray telescope (HXT) covering the energy range from 5 to 80 keV. The HXI is composed of a stacked Si/CdTe semiconductor detector module and surrounding BGO scintillators. The latter work as active shields for efficient reduction of background events caused by cosmic-ray particles, cosmic X-ray background, and in-orbit radiation activation. In this paper, we describe the detector system, and present current status of flight model development, and performance of HXI using an engineering model of HXI.

Statistical modeling of natural backgrounds in hyperspectral LWIR data

NASA Astrophysics Data System (ADS)

Truslow, Eric; Manolakis, Dimitris; Cooley, Thomas; Meola, Joseph

2016-09-01

Hyperspectral sensors operating in the long wave infrared (LWIR) have a wealth of applications including remote material identification and rare target detection. While statistical models for modeling surface reflectance in visible and near-infrared regimes have been well studied, models for the temperature and emissivity in the LWIR have not been rigorously investigated. In this paper, we investigate modeling hyperspectral LWIR data using a statistical mixture model for the emissivity and surface temperature. Statistical models for the surface parameters can be used to simulate surface radiances and at-sensor radiance which drives the variability of measured radiance and ultimately the performance of signal processing algorithms. Thus, having models that adequately capture data variation is extremely important for studying performance trades. The purpose of this paper is twofold. First, we study the validity of this model using real hyperspectral data, and compare the relative variability of hyperspectral data in the LWIR and visible and near-infrared (VNIR) regimes. Second, we illustrate how materials that are easily distinguished in the VNIR, may be difficult to separate when imaged in the LWIR.

Multicentre external validation of IOTA prediction models and RMI by operators with varied training

PubMed Central

Sayasneh, A; Wynants, L; Preisler, J; Kaijser, J; Johnson, S; Stalder, C; Husicka, R; Abdallah, Y; Raslan, F; Drought, A; Smith, A A; Ghaem-Maghami, S; Epstein, E; Van Calster, B; Timmerman, D; Bourne, T

2013-01-01

Background: Correct characterisation of ovarian tumours is critical to optimise patient care. The purpose of this study is to evaluate the diagnostic performance of the International Ovarian Tumour Analysis (IOTA) logistic regression model (LR2), ultrasound Simple Rules (SR), the Risk of Malignancy Index (RMI) and subjective assessment (SA) for preoperative characterisation of adnexal masses, when ultrasonography is performed by examiners with different background training and experience. Methods: A 2-year prospective multicentre cross-sectional study. Thirty-five level II ultrasound examiners contributed in three UK hospitals. Transvaginal ultrasonography was performed using a standardised approach. The final outcome was the surgical findings and histological diagnosis. To characterise the adnexal masses, the six-variable prediction model (LR2) with a cutoff of 0.1, the RMI with cutoff of 200, ten SR (five rules for malignancy and five rules for benignity) and SA were applied. The area under the curves (AUCs) for performance of LR2 and RMI were calculated. Diagnostic performance measures for all models assessed were sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR−), and the diagnostic odds ratio (DOR). Results: Nine-hundred and sixty-two women with adnexal masses underwent transvaginal ultrasonography, whereas 255 had surgery. Prevalence of malignancy was 29% (49 primary invasive epithelial ovarian cancers, 18 borderline ovarian tumours, and 7 metastatic tumours). The AUCs for LR2 and RMI for all masses were 0.94 (95% confidence interval (CI): 0.89–0.97) and 0.90 (95% CI: 0.83–0.94), respectively. In premenopausal women, LR2−RMI difference was 0.09 (95% CI: 0.03–0.15) compared with −0.02 (95% CI: −0.08 to 0.04) in postmenopausal women. For all masses, the DORs for LR2, RMI, SR+SA (using SA when SR inapplicable), SR+MA (assuming malignancy when SR inapplicable), and SA were 62 (95% CI: 27–142), 43 (95% CI: 19–97), 109 (95% CI: 44–274), 66 (95% CI: 27–158), and 70 (95% CI: 30–163), respectively. Conclusion: Overall, the test performance of IOTA prediction models and rules as well as the RMI was maintained in examiners with varying levels of training and experience. PMID:23674083

Impact of advanced technology microwave sounder data in the NCMRWF 4D-VAR data assimilation system

NASA Astrophysics Data System (ADS)

Rani, S. Indira; Srinivas, D.; Mallick, Swapan; George, John P.

2016-05-01

This study demonstrates the added benefits of assimilating the Advanced Technology Microwave Sounder (ATMS) radiances from the Suomi-NPP satellite in the NCMRWF Unified Model (NCUM). ATMS is a cross-track scanning microwave radiometer inherited the legacy of two very successful instrument namely, Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS). ATMS has 22 channels: 11 temperature sounding channels around 50-60 GHz oxygen band and 6 moisture sounding channels around the 183GHz water vapour band in addition to 5 channels sensitive to the surface in clear conditions, or to water vapour, rain, and cloud when conditions are not clear (at 23, 31, 50, 51 and 89 GHz). Before operational assimilation of any new observation by NWP centres it is standard practice to assess data quality with respect to NWP model background (short-forecast) fields. Quality of all channels is estimated against the model background and the biases are computed and compared against that from the similar observations. The impact of the ATMS data on global analyses and forecasts is tested by adding the ATMS data in the NCUM Observation Processing system (OPS) and 4D-Var variational assimilation (VAR) system. This paper also discusses the pre-operational numerical experiments conducted to assess the impact of ATMS radiances in the NCUM assimilation system. It is noted that the performance of ATMS is stable and it contributes to the performance of the model, complimenting observations from other instruments.

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

Soffientini, Chiara Dolores, E-mail: chiaradolores.soffientini@polimi.it; Baselli, Giuseppe; De Bernardi, Elisabetta

Purpose: Quantitative {sup 18}F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level. Methods: An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previousmore » analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD). Results: The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was demonstrated. The inclusion of the spatial prior improved segmentation accuracy only for lesions surrounded by heterogeneous background: in the relevant simulation subset, the median VE significantly decreased from 13% to 7%. Results on clinical data were found in accordance with simulations, with absolute VE <7%, Dice >0.85, CE <0.30, and HD <0.81. Conclusions: The sole introduction of constraints based on background modeling outperformed standard GMM and the other tested algorithms. Insertion of a spatial prior improved the accuracy for realistic cases of objects in heterogeneous backgrounds. Moreover, robustness against initialization supports the applicability in a clinical setting. In conclusion, application-driven constraints can generally improve the capabilities of GMM and statistical clustering algorithms.« less

Effects of mild cognitive impairment on emotional scene memory.

PubMed

Waring, J D; Dimsdale-Zucker, H R; Flannery, S; Budson, A E; Kensinger, E A

2017-02-01

Young and older adults experience benefits in attention and memory for emotional compared to neutral information, but this memory benefit is greatly diminished in Alzheimer's disease (AD). Little is known about whether this impairment arises early or late in the time course between healthy aging and AD. This study compared memory for positive, negative, and neutral items with neutral backgrounds between patients with mild cognitive impairment (MCI) and healthy older adults. We also used a divided attention condition in older adults as a possible model for the deficits observed in MCI patients. Results showed a similar pattern of selective memory for emotional items while forgetting their backgrounds in older adults and MCI patients, but MCI patients had poorer memory overall. Dividing attention during encoding disproportionately reduced memory for backgrounds (versus items) relative to a full attention condition. Participants performing in the lower half on the divided attention task qualitatively and quantitatively mirrored the results in MCI patients. Exploratory analyses comparing lower- and higher-performing MCI patients showed that only higher-performing MCI patients had the characteristic scene memory pattern observed in healthy older adults. Together, these results suggest that the effects of emotion on memory are relatively well preserved for patients with MCI, although emotional memory patterns may start to be altered once memory deficits become more pronounced. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real-time people counting system using a single video camera

NASA Astrophysics Data System (ADS)

Lefloch, Damien; Cheikh, Faouzi A.; Hardeberg, Jon Y.; Gouton, Pierre; Picot-Clemente, Romain

2008-02-01

There is growing interest in video-based solutions for people monitoring and counting in business and security applications. Compared to classic sensor-based solutions the video-based ones allow for more versatile functionalities, improved performance with lower costs. In this paper, we propose a real-time system for people counting based on single low-end non-calibrated video camera. The two main challenges addressed in this paper are: robust estimation of the scene background and the number of real persons in merge-split scenarios. The latter is likely to occur whenever multiple persons move closely, e.g. in shopping centers. Several persons may be considered to be a single person by automatic segmentation algorithms, due to occlusions or shadows, leading to under-counting. Therefore, to account for noises, illumination and static objects changes, a background substraction is performed using an adaptive background model (updated over time based on motion information) and automatic thresholding. Furthermore, post-processing of the segmentation results is performed, in the HSV color space, to remove shadows. Moving objects are tracked using an adaptive Kalman filter, allowing a robust estimation of the objects future positions even under heavy occlusion. The system is implemented in Matlab, and gives encouraging results even at high frame rates. Experimental results obtained based on the PETS2006 datasets are presented at the end of the paper.

Key performance outcomes of patient safety curricula: root cause analysis, failure mode and effects analysis, and structured communications skills.

PubMed

Fassett, William E

2011-10-10

As colleges and schools of pharmacy develop core courses related to patient safety, course-level outcomes will need to include both knowledge and performance measures. Three key performance outcomes for patient safety coursework, measured at the course level, are the ability to perform root cause analyses and healthcare failure mode effects analyses, and the ability to generate effective safety communications using structured formats such as the Situation-Background-Assessment-Recommendation (SBAR) situational briefing model. Each of these skills is widely used in patient safety work and competence in their use is essential for a pharmacist's ability to contribute as a member of a patient safety team.

A unified framework for gesture recognition and spatiotemporal gesture segmentation.

PubMed

Alon, Jonathan; Athitsos, Vassilis; Yuan, Quan; Sclaroff, Stan

2009-09-01

Within the context of hand gesture recognition, spatiotemporal gesture segmentation is the task of determining, in a video sequence, where the gesturing hand is located and when the gesture starts and ends. Existing gesture recognition methods typically assume either known spatial segmentation or known temporal segmentation, or both. This paper introduces a unified framework for simultaneously performing spatial segmentation, temporal segmentation, and recognition. In the proposed framework, information flows both bottom-up and top-down. A gesture can be recognized even when the hand location is highly ambiguous and when information about when the gesture begins and ends is unavailable. Thus, the method can be applied to continuous image streams where gestures are performed in front of moving, cluttered backgrounds. The proposed method consists of three novel contributions: a spatiotemporal matching algorithm that can accommodate multiple candidate hand detections in every frame, a classifier-based pruning framework that enables accurate and early rejection of poor matches to gesture models, and a subgesture reasoning algorithm that learns which gesture models can falsely match parts of other longer gestures. The performance of the approach is evaluated on two challenging applications: recognition of hand-signed digits gestured by users wearing short-sleeved shirts, in front of a cluttered background, and retrieval of occurrences of signs of interest in a video database containing continuous, unsegmented signing in American Sign Language (ASL).

Network Analysis of Associations between Serum Interferon Alpha Activity, Autoantibodies, and Clinical Features in Systemic Lupus Erythematosus

PubMed Central

Weckerle, Corinna E.; Franek, Beverly S.; Kelly, Jennifer A.; Kumabe, Marissa; Mikolaitis, Rachel A.; Green, Stephanie L.; Utset, Tammy O.; Jolly, Meenakshi; James, Judith A.; Harley, John B.; Niewold, Timothy B.

2010-01-01

Background Interferon-alpha (IFN-α) is a primary pathogenic factor in systemic lupus erythematosus (SLE), and high IFN-α levels may be associated with particular clinical manifestations. The prevalence of individual clinical and serologic features differs significantly by ancestry. We used multivariate and network analyses to detect associations between clinical and serologic disease manifestations and serum IFN-α activity in a large diverse SLE cohort. Methods 1089 SLE patients were studied (387 African-American, 186 Hispanic-American, and 516 European-American). Presence or absence of ACR clinical criteria for SLE, autoantibodies, and serum IFN-α activity data were analyzed in univariate and multivariate models. Iterative multivariate logistic regression was performed in each background separately to establish the network of associations between variables that were independently significant following Bonferroni correction. Results In all ancestral backgrounds, high IFN-α activity was associated with anti-Ro and anti-dsDNA antibodies (p-values 4.6×10−18 and 2.9 × 10−16 respectively). Younger age, non-European ancestry, and anti-RNP were also independently associated with increased serum IFN-α activity (p≤6.7×10−4). We found 14 unique associations between variables in network analysis, and only 7 of these associations were shared by more than one ancestral background. Associations between clinical criteria were different in different ancestral backgrounds, while autoantibody-IFN-α relationships were similar across backgrounds. IFN-α activity and autoantibodies were not associated with ACR clinical features in multivariate models. Conclusions Serum IFN-α activity was strongly and consistently associated with autoantibodies, and not independently associated with clinical features in SLE. IFN-α may be more relevant to humoral tolerance and initial pathogenesis than later clinical disease manifestations. PMID:21162028

Discriminative correlation filter tracking with occlusion detection

NASA Astrophysics Data System (ADS)

Zhang, Shuo; Chen, Zhong; Yu, XiPeng; Zhang, Ting; He, Jing

2018-03-01

Aiming at the problem that the correlation filter-based tracking algorithm can not track the target of severe occlusion, a target re-detection mechanism is proposed. First of all, based on the ECO, we propose the multi-peak detection model and the response value to distinguish the occlusion and deformation in the target tracking, which improve the success rate of tracking. And then we add the confidence model to update the mechanism to effectively prevent the model offset problem which due to similar targets or background during the tracking process. Finally, the redetection mechanism of the target is added, and the relocation is performed after the target is lost, which increases the accuracy of the target positioning. The experimental results demonstrate that the proposed tracker performs favorably against state-of-the-art methods in terms of robustness and accuracy.

Modeling the effect of channel number and interaction on consonant recognition in a cochlear implant peak-picking strategy.

PubMed

Verschuur, Carl

2009-03-01

Difficulties in speech recognition experienced by cochlear implant users may be attributed both to information loss caused by signal processing and to information loss associated with the interface between the electrode array and auditory nervous system, including cross-channel interaction. The objective of the work reported here was to attempt to partial out the relative contribution of these different factors to consonant recognition. This was achieved by comparing patterns of consonant feature recognition as a function of channel number and presence/absence of background noise in users of the Nucleus 24 device with normal hearing subjects listening to acoustic models that mimicked processing of that device. Additionally, in the acoustic model experiment, a simulation of cross-channel spread of excitation, or "channel interaction," was varied. Results showed that acoustic model experiments were highly correlated with patterns of performance in better-performing cochlear implant users. Deficits to consonant recognition in this subgroup could be attributed to cochlear implant processing, whereas channel interaction played a much smaller role in determining performance errors. The study also showed that large changes to channel number in the Advanced Combination Encoder signal processing strategy led to no substantial changes in performance.

Predicting Non Return to Work after Orthopaedic Trauma: The Wallis Occupational Rehabilitation RisK (WORRK) Model

PubMed Central

Luthi, François; Deriaz, Olivier; Vuistiner, Philippe; Burrus, Cyrille; Hilfiker, Roger

2014-01-01

Background Workers with persistent disabilities after orthopaedic trauma may need occupational rehabilitation. Despite various risk profiles for non-return-to-work (non-RTW), there is no available predictive model. Moreover, injured workers may have various origins (immigrant workers), which may either affect their return to work or their eligibility for research purposes. The aim of this study was to develop and validate a predictive model that estimates the likelihood of non-RTW after occupational rehabilitation using predictors which do not rely on the worker’s background. Methods Prospective cohort study (3177 participants, native (51%) and immigrant workers (49%)) with two samples: a) Development sample with patients from 2004 to 2007 with Full and Reduced Models, b) External validation of the Reduced Model with patients from 2008 to March 2010. We collected patients’ data and biopsychosocial complexity with an observer rated interview (INTERMED). Non-RTW was assessed two years after discharge from the rehabilitation. Discrimination was assessed by the area under the receiver operating curve (AUC) and calibration was evaluated with a calibration plot. The model was reduced with random forests. Results At 2 years, the non-RTW status was known for 2462 patients (77.5% of the total sample). The prevalence of non-RTW was 50%. The full model (36 items) and the reduced model (19 items) had acceptable discrimination performance (AUC 0.75, 95% CI 0.72 to 0.78 and 0.74, 95% CI 0.71 to 0.76, respectively) and good calibration. For the validation model, the discrimination performance was acceptable (AUC 0.73; 95% CI 0.70 to 0.77) and calibration was also adequate. Conclusions Non-RTW may be predicted with a simple model constructed with variables independent of the patient’s education and language fluency. This model is useful for all kinds of trauma in order to adjust for case mix and it is applicable to vulnerable populations like immigrant workers. PMID:24718689

A Study of Nuclear Recoil Backgrounds in Dark Matter Detectors

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

Westerdale, Shawn S.

2016-01-01

Despite the great success of the Standard Model of particle physics, a preponderance of astrophysical evidence suggests that it cannot explain most of the matter in the universe. This so-called dark matter has eluded direct detection, though many theoretical extensions to the Standard Model predict the existence of particles with a mass on themore » $1-1000$ GeV scale that interact only via the weak nuclear force. Particles in this class are referred to as Weakly Interacting Massive Particles (WIMPs), and their high masses and low scattering cross sections make them viable dark matter candidates. The rarity of WIMP-nucleus interactions makes them challenging to detect: any background can mask the signal they produce. Background rejection is therefore a major problem in dark matter detection. Many experiments greatly reduce their backgrounds by employing techniques to reject electron recoils. However, nuclear recoil backgrounds, which produce signals similar to what we expect from WIMPs, remain problematic. There are two primary sources of such backgrounds: surface backgrounds and neutron recoils. Surface backgrounds result from radioactivity on the inner surfaces of the detector sending recoiling nuclei into the detector. These backgrounds can be removed with fiducial cuts, at some cost to the experiment's exposure. In this dissertation we briefly discuss a novel technique for rejecting these events based on signals they make in the wavelength shifter coating on the inner surfaces of some detectors. Neutron recoils result from neutrons scattering from nuclei in the detector. These backgrounds may produce a signal identical to what we expect from WIMPs and are extensively discussed here. We additionally present a new tool for calculating ($$\\alpha$$, n)yields in various materials. We introduce the concept of a neutron veto system designed to shield against, measure, and provide an anti-coincidence veto signal for background neutrons. We discuss the research and development that informed the design of the DarkSide-50 boron-loaded liquid scintillator neutron veto. We describe the specific implementation of this veto system in DarkSide-50, including a description of its performance, and show that it can reject neutrons with a high enough e_ciency to allow DarkSide-50 to run background-free for three years.« less

An Energy-Efficient Multi-Tier Architecture for Fall Detection Using Smartphones.

PubMed

Guvensan, M Amac; Kansiz, A Oguz; Camgoz, N Cihan; Turkmen, H Irem; Yavuz, A Gokhan; Karsligil, M Elif

2017-06-23

Automatic detection of fall events is vital to providing fast medical assistance to the causality, particularly when the injury causes loss of consciousness. Optimization of the energy consumption of mobile applications, especially those which run 24/7 in the background, is essential for longer use of smartphones. In order to improve energy-efficiency without compromising on the fall detection performance, we propose a novel 3-tier architecture that combines simple thresholding methods with machine learning algorithms. The proposed method is implemented on a mobile application, called uSurvive, for Android smartphones. It runs as a background service and monitors the activities of a person in daily life and automatically sends a notification to the appropriate authorities and/or user defined contacts when it detects a fall. The performance of the proposed method was evaluated in terms of fall detection performance and energy consumption. Real life performance tests conducted on two different models of smartphone demonstrate that our 3-tier architecture with feature reduction could save up to 62% of energy compared to machine learning only solutions. In addition to this energy saving, the hybrid method has a 93% of accuracy, which is superior to thresholding methods and better than machine learning only solutions.

Received optical power calculations for optical communications link performance analysis

NASA Technical Reports Server (NTRS)

Marshall, W. K.; Burk, B. D.

1986-01-01

The factors affecting optical communication link performance differ substantially from those at microwave frequencies, due to the drastically differing technologies, modulation formats, and effects of quantum noise in optical communications. In addition detailed design control table calculations for optical systems are less well developed than corresponding microwave system techniques, reflecting the relatively less mature state of development of optical communications. Described below are detailed calculations of received optical signal and background power in optical communication systems, with emphasis on analytic models for accurately predicting transmitter and receiver system losses.

Implementation of Mamdani Fuzzy Method in Employee Promotion System

NASA Astrophysics Data System (ADS)

Zulfikar, W. B.; Jumadi; Prasetyo, P. K.; Ramdhani, M. A.

2018-01-01

Nowadays, employees are big assets to an institution. Every employee has a different educational background, degree, work skill, attitude and ethic that affect the performance. An institution including government institution implements a promotion system in order to improve the performance of the employees. Pangandaran Tourism, Industry, Trade, and SME Department is one of government agency that implements a promotion system to discover employees who deserve to get promotion. However, there are some practical deficiencies in the promotion system, one of which is the subjectivity issue. This work proposed a classification model that could minimize the subjectivity issue in employee promotion system. This paper reported a classification employee based on their eligibility for promotion. The degree of membership was decided using Mamdani Fuzzy based on determinant factors of the performance of employees. In the evaluation phase, this model had an accuracy of 91.4%. It goes to show that this model may minimize the subjectivity issue in the promotion system, especially at Pangandaran Tourism, Industry, Trade, and SME Department.

Role of highway traffic on spatial and temporal distributions of air pollutants in a Swiss Alpine valley.

PubMed

Ducret-Stich, Regina E; Tsai, Ming-Yi; Ragettli, Martina S; Ineichen, Alex; Kuenzli, Nino; Phuleria, Harish C

2013-07-01

Traffic-related air pollutants show high spatial variability near roads, posing a challenge to adequately assess exposures. Recent modeling approaches (e.g. dispersion models, land-use regression (LUR) models) have addressed this but mostly in urban areas where traffic is abundant. In contrast, our study area was located in a rural Swiss Alpine valley crossed by the main North-south transit highway of Switzerland. We conducted an extensive measurement campaign collecting continuous nitrogen dioxide (NO₂), particulate number concentrations (PN), daily respirable particulate matter (PM10), elemental carbon (EC) and organic carbon (OC) at one background, one highway and seven mobile stations from November 2007 to June 2009. Using these measurements, we built a hybrid model to predict daily outdoor NO₂ concentrations at residences of children participating in an asthma panel study. With the exception of OC, daily variations of the pollutants followed the temporal trends of heavy-duty traffic counts on the highway. In contrast, variations of weekly/seasonal means were strongly determined by meteorological conditions, e.g., winter inversion episodes. For pollutants related to primary exhaust emissions (i.e. NO₂, EC and PN) local spatial variation strongly depended on proximity to the highway. Pollutant concentrations decayed to background levels within 150 to 200 m from the highway. Two separate daily NO₂ prediction models were built using LUR approaches with (a) short-term traffic and weather data (model 1) and (b) subsequent addition of daily background NO₂ to previous model (model 2). Models 1 and 2 explained 70% and 91% of the variability in outdoor NO₂ concentrations, respectively. The biweekly averaged predictions from the final model 2 agreed very well with the independent biweekly integrated passive measurements taken at thirteen homes and nine community sites (validation R(2)=0.74). The excellent spatio-temporal performance of our model provides a very promising basis for the health effect assessment of the panel study. Copyright © 2013 Elsevier B.V. All rights reserved.

The MAJORANA DEMONSTRATOR for 0νββ: Current Status and Future Plans

NASA Astrophysics Data System (ADS)

Green, M. P.; Abgrall, N.; Aguayo, E.; Avignone, F. T.; Barabash, A. S.; Bertrand, F. E.; Boswell, M.; Brudanin, V.; Busch, M.; Byram, D.; Caldwell, A. S.; Chan, Y.-D.; Christofferson, C. D.; Combs, D. C.; Cuesta, C.; Detwiler, J. A.; Doe, P. J.; Efremenko, Yu.; Egorov, V.; Ejiri, H.; Elliott, S. R.; Fast, J. E.; Finnerty, P.; Fraenkle, F. M.; Galindo-Uribarri, A.; Giovanetti, G. K.; Goett, J.; Gruszko, J.; Guiseppe, V. E.; Gusev, K.; Hallin, A. L.; Hazama, R.; Hegai, A.; Henning, R.; Hoppe, E. W.; Howard, S.; Howe, M. A.; Keeter, K. J.; Kidd, M. F.; Kochetov, O.; Konovalov, S. I.; Kouzes, R. T.; LaFerriere, B. D.; Leon, J.; Leviner, L. E.; Loach, J. C.; MacMullin, J.; MacMullin, S.; Martin, R. D.; Meijer, S.; Mertens, S.; Nomachi, M.; Orrell, J. L.; O'Shaughnessy, C.; Overman, N. R.; Phillips, D. G.; Poon, A. W. P.; Pushkin, K.; Radford, D. C.; Rager, J.; Rielage, K.; Robertson, R. G. H.; Romero-Romero, E.; Ronquest, M. C.; Schubert, A. G.; Shanks, B.; Shima, T.; Shirchenko, M.; Snavely, K. J.; Snyder, N.; Suriano, A. M.; Thompson, J.; Timkin, V.; Tornow, W.; Trimble, J. E.; Varner, R. L.; Vasilyev, S.; Vetter, K.; Vorren, K.; White, B. R.; Wilkerson, J. F.; Wiseman, C.; Xu, W.; Yakushev, E.; Young, A. R.; Yu, C.-H.; Yumatov, V.

The MAJORANA DEMONSTRATOR will search for neutrinoless-double-beta decay (0νββ) in 76Ge, while establishing the feasibility of a future tonne-scale germanium-based 0νββ experiment, and performing searches for new physics beyond the Standard Model. The experiment, currently under construction at the Sanford Underground Research Facility in Lead, SD, will consist of a pair of modular high-purity germanium detector arrays housed inside of a compact copper, lead, and polyethylene shield. Through a combination of strict materials qualifications and assay, low-background design, and powerful background rejection techniques, the Demonstrator aims to achieve a background rate in the 0νββ region of interest (ROI) of no more than 3 counts in the 0νββ-decay ROI per tonne of target isotope per year (cnts/(ROI-t-y)). The current status of the Demonstrator is discussed, as are plans for its completion.

The Majorana Demonstrator for 0νββ: Current Status and Future Plans

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

Green, Matthew P.; Avignone, F. T.; Bertrand, Jr, Fred E

2015-01-01

The Majorana Demonstrator will search for neutrinoless-double-beta decay (0νββ) in 76Ge, while establishing the feasibility of a future tonne-scale germanium-based 0νββ experiment, and performing searches for new physics beyond the Standard Model. The experiment, currently under construction at the Sanford Underground Research Facility in Lead, SD, will consist of a pair of modular high-purity germanium detector arrays housed inside of a compact copper, lead, and polyethylene shield. Through a combination of strict materials qualifications and assay, low-background design, and powerful background rejection techniques, the Demonstrator aims to achieve a background rate in the 0νββ region of interest (ROI) of nomore » more than 3cnts/(ROI-t-y). The current status of the Demonstrator is discussed, as are plans for its completion.« less

The Threshold Bias Model: A Mathematical Model for the Nomothetic Approach of Suicide

PubMed Central

Folly, Walter Sydney Dutra

2011-01-01

Background Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. Methodology/Principal Findings A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. Conclusions/Significance The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health. PMID:21909431

How can animal models inform on the transition to chronic symptoms in whiplash?

PubMed Central

Winkelstein, Beth A.

2011-01-01

Study Design A non-systematic review of the literature. Objective The objective was to present general schema for mechanisms of whiplash pain and review the role of animal models in understanding the development of chronic pain from whiplash injury. Summary of Background Data Extensive biomechanical and clinical studies of whiplash have been performed to understand the injury mechanisms and symptoms of whiplash injury. However, only recently have animal models of this painful disorder been developed based on other pain models in the literature. Methods A non-systematic review was performed and findings were integrated to formulate a generalized picture of mechanisms by chronic whiplash pain develops from mechanical tissue injuries. Results The development of chronic pain from tissue injuries in the neck due to whiplash involves complex interactions between the injured tissue and spinal neuroimmune circuits. A variety of animal models are beginning to define these mechanisms. Conclusion Continued work is needed in developing appropriate animal models to investigate chronic pain from whiplash injuries and care must be taken to determine whether such models aim to model the injury event or the pain symptom. PMID:22020616

Theoretical performance of mid wavelength HgCdTe(1 0 0) heterostructure infrared detectors

NASA Astrophysics Data System (ADS)

Kopytko, M.

2017-11-01

The paper presents a theoretical study of the p+BpnN+ design based on HgCdTe(1 0 0) layers, which significantly improves the performance of detectors optimized for the mid-wave infrared spectral range. p+BpnN+ design combines the concept of a high impedance photoconductor with double layer hetero-junction device. Zero valence band offset approximation throughout the p+Bpn heterostructure allows flow of only minority holes generated in the absorber, what in a combination with n-N+ exclusion junction provides the Auger suppression. Modeling shows that by applying a low doping active layer, it is possible to achieve an order of magnitude lower dark current densities than those determined by ;Rule 07;. A key to its success is a reduction of Shockley-Read-Hall centers associated with native defects, residual impurities and misfit dislocations. Reduction of metal site vacancies below 1012 cm-3 and dislocation density to 105 cm-2 allow to achieve a background limited performance at 250 K. If the background radiation can be reduced, operation with a three- or four-stage thermo-electric-cooler may be possible.

Modeling and simulation of a beam emission spectroscopy diagnostic for the ITER prototype neutral beam injector.

PubMed

Barbisan, M; Zaniol, B; Pasqualotto, R

2014-11-01

A test facility for the development of the neutral beam injection system for ITER is under construction at Consorzio RFX. It will host two experiments: SPIDER, a 100 keV H(-)/D(-) ion RF source, and MITICA, a prototype of the full performance ITER injector (1 MV, 17 MW beam). A set of diagnostics will monitor the operation and allow to optimize the performance of the two prototypes. In particular, beam emission spectroscopy will measure the uniformity and the divergence of the fast particles beam exiting the ion source and travelling through the beam line components. This type of measurement is based on the collection of the Hα/Dα emission resulting from the interaction of the energetic particles with the background gas. A numerical model has been developed to simulate the spectrum of the collected emissions in order to design this diagnostic and to study its performance. The paper describes the model at the base of the simulations and presents the modeled Hα spectra in the case of MITICA experiment.

Source detection in astronomical images by Bayesian model comparison

NASA Astrophysics Data System (ADS)

Frean, Marcus; Friedlander, Anna; Johnston-Hollitt, Melanie; Hollitt, Christopher

2014-12-01

The next generation of radio telescopes will generate exabytes of data on hundreds of millions of objects, making automated methods for the detection of astronomical objects ("sources") essential. Of particular importance are faint, diffuse objects embedded in noise. There is a pressing need for source finding software that identifies these sources, involves little manual tuning, yet is tractable to calculate. We first give a novel image discretisation method that incorporates uncertainty about how an image should be discretised. We then propose a hierarchical prior for astronomical images, which leads to a Bayes factor indicating how well a given region conforms to a model of source that is exceptionally unconstrained, compared to a model of background. This enables the efficient localisation of regions that are "suspiciously different" from the background distribution, so our method looks not for brightness but for anomalous distributions of intensity, which is much more general. The model of background can be iteratively improved by removing the influence on it of sources as they are discovered. The approach is evaluated by identifying sources in real and simulated data, and performs well on these measures: the Bayes factor is maximized at most real objects, while returning only a moderate number of false positives. In comparison to a catalogue constructed by widely-used source detection software with manual post-processing by an astronomer, our method found a number of dim sources that were missing from the "ground truth" catalogue.

Detection and correction of laser induced breakdown spectroscopy spectral background based on spline interpolation method

NASA Astrophysics Data System (ADS)

Tan, Bing; Huang, Min; Zhu, Qibing; Guo, Ya; Qin, Jianwei

2017-12-01

Laser-induced breakdown spectroscopy (LIBS) is an analytical technique that has gained increasing attention because of many applications. The production of continuous background in LIBS is inevitable because of factors associated with laser energy, gate width, time delay, and experimental environment. The continuous background significantly influences the analysis of the spectrum. Researchers have proposed several background correction methods, such as polynomial fitting, Lorenz fitting and model-free methods. However, less of them apply these methods in the field of LIBS Technology, particularly in qualitative and quantitative analyses. This study proposes a method based on spline interpolation for detecting and estimating the continuous background spectrum according to its smooth property characteristic. Experiment on the background correction simulation indicated that, the spline interpolation method acquired the largest signal-to-background ratio (SBR) over polynomial fitting, Lorenz fitting and model-free method after background correction. These background correction methods all acquire larger SBR values than that acquired before background correction (The SBR value before background correction is 10.0992, whereas the SBR values after background correction by spline interpolation, polynomial fitting, Lorentz fitting, and model-free methods are 26.9576, 24.6828, 18.9770, and 25.6273 respectively). After adding random noise with different kinds of signal-to-noise ratio to the spectrum, spline interpolation method acquires large SBR value, whereas polynomial fitting and model-free method obtain low SBR values. All of the background correction methods exhibit improved quantitative results of Cu than those acquired before background correction (The linear correlation coefficient value before background correction is 0.9776. Moreover, the linear correlation coefficient values after background correction using spline interpolation, polynomial fitting, Lorentz fitting, and model-free methods are 0.9998, 0.9915, 0.9895, and 0.9940 respectively). The proposed spline interpolation method exhibits better linear correlation and smaller error in the results of the quantitative analysis of Cu compared with polynomial fitting, Lorentz fitting and model-free methods, The simulation and quantitative experimental results show that the spline interpolation method can effectively detect and correct the continuous background.

The Teacher, the Physician and the Person: Exploring Causal Connections between Teaching Performance and Role Model Types Using Directed Acyclic Graphs

PubMed Central

Boerebach, Benjamin C. M.; Lombarts, Kiki M. J. M. H.; Scherpbier, Albert J. J.; Arah, Onyebuchi A.

2013-01-01

Background In fledgling areas of research, evidence supporting causal assumptions is often scarce due to the small number of empirical studies conducted. In many studies it remains unclear what impact explicit and implicit causal assumptions have on the research findings; only the primary assumptions of the researchers are often presented. This is particularly true for research on the effect of faculty’s teaching performance on their role modeling. Therefore, there is a need for robust frameworks and methods for transparent formal presentation of the underlying causal assumptions used in assessing the causal effects of teaching performance on role modeling. This study explores the effects of different (plausible) causal assumptions on research outcomes. Methods This study revisits a previously published study about the influence of faculty’s teaching performance on their role modeling (as teacher-supervisor, physician and person). We drew eight directed acyclic graphs (DAGs) to visually represent different plausible causal relationships between the variables under study. These DAGs were subsequently translated into corresponding statistical models, and regression analyses were performed to estimate the associations between teaching performance and role modeling. Results The different causal models were compatible with major differences in the magnitude of the relationship between faculty’s teaching performance and their role modeling. Odds ratios for the associations between teaching performance and the three role model types ranged from 31.1 to 73.6 for the teacher-supervisor role, from 3.7 to 15.5 for the physician role, and from 2.8 to 13.8 for the person role. Conclusions Different sets of assumptions about causal relationships in role modeling research can be visually depicted using DAGs, which are then used to guide both statistical analysis and interpretation of results. Since study conclusions can be sensitive to different causal assumptions, results should be interpreted in the light of causal assumptions made in each study. PMID:23936020

A Dark Matter Search with MALBEK

NASA Astrophysics Data System (ADS)

Giovanetti, G. K.; Abgrall, N.; Aguayo, E.; Avignone, F. T.; Barabash, A. S.; Bertrand, F. E.; Boswell, M.; Brudanin, V.; Busch, M.; Byram, D.; Caldwell, A. S.; Chan, Y.-D.; Christofferson, C. D.; Combs, D. C.; Cuesta, C.; Detwiler, J. A.; Doe, P. J.; Efremenko, Yu.; Egorov, V.; Ejiri, H.; Elliott, S. R.; Fast, J. E.; Finnerty, P.; Fraenkle, F. M.; Galindo-Uribarri, A.; Goett, J.; Green, M. P.; Gruszko, J.; Guiseppe, V. E.; Gusev, K.; Hallin, A. L.; Hazama, R.; Hegai, A.; Henning, R.; Hoppe, E. W.; Howard, S.; Howe, M. A.; Keeter, K. J.; Kidd, M. F.; Kochetov, O.; Konovalov, S. I.; Kouzes, R. T.; LaFerriere, B. D.; Leon, J.; Leviner, L. E.; Loach, J. C.; MacMullin, J.; MacMullin, S.; Martin, R. D.; Meijer, S.; Mertens, S.; Nomachi, M.; Orrell, J. L.; O'Shaughnessy, C.; Overman, N. R.; Phillips, D. G.; Poon, A. W. P.; Pushkin, K.; Radford, D. C.; Rager, J.; Rielage, K.; Robertson, R. G. H.; Romero-Romero, E.; Ronquest, M. C.; Schubert, A. G.; Shanks, B.; Shima, T.; Shirchenko, M.; Snavely, K. J.; Snyder, N.; Suriano, A. M.; Thompson, J.; Timkin, V.; Tornow, W.; Trimble, J. E.; Varner, R. L.; Vasilyev, S.; Vetter, K.; Vorren, K.; White, B. R.; Wilkerson, J. F.; Wiseman, C.; Xu, W.; Yakushev, E.; Young, A. R.; Yu, C.-H.; Yumatov, V.

The Majorana Demonstrator is an array of natural and enriched high purity germanium detectors that will search for the neutrinoless double-beta decay of 76Ge and perform a search for weakly interacting massive particles (WIMPs) with masses below 10 GeV. As part of the Majorana research and development efforts, we have deployed a modified, low-background broad energy germanium detector at the Kimballton Underground Research Facility. With its sub-keV energy threshold, this detector is sensitive to potential non-Standard Model physics, including interactions with WIMPs. We discuss the backgrounds present in the WIMP region of interest and explore the impact of slow surface event contamination when searching for a WIMP signal.

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

Not Available

This report was prepared at the request of the Lawrence Livermore Laboratory (LLL) to provide background information for analyzing soil-structure interaction by the frequency-independent impedance function approach. LLL is conducting such analyses as part of its seismic review of selected operating plants under the Systematic Evaluation Program for the US Nuclear Regulatory Commission. The analytical background and basic assumptionsof the impedance function theory are briefly reviewed, and the role of radiation damping in soil-structure interaction analysis is discussed. The validity of modeling soil-structure interaction by using frequency-independent functions is evaluated based on data from several field tests. Finally, the recommendedmore » procedures for performing soil-structure interaction analyses are discussed with emphasis on the modal superposition method.« less

A dark matter search with MALBEK

DOE PAGES

Giovanetti, G. K.; Abgrall, N.; Aguayo, E.; ...

2015-01-01

The Majorana Demonstrator is an array of natural and enriched high purity germanium detectors that will search for the neutrinoless double-beta decay of ⁷⁶Ge and perform a search for weakly interacting massive particles (WIMPs) with masses below 10 GeV. As part of the Majorana research and development efforts, we have deployed a modified, low-background broad energy germanium detector at the Kimballton Underground Research Facility. With its sub-keV energy threshold, this detector is sensitive to potential non-Standard Model physics, including interactions with WIMPs. We discuss the backgrounds present in the WIMP region of interest and explore the impact of slow surfacemore » event contamination when searching for a WIMP signal.« less

Muon-Induced Neutrons Do Not Explain the DAMA Data

NASA Astrophysics Data System (ADS)

Klinger, J.; Kudryavtsev, V. A.

2015-04-01

We present an accurate model of the muon-induced background in the DAMA/LIBRA experiment. Our work challenges proposed mechanisms which seek to explain the observed DAMA signal modulation with muon-induced backgrounds. Muon generation and transport are performed using the MUSIC /MUSUN code, and subsequent interactions in the vicinity of the DAMA detector cavern are simulated with Geant4. We estimate the total muon-induced neutron flux in the detector cavern to be Φnν=1.0 ×10-9 cm-2 s-1 . We predict 3.49 ×10-5 counts /day /kg /keV , which accounts for less than 0.3% of the DAMA signal modulation amplitude.

Spectroscopic studies of the parameters of plasma jets during their propagation in the background plasma on the PF-3 facility

NASA Astrophysics Data System (ADS)

Dan'ko, S. A.; Ananyev, S. S.; Kalinin, Yu G.; Krauz, V. I.; Myalton, V. V.

2017-04-01

This paper presents measurement results of neon and helium plasma parameters in axial jets generated in plasma focus discharge. They were obtained in the course of experiments on laboratory modeling of astrophysical jets performed at the PF-3 facility. The plasma concentration was determined according to Stark broadening of spectral lines; the ionization temperature was determined by the average ion charge. The values of the concentration and temperature of jet plasma and background plasma at two distances from the pinch are also presented. In addition, an estimation was made of the heat content losses of the neon and helium jets during their movement through the surrounding medium.

Probing the Higgs couplings to photons in h→4ℓ at the LHC.

PubMed

Chen, Yi; Harnik, Roni; Vega-Morales, Roberto

2014-11-07

We explore the sensitivity of the Higgs decay to four leptons, the so-called golden channel, to higher dimensional loop-induced couplings of the Higgs boson to ZZ, Zγ, and γγ pairs, allowing for general CP mixtures. The larger standard model tree level coupling hZ(μ)Z(μ) is the dominant "background" for the loop-induced couplings. However, this large background interferes with the smaller loop-induced couplings, enhancing the sensitivity. We perform a maximum likelihood analysis based on analytic expressions of the fully differential decay width for h→4ℓ (4ℓ≡2e2μ,4e,4μ), including all interference effects. We find that the spectral shapes induced by Higgs couplings to photons are particularly different than the hZ(μ)Z(μ) background leading to enhanced sensitivity to these couplings. We show that even if the h→γγ and h→4ℓ rates agree with that predicted by the standard model, the golden channel has the potential to probe both the CP nature as well as the overall sign of the Higgs coupling to photons well before the end of a high-luminosity LHC.

Background factors related to and/or influencing occupation in mentally disordered offenders.

PubMed

Lindstedt, Helena; Ivarsson, Ann-Britt; Söderlund, Anne

2006-09-01

Knowledge of background and occupational related factors of mentally disordered offenders are missing. It is essential to understand these issues when planning discharge from forensic psychiatric hospital care to enable community dwelling. One aim was to investigate mentally disordered offenders' background factors, confidence in and how they value occupations. Another aim was to investigate MDOs background factors' in relation to and the influences on Occupational Performance and Social Participation. Data was collected with an explorative, correlative design after informed consent, from 74 mentally disordered offenders (mean age 34,2) cared for in forensic psychiatric hospitals. Assessments were Allen Cognitive Level Screen, Capability to Perform Daily Occupations, Interview Schedule of Social Interaction, Manchester Short Assessment of Quality of Life, Self-efficacy Scale and Importance scale. Eight background factors were assembled from the individual forensic psychiatric investigation. Most of the investigated background factors relate to and half of them influence occupational performance, particular the cognitive aspect of occupational performance. The influences on occupation originate from adulthood, such as suffering from schizophrenia, psycho/social problems, and having performed violent crimes. These findings indicate that staff in forensic hospital care should initiate rehabilitation with knowledge about MDOs' complex daily occupations. For avoiding information bias, information gathering preceding treatment planning should be performed in collaboration between caring staff and mentally disordered offenders.

Extracting Optical Fiber Background from Surface-Enhanced Raman Spectroscopy Spectra Based on Bi-Objective Optimization Modeling.

PubMed

Huang, Jie; Shi, Tielin; Tang, Zirong; Zhu, Wei; Liao, Guanglan; Li, Xiaoping; Gong, Bo; Zhou, Tengyuan

2017-08-01

We propose a bi-objective optimization model for extracting optical fiber background from the measured surface-enhanced Raman spectroscopy (SERS) spectrum of the target sample in the application of fiber optic SERS. The model is built using curve fitting to resolve the SERS spectrum into several individual bands, and simultaneously matching some resolved bands with the measured background spectrum. The Pearson correlation coefficient is selected as the similarity index and its maximum value is pursued during the spectral matching process. An algorithm is proposed, programmed, and demonstrated successfully in extracting optical fiber background or fluorescence background from the measured SERS spectra of rhodamine 6G (R6G) and crystal violet (CV). The proposed model not only can be applied to remove optical fiber background or fluorescence background for SERS spectra, but also can be transferred to conventional Raman spectra recorded using fiber optic instrumentation.

Spectral analysis-based risk score enables early prediction of mortality and cerebral performance in patients undergoing therapeutic hypothermia for ventricular fibrillation and comatose status

PubMed Central

Filgueiras-Rama, David; Calvo, Conrado J.; Salvador-Montañés, Óscar; Cádenas, Rosalía; Ruiz-Cantador, Jose; Armada, Eduardo; Rey, Juan Ramón; Merino, J.L.; Peinado, Rafael; Pérez-Castellano, Nicasio; Pérez-Villacastín, Julián; Quintanilla, Jorge G.; Jiménez, Santiago; Castells, Francisco; Chorro, Francisco J.; López-Sendón, J.L.; Berenfeld, Omer; Jalife, José; López de Sá, Esteban; Millet, José

2017-01-01

Background Early prognosis in comatose survivors after cardiac arrest due to ventricular fibrillation (VF) is unreliable, especially in patients undergoing mild hypothermia. We aimed at developing a reliable risk-score to enable early prediction of cerebral performance and survival. Methods Sixty-one out of 239 consecutive patients undergoing mild hypothermia after cardiac arrest, with eventual return of spontaneous circulation (ROSC), and comatose status on admission fulfilled the inclusion criteria. Background clinical variables, VF time and frequency domain fundamental variables were considered. The primary and secondary outcomes were a favorable neurological performance (FNP) during hospitalization and survival to hospital discharge, respectively. The predictive model was developed in a retrospective cohort (n=32; September 2006–September 2011, 48.5 ± 10.5 months of follow-up) and further validated in a prospective cohort (n = 29; October 2011–July 2013, 5 ± 1.8 months of follow-up). Results FNP was present in 16 (50.0%) and 21 patients (72.4%) in the retrospective and prospective cohorts, respectively. Seventeen (53.1%) and 21 patients (72.4%), respectively, survived to hospital discharge. Both outcomes were significantly associated (p < 0.001). Retrospective multivariate analysis provided a prediction model (sensitivity= 0.94, specificity = 1) that included spectral dominant frequency, derived power density and peak ratios between high and low frequency bands, and the number of shocks delivered before ROSC. Validation on the prospective cohort showed sensitivity = 0.88 and specificity = 0.91. A model-derived risk-score properly predicted 93% of FNP. Testing the model on follow-up showed a c-statistic ≥ 0.89. Conclusions A spectral analysis-based model reliably correlates time-dependent VF spectral changes with acute cerebral injury in comatose survivors undergoing mild hypothermia after cardiac arrest. PMID:25828128

Performance of European chemistry transport models as function of horizontal resolution

NASA Astrophysics Data System (ADS)

Schaap, M.; Cuvelier, C.; Hendriks, C.; Bessagnet, B.; Baldasano, J. M.; Colette, A.; Thunis, P.; Karam, D.; Fagerli, H.; Graff, A.; Kranenburg, R.; Nyiri, A.; Pay, M. T.; Rouïl, L.; Schulz, M.; Simpson, D.; Stern, R.; Terrenoire, E.; Wind, P.

2015-07-01

Air pollution causes adverse effects on human health as well as ecosystems and crop yield and also has an impact on climate change trough short-lived climate forcers. To design mitigation strategies for air pollution, 3D Chemistry Transport Models (CTMs) have been developed to support the decision process. Increases in model resolution may provide more accurate and detailed information, but will cubically increase computational costs and pose additional challenges concerning high resolution input data. The motivation for the present study was therefore to explore the impact of using finer horizontal grid resolution for policy support applications of the European Monitoring and Evaluation Programme (EMEP) model within the Long Range Transboundary Air Pollution (LRTAP) convention. The goal was to determine the "optimum resolution" at which additional computational efforts do not provide increased model performance using presently available input data. Five regional CTMs performed four runs for 2009 over Europe at different horizontal resolutions. The models' responses to an increase in resolution are broadly consistent for all models. The largest response was found for NO2 followed by PM10 and O3. Model resolution does not impact model performance for rural background conditions. However, increasing model resolution improves the model performance at stations in and near large conglomerations. The statistical evaluation showed that the increased resolution better reproduces the spatial gradients in pollution regimes, but does not help to improve significantly the model performance for reproducing observed temporal variability. This study clearly shows that increasing model resolution is advantageous, and that leaving a resolution of 50 km in favour of a resolution between 10 and 20 km is practical and worthwhile. As about 70% of the model response to grid resolution is determined by the difference in the spatial emission distribution, improved emission allocation procedures at high spatial and temporal resolution are a crucial factor for further model resolution improvements.

Music is as distracting as noise: the differential distraction of background music and noise on the cognitive test performance of introverts and extraverts.

PubMed

Furnham, Adrian; Strbac, Lisa

2002-02-20

Previous research has found that introverts' performance on complex cognitive tasks is more negatively affected by distracters, e.g. music and background television, than extraverts' performance. This study extended previous research by examining whether background noise would be as distracting as music. In the presence of silence, background garage music and office noise, 38 introverts and 38 extraverts carried out a reading comprehension task, a prose recall task and a mental arithmetic task. It was predicted that there would be an interaction between personality and background sound on all three tasks: introverts would do less well on all of the tasks than extraverts in the presence of music and noise but in silence performance would be the same. A significant interaction was found on the reading comprehension task only, although a trend for this effect was clearly present on the other two tasks. It was also predicted that there would be a main effect for background sound: performance would be worse in the presence of music and noise than silence. Results confirmed this prediction. These findings support the Eysenckian hypothesis of the difference in optimum cortical arousal in introverts and extraverts.

Acceleration techniques for dependability simulation. M.S. Thesis

NASA Technical Reports Server (NTRS)

Barnette, James David

1995-01-01

As computer systems increase in complexity, the need to project system performance from the earliest design and development stages increases. We have to employ simulation for detailed dependability studies of large systems. However, as the complexity of the simulation model increases, the time required to obtain statistically significant results also increases. This paper discusses an approach that is application independent and can be readily applied to any process-based simulation model. Topics include background on classical discrete event simulation and techniques for random variate generation and statistics gathering to support simulation.

Quadratic integrand double-hybrid made spin-component-scaled

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

Brémond, Éric, E-mail: eric.bremond@iit.it; Savarese, Marika; Sancho-García, Juan C.

2016-03-28

We propose two analytical expressions aiming to rationalize the spin-component-scaled (SCS) and spin-opposite-scaled (SOS) schemes for double-hybrid exchange-correlation density-functionals. Their performances are extensively tested within the framework of the nonempirical quadratic integrand double-hybrid (QIDH) model on energetic properties included into the very large GMTKN30 benchmark database, and on structural properties of semirigid medium-sized organic compounds. The SOS variant is revealed as a less computationally demanding alternative to reach the accuracy of the original QIDH model without losing any theoretical background.

Correlates of the Intention to Remain Sexually Inactive among Male Adolescents in an Islamic Country: Case of the Republic of Iran

ERIC Educational Resources Information Center

Mohtasham, Ghaffari; Shamsaddin, Niknami; Bazargan, Mohsen; Anosheravan, Kazemnejad; Elaheh, Mirzaee; Fazlolah, Ghofranipour

2009-01-01

Background: There are very few studies that have examined sexual intentions and behaviors of adolescents in Islamic countries. This study employs the Health Belief Model to assess the correlates of the intention to remain sexually inactive among male adolescents in the Republic of Iran. Methods: This cross-sectional study was performed with a…

Ground-to-air flow visualization using Solar Calcium-K line Background-Oriented Schlieren

NASA Astrophysics Data System (ADS)

Hill, Michael A.; Haering, Edward A.

2017-01-01

The Calcium-K Eclipse Background-Oriented Schlieren experiment was performed as a proof of concept test to evaluate the effectiveness of using the solar disk as a background to perform the Background-Oriented Schlieren (BOS) method of flow visualization. A ground-based imaging system was equipped with a Calcium-K line optical etalon filter to enable the use of the chromosphere of the sun as the irregular background to be used for BOS. A US Air Force T-38 aircraft performed three supersonic runs which eclipsed the sun as viewed from the imaging system. The images were successfully post-processed using optical flow methods to qualitatively reveal the density gradients in the flow around the aircraft.

Prediction of human observer performance in a 2-alternative forced choice low-contrast detection task using channelized Hotelling observer: Impact of radiation dose and reconstruction algorithms

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

Yu Lifeng; Leng Shuai; Chen Lingyun

2013-04-15

Purpose: Efficient optimization of CT protocols demands a quantitative approach to predicting human observer performance on specific tasks at various scan and reconstruction settings. The goal of this work was to investigate how well a channelized Hotelling observer (CHO) can predict human observer performance on 2-alternative forced choice (2AFC) lesion-detection tasks at various dose levels and two different reconstruction algorithms: a filtered-backprojection (FBP) and an iterative reconstruction (IR) method. Methods: A 35 Multiplication-Sign 26 cm{sup 2} torso-shaped phantom filled with water was used to simulate an average-sized patient. Three rods with different diameters (small: 3 mm; medium: 5 mm; large:more » 9 mm) were placed in the center region of the phantom to simulate small, medium, and large lesions. The contrast relative to background was -15 HU at 120 kV. The phantom was scanned 100 times using automatic exposure control each at 60, 120, 240, 360, and 480 quality reference mAs on a 128-slice scanner. After removing the three rods, the water phantom was again scanned 100 times to provide signal-absent background images at the exact same locations. By extracting regions of interest around the three rods and on the signal-absent images, the authors generated 21 2AFC studies. Each 2AFC study had 100 trials, with each trial consisting of a signal-present image and a signal-absent image side-by-side in randomized order. In total, 2100 trials were presented to both the model and human observers. Four medical physicists acted as human observers. For the model observer, the authors used a CHO with Gabor channels, which involves six channel passbands, five orientations, and two phases, leading to a total of 60 channels. The performance predicted by the CHO was compared with that obtained by four medical physicists at each 2AFC study. Results: The human and model observers were highly correlated at each dose level for each lesion size for both FBP and IR. The Pearson's product-moment correlation coefficients were 0.986 [95% confidence interval (CI): 0.958-0.996] for FBP and 0.985 (95% CI: 0.863-0.998) for IR. Bland-Altman plots showed excellent agreement for all dose levels and lesions sizes with a mean absolute difference of 1.0%{+-} 1.1% for FBP and 2.1%{+-} 3.3% for IR. Conclusions: Human observer performance on a 2AFC lesion detection task in CT with a uniform background can be accurately predicted by a CHO model observer at different radiation dose levels and for both FBP and IR methods.« less

Analytical performance specifications for changes in assay bias (Δbias) for data with logarithmic distributions as assessed by effects on reference change values.

PubMed

Petersen, Per H; Lund, Flemming; Fraser, Callum G; Sölétormos, György

2016-11-01

Background The distributions of within-subject biological variation are usually described as coefficients of variation, as are analytical performance specifications for bias, imprecision and other characteristics. Estimation of specifications required for reference change values is traditionally done using relationship between the batch-related changes during routine performance, described as Δbias, and the coefficients of variation for analytical imprecision (CV A ): the original theory is based on standard deviations or coefficients of variation calculated as if distributions were Gaussian. Methods The distribution of between-subject biological variation can generally be described as log-Gaussian. Moreover, recent analyses of within-subject biological variation suggest that many measurands have log-Gaussian distributions. In consequence, we generated a model for the estimation of analytical performance specifications for reference change value, with combination of Δbias and CV A based on log-Gaussian distributions of CV I as natural logarithms. The model was tested using plasma prolactin and glucose as examples. Results Analytical performance specifications for reference change value generated using the new model based on log-Gaussian distributions were practically identical with the traditional model based on Gaussian distributions. Conclusion The traditional and simple to apply model used to generate analytical performance specifications for reference change value, based on the use of coefficients of variation and assuming Gaussian distributions for both CV I and CV A , is generally useful.

Insights from the Source Physics Experiments on P/S Amplitude Ratio Methods of Identifying Explosions in a Background of Earthquakes

NASA Astrophysics Data System (ADS)

Walter, W. R.; Ford, S. R.; Xu, H.; Pasyanos, M. E.; Pyle, M. L.; Matzel, E.; Mellors, R. J.; Hauk, T. F.

2012-12-01

It is well established empirically that regional distance (200-1600 km) amplitude ratios of seismic P-to-S waves at sufficiently high frequencies (~>2 Hz) can identify explosions among a background of natural earthquakes. However the physical basis for the generation of explosion S-waves, and therefore the predictability of this P/S technique as a function of event properties such as size, depth, geology and path, remains incompletely understood. A goal of the Source Physics Experiments (SPE) at the Nevada National Security Site (NNSS, formerly the Nevada Test Site (NTS)) is to improve our physical understanding of the mechanisms of explosion S-wave generation and advance our ability to numerically model and predict them. Current models of explosion P/S values suggest they are frequency dependent with poor performance below the source corner frequencies and good performance above. This leads to expectations that small magnitude explosions might require much higher frequencies (>10 Hz) to identify them. Interestingly the 1-ton chemical source physics explosions SPE2 and SPE3 appear to discriminate well from background earthquakes in the frequency band 6-8 Hz, where P and S signals are visible at the NVAR array located near Mina, NV about 200 km away. NVAR is a primary seismic station in the International Monitoring System (IMS), part of the Comprehensive nuclear-Test-Ban Treaty (CTBT). The NVAR broadband element NV31 is co-located with the LLNL station MNV that recorded many NTS nuclear tests, allowing the comparison. We find the small SPE explosions in granite have similar Pn/Lg values at 6-8 Hz as the past nuclear tests mainly in softer rocks. We are currently examining a number of other stations in addition to NVAR, including the dedicated SPE stations that recorded the SPE explosions at much closer distances with very high sample rates, in order to better understand the observed frequency dependence as compared with the model predictions. We plan to use these observations to improve our explosion models and our ability to understand and predict where P/S methods of identifying explosions work and any circumstances where they may not. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Computational Assessment of Naturally Occurring Neutron and Photon Background Radiation Produced by Extraterrestrial Sources

DOE PAGES

Miller, Thomas Martin; de Wet, Wouter C.; Patton, Bruce W.

2015-10-28

In this study, a computational assessment of the variation in terrestrial neutron and photon background from extraterrestrial sources is presented. The motivation of this assessment is to evaluate the practicality of developing a tool or database to estimate background in real time (or near–real time) during an experimental measurement or to even predict the background for future measurements. The extraterrestrial source focused on during this assessment is naturally occurring galactic cosmic rays (GCRs). The MCNP6 transport code was used to perform the computational assessment. However, the GCR source available in MCNP6 was not used. Rather, models developed and maintained bymore » NASA were used to generate the GCR sources. The largest variation in both neutron and photon background spectra was found to be caused by changes in elevation on Earth's surface, which can be as large as an order of magnitude. All other perturbations produced background variations on the order of a factor of 3 or less. The most interesting finding was that ~80% and 50% of terrestrial background neutrons and photons, respectively, are generated by interactions in Earth's surface and other naturally occurring and man-made objects near a detector of particles from extraterrestrial sources and their progeny created in Earth's atmosphere. In conclusion, this assessment shows that it will be difficult to estimate the terrestrial background from extraterrestrial sources without a good understanding of a detector's surroundings. Therefore, estimating or predicting background during a measurement environment like a mobile random search will be difficult.« less

The Michigan Context and Performance Report Card: Public Elementary & Middle Schools, 2013

ERIC Educational Resources Information Center

Spalding, Audrey

2013-01-01

The Michigan Context and Performance Report Card measures school performance by adjusting standardized test scores to account for student background. Comparing schools using unadjusted test scores ignores the significant relationship between academic performance and student socioeconomic background--a dynamic outside a school's control. The…

Can the cosmic x ray and gamma ray background be due to reflection of a steep power law spectrum and Compton scattering by relativistic electrons?

NASA Technical Reports Server (NTRS)

Zycki, Piotr T.; Zdziarski, Andrzej A.; Svensson, Roland

1991-01-01

We reconsider the recent model for the origin in the cosmic X-ray and gamma-ray background by Rogers and Field. The background in the model is due to an unresolved population of AGNs. An individual AGN spectrum contains three components: a power law with the energy index of alpha = 1.1, an enhanced reflection component, and a component from Compton scattering by relativistic electrons with a low energy cutoff at some minimum Lorentz factor, gamma(sub min) much greater than 1. The MeV bump seen in the gamma-ray background is then explained by inverse Compton emission by the electrons. We show that the model does not reproduce the shape of the observed X-ray and gamma-ray background below 10 MeV and that it overproduces the background at larger energies. Furthermore, we find the assumptions made for the Compton component to be physically inconsistent. Relaxing the inconsistent assumptions leads to model spectra even more different from that of the observed cosmic background. Thus, we can reject the hypothesis that the high-energy cosmic background is due to the described model.

Radiogenic and muon-induced backgrounds in the LUX dark matter detector

NASA Astrophysics Data System (ADS)

Akerib, D. S.; Araújo, H. M.; Bai, X.; Bailey, A. J.; Balajthy, J.; Bernard, E.; Bernstein, A.; Bradley, A.; Byram, D.; Cahn, S. B.; Carmona-Benitez, M. C.; Chan, C.; Chapman, J. J.; Chiller, A. A.; Chiller, C.; Coffey, T.; Currie, A.; de Viveiros, L.; Dobi, A.; Dobson, J.; Druszkiewicz, E.; Edwards, B.; Faham, C. H.; Fiorucci, S.; Flores, C.; Gaitskell, R. J.; Gehman, V. M.; Ghag, C.; Gibson, K. R.; Gilchriese, M. G. D.; Hall, C.; Hertel, S. A.; Horn, M.; Huang, D. Q.; Ihm, M.; Jacobsen, R. G.; Kazkaz, K.; Knoche, R.; Larsen, N. A.; Lee, C.; Lindote, A.; Lopes, M. I.; Malling, D. C.; Mannino, R.; McKinsey, D. N.; Mei, D.-M.; Mock, J.; Moongweluwan, M.; Morad, J.; Murphy, A. St. J.; Nehrkorn, C.; Nelson, H.; Neves, F.; Ott, R. A.; Pangilinan, M.; Parker, P. D.; Pease, E. K.; Pech, K.; Phelps, P.; Reichhart, L.; Shutt, T.; Silva, C.; Solovov, V. N.; Sorensen, P.; O'Sullivan, K.; Sumner, T. J.; Szydagis, M.; Taylor, D.; Tennyson, B.; Tiedt, D. R.; Tripathi, M.; Uvarov, S.; Verbus, J. R.; Walsh, N.; Webb, R.; White, J. T.; Witherell, M. S.; Wolfs, F. L. H.; Woods, M.; Zhang, C.

2015-03-01

The Large Underground Xenon (LUX) dark matter experiment aims to detect rare low-energy interactions from Weakly Interacting Massive Particles (WIMPs). The radiogenic backgrounds in the LUX detector have been measured and compared with Monte Carlo simulation. Measurements of LUX high-energy data have provided direct constraints on all background sources contributing to the background model. The expected background rate from the background model for the 85.3 day WIMP search run is (2.6 ±0.2stat ±0.4sys) ×10-3 events keVee-1 kg-1day-1 in a 118 kg fiducial volume. The observed background rate is (3.6 ±0.4stat) ×10-3 events keVee-1 kg-1day-1 , consistent with model projections. The expectation for the radiogenic background in a subsequent one-year run is presented.

Infrared small target detection in heavy sky scene clutter based on sparse representation

NASA Astrophysics Data System (ADS)

Liu, Depeng; Li, Zhengzhou; Liu, Bing; Chen, Wenhao; Liu, Tianmei; Cao, Lei

2017-09-01

A novel infrared small target detection method based on sky clutter and target sparse representation is proposed in this paper to cope with the representing uncertainty of clutter and target. The sky scene background clutter is described by fractal random field, and it is perceived and eliminated via the sparse representation on fractal background over-complete dictionary (FBOD). The infrared small target signal is simulated by generalized Gaussian intensity model, and it is expressed by the generalized Gaussian target over-complete dictionary (GGTOD), which could describe small target more efficiently than traditional structured dictionaries. Infrared image is decomposed on the union of FBOD and GGTOD, and the sparse representation energy that target signal and background clutter decomposed on GGTOD differ so distinctly that it is adopted to distinguish target from clutter. Some experiments are induced and the experimental results show that the proposed approach could improve the small target detection performance especially under heavy clutter for background clutter could be efficiently perceived and suppressed by FBOD and the changing target could also be represented accurately by GGTOD.

Validation of Ten Noninvasive Diagnostic Models for Prediction of Liver Fibrosis in Patients with Chronic Hepatitis B

PubMed Central

Cheng, Jieyao; Hou, Jinlin; Ding, Huiguo; Chen, Guofeng; Xie, Qing; Wang, Yuming; Zeng, Minde; Ou, Xiaojuan; Ma, Hong; Jia, Jidong

2015-01-01

Background and Aims Noninvasive models have been developed for fibrosis assessment in patients with chronic hepatitis B. However, the sensitivity, specificity and diagnostic accuracy in evaluating liver fibrosis of these methods have not been validated and compared in the same group of patients. The aim of this study was to verify the diagnostic performance and reproducibility of ten reported noninvasive models in a large cohort of Asian CHB patients. Methods The diagnostic performance of ten noninvasive models (HALF index, FibroScan, S index, Zeng model, Youyi model, Hui model, APAG, APRI, FIB-4 and FibroTest) was assessed against the liver histology by ROC curve analysis in CHB patients. The reproducibility of the ten models were evaluated by recalculating the diagnostic values at the given cut-off values defined by the original studies. Results Six models (HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest) had AUROCs higher than 0.70 in predicting any fibrosis stage and 2 of them had best diagnostic performance with AUROCs to predict F≥2, F≥3 and F4 being 0.83, 0.89 and 0.89 for HALF index, 0.82, 0.87 and 0.87 for FibroScan, respectively. Four models (HALF index, FibroScan, Zeng model and Youyi model) showed good diagnostic values at given cut-offs. Conclusions HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest show a good diagnostic performance and all of them, except S index and FibroTest, have good reproducibility for evaluating liver fibrosis in CHB patients. Registration Number ChiCTR-DCS-07000039. PMID:26709706

Characterizing and Modeling the Noise and Complex Impedance of Feedhorn-Coupled TES Polarimeters

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

Appel, J. W.; Beall, J. A.; Essinger-Hileman, T.

2009-12-16

We present results from modeling the electrothermal performance of feedhorn-coupled transition edge sensor (TES) polarimeters under development for use in cosmic microwave background (CMB) polarization experiments. Each polarimeter couples radiation from a corrugated feedhorn through a planar orthomode transducer, which transmits power from orthogonal polarization modes to two TES bolometers. We model our TES with two- and three-block thermal architectures. We fit the complex impedance data at multiple points in the TES transition. From the fits, we predict the noise spectra. We present comparisons of these predictions to the data for two TESes on a prototype polarimeter.

Variable sound speed in interacting dark energy models

NASA Astrophysics Data System (ADS)

Linton, Mark S.; Pourtsidou, Alkistis; Crittenden, Robert; Maartens, Roy

2018-04-01

We consider a self-consistent and physical approach to interacting dark energy models described by a Lagrangian, and identify a new class of models with variable dark energy sound speed. We show that if the interaction between dark energy in the form of quintessence and cold dark matter is purely momentum exchange this generally leads to a dark energy sound speed that deviates from unity. Choosing a specific sub-case, we study its phenomenology by investigating the effects of the interaction on the cosmic microwave background and linear matter power spectrum. We also perform a global fitting of cosmological parameters using CMB data, and compare our findings to ΛCDM.

Facility Effect Characterization Test of NASA's HERMeS Hall Thruster

NASA Technical Reports Server (NTRS)

Huang, Wensheng; Kamhawi, Hani; Haag, Thomas W.; Ortega, Alejandro Lopez; Mikellides, Ioannis G.

2016-01-01

A test to characterize the effect of varying background pressure on NASA's 12.5-kW Hall Effect Rocket with Magnetic Shielding had being completed. This thruster is the baseline propulsion system for the Solar Electric Propulsion Technology Demonstration Mission (SEP TDM). Potential differences in thruster performance and oscillation characteristics when in ground facilities versus on-orbit are considered a primary risk for the propulsion system of the Asteroid Redirect Robotic Mission, which is a candidate for SEP TDM. The first primary objective of this test was to demonstrate that the tools being developed to predict the zero-background-pressure behavior of the thruster can provide self-consistent results. The second primary objective of this test was to provide data for refining a physics-based model of the thruster plume that will be used in spacecraft interaction studies. Diagnostics deployed included a thrust stand, Faraday probe, Langmuir probe, retarding potential analyzer, Wien filter spectrometer, and high-speed camera. From the data, a physics-based plume model was refined. Comparisons of empirical data to modeling results are shown.

A Computational Model of Afterimage Rotation in the Peripheral Drift Illusion Based on Retinal ON/OFF Responses

PubMed Central

Hayashi, Yuichiro; Ishii, Shin; Urakubo, Hidetoshi

2014-01-01

Human observers perceive illusory rotations after the disappearance of circularly repeating patches containing dark-to-light luminance. This afterimage rotation is a very powerful phenomenon, but little is known about the mechanisms underlying it. Here, we use a computational model to show that the afterimage rotation can be explained by a combination of fast light adaptation and the physiological architecture of the early visual system, consisting of ON- and OFF-type visual pathways. In this retinal ON/OFF model, the afterimage rotation appeared as a rotation of focus lines of retinal ON/OFF responses. Focus lines rotated clockwise on a light background, but counterclockwise on a dark background. These findings were consistent with the results of psychophysical experiments, which were also performed by us. Additionally, the velocity of the afterimage rotation was comparable with that observed in our psychophysical experiments. These results suggest that the early visual system (including the retina) is responsible for the generation of the afterimage rotation, and that this illusory rotation may be systematically misinterpreted by our high-level visual system. PMID:25517906

A study on characteristics of retrospective optimal interpolation with WRF testbed

NASA Astrophysics Data System (ADS)

Kim, S.; Noh, N.; Lim, G.

2012-12-01

This study presents the application of retrospective optimal interpolation (ROI) with Weather Research and Forecasting model (WRF). Song et al. (2009) suggest ROI method which is an optimal interpolation (OI) that gradually assimilates observations over the analysis window for variance-minimum estimate of an atmospheric state at the initial time of the analysis window. Song and Lim (2011) improve the method by incorporating eigen-decomposition and covariance inflation. ROI method assimilates the data at post analysis time using perturbation method (Errico and Raeder, 1999) without adjoint model. In this study, ROI method is applied to WRF model to validate the algorithm and to investigate the capability. The computational costs for ROI can be reduced due to the eigen-decomposition of background error covariance. Using the background error covariance in eigen-space, 1-profile assimilation experiment is performed. The difference between forecast errors with assimilation and without assimilation is obviously increased as time passed, which means the improvement of forecast error by assimilation. The characteristics and strength/weakness of ROI method are investigated by conducting the experiments with other data assimilation method.

Generation of Mouse Lung Epithelial Cells.

PubMed

Kasinski, Andrea L; Slack, Frank J

2013-08-05

Although in vivo models are excellent for assessing various facets of whole organism physiology, pathology, and overall response to treatments, evaluating basic cellular functions, and molecular events in mammalian model systems is challenging. It is therefore advantageous to perform these studies in a refined and less costly setting. One approach involves utilizing cells derived from the model under evaluation. The approach to generate such cells varies based on the cell of origin and often the genetics of the cell. Here we describe the steps involved in generating epithelial cells from the lungs of Kras LSL-G12D/+ ; p53 LSL-R172/+ mice (Kasinski and Slack, 2012). These mice develop aggressive lung adenocarcinoma following cre-recombinase dependent removal of a stop cassette in the transgenes and subsequent expression of Kra -G12D and p53 R172 . While this protocol may be useful for the generation of epithelial lines from other genetic backgrounds, it should be noted that the Kras; p53 cell line generated here is capable of proliferating in culture without any additional genetic manipulation that is often needed for less aggressive backgrounds.

Inconsistency of residents' communication performance in challenging consultations.

PubMed

Wouda, Jan C; van de Wiel, Harry B M

2013-12-01

Communication performance inconsistency between consultations is usually regarded as a measurement error that jeopardizes the reliability of assessments. However, inconsistency is an important phenomenon, since it indicates that physicians' communication may be below standard in some consultations. Fifty residents performed two challenging consultations. Residents' communication competency was assessed with the CELI instrument. Residents' background in communication skills training (CST) was also established. We used multilevel analysis to explore communication performance inconsistency between the two consultations. We also established the relationships between inconsistency and average performance quality, the type of consultation, and CST background. Inconsistency accounted for 45.5% of variance in residents' communication performance. Inconsistency was dependent on the type of consultation. The effect of CST background training on performance quality was case specific. Inconsistency and average performance quality were related for those consultation combinations dissimilar in goals, structure, and required skills. CST background had no effect on inconsistency. Physician communication performance should be of high quality, but also consistent regardless of the type and complexity of the consultation. In order to improve performance quality and reduce performance inconsistency, communication education should offer ample opportunities to practice a wide variety of challenging consultations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Search for gluinos and scalar quarks in pp collisions at square root[s] = 1.8 TeV using the missing energy plus multijets signature.

PubMed

Affolder, T; Akimoto, H; Akopian, A; Albrow, M G; Amaral, P; Amidei, D; Anikeev, K; Antos, J; Apollinari, G; Arisawa, T; Artikov, A; Asakawa, T; Ashmanskas, W; Azfar, F; Azzi-Bacchetta, P; Bacchetta, N; Bachacou, H; Bailey, S; de Barbaro, P; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Barone, M; Bauer, G; Bedeschi, F; Belforte, S; Bell, W H; Bellettini, G; Bellinger, J; Benjamin, D; Bensinger, J; Beretvas, A; Berge, J P; Berryhill, J; Bhatti, A; Binkley, M; Bisello, D; Bishai, M; Blair, R E; Blocker, C; Bloom, K; Blumenfeld, B; Blusk, S R; Bocci, A; Bodek, A; Bokhari, W; Bolla, G; Bonushkin, Y; Bortoletto, D; Boudreau, J; Brandl, A; van den Brink, S; Bromberg, C; Brozovic, M; Brubaker, E; Bruner, N; Buckley-Geer, E; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Byon-Wagner, A; Byrum, K L; Cabrera, S; Calafiura, P; Campbell, M; Carithers, W; Carlson, J; Carlsmith, D; Caskey, W; Castro, A; Cauz, D; Cerri, A; Chan, A W; Chang, P S; Chang, P T; Chapman, J; Chen, C; Chen, Y C; Cheng, M-T; Chertok, M; Chiarelli, G; Chirikov-Zorin, I; Chlachidze, G; Chlebana, F; Christofek, L; Chu, M L; Chung, Y S; Ciobanu, C I; Clark, A G; Connolly, A; Conway, J; Cordelli, M; Cranshaw, J; Cropp, R; Culbertson, R; Dagenhart, D; D'Auria, S; DeJongh, F; Dell'Agnello, S; Dell'Orso, M; Demortier, L; Deninno, M; Derwent, P F; Devlin, T; Dittmann, J R; Dominguez, A; Donati, S; Done, J; D'Onofrio, M; Dorigo, T; Eddy, N; Einsweiler, K; Elias, J E; Engels, E; Erbacher, R; Errede, D; Errede, S; Fan, Q; Feild, R G; Fernandez, J P; Ferretti, C; Field, R D; Fiori, I; Flaugher, B; Foster, G W; Franklin, M; Freeman, J; Friedman, J; Frisch, H J; Fukui, Y; Furic, I; Galeotti, S; Gallas, A; Gallinaro, M; Gao, T; Garcia-Sciveres, M; Garfinkel, A F; Gatti, P; Gay, C; Gerdes, D W; Giannetti, P; Giromini, P; Glagolev, V; Glenzinski, D; Gold, M; Goldstein, J; Gorelov, I; Goshaw, A T; Gotra, Y; Goulianos, K; Green, C; Grim, G; Gris, P; Groer, L; Grosso-Pilcher, C; Guenther, M; Guillian, G; Guimaraes da Costa, J; Haas, R M; Haber, C; Hahn, S R; Hall, C; Handa, T; Handler, R; Hao, W; Happacher, F; Hara, K; Hardman, A D; Harris, R M; Hartmann, F; Hatakeyama, K; Hauser, J; Heinrich, J; Heiss, A; Herndon, M; Hill, C; Hoffman, K D; Holck, C; Hollebeek, R; Holloway, L; Hughes, R; Huston, J; Huth, J; Ikeda, H; Incandela, J; Introzzi, G; Iwai, J; Iwata, Y; James, E; Jones, M; Joshi, U; Kambara, H; Kamon, T; Kaneko, T; Karr, K; Kasha, H; Kato, Y; Keaffaber, T A; Kelley, K; Kelly, M; Kennedy, R D; Kephart, R; Khazins, D; Kikuchi, T; Kilminster, B; Kim, B J; Kim, D H; Kim, H S; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kirby, M; Kirk, M; Kirsch, L; Klimenko, S; Koehn, P; Kondo, K; Konigsberg, J; Korn, A; Korytov, A; Kovacs, E; Kroll, J; Kruse, M; Kuhlmann, S E; Kurino, K; Kuwabara, T; Laasanen, A T; Lai, N; Lami, S; Lammel, S; Lancaster, J; Lancaster, M; Lander, R; Lath, A; Latino, G; LeCompte, T; Lee, A M; Lee, K; Leone, S; Lewis, J D; Lindgren, M; Liss, T M; Liu, J B; Liu, Y C; Litvintsev, D O; Lobban, O; Lockyer, N; Loken, J; Loreti, M; Lucchesi, D; Lukens, P; Lusin, S; Lyons, L; Lys, J; Madrak, R; Maeshima, K; Maksimovic, P; Malferrari, L; Mangano, M; Mariotti, M; Martignon, G; Martin, A; Matthews, J A J; Mayer, J; Mazzanti, P; McFarland, K S; McIntyre, P; McKigney, E; Menguzzato, M; Menzione, A; Mesropian, C; Meyer, A; Miao, T; Miller, R; Miller, J S; Minato, H; Miscetti, S; Mishina, M; Mitselmakher, G; Moggi, N; Moore, E; Moore, R; Morita, Y; Moulik, T; Mulhearn, M; Mukherjee, A; Muller, T; Munar, A; Murat, P; Murgia, S; Nachtman, J; Nagaslaev, V; Nahn, S; Nakada, H; Nakano, I; Nelson, C; Nelson, T; Neu, C; Neuberger, D; Newman-Holmes, C; Ngan, C-Y P; Niu, H; Nodulman, L; Nomerotski, A; Oh, S H; Oh, Y D; Ohmoto, T; Ohsugi, T; Oishi, R; Okusawa, T; Olsen, J; Orejudos, W; Pagliarone, C; Palmonari, F; Paoletti, R; Papadimitriou, V; Partos, D; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pescara, L; Phillips, T J; Piacentino, G; Pitts, K T; Pompos, A; Pondrom, L; Pope, G; Popovic, M; Prokoshin, F; Proudfoot, J; Ptohos, F; Pukhov, O; Punzi, G; Rakitine, A; Ratnikov, F; Reher, D; Reichold, A; Ribon, A; Riegler, W; Rimondi, F; Ristori, L; Riveline, M; Robertson, W J; Robinson, A; Rodrigo, T; Rolli, S; Rosenson, L; Roser, R; Rossin, R; Roy, A; Ruiz, A; Safonov, A; St Denis, R; Sakumoto, W K; Saltzberg, D; Sanchez, C; Sansoni, A; Santi, L; Sato, H; Savard, P; Schlabach, P; Schmidt, E E; Schmidt, M P; Schmitt, M; Scodellaro, L; Scott, A; Scribano, A; Segler, S; Seidel, S; Seiya, Y; Semenov, A; Semeria, F; Shah, T; Shapiro, M D; Shepard, P F; Shibayama, T; Shimojima, M; Shochet, M; Sidoti, A; Siegrist, J; Sill, A; Sinervo, P; Singh, P; Slaughter, A J; Sliwa, K; Smith, C; Snider, F D; Solodsky, A; Spalding, J; Speer, T; Sphicas, P; Spinella, F; Spiropulu, M; Spiegel, L; Steele, J; Stefanini, A; Strologas, J; Strumia, F; Stuart, D; Sumorok, K; Suzuki, T; Takano, T; Takashima, R; Takikawa, K; Tamburello, P; Tanaka, M; Tannenbaum, B; Tecchio, M; Tesarek, R; Teng, P K; Terashi, K; Tether, S; Thompson, A S; Thurman-Keup, R; Tipton, P; Tkaczyk, S; Toback, D; Tollefson, K; Tollestrup, A; Tonelli, D; Toyoda, H; Trischuk, W; de Troconiz, J F; Tseng, J; Turini, N; Ukegawa, F; Vaiciulis, T; Valls, J; Vejcik, S; Velev, G; Veramendi, G; Vidal, R; Vila, I; Vilar, R; Volobouev, I; von der Mey, M; Vucinic, D; Wagner, R G; Wagner, R L; Wallace, N B; Wan, Z; Wang, C; Wang, M J; Ward, B; Waschke, S; Watanabe, T; Waters, D; Watts, T; Webb, R; Wenzel, H; Wester, W C; Wicklund, A B; Wicklund, E; Wilkes, T; Williams, H H; Wilson, P; Winer, B L; Winn, D; Wolbers, S; Wolinski, D; Wolinski, J; Wolinski, S; Worm, S; Wu, X; Wyss, J; Yao, W; Yagil, A; Yeh, G P; Yoh, J; Yosef, C; Yoshida, T; Yu, I; Yu, S; Yu, Z; Zanetti, A; Zetti, F; Zucchelli, S

2002-01-28

We have performed a search for gluinos (g) and scalar quarks (q) in a data sample of 84 pb(-1) of pp collisions at square root[s] = 1.8 TeV, recorded by the Collider Detector at Fermilab. We investigate the final state of large missing transverse energy and three or more jets, a characteristic signature in R-parity-conserving supersymmetric models. The analysis has been performed "blind," in that the inspection of the signal region is made only after the predictions from standard model backgrounds have been calculated. Comparing the data with predictions of constrained supersymmetric models, we exclude gluino masses below 195 GeV/c2 (95% C.L.), independent of the squark mass. For the case m(q) approximately m(g), gluino masses below 300 GeV/c2 are excluded.

Sensitivity of air pollution simulations with LOTOS-EUROS to temporal distribution of anthropogenic emissions

NASA Astrophysics Data System (ADS)

Mues, A.; Kuenen, J.; Hendriks, C.; Manders, A.; Segers, A.; Scholz, Y.; Hueglin, C.; Builtjes, P.; Schaap, M.

2013-07-01

In this study the sensitivity of the model performance of the chemistry transport model (CTM) LOTOS-EUROS to the description of the temporal variability of emissions was investigated. Currently the temporal release of anthropogenic emissions is described by European average diurnal, weekly and seasonal time profiles per sector. These default time profiles largely neglect the variation of emission strength with activity patterns, region, species, emission process and meteorology. The three sources dealt with in this study are combustion in energy and transformation industries (SNAP1), non-industrial combustion (SNAP2) and road transport (SNAP7). First the impact of neglecting the temporal emission profiles for these SNAP categories on simulated concentrations was explored. In a~second step, we constructed more detailed emission time profiles for the three categories and quantified their impact on the model performance separately as well as combined. The performance in comparison to observations for Germany was quantified for the pollutants NO2, SO2 and PM10 and compared to a simulation using the default LOTOS-EUROS emission time profiles. In general the largest impact on the model performance was found when neglecting the default time profiles for the three categories. The daily average correlation coefficient for instance decreased by 0.04 (NO2), 0.11 (SO2) and 0.01 (PM10) at German urban background stations compared to the default simulation. A systematic increase of the correlation coefficient is found when using the new time profiles. The size of the increase depends on the source category, the component and station. Using national profiles for road transport showed important improvements of the explained variability over the weekdays as well as the diurnal cycle for NO2. The largest impact of the SNAP1 and 2 profiles were found for SO2. When using all new time profiles simultaneously in one simulation the daily average correlation coefficient increased by 0.05 (NO2), 0.07 (SO2) and 0.03 (PM10) at urban background stations in Germany. This exercise showed that to improve the performance of a CTM a better representation of the distribution of anthropogenic emission in time is recommendable. This can be done by developing a dynamical emission model which takes into account regional specific factors and meteorology.

Eysenck's Theory of Personality and the Role of Background Music in Cognitive Task Performance: A Mini-Review of Conflicting Findings and a New Perspective.

PubMed

Küssner, Mats B

2017-01-01

The question of whether background music is able to enhance cognitive task performance is of interest to scholars, educators, and stakeholders in business alike. Studies have shown that background music can have beneficial, detrimental or no effects on cognitive task performance. Extraversion-and its postulated underlying cause, cortical arousal-is regarded as an important factor influencing the outcome of such studies. According to Eysenck's theory of personality, extraverts' cortical arousal at rest is lower compared to that of introverts. Scholars have thus hypothesized that extraverts should benefit from background music in cognitive tasks, whereas introverts' performance should decline with music in the background. Reviewing studies that have considered extraversion as a mediator of the effect of background music on cognitive task performance, it is demonstrated that there is as much evidence in favor as there is against Eysenck's theory of personality. Further, revisiting Eysenck's concept of cortical arousal-which has traditionally been assessed by activity in the EEG alpha band-and reviewing literature on the link between extraversion and cortical arousal, it is revealed that there is conflicting evidence. Due to Eysenck's focus on alpha power, scholars have largely neglected higher frequency bands in the EEG signal as indicators of cortical arousal. Based on recent findings, it is suggested that beta power might not only be an indicator of alertness and attention but also a predictor of cognitive task performance. In conclusion, it is proposed that focused music listening prior to cognitive tasks might be a more efficient way to boost performance than listening to background music during cognitive tasks.

Eysenck's Theory of Personality and the Role of Background Music in Cognitive Task Performance: A Mini-Review of Conflicting Findings and a New Perspective

PubMed Central

Küssner, Mats B.

2017-01-01

The question of whether background music is able to enhance cognitive task performance is of interest to scholars, educators, and stakeholders in business alike. Studies have shown that background music can have beneficial, detrimental or no effects on cognitive task performance. Extraversion—and its postulated underlying cause, cortical arousal—is regarded as an important factor influencing the outcome of such studies. According to Eysenck's theory of personality, extraverts' cortical arousal at rest is lower compared to that of introverts. Scholars have thus hypothesized that extraverts should benefit from background music in cognitive tasks, whereas introverts' performance should decline with music in the background. Reviewing studies that have considered extraversion as a mediator of the effect of background music on cognitive task performance, it is demonstrated that there is as much evidence in favor as there is against Eysenck's theory of personality. Further, revisiting Eysenck's concept of cortical arousal—which has traditionally been assessed by activity in the EEG alpha band—and reviewing literature on the link between extraversion and cortical arousal, it is revealed that there is conflicting evidence. Due to Eysenck's focus on alpha power, scholars have largely neglected higher frequency bands in the EEG signal as indicators of cortical arousal. Based on recent findings, it is suggested that beta power might not only be an indicator of alertness and attention but also a predictor of cognitive task performance. In conclusion, it is proposed that focused music listening prior to cognitive tasks might be a more efficient way to boost performance than listening to background music during cognitive tasks. PMID:29184523

Evaluation in Appalachian pasture systems of the 1996 (update 2000) National Research Council model for weaning cattle.

PubMed

Whetsell, M S; Rayburn, E B; Osborne, P I

2006-05-01

This study was conducted to evaluate the accuracy of the National Research Council's (2000) Nutrient Requirements of Beef Cattle computer model when used to predict calf performance during on-farm pasture or dry-lot weaning and backgrounding. Calf performance was measured on 22 farms in 2002 and 8 farms in 2003 that participated in West Virginia Beef Quality Assurance Sale marketing pools. Calves were weaned on pasture (25 farms) or dry-lot (5 farms) and fed supplemental hay, haylage, ground shell corn, soybean hulls, or a commercial concentrate. Concentrates were fed at a rate of 0.0 to 1.5% of BW. The National Research Council (2000) model was used to predict ADG of each group of calves observed on each farm. The model error was measured by calculating residuals (the difference between predicted ADG minus observed ADG). Predicted animal performance was determined using level 1 of the model. Results show that, when using normal on-farm pasture sampling and forage analysis methods, the model error for ADG is high and did not accurately predict the performance of steers or heifers fed high-forage pasture-based diets; the predicted ADG was lower (P < 0.05) than the observed ADG. The estimated intake of low-producing animals was similar to the expected DMI, but for the greater-producing animals it was not. The NRC (2000) beef model may more accurately predict on-farm animal performance in pastured situations if feed analysis values reflect the energy value of the feed, account for selective grazing, and relate empty BW and shrunk BW to NDF.

Traffic contribution to air pollution in urban street canyons: Integrated application of the OSPM, moss biomonitoring and spectral analysis

NASA Astrophysics Data System (ADS)

Lazić, Lazar; Urošević, Mira Aničić; Mijić, Zoran; Vuković, Gordana; Ilić, Luka

2016-09-01

To investigate the air pollutant distribution within the ambient of urban street canyon, Operational Street Pollution Model (OSPM) was used to predict hourly content of NOX, NO, NO2, O3, CO, BNZ and PM10. The study was performed in five street canyons in Belgrade (Serbia) during 10-week summer period. The model receptors were located on each side of street canyons at 4 m, 8 m and 16 m height. To monitor airborne trace element content, the moss bag biomonitors were simultaneously exposed with the model receptors at two heights-4 m and 16 m. The results of both methods, modelling and biomonitoring, showed significantly decreasing trend of the air pollutants with height. The results indirectly demonstrate that biomonitoring, i.e., moss bag technique could be a valuable tool to verify model performance. In addition, spectral analysis was applied to investigate weekly variation of the daily background and modelled data set. Typical periodicities and weekend effect, caused by anthropogenic influences, have been identified.

Background and imaging simulations for the hard X-ray camera of the MIRAX mission

NASA Astrophysics Data System (ADS)

Castro, M.; Braga, J.; Penacchioni, A.; D'Amico, F.; Sacahui, R.

2016-07-01

We report the results of detailed Monte Carlo simulations of the performance expected both at balloon altitudes and at the probable satellite orbit of a hard X-ray coded-aperture camera being developed for the Monitor e Imageador de RAios X (MIRAX) mission. Based on a thorough mass model of the instrument and detailed specifications of the spectra and angular dependence of the various relevant radiation fields at both the stratospheric and orbital environments, we have used the well-known package GEANT4 to simulate the instrumental background of the camera. We also show simulated images of source fields to be observed and calculated the detailed sensitivity of the instrument in both situations. The results reported here are especially important to researchers in this field considering that we provide important information, not easily found in the literature, on how to prepare input files and calculate crucial instrumental parameters to perform GEANT4 simulations for high-energy astrophysics space experiments.

Plume dynamics from UV pulsed ablation of Al and Ti

NASA Astrophysics Data System (ADS)

Bauer, William; Perram, Glen; Haugan, Timothy

2016-12-01

Pulsed laser ablation of Al and Ti with a < 3.3 J/cm2 KrF laser and Ar background pressure of up to 1 Torr was performed to study the ablated plume. Mass loss experiments revealed the number of ablated atoms per pulse increases by 30% for Ti and 20% for Al as pressure decreases from 1 Torr to vacuum. Optical emission imaging performed using a gated ICCD revealed a strong dependence of shock front parameters, defined by the Sedov-Taylor blast and classical drag models, on background pressure. Spatially resolved optical emission spectroscopy from Al I, Al II, Ti I, and Ti II revealed ion temperatures of 104 K that decreased away from the target surface along the surface normal and neutral temperatures of 103 K independent of target distance. Comparison between kinetic energy in the shock and internal excitation energy reveals that nearly 100% of the energy is partitioned into shock front kinetic energy and 1% into internal excitation.

Adaptive Detector Arrays for Optical Communications Receivers

NASA Technical Reports Server (NTRS)

Vilnrotter, V.; Srinivasan, M.

2000-01-01

The structure of an optimal adaptive array receiver for ground-based optical communications is described and its performance investigated. Kolmogorov phase screen simulations are used to model the sample functions of the focal-plane signal distribution due to turbulence and to generate realistic spatial distributions of the received optical field. This novel array detector concept reduces interference from background radiation by effectively assigning higher confidence levels at each instant of time to those detector elements that contain significant signal energy and suppressing those that do not. A simpler suboptimum structure that replaces the continuous weighting function of the optimal receiver by a hard decision on the selection of the signal detector elements also is described and evaluated. Approximations and bounds to the error probability are derived and compared with the exact calculations and receiver simulation results. It is shown that, for photon-counting receivers observing Poisson-distributed signals, performance improvements of approximately 5 dB can be obtained over conventional single-detector photon-counting receivers, when operating in high background environments.

EasyModeller: A graphical interface to MODELLER

PubMed Central

2010-01-01

Background MODELLER is a program for automated protein Homology Modeling. It is one of the most widely used tool for homology or comparative modeling of protein three-dimensional structures, but most users find it a bit difficult to start with MODELLER as it is command line based and requires knowledge of basic Python scripting to use it efficiently. Findings The study was designed with an aim to develop of "EasyModeller" tool as a frontend graphical interface to MODELLER using Perl/Tk, which can be used as a standalone tool in windows platform with MODELLER and Python preinstalled. It helps inexperienced users to perform modeling, assessment, visualization, and optimization of protein models in a simple and straightforward way. Conclusion EasyModeller provides a graphical straight forward interface and functions as a stand-alone tool which can be used in a standard personal computer with Microsoft Windows as the operating system. PMID:20712861

Verbal communication improves laparoscopic team performance.

PubMed

Shiliang Chang; Waid, Erin; Martinec, Danny V; Bin Zheng; Swanstrom, Lee L

2008-06-01

The impact of verbal communication on laparoscopic team performance was examined. A total of 24 dyad teams, comprised of residents, medical students, and office staff, underwent 2 team tasks using a previously validated bench model. Twelve teams (feedback groups) received instant verbal instruction and feedback on their performance from an instructor which was compared with 12 teams (control groups) with minimal or no verbal feedback. Their performances were both video and audio taped for analysis. Surgical backgrounds were similar between feedback and control groups. Teams with more verbal feedback achieved significantly better task performance (P = .002) compared with the control group with less feedback. Impact of verbal feedback was more pronounced for tasks requiring team cooperation (aiming and navigation) than tasks depending on individual skills (knotting). Verbal communication, especially the instructions and feedback from an experienced instructor, improved team efficiency and performance.

AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment

PubMed Central

2011-01-01

Background Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge. In granting the scientific principles of transparency and reproducibility, Open Source solutions are increasingly acknowledged by regulatory authorities. Thus, an Open Source state-of-the-art high performance machine learning platform, interfacing multiple, customized machine learning algorithms for both graphical programming and scripting, to be used for large scale development of QSAR models of regulatory quality, is of great value to the QSAR community. Results This paper describes the implementation of the Open Source machine learning package AZOrange. AZOrange is specially developed to support batch generation of QSAR models in providing the full work flow of QSAR modeling, from descriptor calculation to automated model building, validation and selection. The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process. Several high performance machine learning algorithms are interfaced for efficient data set specific selection of the statistical method, promoting model accuracy. Using the high performance machine learning algorithms of AZOrange does not require programming knowledge as flexible applications can be created, not only at a scripting level, but also in a graphical programming environment. Conclusions AZOrange is a step towards meeting the needs for an Open Source high performance machine learning platform, supporting the efficient development of highly accurate QSAR models fulfilling regulatory requirements. PMID:21798025

User's manual for the generalized computer program system. Open-channel flow and sedimentation, TABS-2. Main text

NASA Astrophysics Data System (ADS)

Thomas, W. A.; McAnally, W. H., Jr.

1985-07-01

TABS-2 is a generalized numerical modeling system for open-channel flows, sedimentation, and constituent transport. It consists of more than 40 computer programs to perform modeling and related tasks. The major modeling components--RMA-2V, STUDH, and RMA-4--calculate two-dimensional, depth-averaged flows, sedimentation, and dispersive transport, respectively. The other programs in the system perform digitizing, mesh generation, data management, graphical display, output analysis, and model interfacing tasks. Utilities include file management and automatic generation of computer job control instructions. TABS-2 has been applied to a variety of waterways, including rivers, estuaries, bays, and marshes. It is designed for use by engineers and scientists who may not have a rigorous computer background. Use of the various components is described in Appendices A-O. The bound version of the report does not include the appendices. A looseleaf form with Appendices A-O is distributed to system users.

Engineered materials characterization report, volume 3 - corrosion data and modeling update for viability assessments

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

McCright, R D

1998-06-30

This Engineered Materials Characterization Report (EMCR), Volume 3, discusses in considerable detail the work of the past 18 months on testing the candidate materials proposed for the waste-package (WP) container and on modeling the performance of those materials in the Yucca Mountain (YM) repository setting This report was prepared as an update of information and serves as one of the supporting documents to the Viability Assessment (VA) of the Yucca Mountain Project. Previous versions of the EMCR have provided a history and background of container-materials selection and evaluation (Volume I), a compilation of physical and mechanical properties for the WPmore » design effort (Volume 2), and corrosion-test data and performance-modeling activities (Volume 3). Because the information in Volumes 1 and 2 is still largely current, those volumes are not being revised. As new information becomes available in the testing and modeling efforts, Volume 3 is periodically updated to include that information.« less

A novel, long-lived, and highly engraftable immunodeficient mouse model of mucopolysaccharidosis type I.

PubMed

Mendez, Daniel C; Stover, Alexander E; Rangel, Anthony D; Brick, David J; Nethercott, Hubert E; Torres, Marissa A; Khalid, Omar; Wong, Andrew Ms; Cooper, Jonathan D; Jester, James V; Monuki, Edwin S; McGuire, Cian; Le, Steven Q; Kan, Shih-Hsin; Dickson, Patricia I; Schwartz, Philip H

2015-01-01

Mucopolysaccharidosis type I (MPS I) is an inherited α-L-iduronidase (IDUA, I) deficiency in which glycosaminoglycan (GAG) accumulation causes progressive multisystem organ dysfunction, neurological impairment, and death. Current MPS I mouse models, based on a NOD/SCID (NS) background, are short-lived, providing a very narrow window to assess the long-term efficacy of therapeutic interventions. They also develop thymic lymphomas, making the assessment of potential tumorigenicity of human stem cell transplantation problematic. We therefore developed a new MPS I model based on a NOD/SCID/Il2rγ (NSG) background. This model lives longer than 1 year and is tumor-free during that time. NSG MPS I (NSGI) mice exhibit the typical phenotypic features of MPS I including coarsened fur and facial features, reduced/abnormal gait, kyphosis, and corneal clouding. IDUA is undetectable in all tissues examined while GAG levels are dramatically higher in most tissues. NSGI brain shows a significant inflammatory response and prominent gliosis. Neurological MPS I manifestations are evidenced by impaired performance in behavioral tests. Human neural and hematopoietic stem cells were found to readily engraft, with human cells detectable for at least 1 year posttransplantation. This new MPS I model is thus suitable for preclinical testing of novel pluripotent stem cell-based therapy approaches.

A novel, long-lived, and highly engraftable immunodeficient mouse model of mucopolysaccharidosis type I

PubMed Central

Mendez, Daniel C; Stover, Alexander E; Rangel, Anthony D; Brick, David J; Nethercott, Hubert E; Torres, Marissa A; Khalid, Omar; Wong, Andrew MS; Cooper, Jonathan D; Jester, James V; Monuki, Edwin S; McGuire, Cian; Le, Steven Q; Kan, Shih-hsin; Dickson, Patricia I; Schwartz, Philip H

2015-01-01

Mucopolysaccharidosis type I (MPS I) is an inherited α-L-iduronidase (IDUA, I) deficiency in which glycosaminoglycan (GAG) accumulation causes progressive multisystem organ dysfunction, neurological impairment, and death. Current MPS I mouse models, based on a NOD/SCID (NS) background, are short-lived, providing a very narrow window to assess the long-term efficacy of therapeutic interventions. They also develop thymic lymphomas, making the assessment of potential tumorigenicity of human stem cell transplantation problematic. We therefore developed a new MPS I model based on a NOD/SCID/Il2rγ (NSG) background. This model lives longer than 1 year and is tumor-free during that time. NSG MPS I (NSGI) mice exhibit the typical phenotypic features of MPS I including coarsened fur and facial features, reduced/abnormal gait, kyphosis, and corneal clouding. IDUA is undetectable in all tissues examined while GAG levels are dramatically higher in most tissues. NSGI brain shows a significant inflammatory response and prominent gliosis. Neurological MPS I manifestations are evidenced by impaired performance in behavioral tests. Human neural and hematopoietic stem cells were found to readily engraft, with human cells detectable for at least 1 year posttransplantation. This new MPS I model is thus suitable for preclinical testing of novel pluripotent stem cell-based therapy approaches. PMID:26052536

The optimisation, design and verification of feed horn structures for future Cosmic Microwave Background missions

NASA Astrophysics Data System (ADS)

McCarthy, Darragh; Trappe, Neil; Murphy, J. Anthony; O'Sullivan, Créidhe; Gradziel, Marcin; Doherty, Stephen; Huggard, Peter G.; Polegro, Arturo; van der Vorst, Maarten

2016-05-01

In order to investigate the origins of the Universe, it is necessary to carry out full sky surveys of the temperature and polarisation of the Cosmic Microwave Background (CMB) radiation, the remnant of the Big Bang. Missions such as COBE and Planck have previously mapped the CMB temperature, however in order to further constrain evolutionary and inflationary models, it is necessary to measure the polarisation of the CMB with greater accuracy and sensitivity than before. Missions undertaking such observations require large arrays of feed horn antennas to feed the detector arrays. Corrugated horns provide the best performance, however owing to the large number required (circa 5000 in the case of the proposed COrE+ mission), such horns are prohibitive in terms of thermal, mechanical and cost limitations. In this paper we consider the optimisation of an alternative smooth-walled piecewise conical profiled horn, using the mode-matching technique alongside a genetic algorithm. The technique is optimised to return a suitable design using efficient modelling software and standard desktop computing power. A design is presented showing a directional beam pattern and low levels of return loss, cross-polar power and sidelobes, as required by future CMB missions. This design is manufactured and the measured results compared with simulation, showing excellent agreement and meeting the required performance criteria. The optimisation process described here is robust and can be applied to many other applications where specific performance characteristics are required, with the user simply defining the beam requirements.

Increased conspicuousness can explain the match between visual sensitivities and blue plumage colours in fairy-wrens.

PubMed

Delhey, Kaspar; Hall, Michelle; Kingma, Sjouke A; Peters, Anne

2013-01-07

Colour signals are expected to match visual sensitivities of intended receivers. In birds, evolutionary shifts from violet-sensitive (V-type) to ultraviolet-sensitive (U-type) vision have been linked to increased prevalence of colours rich in shortwave reflectance (ultraviolet/blue), presumably due to better perception of such colours by U-type vision. Here we provide the first test of this widespread idea using fairy-wrens and allies (Family Maluridae) as a model, a family where shifts in visual sensitivities from V- to U-type eyes are associated with male nuptial plumage rich in ultraviolet/blue colours. Using psychophysical visual models, we compared the performance of both types of visual systems at two tasks: (i) detecting contrast between male plumage colours and natural backgrounds, and (ii) perceiving intraspecific chromatic variation in male plumage. While U-type outperforms V-type vision at both tasks, the crucial test here is whether U-type vision performs better at detecting and discriminating ultraviolet/blue colours when compared with other colours. This was true for detecting contrast between plumage colours and natural backgrounds (i), but not for discriminating intraspecific variability (ii). Our data indicate that selection to maximize conspicuousness to conspecifics may have led to the correlation between ultraviolet/blue colours and U-type vision in this clade of birds.

Target acquisition modeling over the exact optical path: extending the EOSTAR TDA with the TOD sensor performance model

NASA Astrophysics Data System (ADS)

Dijk, J.; Bijl, P.; Oppeneer, M.; ten Hove, R. J. M.; van Iersel, M.

2017-10-01

The Electro-Optical Signal Transmission and Ranging (EOSTAR) model is an image-based Tactical Decision Aid (TDA) for thermal imaging systems (MWIR/LWIR) developed for a sea environment with an extensive atmosphere model. The Triangle Orientation Discrimination (TOD) Target Acquisition model calculates the sensor and signal processing effects on a set of input triangle test pattern images, judges their orientation using humans or a Human Visual System (HVS) model and derives the system image quality and operational field performance from the correctness of the responses. Combination of the TOD model and EOSTAR, basically provides the possibility to model Target Acquisition (TA) performance over the exact path from scene to observer. In this method ship representative TOD test patterns are placed at the position of the real target, subsequently the combined effects of the environment (atmosphere, background, etc.), sensor and signal processing on the image are calculated using EOSTAR and finally the results are judged by humans. The thresholds are converted into Detection-Recognition-Identification (DRI) ranges of the real target. In experiments is shown that combination of the TOD model and the EOSTAR model is indeed possible. The resulting images look natural and provide insight in the possibilities of combining the two models. The TOD observation task can be done well by humans, and the measured TOD is consistent with analytical TOD predictions for the same camera that was modeled in the ECOMOS project.

Robust Data Detection for the Photon-Counting Free-Space Optical System With Implicit CSI Acquisition and Background Radiation Compensation

NASA Astrophysics Data System (ADS)

Song, Tianyu; Kam, Pooi-Yuen

2016-02-01

Since atmospheric turbulence and pointing errors cause signal intensity fluctuations and the background radiation surrounding the free-space optical (FSO) receiver contributes an undesired noisy component, the receiver requires accurate channel state information (CSI) and background information to adjust the detection threshold. In most previous studies, for CSI acquisition, pilot symbols were employed, which leads to a reduction of spectral and energy efficiency; and an impractical assumption that the background radiation component is perfectly known was made. In this paper, we develop an efficient and robust sequence receiver, which acquires the CSI and the background information implicitly and requires no knowledge about the channel model information. It is robust since it can automatically estimate the CSI and background component and detect the data sequence accordingly. Its decision metric has a simple form and involves no integrals, and thus can be easily evaluated. A Viterbi-type trellis-search algorithm is adopted to improve the search efficiency, and a selective-store strategy is adopted to overcome a potential error floor problem as well as to increase the memory efficiency. To further simplify the receiver, a decision-feedback symbol-by-symbol receiver is proposed as an approximation of the sequence receiver. By simulations and theoretical analysis, we show that the performance of both the sequence receiver and the symbol-by-symbol receiver, approach that of detection with perfect knowledge of the CSI and background radiation, as the length of the window for forming the decision metric increases.

A Dark Matter Search with MALBEK

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

Giovanetti, G. K.; Abgrall, N.; Aguayo, Estanislao

2015-06-01

The Majorana Demonstrator is an array of natural and enriched high purity germanium detectors that will search for the neutrinoless double-beta decay of 76Ge and perform a search for weakly interacting massive particles (WIMPs) with masses below 10 GeV. As part of the Majorana research and development efforts, we have deployed a modified, low-background broad energy germanium detector at the Kimballton Underground Research Facility. With its sub-keV energy threshold, this detector is potentially sensitive to non-Standard Model physics, including interactions with WIMPs. We discuss the backgrounds present in the WIMP region of interest and present results from a WIMP searchmore » with 221.49 live days of data from this detector.« less

A statistical downscaling approach for roadside NO2 concentrations: Application to a WRF-Chem study for Berlin

NASA Astrophysics Data System (ADS)

Kuik, Friderike; Lauer, Axel; von Schneidemesser, Erika; Butler, Tim

2017-04-01

Many European cities continue to struggle with meeting the European air quality limits for NO2. In Berlin, Germany, most of the exceedances in NO2 recorded at monitoring sites near busy roads can be largely attributed to emissions from traffic. In order to assess the impact of changes in traffic emissions on air quality at policy relevant scales, we combine the regional atmosphere-chemistry transport model WRF-Chem at a resolution of 1kmx1km with a statistical downscaling approach. Here, we build on the recently published study evaluating the performance of a WRF-Chem setup in representing observed urban background NO2 concentrations from Kuik et al. (2016) and extend this setup by developing and testing an approach to statistically downscale simulated urban background NO2 concentrations to street level. The approach uses a multilinear regression model to relate roadside NO2 concentrations observed with the municipal monitoring network with observed NO2 concentrations at urban background sites and observed traffic counts. For this, the urban background NO2 concentrations are decomposed into a long term, a synoptic and a diurnal component using the Kolmogorov-Zurbenko filtering method. We estimate the coefficients of the regression model for five different roadside stations in Berlin representing different street types. In a next step we combine the coefficients with simulated urban background concentrations and observed traffic counts, in order to estimate roadside NO2 concentrations based on the results obtained with WRF-Chem at the five selected stations. In a third step, we extrapolate the NO2 concentrations to all major roads in Berlin. The latter is based on available data for Berlin of daily mean traffic counts, diurnal and weekly cycles of traffic as well as simulated urban background NO2 concentrations. We evaluate the NO2 concentrations estimated with this method at street level for Berlin with additional observational data from stationary measurements and mobile measurements conducted during a campaign in summer 2014. The results show that this approach allows us to estimate NO2 concentrations at roadside reasonably well. The approach can be applied when observations show a strong correlation between roadside NO2 concentrations and traffic emissions from a single type of road. The method, however, shows weaknesses for intersections where observed NO2 concentrations are influenced by traffic on several different roads. We then apply this downscaling approach to estimate the impact of different traffic emission scenarios both on urban background and street level NO2 concentrations. References Kuik, F., Lauer, A., Churkina, G., Denier van der Gon, H. A. C., Fenner, D., Mar, K. A., and Butler, T. M.: Air quality modelling in the Berlin-Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data, Geosci. Model Dev., 9, 4339-4363, doi:10.5194/gmd-9-4339-2016, 2016.

Effect of Background Pressure on the Plasma Oscillation Characteristics of the HiVHAc Hall Thruster

DTIC Science & Technology

2014-06-01

Hall thruster , a number of plasma diagnostics were implemented to study the effect of varying facility background pressure on thruster operation. These diagnostics characterized the thruster performance, the plume, and the plasma oscillations in the thruster. Thruster performance and plume characteristics as functions of background pressure were previously published. This paper will focus on changes in the plasma oscillation characteristics with changing background pressure. The diagnostics used to study plasma oscillations include a high-speed camera and a set of

Background-Error Correlation Model Based on the Implicit Solution of a Diffusion Equation

DTIC Science & Technology

2010-01-01

1 Background- Error Correlation Model Based on the Implicit Solution of a Diffusion Equation Matthew J. Carrier* and Hans Ngodock...4. TITLE AND SUBTITLE Background- Error Correlation Model Based on the Implicit Solution of a Diffusion Equation 5a. CONTRACT NUMBER 5b. GRANT...2001), which sought to model error correlations based on the explicit solution of a generalized diffusion equation. The implicit solution is

Background Signal as an in Situ Predictor of Dopamine Oxidation Potential: Improving Interpretation of Fast-Scan Cyclic Voltammetry Data.

PubMed

Meunier, Carl J; Roberts, James G; McCarty, Gregory S; Sombers, Leslie A

2017-02-15

Background-subtracted fast-scan cyclic voltammetry (FSCV) has emerged as a powerful analytical technique for monitoring subsecond molecular fluctuations in live brain tissue. Despite increasing utilization of FSCV, efforts to improve the accuracy of quantification have been limited due to the complexity of the technique and the dynamic recording environment. It is clear that variable electrode performance renders calibration necessary for accurate quantification; however, the nature of in vivo measurements can make conventional postcalibration difficult, or even impossible. Analyte-specific voltammograms and scaling factors that are critical for quantification can shift or fluctuate in vivo. This is largely due to impedance changes, and the effects of impedance on these measurements have not been characterized. We have previously reported that the background current can be used to predict electrode-specific scaling factors in situ. In this work, we employ model circuits to investigate the impact of impedance on FSCV measurements. Additionally, we take another step toward in situ electrode calibration by using the oxidation potential of quinones on the electrode surface to accurately predict the oxidation potential for dopamine at any point in an electrochemical experiment, as both are dependent on impedance. The model, validated both in adrenal slice and live brain tissue, enables information encoded in the shape of the background voltammogram to determine electrochemical parameters that are critical for accurate quantification. This improves data interpretation and provides a significant next step toward more automated methods for in vivo data analysis.

Recognition and characterization of unstructured environmental sounds

NASA Astrophysics Data System (ADS)

Chu, Selina

2011-12-01

Environmental sounds are what we hear everyday, or more generally sounds that surround us ambient or background audio. Humans utilize both vision and hearing to respond to their surroundings, a capability still quite limited in machine processing. The first step toward achieving multimodal input applications is the ability to process unstructured audio and recognize audio scenes (or environments). Such ability would have applications in content analysis and mining of multimedia data or improving robustness in context aware applications through multi-modality, such as in assistive robotics, surveillances, or mobile device-based services. The goal of this thesis is on the characterization of unstructured environmental sounds for understanding and predicting the context surrounding of an agent or device. Most research on audio recognition has focused primarily on speech and music. Less attention has been paid to the challenges and opportunities for using audio to characterize unstructured audio. My research focuses on investigating challenging issues in characterizing unstructured environmental audio and to develop novel algorithms for modeling the variations of the environment. The first step in building a recognition system for unstructured auditory environment was to investigate on techniques and audio features for working with such audio data. We begin by performing a study that explore suitable features and the feasibility of designing an automatic environment recognition system using audio information. In my initial investigation to explore the feasibility of designing an automatic environment recognition system using audio information, I have found that traditional recognition and feature extraction for audio were not suitable for environmental sound, as they lack any type of structures, unlike those of speech and music which contain formantic and harmonic structures, thus dispelling the notion that traditional speech and music recognition techniques can simply be used for realistic environmental sound. Natural unstructured environment sounds contain a large variety of sounds, which are in fact noise-like and are not effectively modeled by Mel-frequency cepstral coefficients (MFCCs) or other commonly-used audio features, e.g. energy, zero-crossing, etc. Due to the lack of appropriate features that is suitable for environmental audio and to achieve a more effective representation, I proposed a specialized feature extraction algorithm for environmental sounds that utilizes the matching pursuit (MP) algorithm to learn the inherent structure of each type of sounds, which we called MP-features. MP-features have shown to capture and represent sounds from different sources and different ranges, where frequency domain features (e.g., MFCCs) fail and can be advantageous when combining with MFCCs to improve the overall performance. The third component leads to our investigation on modeling and detecting the background audio. One of the goals of this research is to characterize an environment. Since many events would blend into the background, I wanted to look for a way to achieve a general model for any particular environment. Once we have an idea of the background, it will enable us to identify foreground events even if we havent seen these events before. Therefore, the next step is to investigate into learning the audio background model for each environment type, despite the occurrences of different foreground events. In this work, I presented a framework for robust audio background modeling, which includes learning the models for prediction, data knowledge and persistent characteristics of the environment. This approach has the ability to model the background and detect foreground events as well as the ability to verify whether the predicted background is indeed the background or a foreground event that protracts for a longer period of time. In this work, I also investigated the use of a semi-supervised learning technique to exploit and label new unlabeled audio data. The final components of my thesis will involve investigating on learning sound structures for generalization and applying the proposed ideas to context aware applications. The inherent nature of environmental sound is noisy and contains relatively large amounts of overlapping events between different environments. Environmental sounds contain large variances even within a single environment type, and frequently, there are no divisible or clear boundaries between some types. Traditional methods of classification are generally not robust enough to handle classes with overlaps. This audio, hence, requires representation by complex models. Using deep learning architecture provides a way to obtain a generative model-based method for classification. Specifically, I considered the use of Deep Belief Networks (DBNs) to model environmental audio and investigate its applicability with noisy data to improve robustness and generalization. A framework was proposed using composite-DBNs to discover high-level representations and to learn a hierarchical structure for different acoustic environments in a data-driven fashion. Experimental results on real data sets demonstrate its effectiveness over traditional methods with over 90% accuracy on recognition for a high number of environmental sound types.

An Energy-Efficient Multi-Tier Architecture for Fall Detection on Smartphones

PubMed Central

Guvensan, M. Amac; Kansiz, A. Oguz; Camgoz, N. Cihan; Turkmen, H. Irem; Yavuz, A. Gokhan; Karsligil, M. Elif

2017-01-01

Automatic detection of fall events is vital to providing fast medical assistance to the causality, particularly when the injury causes loss of consciousness. Optimization of the energy consumption of mobile applications, especially those which run 24/7 in the background, is essential for longer use of smartphones. In order to improve energy-efficiency without compromising on the fall detection performance, we propose a novel 3-tier architecture that combines simple thresholding methods with machine learning algorithms. The proposed method is implemented on a mobile application, called uSurvive, for Android smartphones. It runs as a background service and monitors the activities of a person in daily life and automatically sends a notification to the appropriate authorities and/or user defined contacts when it detects a fall. The performance of the proposed method was evaluated in terms of fall detection performance and energy consumption. Real life performance tests conducted on two different models of smartphone demonstrate that our 3-tier architecture with feature reduction could save up to 62% of energy compared to machine learning only solutions. In addition to this energy saving, the hybrid method has a 93% of accuracy, which is superior to thresholding methods and better than machine learning only solutions. PMID:28644378

Targeting the minimal supersymmetric standard model with the compact muon solenoid experiment

NASA Astrophysics Data System (ADS)

Bein, Samuel Louis

An interpretation of CMS searches for evidence of supersymmetry in the context of the minimal supersymmetric Standard Model (MSSM) is given. It is found that supersymmetric particles with color charge are excluded in the mass range below about 400 GeV, but neutral and weakly-charged sparticles remain non-excluded in all mass ranges. Discussion of the non-excluded regions of the model parameter space is given, including details on the strengths and weaknesses of existing searches, and recommendations for future analysis strategies. Advancements in the modeling of events arising from quantum chromodynamics and electroweak boson production, which are major backgrounds in searches for new physics at the LHC, are also presented. These methods have been implemented as components of CMS searches for supersymmetry in proton-proton collisions resulting in purely hadronic events (i.e., events with no identified leptons) at a center of momentum energy of 13 TeV. These searches, interpreted in the context of simplified models, exclude supersymmetric gluons (gluinos) up to masses of 1400 to 1600 GeV, depending on the model considered, and exclude scalar top quarks with masses up to about 800 GeV, assuming a massless lightest supersymmetric particle. A search for non-excluded supersymmetry models is also presented, which uses multivariate discriminants to isolate potential signal candidate events. The search achieves sensitivity to new physics models in background-dominated kinematic regions not typically considered by analyses, and rules out supersymmetry models that survived 7 and 8 TeV searches performed by CMS.

Sensitivity of air pollution simulations with LOTOS-EUROS to the temporal distribution of anthropogenic emissions

NASA Astrophysics Data System (ADS)

Mues, A.; Kuenen, J.; Hendriks, C.; Manders, A.; Segers, A.; Scholz, Y.; Hueglin, C.; Builtjes, P.; Schaap, M.

2014-01-01

In this study the sensitivity of the model performance of the chemistry transport model (CTM) LOTOS-EUROS to the description of the temporal variability of emissions was investigated. Currently the temporal release of anthropogenic emissions is described by European average diurnal, weekly and seasonal time profiles per sector. These default time profiles largely neglect the variation of emission strength with activity patterns, region, species, emission process and meteorology. The three sources dealt with in this study are combustion in energy and transformation industries (SNAP1), nonindustrial combustion (SNAP2) and road transport (SNAP7). First of all, the impact of neglecting the temporal emission profiles for these SNAP categories on simulated concentrations was explored. In a second step, we constructed more detailed emission time profiles for the three categories and quantified their impact on the model performance both separately as well as combined. The performance in comparison to observations for Germany was quantified for the pollutants NO2, SO2 and PM10 and compared to a simulation using the default LOTOS-EUROS emission time profiles. The LOTOS-EUROS simulations were performed for the year 2006 with a temporal resolution of 1 h and a horizontal resolution of approximately 25 × 25km2. In general the largest impact on the model performance was found when neglecting the default time profiles for the three categories. The daily average correlation coefficient for instance decreased by 0.04 (NO2), 0.11 (SO2) and 0.01 (PM10) at German urban background stations compared to the default simulation. A systematic increase in the correlation coefficient is found when using the new time profiles. The size of the increase depends on the source category, component and station. Using national profiles for road transport showed important improvements in the explained variability over the weekdays as well as the diurnal cycle for NO2. The largest impact of the SNAP1 and 2 profiles were found for SO2. When using all new time profiles simultaneously in one simulation, the daily average correlation coefficient increased by 0.05 (NO2), 0.07 (SO2) and 0.03 (PM10) at urban background stations in Germany. This exercise showed that to improve the performance of a CTM, a better representation of the distribution of anthropogenic emission in time is recommendable. This can be done by developing a dynamical emission model that takes into account regional specific factors and meteorology.

Are changing emission patterns across the Northern Hemisphere influencing long-range transport contributions to background air pollution?

NASA Astrophysics Data System (ADS)

Mathur, R.; Kang, D.; Napelenok, S. L.; Xing, J.; Hogrefe, C.

2017-12-01

Air pollution reduction strategies for a region are complicated not only by the interplay of local emissions sources and several complex physical, chemical, dynamical processes in the atmosphere, but also hemispheric background levels of pollutants. Contrasting changes in emission patterns across the globe (e.g. declining emissions in North America and Western Europe in response to implementation of control measures and increasing emissions across Asia due to economic and population growth) are resulting in heterogeneous changes in the tropospheric chemical composition and are likely altering long-range transport impacts and consequently background pollution levels at receptor regions. To quantify these impacts, the WRF-CMAQ model is expanded to hemispheric scales and multi-decadal model simulations are performed for the period spanning 1990-2010 to examine changes in hemispheric air pollution resulting from changes in emissions over this period. Simulated trends in ozone and precursor species concentrations across the U.S. and the Northern Hemisphere over the past two decades are compared with those inferred from available measurements during this period. Additionally, the decoupled direct method (DDM) in CMAQ, a first- and higher-order sensitivity calculation technique, is used to estimate the sensitivity of O3 to emissions from different source regions across the Northern Hemisphere. The seasonal variations in source region contributions to background O3 are then estimated from these sensitivity calculations and will be discussed. These source region sensitivities estimated from DDM are then combined with the multi-decadal simulations of O3 distributions and emissions trends to characterize the changing contributions of different source regions to background O3 levels across North America. This characterization of changing long-range transport contributions is critical for the design and implementation of tighter national air quality standards

E2F transcription factor-1 deficiency reduces pathophysiology in the mouse model of Duchenne muscular dystrophy through increased muscle oxidative metabolism.

PubMed

Blanchet, Emilie; Annicotte, Jean-Sébastien; Pradelli, Ludivine A; Hugon, Gérald; Matecki, Stéfan; Mornet, Dominique; Rivier, François; Fajas, Lluis

2012-09-01

E2F1 deletion leads to increased mitochondrial number and function, increased body temperature in response to cold and increased resistance to fatigue with exercise. Since E2f1-/- mice show increased muscle performance, we examined the effect of E2f1 genetic inactivation in the mdx background, a mouse model of Duchenne muscular dystrophy (DMD). E2f1-/-;mdx mice demonstrated a strong reduction of physiopathological signs of DMD, including preservation of muscle structure, decreased inflammatory profile, increased utrophin expression, resulting in better endurance and muscle contractile parameters, comparable to normal mdx mice. E2f1 deficiency in the mdx genetic background increased the oxidative metabolic gene program, mitochondrial activity and improved muscle functions. Interestingly, we observed increased E2F1 protein levels in DMD patients, suggesting that E2F1 might represent a promising target for the treatment of DMD.

A search for top squarks with R-parity-violating decays to all-hadronic final states with the ATLAS detector in $$ \\sqrt{s}=8 $$ TeV proton-proton collisions

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2016-06-10

A search for the pair production of top squarks, each with R -parity-violating decays into two Standard Model quarks, is performed using 17.4 fb -1 of √s=8 TeV proton-proton collision data recorded by the ATLAS experiment at the LHC. Each top squark is assumed to decay to a b- and an s-quark, leading to four quarks in the final state. Background discrimination is achieved with the use of b-tagging and selections on the mass and substructure of large-radius jets, providing sensitivity to top squark masses as low as 100 GeV. Finally, no evidence of an excess beyond the Standard Model background prediction is observed and top squarks decaying tomore » $$\\overline{b}$$$\\overline{s}$$ are excluded for top squark masses in the range 100 ≤ m $$\\overline{t}$$ ≤ 315 GeV at 95% confidence level.« less

Obtaining phase velocity of turbulent boundary layer pressure fluctuations at high subsonic Mach number from wind tunnel data affected by strong background noise

NASA Astrophysics Data System (ADS)

Haxter, Stefan; Brouwer, Jens; Sesterhenn, Jörn; Spehr, Carsten

2017-08-01

Boundary layer measurements at high subsonic Mach number are evaluated in order to obtain the dominant phase velocities of boundary layer pressure fluctuations. The measurements were performed in a transonic wind tunnel which had a very strong background noise. The phase velocity was taken from phase inclination and from the convective peak in one- and two-dimensional wavenumber spectra. An approach was introduced to remove the acoustic noise from the data by applying a method based on CLEAN-SC on the two-dimensional spectra, thereby increasing the frequency range where information about the boundary layer was retrievable. A comparison with prediction models showed some discrepancies in the low-frequency range. Therefore, pressure data from a DNS calculation was used to substantiate the results of the analysis in this frequency range. Using the measured data, the DNS results and a review of the models used for comparison it was found that the phase velocity decreases at low frequencies.

A search for top squarks with R-parity-violating decays to all-hadronic final states with the ATLAS detector in $$ \\sqrt{s}=8 $$ TeV proton-proton collisions

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

Aad, G.; Abbott, B.; Abdallah, J.

A search for the pair production of top squarks, each with R -parity-violating decays into two Standard Model quarks, is performed using 17.4 fb -1 of √s=8 TeV proton-proton collision data recorded by the ATLAS experiment at the LHC. Each top squark is assumed to decay to a b- and an s-quark, leading to four quarks in the final state. Background discrimination is achieved with the use of b-tagging and selections on the mass and substructure of large-radius jets, providing sensitivity to top squark masses as low as 100 GeV. Finally, no evidence of an excess beyond the Standard Model background prediction is observed and top squarks decaying tomore » $$\\overline{b}$$$\\overline{s}$$ are excluded for top squark masses in the range 100 ≤ m $$\\overline{t}$$ ≤ 315 GeV at 95% confidence level.« less

Probabilistic segmentation and intensity estimation for microarray images.

PubMed

Gottardo, Raphael; Besag, Julian; Stephens, Matthew; Murua, Alejandro

2006-01-01

We describe a probabilistic approach to simultaneous image segmentation and intensity estimation for complementary DNA microarray experiments. The approach overcomes several limitations of existing methods. In particular, it (a) uses a flexible Markov random field approach to segmentation that allows for a wider range of spot shapes than existing methods, including relatively common 'doughnut-shaped' spots; (b) models the image directly as background plus hybridization intensity, and estimates the two quantities simultaneously, avoiding the common logical error that estimates of foreground may be less than those of the corresponding background if the two are estimated separately; and (c) uses a probabilistic modeling approach to simultaneously perform segmentation and intensity estimation, and to compute spot quality measures. We describe two approaches to parameter estimation: a fast algorithm, based on the expectation-maximization and the iterated conditional modes algorithms, and a fully Bayesian framework. These approaches produce comparable results, and both appear to offer some advantages over other methods. We use an HIV experiment to compare our approach to two commercial software products: Spot and Arrayvision.

Determination of blood oxygenation in the brain by time-resolved reflectance spectroscopy: influence of the skin, skull, and meninges

NASA Astrophysics Data System (ADS)

Hielscher, Andreas H.; Liu, Hanli; Wang, Lihong V.; Tittel, Frank K.; Chance, Britton; Jacques, Steven L.

1994-07-01

Near infrared light has been used for the determination of blood oxygenation in the brain but little attention has been paid to the fact that the states of blood oxygenation in arteries, veins, and capillaries differ substantially. In this study, Monte Carlo simulations for a heterogeneous system were conducted, and near infrared time-resolved reflectance measurements were performed on a heterogeneous tissue phantom model. The model was made of a solid polyester resin, which simulates the tissue background. A network of tubes was distributed uniformly through the resin to simulate the blood vessels. The time-resolved reflectance spectra were taken with different absorbing solutions filled in the network. Based on the simulation and experimental results, we investigated the dependence of the absorption coefficient obtained from the heterogeneous system on the absorption of the actual absorbing solution filled in the tubes. We show that light absorption by the brain should result from the combination of blood and blood-free tissue background.

Variance analysis of x-ray CT sinograms in the presence of electronic noise background.

PubMed

Ma, Jianhua; Liang, Zhengrong; Fan, Yi; Liu, Yan; Huang, Jing; Chen, Wufan; Lu, Hongbing

2012-07-01

Low-dose x-ray computed tomography (CT) is clinically desired. Accurate noise modeling is a fundamental issue for low-dose CT image reconstruction via statistics-based sinogram restoration or statistical iterative image reconstruction. In this paper, the authors analyzed the statistical moments of low-dose CT data in the presence of electronic noise background. The authors first studied the statistical moment properties of detected signals in CT transmission domain, where the noise of detected signals is considered as quanta fluctuation upon electronic noise background. Then the authors derived, via the Taylor expansion, a new formula for the mean-variance relationship of the detected signals in CT sinogram domain, wherein the image formation becomes a linear operation between the sinogram data and the unknown image, rather than a nonlinear operation in the CT transmission domain. To get insight into the derived new formula by experiments, an anthropomorphic torso phantom was scanned repeatedly by a commercial CT scanner at five different mAs levels from 100 down to 17. The results demonstrated that the electronic noise background is significant when low-mAs (or low-dose) scan is performed. The influence of the electronic noise background should be considered in low-dose CT imaging.

Variance analysis of x-ray CT sinograms in the presence of electronic noise background

PubMed Central

Ma, Jianhua; Liang, Zhengrong; Fan, Yi; Liu, Yan; Huang, Jing; Chen, Wufan; Lu, Hongbing

2012-01-01

Purpose: Low-dose x-ray computed tomography (CT) is clinically desired. Accurate noise modeling is a fundamental issue for low-dose CT image reconstruction via statistics-based sinogram restoration or statistical iterative image reconstruction. In this paper, the authors analyzed the statistical moments of low-dose CT data in the presence of electronic noise background. Methods: The authors first studied the statistical moment properties of detected signals in CT transmission domain, where the noise of detected signals is considered as quanta fluctuation upon electronic noise background. Then the authors derived, via the Taylor expansion, a new formula for the mean–variance relationship of the detected signals in CT sinogram domain, wherein the image formation becomes a linear operation between the sinogram data and the unknown image, rather than a nonlinear operation in the CT transmission domain. To get insight into the derived new formula by experiments, an anthropomorphic torso phantom was scanned repeatedly by a commercial CT scanner at five different mAs levels from 100 down to 17. Results: The results demonstrated that the electronic noise background is significant when low-mAs (or low-dose) scan is performed. Conclusions: The influence of the electronic noise background should be considered in low-dose CT imaging. PMID:22830738

Natural abundance deuterium and 18-oxygen effects on the precision of the doubly labeled water method

NASA Technical Reports Server (NTRS)

Horvitz, M. A.; Schoeller, D. A.

2001-01-01

The doubly labeled water method for measuring total energy expenditure is subject to error from natural variations in the background 2H and 18O in body water. There is disagreement as to whether the variations in background abundances of the two stable isotopes covary and what relative doses of 2H and 18O minimize the impact of variation on the precision of the method. We have performed two studies to investigate the amount and covariance of the background variations. These were a study of urine collected weekly from eight subjects who remained in the Madison, WI locale for 6 wk and frequent urine samples from 14 subjects during round-trip travel to a locale > or = 500 miles from Madison, WI. Background variation in excess of analytical error was detected in six of the eight nontravelers, and covariance was demonstrated in four subjects. Background variation was detected in all 14 travelers, and covariance was demonstrated in 11 subjects. The median slopes of the regression lines of delta2H vs. delta18O were 6 and 7, respectively. Modeling indicated that 2H and 18O doses yielding a 6:1 ratio of final enrichments should minimize this error introduced to the doubly labeled water method.

The Effect of Background Plasma Temperature on Growth and Damping of Whistler Mode Wave Power in the Earth's Magnetosphere

NASA Astrophysics Data System (ADS)

Maxworth, A. S.; Golkowski, M.; Malaspina, D.; Jaynes, A. N.

2017-12-01

Whistler mode waves play a dominant role in the energy dynamics of the Earth's magnetosphere. Trajectory of whistler mode waves can be predicted by raytracing. Raytracing is a numerical method which solves the Haselgrove's equations at each time step taking the background plasma parameters in to account. The majority of previous raytracing work was conducted assuming a cold (0 K) background magnetospheric plasma. Here we perform raytracing in a finite temperature plasma with background electron and ion temperatures of a few eV. When encountered with a high energy (>10 keV) electron distribution, whistler mode waves can undergo a power attenuation and/or growth, depending on resonance conditions which are a function of wave frequency, wave normal angle and particle energy. In this work we present the wave power attenuation and growth analysis of whistler mode waves, during the interaction with a high energy electron distribution. We have numerically modelled the high energy electron distribution as an isotropic velocity distribution, as well as an anisotropic bi-Maxwellian distribution. Both cases were analyzed with and without the temperature effects for the background magnetospheric plasma. Finally we compare our results with the whistler mode energy distribution obtained by the EMFISIS instrument hosted at the Van Allen Probe spacecraft.

Natural abundance deuterium and 18-oxygen effects on the precision of the doubly labeled water method.

PubMed

Horvitz, M A; Schoeller, D A

2001-06-01

The doubly labeled water method for measuring total energy expenditure is subject to error from natural variations in the background 2H and 18O in body water. There is disagreement as to whether the variations in background abundances of the two stable isotopes covary and what relative doses of 2H and 18O minimize the impact of variation on the precision of the method. We have performed two studies to investigate the amount and covariance of the background variations. These were a study of urine collected weekly from eight subjects who remained in the Madison, WI locale for 6 wk and frequent urine samples from 14 subjects during round-trip travel to a locale > or = 500 miles from Madison, WI. Background variation in excess of analytical error was detected in six of the eight nontravelers, and covariance was demonstrated in four subjects. Background variation was detected in all 14 travelers, and covariance was demonstrated in 11 subjects. The median slopes of the regression lines of delta2H vs. delta18O were 6 and 7, respectively. Modeling indicated that 2H and 18O doses yielding a 6:1 ratio of final enrichments should minimize this error introduced to the doubly labeled water method.

Assessing the impact of background spectral graph construction techniques on the topological anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Ziemann, Amanda K.; Messinger, David W.; Albano, James A.; Basener, William F.

2012-06-01

Anomaly detection algorithms have historically been applied to hyperspectral imagery in order to identify pixels whose material content is incongruous with the background material in the scene. Typically, the application involves extracting man-made objects from natural and agricultural surroundings. A large challenge in designing these algorithms is determining which pixels initially constitute the background material within an image. The topological anomaly detection (TAD) algorithm constructs a graph theory-based, fully non-parametric topological model of the background in the image scene, and uses codensity to measure deviation from this background. In TAD, the initial graph theory structure of the image data is created by connecting an edge between any two pixel vertices x and y if the Euclidean distance between them is less than some resolution r. While this type of proximity graph is among the most well-known approaches to building a geometric graph based on a given set of data, there is a wide variety of dierent geometrically-based techniques. In this paper, we present a comparative test of the performance of TAD across four dierent constructs of the initial graph: mutual k-nearest neighbor graph, sigma-local graph for two different values of σ > 1, and the proximity graph originally implemented in TAD.

Cardiac arrest risk standardization using administrative data compared to registry data

PubMed Central

Gaieski, David F.; Donnino, Michael W.; Nelson, Joshua I. M.; Mutter, Eric L.; Carr, Brendan G.; Abella, Benjamin S.; Wiebe, Douglas J.

2017-01-01

Background Methods for comparing hospitals regarding cardiac arrest (CA) outcomes, vital for improving resuscitation performance, rely on data collected by cardiac arrest registries. However, most CA patients are treated at hospitals that do not participate in such registries. This study aimed to determine whether CA risk standardization modeling based on administrative data could perform as well as that based on registry data. Methods and results Two risk standardization logistic regression models were developed using 2453 patients treated from 2000–2015 at three hospitals in an academic health system. Registry and administrative data were accessed for all patients. The outcome was death at hospital discharge. The registry model was considered the “gold standard” with which to compare the administrative model, using metrics including comparing areas under the curve, calibration curves, and Bland-Altman plots. The administrative risk standardization model had a c-statistic of 0.891 (95% CI: 0.876–0.905) compared to a registry c-statistic of 0.907 (95% CI: 0.895–0.919). When limited to only non-modifiable factors, the administrative model had a c-statistic of 0.818 (95% CI: 0.799–0.838) compared to a registry c-statistic of 0.810 (95% CI: 0.788–0.831). All models were well-calibrated. There was no significant difference between c-statistics of the models, providing evidence that valid risk standardization can be performed using administrative data. Conclusions Risk standardization using administrative data performs comparably to standardization using registry data. This methodology represents a new tool that can enable opportunities to compare hospital performance in specific hospital systems or across the entire US in terms of survival after CA. PMID:28783754

Information flow in an atmospheric model and data assimilation

NASA Astrophysics Data System (ADS)

Yoon, Young-noh

2011-12-01

Weather forecasting consists of two processes, model integration and analysis (data assimilation). During the model integration, the state estimate produced by the analysis evolves to the next cycle time according to the atmospheric model to become the background estimate. The analysis then produces a new state estimate by combining the background state estimate with new observations, and the cycle repeats. In an ensemble Kalman filter, the probability distribution of the state estimate is represented by an ensemble of sample states, and the covariance matrix is calculated using the ensemble of sample states. We perform numerical experiments on toy atmospheric models introduced by Lorenz in 2005 to study the information flow in an atmospheric model in conjunction with ensemble Kalman filtering for data assimilation. This dissertation consists of two parts. The first part of this dissertation is about the propagation of information and the use of localization in ensemble Kalman filtering. If we can perform data assimilation locally by considering the observations and the state variables only near each grid point, then we can reduce the number of ensemble members necessary to cover the probability distribution of the state estimate, reducing the computational cost for the data assimilation and the model integration. Several localized versions of the ensemble Kalman filter have been proposed. Although tests applying such schemes have proven them to be extremely promising, a full basic understanding of the rationale and limitations of localization is currently lacking. We address these issues and elucidate the role played by chaotic wave dynamics in the propagation of information and the resulting impact on forecasts. The second part of this dissertation is about ensemble regional data assimilation using joint states. Assuming that we have a global model and a regional model of higher accuracy defined in a subregion inside the global region, we propose a data assimilation scheme that produces the analyses for the global and the regional model simultaneously, considering forecast information from both models. We show that our new data assimilation scheme produces better results both in the subregion and the global region than the data assimilation scheme that produces the analyses for the global and the regional model separately.

Impact of scatterometer wind (ASCAT-A/B) data assimilation on semi real-time forecast system at KIAPS

NASA Astrophysics Data System (ADS)

Han, H. J.; Kang, J. H.

2016-12-01

Since Jul. 2015, KIAPS (Korea Institute of Atmospheric Prediction Systems) has been performing the semi real-time forecast system to assess the performance of their forecast system as a NWP model. KPOP (KIAPS Protocol for Observation Processing) is a part of KIAPS data assimilation system and has been performing well in KIAPS semi real-time forecast system. In this study, due to the fact that KPOP would be able to treat the scatterometer wind data, we analyze the effect of scatterometer wind (ASCAT-A/B) on KIAPS semi real-time forecast system. O-B global distribution and statistics of scatterometer wind give use two information which are the difference between background field and observation is not too large and KPOP processed the scatterometer wind data well. The changes of analysis increment because of O-B global distribution appear remarkably at the bottom of atmospheric field. It also shows that scatterometer wind data cover wide ocean where data would be able to short. Performance of scatterometer wind data can be checked through the vertical error reduction against IFS between background and analysis field and vertical statistics of O-A. By these analysis result, we can notice that scatterometer wind data will influence the positive effect on lower level performance of semi real-time forecast system at KIAPS. After, long-term result based on effect of scatterometer wind data will be analyzed.

First-Stage Development and Validation of a Web-Based Automated Dietary Modeling Tool: Using Constraint Optimization Techniques to Streamline Food Group and Macronutrient Focused Dietary Prescriptions for Clinical Trials

PubMed Central

Morrison, Evan; Sullivan, Emma; Dam, Hoa Khanh

2016-01-01

Background Standardizing the background diet of participants during a dietary randomized controlled trial is vital to trial outcomes. For this process, dietary modeling based on food groups and their target servings is employed via a dietary prescription before an intervention, often using a manual process. Partial automation has employed the use of linear programming. Validity of the modeling approach is critical to allow trial outcomes to be translated to practice. Objective This paper describes the first-stage development of a tool to automatically perform dietary modeling using food group and macronutrient requirements as a test case. The Dietary Modeling Tool (DMT) was then compared with existing approaches to dietary modeling (manual and partially automated), which were previously available to dietitians working within a dietary intervention trial. Methods Constraint optimization techniques were implemented to determine whether nonlinear constraints are best suited to the development of the automated dietary modeling tool using food composition and food consumption data. Dietary models were produced and compared with a manual Microsoft Excel calculator, a partially automated Excel Solver approach, and the automated DMT that was developed. Results The web-based DMT was produced using nonlinear constraint optimization, incorporating estimated energy requirement calculations, nutrition guidance systems, and the flexibility to amend food group targets for individuals. Percentage differences between modeling tools revealed similar results for the macronutrients. Polyunsaturated fatty acids and monounsaturated fatty acids showed greater variation between tools (practically equating to a 2-teaspoon difference), although it was not considered clinically significant when the whole diet, as opposed to targeted nutrients or energy requirements, were being addressed. Conclusions Automated modeling tools can streamline the modeling process for dietary intervention trials ensuring consistency of the background diets, although appropriate constraints must be used in their development to achieve desired results. The DMT was found to be a valid automated tool producing similar results to tools with less automation. The results of this study suggest interchangeability of the modeling approaches used, although implementation should reflect the requirements of the dietary intervention trial in which it is used. PMID:27471104

Development of NASA's Sample Cartridge Assembly: Summary of GEDS Design, Development Testing, and Thermal Analyses

NASA Technical Reports Server (NTRS)

O'Connor, Brian; Hernandez, Deborah; Hornsby, Linda; Brown, Maria; Horton-Mullins, Kathryn

2017-01-01

Outline: Background of ISS (International Space Station) Material Science Research Rack; NASA SCA (Sample Cartridge Assembly) Design; GEDS (Gravitational Effects in Distortion in Sintering) Experiment Ampoule Design; Development Testing Summary; Thermal Modeling and Analysis. Summary: GEDS design development challenging (GEDS Ampoule design developed through MUGS (Microgravity) testing; Short duration transient sample processing; Unable to measure sample temperatures); MUGS Development testing used to gather data (Actual LGF (Low Gradient Furnace)-like furnace response; Provided sample for sintering evaluation); Transient thermal model integral to successful GEDS experiment (Development testing provided furnace response; PI (Performance Indicator) evaluation of sintering anchored model evaluation of processing durations; Thermal transient model used to determine flight SCA sample processing profiles).

Multifluid MHD Simulations of the Plasma Environment of Comet Churyumov-Gerasimenko at Different Heliocentric Distances

NASA Astrophysics Data System (ADS)

Huang, Z.; Jia, X.; Rubin, M.; Fougere, N.; Gombosi, T. I.; Tenishev, V.; Combi, M. R.; Bieler, A. M.; Toth, G.; Hansen, K. C.; Shou, Y.

2014-12-01

We study the plasma environment of the comet Churyumov-Gerasimenko, which is the target of the Rosetta mission, by performing large scale numerical simulations. Our model is based on BATS-R-US within the Space Weather Modeling Framework that solves the governing multifluid MHD equations, which describe the behavior of the cometary heavy ions, the solar wind protons, and electrons. The model includes various mass loading processes, including ionization, charge exchange, dissociative ion-electron recombination, as well as collisional interactions between different fluids. The neutral background used in our MHD simulations is provided by a kinetic Direct Simulation Monte Carlo (DSMC) model. We will simulate how the cometary plasma environment changes at different heliocentric distances.

Modeling and simulation of a beam emission spectroscopy diagnostic for the ITER prototype neutral beam injector

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

Barbisan, M., E-mail: marco.barbisan@igi.cnr.it; Zaniol, B.; Pasqualotto, R.

2014-11-15

A test facility for the development of the neutral beam injection system for ITER is under construction at Consorzio RFX. It will host two experiments: SPIDER, a 100 keV H{sup −}/D{sup −} ion RF source, and MITICA, a prototype of the full performance ITER injector (1 MV, 17 MW beam). A set of diagnostics will monitor the operation and allow to optimize the performance of the two prototypes. In particular, beam emission spectroscopy will measure the uniformity and the divergence of the fast particles beam exiting the ion source and travelling through the beam line components. This type of measurementmore » is based on the collection of the H{sub α}/D{sub α} emission resulting from the interaction of the energetic particles with the background gas. A numerical model has been developed to simulate the spectrum of the collected emissions in order to design this diagnostic and to study its performance. The paper describes the model at the base of the simulations and presents the modeled H{sub α} spectra in the case of MITICA experiment.« less

Associations of PM2.5 and black carbon concentrations with traffic, idling, background pollution, and meteorology during school dismissals.

PubMed

Richmond-Bryant, J; Saganich, C; Bukiewicz, L; Kalin, R

2009-05-01

An air quality study was performed outside a cluster of schools in the East Harlem neighborhood of New York City. PM(2.5) and black carbon concentrations were monitored using real-time equipment with a one-minute averaging interval. Monitoring was performed at 1:45-3:30 PM during school days over the period October 31-November 17, 2006. The designated time period was chosen to capture vehicle emissions during end-of-day dismissals from the schools. During the monitoring period, minute-by-minute volume counts of idling and passing school buses, diesel trucks, and automobiles were obtained. These data were transcribed into time series of number of diesel vehicles idling, number of gasoline automobiles idling, number of diesel vehicles passing, and number of automobiles passing along the block adjacent to the school cluster. Multivariate regression models of the log-transform of PM(2.5) and black carbon (BC) concentrations in the East Harlem street canyon were developed using the observation data and data from the New York State Department of Environmental Conservation on meteorology and background PM(2.5). Analysis of variance was used to test the contribution of each covariate to variability in the log-transformed concentrations as a means to judge the relative contribution of each covariate. The models demonstrated that variability in background PM(2.5) contributes 80.9% of the variability in log[PM(2.5)] and 81.5% of the variability in log[BC]. Local traffic sources were demonstrated to contribute 5.8% of the variability in log[BC] and only 0.43% of the variability in log[PM(2.5)]. Diesel idling and passing were both significant contributors to variability in log[BC], while diesel passing was a significant contributor to log[PM(2.5)]. Automobile idling and passing did not contribute significant levels of variability to either concentration. The remainder of variability in each model was explained by temperature, along-canyon wind, and cross-canyon wind, which were all significant in the models.

NASA Technical Interchange Meeting (TIM): Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box

NASA Technical Reports Server (NTRS)

ONeil, D. A.; Craig, D. A.; Christensen, C. B.; Gresham, E. C.

2005-01-01

The objective of this Technical Interchange Meeting was to increase the quantity and quality of technical, cost, and programmatic data used to model the impact of investing in different technologies. The focus of this meeting was the Technology Tool Box (TTB), a database of performance, operations, and programmatic parameters provided by technologists and used by systems engineers. The TTB is the data repository used by a system of models known as the Advanced Technology Lifecycle Analysis System (ATLAS). This report describes the result of the November meeting, and also provides background information on ATLAS and the TTB.

Automated mixed traffic vehicle control and scheduling study

NASA Technical Reports Server (NTRS)

Peng, T. K. C.; Chon, K.

1976-01-01

The operation and the expected performance of a proposed automatic guideway transit system which uses low speed automated mixed traffic vehicles (AMTVs) were analyzed. Vehicle scheduling and headway control policies were evaluated with a transit system simulation model. The effect of mixed traffic interference on the average vehicle speed was examined with a vehicle pedestrian interface model. Control parameters regulating vehicle speed were evaluated for safe stopping and passenger comfort. Some preliminary data on the cost and operation of an experimental AMTV system are included. These data were the result of a separate task conducted at JPL, and were included as background information.

Primordial perturbations with pre-inflationary bounce

NASA Astrophysics Data System (ADS)

Cai, Yong; Wang, Yu-Tong; Zhao, Jin-Yun; Piao, Yun-Song

2018-05-01

Based on the effective field theory (EFT) of nonsingular cosmologies, we build a stable model, without the ghost and gradient instabilities, of bounce-inflation (inflation is preceded by a cosmological bounce). We perform a full simulation for the evolution of scalar perturbation, and find that the perturbation spectrum has a large-scale suppression (as expected), which is consistent with the power deficit of the cosmic microwave background (CMB) TT-spectrum at low multipoles, but unexpectedly, it also shows itself one marked lower valley. The depth of valley is relevant with the physics around the bounce scale, which is model-dependent.

Experiment-specific cosmic microwave background calculations made easier - Approximation formula for smoothed delta T/T windows

NASA Technical Reports Server (NTRS)

Gorski, Krzysztof M.

1993-01-01

Simple and easy to implement elementary function approximations are introduced to the spectral window functions needed in calculations of model predictions of the cosmic microwave backgrond (CMB) anisotropy. These approximations allow the investigator to obtain model delta T/T predictions in terms of single integrals over the power spectrum of cosmological perturbations and to avoid the necessity of performing the additional integrations. The high accuracy of these approximations is demonstrated here for the CDM theory-based calculations of the expected delta T/T signal in several experiments searching for the CMB anisotropy.

Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

PubMed Central

Cadieu, Charles F.; Hong, Ha; Yamins, Daniel L. K.; Pinto, Nicolas; Ardila, Diego; Solomon, Ethan A.; Majaj, Najib J.; DiCarlo, James J.

2014-01-01

The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition). This remarkable performance is mediated by the representation formed in inferior temporal (IT) cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs). It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of “kernel analysis” that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds. PMID:25521294

Determination of serum aluminum by electrothermal atomic absorption spectrometry: A comparison between Zeeman and continuum background correction systems

NASA Astrophysics Data System (ADS)

Kruger, Pamela C.; Parsons, Patrick J.

2007-03-01

Excessive exposure to aluminum (Al) can produce serious health consequences in people with impaired renal function, especially those undergoing hemodialysis. Al can accumulate in the brain and in bone, causing dialysis-related encephalopathy and renal osteodystrophy. Thus, dialysis patients are routinely monitored for Al overload, through measurement of their serum Al. Electrothermal atomic absorption spectrometry (ETAAS) is widely used for serum Al determination. Here, we assess the analytical performances of three ETAAS instruments, equipped with different background correction systems and heating arrangements, for the determination of serum Al. Specifically, we compare (1) a Perkin Elmer (PE) Model 3110 AAS, equipped with a longitudinally (end) heated graphite atomizer (HGA) and continuum-source (deuterium) background correction, with (2) a PE Model 4100ZL AAS equipped with a transversely heated graphite atomizer (THGA) and longitudinal Zeeman background correction, and (3) a PE Model Z5100 AAS equipped with a HGA and transverse Zeeman background correction. We were able to transfer the method for serum Al previously established for the Z5100 and 4100ZL instruments to the 3110, with only minor modifications. As with the Zeeman instruments, matrix-matched calibration was not required for the 3110 and, thus, aqueous calibration standards were used. However, the 309.3-nm line was chosen for analysis on the 3110 due to failure of the continuum background correction system at the 396.2-nm line. A small, seemingly insignificant overcorrection error was observed in the background channel on the 3110 instrument at the 309.3-nm line. On the 4100ZL, signal oscillation was observed in the atomization profile. The sensitivity, or characteristic mass ( m0), for Al at the 309.3-nm line on the 3110 AAS was found to be 12.1 ± 0.6 pg, compared to 16.1 ± 0.7 pg for the Z5100, and 23.3 ± 1.3 pg for the 4100ZL at the 396.2-nm line. However, the instrumental detection limits (3 SD) for Al were very similar: 3.0, 3.2, and 4.1 μg L - 1 for the Z5100, 4100ZL, and 3110, respectively. Serum Al method detection limits (3 SD) were 9.8, 6.9, and 7.3 μg L - 1 , respectively. Accuracy was assessed using archived serum (and plasma) reference materials from various external quality assessment schemes (EQAS). Values found with all three instruments were within the acceptable EQAS ranges. The data indicate that relatively modest ETAAS instrumentation equipped with continuum background correction is adequate for routine serum Al monitoring.

Measurement of Model Noise in a Hard-Wall Wind Tunnel

NASA Technical Reports Server (NTRS)

Soderman, Paul T.

2006-01-01

Identification, analysis, and control of fluid-mechanically-generated sound from models of aircraft and automobiles in special low-noise, semi-anechoic wind tunnels are an important research endeavor. Such studies can also be done in aerodynamic wind tunnels that have hard walls if phased microphone arrays are used to focus on the noise-source regions and reject unwanted reflections or background noise. Although it may be difficult to simulate the total flyover or drive-by noise in a closed wind tunnel, individual noise sources can be isolated and analyzed. An acoustic and aerodynamic study was made of a 7-percent-scale aircraft model in a NASA Ames 7-by-10-ft (about 2-by-3-m) wind tunnel for the purpose of identifying and attenuating airframe noise sources. Simulated landing, takeoff, and approach configurations were evaluated at Mach 0.26. Using a phased microphone array mounted in the ceiling over the inverted model, various noise sources in the high-lift system, landing gear, fins, and miscellaneous other components were located and compared for sound level and frequency at one flyover location. Numerous noise-alleviation devices and modifications of the model were evaluated. Simultaneously with acoustic measurements, aerodynamic forces were recorded to document aircraft conditions and any performance changes caused by geometric modifications. Most modern microphone-array systems function in the frequency domain in the sense that spectra of the microphone outputs are computed, then operations are performed on the matrices of microphone-signal cross-spectra. The entire acoustic field at one station in such a system is acquired quickly and interrogated during postprocessing. Beam-forming algorithms are employed to scan a plane near the model surface and locate noise sources while rejecting most background noise and spurious reflections. In the case of the system used in this study, previous studies in the wind tunnel have identified noise sources up to 19 dB below the normal background noise of the wind tunnel. Theoretical predictions of array performance are used to minimize the width and the side lobes of the beam pattern of the microphone array for a given test arrangement. To capture flyover noise of the inverted model, a 104-element microphone array in a 622-mm-diameter cluster was installed in a 19-mm-thick poly(methyl methacrylate) plate in the ceiling of the test section of the wind tunnel above the aircraft model (see Figure 1). The microphones were of the condenser type, and their diaphragms were mounted flush in the array plate, which was recessed 12.7 mm into the ceiling and covered by a porous aromatic polyamide cloth (not shown in the figure) to minimize boundary-layer noise. This design caused the level of flow noise to be much less than that of flush-mount designs. The drawback of this design was that the cloth attenuated sound somewhat and created acoustic resonances that could grow to several dB at a frequency of 10 kHz.

Probing the Higgs Couplings to Photons in h→4l at the LHC

DOE PAGES

Chen, Yi; Harnik, Roni; Vega-Morales, Roberto

2014-11-01

We explore the sensitivity of the Higgs decay to four leptons, the so-called golden channel, to higher dimensional loop-induced couplings of the Higgs boson tomore » $ZZ$, $$Z\\gamma$$, and $$\\gamma\\gamma$$, allowing for general CP mixtures. The larger standard model tree level coupling $$hZ^\\mu Z_\\mu$$ is the dominant "background" for the loop induced couplings. However this large background interferes with the smaller loop induced couplings, enhancing the sensitivity. We perform a maximum likelihood analysis based on analytic expressions of the fully differential decay width for $$h\\to 4\\ell$$ ($$4\\ell \\equiv 2e2\\mu, 4e, 4\\mu$$) including all interference effects. We find that the spectral shapes induced by Higgs couplings to photons are particularly different than the $$hZ^\\mu Z_\\mu$$ background leading to enhanced sensitivity to these couplings. We show that even if the $$h\\to\\gamma\\gamma$$ and $$h\\to 4\\ell$$ rates agree with that predicted by the Standard Model, the golden channel has the potential to probe both the CP nature as well as the overall sign of the Higgs coupling to photons well before the end of high-luminosity LHC running ($$\\sim$$3 ab$$^{-1}$$).« less

Ovariectomy results in inbred strain-specific increases in anxiety-like behavior in mice

PubMed Central

Schoenrock, Sarah Adams; Oreper, Daniel; Young, Nancy; Ervin, Robin Betsch; Bogue, Molly A.; Valdar, William; Tarantino, Lisa M.

2017-01-01

Women are at an increased risk for developing affective disorders during times of hormonal flux, including menopause when the ovaries cease production of estrogen. However, while all women undergo menopause, not all develop an affective disorder. Increased vulnerability can result from genetic predisposition, environmental factors and gene by environment interactions. In order to investigate interactions between genetic background and estrogen depletion, we performed bilateral ovariectomy, a surgical procedure that results in estrogen depletion and is thought to model the post-menopausal state, in a genetically defined panel of 37 inbred mouse strains. Seventeen days post-ovariectomy, we assessed behavior in two standard rodent assays of anxiety- and depressive-like behavior, the open field and forced swim tests. We detected a significant interaction between ovariectomy and genetic background on anxiety-like behavior in the open field. No strain specific effects of ovariectomy were observed in the forced swim assay. However, we did observe significant strain effects for all behaviors in both the open field and forced swim tests. This study is the largest to date to look at the effects of ovariectomy on behavior and provides evidence that ovariectomy interacts with genetic background to alter anxiety-like behavior in an animal model of menopause. PMID:27693591

Resonant Raman scattering background in XRF spectra of binary samples

NASA Astrophysics Data System (ADS)

Sánchez, Héctor Jorge; Leani, Juan José

2015-02-01

In x-ray fluorescence analysis, spectra present singular characteristics produced by the different scattering processes. When atoms are irradiated with incident energy lower and close to an absorption edge, scattering peaks appear due to an inelastic process known as resonant Raman scattering. In this work we present theoretical calculations of the resonant Raman scattering contributions to the background of x-ray fluorescence spectra of binary samples of current technological or biological interest. On one hand, a binary alloy of Fe with traces of Mn (Mn: 0.01%, Fe: 99.99%) was studied because of its importance in the stainless steels industries. On the second hand a pure sample of Ti with V traces (Ti: 99%, V: 1%) was analyzed due to the current relevance in medical applications. In order to perform the calculations the Shiraiwa and Fujino's model was used to calculate characteristic intensities and scattering interactions. This model makes certain assumptions and approximations to achieve the calculations, especially in the case of the geometrical conditions and the incident and take-off beams. For the binary sample studied in this work and the considered experimental conditions, the calculations show that the resonant Raman scattering background is significant under the fluorescent peak, affects the symmetry of the peaks and, depending on the concentrations, overcomes the enhancements contributions (secondary fluorescence).

Hybrid Higgs inflation: The use of disformal transformation

NASA Astrophysics Data System (ADS)

Sato, Seiga; Maeda, Kei-ichi

2018-04-01

We propose a hybrid type of the conventional Higgs inflation and new Higgs inflation models. We perform a disformal transformation into the Einstein frame and analyze the background dynamics and the cosmological perturbations in the truncated model, in which we ignore the higher-derivative terms of the Higgs field. From the observed power spectrum of the density perturbations, we obtain the constraint on the nonminimal coupling constant ξ and the mass parameter M in the derivative coupling. Although the primordial tilt ns in the hybrid model barely changes, the tensor-to-scalar ratio r moves from the value in the new Higgs inflationary model to that in the conventional Higgs inflationary model as |ξ | increases. We confirm our results by numerical analysis by ADM formalism of the full theory in the Jordan frame.

The MAJORANA DEMONSTRATOR for 0νββ: Current status and future plans

DOE PAGES

Green, M. P.; Abgrall, N.; Aguayo, E.; ...

2015-01-01

The Majorana Demonstrator will search for neutrinoless-double-beta decay (0νββ) in 76Ge, while establishing the feasibility of a future tonne-scale germanium-based 0νββ experiment, and performing searches for new physics beyond the Standard Model. The experiment, currently under construction at the Sanford Underground Research Facility in Lead, SD, will consist of a pair of modular high-purity germanium detector arrays housed inside of a compact copper, lead, and polyethylene shield. Through a combination of strict materials qualifications and assay, low-background design, and powerful background rejection techniques, the Demonstrator aims to achieve a background rate in the 0νββ region of interest (ROI) of nomore » more than 3 counts in the 0νββ-decay ROI per tonne of target isotope per year (cnts/(ROI-t-y)). The current status of the Demonstrator is discussed, as are plans for its completion.« less

Writer identification on historical Glagolitic documents

NASA Astrophysics Data System (ADS)

Fiel, Stefan; Hollaus, Fabian; Gau, Melanie; Sablatnig, Robert

2013-12-01

This work aims at automatically identifying scribes of historical Slavonic manuscripts. The quality of the ancient documents is partially degraded by faded-out ink or varying background. The writer identification method used is based on image features, which are described with Scale Invariant Feature Transform (SIFT) features. A visual vocabulary is used for the description of handwriting characteristics, whereby the features are clustered using a Gaussian Mixture Model and employing the Fisher kernel. The writer identification approach is originally designed for grayscale images of modern handwritings. But contrary to modern documents, the historical manuscripts are partially corrupted by background clutter and water stains. As a result, SIFT features are also found on the background. Since the method shows also good results on binarized images of modern handwritings, the approach was additionally applied on binarized images of the ancient writings. Experiments show that this preprocessing step leads to a significant performance increase: The identification rate on binarized images is 98.9%, compared to an identification rate of 87.6% gained on grayscale images.

Role of genetic background in induced instability

NASA Technical Reports Server (NTRS)

Kadhim, Munira A.; Nelson, G. A. (Principal Investigator)

2003-01-01

Genomic instability is effectively induced by ionizing radiation. Recently, evidence has accumulated supporting a relationship between genetic background and the radiation-induced genomic instability phenotype. This is possibly due to alterations in proteins responsible for maintenance of genomic integrity or altered oxidative metabolism. Studies in human cell lines, human primary cells, and mouse models have been performed predominantly using high linear energy transfer (LET) radiation, or high doses of low LET radiation. The interplay between genetics, radiation response, and genomic instability has not been fully determined at low doses of low LET radiation. However, recent studies using low doses of low LET radiation suggest that the relationship between genetic background and radiation-induced genomic instability may be more complicated than these same relationships at high LET or high doses of low LET radiation. The complexity of this relationship at low doses of low LET radiation suggests that more of the population may be at risk than previously recognized and may have implications for radiation risk assessment.

BIPAD: A web server for modeling bipartite sequence elements

PubMed Central

Bi, Chengpeng; Rogan, Peter K

2006-01-01

Background Many dimeric protein complexes bind cooperatively to families of bipartite nucleic acid sequence elements, which consist of pairs of conserved half-site sequences separated by intervening distances that vary among individual sites. Results We introduce the Bipad Server [1], a web interface to predict sequence elements embedded within unaligned sequences. Either a bipartite model, consisting of a pair of one-block position weight matrices (PWM's) with a gap distribution, or a single PWM matrix for contiguous single block motifs may be produced. The Bipad program performs multiple local alignment by entropy minimization and cyclic refinement using a stochastic greedy search strategy. The best models are refined by maximizing incremental information contents among a set of potential models with varying half site and gap lengths. Conclusion The web service generates information positional weight matrices, identifies binding site motifs, graphically represents the set of discovered elements as a sequence logo, and depicts the gap distribution as a histogram. Server performance was evaluated by generating a collection of bipartite models for distinct DNA binding proteins. PMID:16503993

Modelling and forecasting 3D-hypocentre seismicity in the Kanto region

NASA Astrophysics Data System (ADS)

Guo, Yicun; Zhuang, Jiancang; Hirata, Naoshi

2018-04-01

This study analyses the seismicity in the Kanto region by fitting the 2D-epicentre and 3D-hypocentre ETAS models to the JMA catalogue for events above magnitude M4.0. In the 3D ETAS model, the focal depth is assumed to follow the beta distribution. Compared with results from the 2D-epicentre ETAS model, the 3D ETAS model greatly improves the data fitting. In addition, the stochastic reconstruction method is used when validating the results of the 3D ETAS model, with results indicating that the shallow events are more productive and their aftershocks decay slightly faster in the time and epicentre dimensions. We also study the changes of seismicity patterns before and after the 2011 Tohoku earthquake. The direct aftershocks of events from the post-Tohoku period are more diffusive in time and epicentre but more concentrated in depth. The seismicity rate increases significantly following the Tohoku earthquake, especially along the interface of the subducting Pacific plate. The curve of cumulative background probabilities for events above M4.0 implies that the background rate decays back to the pre-Tohoku level in about 5 years after the Tohoku earthquake. However, the occurrence rates of smaller events (from M2.0 to M4.0) indicate that the adjustments of local stress field continue at finer scales. Finally, we verify that the 3D model can reproduce the focal depths better than the 2D model and improve the forecasting performance.

Three site Higgsless model at one loop

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

Chivukula, R. Sekhar; Simmons, Elizabeth H.; Matsuzaki, Shinya

2007-04-01

In this paper we compute the one loop chiral-logarithmic corrections to all O(p{sup 4}) counterterms in the three site Higgsless model. The calculation is performed using the background field method for both the chiral and gauge fields, and using Landau gauge for the quantum fluctuations of the gauge fields. The results agree with our previous calculations of the chiral-logarithmic corrections to the S and T parameters in 't Hooft-Feynman gauge. The work reported here includes a complete evaluation of all one loop divergences in an SU(2)xU(1) nonlinear sigma model, corresponding to an electroweak effective Lagrangian in the absence of custodialmore » symmetry.« less

Quasi-normal modes from non-commutative matrix dynamics

NASA Astrophysics Data System (ADS)

Aprile, Francesco; Sanfilippo, Francesco

2017-09-01

We explore similarities between the process of relaxation in the BMN matrix model and the physics of black holes in AdS/CFT. Focusing on Dyson-fluid solutions of the matrix model, we perform numerical simulations of the real time dynamics of the system. By quenching the equilibrium distribution we study quasi-normal oscillations of scalar single trace observables, we isolate the lowest quasi-normal mode, and we determine its frequencies as function of the energy. Considering the BMN matrix model as a truncation of N=4 SYM, we also compute the frequencies of the quasi-normal modes of the dual scalar fields in the AdS5-Schwarzschild background. We compare the results, and we finda surprising similarity.

Generic analysis of kinetically driven inflation

NASA Astrophysics Data System (ADS)

Saitou, Rio

2018-04-01

We perform a model-independent analysis of kinetically driven inflation (KDI) which (partially) includes generalized G-inflation and ghost inflation. We evaluate the background evolution splitting into the inflationary attractor and the perturbation around it. We also consider the quantum fluctuation of the scalar mode with a usual scaling and derive the spectral index, ignoring the contribution from the second-order products of slow-roll parameters. Using these formalisms, we find that within our generic framework the models of KDI which possess the shift symmetry of scalar field cannot create the quantum fluctuation consistent with the observation. Breaking the shift symmetry, we obtain a few essential conditions for viable models of KDI associated with the graceful exit.

Integrated species distribution models: combining presence-background data and site-occupancy data with imperfect detection

USGS Publications Warehouse

Koshkina, Vira; Wang, Yang; Gordon, Ascelin; Dorazio, Robert; White, Matthew; Stone, Lewi

2017-01-01

Two main sources of data for species distribution models (SDMs) are site-occupancy (SO) data from planned surveys, and presence-background (PB) data from opportunistic surveys and other sources. SO surveys give high quality data about presences and absences of the species in a particular area. However, due to their high cost, they often cover a smaller area relative to PB data, and are usually not representative of the geographic range of a species. In contrast, PB data is plentiful, covers a larger area, but is less reliable due to the lack of information on species absences, and is usually characterised by biased sampling. Here we present a new approach for species distribution modelling that integrates these two data types.We have used an inhomogeneous Poisson point process as the basis for constructing an integrated SDM that fits both PB and SO data simultaneously. It is the first implementation of an Integrated SO–PB Model which uses repeated survey occupancy data and also incorporates detection probability.The Integrated Model's performance was evaluated, using simulated data and compared to approaches using PB or SO data alone. It was found to be superior, improving the predictions of species spatial distributions, even when SO data is sparse and collected in a limited area. The Integrated Model was also found effective when environmental covariates were significantly correlated. Our method was demonstrated with real SO and PB data for the Yellow-bellied glider (Petaurus australis) in south-eastern Australia, with the predictive performance of the Integrated Model again found to be superior.PB models are known to produce biased estimates of species occupancy or abundance. The small sample size of SO datasets often results in poor out-of-sample predictions. Integrated models combine data from these two sources, providing superior predictions of species abundance compared to using either data source alone. Unlike conventional SDMs which have restrictive scale-dependence in their predictions, our Integrated Model is based on a point process model and has no such scale-dependency. It may be used for predictions of abundance at any spatial-scale while still maintaining the underlying relationship between abundance and area.

To BG or not to BG: Background Subtraction for EIT Coronal Loops

NASA Astrophysics Data System (ADS)

Beene, J. E.; Schmelz, J. T.

2003-05-01

One of the few observational tests for various coronal heating models is to determine the temperature profile along coronal loops. Since loops are such an abundant coronal feature, this method originally seemed quite promising - that the coronal heating problem might actually be solved by determining the temperature as a function of arc length and comparing these observations with predictions made by different models. But there are many instruments currently available to study loops, as well as various techniques used to determine their temperature characteristics. Consequently, there are many different, mostly conflicting temperature results. We chose data for ten coronal loops observed with the Extreme ultraviolet Imaging Telescope (EIT), and chose specific pixels along each loop, as well as corresponding nearby background pixels where the loop emission was not present. Temperature analysis from the 171-to-195 and 195-to-284 angstrom image ratios was then performed on three forms of the data: the original data alone, the original data with a uniform background subtraction, and the original data with a pixel-by-pixel background subtraction. The original results show loops of constant temperature, as other authors have found before us, but the 171-to-195 and 195-to-284 results are significantly different. Background subtraction does not change the constant-temperature result or the value of the temperature itself. This does not mean that loops are isothermal, however, because the background pixels, which are not part of any contiguous structure, also produce a constant-temperature result with the same value as the loop pixels. These results indicate that EIT temperature analysis should not be trusted, and the isothermal loops that result from EIT (and TRACE) analysis may be an artifact of the analysis process. Solar physics research at the University of Memphis is supported by NASA grants NAG5-9783 and NAG5-12096.

Estimating the Effects of Pre-College Education on College Performance

DTIC Science & Technology

2013-05-10

background information from many variables into a single measure of the expected likelihood of a person receiving treatment. This leads into a discussion of...but do not directly effect outcome variables like academic order of merit, graduation rates, or academic grades. Our model had to not only include the...both indicator variables for whether the individual’s parents ever served in any of the armed forces. High School Quality Measure is a variable

Goddard Visiting Scientist Program for the Space and Earth Sciences Directorate

NASA Technical Reports Server (NTRS)

Kerr, Frank

1992-01-01

A visiting scientist program was conducted in the space and earth sciences at GSFC. Research was performed in the following areas: astronomical observations; broadband x-ray spectral variability; ground-based spectroscopic and photometric studies; Seyfert galaxies; active galactic nuclei (AGN); massive stellar black holes; the differential microwave radiometer (DMR) onboard the cosmic background explorer (COBE); atmospheric models; and airborne and ground based radar observations. The specific research efforts are detailed by tasks.

Comparison of Combat Gauze with Fibrin Sealant Patch in Hemorrhage Control after Vascular or Hepatic Trauma

DTIC Science & Technology

2017-05-15

experimentation are needed to determine the role of fibrin patches in acute traumatic hemorrhage control . 2.0 BACKGROUND Hemorrhage remains the most...Compare performance of CG to EVARREST in a porcine model of vascular trauma. Animals were separated into three groups : 1. Control : Arterial and...trauma. Animals were separated into three groups : 1. Control : Arterial and venous cannulation followed by laparotomy with liver injury and

Comparison of Combat Gauze with Fibrin Sealant Patch in Hemorrhage Control after Vascular or Hepatic Trauma

DTIC Science & Technology

2017-05-01

experimentation are needed to determine the role of fibrin patches in acute traumatic hemorrhage control . 2.0 BACKGROUND Hemorrhage remains the most...Compare performance of CG to EVARREST in a porcine model of vascular trauma. Animals were separated into three groups : 1. Control : Arterial and...trauma. Animals were separated into three groups : 1. Control : Arterial and venous cannulation followed by laparotomy with liver injury and

An innovative Near-Peer Mentoring Model for Undergraduate and Secondary Students: STEM Focus

DTIC Science & Technology

2014-03-14

searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments...568 Doughten Drive,Fort Detrick,MD,21702-5010 8. PERFORMING ORGANIZATION REPORT NUMBER N /A 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES...applications, research background, experience with youth, and interviews. They ranged in age from 18 to 25 (M = 21) and were either undergraduate ( n = 7

Background stratified Poisson regression analysis of cohort data.

PubMed

Richardson, David B; Langholz, Bryan

2012-03-01

Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.

Computational State Space Models for Activity and Intention Recognition. A Feasibility Study

PubMed Central

Krüger, Frank; Nyolt, Martin; Yordanova, Kristina; Hein, Albert; Kirste, Thomas

2014-01-01

Background Computational state space models (CSSMs) enable the knowledge-based construction of Bayesian filters for recognizing intentions and reconstructing activities of human protagonists in application domains such as smart environments, assisted living, or security. Computational, i. e., algorithmic, representations allow the construction of increasingly complex human behaviour models. However, the symbolic models used in CSSMs potentially suffer from combinatorial explosion, rendering inference intractable outside of the limited experimental settings investigated in present research. The objective of this study was to obtain data on the feasibility of CSSM-based inference in domains of realistic complexity. Methods A typical instrumental activity of daily living was used as a trial scenario. As primary sensor modality, wearable inertial measurement units were employed. The results achievable by CSSM methods were evaluated by comparison with those obtained from established training-based methods (hidden Markov models, HMMs) using Wilcoxon signed rank tests. The influence of modeling factors on CSSM performance was analyzed via repeated measures analysis of variance. Results The symbolic domain model was found to have more than states, exceeding the complexity of models considered in previous research by at least three orders of magnitude. Nevertheless, if factors and procedures governing the inference process were suitably chosen, CSSMs outperformed HMMs. Specifically, inference methods used in previous studies (particle filters) were found to perform substantially inferior in comparison to a marginal filtering procedure. Conclusions Our results suggest that the combinatorial explosion caused by rich CSSM models does not inevitably lead to intractable inference or inferior performance. This means that the potential benefits of CSSM models (knowledge-based model construction, model reusability, reduced need for training data) are available without performance penalty. However, our results also show that research on CSSMs needs to consider sufficiently complex domains in order to understand the effects of design decisions such as choice of heuristics or inference procedure on performance. PMID:25372138

Verification of a Quality Management Theory: Using a Delphi Study

PubMed Central

Mosadeghrad, Ali Mohammad

2013-01-01

Background: A model of quality management called Strategic Collaborative Quality Management (SCQM) model was developed based on the quality management literature review, the findings of a survey on quality management assessment in healthcare organisations, semi-structured interviews with healthcare stakeholders, and a Delphi study on healthcare quality management experts. The purpose of this study was to verify the SCQM model. Methods: The proposed model was further developed using feedback from thirty quality management experts using a Delphi method. Further, a guidebook for its implementation was prepared including a road map and performance measurement. Results: The research led to the development of a context-specific model of quality management for healthcare organisations and a series of guidelines for its implementation. Conclusion: A proper model of quality management should be developed and implemented properly in healthcare organisations to achieve business excellence. PMID:24596883

Teaching Elliptical Excision Skills to Novice Medical Students: A Randomized Controlled Study Comparing Low- and High-Fidelity Bench Models

PubMed Central

Denadai, Rafael; Oshiiwa, Marie; Saad-Hossne, Rogério

2014-01-01

Background: The search for alternative and effective forms of training simulation is needed due to ethical and medico-legal aspects involved in training surgical skills on living patients, human cadavers and living animals. Aims: To evaluate if the bench model fidelity interferes in the acquisition of elliptical excision skills by novice medical students. Materials and Methods: Forty novice medical students were randomly assigned to 5 practice conditions with instructor-directed elliptical excision skills’ training (n = 8): didactic materials (control); organic bench model (low-fidelity); ethylene-vinyl acetate bench model (low-fidelity); chicken legs’ skin bench model (high-fidelity); or pig foot skin bench model (high-fidelity). Pre- and post-tests were applied. Global rating scale, effect size, and self-perceived confidence based on Likert scale were used to evaluate all elliptical excision performances. Results: The analysis showed that after training, the students practicing on bench models had better performance based on Global rating scale (all P < 0.0000) and felt more confident to perform elliptical excision skills (all P < 0.0000) when compared to the control. There was no significant difference (all P > 0.05) between the groups that trained on bench models. The magnitude of the effect (basic cutaneous surgery skills’ training) was considered large (>0.80) in all measurements. Conclusion: The acquisition of elliptical excision skills after instructor-directed training on low-fidelity bench models was similar to the training on high-fidelity bench models; and there was a more substantial increase in elliptical excision performances of students that trained on all simulators compared to the learning on didactic materials. PMID:24700937

Investigating Galactic Structure with COBE/DIRBE and Simulation

NASA Technical Reports Server (NTRS)

Cohen, Martin

1999-01-01

In this work I applied the current version of the SKY model of the point source sky to the interpretation of the diffuse all-sky emission observed by COBE/DIRBE (Cosmic Background Explorer Satellite/Diffuse Infrared Background Experiment). The goal was to refine the SKY model using the all-sky DIRBE maps of the Galaxy, in order that a search could be made for an isotropic cosmic background."Faint Source Model" [FSM] was constructed to remove Galactic fore ground stars from the ZSMA products. The FSM mimics SKY version 1 but it was inadequate to seek cosmic background emission because of the sizeable residual emission in the ZSMA products after this starlight subtraction. At this point I can only support that such models are currently inadequate to reveal a cosmic background. Even SKY5 yields the same disappointing result.

Low noise WDR ROIC for InGaAs SWIR image sensor

NASA Astrophysics Data System (ADS)

Ni, Yang

2017-11-01

Hybridized image sensors are actually the only solution for image sensing beyond the spectral response of silicon devices. By hybridization, we can combine the best sensing material and photo-detector design with high performance CMOS readout circuitry. In the infrared band, we are facing typically 2 configurations: high background situation and low background situation. The performance of high background sensors are conditioned mainly by the integration capacity in each pixel which is the case for mid-wave and long-wave infrared detectors. For low background situation, the detector's performance is mainly limited by the pixel's noise performance which is conditioned by dark signal and readout noise. In the case of reflection based imaging condition, the pixel's dynamic range is also an important parameter. This is the case for SWIR band imaging. We are particularly interested by InGaAs based SWIR image sensors.

Characterizing, modeling, and addressing gender disparities in introductory college physics

NASA Astrophysics Data System (ADS)

Kost-Smith, Lauren Elizabeth

2011-12-01

The underrepresentation and underperformance of females in physics has been well documented and has long concerned policy-makers, educators, and the physics community. In this thesis, we focus on gender disparities in the first- and second-semester introductory, calculus-based physics courses at the University of Colorado. Success in these courses is critical for future study and careers in physics (and other sciences). Using data gathered from roughly 10,000 undergraduate students, we identify and model gender differences in the introductory physics courses in three areas: student performance, retention, and psychological factors. We observe gender differences on several measures in the introductory physics courses: females are less likely to take a high school physics course than males and have lower standardized mathematics test scores; males outscore females on both pre- and post-course conceptual physics surveys and in-class exams; and males have more expert-like attitudes and beliefs about physics than females. These background differences of males and females account for 60% to 70% of the gender gap that we observe on a post-course survey of conceptual physics understanding. In analyzing underlying psychological factors of learning, we find that female students report lower self-confidence related to succeeding in the introductory courses (self-efficacy) and are less likely to report seeing themselves as a "physics person". Students' self-efficacy beliefs are significant predictors of their performance, even when measures of physics and mathematics background are controlled, and account for an additional 10% of the gender gap. Informed by results from these studies, we implemented and tested a psychological, self-affirmation intervention aimed at enhancing female students' performance in Physics 1. Self-affirmation reduced the gender gap in performance on both in-class exams and the post-course conceptual physics survey. Further, the benefit of the self-affirmation was strongest for females who endorsed the stereotype that men do better than women in physics. The findings of this thesis suggest that there are multiple factors that contribute to the underperformance of females in physics. Establishing this model of gender differences is a first step towards increasing females' participation and performance in physics, and can be used to guide future interventions to address the disparities.

Effects of Background Lighting Color and Movement Distance on Reaching Times Among Participants With Low Vision, Myopia, and Normal Vision.

PubMed

Chen, Chun-Fu; Huang, Kuo-Chen

2016-04-01

This study investigated the effects of target distance (30, 35, and 40 cm) and the color of background lighting (red, green, blue, and yellow) on the duration of movements made by participants with low vision, myopia, and normal vision while performing a reaching task; 48 students (21 women, 27 men; M age = 21.8 year, SD = 2.4) participated in the study. Participants reached for a target (a white LED light) whose vertical position varied randomly across trials, ranging in distance from 30 to 40 cm. Movement time was analyzed using a 3 (participant group) × [4 (color of background lighting) × 3 (movement distance)] mixed-design ANOVA model. Results indicated longer times for completing a reaching movement when: participants belonged to the low vision group; the target distance between the starting position and the target position was longer (40 cm); and the reaching movement occurred in the red-background lighting condition. These results are particularly relevant for situations in which a user is required to respond to a signal by reaching toward a button or an icon. © The Author(s) 2016.

Recovery of intrinsic fluorescence from single-point interstitial measurements for quantification of doxorubicin concentration

PubMed Central

Baran, Timothy M.; Foster, Thomas H.

2014-01-01

Background and Objective We developed a method for the recovery of intrinsic fluorescence from single-point measurements in highly scattering and absorbing samples without a priori knowledge of the sample optical properties. The goal of the study was to demonstrate accurate recovery of fluorophore concentration in samples with widely varying background optical properties, while simultaneously recovering the optical properties. Materials and Methods Tissue-simulating phantoms containing doxorubicin, MnTPPS, and Intralipid-20% were created, and fluorescence measurements were performed using a single isotropic probe. The resulting spectra were analyzed using a forward-adjoint fluorescence model in order to recover the fluorophore concentration and background optical properties. Results We demonstrated recovery of doxorubicin concentration with a mean error of 11.8%. The concentration of the background absorber was recovered with an average error of 23.2% and the scattering spectrum was recovered with a mean error of 19.8%. Conclusion This method will allow for the determination of local concentrations of fluorescent drugs, such as doxorubicin, from minimally invasive fluorescence measurements. This is particularly interesting in the context of transarterial chemoembolization (TACE) treatment of liver cancer. PMID:24037853

Parafoveal Target Detectability Reversal Predicted by Local Luminance and Contrast Gain Control

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Beard, Bettina L.; Null, Cynthia H. (Technical Monitor)

1996-01-01

This project is part of a program to develop image discrimination models for the prediction of the detectability of objects in a range of backgrounds. We wanted to see if the models could predict parafoveal object detection as well as they predict detection in foveal vision. We also wanted to make our simplified models more general by local computation of luminance and contrast gain control. A signal image (0.78 x 0.17 deg) was made by subtracting a simulated airport runway scene background image (2.7 deg square) from the same scene containing an obstructing aircraft. Signal visibility contrast thresholds were measured in a fully crossed factorial design with three factors: eccentricity (0 deg or 4 deg), background (uniform or runway scene background), and fixed-pattern white noise contrast (0%, 5%, or 10%). Three experienced observers responded to three repetitions of 60 2IFC trials in each condition and thresholds were estimated by maximum likelihood probit analysis. In the fovea the average detection contrast threshold was 4 dB lower for the runway background than for the uniform background, but in the parafovea, the average threshold was 6 dB higher for the runway background than for the uniform background. This interaction was similar across the different noise levels and for all three observers. A likely reason for the runway background giving a lower threshold in the fovea is the low luminance near the signal in that scene. In our model, the local luminance computation is controlled by a spatial spread parameter. When this parameter and a corresponding parameter for the spatial spread of contrast gain were increased for the parafoveal predictions, the model predicts the interaction of background with eccentricity.

Pupil Home Background Characteristics and Academic Performance in Senior Secondary Schools: A Case Study of Selected Secondary Schools in Kitwe District, Zambia

ERIC Educational Resources Information Center

Kakumbi, Zonic; Samuel, Elizabeth B.; Mulendema, Peter J.

2016-01-01

The purpose of this research was to investigate pupil background characteristics and academic performance in senior secondary schools in Kitwe district with a view of recommending on how to improve pupils' performance. The study was conducted in Kitwe district because in the past years pupils' performance in senior secondary schools has been…

The background in the experiment Gerda

NASA Astrophysics Data System (ADS)

Agostini, M.; Allardt, M.; Andreotti, E.; Bakalyarov, A. M.; Balata, M.; Barabanov, I.; Barnabé Heider, M.; Barros, N.; Baudis, L.; Bauer, C.; Becerici-Schmidt, N.; Bellotti, E.; Belogurov, S.; Belyaev, S. T.; Benato, G.; Bettini, A.; Bezrukov, L.; Bode, T.; Brudanin, V.; Brugnera, R.; Budjáš, D.; Caldwell, A.; Cattadori, C.; Chernogorov, A.; Cossavella, F.; Demidova, E. V.; Domula, A.; Egorov, V.; Falkenstein, R.; Ferella, A.; Freund, K.; Frodyma, N.; Gangapshev, A.; Garfagnini, A.; Gotti, C.; Grabmayr, P.; Gurentsov, V.; Gusev, K.; Guthikonda, K. K.; Hampel, W.; Hegai, A.; Heisel, M.; Hemmer, S.; Heusser, G.; Hofmann, W.; Hult, M.; Inzhechik, L. V.; Ioannucci, L.; Csáthy, J. Janicskó; Jochum, J.; Junker, M.; Kihm, T.; Kirpichnikov, I. V.; Kirsch, A.; Klimenko, A.; Knöpfle, K. T.; Kochetov, O.; Kornoukhov, V. N.; Kuzminov, V. V.; Laubenstein, M.; Lazzaro, A.; Lebedev, V. I.; Lehnert, B.; Liao, H. Y.; Lindner, M.; Lippi, I.; Liu, X.; Lubashevskiy, A.; Lubsandorzhiev, B.; Lutter, G.; Macolino, C.; Machado, A. A.; Majorovits, B.; Maneschg, W.; Nemchenok, I.; Nisi, S.; O'Shaughnessy, C.; Palioselitis, D.; Pandola, L.; Pelczar, K.; Pessina, G.; Pullia, A.; Riboldi, S.; Sada, C.; Salathe, M.; Schmitt, C.; Schreiner, J.; Schulz, O.; Schwingenheuer, B.; Schönert, S.; Shevchik, E.; Shirchenko, M.; Simgen, H.; Smolnikov, A.; Stanco, L.; Strecker, H.; Tarka, M.; Ur, C. A.; Vasenko, A. A.; Volynets, O.; von Sturm, K.; Wagner, V.; Walter, M.; Wegmann, A.; Wester, T.; Wojcik, M.; Yanovich, E.; Zavarise, P.; Zhitnikov, I.; Zhukov, S. V.; Zinatulina, D.; Zuber, K.; Zuzel, G.

2014-04-01

The GERmanium Detector Array ( Gerda) experiment at the Gran Sasso underground laboratory (LNGS) of INFN is searching for neutrinoless double beta () decay of Ge. The signature of the signal is a monoenergetic peak at 2039 keV, the value of the decay. To avoid bias in the signal search, the present analysis does not consider all those events, that fall in a 40 keV wide region centered around . The main parameters needed for the analysis are described. A background model was developed to describe the observed energy spectrum. The model contains several contributions, that are expected on the basis of material screening or that are established by the observation of characteristic structures in the energy spectrum. The model predicts a flat energy spectrum for the blinding window around with a background index ranging from 17.6 to 23.8 cts/(keV kg yr). A part of the data not considered before has been used to test if the predictions of the background model are consistent. The observed number of events in this energy region is consistent with the background model. The background at is dominated by close sources, mainly due to K, Bi, Th, Co and emitting isotopes from the Ra decay chain. The individual fractions depend on the assumed locations of the contaminants. It is shown, that after removal of the known peaks, the energy spectrum can be fitted in an energy range of 200 keV around with a constant background. This gives a background index consistent with the full model and uncertainties of the same size.

Model-based segmentation of abdominal aortic aneurysms in CTA images

NASA Astrophysics Data System (ADS)

de Bruijne, Marleen; van Ginneken, Bram; Niessen, Wiro J.; Loog, Marco; Viergever, Max A.

2003-05-01

Segmentation of thrombus in abdominal aortic aneurysms is complicated by regions of low boundary contrast and by the presence of many neighboring structures in close proximity to the aneurysm wall. We present an automated method that is similar to the well known Active Shape Models (ASM), combining a three-dimensional shape model with a one-dimensional boundary appearance model. Our contribution is twofold: we developed a non-parametric appearance modeling scheme that effectively deals with a highly varying background, and we propose a way of generalizing models of curvilinear structures from small training sets. In contrast with the conventional ASM approach, the new appearance model trains on both true and false examples of boundary profiles. The probability that a given image profile belongs to the boundary is obtained using k nearest neighbor (kNN) probability density estimation. The performance of this scheme is compared to that of original ASMs, which minimize the Mahalanobis distance to the average true profile in the training set. The generalizability of the shape model is improved by modeling the objects axis deformation independent of its cross-sectional deformation. A leave-one-out experiment was performed on 23 datasets. Segmentation using the kNN appearance model significantly outperformed the original ASM scheme; average volume errors were 5.9% and 46% respectively.

Final Report on Jobin Yvon Contained Inductively Coupled Plasma Emission Spectrometer

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

Pennebaker, F.M.

2003-03-17

A new Inductively Coupled Plasma -- Emission Spectrometer (ICP-ES) was recently purchased and installed in Lab B-147/151 at SRTC. The contained JY Model Ultima 170-C ICP-ES has been tested and compared to current ADS ICP-ES instrumentation. The testing has included both performance tests to evaluate instrumental ability, and the measurement of matrix standards commonly analyzed by ICP-ES at Savannah River. In developing operating procedures for this instrument, we have implemented the use of internal standards and off-peak background subtraction. Both of these techniques are recommended by EPA SW-846 ICP-ES methods and are common to current ICP-ES operations. Based on themore » testing and changes, the JY Model Ultima 170-C ICP-ES provides improved performance for elemental analysis of radioactive samples in the Analytical Development Section.« less

Examination performances of German and international medical students in the preclinical studying-term – A descriptive study

PubMed Central

Huhn, D.; Resch, F.; Duelli, R.; Möltner, A.; Huber, J.; Karimian Jazi, K.; Amr, A.; Eckart, W.; Herzog, W.; Nikendei, C.

2014-01-01

Introduction: Medical students with a migration background face several specific problems during their studies. International surveys show first indications that this group of students performs worse in written, oral or practical exams. However, so far, nothing is known about the performance of international students in written pre-clinical tests as well as in pre-clinical State Examinations for German-speaking countries. Method: A descriptive, retrospective analysis of the exam performances of medical students in the pre-clinical part of their studies was conducted at the Faculty of Medicine of Heidelberg in for the year 2012. Performance in written tests of the final exams in the second (N=276), third (N=292) and fourth semester (N=285) were compared between German students, students from EU countries and students from non-EU countries. Same comparison was drawn for the performance in the oral exam of the First State Examination in the period from 2009 - 2012 (N=1137). Results: German students performed significantly better than students with a non-EU migration background both in all written exams and in the oral State Examination (all p<.05). The performance of students with an EU migration background was significantly better than that of students with a non-EU background in the written exam at the end of the third and fourth semester (p<.05). Furthermore, German students completed the oral exam of the First State Examination significantly earlier than students with a non-EU migration background (<.01). Discussion: Due to its poorer performance in written and oral examinations and its simultaneously longer duration of study, the group of non-German medical students with a country of origin outside of the European Union has to be seen as a high-risk group among students with a migration background. For this group, there is an urgent need for early support to prepare for written and oral examinations. PMID:25228931

No Evidence for Extensions to the Standard Cosmological Model.

PubMed

Heavens, Alan; Fantaye, Yabebal; Sellentin, Elena; Eggers, Hans; Hosenie, Zafiirah; Kroon, Steve; Mootoovaloo, Arrykrishna

2017-09-08

We compute the Bayesian evidence for models considered in the main analysis of Planck cosmic microwave background data. By utilizing carefully defined nearest-neighbor distances in parameter space, we reuse the Monte Carlo Markov chains already produced for parameter inference to compute Bayes factors B for many different model-data set combinations. The standard 6-parameter flat cold dark matter model with a cosmological constant (ΛCDM) is favored over all other models considered, with curvature being mildly favored only when cosmic microwave background lensing is not included. Many alternative models are strongly disfavored by the data, including primordial correlated isocurvature models (lnB=-7.8), nonzero scalar-to-tensor ratio (lnB=-4.3), running of the spectral index (lnB=-4.7), curvature (lnB=-3.6), nonstandard numbers of neutrinos (lnB=-3.1), nonstandard neutrino masses (lnB=-3.2), nonstandard lensing potential (lnB=-4.6), evolving dark energy (lnB=-3.2), sterile neutrinos (lnB=-6.9), and extra sterile neutrinos with a nonzero scalar-to-tensor ratio (lnB=-10.8). Other models are less strongly disfavored with respect to flat ΛCDM. As with all analyses based on Bayesian evidence, the final numbers depend on the widths of the parameter priors. We adopt the priors used in the Planck analysis, while performing a prior sensitivity analysis. Our quantitative conclusion is that extensions beyond the standard cosmological model are disfavored by Planck data. Only when newer Hubble constant measurements are included does ΛCDM become disfavored, and only mildly, compared with a dynamical dark energy model (lnB∼+2).

No Evidence for Extensions to the Standard Cosmological Model

NASA Astrophysics Data System (ADS)

Heavens, Alan; Fantaye, Yabebal; Sellentin, Elena; Eggers, Hans; Hosenie, Zafiirah; Kroon, Steve; Mootoovaloo, Arrykrishna

2017-09-01

We compute the Bayesian evidence for models considered in the main analysis of Planck cosmic microwave background data. By utilizing carefully defined nearest-neighbor distances in parameter space, we reuse the Monte Carlo Markov chains already produced for parameter inference to compute Bayes factors B for many different model-data set combinations. The standard 6-parameter flat cold dark matter model with a cosmological constant (Λ CDM ) is favored over all other models considered, with curvature being mildly favored only when cosmic microwave background lensing is not included. Many alternative models are strongly disfavored by the data, including primordial correlated isocurvature models (ln B =-7.8 ), nonzero scalar-to-tensor ratio (ln B =-4.3 ), running of the spectral index (ln B =-4.7 ), curvature (ln B =-3.6 ), nonstandard numbers of neutrinos (ln B =-3.1 ), nonstandard neutrino masses (ln B =-3.2 ), nonstandard lensing potential (ln B =-4.6 ), evolving dark energy (ln B =-3.2 ), sterile neutrinos (ln B =-6.9 ), and extra sterile neutrinos with a nonzero scalar-to-tensor ratio (ln B =-10.8 ). Other models are less strongly disfavored with respect to flat Λ CDM . As with all analyses based on Bayesian evidence, the final numbers depend on the widths of the parameter priors. We adopt the priors used in the Planck analysis, while performing a prior sensitivity analysis. Our quantitative conclusion is that extensions beyond the standard cosmological model are disfavored by Planck data. Only when newer Hubble constant measurements are included does Λ CDM become disfavored, and only mildly, compared with a dynamical dark energy model (ln B ˜+2 ).

Mean-variance model for portfolio optimization with background risk based on uncertainty theory

NASA Astrophysics Data System (ADS)

Zhai, Jia; Bai, Manying

2018-04-01

The aim of this paper is to develop a mean-variance model for portfolio optimization considering the background risk, liquidity and transaction cost based on uncertainty theory. In portfolio selection problem, returns of securities and assets liquidity are assumed as uncertain variables because of incidents or lacking of historical data, which are common in economic and social environment. We provide crisp forms of the model and a hybrid intelligent algorithm to solve it. Under a mean-variance framework, we analyze the portfolio frontier characteristic considering independently additive background risk. In addition, we discuss some effects of background risk and liquidity constraint on the portfolio selection. Finally, we demonstrate the proposed models by numerical simulations.