Super-resolution imaging of multiple cells by optimized flat-field epi-illumination

NASA Astrophysics Data System (ADS)

Douglass, Kyle M.; Sieben, Christian; Archetti, Anna; Lambert, Ambroise; Manley, Suliana

2016-11-01

Biological processes are inherently multi-scale, and supramolecular complexes at the nanoscale determine changes at the cellular scale and beyond. Single-molecule localization microscopy (SMLM) techniques have been established as important tools for studying cellular features with resolutions of the order of around 10 nm. However, in their current form these modalities are limited by a highly constrained field of view (FOV) and field-dependent image resolution. Here, we develop a low-cost microlens array (MLA)-based epi-illumination system—flat illumination for field-independent imaging (FIFI)—that can efficiently and homogeneously perform simultaneous imaging of multiple cells with nanoscale resolution. The optical principle of FIFI, which is an extension of the Köhler integrator, is further elucidated and modelled with a new, free simulation package. We demonstrate FIFI's capabilities by imaging multiple COS-7 and bacteria cells in 100 × 100 μm2 SMLM images—more than quadrupling the size of a typical FOV and producing near-gigapixel-sized images of uniformly high quality.

A light-trapping strategy for nanocrystalline silicon thin-film solar cells using three-dimensionally assembled nanoparticle structures.

PubMed

Ha, Kyungyeon; Jang, Eunseok; Jang, Segeun; Lee, Jong-Kwon; Jang, Min Seok; Choi, Hoseop; Cho, Jun-Sik; Choi, Mansoo

2016-02-05

We report three-dimensionally assembled nanoparticle structures inducing multiple plasmon resonances for broadband light harvesting in nanocrystalline silicon (nc-Si:H) thin-film solar cells. A three-dimensional multiscale (3DM) assembly of nanoparticles generated using a multi-pin spark discharge method has been accomplished over a large area under atmospheric conditions via ion-assisted aerosol lithography. The multiscale features of the sophisticated 3DM structures exhibit surface plasmon resonances at multiple frequencies, which increase light scattering and absorption efficiency over a wide spectral range from 350-1100 nm. The multiple plasmon resonances, together with the antireflection functionality arising from the conformally deposited top surface of the 3D solar cell, lead to a 22% and an 11% improvement in power conversion efficiency of the nc-Si:H thin-film solar cells compared to flat cells and cells employing nanoparticle clusters, respectively. Finite-difference time-domain simulations were also carried out to confirm that the improved device performance mainly originates from the multiple plasmon resonances generated from three-dimensionally assembled nanoparticle structures.

Demonstration of Wavelet Techniques in the Spectral Analysis of Bypass Transition Data

NASA Technical Reports Server (NTRS)

Lewalle, Jacques; Ashpis, David E.; Sohn, Ki-Hyeon

1997-01-01

A number of wavelet-based techniques for the analysis of experimental data are developed and illustrated. A multiscale analysis based on the Mexican hat wavelet is demonstrated as a tool for acquiring physical and quantitative information not obtainable by standard signal analysis methods. Experimental data for the analysis came from simultaneous hot-wire velocity traces in a bypass transition of the boundary layer on a heated flat plate. A pair of traces (two components of velocity) at one location was excerpted. A number of ensemble and conditional statistics related to dominant time scales for energy and momentum transport were calculated. The analysis revealed a lack of energy-dominant time scales inside turbulent spots but identified transport-dominant scales inside spots that account for the largest part of the Reynolds stress. Momentum transport was much more intermittent than were energetic fluctuations. This work is the first step in a continuing study of the spatial evolution of these scale-related statistics, the goal being to apply the multiscale analysis results to improve the modeling of transitional and turbulent industrial flows.

Extended AIC model based on high order moments and its application in the financial market

NASA Astrophysics Data System (ADS)

Mao, Xuegeng; Shang, Pengjian

2018-07-01

In this paper, an extended method of traditional Akaike Information Criteria(AIC) is proposed to detect the volatility of time series by combining it with higher order moments, such as skewness and kurtosis. Since measures considering higher order moments are powerful in many aspects, the properties of asymmetry and flatness can be observed. Furthermore, in order to reduce the effect of noise and other incoherent features, we combine the extended AIC algorithm with multiscale wavelet analysis, in which the newly extended AIC algorithm is applied to wavelet coefficients at several scales and the time series are reconstructed by wavelet transform. After that, we create AIC planes to derive the relationship among AIC values using variance, skewness and kurtosis respectively. When we test this technique on the financial market, the aim is to analyze the trend and volatility of the closing price of stock indices and classify them. And we also adapt multiscale analysis to measure complexity of time series over a range of scales. Empirical results show that the singularity of time series in stock market can be detected via extended AIC algorithm.

Topographical modulation of macrophage phenotype by shrink-film multi-scale wrinkles.

PubMed

Wang, Tingting; Luu, Thuy U; Chen, Aaron; Khine, Michelle; Liu, Wendy F

2016-06-24

The host immune response to foreign materials is a major hurdle for implanted medical devices. To control this response, modulation of macrophage behavior has emerged as a promising strategy, given their prominent role in inflammation and wound healing. Towards this goal, we explore the effect of biomimetic multi-scale wrinkles on macrophage adhesion and expression of phenotype markers. We find that macrophages elongate along the direction of the uniaxial wrinkles made from shape memory polymers, and express more arginase-1 and IL-10, and less TNF-α, suggesting polarization towards an alternatively activated, anti-inflammatory phenotype. Materials were further implanted in the subcutaneous space of mice and tissue surrounding the material evaluated by histology and immunohistochemistry. We found that material surface topography altered the distribution of collagen deposition in the adjacent tissue, with denser collagen tissue observed near flat materials when compared to wrinkled materials. Furthermore, cells surrounding wrinkled materials exhibited higher arginase-1 expression. Together these data suggest that wrinkled material surfaces promote macrophage alternative activation, and may influence the foreign body response to implants.

Multi-scale modeling of Puget Sound using an unstructured-grid coastal ocean model: from tide flats to estuaries and coastal waters

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

Yang, Zhaoqing; Khangaonkar, Tarang

2010-11-19

Water circulation in Puget Sound, a large complex estuary system in the Pacific Northwest coastal ocean of the United States, is governed by multiple spatially and temporally varying forcings from tides, atmosphere (wind, heating/cooling, precipitation/evaporation, pressure), and river inflows. In addition, the hydrodynamic response is affected strongly by geomorphic features, such as fjord-like bathymetry and complex shoreline features, resulting in many distinguishing characteristics in its main and sub-basins. To better understand the details of circulation features in Puget Sound and to assist with proposed nearshore restoration actions for improving water quality and the ecological health of Puget Sound, a high-resolutionmore » (around 50 m in estuaries and tide flats) hydrodynamic model for the entire Puget Sound was needed. Here, a threedimensional circulation model of Puget Sound using an unstructured-grid finite volume coastal ocean model is presented. The model was constructed with sufficient resolution in the nearshore region to address the complex coastline, multi-tidal channels, and tide flats. Model open boundaries were extended to the entrance of the Strait of Juan de Fuca and the northern end of the Strait of Georgia to account for the influences of ocean water intrusion from the Strait of Juan de Fuca and the Fraser River plume from the Strait of Georgia, respectively. Comparisons of model results, observed data, and associated error statistics for tidal elevation, velocity, temperature, and salinity indicate that the model is capable of simulating the general circulation patterns on the scale of a large estuarine system as well as detailed hydrodynamics in the nearshore tide flats. Tidal characteristics, temperature/salinity stratification, mean circulation, and river plumes in estuaries with tide flats are discussed.« less

Mixing in 3D Sparse Multi-Scale Grid Generated Turbulence

NASA Astrophysics Data System (ADS)

Usama, Syed; Kopec, Jacek; Tellez, Jackson; Kwiatkowski, Kamil; Redondo, Jose; Malik, Nadeem

2017-04-01

Flat 2D fractal grids are known to alter turbulence characteristics downstream of the grid as compared to the regular grids with the same blockage ratio and the same mass inflow rates [1]. This has excited interest in the turbulence community for possible exploitation for enhanced mixing and related applications. Recently, a new 3D multi-scale grid design has been proposed [2] such that each generation of length scale of turbulence grid elements is held in its own frame, the overall effect is a 3D co-planar arrangement of grid elements. This produces a 'sparse' grid system whereby each generation of grid elements produces a turbulent wake pattern that interacts with the other wake patterns downstream. A critical motivation here is that the effective blockage ratio in the 3D Sparse Grid Turbulence (3DSGT) design is significantly lower than in the flat 2D counterpart - typically the blockage ratio could be reduced from say 20% in 2D down to 4% in the 3DSGT. If this idea can be realized in practice, it could potentially greatly enhance the efficiency of turbulent mixing and transfer processes clearly having many possible applications. Work has begun on the 3DSGT experimentally using Surface Flow Image Velocimetry (SFIV) [3] at the European facility in the Max Planck Institute for Dynamics and Self-Organization located in Gottingen, Germany and also at the Technical University of Catalonia (UPC) in Spain, and numerically using Direct Numerical Simulation (DNS) at King Fahd University of Petroleum & Minerals (KFUPM) in Saudi Arabia and in University of Warsaw in Poland. DNS is the most useful method to compare the experimental results with, and we are studying different types of codes such as Imcompact3d, and OpenFoam. Many variables will eventually be investigated for optimal mixing conditions. For example, the number of scale generations, the spacing between frames, the size ratio of grid elements, inflow conditions, etc. We will report upon the first set of findings from the 3DSGT by the time of the conference. {Acknowledgements}: This work has been supported partly by the EuHIT grant, 'Turbulence Generated by Sparse 3D Multi-Scale Grid (M3SG)', 2017. {References} [1] S. Laizet, J. C. Vassilicos. DNS of Fractal-Generated Turbulence. Flow Turbulence Combust 87:673705, (2011). [2] N. A. Malik. Sparse 3D Multi-Scale Grid Turbulence Generator. USPTO Application no. 14/710,531, Patent Pending, (2015). [3] J. Tellez, M. Gomez, B. Russo, J.M. Redondo. Surface Flow Image Velocimetry (SFIV) for hydraulics applications. 18th Int. Symposium on the Application of Laser Imaging Techniques in Fluid Mechanics, Lisbon, Portugal (2016).

Multiscale properties of weighted total variation flow with applications to denoising and registration.

PubMed

Athavale, Prashant; Xu, Robert; Radau, Perry; Nachman, Adrian; Wright, Graham A

2015-07-01

Images consist of structures of varying scales: large scale structures such as flat regions, and small scale structures such as noise, textures, and rapidly oscillatory patterns. In the hierarchical (BV, L(2)) image decomposition, Tadmor, et al. (2004) start with extracting coarse scale structures from a given image, and successively extract finer structures from the residuals in each step of the iterative decomposition. We propose to begin instead by extracting the finest structures from the given image and then proceed to extract increasingly coarser structures. In most images, noise could be considered as a fine scale structure. Thus, starting the image decomposition with finer scales, rather than large scales, leads to fast denoising. We note that our approach turns out to be equivalent to the nonstationary regularization in Scherzer and Weickert (2000). The continuous limit of this procedure leads to a time-scaled version of total variation flow. Motivated by specific clinical applications, we introduce an image depending weight in the regularization functional, and study the corresponding weighted TV flow. We show that the edge-preserving property of the multiscale representation of an input image obtained with the weighted TV flow can be enhanced and localized by appropriate choice of the weight. We use this in developing an efficient and edge-preserving denoising algorithm with control on speed and localization properties. We examine analytical properties of the weighted TV flow that give precise information about the denoising speed and the rate of change of energy of the images. An additional contribution of the paper is to use the images obtained at different scales for robust multiscale registration. We show that the inherently multiscale nature of the weighted TV flow improved performance for registration of noisy cardiac MRI images, compared to other methods such as bilateral or Gaussian filtering. A clinical application of the multiscale registration algorithm is also demonstrated for aligning viability assessment magnetic resonance (MR) images from 8 patients with previous myocardial infarctions. Copyright © 2015. Published by Elsevier B.V.

Gradient design for liquid chromatography using multi-scale optimization.

PubMed

López-Ureña, S; Torres-Lapasió, J R; Donat, R; García-Alvarez-Coque, M C

2018-01-26

In reversed phase-liquid chromatography, the usual solution to the "general elution problem" is the application of gradient elution with programmed changes of organic solvent (or other properties). A correct quantification of chromatographic peaks in liquid chromatography requires well resolved signals in a proper analysis time. When the complexity of the sample is high, the gradient program should be accommodated to the local resolution needs of each analyte. This makes the optimization of such situations rather troublesome, since enhancing the resolution for a given analyte may imply a collateral worsening of the resolution of other analytes. The aim of this work is to design multi-linear gradients that maximize the resolution, while fulfilling some restrictions: all peaks should be eluted before a given maximal time, the gradient should be flat or increasing, and sudden changes close to eluting peaks are penalized. Consequently, an equilibrated baseline resolution for all compounds is sought. This goal is achieved by splitting the optimization problem in a multi-scale framework. In each scale κ, an optimization problem is solved with N κ  ≈ 2 κ variables that are used to build the gradients. The N κ variables define cubic splines written in terms of a B-spline basis. This allows expressing gradients as polygonals of M points approximating the splines. The cubic splines are built using subdivision schemes, a technique of fast generation of smooth curves, compatible with the multi-scale framework. Owing to the nature of the problem and the presence of multiple local maxima, the algorithm used in the optimization problem of each scale κ should be "global", such as the pattern-search algorithm. The multi-scale optimization approach is successfully applied to find the best multi-linear gradient for resolving a mixture of amino acid derivatives. Copyright © 2017 Elsevier B.V. All rights reserved.

High resolution P-wave velocity structure beneath Northeastern Tibet from multiscale seismic tomography

NASA Astrophysics Data System (ADS)

Guo, B.; Gao, X.; Chen, J.; Liu, Q.; Li, S.

2016-12-01

The continuing collision of the northward advancing Indian continent with the Eurasia results in the high elevations and thickened Tibetan Plateau. Numerous geologic and geophysical studies engaged in the mechanics of the Tibetan Plateau deformation and uplift. Many seismic experiments were deployed in south and central Tibet, such as INDEPTH and Hi-climb, but very few in northeastern Tibet. Between 2013 and 2015, The China Seismic Array-experiment operated 670 broadband seismic stations with an average station spacing of 35km. This seismic array located in northeastern Tibet and covered the Qilian Mountains, Qaidam Basin, and part of Songpan-Ganzi, Gobi-Alashan, Yangzi, and Ordos. A new multiscale seismic traveltime tomography technique with sparsity constrains were used to map the upper mantle P-wave velocity structure beneath northeastern Tibet. The seismic tomography algorithm employs sparsity constrains on the wavelet representation velocity model via the L1-norm regularization. This algorithm can efficiently deal with the uneven-sampled volume, and give multiscale images of the model. Our preliminary results can be summarized as follows: 1) in the upper mantle down to 200km, significate low-velocity anomalies exist beneath the northeastern Tibet, and slight high-velocity anomalies beneath the Qaidam basin; 2) under Gobi-Alashan, Yangzi, and Ordos, high-velocity anomalies appear to extend to a depth of 250km, this high-velocity may correspond to the lithosphere; 3) there exist relative high-velocity anomalies at depth of 250km-350km underneath north Tibet, which suggests lithospheric delamination; 4) the strong velocity contrast between north Tibet and Yangzi, Gabi-Alashan is visible down to 200km, which implies the north Tibet boundary.

A Multiscale pipeline for the search of string-induced CMB anisotropies

NASA Astrophysics Data System (ADS)

Vafaei Sadr, A.; Movahed, S. M. S.; Farhang, M.; Ringeval, C.; Bouchet, F. R.

2018-03-01

We propose a multiscale edge-detection algorithm to search for the Gott-Kaiser-Stebbins imprints of a cosmic string (CS) network on the cosmic microwave background (CMB) anisotropies. Curvelet decomposition and extended Canny algorithm are used to enhance the string detectability. Various statistical tools are then applied to quantify the deviation of CMB maps having a CS contribution with respect to pure Gaussian anisotropies of inflationary origin. These statistical measures include the one-point probability density function, the weighted two-point correlation function (TPCF) of the anisotropies, the unweighted TPCF of the peaks and of the up-crossing map, as well as their cross-correlation. We use this algorithm on a hundred of simulated Nambu-Goto CMB flat sky maps, covering approximately 10 per cent of the sky, and for different string tensions Gμ. On noiseless sky maps with an angular resolution of 0.9 arcmin, we show that our pipeline detects CSs with Gμ as low as Gμ ≳ 4.3 × 10-10. At the same resolution, but with a noise level typical to a CMB-S4 phase II experiment, the detection threshold would be to Gμ ≳ 1.2 × 10-7.

Structure of sheared and rotating turbulence: Multiscale statistics of Lagrangian and Eulerian accelerations and passive scalar dynamics.

PubMed

Jacobitz, Frank G; Schneider, Kai; Bos, Wouter J T; Farge, Marie

2016-01-01

The acceleration statistics of sheared and rotating homogeneous turbulence are studied using direct numerical simulation results. The statistical properties of Lagrangian and Eulerian accelerations are considered together with the influence of the rotation to shear ratio, as well as the scale dependence of their statistics. The probability density functions (pdfs) of both Lagrangian and Eulerian accelerations show a strong and similar dependence on the rotation to shear ratio. The variance and flatness of both accelerations are analyzed and the extreme values of the Eulerian acceleration are observed to be above those of the Lagrangian acceleration. For strong rotation it is observed that flatness yields values close to three, corresponding to Gaussian-like behavior, and for moderate and vanishing rotation the flatness increases. Furthermore, the Lagrangian and Eulerian accelerations are shown to be strongly correlated for strong rotation due to a reduced nonlinear term in this case. A wavelet-based scale-dependent analysis shows that the flatness of both Eulerian and Lagrangian accelerations increases as scale decreases, which provides evidence for intermittent behavior. For strong rotation the Eulerian acceleration is even more intermittent than the Lagrangian acceleration, while the opposite result is obtained for moderate rotation. Moreover, the dynamics of a passive scalar with gradient production in the direction of the mean velocity gradient is analyzed and the influence of the rotation to shear ratio is studied. Concerning the concentration of a passive scalar spread by the flow, the pdf of its Eulerian time rate of change presents higher extreme values than those of its Lagrangian time rate of change. This suggests that the Eulerian time rate of change of scalar concentration is mainly due to advection, while its Lagrangian counterpart is only due to gradient production and viscous dissipation.

Satisfaction with facial profile aesthetics: are norms overrated?

PubMed

Manevska, I; Pavlic, A; Katic, V; Trinajstic Zrinski, M; Drevensek, M; Spalj, S

2018-01-01

This study aimed to explore to what extent adults perceive deviations from the norm of a balanced profile with normal occlusion as reducing satisfaction with facial appearance and having a psychosocial impact. This cross-sectional study included 225 Caucasian subjects (64% women) aged 18-42 years. Their facial profiles were analyzed photogrammetrically and they were classified into three categories: within, below, or above the standard range for the Croatian population with a normal occlusion. Psychosocial issues were assessed by self-reported satisfaction with facial appearance and domains from the Orthognathic Quality of Life Questionnaire: social aspects of dentofacial aesthetics (SA), facial aesthetics concern (FA), and awareness of dentofacial aesthetics (AW). Men with a concave profile were less satisfied with their faces than those with a flat or convex profile (P<0.05). A reduced upper lip height in men resulted in a lower level of satisfaction and increased FA score, when compared to men with a normal or increased upper lip height (P<0.05). In women, a reduced middle third of the face increased AW (P=0.045). Deviations from a well-balanced facial profile, as well as the morphology of the nose and lip, do not increase psychosocial issues to a great extent. The range of acceptable facial characteristics is evidently much broader than the norms. Copyright © 2017 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Investigation of the spinfoam path integral with quantum cuboid intertwiners

NASA Astrophysics Data System (ADS)

Bahr, Benjamin; Steinhaus, Sebastian

2016-05-01

In this work, we investigate the 4d path integral for Euclidean quantum gravity on a hypercubic lattice, as given by the spinfoam model by Engle, Pereira, Rovelli, Livine, Freidel and Krasnov. To tackle the problem, we restrict to a set of quantum geometries that reflects the large amount of lattice symmetries. In particular, the sum over intertwiners is restricted to quantum cuboids, i.e. coherent intertwiners which describe a cuboidal geometry in the large-j limit. Using asymptotic expressions for the vertex amplitude, we find several interesting properties of the state sum. First of all, the value of coupling constants in the amplitude functions determines whether geometric or nongeometric configurations dominate the path integral. Secondly, there is a critical value of the coupling constant α , which separates two phases. In both phases, the diffeomorphism symmetry appears to be broken. In one, the dominant contribution comes from highly irregular, in the other from highly regular configurations, both describing flat Euclidean space with small quantum fluctuations around them, viewed in different coordinate systems. On the critical point diffeomorphism symmetry is nearly restored, however. Thirdly, we use the state sum to compute the physical norm of kinematical states, i.e. their norm in the physical Hilbert space. We find that states which describe boundary geometry with high torsion have an exponentially suppressed physical norm. We argue that this allows one to exclude them from the state sum in calculations.

Dwell time algorithm based on the optimization theory for magnetorheological finishing

NASA Astrophysics Data System (ADS)

Zhang, Yunfei; Wang, Yang; Wang, Yajun; He, Jianguo; Ji, Fang; Huang, Wen

2010-10-01

Magnetorheological finishing (MRF) is an advanced polishing technique capable of rapidly converging to the required surface figure. This process can deterministically control the amount of the material removed by varying a time to dwell at each particular position on the workpiece surface. The dwell time algorithm is one of the most important key techniques of the MRF. A dwell time algorithm based on the1 matrix equation and optimization theory was presented in this paper. The conventional mathematical model of the dwell time was transferred to a matrix equation containing initial surface error, removal function and dwell time function. The dwell time to be calculated was just the solution to the large, sparse matrix equation. A new mathematical model of the dwell time based on the optimization theory was established, which aims to minimize the 2-norm or ∞-norm of the residual surface error. The solution meets almost all the requirements of precise computer numerical control (CNC) without any need for extra data processing, because this optimization model has taken some polishing condition as the constraints. Practical approaches to finding a minimal least-squares solution and a minimal maximum solution are also discussed in this paper. Simulations have shown that the proposed algorithm is numerically robust and reliable. With this algorithm an experiment has been performed on the MRF machine developed by ourselves. After 4.7 minutes' polishing, the figure error of a flat workpiece with a 50 mm diameter is improved by PV from 0.191λ(λ = 632.8 nm) to 0.087λ and RMS 0.041λ to 0.010λ. This algorithm can be constructed to polish workpieces of all shapes including flats, spheres, aspheres, and prisms, and it is capable of improving the polishing figures dramatically.

Buoyant Turbulence Kinetic Energy (TKE) Production in Katabatic Flow Despite Stable Thermal Stratification

NASA Astrophysics Data System (ADS)

Oldroyd, H. J.; Pardyjak, E.; Higgins, C. W.; Parlange, M. B.

2015-12-01

As micrometeorological research shifts to increasingly non-idealized environments, the lens through which we view classical atmospheric boundary layer theory must also shift to accommodate unfamiliar behavior. We present observations of katabatic flow over a steep (35.5 degree), alpine slope and draw comparisons with classical theory for nocturnal boundary layers (NBL) over flat terrain to delineate key physical differences and similarities. In both cases, the NBL is characterized by a strong, terrain-aligned thermal stratification. Over flat terrain, this temperature inversion tends to stabilize perturbations and suppresses vertical motions. Hence, the buoyancy term in the TKE budget equation acts as a sink. In contrast, the steep-slope katabatic flow regime is characterized by buoyant TKE production despite NBL thermal stratification. This buoyant TKE production occurs because streamwise (upslope) heat fluxes, which are typically treated as unimportant over flat terrain, contribute to the total vertical buoyancy flux since the gravity vector is not terrain-normal. Due to a relatively small number of observations over steep terrain, the turbulence structure of such flows and the implications of buoyant TKE production in the NBL have gone largely unexplored. As an important consequence of this characteristic, we show that conventional stability characterizations require careful coordinate system alignment and interpretation for katabatic flows. The streamwise heat fluxes play an integral role in characterizing stability and turbulent transport, more broadly, in katabatic flows. Therefore, multi-scale statistics and budget analyses describing physical interactions between turbulent fluxes at various scales are presented to interpret similarities and differences between the observations and classical theories regarding streamwise heat fluxes.

Brain abnormality segmentation based on l1-norm minimization

NASA Astrophysics Data System (ADS)

Zeng, Ke; Erus, Guray; Tanwar, Manoj; Davatzikos, Christos

2014-03-01

We present a method that uses sparse representations to model the inter-individual variability of healthy anatomy from a limited number of normal medical images. Abnormalities in MR images are then defined as deviations from the normal variation. More precisely, we model an abnormal (pathological) signal y as the superposition of a normal part ~y that can be sparsely represented under an example-based dictionary, and an abnormal part r. Motivated by a dense error correction scheme recently proposed for sparse signal recovery, we use l1- norm minimization to separate ~y and r. We extend the existing framework, which was mainly used on robust face recognition in a discriminative setting, to address challenges of brain image analysis, particularly the high dimensionality and low sample size problem. The dictionary is constructed from local image patches extracted from training images aligned using smooth transformations, together with minor perturbations of those patches. A multi-scale sliding-window scheme is applied to capture anatomical variations ranging from fine and localized to coarser and more global. The statistical significance of the abnormality term r is obtained by comparison to its empirical distribution through cross-validation, and is used to assign an abnormality score to each voxel. In our validation experiments the method is applied for segmenting abnormalities on 2-D slices of FLAIR images, and we obtain segmentation results consistent with the expert-defined masks.

Almost all quantum channels are equidistant

NASA Astrophysics Data System (ADS)

Nechita, Ion; Puchała, Zbigniew; Pawela, Łukasz; Życzkowski, Karol

2018-05-01

In this work, we analyze properties of generic quantum channels in the case of large system size. We use random matrix theory and free probability to show that the distance between two independent random channels converges to a constant value as the dimension of the system grows larger. As a measure of the distance we use the diamond norm. In the case of a flat Hilbert-Schmidt distribution on quantum channels, we obtain that the distance converges to 1/2 +2/π , giving also an estimate for the maximum success probability for distinguishing the channels. We also consider the problem of distinguishing two random unitary rotations.

A multiscale analysis of coral reef topographic complexity using lidar-derived bathymetry

USGS Publications Warehouse

Zawada, D.G.; Brock, J.C.

2009-01-01

Coral reefs represent one of the most irregular substrates in the marine environment. This roughness or topographic complexity is an important structural characteristic of reef habitats that affects a number of ecological and environmental attributes, including species diversity and water circulation. Little is known about the range of topographic complexity exhibited within a reef or between different reef systems. The objective of this study was to quantify topographic complexity for a 5-km x 5-km reefscape along the northern Florida Keys reef tract, over spatial scales ranging from meters to hundreds of meters. The underlying dataset was a 1-m spatial resolution, digital elevation model constructed from lidar measurements. Topographic complexity was quantified using a fractal algorithm, which provided a multi-scale characterization of reef roughness. The computed fractal dimensions (D) are a measure of substrate irregularity and are bounded between values of 2 and 3. Spatial patterns in D were positively correlated with known reef zonation in the area. Landward regions of the study site contain relatively smooth (D ??? 2.35) flat-topped patch reefs, which give way to rougher (D ??? 2.5), deep, knoll-shaped patch reefs. The seaward boundary contains a mixture of substrate features, including discontinuous shelf-edge reefs, and exhibits a corresponding range of roughness values (2.28 ??? D ??? 2.61). ?? 2009 Coastal Education and Research Foundation.

The Drivers of the CH4 Seasonal Cycle in the Arctic and What Long-Term Observations of CH4 Imply About Trends in Arctic CH4 Fluxes

NASA Astrophysics Data System (ADS)

Sweeney, C.; Karion, A.; Bruhwiler, L.; Miller, J. B.; Wofsy, S. C.; Miller, C. E.; Chang, R. Y.; Dlugokencky, E. J.; Daube, B.; Pittman, J. V.; Dinardo, S. J.

2012-12-01

The large seasonal change in the atmospheric column for CH4 in the Arctic is driven by two dominant processes: transport of CH4 from low latitudes and surface emissions throughout the Arctic region. The NOAA ESRL Carbon Cycle Group Aircraft Program along with the NASA funded Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) have initiated an effort to better understand the factors controlling the seasonal changes in the mole fraction of CH4 in the Arctic with a multi-scale aircraft observing network in Alaska. The backbone of this network is multi-species flask sampling from 500 to 8000 masl that has been conducted every two weeks for the last 10 years over Poker Flat, AK. In addition regular profiles at the interior Alaska site at Poker Flat, NOAA has teamed up with the United States Coast Guard to make profiling flights with continuous observations of CO2, CO, CH4 and Ozone between Kodiak and Barrow every 2 weeks. More recently, CARVE has significantly added to this observational network with targeted flights focused on exploring the variability of CO2, CH4 and CO in the boundary layer both in the interior and the North Slope regions of Alaska. Taken together with the profiling of HIAPER Pole-to-Pole Observations (HIPPO), ground sites at Barrow and a new CARVE interior Alaska surface site just north of Fairbanks, AK, we now have the ability to investigate the full evolution of the seasonal cycle in the Arctic using both the multi-scale sampling offered by the different aircraft platforms as well as the multi-species sampling offered by in-situ and flask sampling. The flasks also provide a valuable tie-point between different platforms so that spatial and temporal gradients can be properly interpreted. In the context of the seasonal cycle observed by the aircraft platforms we will look at long term ground observations over the last 20 years to assess changes in Arctic CH4 emissions which have occurred as a result of 0.6C/decade changes in mean surface temperatures.

An Investigation of Spontaneous Lorentz Violation and Cosmic Inflation

NASA Astrophysics Data System (ADS)

Tam, Heywood

2010-12-01

In this thesis we re-examine two established ideas in theoretical physics: Lorentz invariance and cosmic inflation. In the first four chapters, we (i) propose a way to hide large extra dimensions by coupling standard model fields with Lorentz-violating tensor fields with expectation values along the extra dimensions; (ii) examine the stability of theories in which Lorentz invariance is spontaneously broken by fixed-norm 'aether' fields; (iii) investigate the phenomenological properties of the sigma-model aether theory; and (iv) explore the implications of an alternative theory of gravity in which the graviton arises from the Goldstone modes of a two-index symmetric aether field. In the final chapter, we examine the horizon and flatness problems using the canonical measure (developed by Gibbons, Hawking, and Stewart) on the space of solutions to Einstein's equations. We find that the flatness problem does not exist, while the homogeneity of our universe does represent a substantial fine-tuning. Based on the assumption of unitary evolution (Liouville's theorem), we further dispute the widely accepted claim that inflation makes our universe more natural.

A Multi-Scale Approach to Investigating the Red-Crowned Crane–Habitat Relationship in the Yellow River Delta Nature Reserve, China: Implications for Conservation

PubMed Central

Cao, Mingchang; Xu, Haigen; Le, Zhifang; Zhu, Mingchang; Cao, Yun

2015-01-01

The red-crowned crane (Grus japonensis (Statius Müller, 1776)) is a rare and endangered species that lives in wetlands. In this study, we used variance partitioning and hierarchical partitioning methods to explore the red-crowned crane–habitat relationship at multiple scales in the Yellow River Delta Nature Reserve (YRDNR). In addition, we used habitat modeling to identify the cranes’ habitat distribution pattern and protection gaps in the YRDNR. The variance partitioning results showed that habitat variables accounted for a substantially larger total and pure variation in crane occupancy than the variation accounted for by spatial variables at the first level. Landscape factors had the largest total (45.13%) and independent effects (17.42%) at the second level. The hierarchical partitioning results showed that the percentage of seepweed tidal flats were the main limiting factor at the landscape scale. Vegetation coverage contributed the greatest independent explanatory power at the plot scale, and patch area was the predominant factor at the patch scale. Our habitat modeling results showed that crane suitable habitat covered more than 26% of the reserve area and that there remained a large protection gap with an area of 20,455 ha, which accounted for 69.51% of the total suitable habitat of cranes. Our study indicates that landscape and plot factors make a relatively large contribution to crane occupancy and that the focus of conservation effects should be directed toward landscape- and plot-level factors by enhancing the protection of seepweed tidal flats, tamarisk-seepweed tidal flats, reed marshes and other natural wetlands. We propose that efforts should be made to strengthen wetland restoration, adjust functional zoning maps, and improve the management of human disturbance in the YRDNR. PMID:26065417

On steady motion of viscoelastic fluid of Oldroyd type

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

Baranovskii, E. S., E-mail: esbaranovskii@gmail.com

2014-06-01

We consider a mathematical model describing the steady motion of a viscoelastic medium of Oldroyd type under the Navier slip condition at the boundary. In the rheological relation, we use the objective regularized Jaumann derivative. We prove the solubility of the corresponding boundary-value problem in the weak setting. We obtain an estimate for the norm of a solution in terms of the data of the problem. We show that the solution set is sequentially weakly closed. Furthermore, we give an analytic solution of the boundary-value problem describing the flow of a viscoelastic fluid in a flat channel under a slipmore » condition at the walls. Bibliography: 13 titles. (paper)« less

Computerized tomography with total variation and with shearlets

NASA Astrophysics Data System (ADS)

Garduño, Edgar; Herman, Gabor T.

2017-04-01

To reduce the x-ray dose in computerized tomography (CT), many constrained optimization approaches have been proposed aiming at minimizing a regularizing function that measures a lack of consistency with some prior knowledge about the object that is being imaged, subject to a (predetermined) level of consistency with the detected attenuation of x-rays. One commonly investigated regularizing function is total variation (TV), while other publications advocate the use of some type of multiscale geometric transform in the definition of the regularizing function, a particular recent choice for this is the shearlet transform. Proponents of the shearlet transform in the regularizing function claim that the reconstructions so obtained are better than those produced using TV for texture preservation (but may be worse for noise reduction). In this paper we report results related to this claim. In our reported experiments using simulated CT data collection of the head, reconstructions whose shearlet transform has a small ℓ 1-norm are not more efficacious than reconstructions that have a small TV value. Our experiments for making such comparisons use the recently-developed superiorization methodology for both regularizing functions. Superiorization is an automated procedure for turning an iterative algorithm for producing images that satisfy a primary criterion (such as consistency with the observed measurements) into its superiorized version that will produce results that, according to the primary criterion are as good as those produced by the original algorithm, but in addition are superior to them according to a secondary (regularizing) criterion. The method presented for superiorization involving the ℓ 1-norm of the shearlet transform is novel and is quite general: It can be used for any regularizing function that is defined as the ℓ 1-norm of a transform specified by the application of a matrix. Because in the previous literature the split Bregman algorithm is used for similar purposes, a section is included comparing the results of the superiorization algorithm with the split Bregman algorithm.

A millennial-scale chronicle of evolutionary responses to cultural eutrophication in Daphnia.

PubMed

Frisch, Dagmar; Morton, Philip K; Chowdhury, Priyanka Roy; Culver, Billy W; Colbourne, John K; Weider, Lawrence J; Jeyasingh, Punidan D

2014-03-01

For an accurate assessment of the anthropogenic impacts on evolutionary change in natural populations, we need long-term environmental, genetic and phenotypic data that predate human disturbances. Analysis of c. 1600 years of history chronicled in the sediments of South Center Lake, Minnesota, USA, revealed major environmental changes beginning c. 120 years ago coinciding with the initiation of industrialised agriculture in the catchment area. Population genetic structure, analysed using DNA from dormant eggs of the keystone aquatic herbivore, Daphnia pulicaria, suggested no change for c. 1500 years prior to striking shifts associated with anthropogenic environmental alterations. Furthermore, phenotypic assays on the oldest resurrected metazoan genotypes (potentially as old as c. 700 years) indicate significant shifts in phosphorus utilisation rates compared to younger genotypes. Younger genotypes show steeper reaction norms with high growth under high phosphorus (P), and low growth under low P, while 'ancient' genotypes show flat reaction norms, yet higher growth efficiency under low P. Using this resurrection ecology approach, environmental, genetic and phenotypic data spanning pre- and post-industrialised agricultural eras clearly reveal the evolutionary consequences of anthropogenic environmental change. © 2014 John Wiley & Sons Ltd/CNRS.

A blind deconvolution method based on L1/L2 regularization prior in the gradient space

NASA Astrophysics Data System (ADS)

Cai, Ying; Shi, Yu; Hua, Xia

2018-02-01

In the process of image restoration, the result of image restoration is very different from the real image because of the existence of noise, in order to solve the ill posed problem in image restoration, a blind deconvolution method based on L1/L2 regularization prior to gradient domain is proposed. The method presented in this paper first adds a function to the prior knowledge, which is the ratio of the L1 norm to the L2 norm, and takes the function as the penalty term in the high frequency domain of the image. Then, the function is iteratively updated, and the iterative shrinkage threshold algorithm is applied to solve the high frequency image. In this paper, it is considered that the information in the gradient domain is better for the estimation of blur kernel, so the blur kernel is estimated in the gradient domain. This problem can be quickly implemented in the frequency domain by fast Fast Fourier Transform. In addition, in order to improve the effectiveness of the algorithm, we have added a multi-scale iterative optimization method. This paper proposes the blind deconvolution method based on L1/L2 regularization priors in the gradient space can obtain the unique and stable solution in the process of image restoration, which not only keeps the edges and details of the image, but also ensures the accuracy of the results.

Comparison of Multi-Scale Digital Elevation Models for Defining Waterways and Catchments Over Large Areas

NASA Astrophysics Data System (ADS)

Harris, B.; McDougall, K.; Barry, M.

2012-07-01

Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.

Sparsity-based acoustic inversion in cross-sectional multiscale optoacoustic imaging.

PubMed

Han, Yiyong; Tzoumas, Stratis; Nunes, Antonio; Ntziachristos, Vasilis; Rosenthal, Amir

2015-09-01

With recent advancement in hardware of optoacoustic imaging systems, highly detailed cross-sectional images may be acquired at a single laser shot, thus eliminating motion artifacts. Nonetheless, other sources of artifacts remain due to signal distortion or out-of-plane signals. The purpose of image reconstruction algorithms is to obtain the most accurate images from noisy, distorted projection data. In this paper, the authors use the model-based approach for acoustic inversion, combined with a sparsity-based inversion procedure. Specifically, a cost function is used that includes the L1 norm of the image in sparse representation and a total variation (TV) term. The optimization problem is solved by a numerically efficient implementation of a nonlinear gradient descent algorithm. TV-L1 model-based inversion is tested in the cross section geometry for numerically generated data as well as for in vivo experimental data from an adult mouse. In all cases, model-based TV-L1 inversion showed a better performance over the conventional Tikhonov regularization, TV inversion, and L1 inversion. In the numerical examples, the images reconstructed with TV-L1 inversion were quantitatively more similar to the originating images. In the experimental examples, TV-L1 inversion yielded sharper images and weaker streak artifact. The results herein show that TV-L1 inversion is capable of improving the quality of highly detailed, multiscale optoacoustic images obtained in vivo using cross-sectional imaging systems. As a result of its high fidelity, model-based TV-L1 inversion may be considered as the new standard for image reconstruction in cross-sectional imaging.

Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation

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

Hou, Thomas; Efendiev, Yalchin; Tchelepi, Hamdi

2016-05-24

Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scalemore » basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics.« less

Multiscale analysis and computation for flows in heterogeneous media

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

Efendiev, Yalchin; Hou, T. Y.; Durlofsky, L. J.

Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scalemore » basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics. Below, we present a brief overview of each of these contributions.« less

Modeling of Mutiscale Electromagnetic Magnetosphere-Ionosphere Interactions near Discrete Auroral Arcs Observed by the MICA Sounding Rocket

NASA Astrophysics Data System (ADS)

Streltsov, A. V.; Lynch, K. A.; Fernandes, P. A.; Miceli, R.; Hampton, D. L.; Michell, R. G.; Samara, M.

2012-12-01

The MICA (Magnetosphere-Ionosphere Coupling in the Alfvén Resonator) sounding rocket was launched from Poker Flat on February 19, 2012. The rocket was aimed into the system of discrete auroral arcs and during its flight it detected small-scale electromagnetic disturbances with characteristic features of dispersive Alfvén waves. We report results from numerical modeling of these observations. Our simulations are based on a two-fluid MHD model describing multi-scale interactions between magnetic field-aligned currents carried by shear Alfven waves and the ionosphere. The results from our simulations suggest that the small-scale electromagnetic structures measured by MICA indeed can be interpreted as dispersive Alfvén waves generated by the active ionospheric response (ionopspheric feedback instability) inside the large-scale downward magnetic field-aligned current interacting with the ionosphere.

Multi-Scaled Modeling the Mechanical Properties of Tubular Composites Reinforced with Innovated 3D Weft Knitted Spacer Fabrics

NASA Astrophysics Data System (ADS)

Omrani, Elahe; Hasani, Hossein; Dibajian, Sayed Houssain

2018-02-01

Textile composites of 3D integrated spacer configurations have been recently focused by several researchers all over the world. In the present study, newly-designed tubular composites reinforced with 3D spacer weft knitted fabrics were considered and the effects of their structural parameters on some applicable mechanical properties were investigated. For this purpose, two different samples of 3D spacer weft knitted textile types in tubular form were produced on an electronic flat knitting machine, using glass/nylon hybrid yarns. Thermoset tubular-shaped composite parts were manufactured via vacuum infusion molding process using epoxy resin. The mechanical properties of the produced knitted composites in term of external static and internal hydrostatic pressures were evaluated. Resistance of the produced composites against the external static and internal hydrostatic pressures was numerically simulated using multi-scale modeling method. The finding revealed that there is acceptable correlation between experimental and theoretical results.

This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms--theory and practice.

PubMed

Harmany, Zachary T; Marcia, Roummel F; Willett, Rebecca M

2012-03-01

Observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Gaussian noise model, and instead require a Poisson noise model. As a result, accurate reconstruction of a spatially or temporally distributed phenomenon (f*) from Poisson data (y) cannot be effectively accomplished by minimizing a conventional penalized least-squares objective function. The problem addressed in this paper is the estimation of f* from y in an inverse problem setting, where the number of unknowns may potentially be larger than the number of observations and f* admits sparse approximation. The optimization formulation considered in this paper uses a penalized negative Poisson log-likelihood objective function with nonnegativity constraints (since Poisson intensities are naturally nonnegative). In particular, the proposed approach incorporates key ideas of using separable quadratic approximations to the objective function at each iteration and penalization terms related to l1 norms of coefficient vectors, total variation seminorms, and partition-based multiscale estimation methods.

Multiscale Modeling: A Review

NASA Astrophysics Data System (ADS)

Horstemeyer, M. F.

This review of multiscale modeling covers a brief history of various multiscale methodologies related to solid materials and the associated experimental influences, the various influence of multiscale modeling on different disciplines, and some examples of multiscale modeling in the design of structural components. Although computational multiscale modeling methodologies have been developed in the late twentieth century, the fundamental notions of multiscale modeling have been around since da Vinci studied different sizes of ropes. The recent rapid growth in multiscale modeling is the result of the confluence of parallel computing power, experimental capabilities to characterize structure-property relations down to the atomic level, and theories that admit multiple length scales. The ubiquitous research that focus on multiscale modeling has broached different disciplines (solid mechanics, fluid mechanics, materials science, physics, mathematics, biological, and chemistry), different regions of the world (most continents), and different length scales (from atoms to autos).

Improving IQ measurement in intellectual disabilities using true deviation from population norms

PubMed Central

2014-01-01

Background Intellectual disability (ID) is characterized by global cognitive deficits, yet the very IQ tests used to assess ID have limited range and precision in this population, especially for more impaired individuals. Methods We describe the development and validation of a method of raw z-score transformation (based on general population norms) that ameliorates floor effects and improves the precision of IQ measurement in ID using the Stanford Binet 5 (SB5) in fragile X syndrome (FXS; n = 106), the leading inherited cause of ID, and in individuals with idiopathic autism spectrum disorder (ASD; n = 205). We compared the distributional characteristics and Q-Q plots from the standardized scores with the deviation z-scores. Additionally, we examined the relationship between both scoring methods and multiple criterion measures. Results We found evidence that substantial and meaningful variation in cognitive ability on standardized IQ tests among individuals with ID is lost when converting raw scores to standardized scaled, index and IQ scores. Use of the deviation z- score method rectifies this problem, and accounts for significant additional variance in criterion validation measures, above and beyond the usual IQ scores. Additionally, individual and group-level cognitive strengths and weaknesses are recovered using deviation scores. Conclusion Traditional methods for generating IQ scores in lower functioning individuals with ID are inaccurate and inadequate, leading to erroneously flat profiles. However assessment of cognitive abilities is substantially improved by measuring true deviation in performance from standardization sample norms. This work has important implications for standardized test development, clinical assessment, and research for which IQ is an important measure of interest in individuals with neurodevelopmental disorders and other forms of cognitive impairment. PMID:26491488

Improving IQ measurement in intellectual disabilities using true deviation from population norms.

PubMed

Sansone, Stephanie M; Schneider, Andrea; Bickel, Erika; Berry-Kravis, Elizabeth; Prescott, Christina; Hessl, David

2014-01-01

Intellectual disability (ID) is characterized by global cognitive deficits, yet the very IQ tests used to assess ID have limited range and precision in this population, especially for more impaired individuals. We describe the development and validation of a method of raw z-score transformation (based on general population norms) that ameliorates floor effects and improves the precision of IQ measurement in ID using the Stanford Binet 5 (SB5) in fragile X syndrome (FXS; n = 106), the leading inherited cause of ID, and in individuals with idiopathic autism spectrum disorder (ASD; n = 205). We compared the distributional characteristics and Q-Q plots from the standardized scores with the deviation z-scores. Additionally, we examined the relationship between both scoring methods and multiple criterion measures. We found evidence that substantial and meaningful variation in cognitive ability on standardized IQ tests among individuals with ID is lost when converting raw scores to standardized scaled, index and IQ scores. Use of the deviation z- score method rectifies this problem, and accounts for significant additional variance in criterion validation measures, above and beyond the usual IQ scores. Additionally, individual and group-level cognitive strengths and weaknesses are recovered using deviation scores. Traditional methods for generating IQ scores in lower functioning individuals with ID are inaccurate and inadequate, leading to erroneously flat profiles. However assessment of cognitive abilities is substantially improved by measuring true deviation in performance from standardization sample norms. This work has important implications for standardized test development, clinical assessment, and research for which IQ is an important measure of interest in individuals with neurodevelopmental disorders and other forms of cognitive impairment.

Sparsity-based acoustic inversion in cross-sectional multiscale optoacoustic imaging

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

Han, Yiyong; Tzoumas, Stratis; Nunes, Antonio

2015-09-15

Purpose: With recent advancement in hardware of optoacoustic imaging systems, highly detailed cross-sectional images may be acquired at a single laser shot, thus eliminating motion artifacts. Nonetheless, other sources of artifacts remain due to signal distortion or out-of-plane signals. The purpose of image reconstruction algorithms is to obtain the most accurate images from noisy, distorted projection data. Methods: In this paper, the authors use the model-based approach for acoustic inversion, combined with a sparsity-based inversion procedure. Specifically, a cost function is used that includes the L1 norm of the image in sparse representation and a total variation (TV) term. Themore » optimization problem is solved by a numerically efficient implementation of a nonlinear gradient descent algorithm. TV–L1 model-based inversion is tested in the cross section geometry for numerically generated data as well as for in vivo experimental data from an adult mouse. Results: In all cases, model-based TV–L1 inversion showed a better performance over the conventional Tikhonov regularization, TV inversion, and L1 inversion. In the numerical examples, the images reconstructed with TV–L1 inversion were quantitatively more similar to the originating images. In the experimental examples, TV–L1 inversion yielded sharper images and weaker streak artifact. Conclusions: The results herein show that TV–L1 inversion is capable of improving the quality of highly detailed, multiscale optoacoustic images obtained in vivo using cross-sectional imaging systems. As a result of its high fidelity, model-based TV–L1 inversion may be considered as the new standard for image reconstruction in cross-sectional imaging.« less

Self-dissimilar landscapes: Revealing the signature of geologic constraints on landscape dissection via topologic and multi-scale analysis

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Tejedor, Alejandro; Foufoula-Georgiou, Efi

2017-10-01

Climatic or geologic controls, such as tectonics or glacial drainage, might impose constraints on landscape self-organization resulting in spatial patterns of rivers and valleys which do not obey the typical self-similar relationships found in most landscapes. The goal of this study is to quantify how such geologic constraints express themselves on channel network topology, spatial heterogeneity of drainage patterns, and emergence of preferred scales of landscape dissection. We use as an example a basin located in the Upper Midwestern United States where successive glaciations over the past thousand years have led to a pronounced spatially anisotropic channel network structure which defeats most scaling laws of fluvial landscapes. This is contrasted with another river basin in the North-Central U.S. which has been organized under the absence of major geologic influences and follows a typical self-similar channel network organization. We show how the geologic constraints have imposed a competition for space which is captured in the slope-local drainage density probabilistic structure, in the failure of self-similarity in basin-wide river network topology, and in the length-area scaling relationship being not typical of fluvial landscapes. Via a two-dimensional wavelet analysis and synthesis, we demonstrate the occurrence of a gap in the power spectrum which corresponds to the presence of preferred scales of organization, and characterize them through multi-scale detrending. The developed methodologies can be useful in advancing our geomorphologic understanding of how external controls might manifest themselves in creating a landscape dissection that is outside the norm and how this dissection can be studied objectively for understanding cause and effect.

Networked high-speed auroral observations combined with radar measurements for multi-scale insights

NASA Astrophysics Data System (ADS)

Hirsch, M.; Semeter, J. L.

2015-12-01

Networks of ground-based instruments to study terrestrial aurora for the purpose of analyzing particle precipitation characteristics driving the aurora have been established. Additional funding is pouring into future ground-based auroral observation networks consisting of combinations of tossable, portable, and fixed installation ground-based legacy equipment. Our approach to this problem using the High Speed Tomography (HiST) system combines tightly-synchronized filtered auroral optical observations capturing temporal features of order 10 ms with supporting measurements from incoherent scatter radar (ISR). ISR provides a broader spatial context up to order 100 km laterally on one minute time scales, while our camera field of view (FOV) is chosen to be order 10 km at auroral altitudes in order to capture 100 m scale lateral auroral features. The dual-scale observations of ISR and HiST fine-scale optical observations may be coupled through a physical model using linear basis functions to estimate important ionospheric quantities such as electron number density in 3-D (time, perpendicular and parallel to the geomagnetic field).Field measurements and analysis using HiST and PFISR are presented from experiments conducted at the Poker Flat Research Range in central Alaska. Other multiscale configuration candidates include supplementing networks of all-sky cameras such as THEMIS with co-locations of HiST-like instruments to fuse wide FOV measurements with the fine-scale HiST precipitation characteristic estimates. Candidate models for this coupling include GLOW and TRANSCAR. Future extensions of this work may include incorporating line of sight total electron count estimates from ground-based networks of GPS receivers in a sensor fusion problem.

Predicting multicellular function through multi-layer tissue networks

PubMed Central

Zitnik, Marinka; Leskovec, Jure

2017-01-01

Abstract Motivation: Understanding functions of proteins in specific human tissues is essential for insights into disease diagnostics and therapeutics, yet prediction of tissue-specific cellular function remains a critical challenge for biomedicine. Results: Here, we present OhmNet, a hierarchy-aware unsupervised node feature learning approach for multi-layer networks. We build a multi-layer network, where each layer represents molecular interactions in a different human tissue. OhmNet then automatically learns a mapping of proteins, represented as nodes, to a neural embedding-based low-dimensional space of features. OhmNet encourages sharing of similar features among proteins with similar network neighborhoods and among proteins activated in similar tissues. The algorithm generalizes prior work, which generally ignores relationships between tissues, by modeling tissue organization with a rich multiscale tissue hierarchy. We use OhmNet to study multicellular function in a multi-layer protein interaction network of 107 human tissues. In 48 tissues with known tissue-specific cellular functions, OhmNet provides more accurate predictions of cellular function than alternative approaches, and also generates more accurate hypotheses about tissue-specific protein actions. We show that taking into account the tissue hierarchy leads to improved predictive power. Remarkably, we also demonstrate that it is possible to leverage the tissue hierarchy in order to effectively transfer cellular functions to a functionally uncharacterized tissue. Overall, OhmNet moves from flat networks to multiscale models able to predict a range of phenotypes spanning cellular subsystems. Availability and implementation: Source code and datasets are available at http://snap.stanford.edu/ohmnet. Contact: jure@cs.stanford.edu PMID:28881986

Self-excited multi-scale skin vibrations probed by optical tracking micro-motions of tracers on arms

NASA Astrophysics Data System (ADS)

Chen, Wei-Chia; Chen, Hsiang-Ying; Chen, Yu-Sheng; Tian, Yong; I, Lin

2017-07-01

The self-excited multi-scale mechanical vibrations, their sources and their mutual coupling of different regions on the forearms of supine subjects, are experimentally investigated, using a simple noncontact method, optical video microscopy, which provides 1 μm and 25 ms spatiotemporal resolutions. It is found that, in proximal regions far from the radial artery, the vibrations are the global vibrations of the entire forearm excited by remote sources, propagating through the trunk and the limb. The spectrum is mainly composed of peaks of very low frequency motion (down to 0.05 Hz), low frequency respiration modes, and heartbeat induced modes (about 1 Hz and its harmonics), standing out of the spectrum floor exhibiting power law decay. The nonlinear mode-mode coupling leads to the cascaded modulations of higher frequency modes by lower frequency modes. The nearly identical waveforms without detectable phase delays for a pair of signals along or transverse to the meridian of regions far away from the artery rule out the detectable contribution from the propagation of Qi, some kind of collective excitation which more efficiently propagates along meridians, according to the Chinese medicine theory. Around the radial artery, in addition to the global vibration, the local vibration spectrum shows very slow breathing type vibration around 0.05 Hz, and the artery pulsation induced fundamental and higher harmonics with descending intensities up to the fifth harmonics, standing out of a flat spectrum floor. All the artery pulsation modes are also modulated by respiration and the very slow vibration.

Multiscale Modeling in Computational Biomechanics: Determining Computational Priorities and Addressing Current Challenges

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

Tawhai, Merryn; Bischoff, Jeff; Einstein, Daniel R.

2009-05-01

Abstract In this article, we describe some current multiscale modeling issues in computational biomechanics from the perspective of the musculoskeletal and respiratory systems and mechanotransduction. First, we outline the necessity of multiscale simulations in these biological systems. Then we summarize challenges inherent to multiscale biomechanics modeling, regardless of the subdiscipline, followed by computational challenges that are system-specific. We discuss some of the current tools that have been utilized to aid research in multiscale mechanics simulations, and the priorities to further the field of multiscale biomechanics computation.

Community Multiscale Air Quality Model

EPA Science Inventory

The U.S. EPA developed the Community Multiscale Air Quality (CMAQ) system to apply a “one atmosphere” multiscale and multi-pollutant modeling approach based mainly on the “first principles” description of the atmosphere. The multiscale capability is supported by the governing di...

Development of Semantic Description for Multiscale Models of Thermo-Mechanical Treatment of Metal Alloys

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Regulski, Krzysztof

2016-08-01

We present a process of semantic meta-model development for data management in an adaptable multiscale modeling framework. The main problems in ontology design are discussed, and a solution achieved as a result of the research is presented. The main concepts concerning the application and data management background for multiscale modeling were derived from the AM3 approach—object-oriented Agile multiscale modeling methodology. The ontological description of multiscale models enables validation of semantic correctness of data interchange between submodels. We also present a possibility of using the ontological model as a supervisor in conjunction with a multiscale model controller and a knowledge base system. Multiscale modeling formal ontology (MMFO), designed for describing multiscale models' data and structures, is presented. A need for applying meta-ontology in the MMFO development process is discussed. Examples of MMFO application in describing thermo-mechanical treatment of metal alloys are discussed. Present and future applications of MMFO are described.

Comparison of Multiscale Method of Cells-Based Models for Predicting Elastic Properties of Filament Wound C/C-SiC

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Fassin, Marek; Bednarcyk, Brett A.; Reese, Stefanie; Simon, Jaan-Willem

2017-01-01

Three different multiscale models, based on the method of cells (generalized and high fidelity) micromechanics models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following multiscale modeling strategies were employed: Concurrent multiscale modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) multiscale modeling with the high fidelity generalized method of cells. The three models are validated against data from a hierarchical multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the multiscale models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute.

A ballistic performance study on multiphase particulate systems impacted by various projectiles

NASA Astrophysics Data System (ADS)

Comtois-Arnaldo, Christian; Petel, Oren

2017-06-01

The present study investigates the complex multiscale dynamic response of particulate composites, in an effort to link the bulk material behavior to strain-rate activated microstructures. These investigations involve multiphase systems containing micron-sized ceramic particles integrated into a siloxane elastomer to create flexible nanocomposites with varying inclusion properties. In particular, the effects of varying particle morphology, strength, volume fraction, and density are under investigation. The experimental focus of the study concerns the ballistic penetration of the nanocomposite targets. The targets are impacted by fragment simulating steel projectiles of constant mass and varying nose shapes (i.e., flat, ogive, and chisel-nose) to identify variations in the penetration mechanics. The projectiles are accelerated in a single-stage gas gun to velocities ranging from 200 m/s to 900 m/s prior to impact. The results for each projectile type are compared to analytical penetration models in order to shed light on the dominant penetration mechanisms and their relationship to the microstructure of the nanocomposites.

Molecular dynamics of single-particle impacts predicts phase diagrams for large scale pattern formation.

PubMed

Norris, Scott A; Samela, Juha; Bukonte, Laura; Backman, Marie; Djurabekova, Flyura; Nordlund, Kai; Madi, Charbel S; Brenner, Michael P; Aziz, Michael J

2011-01-01

Energetic particle irradiation can cause surface ultra-smoothening, self-organized nanoscale pattern formation or degradation of the structural integrity of nuclear reactor components. A fundamental understanding of the mechanisms governing the selection among these outcomes has been elusive. Here we predict the mechanism governing the transition from pattern formation to flatness using only parameter-free molecular dynamics simulations of single-ion impacts as input into a multiscale analysis, obtaining good agreement with experiment. Our results overturn the paradigm attributing these phenomena to the removal of target atoms via sputter erosion: the mechanism dominating both stability and instability is the impact-induced redistribution of target atoms that are not sputtered away, with erosive effects being essentially irrelevant. We discuss the potential implications for the formation of a mysterious nanoscale topography, leading to surface degradation, of tungsten plasma-facing fusion reactor walls. Consideration of impact-induced redistribution processes may lead to a new design criterion for stability under irradiation.

Multiscale Model of Swarming Bacteria

NASA Astrophysics Data System (ADS)

Alber, Mark

2011-03-01

Many bacteria can rapidly traverse surfaces from which they are extracting nutrient for growth. They generate flat, spreading colonies, called swarms because they resemble swarms of insects. In the beginning of the talk, swarms of the M. xanthus will be described in detail. Individual M. xanthus cells are elongated; they always move in the direction of their long axis; and they are in constant motion, repeatedly touching each other. As a cell glides, the slime capsule of a cell interacts with the bare agar surface, non-oriented slime which arises from the surface contact with the slime capsule, or oriented slime trails. Remarkably, cells regularly reverse their gliding directions. In this talk a detailed cell- and behavior-based computational model of M. xanthus swarming will be used to demonstrate that reversals of gliding direction and cell bending are essential for swarming and that specific reversal frequencies result in optimal swarming rate of the whole population. This suggests that the circuit regulating reversals evolved to its current sensitivity under selection for growth achieved by swarming.

Parallelization of fine-scale computation in Agile Multiscale Modelling Methodology

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Michalik, Kazimierz

2016-10-01

Nowadays, multiscale modelling of material behavior is an extensively developed area. An important obstacle against its wide application is high computational demands. Among others, the parallelization of multiscale computations is a promising solution. Heterogeneous multiscale models are good candidates for parallelization, since communication between sub-models is limited. In this paper, the possibility of parallelization of multiscale models based on Agile Multiscale Methodology framework is discussed. A sequential, FEM based macroscopic model has been combined with concurrently computed fine-scale models, employing a MatCalc thermodynamic simulator. The main issues, being investigated in this work are: (i) the speed-up of multiscale models with special focus on fine-scale computations and (ii) on decreasing the quality of computations enforced by parallel execution. Speed-up has been evaluated on the basis of Amdahl's law equations. The problem of `delay error', rising from the parallel execution of fine scale sub-models, controlled by the sequential macroscopic sub-model is discussed. Some technical aspects of combining third-party commercial modelling software with an in-house multiscale framework and a MPI library are also discussed.

25th anniversary article: scalable multiscale patterned structures inspired by nature: the role of hierarchy.

PubMed

Bae, Won-Gyu; Kim, Hong Nam; Kim, Doogon; Park, Suk-Hee; Jeong, Hoon Eui; Suh, Kahp-Yang

2014-02-01

Multiscale, hierarchically patterned surfaces, such as lotus leaves, butterfly wings, adhesion pads of gecko lizards are abundantly found in nature, where microstructures are usually used to strengthen the mechanical stability while nanostructures offer the main functionality, i.e., wettability, structural color, or dry adhesion. To emulate such hierarchical structures in nature, multiscale, multilevel patterning has been extensively utilized for the last few decades towards various applications ranging from wetting control, structural colors, to tissue scaffolds. In this review, we highlight recent advances in scalable multiscale patterning to bring about improved functions that can even surpass those found in nature, with particular focus on the analogy between natural and synthetic architectures in terms of the role of different length scales. This review is organized into four sections. First, the role and importance of multiscale, hierarchical structures is described with four representative examples. Second, recent achievements in multiscale patterning are introduced with their strengths and weaknesses. Third, four application areas of wetting control, dry adhesives, selectively filtrating membranes, and multiscale tissue scaffolds are overviewed by stressing out how and why multiscale structures need to be incorporated to carry out their performances. Finally, we present future directions and challenges for scalable, multiscale patterned surfaces. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On high heels and short muscles: A multiscale model for sarcomere loss in the gastrocnemius muscle

PubMed Central

Zöllner, Alexander M.; Pok, Jacquelynn M.; McWalter, Emily J.; Gold, Garry E.; Kuhl, Ellen

2014-01-01

High heels are a major source of chronic lower limb pain. Yet, more than one third of all women compromise health for looks and wear high heels on a daily basis. Changing from flat footwear to high heels induces chronic muscle shortening associated with discomfort, fatigue, reduced shock absorption, and increased injury risk. However, the long-term effects of high-heeled footwear on the musculoskeletal kinematics of the lower extremities remain poorly understood. Here we create a multiscale computational model for chronic muscle adaptation to characterize the acute and chronic effects of global muscle shortening on local sarcomere lengths. We perform a case study of a healthy female subject and show that raising the heel by 13 cm shortens the gastrocnemius muscle by 5% while the Achilles tendon remains virtually unaffected. Our computational simulation indicates that muscle shortening displays significant regional variations with extreme values of 22% in the central gastrocnemius. Our model suggests that the muscle gradually adjusts to its new functional length by a chronic loss of sarcomeres in series. Sarcomere loss varies significantly across the muscle with an average loss of 9%, virtually no loss at the proximal and distal ends, and a maximum loss of 39% in the central region. These changes reposition the remaining sarcomeres back into their optimal operating regime. Computational modeling of chronic muscle shortening provides a valuable tool to shape our understanding of the underlying mechanisms of muscle adaptation. Our study could open new avenues in orthopedic surgery and enhance treatment for patients with muscle contracture caused by other conditions than high heel wear such as paralysis, muscular atrophy, and muscular dystrophy. PMID:25451524

Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures.

PubMed

Costa, Madalena D; Peng, Chung-Kang; Goldberger, Ary L

2008-06-01

Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.

Multiscale Analysis of Heart Rate Dynamics: Entropy and Time Irreversibility Measures

PubMed Central

Peng, Chung-Kang; Goldberger, Ary L.

2016-01-01

Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and nonequilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools— multiscale entropy and multiscale time irreversibility—are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs. PMID:18172763

Multiscale measurement error models for aggregated small area health data.

PubMed

Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

2016-08-01

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.

Fluid-flow, diagenesis and generation of secondary porosity-permeability in the Cretaceous Jandaira Formation, Brazil - an analogue of karstified carbonate reservoirs

NASA Astrophysics Data System (ADS)

Bezerra, F. H.; Cazarin, C. L.; Srivastava, N. K.

2017-12-01

This study investigates the diagenetic processes that generated secondary porosity-permeability in carbonates. Our study area is the Jandaira Formation, a post-rift unit, 50-700 m thick, which occurs over an area of 70 x 260 km in the Potiguar Basin, Equatorial margin of Brazil. The Jandaira Formation formed in the Turonian-Campanian and is the major exposed Cretaceous carbonate platform in the eastern continental margin of South America. Little folding and nearly flat-lying layers characterize this unit. We used a multidisciplinary approach, which included drone imagery, petrographic, petrophysical, petrological, and structural studies. Our results indicate that several levels of dissolution occurred in mudstone, grainstone, and wackestone facies along faults, fractures, and bedding planes. Fracture and faults provided vertical leaching pathways and sedimentary bedding provided horizontal pathways of increased secondary porosity and permeability. Dissolution resulted in a multi-scale karst system that could reach voids 5 m wide and 1 km long. Dissolution mostly affect the dolomitized sedimentary facies in the form of vugular, moldic, interparticular, and intercrystalline porosity. It also generated a new modified facies that we defined as karstified facies. Dissolution increased permeability in carbonate rocks from primary values of 0.0-0.94 mD to as much as 1370.11 mD. Micritization, lixiviation of evaporites, meteoric water infiltration and dolomitization during late diagenesis could have triggered dissolution processes. The Jandaira Formation serves as an analog of fractured and karstified carbonate reservoirs, where faults, joints, and bedding acted as pathways of high permeability.

Towards a Multiscale Approach to Cybersecurity Modeling

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

Hogan, Emilie A.; Hui, Peter SY; Choudhury, Sutanay

2013-11-12

We propose a multiscale approach to modeling cyber networks, with the goal of capturing a view of the network and overall situational awareness with respect to a few key properties--- connectivity, distance, and centrality--- for a system under an active attack. We focus on theoretical and algorithmic foundations of multiscale graphs, coming from an algorithmic perspective, with the goal of modeling cyber system defense as a specific use case scenario. We first define a notion of \\emph{multiscale} graphs, in contrast with their well-studied single-scale counterparts. We develop multiscale analogs of paths and distance metrics. As a simple, motivating example ofmore » a common metric, we present a multiscale analog of the all-pairs shortest-path problem, along with a multiscale analog of a well-known algorithm which solves it. From a cyber defense perspective, this metric might be used to model the distance from an attacker's position in the network to a sensitive machine. In addition, we investigate probabilistic models of connectivity. These models exploit the hierarchy to quantify the likelihood that sensitive targets might be reachable from compromised nodes. We believe that our novel multiscale approach to modeling cyber-physical systems will advance several aspects of cyber defense, specifically allowing for a more efficient and agile approach to defending these systems.« less

Filters for Improvement of Multiscale Data from Atomistic Simulations

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

Gardner, David J.; Reynolds, Daniel R.

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less

Filters for Improvement of Multiscale Data from Atomistic Simulations

DOE PAGES

Gardner, David J.; Reynolds, Daniel R.

2017-01-05

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less

Towards practical multiscale approach for analysis of reinforced concrete structures

NASA Astrophysics Data System (ADS)

Moyeda, Arturo; Fish, Jacob

2017-12-01

We present a novel multiscale approach for analysis of reinforced concrete structural elements that overcomes two major hurdles in utilization of multiscale technologies in practice: (1) coupling between material and structural scales due to consideration of large representative volume elements (RVE), and (2) computational complexity of solving complex nonlinear multiscale problems. The former is accomplished using a variant of computational continua framework that accounts for sizeable reinforced concrete RVEs by adjusting the location of quadrature points. The latter is accomplished by means of reduced order homogenization customized for structural elements. The proposed multiscale approach has been verified against direct numerical simulations and validated against experimental results.

A concurrent multiscale micromorphic molecular dynamics

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

Li, Shaofan, E-mail: shaofan@berkeley.edu; Tong, Qi

2015-04-21

In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from firstmore » principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation.« less

Multiscale Materials Modeling Workshop Summary

DOT National Transportation Integrated Search

2013-12-01

This report summarizes a 2-day workshop held to share information on multiscale material modeling. The aim was to gain expert feedback on the state of the art and identify Exploratory Advanced Research (EAR) Program opportunities for multiscale mater...

Multiplex lithography for multilevel multiscale architectures and its application to polymer electrolyte membrane fuel cell

NASA Astrophysics Data System (ADS)

Cho, Hyesung; Moon Kim, Sang; Sik Kang, Yun; Kim, Junsoo; Jang, Segeun; Kim, Minhyoung; Park, Hyunchul; Won Bang, Jung; Seo, Soonmin; Suh, Kahp-Yang; Sung, Yung-Eun; Choi, Mansoo

2015-09-01

The production of multiscale architectures is of significant interest in materials science, and the integration of those structures could provide a breakthrough for various applications. Here we report a simple yet versatile strategy that allows for the LEGO-like integrations of microscale membranes by quantitatively controlling the oxygen inhibition effects of ultraviolet-curable materials, leading to multilevel multiscale architectures. The spatial control of oxygen concentration induces different curing contrasts in a resin allowing the selective imprinting and bonding at different sides of a membrane, which enables LEGO-like integration together with the multiscale pattern formation. Utilizing the method, the multilevel multiscale Nafion membranes are prepared and applied to polymer electrolyte membrane fuel cell. Our multiscale membrane fuel cell demonstrates significant enhancement of performance while ensuring mechanical robustness. The performance enhancement is caused by the combined effect of the decrease of membrane resistance and the increase of the electrochemical active surface area.

A complete categorization of multiscale models of infectious disease systems.

PubMed

Garira, Winston

2017-12-01

Modelling of infectious disease systems has entered a new era in which disease modellers are increasingly turning to multiscale modelling to extend traditional modelling frameworks into new application areas and to achieve higher levels of detail and accuracy in characterizing infectious disease systems. In this paper we present a categorization framework for categorizing multiscale models of infectious disease systems. The categorization framework consists of five integration frameworks and five criteria. We use the categorization framework to give a complete categorization of host-level immuno-epidemiological models (HL-IEMs). This categorization framework is also shown to be applicable in categorizing other types of multiscale models of infectious diseases beyond HL-IEMs through modifying the initial categorization framework presented in this study. Categorization of multiscale models of infectious disease systems in this way is useful in bringing some order to the discussion on the structure of these multiscale models.

A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

NASA Astrophysics Data System (ADS)

Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

2017-12-01

Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

Alternative transitions between existing representations in multi-scale maps

NASA Astrophysics Data System (ADS)

Dumont, Marion; Touya, Guillaume; Duchêne, Cécile

2018-05-01

Map users may have issues to achieve multi-scale navigation tasks, as cartographic objects may have various representations across scales. We assume that adding intermediate representations could be one way to reduce the differences between existing representations, and to ease the transitions across scales. We consider an existing multiscale map on the scale range from 1 : 25k to 1 : 100k scales. Based on hypotheses about intermediate representations design, we build custom multi-scale maps with alternative transitions. We will conduct in a next future a user evaluation to compare the efficiency of these alternative maps for multi-scale navigation. This paper discusses the hypotheses and production process of these alternative maps.

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

DOE PAGES

Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.

2018-03-27

In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

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

Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.

In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

Intercomparison of Multiscale Modeling Approaches in Simulating Subsurface Flow and Transport

NASA Astrophysics Data System (ADS)

Yang, X.; Mehmani, Y.; Barajas-Solano, D. A.; Song, H. S.; Balhoff, M.; Tartakovsky, A. M.; Scheibe, T. D.

2016-12-01

Hybrid multiscale simulations that couple models across scales are critical to advance predictions of the larger system behavior using understanding of fundamental processes. In the current study, three hybrid multiscale methods are intercompared: multiscale loose-coupling method, multiscale finite volume (MsFV) method and multiscale mortar method. The loose-coupling method enables a parallel workflow structure based on the Swift scripting environment that manages the complex process of executing coupled micro- and macro-scale models without being intrusive to the at-scale simulators. The MsFV method applies microscale and macroscale models over overlapping subdomains of the modeling domain and enforces continuity of concentration and transport fluxes between models via restriction and prolongation operators. The mortar method is a non-overlapping domain decomposition approach capable of coupling all permutations of pore- and continuum-scale models with each other. In doing so, Lagrange multipliers are used at interfaces shared between the subdomains so as to establish continuity of species/fluid mass flux. Subdomain computations can be performed either concurrently or non-concurrently depending on the algorithm used. All the above methods have been proven to be accurate and efficient in studying flow and transport in porous media. However, there has not been any field-scale applications and benchmarking among various hybrid multiscale approaches. To address this challenge, we apply all three hybrid multiscale methods to simulate water flow and transport in a conceptualized 2D modeling domain of the hyporheic zone, where strong interactions between groundwater and surface water exist across multiple scales. In all three multiscale methods, fine-scale simulations are applied to a thin layer of riverbed alluvial sediments while the macroscopic simulations are used for the larger subsurface aquifer domain. Different numerical coupling methods are then applied between scales and inter-compared. Comparisons are drawn in terms of velocity distributions, solute transport behavior, algorithm-induced numerical error and computing cost. The intercomparison work provides support for confidence in a variety of hybrid multiscale methods and motivates further development and applications.

Statistical CT noise reduction with multiscale decomposition and penalized weighted least squares in the projection domain

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

Tang Shaojie; Tang Xiangyang; School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi 710121

2012-09-15

Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation ofmore » interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of 'salt-and-pepper' noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain multiscale decomposition, the proposed method is anticipated to be useful in advanced clinical and preclinical applications where the interview sampling rate varies.« less

An approach to multiscale modelling with graph grammars.

PubMed

Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried

2014-09-01

Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.

An approach to multiscale modelling with graph grammars

PubMed Central

Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried

2014-01-01

Background and Aims Functional–structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. Methods A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Key Results Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. Conclusions The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models. PMID:25134929

Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

NASA Astrophysics Data System (ADS)

Yang, Qiu

Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.

Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

PubMed Central

Biggs, Matthew B.; Papin, Jason A.

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool. PMID:24147108

Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

PubMed

Biggs, Matthew B; Papin, Jason A

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

PubMed

Zanin, Massimiliano; Chorbev, Ivan; Stres, Blaz; Stalidzans, Egils; Vera, Julio; Tieri, Paolo; Castiglione, Filippo; Groen, Derek; Zheng, Huiru; Baumbach, Jan; Schmid, Johannes A; Basilio, José; Klimek, Peter; Debeljak, Nataša; Rozman, Damjana; Schmidt, Harald H H W

2017-12-05

Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine. © The Author 2017. Published by Oxford University Press.

Performance of distributed multiscale simulations

PubMed Central

Borgdorff, J.; Ben Belgacem, M.; Bona-Casas, C.; Fazendeiro, L.; Groen, D.; Hoenen, O.; Mizeranschi, A.; Suter, J. L.; Coster, D.; Coveney, P. V.; Dubitzky, W.; Hoekstra, A. G.; Strand, P.; Chopard, B.

2014-01-01

Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption. PMID:24982258

An optimized algorithm for multiscale wideband deconvolution of radio astronomical images

NASA Astrophysics Data System (ADS)

Offringa, A. R.; Smirnov, O.

2017-10-01

We describe a new multiscale deconvolution algorithm that can also be used in a multifrequency mode. The algorithm only affects the minor clean loop. In single-frequency mode, the minor loop of our improved multiscale algorithm is over an order of magnitude faster than the casa multiscale algorithm, and produces results of similar quality. For multifrequency deconvolution, a technique named joined-channel cleaning is used. In this mode, the minor loop of our algorithm is two to three orders of magnitude faster than casa msmfs. We extend the multiscale mode with automated scale-dependent masking, which allows structures to be cleaned below the noise. We describe a new scale-bias function for use in multiscale cleaning. We test a second deconvolution method that is a variant of the moresane deconvolution technique, and uses a convex optimization technique with isotropic undecimated wavelets as dictionary. On simple well-calibrated data, the convex optimization algorithm produces visually more representative models. On complex or imperfect data, the convex optimization algorithm has stability issues.

Multiplex lithography for multilevel multiscale architectures and its application to polymer electrolyte membrane fuel cell

PubMed Central

Cho, Hyesung; Moon Kim, Sang; Sik Kang, Yun; Kim, Junsoo; Jang, Segeun; Kim, Minhyoung; Park, Hyunchul; Won Bang, Jung; Seo, Soonmin; Suh, Kahp-Yang; Sung, Yung-Eun; Choi, Mansoo

2015-01-01

The production of multiscale architectures is of significant interest in materials science, and the integration of those structures could provide a breakthrough for various applications. Here we report a simple yet versatile strategy that allows for the LEGO-like integrations of microscale membranes by quantitatively controlling the oxygen inhibition effects of ultraviolet-curable materials, leading to multilevel multiscale architectures. The spatial control of oxygen concentration induces different curing contrasts in a resin allowing the selective imprinting and bonding at different sides of a membrane, which enables LEGO-like integration together with the multiscale pattern formation. Utilizing the method, the multilevel multiscale Nafion membranes are prepared and applied to polymer electrolyte membrane fuel cell. Our multiscale membrane fuel cell demonstrates significant enhancement of performance while ensuring mechanical robustness. The performance enhancement is caused by the combined effect of the decrease of membrane resistance and the increase of the electrochemical active surface area. PMID:26412619

2D deblending using the multi-scale shaping scheme

NASA Astrophysics Data System (ADS)

Li, Qun; Ban, Xingan; Gong, Renbin; Li, Jinnuo; Ge, Qiang; Zu, Shaohuan

2018-01-01

Deblending can be posed as an inversion problem, which is ill-posed and requires constraint to obtain unique and stable solution. In blended record, signal is coherent, whereas interference is incoherent in some domains (e.g., common receiver domain and common offset domain). Due to the different sparsity, coefficients of signal and interference locate in different curvelet scale domains and have different amplitudes. Take into account the two differences, we propose a 2D multi-scale shaping scheme to constrain the sparsity to separate the blended record. In the domain where signal concentrates, the multi-scale scheme passes all the coefficients representing signal, while, in the domain where interference focuses, the multi-scale scheme suppresses the coefficients representing interference. Because the interference is suppressed evidently at each iteration, the constraint of multi-scale shaping operator in all scale domains are weak to guarantee the convergence of algorithm. We evaluate the performance of the multi-scale shaping scheme and the traditional global shaping scheme by using two synthetic and one field data examples.

Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

DNS study on bursting and intermittency in late boundary layer transition

NASA Astrophysics Data System (ADS)

Wang, YiQian; Liu, ChaoQun

2017-11-01

Experimental and numerical investigations have suggested the existence of a strong correlation between the passage of coherent structures and events of bursting and intermittency. However, a detailed cause-and-effect study on the subject is rarely found in the literature due to the complexity and the nonlinear multiscale nature of turbulent flows. The primary goal of this research is to explore the motion and evolution of coherent structures during late transition, whose structure is much more ordered than that of fully developed turbulence, and their relationship with events of bursting and intermittency based on a verified high-order direct numerical simulation (DNS). The computation was carried out on a flat plate at Reynolds number 1000 (based on the inflow displacement thickness) with an inflow Mach number 0.5. It is concluded that bursting and intermittency detected by stationary sensors in a transitional boundary layer actually result from the passage and development of vortical structures, and it would be more rational to design transitional turbulence models based on modelling the moving vortical structures rather than the statistical features and experimental experiences.

Developing a regional canopy fuels assessment strategy using multi-scale lidar

USGS Publications Warehouse

Peterson, Birgit E.; Nelson, Kurtis

2011-01-01

Accurate assessments of canopy fuels are needed by fire scientists to understand fire behavior and to predict future fire occurrence. A key descriptor for canopy fuels is canopy bulk density (CBD). CBD is closely linked to the structure of the canopy; therefore, lidar measurements are particularly well suited to assessments of CBD. LANDFIRE scientists are exploring methods to integrate airborne and spaceborne lidar datasets into a national mapping effort. In this study, airborne lidar, spaceborne lidar, and field data are used to map CBD in the Yukon Flats Ecoregion, with the airborne lidar serving as a bridge between the field data and the spaceborne observations. The field-based CBD was positively correlated with airborne lidar observations (R2=0.78). Mapped values of CBD using the airborne lidar dataset were significantly correlated with spaceborne lidar observations when analyzed by forest type (R2=0.62, evergreen and R2=0.71, mixed). Though continued research is necessary to validate these results, they do support the feasibility of airborne and, most importantly, spaceborne lidar data for canopy fuels assessment.

Multiscale analysis of neural spike trains.

PubMed

Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin

2014-01-30

This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code. Copyright © 2013 John Wiley & Sons, Ltd.

Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

ERIC Educational Resources Information Center

Schwalbe, Michelle Kristin

2010-01-01

This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…

Convective boundary layer heights over mountainous terrain - A review of concepts -

NASA Astrophysics Data System (ADS)

De Wekker, Stephan; Kossmann, Meinolf

2015-12-01

Mountainous terrain exerts an important influence on the Earth's atmosphere and affects atmospheric transport and mixing at a wide range of temporal and spatial scales. The vertical scale of this transport and mixing is determined by the height of the atmospheric boundary layer, which is therefore an important parameter in air pollution studies, weather forecasting, climate modeling, and many other applications. It is recognized that the spatio-temporal structure of the daytime convective boundary layer (CBL) height is strongly modified and more complex in hilly and mountainous terrain compared to flat terrain. While the CBL over flat terrain is mostly dominated by turbulent convection, advection from multi-scale thermally driven flows plays an important role for the CBL evolution over mountainous terrain. However, detailed observations of the CBL structure and understanding of the underlying processes are still limited. Characteristics of CBL heights in mountainous terrain are reviewed for dry, convective conditions. CBLs in valleys and basins, where hazardous accumulation of pollutants is of particular concern, are relatively well-understood compared to CBLs over slopes, ridges, or mountain peaks. Interests in the initiation of shallow and deep convection, and of budgets and long-range transport of air pollutants and trace gases, have triggered some recent studies on terrain induced exchange processes between the CBL and the overlying atmosphere. These studies have helped to gain more insight into CBL structure over complex mountainous terrain, but also show that the universal definition of CBL height over mountains remains an unresolved issue. The review summarizes the progress that has been made in documenting and understanding spatio-temporal behavior of CBL heights in mountainous terrain and concludes with a discussion of open research questions and opportunities for future research.

Multiscale Speciation of U and Pu at Chernobyl, Hanford, Los Alamos, McGuire AFB, Mayak, and Rocky Flats.

PubMed

Batuk, Olga N; Conradson, Steven D; Aleksandrova, Olga N; Boukhalfa, Hakim; Burakov, Boris E; Clark, David L; Czerwinski, Ken R; Felmy, Andrew R; Lezama-Pacheco, Juan S; Kalmykov, Stepan N; Moore, Dean A; Myasoedov, Boris F; Reed, Donald T; Reilly, Dallas D; Roback, Robert C; Vlasova, Irina E; Webb, Samuel M; Wilkerson, Marianne P

2015-06-02

The speciation of U and Pu in soil and concrete from Rocky Flats and in particles from soils from Chernobyl, Hanford, Los Alamos, and McGuire Air Force Base and bottom sediments from Mayak was determined by a combination of X-ray absorption fine structure (XAFS) spectroscopy and X-ray fluorescence (XRF) element maps. These experiments identify four types of speciation that sometimes may and other times do not exhibit an association with the source terms and histories of these samples: relatively well ordered PuO2+x and UO2+x that had equilibrated with O2 and H2O under both ambient conditions and in fires or explosions; instances of small, isolated particles of U as UO2+x, U3O8, and U(VI) species coexisting in close proximity after decades in the environment; alteration phases of uranyl with other elements including ones that would not have come from soils; and mononuclear Pu-O species and novel PuO2+x-type compounds incorporating additional elements that may have occurred because the Pu was exposed to extreme chemical conditions such as acidic solutions released directly into soil or concrete. Our results therefore directly demonstrate instances of novel complexity in the Å and μm-scale chemical speciation and reactivity of U and Pu in their initial formation and after environmental exposure as well as occasions of unexpected behavior in the reaction pathways over short geological but significant sociological times. They also show that incorporating the actual disposal and site conditions and resultant novel materials such as those reported here may be necessary to develop the most accurate predictive models for Pu and U in the environment.

DETECTING RELATIVISTIC X-RAY JETS IN HIGH-REDSHIFT QUASARS

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

McKeough, Kathryn; Siemiginowska, Aneta; Kashyap, Vinay L.

We analyze Chandra X-ray images of a sample of 11 quasars that are known to contain kiloparsec scale radio jets. The sample consists of five high-redshift ( z  ≥ 3.6) flat-spectrum radio quasars, and six intermediate redshift (2.1 <  z  < 2.9) quasars. The data set includes four sources with integrated steep radio spectra and seven with flat radio spectra. A total of 25 radio jet features are present in this sample. We apply a Bayesian multi-scale image reconstruction method to detect and measure the X-ray emission from the jets. We compute deviations from a baseline model that does not include the jet,more » and compare observed X-ray images with those computed with simulated images where no jet features exist. This allows us to compute p -value upper bounds on the significance that an X-ray jet is detected in a pre-determined region of interest. We detected 12 of the features unambiguously, and an additional six marginally. We also find residual emission in the cores of three quasars and in the background of one quasar that suggest the existence of unresolved X-ray jets. The dependence of the X-ray to radio luminosity ratio on redshift is a potential diagnostic of the emission mechanism, since the inverse Compton scattering of cosmic microwave background photons (IC/CMB) is thought to be redshift dependent, whereas in synchrotron models no clear redshift dependence is expected. We find that the high-redshift jets have X-ray to radio flux ratios that are marginally inconsistent with those from lower redshifts, suggesting that either the X-ray emissions are due to the IC/CMB rather than the synchrotron process, or that high-redshift jets are qualitatively different.« less

A weak Galerkin generalized multiscale finite element method

DOE PAGES

Mu, Lin; Wang, Junping; Ye, Xiu

2016-03-31

In this study, we propose a general framework for weak Galerkin generalized multiscale (WG-GMS) finite element method for the elliptic problems with rapidly oscillating or high contrast coefficients. This general WG-GMS method features in high order accuracy on general meshes and can work with multiscale basis derived by different numerical schemes. A special case is studied under this WG-GMS framework in which the multiscale basis functions are obtained by solving local problem with the weak Galerkin finite element method. Convergence analysis and numerical experiments are obtained for the special case.

A weak Galerkin generalized multiscale finite element method

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

Mu, Lin; Wang, Junping; Ye, Xiu

In this study, we propose a general framework for weak Galerkin generalized multiscale (WG-GMS) finite element method for the elliptic problems with rapidly oscillating or high contrast coefficients. This general WG-GMS method features in high order accuracy on general meshes and can work with multiscale basis derived by different numerical schemes. A special case is studied under this WG-GMS framework in which the multiscale basis functions are obtained by solving local problem with the weak Galerkin finite element method. Convergence analysis and numerical experiments are obtained for the special case.

Multi-Scale Scattering Transform in Music Similarity Measuring

NASA Astrophysics Data System (ADS)

Wang, Ruobai

Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.

Multiscale molecular dynamics/hydrodynamics implementation of two dimensional "Mercedes Benz" water model

NASA Astrophysics Data System (ADS)

Scukins, A.; Nerukh, D.; Pavlov, E.; Karabasov, S.; Markesteijn, A.

2015-09-01

A multiscale Molecular Dynamics/Hydrodynamics implementation of the 2D Mercedes Benz (MB or BN2D) [1] water model is developed and investigated. The concept and the governing equations of multiscale coupling together with the results of the two-way coupling implementation are reported. The sensitivity of the multiscale model for obtaining macroscopic and microscopic parameters of the system, such as macroscopic density and velocity fluctuations, radial distribution and velocity autocorrelation functions of MB particles, is evaluated. Critical issues for extending the current model to large systems are discussed.

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network

PubMed Central

Qu, Xiaobo; He, Yifan

2018-01-01

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods. PMID:29509666

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

PubMed

Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

2018-03-06

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

Transfer the multiscale texture of crystalline Si onto thin-film micromorph cell by UV nanoimprint for light trapping

NASA Astrophysics Data System (ADS)

Liu, Daiming; Wang, Qingkang; Wang, Qing

2018-05-01

Surface texturing is of great significance in light trapping for solar cells. Herein, the multiscale texture, consisting of microscale pyramids and nanoscale porous arrangement, was fabricated on crystalline Si by KOH etching and Ag-assisted HF etching processes and subsequently replicated onto glass with high fidelity by UV nanoimprint method. Light trapping of the multiscale texture was studied by spectral (reflectance, haze ratio) characterizations. Results reveal the multiscale texture provides the broadband reflection reducing, the highlighted light scattering and the additional self-cleaning behaviors. Compared with bare cell, the multiscale textured micromorph cell achieves a 4% relative increase in power conversion efficiency. This surface texturing route paves a promising way for developing low-cost, large-scale and high-efficiency solar applications.

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

NASA Astrophysics Data System (ADS)

Gao, Kai; Fu, Shubin; Chung, Eric T.

2018-05-01

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructs high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss-Lobatto-Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

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

Gao, Kai; Fu, Shubin; Chung, Eric T.

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructsmore » high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss–Lobatto–Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.« less

Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

PubMed

Li, Xiangfang L; Oduola, Wasiu O; Qian, Lijun; Dougherty, Edward R

2015-01-01

In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute.

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

DOE PAGES

Gao, Kai; Fu, Shubin; Chung, Eric T.

2018-02-04

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructsmore » high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss–Lobatto–Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.« less

Multiscale decoding for reliable brain-machine interface performance over time.

PubMed

Han-Lin Hsieh; Wong, Yan T; Pesaran, Bijan; Shanechi, Maryam M

2017-07-01

Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously use spikes and other recording modalities such as local field potentials (LFP), which are more robust to signal degradation over time. We have developed a multiscale decoder that can simultaneously model the different statistical profiles of multi-scale spike/LFP activity (discrete spikes vs. continuous LFP). This decoder can also run at multiple time-scales (millisecond for spikes vs. tens of milliseconds for LFP). Here, we validate the multiscale decoder for estimating the movement of 7 major upper-arm joint angles in a non-human primate (NHP) during a 3D reach-to-grasp task. The multiscale decoder uses motor cortical spike/LFP recordings as its input. We show that the multiscale decoder can improve decoding accuracy by adding information from LFP to spikes, while running at the fast millisecond time-scale of the spiking activity. Moreover, this improvement is achieved using relatively few LFP channels, demonstrating the robustness of the approach. These results suggest that using multiscale decoders has the potential to improve the reliability and longevity of BMIs.

Multi-scale calculation based on dual domain material point method combined with molecular dynamics

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

Dhakal, Tilak Raj

This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crackmore » tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared with direct MD simulation results to demonstrate the feasibility of the method. Also, the multi-scale method is applied for a two dimensional problem of jet formation around copper notch under a strong impact.« less

ONE-ATMOSPHERE DYNAMICS DESCRIPTION IN THE MODELS-3 COMMUNITY MULTI-SCALE QUALITY (CMAQ) MODELING SYSTEM

EPA Science Inventory

This paper proposes a general procedure to link meteorological data with air quality models, such as U.S. EPA's Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. CMAQ is intended to be used for studying multi-scale (urban and regional) and multi-pollutant (ozon...

Multiscale Models in the Biomechanics of Plant Growth

PubMed Central

Fozard, John A.

2015-01-01

Plant growth occurs through the coordinated expansion of tightly adherent cells, driven by regulated softening of cell walls. It is an intrinsically multiscale process, with the integrated properties of multiple cell walls shaping the whole tissue. Multiscale models encode physical relationships to bring new understanding to plant physiology and development. PMID:25729061

Filter-based multiscale entropy analysis of complex physiological time series.

PubMed

Xu, Yuesheng; Zhao, Liang

2013-08-01

Multiscale entropy (MSE) has been widely and successfully used in analyzing the complexity of physiological time series. We reinterpret the averaging process in MSE as filtering a time series by a filter of a piecewise constant type. From this viewpoint, we introduce filter-based multiscale entropy (FME), which filters a time series to generate multiple frequency components, and then we compute the blockwise entropy of the resulting components. By choosing filters adapted to the feature of a given time series, FME is able to better capture its multiscale information and to provide more flexibility for studying its complexity. Motivated by the heart rate turbulence theory, which suggests that the human heartbeat interval time series can be described in piecewise linear patterns, we propose piecewise linear filter multiscale entropy (PLFME) for the complexity analysis of the time series. Numerical results from PLFME are more robust to data of various lengths than those from MSE. The numerical performance of the adaptive piecewise constant filter multiscale entropy without prior information is comparable to that of PLFME, whose design takes prior information into account.

Facing the challenges of multiscale modelling of bacterial and fungal pathogen–host interactions

PubMed Central

Schleicher, Jana; Conrad, Theresia; Gustafsson, Mika; Cedersund, Gunnar; Guthke, Reinhard

2017-01-01

Abstract Recent and rapidly evolving progress on high-throughput measurement techniques and computational performance has led to the emergence of new disciplines, such as systems medicine and translational systems biology. At the core of these disciplines lies the desire to produce multiscale models: mathematical models that integrate multiple scales of biological organization, ranging from molecular, cellular and tissue models to organ, whole-organism and population scale models. Using such models, hypotheses can systematically be tested. In this review, we present state-of-the-art multiscale modelling of bacterial and fungal infections, considering both the pathogen and host as well as their interaction. Multiscale modelling of the interactions of bacteria, especially Mycobacterium tuberculosis, with the human host is quite advanced. In contrast, models for fungal infections are still in their infancy, in particular regarding infections with the most important human pathogenic fungi, Candida albicans and Aspergillus fumigatus. We reflect on the current availability of computational approaches for multiscale modelling of host–pathogen interactions and point out current challenges. Finally, we provide an outlook for future requirements of multiscale modelling. PMID:26857943

Multiscale Pressure-Balanced Structures in Three-dimensional Magnetohydrodynamic Turbulence

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

Yang, Liping; Zhang, Lei; Feng, Xueshang

2017-02-10

Observations of solar wind turbulence indicate the existence of multiscale pressure-balanced structures (PBSs) in the solar wind. In this work, we conduct a numerical simulation to investigate multiscale PBSs and in particular their formation in compressive magnetohydrodynamic turbulence. By the use of the higher-order Godunov code Athena, a driven compressible turbulence with an imposed uniform guide field is simulated. The simulation results show that both the magnetic pressure and the thermal pressure exhibit a turbulent spectrum with a Kolmogorov-like power law, and that in many regions of the simulation domain they are anticorrelated. The computed wavelet cross-coherence spectra of themore » magnetic pressure and the thermal pressure, as well as their space series, indicate the existence of multiscale PBSs, with the small PBSs being embedded in the large ones. These multiscale PBSs are likely to be related to the highly oblique-propagating slow-mode waves, as the traced multiscale PBS is found to be traveling in a certain direction at a speed consistent with that predicted theoretically for a slow-mode wave propagating in the same direction.« less

Multi-scale signed envelope inversion

NASA Astrophysics Data System (ADS)

Chen, Guo-Xin; Wu, Ru-Shan; Wang, Yu-Qing; Chen, Sheng-Chang

2018-06-01

Envelope inversion based on modulation signal mode was proposed to reconstruct large-scale structures of underground media. In order to solve the shortcomings of conventional envelope inversion, multi-scale envelope inversion was proposed using new envelope Fréchet derivative and multi-scale inversion strategy to invert strong contrast models. In multi-scale envelope inversion, amplitude demodulation was used to extract the low frequency information from envelope data. However, only to use amplitude demodulation method will cause the loss of wavefield polarity information, thus increasing the possibility of inversion to obtain multiple solutions. In this paper we proposed a new demodulation method which can contain both the amplitude and polarity information of the envelope data. Then we introduced this demodulation method into multi-scale envelope inversion, and proposed a new misfit functional: multi-scale signed envelope inversion. In the numerical tests, we applied the new inversion method to the salt layer model and SEG/EAGE 2-D Salt model using low-cut source (frequency components below 4 Hz were truncated). The results of numerical test demonstrated the effectiveness of this method.

An Analysis Platform for Multiscale Hydrogeologic Modeling with Emphasis on Hybrid Multiscale Methods

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

Scheibe, Timothy D.; Murphy, Ellyn M.; Chen, Xingyuan

2015-01-01

One of the most significant challenges facing hydrogeologic modelers is the disparity between those spatial and temporal scales at which fundamental flow, transport and reaction processes can best be understood and quantified (e.g., microscopic to pore scales, seconds to days) and those at which practical model predictions are needed (e.g., plume to aquifer scales, years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computational and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that modelmore » parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this paper, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flow chart (Multiscale Analysis Platform or MAP), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to improve, we envision that hybrid multiscale modeling will become more common and may become a viable alternative to conventional single-scale models in the near future.« less

An analysis platform for multiscale hydrogeologic modeling with emphasis on hybrid multiscale methods.

PubMed

Scheibe, Timothy D; Murphy, Ellyn M; Chen, Xingyuan; Rice, Amy K; Carroll, Kenneth C; Palmer, Bruce J; Tartakovsky, Alexandre M; Battiato, Ilenia; Wood, Brian D

2015-01-01

One of the most significant challenges faced by hydrogeologic modelers is the disparity between the spatial and temporal scales at which fundamental flow, transport, and reaction processes can best be understood and quantified (e.g., microscopic to pore scales and seconds to days) and at which practical model predictions are needed (e.g., plume to aquifer scales and years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computation and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this article, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flowchart (Multiscale Analysis Platform), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to improve, we envision that hybrid multiscale modeling will become more common and also a viable alternative to conventional single-scale models in the near future. © 2014, National Ground Water Association.

Modified DFA and DCCA approach for quantifying the multiscale correlation structure of financial markets

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2013-12-01

We use multiscale detrended fluctuation analysis (MSDFA) and multiscale detrended cross-correlation analysis (MSDCCA) to investigate auto-correlation (AC) and cross-correlation (CC) in the US and Chinese stock markets during 1997-2012. The results show that US and Chinese stock indices differ in terms of their multiscale AC structures. Stock indices in the same region also differ with regard to their multiscale AC structures. We analyze AC and CC behaviors among indices for the same region to determine similarity among six stock indices and divide them into four groups accordingly. We choose S&P500, NQCI, HSI, and the Shanghai Composite Index as representative samples for simplicity. MSDFA and MSDCCA results and average MSDFA spectra for local scaling exponents (LSEs) for individual series are presented. We find that the MSDCCA spectrum for LSE CC between two time series generally tends to be greater than the average MSDFA LSE spectrum for individual series. We obtain detailed multiscale structures and relations for CC between the four representatives. MSDFA and MSDCCA with secant rolling windows of different sizes are then applied to reanalyze the AC and CC. Vertical and horizontal comparisons of different window sizes are made. The MSDFA and MSDCCA results for the original window size are confirmed and some new interesting characteristics and conclusions regarding multiscale correlation structures are obtained.

Taylor-Aris Dispersion: An Explicit Example for Understanding Multiscale Analysis via Volume Averaging

ERIC Educational Resources Information Center

Wood, Brian D.

2009-01-01

Although the multiscale structure of many important processes in engineering is becoming more widely acknowledged, making this connection in the classroom is a difficult task. This is due in part because the concept of multiscale structure itself is challenging and it requires the students to develop new conceptual pictures of physical systems,…

Shaken but not stirred: Multiscale habitat suitability modeling of sympatric marten species (Martes martes and Martes foina) in the northern Iberian Peninsula

Treesearch

Maria Vergara; Samuel A. Cushman; Fermin Urra; Aritz Ruiz-Gonzalez

2016-01-01

Multispecies and multiscale habitat suitability models (HSM) are important to identify the environmental variables and scales influencing habitat selection and facilitate the comparison of closely related species with different ecological requirements. Objectives This study explores the multiscale relationships of habitat suitability for the pine (Martes...

Adaptation of a Fast Optimal Interpolation Algorithm to the Mapping of Oceangraphic Data

NASA Technical Reports Server (NTRS)

Menemenlis, Dimitris; Fieguth, Paul; Wunsch, Carl; Willsky, Alan

1997-01-01

A fast, recently developed, multiscale optimal interpolation algorithm has been adapted to the mapping of hydrographic and other oceanographic data. This algorithm produces solution and error estimates which are consistent with those obtained from exact least squares methods, but at a small fraction of the computational cost. Problems whose solution would be completely impractical using exact least squares, that is, problems with tens or hundreds of thousands of measurements and estimation grid points, can easily be solved on a small workstation using the multiscale algorithm. In contrast to methods previously proposed for solving large least squares problems, our approach provides estimation error statistics while permitting long-range correlations, using all measurements, and permitting arbitrary measurement locations. The multiscale algorithm itself, published elsewhere, is not the focus of this paper. However, the algorithm requires statistical models having a very particular multiscale structure; it is the development of a class of multiscale statistical models, appropriate for oceanographic mapping problems, with which we concern ourselves in this paper. The approach is illustrated by mapping temperature in the northeastern Pacific. The number of hydrographic stations is kept deliberately small to show that multiscale and exact least squares results are comparable. A portion of the data were not used in the analysis; these data serve to test the multiscale estimates. A major advantage of the present approach is the ability to repeat the estimation procedure a large number of times for sensitivity studies, parameter estimation, and model testing. We have made available by anonymous Ftp a set of MATLAB-callable routines which implement the multiscale algorithm and the statistical models developed in this paper.

Transition between inverse and direct energy cascades in multiscale optical turbulence

DOE PAGES

Malkin, V. M.; Fisch, N. J.

2018-03-06

Transition between inverse and direct energy cascades in multiscale optical turbulence. Multiscale turbulence naturally develops and plays an important role in many fluid, gas, and plasma phenomena. Statistical models of multiscale turbulence usually employ Kolmogorov hypotheses of spectral locality of interactions (meaning that interactions primarily occur between pulsations of comparable scales) and scale-invariance of turbulent pulsations. However, optical turbulence described by the nonlinear Schrodinger equation exhibits breaking of both the Kolmogorov locality and scale-invariance. A weaker form of spectral locality that holds for multi-scale optical turbulence enables a derivation of simplified evolution equations that reduce the problem to a singlemore » scale modeling. We present the derivation of these equations for Kerr media with random inhomogeneities. Then, we find the analytical solution that exhibits a transition between inverse and direct energy cascades in optical turbulence.« less

Multiscale Integration of -Omic, Imaging, and Clinical Data in Biomedical Informatics

PubMed Central

Phan, John H.; Quo, Chang F.; Cheng, Chihwen; Wang, May Dongmei

2016-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data. PMID:23231990

Multiscale Cancer Modeling

PubMed Central

Macklin, Paul; Cristini, Vittorio

2013-01-01

Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insight on the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community. PMID:21529163

Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.

PubMed

Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei

2012-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.

Multiscale Simulation of Blood Flow in Brain Arteries with an Aneurysm

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

Leopold Grinberg; Vitali Morozov; Dmitry A. Fedosov

2013-04-24

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations.This animation presents results of studies used in the development of a multi-scale visualization methodology. First we use streamlines to show the path the flow is taking as it moves through the system, including the aneurysm. Next we investigate themore » process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of the aneurysm.« less

Goal-oriented robot navigation learning using a multi-scale space representation.

PubMed

Llofriu, M; Tejera, G; Contreras, M; Pelc, T; Fellous, J M; Weitzenfeld, A

2015-12-01

There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiscale modelling in immunology: a review.

PubMed

Cappuccio, Antonio; Tieri, Paolo; Castiglione, Filippo

2016-05-01

One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Multiscale Study of Currents Affected by Topography

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Multiscale Study of Currents Affected by Topography ... topography on the ocean general circulation is challenging because of the multiscale nature of the flow interactions. Small-scale details of the... topography , and the waves, drag, and turbulence generated at the boundary, from meter scale to mesoscale, interact in the boundary layers to influence the

Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

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

Plechac, Petr; Vlachos, Dionisios; Katsoulakis, Markos

2013-09-05

The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomassmore » transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.« less

Petascale computation performance of lightweight multiscale cardiac models using hybrid programming models.

PubMed

Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias

2011-01-01

Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models.

Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under various incoherence conditions, the convex program recovers the multi-scale low rank components either exactly or approximately. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information. PMID:28450978

A fast solver for the Helmholtz equation based on the generalized multiscale finite-element method

NASA Astrophysics Data System (ADS)

Fu, Shubin; Gao, Kai

2017-11-01

Conventional finite-element methods for solving the acoustic-wave Helmholtz equation in highly heterogeneous media usually require finely discretized mesh to represent the medium property variations with sufficient accuracy. Computational costs for solving the Helmholtz equation can therefore be considerably expensive for complicated and large geological models. Based on the generalized multiscale finite-element theory, we develop a novel continuous Galerkin method to solve the Helmholtz equation in acoustic media with spatially variable velocity and mass density. Instead of using conventional polynomial basis functions, we use multiscale basis functions to form the approximation space on the coarse mesh. The multiscale basis functions are obtained from multiplying the eigenfunctions of a carefully designed local spectral problem with an appropriate multiscale partition of unity. These multiscale basis functions can effectively incorporate the characteristics of heterogeneous media's fine-scale variations, thus enable us to obtain accurate solution to the Helmholtz equation without directly solving the large discrete system formed on the fine mesh. Numerical results show that our new solver can significantly reduce the dimension of the discrete Helmholtz equation system, and can also obviously reduce the computational time.

A Handful of Paragraphs on "Translation" and "Norms."

ERIC Educational Resources Information Center

Toury, Gideon

1998-01-01

Presents some thoughts on the issue of translation and norms, focusing on the relationships between social agreements, conventions, and norms; translational norms; acts of translation and translation events; norms and values; norms for translated texts versus norms for non-translated texts; and competing norms. Comments on the reactions to three…

A norm knockout method on indirect reciprocity to reveal indispensable norms

PubMed Central

Yamamoto, Hitoshi; Okada, Isamu; Uchida, Satoshi; Sasaki, Tatsuya

2017-01-01

Although various norms for reciprocity-based cooperation have been suggested that are evolutionarily stable against invasion from free riders, the process of alternation of norms and the role of diversified norms remain unclear in the evolution of cooperation. We clarify the co-evolutionary dynamics of norms and cooperation in indirect reciprocity and also identify the indispensable norms for the evolution of cooperation. Inspired by the gene knockout method, a genetic engineering technique, we developed the norm knockout method and clarified the norms necessary for the establishment of cooperation. The results of numerical investigations revealed that the majority of norms gradually transitioned to tolerant norms after defectors are eliminated by strict norms. Furthermore, no cooperation emerges when specific norms that are intolerant to defectors are knocked out. PMID:28276485

A norm knockout method on indirect reciprocity to reveal indispensable norms

NASA Astrophysics Data System (ADS)

Yamamoto, Hitoshi; Okada, Isamu; Uchida, Satoshi; Sasaki, Tatsuya

2017-03-01

Although various norms for reciprocity-based cooperation have been suggested that are evolutionarily stable against invasion from free riders, the process of alternation of norms and the role of diversified norms remain unclear in the evolution of cooperation. We clarify the co-evolutionary dynamics of norms and cooperation in indirect reciprocity and also identify the indispensable norms for the evolution of cooperation. Inspired by the gene knockout method, a genetic engineering technique, we developed the norm knockout method and clarified the norms necessary for the establishment of cooperation. The results of numerical investigations revealed that the majority of norms gradually transitioned to tolerant norms after defectors are eliminated by strict norms. Furthermore, no cooperation emerges when specific norms that are intolerant to defectors are knocked out.

Dynamics of Oceanic Motions

DTIC Science & Technology

1997-09-30

research is multiscale , interdisciplinary and generic. The methods are applicable to an arbitrary region of the coastal and/or deep ocean and across the...dynamics. OBJECTIVES General objectives are: (I) To determine for the coastal and/or coupled deep ocean the multiscale processes which occur: i) in...Straits and the eastern basin; iii) extension and application of our balance of terms scheme (EVA) to multiscale , interdisciplinary fields with data

Multi-scale Mexican spotted owl (Strix occidentalis lucida) nest/roost habitat selection in Arizona and a comparison with single-scale modeling results

Treesearch

Brad C. Timm; Kevin McGarigal; Samuel A. Cushman; Joseph L. Ganey

2016-01-01

Efficacy of future habitat selection studies will benefit by taking a multi-scale approach. In addition to potentially providing increased explanatory power and predictive capacity, multi-scale habitat models enhance our understanding of the scales at which species respond to their environment, which is critical knowledge required to implement effective...

Multiscale System Theory

DTIC Science & Technology

1990-02-21

LIDS-P-1953 Multiscale System Theory Albert Benveniste IRISA-INRIA, Campus de Beaulieu 35042 RENNES CEDEX, FRANCE Ramine Nikoukhah INRIA...TITLE AND SUBTITLE Multiscale System Theory 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e...the development of a corresponding system theory and a theory of stochastic processes and their estimation. The research presented in this and several

Characterization of Cyclohexanone Inclusions in Class 1 RDX

DTIC Science & Technology

2014-06-01

characterized with respect to solvent inclusions in support of a U.S. Army Research Laboratory (ARL) program to model Multiscale Response of Energetic...pertinent to their modeling effort under the Multiscale Response of Energetic Materials (MREM) program, and the Weapons and Materials Research...support of a U.S. Army Research Laboratory (ARL) initiative called “ Multiscale Modeling of Energetic Materials” (MREM). The MREM program aims, for

Statistical Field Estimation for Complex Coastal Regions and Archipelagos (PREPRINT)

DTIC Science & Technology

2011-04-09

and study the computational properties of these schemes. Specifically, we extend a multiscale Objective Analysis (OA) approach to complex coastal...computational properties of these schemes. Specifically, we extend a multiscale Objective Analysis (OA) approach to complex coastal regions and... multiscale free-surface code builds on the primitive-equation model of the Harvard Ocean Predic- tion System (HOPS, Haley et al. (2009)). Additionally

Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing

DTIC Science & Technology

2016-07-15

AFRL-AFOSR-JP-TR-2016-0068 Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing Hean-Teik...SUBTITLE Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER... electromagnetics to the application in microwave remote sensing as well as extension of modelling capability with computational flexibility to study

Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing

DTIC Science & Technology

2016-07-15

AFRL-AFOSR-JP-TR-2016-0068 Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing Hean-Teik...SUBTITLE Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER...electromagnetics to the application in microwave remote sensing as well as extension of modelling capability with computational flexibility to study

Understanding multiple levels of norms about teen pregnancy and their relationships to teens' sexual behaviors.

PubMed

Mollborn, Stefanie; Domingue, Benjamin W; Boardman, Jason D

2014-06-01

Researchers seeking to understand teen sexual behaviors often turn to age norms, but they are difficult to measure quantitatively. Previous work has usually inferred norms from behavioral patterns or measured group-level norms at the individual level, ignoring multiple reference groups. Capitalizing on the multilevel design of the Add Health survey, we measure teen pregnancy norms perceived by teenagers, as well as average norms at the school and peer network levels. School norms predict boys' perceived norms, while peer network norms predict girls' perceived norms. Peer network and individually perceived norms against teen pregnancy independently and negatively predict teens' likelihood of sexual intercourse. Perceived norms against pregnancy predict increased likelihood of contraception among sexually experienced girls, but sexually experienced boys' contraceptive behavior is more complicated: When both the boy and his peers or school have stronger norms against teen pregnancy he is more likely to contracept, and in the absence of school or peer norms against pregnancy, boys who are embarrassed are less likely to contracept. We conclude that: (1) patterns of behavior cannot adequately operationalize teen pregnancy norms, (2) norms are not simply linked to behaviors through individual perceptions, and (3) norms at different levels can operate independently of each other, interactively, or in opposition. This evidence creates space for conceptualizations of agency, conflict, and change that can lead to progress in understanding age norms and sexual behaviors.

Understanding multiple levels of norms about teen pregnancy and their relationships to teens’ sexual behaviors

PubMed Central

Mollborn, Stefanie; Domingue, Benjamin W.; Boardman, Jason D.

2014-01-01

Researchers seeking to understand teen sexual behaviors often turn to age norms, but they are difficult to measure quantitatively. Previous work has usually inferred norms from behavioral patterns or measured group-level norms at the individual level, ignoring multiple reference groups. Capitalizing on the multilevel design of the Add Health survey, we measure teen pregnancy norms perceived by teenagers, as well as average norms at the school and peer network levels. School norms predict boys’ perceived norms, while peer network norms predict girls’ perceived norms. Peer network and individually perceived norms against teen pregnancy independently and negatively predict teens’ likelihood of sexual intercourse. Perceived norms against pregnancy predict increased likelihood of contraception among sexually experienced girls, but sexually experienced boys’ contraceptive behavior is more complicated: When both the boy and his peers or school have stronger norms against teen pregnancy he is more likely to contracept, and in the absence of school or peer norms against pregnancy, boys who are embarrassed are less likely to contracept. We conclude that: (1) patterns of behavior cannot adequately operationalize teen pregnancy norms, (2) norms are not simply linked to behaviors through individual perceptions, and (3) norms at different levels can operate independently of each other, interactively, or in opposition. This evidence creates space for conceptualizations of agency, conflict, and change that can lead to progress in understanding age norms and sexual behaviors. PMID:25104920

Norm-Aware Socio-Technical Systems

NASA Astrophysics Data System (ADS)

Savarimuthu, Bastin Tony Roy; Ghose, Aditya

The following sections are included: * Introduction * The Need for Norm-Aware Systems * Norms in human societies * Why should software systems be norm-aware? * Case Studies of Norm-Aware Socio-Technical Systems * Human-computer interactions * Virtual environments and multi-player online games * Extracting norms from big data and software repositories * Norms and Sustainability * Sustainability and green ICT * Norm awareness through software systems * Where To, From Here? * Conclusions

A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2012-01-01

A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

Multiscale modeling of a low magnetostrictive Fe-27wt%Co-0.5wt%Cr alloy

NASA Astrophysics Data System (ADS)

Savary, M.; Hubert, O.; Helbert, A. L.; Baudin, T.; Batonnet, R.; Waeckerlé, T.

2018-05-01

The present paper deals with the improvement of a multi-scale approach describing the magneto-mechanical coupling of Fe-27wt%Co-0.5wt%Cr alloy. The magnetostriction behavior is demonstrated as very different (low magnetostriction vs. high magnetostriction) when this material is submitted to two different final annealing conditions after cold rolling. The numerical data obtained from a multi-scale approach are in accordance with experimental data corresponding to the high magnetostriction level material. A bi-domain structure hypothesis is employed to explain the low magnetostriction behavior, in accordance with the effect of an applied tensile stress. A modification of the multiscale approach is proposed to match this result.

Generalization Performance of Regularized Ranking With Multiscale Kernels.

PubMed

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

Multiscale hidden Markov models for photon-limited imaging

NASA Astrophysics Data System (ADS)

Nowak, Robert D.

1999-06-01

Photon-limited image analysis is often hindered by low signal-to-noise ratios. A novel Bayesian multiscale modeling and analysis method is developed in this paper to assist in these challenging situations. In addition to providing a very natural and useful framework for modeling an d processing images, Bayesian multiscale analysis is often much less computationally demanding compared to classical Markov random field models. This paper focuses on a probabilistic graph model called the multiscale hidden Markov model (MHMM), which captures the key inter-scale dependencies present in natural image intensities. The MHMM framework presented here is specifically designed for photon-limited imagin applications involving Poisson statistics, and applications to image intensity analysis are examined.

Deep multi-scale convolutional neural network for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2011-01-01

A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

Characterising Dynamic Instability in High Water-Cut Oil-Water Flows Using High-Resolution Microwave Sensor Signals

NASA Astrophysics Data System (ADS)

Liu, Weixin; Jin, Ningde; Han, Yunfeng; Ma, Jing

2018-06-01

In the present study, multi-scale entropy algorithm was used to characterise the complex flow phenomena of turbulent droplets in high water-cut oil-water two-phase flow. First, we compared multi-scale weighted permutation entropy (MWPE), multi-scale approximate entropy (MAE), multi-scale sample entropy (MSE) and multi-scale complexity measure (MCM) for typical nonlinear systems. The results show that MWPE presents satisfied variability with scale and anti-noise ability. Accordingly, we conducted an experiment of vertical upward oil-water two-phase flow with high water-cut and collected the signals of a high-resolution microwave resonant sensor, based on which two indexes, the entropy rate and mean value of MWPE, were extracted. Besides, the effects of total flow rate and water-cut on these two indexes were analysed. Our researches show that MWPE is an effective method to uncover the dynamic instability of oil-water two-phase flow with high water-cut.

Multiscale Shannon's Entropy Modeling of Orientation and Distance in Steel Fiber Micro-Tomography Data.

PubMed

Chiverton, John P; Ige, Olubisi; Barnett, Stephanie J; Parry, Tony

2017-11-01

This paper is concerned with the modeling and analysis of the orientation and distance between steel fibers in X-ray micro-tomography data. The advantage of combining both orientation and separation in a model is that it helps provide a detailed understanding of how the steel fibers are arranged, which is easy to compare. The developed models are designed to summarize the randomness of the orientation distribution of the steel fibers both locally and across an entire volume based on multiscale entropy. Theoretical modeling, simulation, and application to real imaging data are shown here. The theoretical modeling of multiscale entropy for orientation includes a proof showing the final form of the multiscale taken over a linear range of scales. A series of image processing operations are also included to overcome interslice connectivity issues to help derive the statistical descriptions of the orientation distributions of the steel fibers. The results demonstrate that multiscale entropy provides unique insights into both simulated and real imaging data of steel fiber reinforced concrete.

Multiscale modeling and simulation of brain blood flow

NASA Astrophysics Data System (ADS)

Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em

2016-02-01

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.

Multiscale Modeling of Structurally-Graded Materials Using Discrete Dislocation Plasticity Models and Continuum Crystal Plasticity Models

NASA Technical Reports Server (NTRS)

Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.

2012-01-01

A multiscale modeling methodology that combines the predictive capability of discrete dislocation plasticity and the computational efficiency of continuum crystal plasticity is developed. Single crystal configurations of different grain sizes modeled with periodic boundary conditions are analyzed using discrete dislocation plasticity (DD) to obtain grain size-dependent stress-strain predictions. These relationships are mapped into crystal plasticity parameters to develop a multiscale DD/CP model for continuum level simulations. A polycrystal model of a structurally-graded microstructure is developed, analyzed and used as a benchmark for comparison between the multiscale DD/CP model and the DD predictions. The multiscale DD/CP model follows the DD predictions closely up to an initial peak stress and then follows a strain hardening path that is parallel but somewhat offset from the DD predictions. The difference is believed to be from a combination of the strain rate in the DD simulation and the inability of the DD/CP model to represent non-monotonic material response.

Using the PORS Problems to Examine Evolutionary Optimization of Multiscale Systems

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

Reinhart, Zachary; Molian, Vaelan; Bryden, Kenneth

2013-01-01

Nearly all systems of practical interest are composed of parts assembled across multiple scales. For example, an agrodynamic system is composed of flora and fauna on one scale; soil types, slope, and water runoff on another scale; and management practice and yield on another scale. Or consider an advanced coal-fired power plant: combustion and pollutant formation occurs on one scale, the plant components on another scale, and the overall performance of the power system is measured on another. In spite of this, there are few practical tools for the optimization of multiscale systems. This paper examines multiscale optimization of systemsmore » composed of discrete elements using the plus-one-recall-store (PORS) problem as a test case or study problem for multiscale systems. From this study, it is found that by recognizing the constraints and patterns present in discrete multiscale systems, the solution time can be significantly reduced and much more complex problems can be optimized.« less

Developing a novel hierarchical approach for multiscale structural reliability predictions for ultra-high consequence applications

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

Emery, John M.; Coffin, Peter; Robbins, Brian A.

Microstructural variabilities are among the predominant sources of uncertainty in structural performance and reliability. We seek to develop efficient algorithms for multiscale calcu- lations for polycrystalline alloys such as aluminum alloy 6061-T6 in environments where ductile fracture is the dominant failure mode. Our approach employs concurrent multiscale methods, but does not focus on their development. They are a necessary but not sufficient ingredient to multiscale reliability predictions. We have focused on how to efficiently use concurrent models for forward propagation because practical applications cannot include fine-scale details throughout the problem domain due to exorbitant computational demand. Our approach begins withmore » a low-fidelity prediction at the engineering scale that is sub- sequently refined with multiscale simulation. The results presented in this report focus on plasticity and damage at the meso-scale, efforts to expedite Monte Carlo simulation with mi- crostructural considerations, modeling aspects regarding geometric representation of grains and second-phase particles, and contrasting algorithms for scale coupling.« less

Multiscale Data Assimilation

DTIC Science & Technology

2014-09-30

good test 3 case to study the multiscale data assimilation capabilities of our GMM-DO filter. We also performed stochastic simulations with our DO...Morakot and internal tides. The ignorance score and Kullback - Leibler divergence were employed to measure the skill of the multiscale pdf forecasts...read off from the posterior of the augmented state vector. We implemented this new smoother and tested it using a 2D-in-space stochastic flow exiting

Multiscale Modeling in the Clinic: Drug Design and Development

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

Clancy, Colleen E.; An, Gary; Cannon, William R.

A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions tomore » guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.« less

Generalized multiscale finite-element method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

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

Gao, Kai; Fu, Shubin; Gibson, Richard L.

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less

Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

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

Gao, Kai, E-mail: kaigao87@gmail.com; Fu, Shubin, E-mail: shubinfu89@gmail.com; Gibson, Richard L., E-mail: gibson@tamu.edu

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less

Generalized multiscale finite-element method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

DOE PAGES

Gao, Kai; Fu, Shubin; Gibson, Richard L.; ...

2015-04-14

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less

Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

Bio-inspired configurable multiscale extracellular matrix-like structures for functional alignment and guided orientation of cells.

PubMed

Bae, Won-Gyu; Kim, Jangho; Choung, Yun-Hoon; Chung, Yesol; Suh, Kahp Y; Pang, Changhyun; Chung, Jong Hoon; Jeong, Hoon Eui

2015-11-01

Inspired by the hierarchically organized protein fibers in extracellular matrix (ECM) as well as the physiological importance of multiscale topography, we developed a simple but robust method for the design and manipulation of precisely controllable multiscale hierarchical structures using capillary force lithography in combination with an original wrinkling technique. In this study, based on our proposed fabrication technology, we approached a conceptual platform that can mimic the hierarchically multiscale topographical and orientation cues of the ECM for controlling cell structure and function. We patterned the polyurethane acrylate-based nanotopography with various orientations on the microgrooves, which could provide multiscale topography signals of ECM to control single and multicellular morphology and orientation with precision. Using our platforms, we found that the structures and orientations of fibroblast cells were greatly influenced by the nanotopography, rather than the microtopography. We also proposed a new approach that enables the generation of native ECM having nanofibers in specific three-dimensional (3D) configurations by culturing fibroblast cells on the multiscale substrata. We suggest that our methodology could be used as efficient strategies for the design and manipulation of various functional platforms, including well-defined 3D tissue structures for advanced regenerative medicine applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

PubMed Central

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

Multi-scale graph-cut algorithm for efficient water-fat separation.

PubMed

Berglund, Johan; Skorpil, Mikael

2017-09-01

To improve the accuracy and robustness to noise in water-fat separation by unifying the multiscale and graph cut based approaches to B 0 -correction. A previously proposed water-fat separation algorithm that corrects for B 0 field inhomogeneity in 3D by a single quadratic pseudo-Boolean optimization (QPBO) graph cut was incorporated into a multi-scale framework, where field map solutions are propagated from coarse to fine scales for voxels that are not resolved by the graph cut. The accuracy of the single-scale and multi-scale QPBO algorithms was evaluated against benchmark reference datasets. The robustness to noise was evaluated by adding noise to the input data prior to water-fat separation. Both algorithms achieved the highest accuracy when compared with seven previously published methods, while computation times were acceptable for implementation in clinical routine. The multi-scale algorithm was more robust to noise than the single-scale algorithm, while causing only a small increase (+10%) of the reconstruction time. The proposed 3D multi-scale QPBO algorithm offers accurate water-fat separation, robustness to noise, and fast reconstruction. The software implementation is freely available to the research community. Magn Reson Med 78:941-949, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Ways of giving benefits in marriage: norm use, relationship satisfaction, and attachment-related variability.

PubMed

Clark, Margaret S; Lemay, Edward P; Graham, Steven M; Pataki, Sherri P; Finkel, Eli J

2010-07-01

Couples reported on bases for giving support and on relationship satisfaction just prior to and approximately 2 years into marriage. Overall, a need-based, noncontingent (communal) norm was seen as ideal and was followed, and greater use of this norm was linked to higher relationship satisfaction. An exchange norm was seen as not ideal and was followed significantly less frequently than was a communal norm; by 2 years into marriage, greater use of an exchange norm was linked with lower satisfaction. Insecure attachment predicted greater adherence to an exchange norm. Idealization of and adherence to a communal norm dropped slightly across time. As idealization of a communal norm and own use and partner use of a communal norm decreased, people high in avoidance increased their use of an exchange norm, whereas people low in avoidance decreased their use of an exchange norm. Anxious individuals evidenced tighter links between norm use and marital satisfaction relative to nonanxious individuals. Overall, a picture of people valuing a communal norm and striving toward adherence to a communal norm emerged, with secure individuals doing so with more success and equanimity across time than insecure individuals.

Gyrokinetic predictions of multiscale transport in a DIII-D ITER baseline discharge

NASA Astrophysics Data System (ADS)

Holland, C.; Howard, N. T.; Grierson, B. A.

2017-06-01

New multiscale gyrokinetic simulations predict that electron energy transport in a DIII-D ITER baseline discharge with dominant electron heating and low input torque is multiscale in nature, with roughly equal amounts of the electron energy flux Q e coming from long wavelength ion-scale (k y ρ s  <  1) and short wavelength electron-scale (k y ρ s  >  1) fluctuations when the gyrokinetic results match independent power balance calculations. Corresponding conventional ion-scale simulations are able to match the power balance ion energy flux Q i, but systematically underpredict Q e when doing so. Significant nonlinear cross-scale couplings are observed in the multiscale simulations, but the exact simulation predictions are found to be extremely sensitive to variations of model input parameters within experimental uncertainties. Most notably, depending upon the exact value of the equilibrium E  ×  B shearing rate γ E×B used, either enhancement or suppression of the long-wavelength turbulence and transport levels in the multiscale simulations is observed relative to what is predicted by ion-scale simulations. While the enhancement of the long wavelength fluctuations by inclusion of the short wavelength turbulence was previously observed in similar multiscale simulations of an Alcator C-Mod L-mode discharge, these new results show for the first time a complete suppression of long-wavelength turbulence in a multiscale simulation, for parameters at which conventional ion-scale simulation predicts small but finite levels of low-k turbulence and transport consistent with the power balance Q i. Although computational resource limitations prevent a fully rigorous validation assessment of these new results, they provide significant new evidence that electron energy transport in burning plasmas is likely to have a strong multiscale character, with significant nonlinear cross-scale couplings that must be fully understood to predict the performance of those plasmas with confidence.

Development of an integrated utilities billing management system for the Navy Public Works Center San Diego, California

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

Monsabert, S. de; Lemmer, H.; Dinwiddie, D.

1995-10-01

In the past, most buildings, structures, and ship visits were not metered, and flat estimates were calculated based on various estimating techniques. The decomposition process was further complicated by the fact that many of the meters monitor consumption values only and do not provide demand or time of use data. This method of billing provides no incentives to the PWC customers to implement energy conservation programs, including load shedding, Energy Monitoring and Control Systems (EMCS), building shell improvements, low flow toilets and shower heads, efficient lighting systems, or other energy savings alternatives. Similarly, the method had no means of adjustmentmore » for seasonal or climatic variations outside of the norm. As an alternative to flat estimates, the Customized Utility Billing Integrated Control (CUBIC) system and the Graphical Data Input System (GDIS) were developed to better manage the data to the major claimant area users based on utilities usage factors, building size, weather data, and hours of operation. GDIS is a graphical database that assists PWC engineers in the development and maintenance of single-line utility diagrams of the facilities and meters. It functions as a drawing associate system and is written in AutoLISP for AutoCAD version 12. GDIS interprets the drawings and provides the facility-to-meter and meter-to-meter hierarchy data that are used by the CUBIC to allocate the billings. This paper reviews the design, development and implementation aspects of CUBIC/GDIS and discusses the benefits of this improved utilities management system.« less

Deformation field heterogeneity in punch indentation

PubMed Central

Murthy, Tejas G.; Saldana, Christopher; Hudspeth, Matthew; M'Saoubi, Rachid

2014-01-01

Plastic heterogeneity in indentation is fundamental for understanding mechanics of hardness testing and impression-based deformation processing methods. The heterogeneous deformation underlying plane-strain indentation was investigated in plastic loading of copper by a flat punch. Deformation parameters were measured, in situ, by tracking the motion of asperities in high-speed optical imaging. These measurements were coupled with multi-scale analyses of strength, microstructure and crystallographic texture in the vicinity of the indentation. Self-consistency is demonstrated in description of the deformation field using the in situ mechanics-based measurements and post-mortem materials characterization. Salient features of the punch indentation process elucidated include, among others, the presence of a dead-metal zone underneath the indenter, regions of intense strain rate (e.g. slip lines) and extent of the plastic flow field. Perhaps more intriguing are the transitions between shear-type and compression-type deformation modes over the indentation region that were quantified by the high-resolution crystallographic texture measurements. The evolution of the field concomitant to the progress of indentation is discussed and primary differences between the mechanics of indentation for a rigid perfectly plastic material and a strain-hardening material are described. PMID:24910521

Image analysis for material characterisation

NASA Astrophysics Data System (ADS)

Livens, Stefan

In this thesis, a number of image analysis methods are presented as solutions to two applications concerning the characterisation of materials. Firstly, we deal with the characterisation of corrosion images, which is handled using a multiscale texture analysis method based on wavelets. We propose a feature transformation that deals with the problem of rotation invariance. Classification is performed with a Learning Vector Quantisation neural network and with combination of outputs. In an experiment, 86,2% of the images showing either pit formation or cracking, are correctly classified. Secondly, we develop an automatic system for the characterisation of silver halide microcrystals. These are flat crystals with a triangular or hexagonal base and a thickness in the 100 to 200 nm range. A light microscope is used to image them. A novel segmentation method is proposed, which allows to separate agglomerated crystals. For the measurement of shape, the ratio between the largest and the smallest radius yields the best results. The thickness measurement is based on the interference colours that appear for light reflected at the crystals. The mean colour of different thickness populations is determined, from which a calibration curve is derived. With this, the thickness of new populations can be determined accurately.

Multiscale Modeling and Simulation of Material Processing

DTIC Science & Technology

2006-07-01

As a re- GIMP simulations . Fig. 2 illustrates the contact algo- suit, MPM using a single mesh tends to induce early con- rithm for the contact pair ...21-07-2006 Final Performance Report 05-01-2003 - 04-30-2006 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Multiscale Modeling and Simulation of Material...development of scaling laws for multiscale simulations from atomistic to continuum using material testing techniques, such as tension and indentation

Smart Functional Nanoenergetic Materials

DTIC Science & Technology

2012-08-01

Integrated Multiscale Organization of Energetic Materials Many biological and physical objects derive their unique properties through an...ve,  .  ancau , an   .  oss ,  g   nergy  u Nanocomposites obtained by DNA‐Directed Assembly, Adv. Functional Materials, 22,  323, 2012 Multiscale ...to any Multiscale Energetic Composites Fabricated on pSi Substrates • Si wafers (highly doped p-type) were photo lithographically patterned using

Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation

PubMed Central

Xu, Feng; Moon, Sangjun; Zhang, Xiaohui; Shao, Lei; Song, Young Seok; Demirci, Utkan

2010-01-01

Cells and tissues undergo complex physical processes during cryopreservation. Understanding the underlying physical phenomena is critical to improve current cryopreservation methods and to develop new techniques. Here, we describe multi-scale approaches for modelling cell and tissue cryopreservation including heat transfer at macroscale level, crystallization, cell volume change and mass transport across cell membranes at microscale level. These multi-scale approaches allow us to study cell and tissue cryopreservation. PMID:20047939

Coherent structures shed by multiscale cut-in trailing edge serrations on lifting wings

NASA Astrophysics Data System (ADS)

Prigent, S. L.; Buxton, O. R. H.; Bruce, P. J. K.

2017-07-01

This experimental study presents the effect of multiscale cut-in trailing edge serrations on the coherent structures shed into the wake of a lifting wing. Two-probe span-wise hot-wire traverses are performed to study spectra, coherence, and phase shift. In addition, planar particle image velocimetry is used to study the spatio-temporal structure of the vortices shed by the airfoils. Compared with a single tone sinusoidal serration, the multiscale ones reduce the vortex shedding energy as well as the span-wise coherence. Results indicate that the vortex shedding is locked into an arch-shaped cell structure. This structure is weakened by the multiscale patterns, which explains the reduction in both shedding energy and coherence.

Response normalization and blur adaptation: Data and multi-scale model

PubMed Central

Elliott, Sarah L.; Georgeson, Mark A.; Webster, Michael A.

2011-01-01

Adapting to blurred or sharpened images alters perceived blur of a focused image (M. A. Webster, M. A. Georgeson, & S. M. Webster, 2002). We asked whether blur adaptation results in (a) renormalization of perceived focus or (b) a repulsion aftereffect. Images were checkerboards or 2-D Gaussian noise, whose amplitude spectra had (log–log) slopes from −2 (strongly blurred) to 0 (strongly sharpened). Observers adjusted the spectral slope of a comparison image to match different test slopes after adaptation to blurred or sharpened images. Results did not show repulsion effects but were consistent with some renormalization. Test blur levels at and near a blurred or sharpened adaptation level were matched by more focused slopes (closer to 1/f) but with little or no change in appearance after adaptation to focused (1/f) images. A model of contrast adaptation and blur coding by multiple-scale spatial filters predicts these blur aftereffects and those of Webster et al. (2002). A key proposal is that observers are pre-adapted to natural spectra, and blurred or sharpened spectra induce changes in the state of adaptation. The model illustrates how norms might be encoded and recalibrated in the visual system even when they are represented only implicitly by the distribution of responses across multiple channels. PMID:21307174

The Condensate Database for Big Data Analysis

NASA Astrophysics Data System (ADS)

Gallaher, D. W.; Lv, Q.; Grant, G.; Campbell, G. G.; Liu, Q.

2014-12-01

Although massive amounts of cryospheric data have been and are being generated at an unprecedented rate, a vast majority of the otherwise valuable data have been ``sitting in the dark'', with very limited quality assurance or runtime access for higher-level data analytics such as anomaly detection. This has significantly hindered data-driven scientific discovery and advances in the polar research and Earth sciences community. In an effort to solve this problem we have investigated and developed innovative techniques for the construction of ``condensate database'', which is much smaller than the original data yet still captures the key characteristics (e.g., spatio-temporal norm and changes). In addition we are taking advantage of parallel databases that make use of low cost GPU processors. As a result, efficient anomaly detection and quality assurance can be achieved with in-memory data analysis or limited I/O requests. The challenges lie in the fact that cryospheric data are massive and diverse, with normal/abnomal patterns spanning a wide range of spatial and temporal scales. This project consists of investigations in three main areas: (1) adaptive neighborhood-based thresholding in both space and time; (2) compressive-domain pattern detection and change analysis; and (3) hybrid and adaptive condensation of multi-modal, multi-scale cryospheric data.

Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

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

Jablonowski, Christiane

The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively withmore » advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project demonstrate significant advances in all six research areas. The major conclusions are that statically-adaptive variable-resolution modeling is currently becoming mature in the climate sciences, and that AMR holds outstanding promise for future-generation weather and climate models on high-performance computing architectures.« less

Using Peer Injunctive Norms to Predict Early Adolescent Cigarette Smoking Intentions

PubMed Central

Zaleski, Adam C.; Aloise-Young, Patricia A.

2013-01-01

The present study investigated the importance of the perceived injunctive norm to predict early adolescent cigarette smoking intentions. A total of 271 6th graders completed a survey that included perceived prevalence of friend smoking (descriptive norm), perceptions of friends’ disapproval of smoking (injunctive norm), and future smoking intentions. Participants also listed their five best friends, in which the actual injunctive norm was calculated. Results showed that smoking intentions were significantly correlated with the perceived injunctive norm but not with the actual injunctive norm. Secondly, the perceived injunctive norm predicted an additional 3.4% of variance in smoking intentions above and beyond the perceived descriptive norm. These results demonstrate the importance of the perceived injunctive norm in predicting early adolescent smoking intentions. PMID:24078745

Multiscale Methods for Nuclear Reactor Analysis

NASA Astrophysics Data System (ADS)

Collins, Benjamin S.

The ability to accurately predict local pin powers in nuclear reactors is necessary to understand the mechanisms that cause fuel pin failure during steady state and transient operation. In the research presented here, methods are developed to improve the local solution using high order methods with boundary conditions from a low order global solution. Several different core configurations were tested to determine the improvement in the local pin powers compared to the standard techniques, that use diffusion theory and pin power reconstruction (PPR). Two different multiscale methods were developed and analyzed; the post-refinement multiscale method and the embedded multiscale method. The post-refinement multiscale methods use the global solution to determine boundary conditions for the local solution. The local solution is solved using either a fixed boundary source or an albedo boundary condition; this solution is "post-refinement" and thus has no impact on the global solution. The embedded multiscale method allows the local solver to change the global solution to provide an improved global and local solution. The post-refinement multiscale method is assessed using three core designs. When the local solution has more energy groups, the fixed source method has some difficulties near the interface: however the albedo method works well for all cases. In order to remedy the issue with boundary condition errors for the fixed source method, a buffer region is used to act as a filter, which decreases the sensitivity of the solution to the boundary condition. Both the albedo and fixed source methods benefit from the use of a buffer region. Unlike the post-refinement method, the embedded multiscale method alters the global solution. The ability to change the global solution allows for refinement in areas where the errors in the few group nodal diffusion are typically large. The embedded method is shown to improve the global solution when it is applied to a MOX/LEU assembly interface, the fuel/reflector interface, and assemblies where control rods are inserted. The embedded method also allows for multiple solution levels to be applied in a single calculation. The addition of intermediate levels to the solution improves the accuracy of the method. Both multiscale methods considered here have benefits and drawbacks, but both can provide improvements over the current PPR methodology.

Social norms and their influence on eating behaviours.

PubMed

Higgs, Suzanne

2015-03-01

Social norms are implicit codes of conduct that provide a guide to appropriate action. There is ample evidence that social norms about eating have a powerful effect on both food choice and amounts consumed. This review explores the reasons why people follow social eating norms and the factors that moderate norm following. It is proposed that eating norms are followed because they provide information about safe foods and facilitate food sharing. Norms are a powerful influence on behaviour because following (or not following) norms is associated with social judgements. Norm following is more likely when there is uncertainty about what constitutes correct behaviour and when there is greater shared identity with the norm referent group. Social norms may affect food choice and intake by altering self-perceptions and/or by altering the sensory/hedonic evaluation of foods. The same neural systems that mediate the rewarding effects of food itself are likely to reinforce the following of eating norms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Radiomics Evaluation of Histological Heterogeneity Using Multiscale Textures Derived From 3D Wavelet Transformation of Multispectral Images.

PubMed

Chaddad, Ahmad; Daniel, Paul; Niazi, Tamim

2018-01-01

Colorectal cancer (CRC) is markedly heterogeneous and develops progressively toward malignancy through several stages which include stroma (ST), benign hyperplasia (BH), intraepithelial neoplasia (IN) or precursor cancerous lesion, and carcinoma (CA). Identification of the malignancy stage of CRC pathology tissues (PT) allows the most appropriate therapeutic intervention. This study investigates multiscale texture features extracted from CRC pathology sections using 3D wavelet transform (3D-WT) filter. Multiscale features were extracted from digital whole slide images of 39 patients that were segmented in a pre-processing step using an active contour model. The capacity for multiscale texture to compare and classify between PTs was investigated using ANOVA significance test and random forest classifier models, respectively. 12 significant features derived from the multiscale texture (i.e., variance, entropy, and energy) were found to discriminate between CRC grades at a significance value of p  < 0.01 after correction. Combining multiscale texture features lead to a better predictive capacity compared to prediction models based on individual scale features with an average (±SD) classification accuracy of 93.33 (±3.52)%, sensitivity of 88.33 (± 4.12)%, and specificity of 96.89 (± 3.88)%. Entropy was found to be the best classifier feature across all the PT grades with an average of the area under the curve (AUC) value of 91.17, 94.21, 97.70, 100% for ST, BH, IN, and CA, respectively. Our results suggest that multiscale texture features based on 3D-WT are sensitive enough to discriminate between CRC grades with the entropy feature, the best predictor of pathology grade.

Development of Multiscale Biological Image Data Analysis: Review of 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics, Santa Barbara, USA (BII06)

PubMed Central

Auer, Manfred; Peng, Hanchuan; Singh, Ambuj

2007-01-01

The 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics was held at Santa Barbara, on Sept 7–8, 2006. Based on the presentations at the workshop, we selected and compiled this collection of research articles related to novel algorithms and enabling techniques for bio- and biomedical image analysis, mining, visualization, and biology applications. PMID:17634090

Fast online generalized multiscale finite element method using constraint energy minimization

NASA Astrophysics Data System (ADS)

Chung, Eric T.; Efendiev, Yalchin; Leung, Wing Tat

2018-02-01

Local multiscale methods often construct multiscale basis functions in the offline stage without taking into account input parameters, such as source terms, boundary conditions, and so on. These basis functions are then used in the online stage with a specific input parameter to solve the global problem at a reduced computational cost. Recently, online approaches have been introduced, where multiscale basis functions are adaptively constructed in some regions to reduce the error significantly. In multiscale methods, it is desired to have only 1-2 iterations to reduce the error to a desired threshold. Using Generalized Multiscale Finite Element Framework [10], it was shown that by choosing sufficient number of offline basis functions, the error reduction can be made independent of physical parameters, such as scales and contrast. In this paper, our goal is to improve this. Using our recently proposed approach [4] and special online basis construction in oversampled regions, we show that the error reduction can be made sufficiently large by appropriately selecting oversampling regions. Our numerical results show that one can achieve a three order of magnitude error reduction, which is better than our previous methods. We also develop an adaptive algorithm and enrich in selected regions with large residuals. In our adaptive method, we show that the convergence rate can be determined by a user-defined parameter and we confirm this by numerical simulations. The analysis of the method is presented.

Parameters Selection for Bivariate Multiscale Entropy Analysis of Postural Fluctuations in Fallers and Non-Fallers Older Adults.

PubMed

Ramdani, Sofiane; Bonnet, Vincent; Tallon, Guillaume; Lagarde, Julien; Bernard, Pierre Louis; Blain, Hubert

2016-08-01

Entropy measures are often used to quantify the regularity of postural sway time series. Recent methodological developments provided both multivariate and multiscale approaches allowing the extraction of complexity features from physiological signals; see "Dynamical complexity of human responses: A multivariate data-adaptive framework," in Bulletin of Polish Academy of Science and Technology, vol. 60, p. 433, 2012. The resulting entropy measures are good candidates for the analysis of bivariate postural sway signals exhibiting nonstationarity and multiscale properties. These methods are dependant on several input parameters such as embedding parameters. Using two data sets collected from institutionalized frail older adults, we numerically investigate the behavior of a recent multivariate and multiscale entropy estimator; see "Multivariate multiscale entropy: A tool for complexity analysis of multichannel data," Physics Review E, vol. 84, p. 061918, 2011. We propose criteria for the selection of the input parameters. Using these optimal parameters, we statistically compare the multivariate and multiscale entropy values of postural sway data of non-faller subjects to those of fallers. These two groups are discriminated by the resulting measures over multiple time scales. We also demonstrate that the typical parameter settings proposed in the literature lead to entropy measures that do not distinguish the two groups. This last result confirms the importance of the selection of appropriate input parameters.

Coupled numerical approach combining finite volume and lattice Boltzmann methods for multi-scale multi-physicochemical processes

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

Chen, Li; He, Ya-Ling; Kang, Qinjun

2013-12-15

A coupled (hybrid) simulation strategy spatially combining the finite volume method (FVM) and the lattice Boltzmann method (LBM), called CFVLBM, is developed to simulate coupled multi-scale multi-physicochemical processes. In the CFVLBM, computational domain of multi-scale problems is divided into two sub-domains, i.e., an open, free fluid region and a region filled with porous materials. The FVM and LBM are used for these two regions, respectively, with information exchanged at the interface between the two sub-domains. A general reconstruction operator (RO) is proposed to derive the distribution functions in the LBM from the corresponding macro scalar, the governing equation of whichmore » obeys the convection–diffusion equation. The CFVLBM and the RO are validated in several typical physicochemical problems and then are applied to simulate complex multi-scale coupled fluid flow, heat transfer, mass transport, and chemical reaction in a wall-coated micro reactor. The maximum ratio of the grid size between the FVM and LBM regions is explored and discussed. -- Highlights: •A coupled simulation strategy for simulating multi-scale phenomena is developed. •Finite volume method and lattice Boltzmann method are coupled. •A reconstruction operator is derived to transfer information at the sub-domains interface. •Coupled multi-scale multiple physicochemical processes in micro reactor are simulated. •Techniques to save computational resources and improve the efficiency are discussed.« less

Self adaptive multi-scale morphology AVG-Hat filter and its application to fault feature extraction for wheel bearing

NASA Astrophysics Data System (ADS)

Deng, Feiyue; Yang, Shaopu; Tang, Guiji; Hao, Rujiang; Zhang, Mingliang

2017-04-01

Wheel bearings are essential mechanical components of trains, and fault detection of the wheel bearing is of great significant to avoid economic loss and casualty effectively. However, considering the operating conditions, detection and extraction of the fault features hidden in the heavy noise of the vibration signal have become a challenging task. Therefore, a novel method called adaptive multi-scale AVG-Hat morphology filter (MF) is proposed to solve it. The morphology AVG-Hat operator not only can suppress the interference of the strong background noise greatly, but also enhance the ability of extracting fault features. The improved envelope spectrum sparsity (IESS), as a new evaluation index, is proposed to select the optimal filtering signal processed by the multi-scale AVG-Hat MF. It can present a comprehensive evaluation about the intensity of fault impulse to the background noise. The weighted coefficients of the different scale structural elements (SEs) in the multi-scale MF are adaptively determined by the particle swarm optimization (PSO) algorithm. The effectiveness of the method is validated by analyzing the real wheel bearing fault vibration signal (e.g. outer race fault, inner race fault and rolling element fault). The results show that the proposed method could improve the performance in the extraction of fault features effectively compared with the multi-scale combined morphological filter (CMF) and multi-scale morphology gradient filter (MGF) methods.

Research Collaborations | NREL

Science.gov Websites

University, and the University of Colorado at Boulder. Visit CRES ICMC-International Center for Multiscale the art in multiscale characterization. Of special interest are materials for photovoltaic, battery

American Society of Composites, 32nd Technical Conference

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

Aitharaju, Venkat; Wollschlager, Jeffrey; Plakomytis2, Dimitrios

This paper will present a general methodology by which weave draping manufacturing simulation results can be utilized to include the effects of weave draping and scissor angle in a structural multiscale simulation. While the methodology developed is general in nature, this paper will specifically demonstrate the methodology applied to a truncated pyramid, utilizing manufacturing simulation weave draping results from ESI PAM-FORM, and multiscale simulation using Altair Multiscale Designer (MDS) and OptiStruct. From a multiscale simulation perspective, the weave draping manufacturing simulation results will be used to develop a series of woven unit cells which cover the range of weave scissormore » angles existing within the part. For each unit cell, a multiscale material model will be developed, and applied to the corresponding spatial locations within the structural simulation mesh. In addition, the principal material orientation will be mapped from the wave draping manufacturing simulation mesh to the structural simulation mesh using Altair HyperMesh mapping technology. Results of the coupled simulation will be compared and verified against experimental data of the same available via General Motors (GM) Department of Energy (DOE) project.« less

Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success.

PubMed

Yankeelov, Thomas E; An, Gary; Saut, Oliver; Luebeck, E Georg; Popel, Aleksander S; Ribba, Benjamin; Vicini, Paolo; Zhou, Xiaobo; Weis, Jared A; Ye, Kaiming; Genin, Guy M

2016-09-01

Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing and assessing treatment strategies that account for these hierarchies. The basic science underlying these modeling efforts is maturing into a new discipline that is close to influencing and facilitating clinical successes. The purpose of this review is to capture the state-of-the-art as well as the key barriers to success for multi-scale modeling in clinical oncology. We begin with a summary of the long-envisioned promise of multi-scale modeling in clinical oncology, including the synthesis of disparate data types into models that reveal underlying mechanisms and allow for experimental testing of hypotheses. We then evaluate the mathematical techniques employed most widely and present several examples illustrating their application as well as the current gap between pre-clinical and clinical applications. We conclude with a discussion of what we view to be the key challenges and opportunities for multi-scale modeling in clinical oncology.

A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system

PubMed Central

Li, Xin; Liu, Shaomin; Xiao, Qin; Ma, Mingguo; Jin, Rui; Che, Tao; Wang, Weizhen; Hu, Xiaoli; Xu, Ziwei; Wen, Jianguang; Wang, Liangxu

2017-01-01

We introduce a multiscale dataset obtained from Heihe Watershed Allied Telemetry Experimental Research (HiWATER) in an oasis-desert area in 2012. Upscaling of eco-hydrological processes on a heterogeneous surface is a grand challenge. Progress in this field is hindered by the poor availability of multiscale observations. HiWATER is an experiment designed to address this challenge through instrumentation on hierarchically nested scales to obtain multiscale and multidisciplinary data. The HiWATER observation system consists of a flux observation matrix of eddy covariance towers, large aperture scintillometers, and automatic meteorological stations; an eco-hydrological sensor network of soil moisture and leaf area index; hyper-resolution airborne remote sensing using LiDAR, imaging spectrometer, multi-angle thermal imager, and L-band microwave radiometer; and synchronical ground measurements of vegetation dynamics, and photosynthesis processes. All observational data were carefully quality controlled throughout sensor calibration, data collection, data processing, and datasets generation. The data are freely available at figshare and the Cold and Arid Regions Science Data Centre. The data should be useful for elucidating multiscale eco-hydrological processes and developing upscaling methods. PMID:28654086

Multi-scale streamflow variability responses to precipitation over the headwater catchments in southern China

NASA Astrophysics Data System (ADS)

Niu, Jun; Chen, Ji; Wang, Keyi; Sivakumar, Bellie

2017-08-01

This paper examines the multi-scale streamflow variability responses to precipitation over 16 headwater catchments in the Pearl River basin, South China. The long-term daily streamflow data (1952-2000), obtained using a macro-scale hydrological model, the Variable Infiltration Capacity (VIC) model, and a routing scheme, are studied. Temporal features of streamflow variability at 10 different timescales, ranging from 6 days to 8.4 years, are revealed with the Haar wavelet transform. The principal component analysis (PCA) is performed to categorize the headwater catchments with the coherent modes of multi-scale wavelet spectra. The results indicate that three distinct modes, with different variability distributions at small timescales and seasonal scales, can explain 95% of the streamflow variability. A large majority of the catchments (i.e. 12 out of 16) exhibit consistent mode feature on multi-scale variability throughout three sub-periods (1952-1968, 1969-1984, and 1985-2000). The multi-scale streamflow variability responses to precipitation are identified to be associated with the regional flood and drought tendency over the headwater catchments in southern China.

Multiscale time-dependent density functional theory: Demonstration for plasmons.

PubMed

Jiang, Jiajian; Abi Mansour, Andrew; Ortoleva, Peter J

2017-08-07

Plasmon properties are of significant interest in pure and applied nanoscience. While time-dependent density functional theory (TDDFT) can be used to study plasmons, it becomes impractical for elucidating the effect of size, geometric arrangement, and dimensionality in complex nanosystems. In this study, a new multiscale formalism that addresses this challenge is proposed. This formalism is based on Trotter factorization and the explicit introduction of a coarse-grained (CG) structure function constructed as the Weierstrass transform of the electron wavefunction. This CG structure function is shown to vary on a time scale much longer than that of the latter. A multiscale propagator that coevolves both the CG structure function and the electron wavefunction is shown to bring substantial efficiency over classical propagators used in TDDFT. This efficiency follows from the enhanced numerical stability of the multiscale method and the consequence of larger time steps that can be used in a discrete time evolution. The multiscale algorithm is demonstrated for plasmons in a group of interacting sodium nanoparticles (15-240 atoms), and it achieves improved efficiency over TDDFT without significant loss of accuracy or space-time resolution.

Scale-specific effects: A report on multiscale analysis of acupunctured EEG in entropy and power

NASA Astrophysics Data System (ADS)

Song, Zhenxi; Deng, Bin; Wei, Xile; Cai, Lihui; Yu, Haitao; Wang, Jiang; Wang, Ruofan; Chen, Yingyuan

2018-02-01

Investigating acupuncture effects contributes to improving clinical application and understanding neuronal dynamics under external stimulation. In this report, we recorded electroencephalography (EEG) signals evoked by acupuncture at ST36 acupoint with three stimulus frequencies of 50, 100 and 200 times per minutes, and selected non-acupuncture EEGs as the control group. Multiscale analyses were introduced to investigate the possible acupuncture effects on complexity and power in multiscale level. Using multiscale weighted-permutation entropy, we found the significant effects on increased complexity degree in EEG signals induced by acupuncture. The comparison of three stimulation manipulations showed that 100 times/min generated most obvious effects, and affected most cortical regions. By estimating average power spectral density, we found decreased power induced by acupuncture. The joint distribution of entropy and power indicated an inverse correlation, and this relationship was weakened by acupuncture effects, especially under the manipulation of 100 times/min frequency. Above findings are more evident and stable in large scales than small scales, which suggests that multiscale analysis allows evaluating significant effects in specific scale and enables to probe the inherent characteristics underlying physiological signals.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success

PubMed Central

Yankeelov, Thomas E.; An, Gary; Saut, Oliver; Luebeck, E. Georg; Popel, Aleksander S.; Ribba, Benjamin; Vicini, Paolo; Zhou, Xiaobo; Weis, Jared A.; Ye, Kaiming; Genin, Guy M.

2016-01-01

Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing and assessing treatment strategies that account for these hierarchies. The basic science underlying these modeling efforts is maturing into a new discipline that is close to influencing and facilitating clinical successes. The purpose of this review is to capture the state-of-the-art as well as the key barriers to success for multi-scale modeling in clinical oncology. We begin with a summary of the long-envisioned promise of multi-scale modeling in clinical oncology, including the synthesis of disparate data types into models that reveal underlying mechanisms and allow for experimental testing of hypotheses. We then evaluate the mathematical techniques employed most widely and present several examples illustrating their application as well as the current gap between pre-clinical and clinical applications. We conclude with a discussion of what we view to be the key challenges and opportunities for multi-scale modeling in clinical oncology. PMID:27384942

Modeling Framework for Fracture in Multiscale Cement-Based Material Structures

PubMed Central

Qian, Zhiwei; Schlangen, Erik; Ye, Guang; van Breugel, Klaas

2017-01-01

Multiscale modeling for cement-based materials, such as concrete, is a relatively young subject, but there are already a number of different approaches to study different aspects of these classical materials. In this paper, the parameter-passing multiscale modeling scheme is established and applied to address the multiscale modeling problem for the integrated system of cement paste, mortar, and concrete. The block-by-block technique is employed to solve the length scale overlap challenge between the mortar level (0.1–10 mm) and the concrete level (1–40 mm). The microstructures of cement paste are simulated by the HYMOSTRUC3D model, and the material structures of mortar and concrete are simulated by the Anm material model. Afterwards the 3D lattice fracture model is used to evaluate their mechanical performance by simulating a uniaxial tensile test. The simulated output properties at a lower scale are passed to the next higher scale to serve as input local properties. A three-level multiscale lattice fracture analysis is demonstrated, including cement paste at the micrometer scale, mortar at the millimeter scale, and concrete at centimeter scale. PMID:28772948

Integrated multiscale biomaterials experiment and modelling: a perspective

PubMed Central

Buehler, Markus J.; Genin, Guy M.

2016-01-01

Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126

Transition between inverse and direct energy cascades in multiscale optical turbulence.

PubMed

Malkin, V M; Fisch, N J

2018-03-01

Multiscale turbulence naturally develops and plays an important role in many fluid, gas, and plasma phenomena. Statistical models of multiscale turbulence usually employ Kolmogorov hypotheses of spectral locality of interactions (meaning that interactions primarily occur between pulsations of comparable scales) and scale-invariance of turbulent pulsations. However, optical turbulence described by the nonlinear Schrodinger equation exhibits breaking of both the Kolmogorov locality and scale-invariance. A weaker form of spectral locality that holds for multi-scale optical turbulence enables a derivation of simplified evolution equations that reduce the problem to a single scale modeling. We present the derivation of these equations for Kerr media with random inhomogeneities. Then, we find the analytical solution that exhibits a transition between inverse and direct energy cascades in optical turbulence.

Multiscale Modeling of Damage Processes in fcc Aluminum: From Atoms to Grains

NASA Technical Reports Server (NTRS)

Glaessgen, E. H.; Saether, E.; Yamakov, V.

2008-01-01

Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, current analysis is limited to small domains and increasing the size of the MD domain quickly presents intractable computational demands. A preferred approach to surmount this computational limitation has been to combine continuum mechanics-based modeling procedures, such as the finite element method (FEM), with MD analyses thereby reducing the region of atomic scale refinement. Such multiscale modeling strategies can be divided into two broad classifications: concurrent multiscale methods that directly incorporate an atomistic domain within a continuum domain and sequential multiscale methods that extract an averaged response from the atomistic simulation for later use as a constitutive model in a continuum analysis.

Transition between inverse and direct energy cascades in multiscale optical turbulence

NASA Astrophysics Data System (ADS)

Malkin, V. M.; Fisch, N. J.

2018-03-01

Multiscale turbulence naturally develops and plays an important role in many fluid, gas, and plasma phenomena. Statistical models of multiscale turbulence usually employ Kolmogorov hypotheses of spectral locality of interactions (meaning that interactions primarily occur between pulsations of comparable scales) and scale-invariance of turbulent pulsations. However, optical turbulence described by the nonlinear Schrodinger equation exhibits breaking of both the Kolmogorov locality and scale-invariance. A weaker form of spectral locality that holds for multi-scale optical turbulence enables a derivation of simplified evolution equations that reduce the problem to a single scale modeling. We present the derivation of these equations for Kerr media with random inhomogeneities. Then, we find the analytical solution that exhibits a transition between inverse and direct energy cascades in optical turbulence.

Color Image Enhancement Using Multiscale Retinex Based on Particle Swarm Optimization Method

NASA Astrophysics Data System (ADS)

Matin, F.; Jeong, Y.; Kim, K.; Park, K.

2018-01-01

This paper introduces, a novel method for the image enhancement using multiscale retinex and practical swarm optimization. Multiscale retinex is widely used image enhancement technique which intemperately pertains on parameters such as Gaussian scales, gain and offset, etc. To achieve the privileged effect, the parameters need to be tuned manually according to the image. In order to handle this matter, a developed retinex algorithm based on PSO has been used. The PSO method adjusted the parameters for multiscale retinex with chromaticity preservation (MSRCP) attains better outcome to compare with other existing methods. The experimental result indicates that the proposed algorithm is an efficient one and not only provides true color loyalty in low light conditions but also avoid color distortion at the same time.

Graph-Based Norm Explanation

NASA Astrophysics Data System (ADS)

Croitoru, Madalina; Oren, Nir; Miles, Simon; Luck, Michael

Norms impose obligations, permissions and prohibitions on individual agents operating as part of an organisation. Typically, the purpose of such norms is to ensure that an organisation acts in some socially (or mutually) beneficial manner, possibly at the expense of individual agent utility. In this context, agents are normaware if they are able to reason about which norms are applicable to them, and to decide whether to comply with or ignore them. While much work has focused on the creation of norm-aware agents, much less has been concerned with aiding system designers in understanding the effects of norms on a system. The ability to understand such norm effects can aid the designer in avoiding incorrect norm specification, eliminating redundant norms and reducing normative conflict. In this paper, we address the problem of norm understanding by providing explanations as to why a norm is applicable, violated, or in some other state. We make use of conceptual graph based semantics to provide a graphical representation of the norms within a system. Given knowledge of the current and historical state of the system, such a representation allows for explanation of the state of norms, showing for example why they may have been activated or violated.

Associations of Perceived Norms With Intentions to Learn Genomic Sequencing Results: Roles for Attitudes and Ambivalence

PubMed Central

Reid, Allecia E.; Taber, Jennifer M.; Ferrer, Rebecca A.; Biesecker, Barbara B.; Lewis, Katie L.; Biesecker, Leslie G.; Klein, William M. P.

2018-01-01

Objective Genomic sequencing is becoming increasingly accessible, highlighting the need to understand the social and psychological factors that drive interest in receiving testing results. These decisions may depend on perceived descriptive norms (how most others behave) and injunctive norms (what is approved of by others). We predicted that descriptive norms would be directly associated with intentions to learn genomic sequencing results, whereas injunctive norms would be associated indirectly, via attitudes. These differential associations with intentions versus attitudes were hypothesized to be strongest when individuals held ambivalent attitudes toward obtaining results. Methods Participants enrolled in a genomic sequencing trial (n=372) reported intentions to learn medically actionable, non-medically actionable, and carrier sequencing results. Descriptive norms items referenced other study participants. Injunctive norms were analyzed separately for close friends and family members. Attitudes, attitudinal ambivalence, and sociodemographic covariates were also assessed. Results In structural equation models, both descriptive norms and friend injunctive norms were associated with intentions to receive all sequencing results (ps<.004). Attitudes consistently mediated all friend injunctive norms-intentions associations, but not the descriptive norms-intentions associations. Attitudinal ambivalence moderated the association between friend injunctive norms (p≤.001), but not descriptive norms (p=.16), and attitudes. Injunctive norms were significantly associated with attitudes when ambivalence was high, but were unrelated when ambivalence was low. Results replicated for family injunctive norms. Conclusions Descriptive and injunctive norms play roles in genomic sequencing decisions. Considering mediators and moderators of these processes enhances ability to optimize use of normative information to support informed decision making. PMID:29745680

Injunctive Norms and Alcohol Consumption: A Revised Conceptualization

PubMed Central

Krieger, Heather; Neighbors, Clayton; Lewis, Melissa A.; LaBrie, Joseph W.; Foster, Dawn W.; Larimer, Mary E.

2016-01-01

Background Injunctive norms have been found to be important predictors of behaviors in many disciplines with the exception of alcohol research. This exception is likely due to a misconceptualization of injunctive norms for alcohol consumption. To address this, we outline and test a new conceptualization of injunctive norms and personal approval for alcohol consumption. Traditionally, injunctive norms have been assessed using Likert scale ratings of approval perceptions, whereas descriptive norms and individual behaviors are typically measured with behavioral estimates (i.e., number of drinks consumed per week, frequency of drinking, etc.). This makes comparisons between these constructs difficult because they are not similar conceptualizations of drinking behaviors. The present research evaluated a new representation of injunctive norms with anchors comparable to descriptive norms measures. Methods A study and a replication were conducted including 2,559 and 1,189 undergraduate students from three different universities. Participants reported on their alcohol-related consumption behaviors, personal approval of drinking, and descriptive and injunctive norms. Personal approval and injunctive norms were measured using both traditional measures and a new drink-based measure. Results Results from both studies indicated that drink-based injunctive norms were uniquely and positively associated with drinking whereas traditionally assessed injunctive norms were negatively associated with drinking. Analyses also revealed significant unique associations between drink-based injunctive norms and personal approval when controlling for descriptive norms. Conclusions These findings provide support for a modified conceptualization of personal approval and injunctive norms related to alcohol consumption and, importantly, offers an explanation and practical solution for the small and inconsistent findings related to injunctive norms and drinking in past studies. PMID:27030295

The Moderating Role of Close versus Distal Peer Injunctive Norms and Interdependent Self-Construal in the Effects of Descriptive Norms on College Drinking.

PubMed

Yang, Bo

2018-06-01

Based on the theory of normative social behavior (Rimal & Real, 2005), this study examined the effects of descriptive norms, close versus distal peer injunctive norms, and interdependent self-construal on college students' intentions to consume alcohol. Results of a cross-sectional study conducted among U.S. college students (N = 581) found that descriptive norms, close, and distal peer injunctive norms had independent effects on college students' intentions to consume alcohol. Furthermore, close peer injunctive norms moderated the effects of descriptive norms on college students' intentions to consume alcohol and the interaction showed different patterns among students with a strong and weak interdependent self-construal. High levels of close peer injunctive norms weakened the relationship between descriptive norms and intentions to consume alcohol among students with a strong interdependent self-construal but strengthened the relationship between descriptive norms and intentions to consume alcohol among students with a weak interdependent self-construal. Implications of the findings for norms-based research and college drinking interventions are discussed.

Alcohol evaluations and acceptability: Examining descriptive and injunctive norms among heavy drinkers

PubMed Central

Foster, Dawn W.; Neighbors, Clayton; Krieger, Heather

2015-01-01

Objectives This study assessed descriptive and injunctive norms, evaluations of alcohol consequences, and acceptability of drinking. Methods Participants were 248 heavy-drinking undergraduates (81.05% female; Mage = 23.45). Results Stronger perceptions of descriptive and injunctive norms for drinking and more positive evaluations of alcohol consequences were positively associated with drinking and the number of drinks considered acceptable. Descriptive and injunctive norms interacted, indicating that injunctive norms were linked with number of acceptable drinks among those with higher descriptive norms. Descriptive norms and evaluations of consequences interacted, indicating that descriptive norms were positively linked with number of acceptable drinks among those with negative evaluations of consequences; however, among those with positive evaluations of consequences, descriptive norms were negatively associated with number of acceptable drinks. Injunctive norms and evaluations of consequences interacted, indicating that injunctive norms were positively associated with number of acceptable drinks, particularly among those with positive evaluations of consequences. A three-way interaction emerged between injunctive and descriptive norms and evaluations of consequences, suggesting that injunctive norms and the number of acceptable drinks were positively associated more strongly among those with negative versus positive evaluations of consequences. Those with higher acceptable drinks also had positive evaluations of consequences and were high in injunctive norms. Conclusions Findings supported hypotheses that norms and evaluations of alcohol consequences would interact with respect to drinking and acceptance of drinking. These examinations have practical utility and may inform development and implementation of interventions and programs targeting alcohol misuse among heavy drinking undergraduates. PMID:25437265

Multiscale modeling of nerve agent hydrolysis mechanisms: a tale of two Nobel Prizes

NASA Astrophysics Data System (ADS)

Field, Martin J.; Wymore, Troy W.

2014-10-01

The 2013 Nobel Prize in Chemistry was awarded for the development of multiscale models for complex chemical systems, whereas the 2013 Peace Prize was given to the Organisation for the Prohibition of Chemical Weapons for their efforts to eliminate chemical warfare agents. This review relates the two by introducing the field of multiscale modeling and highlighting its application to the study of the biological mechanisms by which selected chemical weapon agents exert their effects at an atomic level.

Multiscale Materials Science - A Mathematical Approach to the Role of Defects and Uncertainty

DTIC Science & Technology

2016-10-28

AFRL-AFOSR-UK-TR-2016-0034 Multiscale materials science - a mathematical approach to the role of defects and uncertainty Claude Le Bris ECOLE...science - a mathematical approach to the role of defects and uncertainty 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA8655-13-1-3061 5c.  PROGRAM ELEMENT...1FORM SF 298 10/31/2016https://livelink.ebs.afrl.af.mil/livelink/llisapi.dll Contract FA 8655-13-1-3061 Multiscale materials science: a mathematical

Multiscale Shannon entropy and its application in the stock market

NASA Astrophysics Data System (ADS)

Gu, Rongbao

2017-10-01

In this paper, we perform a multiscale entropy analysis on the Dow Jones Industrial Average Index using the Shannon entropy. The stock index shows the characteristic of multi-scale entropy that caused by noise in the market. The entropy is demonstrated to have significant predictive ability for the stock index in both long-term and short-term, and empirical results verify that noise does exist in the market and can affect stock price. It has important implications on market participants such as noise traders.

A multiscale approach to accelerate pore-scale simulation of porous electrodes

NASA Astrophysics Data System (ADS)

Zheng, Weibo; Kim, Seung Hyun

2017-04-01

A new method to accelerate pore-scale simulation of porous electrodes is presented. The method combines the macroscopic approach with pore-scale simulation by decomposing a physical quantity into macroscopic and local variations. The multiscale method is applied to the potential equation in pore-scale simulation of a Proton Exchange Membrane Fuel Cell (PEMFC) catalyst layer, and validated with the conventional approach for pore-scale simulation. Results show that the multiscale scheme substantially reduces the computational cost without sacrificing accuracy.

Multiscale simulation of molecular processes in cellular environments.

PubMed

Chiricotto, Mara; Sterpone, Fabio; Derreumaux, Philippe; Melchionna, Simone

2016-11-13

We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).

Multiscale Information Transfer in Functional Corticomuscular Coupling Estimation Following Stroke: A Pilot Study

PubMed Central

Chen, Xiaoling; Xie, Ping; Zhang, Yuanyuan; Chen, Yuling; Yang, Fangmei; Zhang, Litai; Li, Xiaoli

2018-01-01

Recently, functional corticomuscular coupling (FCMC) between the cortex and the contralateral muscle has been used to evaluate motor function after stroke. As we know, the motor-control system is a closed-loop system that is regulated by complex self-regulating and interactive mechanisms which operate in multiple spatial and temporal scales. Multiscale analysis can represent the inherent complexity. However, previous studies in FCMC for stroke patients mainly focused on the coupling strength in single-time scale, without considering the changes of the inherently directional and multiscale properties in sensorimotor systems. In this paper, a multiscale-causal model, named multiscale transfer entropy, was used to quantify the functional connection between electroencephalogram over the scalp and electromyogram from the flexor digitorum superficialis (FDS) recorded simultaneously during steady-state grip task in eight stroke patients and eight healthy controls. Our results showed that healthy controls exhibited higher coupling when the scale reached up to about 12, and the FCMC in descending direction was stronger at certain scales (1, 7, 12, and 14) than that in ascending direction. Further analysis showed these multi-time scale characteristics mainly focused on the beta1 band at scale 11 and beta2 band at scale 9, 11, 13, and 15. Compared to controls, the multiscale properties of the FCMC for stroke were changed, the strengths in both directions were reduced, and the gaps between the descending and ascending directions were disappeared over all scales. Further analysis in specific bands showed that the reduced FCMC mainly focused on the alpha2 at higher scale, beta1 and beta2 across almost the entire scales. This study about multi-scale confirms that the FCMC between the brain and muscles is capable of complex and directional characteristics, and these characteristics in functional connection for stroke are destroyed by the structural lesion in the brain that might disrupt coordination, feedback, and information transmission in efferent control and afferent feedback. The study demonstrates for the first time the multiscale and directional characteristics of the FCMC for stroke patients, and provides a preliminary observation for application in clinical assessment following stroke. PMID:29765351

Extending the Mertonian Norms: Scientists' Subscription to Norms of Research

ERIC Educational Resources Information Center

Anderson, Melissa S.; Ronning, Emily A.; De Vries, Raymond; Martinson, Brian C.

2010-01-01

This analysis, based on focus groups and a national survey, assesses scientists' subscription to the Mertonian norms of science and associated counternorms. It also supports extension of these norms to governance (as opposed to administration), as a norm of decision-making, and quality (as opposed to quantity), as an evaluative norm. (Contains 1…

Children are sensitive to norms of giving.

PubMed

McAuliffe, Katherine; Raihani, Nichola J; Dunham, Yarrow

2017-10-01

People across societies engage in costly sharing, but the extent of such sharing shows striking cultural variation, highlighting the importance of local norms in shaping generosity. Despite this acknowledged role for norms, it is unclear when they begin to exert their influence in development. Here we use a Dictator Game to investigate the extent to which 4- to 9-year-old children are sensitive to selfish (give 20%) and generous (give 80%) norms. Additionally, we varied whether children were told how much other children give (descriptive norm) or what they should give according to an adult (injunctive norm). Results showed that children generally gave more when they were exposed to a generous norm. However, patterns of compliance varied with age. Younger children were more likely to comply with the selfish norm, suggesting a licensing effect. By contrast, older children were more influenced by the generous norm, yet capped their donations at 50%, perhaps adhering to a pre-existing norm of equality. Children were not differentially influenced by descriptive or injunctive norms, suggesting a primacy of norm content over norm format. Together, our findings indicate that while generosity is malleable in children, normative information does not completely override pre-existing biases. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of Norm Perceptions and Guilt on Audience Response to Anti-Smoking Norm PSAs: The Case of Korean Male Smokers

ERIC Educational Resources Information Center

Lee, Hyegyu; Paek, Hye-Jin

2013-01-01

Objective: To examine how norm appeals and guilt influence smokers' behavioural intention. Design: Quasi-experimental design. Setting: South Korea. Method: Two hundred and fifty-five male smokers were randomly assigned to descriptive, injunctive, or subjective anti-smoking norm messages. After they viewed the norm messages, their norm perceptions,…

Overview of NORM and activities by a NORM licensed permanent decontamination and waste processing facility

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

Mirro, G.A.

1997-02-01

This paper presents an overview of issues related to handling NORM materials, and provides a description of a facility designed for the processing of NORM contaminated equipment. With regard to handling NORM materials the author discusses sources of NORM, problems, regulations and disposal options, potential hazards, safety equipment, and issues related to personnel protection. For the facility, the author discusses: description of the permanent facility; the operations of the facility; the license it has for handling specific radioactive material; operating and safety procedures; decontamination facilities on site; NORM waste processing capabilities; and offsite NORM services which are available.

A case study on the formation and sharing process of science classroom norms

NASA Astrophysics Data System (ADS)

Chang, Jina; Song, Jinwoong

2016-03-01

The teaching and learning of science in school are influenced by various factors, including both individual factors, such as member beliefs, and social factors, such as the power structure of the class. To understand this complex context affected by various factors in schools, we investigated the formation and sharing process of science classroom norms in connection with these factors. By examining the developmental process of science classroom norms, we identified how the norms were realized, shared, and internalized among the members. We collected data through classroom observations and interviews focusing on two elementary science classrooms in Korea. From these data, factors influencing norm formation were extracted and developed as stories about norm establishment. The results indicate that every science classroom norm was established, shared, and internalized differently according to the values ingrained in the norms, the agent of norm formation, and the members' understanding about the norm itself. The desirable norms originating from values in science education, such as having an inquiring mind, were not established spontaneously by students, but were instead established through well-organized norm networks to encourage concrete practice. Educational implications were discussed in terms of the practice of school science inquiry, cultural studies, and value-oriented education.

Coherent multiscale image processing using dual-tree quaternion wavelets.

PubMed

Chan, Wai Lam; Choi, Hyeokho; Baraniuk, Richard G

2008-07-01

The dual-tree quaternion wavelet transform (QWT) is a new multiscale analysis tool for geometric image features. The QWT is a near shift-invariant tight frame representation whose coefficients sport a magnitude and three phases: two phases encode local image shifts while the third contains image texture information. The QWT is based on an alternative theory for the 2-D Hilbert transform and can be computed using a dual-tree filter bank with linear computational complexity. To demonstrate the properties of the QWT's coherent magnitude/phase representation, we develop an efficient and accurate procedure for estimating the local geometrical structure of an image. We also develop a new multiscale algorithm for estimating the disparity between a pair of images that is promising for image registration and flow estimation applications. The algorithm features multiscale phase unwrapping, linear complexity, and sub-pixel estimation accuracy.

A Comprehensive Specimen-Specific Multiscale Data Set for Anatomical and Mechanical Characterization of the Tibiofemoral Joint

PubMed Central

Chokhandre, Snehal; Colbrunn, Robb; Bennetts, Craig; Erdemir, Ahmet

2015-01-01

Understanding of tibiofemoral joint mechanics at multiple spatial scales is essential for developing effective preventive measures and treatments for both pathology and injury management. Currently, there is a distinct lack of specimen-specific biomechanical data at multiple spatial scales, e.g., joint, tissue, and cell scales. Comprehensive multiscale data may improve the understanding of the relationship between biomechanical and anatomical markers across various scales. Furthermore, specimen-specific multiscale data for the tibiofemoral joint may assist development and validation of specimen-specific computational models that may be useful for more thorough analyses of the biomechanical behavior of the joint. This study describes an aggregation of procedures for acquisition of multiscale anatomical and biomechanical data for the tibiofemoral joint. Magnetic resonance imaging was used to acquire anatomical morphology at the joint scale. A robotic testing system was used to quantify joint level biomechanical response under various loading scenarios. Tissue level material properties were obtained from the same specimen for the femoral and tibial articular cartilage, medial and lateral menisci, anterior and posterior cruciate ligaments, and medial and lateral collateral ligaments. Histology data were also obtained for all tissue types to measure specimen-specific cell scale information, e.g., cellular distribution. This study is the first of its kind to establish a comprehensive multiscale data set for a musculoskeletal joint and the presented data collection approach can be used as a general template to guide acquisition of specimen-specific comprehensive multiscale data for musculoskeletal joints. PMID:26381404

Bodies obliged and unbound: differentiated response tendencies for injunctive and descriptive social norms.

PubMed

Jacobson, Ryan P; Mortensen, Chad R; Cialdini, Robert B

2011-03-01

The authors suggest that injunctive and descriptive social norms engage different psychological response tendencies when made selectively salient. On the basis of suggestions derived from the focus theory of normative conduct and from consideration of the norms' functions in social life, the authors hypothesized that the 2 norms would be cognitively associated with different goals, would lead individuals to focus on different aspects of self, and would stimulate different levels of conflict over conformity decisions. Additionally, a unique role for effortful self-regulation was hypothesized for each type of norm-used as a means to resist conformity to descriptive norms but as a means to facilitate conformity for injunctive norms. Four experiments supported these hypotheses. Experiment 1 demonstrated differences in the norms' associations to the goals of making accurate/efficient decisions and gaining/maintaining social approval. Experiment 2 provided evidence that injunctive norms lead to a more interpersonally oriented form of self-awareness and to a greater feeling of conflict about conformity decisions than descriptive norms. In the final 2 experiments, conducted in the lab (Experiment 3) and in a naturalistic environment (Experiment 4), self-regulatory depletion decreased conformity to an injunctive norm (Experiments 3 and 4) and increased conformity to a descriptive norm (Experiment 4)-even though the norms advocated identical behaviors. By illustrating differentiated response tendencies for each type of social norm, this research provides new and converging support for the focus theory of normative conduct. (c) 2011 APA, all rights reserved

Reconstructing Norms

ERIC Educational Resources Information Center

Gorgorio, Nuria; Planas, Nuria

2005-01-01

Starting from the constructs "cultural scripts" and "social representations", and on the basis of the empirical research we have been developing until now, we revisit the construct norms from a sociocultural perspective. Norms, both sociomathematical norms and norms of the mathematical practice, as cultural scripts influenced…

Peer Group Norms and Accountability Moderate the Effect of School Norms on Children's Intergroup Attitudes

ERIC Educational Resources Information Center

McGuire, Luke; Rutland, Adam; Nesdale, Drew

2015-01-01

The present study examined the interactive effects of school norms, peer norms, and accountability on children's intergroup attitudes. Participants (n = 229) aged 5-11 years, in a between-subjects design, were randomly assigned to a peer group with an inclusion or exclusion norm, learned their school either had an inclusion norm or not, and were…

Performance of hybrid programming models for multiscale cardiac simulations: preparing for petascale computation.

PubMed

Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias

2011-10-01

Future multiscale and multiphysics models that support research into human disease, translational medical science, and treatment can utilize the power of high-performance computing (HPC) systems. We anticipate that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message-passing processes [e.g., the message-passing interface (MPI)] with multithreading (e.g., OpenMP, Pthreads). The objective of this study is to compare the performance of such hybrid programming models when applied to the simulation of a realistic physiological multiscale model of the heart. Our results show that the hybrid models perform favorably when compared to an implementation using only the MPI and, furthermore, that OpenMP in combination with the MPI provides a satisfactory compromise between performance and code complexity. Having the ability to use threads within MPI processes enables the sophisticated use of all processor cores for both computation and communication phases. Considering that HPC systems in 2012 will have two orders of magnitude more cores than what was used in this study, we believe that faster than real-time multiscale cardiac simulations can be achieved on these systems.

Systems oncology: towards patient-specific treatment regimes informed by multiscale mathematical modelling.

PubMed

Powathil, Gibin G; Swat, Maciej; Chaplain, Mark A J

2015-02-01

The multiscale complexity of cancer as a disease necessitates a corresponding multiscale modelling approach to produce truly predictive mathematical models capable of improving existing treatment protocols. To capture all the dynamics of solid tumour growth and its progression, mathematical modellers need to couple biological processes occurring at various spatial and temporal scales (from genes to tissues). Because effectiveness of cancer therapy is considerably affected by intracellular and extracellular heterogeneities as well as by the dynamical changes in the tissue microenvironment, any model attempt to optimise existing protocols must consider these factors ultimately leading to improved multimodal treatment regimes. By improving existing and building new mathematical models of cancer, modellers can play important role in preventing the use of potentially sub-optimal treatment combinations. In this paper, we analyse a multiscale computational mathematical model for cancer growth and spread, incorporating the multiple effects of radiation therapy and chemotherapy in the patient survival probability and implement the model using two different cell based modelling techniques. We show that the insights provided by such multiscale modelling approaches can ultimately help in designing optimal patient-specific multi-modality treatment protocols that may increase patients quality of life. Copyright © 2014 Elsevier Ltd. All rights reserved.

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

A Liver-centric Multiscale Modeling Framework for Xenobiotics ...

EPA Pesticide Factsheets

We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. To validate the model, we estimated our model parameters by fi?tting serum concentrations of acetaminophen and its glucuronide and sulfate metabolites to experiments, and carried out sensitivity analysis on 35 parameters selected from three modules. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. This multiscale model bridges the CompuCell3D tool used by the Virtual Tissue project with the httk tool developed by the Rapid Exposure and Dosimetry project.

Current Trends in the study of Gender Norms and Health Behaviors

PubMed Central

Fleming, Paul J.; Agnew-Brune, Christine

2015-01-01

Gender norms are recognized as one of the major social determinants of health and gender norms can have implications for an individual’s health behaviors. This paper reviews the recent advances in research on the role of gender norms on health behaviors most associated with morbidity and mortality. We find that (1) the study of gender norms and health behaviors is varied across different types of health behaviors, (2) research on masculinity and masculine norms appears to have taken on an increasing proportion of studies on the relationship between gender norms and health, and (3) we are seeing new and varied populations integrated into the study of gender norms and health behaviors. PMID:26075291

1-norm support vector novelty detection and its sparseness.

PubMed

Zhang, Li; Zhou, WeiDa

2013-12-01

This paper proposes a 1-norm support vector novelty detection (SVND) method and discusses its sparseness. 1-norm SVND is formulated as a linear programming problem and uses two techniques for inducing sparseness, or the 1-norm regularization and the hinge loss function. We also find two upper bounds on the sparseness of 1-norm SVND, or exact support vector (ESV) and kernel Gram matrix rank bounds. The ESV bound indicates that 1-norm SVND has a sparser representation model than SVND. The kernel Gram matrix rank bound can loosely estimate the sparseness of 1-norm SVND. Experimental results show that 1-norm SVND is feasible and effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

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

Plechac, Petr

2016-03-01

The overall objective of this project was to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics and developing rigorous mathematical techniques and computational algorithms to study such models. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals.

Application of LOD technology to the economic residence GIS for industry and commerce administration

NASA Astrophysics Data System (ADS)

Song, Yongjun; Feng, Xuezhi; Zhao, Shuhe; Yin, Haiwei; Li, Yulin; Cui, Hongxia; Zhang, Hui; Zhong, Quanbao

2007-06-01

The LOD technology has an impact upon the multi-scale representation of spatial database. This paper takes advantage of LOD technology to express the multi-scale geographical data, and establish the exchange of multi-scale electronic map, further attain the goal that the details of geographic features such as point, line and polygon can be displayed more and more clearly with the display scale being enlarged to be convenient for the personnel of all offices of industry and commerce administration to label the locations of the corporations or enterprises.

Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale

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

Zabaras, Nicolas J.

2016-11-08

Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.

Multiscale approach to the physics of radiation damage with ions

NASA Astrophysics Data System (ADS)

Surdutovich, Eugene; Solov'yov, Andrey V.

2013-04-01

We review a multiscale approach to the physics of ion-beam cancer therapy, an approach suggested in order to understand the interplay of a large number of phenomena involved in radiation damage scenario occurring on a range of temporal, spatial, and energy scales. We briefly overview its history and present the current stage of its development. The differences of the multiscale approach from other methods of understanding and assessment of radiation damage are discussed as well as its relationship to other branches of physics, chemistry and biology.

Classification of JERS-1 Image Mosaic of Central Africa Using A Supervised Multiscale Classifier of Texture Features

NASA Technical Reports Server (NTRS)

Saatchi, Sassan; DeGrandi, Franco; Simard, Marc; Podest, Erika

1999-01-01

In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.

Multiscale Modeling of Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Mital, Subodh K.; Pineda, Evan J.; Arnold, Steven M.

2015-01-01

Results of multiscale modeling simulations of the nonlinear response of SiC/SiC ceramic matrix composites are reported, wherein the microstructure of the ceramic matrix is captured. This micro scale architecture, which contains free Si material as well as the SiC ceramic, is responsible for residual stresses that play an important role in the subsequent thermo-mechanical behavior of the SiC/SiC composite. Using the novel Multiscale Generalized Method of Cells recursive micromechanics theory, the microstructure of the matrix, as well as the microstructure of the composite (fiber and matrix) can be captured.

The Social Norms of Suicidal and Self-Harming Behaviours in Scottish Adolescents.

PubMed

Quigley, Jody; Rasmussen, Susan; McAlaney, John

2017-03-15

Although the suicidal and self-harming behaviour of individuals is often associated with similar behaviours in people they know, little is known about the impact of perceived social norms on those behaviours. In a range of other behavioural domains (e.g., alcohol consumption, smoking, eating behaviours) perceived social norms have been found to strongly predict individuals' engagement in those behaviours, although discrepancies often exist between perceived and reported norms. Interventions which align perceived norms more closely with reported norms have been effective in reducing damaging behaviours. The current study aimed to explore whether the Social Norms Approach is applicable to suicidal and self-harming behaviours in adolescents. Participants were 456 pupils from five Scottish high-schools (53% female, mean age = 14.98 years), who completed anonymous, cross-sectional surveys examining reported and perceived norms around suicidal and self-harming behaviour. Friedman's ANOVA with post-hoc Wilcoxen signed-ranks tests indicated that proximal groups were perceived as less likely to engage in or be permissive of suicidal and self-harming behaviours than participants' reported themselves, whilst distal groups tended towards being perceived as more likely to do so. Binary logistic regression analyses identified a number of perceived norms associated with reported norms, with close friends' norms positively associated with all outcome variables. The Social Norms Approach may be applicable to suicidal and self-harming behaviour, but associations between perceived and reported norms and predictors of reported norms differ to those found in other behavioural domains. Theoretical and practical implications of the findings are considered.

The Social Norms of Suicidal and Self-Harming Behaviours in Scottish Adolescents

PubMed Central

Quigley, Jody; Rasmussen, Susan; McAlaney, John

2017-01-01

Although the suicidal and self-harming behaviour of individuals is often associated with similar behaviours in people they know, little is known about the impact of perceived social norms on those behaviours. In a range of other behavioural domains (e.g., alcohol consumption, smoking, eating behaviours) perceived social norms have been found to strongly predict individuals’ engagement in those behaviours, although discrepancies often exist between perceived and reported norms. Interventions which align perceived norms more closely with reported norms have been effective in reducing damaging behaviours. The current study aimed to explore whether the Social Norms Approach is applicable to suicidal and self-harming behaviours in adolescents. Participants were 456 pupils from five Scottish high-schools (53% female, mean age = 14.98 years), who completed anonymous, cross-sectional surveys examining reported and perceived norms around suicidal and self-harming behaviour. Friedman’s ANOVA with post-hoc Wilcoxen signed-ranks tests indicated that proximal groups were perceived as less likely to engage in or be permissive of suicidal and self-harming behaviours than participants’ reported themselves, whilst distal groups tended towards being perceived as more likely to do so. Binary logistic regression analyses identified a number of perceived norms associated with reported norms, with close friends’ norms positively associated with all outcome variables. The Social Norms Approach may be applicable to suicidal and self-harming behaviour, but associations between perceived and reported norms and predictors of reported norms differ to those found in other behavioural domains. Theoretical and practical implications of the findings are considered. PMID:28294999

Performance of Dutch children on the Bayley III: a comparison study of US and Dutch norms.

PubMed

Steenis, Leonie J P; Verhoeven, Marjolein; Hessen, Dave J; van Baar, Anneloes L

2015-01-01

The Bayley Scales of Infant and Toddler Development-third edition (Bayley-III) are frequently used to assess early child development worldwide. However, the original standardization only included US children, and it is still unclear whether or not these norms are adequate for use in other populations. Recently, norms for the Dutch version of the Bayley-III (The Bayley-III-NL) were made. Scores based on Dutch and US norms were compared to study the need for population-specific norms. Scaled scores based on Dutch and US norms were compared for 1912 children between 14 days and 42 months 14 days. Next, the proportions of children scoring < 1-SD and < -2 SD based on the two norms were compared, to identify over- or under-referral for developmental delay resulting from non-population-based norms. Scaled scores based on Dutch norms fluctuated around values based on US norms on all subtests. The extent of the deviations differed across ages and subtests. Differences in means were significant across all five subtests (p < .01) with small to large effect sizes (ηp2) ranging from .03 to .26). Using the US instead of Dutch norms resulted in over-referral regarding gross motor skills, and under-referral regarding cognitive, receptive communication, expressive communication, and fine motor skills. The Dutch norms differ from the US norms for all subtests and these differences are clinically relevant. Population specific norms are needed to identify children with low scores for referral and intervention, and to facilitate international comparisons of population data.

Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

PubMed Central

Baydil, Banu; Daley, William P.; Larsen, Melinda; Yener, Bülent

2012-01-01

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We here show how to define and calculate a multiscale feature set as an effective computational approach to identify and quantify changes at multiple biological scales and to distinguish between different states in developing tissues. PMID:22403724

Gyrokinetic predictions of multiscale transport in a DIII-D ITER baseline discharge

DOE PAGES

Holland, C.; Howard, N. T.; Grierson, B. A.

2017-05-08

New multiscale gyrokinetic simulations predict that electron energy transport in a DIII-D ITER baseline discharge with dominant electron heating and low input torque is multiscale in nature, with roughly equal amounts of the electron energy flux Q e coming from long wavelength ion-scale (k yρ s < 1) and short wavelength electron-scale (k yρ s > 1) fluctuations when the gyrokinetic results match independent power balance calculations. Corresponding conventional ion-scale simulations are able to match the power balance ion energy flux Q i, but systematically underpredict Q e when doing so. We observe significant nonlinear cross-scale couplings in the multiscalemore » simulations, but the exact simulation predictions are found to be extremely sensitive to variations of model input parameters within experimental uncertainties. Most notably, depending upon the exact value of the equilibrium E x B shearing rate γ E x B used, either enhancement or suppression of the long-wavelength turbulence and transport levels in the multiscale simulations is observed relative to what is predicted by ion-scale simulations. And while the enhancement of the long wavelength fluctuations by inclusion of the short wavelength turbulence was previously observed in similar multiscale simulations of an Alcator C-Mod L-mode discharge, these new results show for the first time a complete suppression of long-wavelength turbulence in a multiscale simulation, for parameters at which conventional ion-scale simulation predicts small but finite levels of low-k turbulence and transport consistent with the power balance Q i. Though computational resource limitations prevent a fully rigorous validation assessment of these new results, they provide significant new evidence that electron energy transport in burning plasmas is likely to have a strong multiscale character, with significant nonlinear cross-scale couplings that must be fully understood to predict the performance of those plasmas with confidence.« less

Multi-element least square HDMR methods and their applications for stochastic multiscale model reduction

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

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Xinping, E-mail: exping@126.com

Stochastic multiscale modeling has become a necessary approach to quantify uncertainty and characterize multiscale phenomena for many practical problems such as flows in stochastic porous media. The numerical treatment of the stochastic multiscale models can be very challengeable as the existence of complex uncertainty and multiple physical scales in the models. To efficiently take care of the difficulty, we construct a computational reduced model. To this end, we propose a multi-element least square high-dimensional model representation (HDMR) method, through which the random domain is adaptively decomposed into a few subdomains, and a local least square HDMR is constructed in eachmore » subdomain. These local HDMRs are represented by a finite number of orthogonal basis functions defined in low-dimensional random spaces. The coefficients in the local HDMRs are determined using least square methods. We paste all the local HDMR approximations together to form a global HDMR approximation. To further reduce computational cost, we present a multi-element reduced least-square HDMR, which improves both efficiency and approximation accuracy in certain conditions. To effectively treat heterogeneity properties and multiscale features in the models, we integrate multiscale finite element methods with multi-element least-square HDMR for stochastic multiscale model reduction. This approach significantly reduces the original model's complexity in both the resolution of the physical space and the high-dimensional stochastic space. We analyze the proposed approach, and provide a set of numerical experiments to demonstrate the performance of the presented model reduction techniques. - Highlights: • Multi-element least square HDMR is proposed to treat stochastic models. • Random domain is adaptively decomposed into some subdomains to obtain adaptive multi-element HDMR. • Least-square reduced HDMR is proposed to enhance computation efficiency and approximation accuracy in certain conditions. • Integrating MsFEM and multi-element least square HDMR can significantly reduce computation complexity.« less

Structural and Practical Identifiability Issues of Immuno-Epidemiological Vector-Host Models with Application to Rift Valley Fever.

PubMed

Tuncer, Necibe; Gulbudak, Hayriye; Cannataro, Vincent L; Martcheva, Maia

2016-09-01

In this article, we discuss the structural and practical identifiability of a nested immuno-epidemiological model of arbovirus diseases, where host-vector transmission rate, host recovery, and disease-induced death rates are governed by the within-host immune system. We incorporate the newest ideas and the most up-to-date features of numerical methods to fit multi-scale models to multi-scale data. For an immunological model, we use Rift Valley Fever Virus (RVFV) time-series data obtained from livestock under laboratory experiments, and for an epidemiological model we incorporate a human compartment to the nested model and use the number of human RVFV cases reported by the CDC during the 2006-2007 Kenya outbreak. We show that the immunological model is not structurally identifiable for the measurements of time-series viremia concentrations in the host. Thus, we study the non-dimensionalized and scaled versions of the immunological model and prove that both are structurally globally identifiable. After fixing estimated parameter values for the immunological model derived from the scaled model, we develop a numerical method to fit observable RVFV epidemiological data to the nested model for the remaining parameter values of the multi-scale system. For the given (CDC) data set, Monte Carlo simulations indicate that only three parameters of the epidemiological model are practically identifiable when the immune model parameters are fixed. Alternatively, we fit the multi-scale data to the multi-scale model simultaneously. Monte Carlo simulations for the simultaneous fitting suggest that the parameters of the immunological model and the parameters of the immuno-epidemiological model are practically identifiable. We suggest that analytic approaches for studying the structural identifiability of nested models are a necessity, so that identifiable parameter combinations can be derived to reparameterize the nested model to obtain an identifiable one. This is a crucial step in developing multi-scale models which explain multi-scale data.

Multi-Scale Infrastructure Assessment

EPA Science Inventory

The U.S. Environmental Protection Agency’s (EPA) multi-scale infrastructure assessment project supports both water resource adaptation to climate change and the rehabilitation of the nation’s aging water infrastructure by providing tools, scientific data and information to progra...

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

Complexity multiscale asynchrony measure and behavior for interacting financial dynamics

NASA Astrophysics Data System (ADS)

Yang, Ge; Wang, Jun; Niu, Hongli

2016-08-01

A stochastic financial price process is proposed and investigated by the finite-range multitype contact dynamical system, in an attempt to study the nonlinear behaviors of real asset markets. The viruses spreading process in a finite-range multitype system is used to imitate the interacting behaviors of diverse investment attitudes in a financial market, and the empirical research on descriptive statistics and autocorrelation behaviors of return time series is performed for different values of propagation rates. Then the multiscale entropy analysis is adopted to study several different shuffled return series, including the original return series, the corresponding reversal series, the random shuffled series, the volatility shuffled series and the Zipf-type shuffled series. Furthermore, we propose and compare the multiscale cross-sample entropy and its modification algorithm called composite multiscale cross-sample entropy. We apply them to study the asynchrony of pairs of time series under different time scales.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Correlations of stock price fluctuations under multi-scale and multi-threshold scenarios

NASA Astrophysics Data System (ADS)

Sui, Guo; Li, Huajiao; Feng, Sida; Liu, Xueyong; Jiang, Meihui

2018-01-01

The multi-scale method is widely used in analyzing time series of financial markets and it can provide market information for different economic entities who focus on different periods. Through constructing multi-scale networks of price fluctuation correlation in the stock market, we can detect the topological relationship between each time series. Previous research has not addressed the problem that the original fluctuation correlation networks are fully connected networks and more information exists within these networks that is currently being utilized. Here we use listed coal companies as a case study. First, we decompose the original stock price fluctuation series into different time scales. Second, we construct the stock price fluctuation correlation networks at different time scales. Third, we delete the edges of the network based on thresholds and analyze the network indicators. Through combining the multi-scale method with the multi-threshold method, we bring to light the implicit information of fully connected networks.

Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

NASA Technical Reports Server (NTRS)

Pisani, William A.; Radue, Matthew; Chinkanjanarot, Sorayot; Bednarcyk, Brett A.; Pineda, Evan J.; King, Julia A.; Odegard, Gregory M.

2018-01-01

Polyether ether ketone (PEEK) is a high-performance, semi-crystalline thermoplastic that is used in a wide range of engineering applications, including some structural components of aircraft. The design of new PEEK-based materials requires a precise understanding of the multiscale structure and behavior of semi-crystalline PEEK. Molecular Dynamics (MD) modeling can efficiently predict bulk-level properties of single phase polymers, and micromechanics can be used to homogenize those phases based on the overall polymer microstructure. In this study, MD modeling was used to predict the mechanical properties of the amorphous and crystalline phases of PEEK. The hierarchical microstructure of PEEK, which combines the aforementioned phases, was modeled using a multiscale modeling approach facilitated by NASA's MSGMC. The bulk mechanical properties of semi-crystalline PEEK predicted using MD modeling and MSGMC agree well with vendor data, thus validating the multiscale modeling approach.

Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency

NASA Astrophysics Data System (ADS)

Liu, Changjiang; Cheng, Irene; Zhang, Yi; Basu, Anup

2017-06-01

This paper presents an improved multi-scale Retinex (MSR) based enhancement for ariel images under low visibility. For traditional multi-scale Retinex, three scales are commonly employed, which limits its application scenarios. We extend our research to a general purpose enhanced method, and design an MSR with more than three scales. Based on the mathematical analysis and deductions, an explicit multi-scale representation is proposed that balances image contrast and color consistency. In addition, a histogram truncation technique is introduced as a post-processing strategy to remap the multi-scale Retinex output to the dynamic range of the display. Analysis of experimental results and comparisons with existing algorithms demonstrate the effectiveness and generality of the proposed method. Results on image quality assessment proves the accuracy of the proposed method with respect to both objective and subjective criteria.

A Micromechanics-Based Method for Multiscale Fatigue Prediction

NASA Astrophysics Data System (ADS)

Moore, John Allan

An estimated 80% of all structural failures are due to mechanical fatigue, often resulting in catastrophic, dangerous and costly failure events. However, an accurate model to predict fatigue remains an elusive goal. One of the major challenges is that fatigue is intrinsically a multiscale process, which is dependent on a structure's geometric design as well as its material's microscale morphology. The following work begins with a microscale study of fatigue nucleation around non- metallic inclusions. Based on this analysis, a novel multiscale method for fatigue predictions is developed. This method simulates macroscale geometries explicitly while concurrently calculating the simplified response of microscale inclusions. Thus, providing adequate detail on multiple scales for accurate fatigue life predictions. The methods herein provide insight into the multiscale nature of fatigue, while also developing a tool to aid in geometric design and material optimization for fatigue critical devices such as biomedical stents and artificial heart valves.

High-Temperature Tolerance in Multi-Scale Cermet Solar-Selective Absorbing Coatings Prepared by Laser Cladding.

PubMed

Pang, Xuming; Wei, Qian; Zhou, Jianxin; Ma, Huiyang

2018-06-19

In order to achieve cermet-based solar absorber coatings with long-term thermal stability at high temperatures, a novel single-layer, multi-scale TiC-Ni/Mo cermet coating was first prepared using laser cladding technology in atmosphere. The results show that the optical properties of the cermet coatings using laser cladding were much better than the preplaced coating. In addition, the thermal stability of the optical properties for the laser cladding coating were excellent after annealing at 650 °C for 200 h. The solar absorptance and thermal emittance of multi-scale cermet coating were 85% and 4.7% at 650 °C. The results show that multi-scale cermet materials are more suitable for solar-selective absorbing coating. In addition, laser cladding is a new technology that can be used for the preparation of spectrally-selective coatings.

Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics

NASA Astrophysics Data System (ADS)

Vijaykumar, Adithya; Ouldridge, Thomas E.; ten Wolde, Pieter Rein; Bolhuis, Peter G.

2017-03-01

The modeling of complex reaction-diffusion processes in, for instance, cellular biochemical networks or self-assembling soft matter can be tremendously sped up by employing a multiscale algorithm which combines the mesoscopic Green's Function Reaction Dynamics (GFRD) method with explicit stochastic Brownian, Langevin, or deterministic molecular dynamics to treat reactants at the microscopic scale [A. Vijaykumar, P. G. Bolhuis, and P. R. ten Wolde, J. Chem. Phys. 143, 214102 (2015)]. Here we extend this multiscale MD-GFRD approach to include the orientational dynamics that is crucial to describe the anisotropic interactions often prevalent in biomolecular systems. We present the novel algorithm focusing on Brownian dynamics only, although the methodology is generic. We illustrate the novel algorithm using a simple patchy particle model. After validation of the algorithm, we discuss its performance. The rotational Brownian dynamics MD-GFRD multiscale method will open up the possibility for large scale simulations of protein signalling networks.

Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

NASA Astrophysics Data System (ADS)

Dai, Jun; Zhou, Haigang; Zhao, Shaoquan

2017-01-01

This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

Professional Norms Guiding School Principals' Pedagogical Leadership

ERIC Educational Resources Information Center

Leo, Ulf

2015-01-01

Purpose: The purpose of this paper is to identify and analyze the professional norms surrounding school development, with a special emphasis on school principals' pedagogical leadership. Design/methodology/approach: A norm perspective is used to identify possible links between legal norms, professional norms, and actions. The findings are based on…

The hitchhiker's guide to altruism: gene-culture coevolution, and the internalization of norms.

PubMed

Gintis, Herbert

2003-02-21

An internal norm is a pattern of behavior enforced in part by internal sanctions, such as shame, guilt and loss of self-esteem, as opposed to purely external sanctions, such as material rewards and punishment. The ability to internalize norms is widespread among humans, although in some so-called "sociopaths", this capacity is diminished or lacking. Suppose there is one genetic locus that controls the capacity to internalize norms. This model shows that if an internal norm is fitness enhancing, then for plausible patterns of socialization, the allele for internalization of norms is evolutionarily stable. This framework can be used to model Herbert Simon's (1990) explanation of altruism, showing that altruistic norms can "hitchhike" on the general tendency of internal norms to be personally fitness-enhancing. A multi-level selection, gene-culture coevolution argument then explains why individually fitness-reducing internal norms are likely to be prosocial as opposed to socially harmful.

Boosting safety behaviour: Descriptive norms encourage child booster seat usage amongst low involvement parents.

PubMed

Jeffrey, Jennifer; Whelan, Jodie; Pirouz, Dante M; Snowdon, Anne W

2016-07-01

Campaigns advocating behavioural changes often employ social norms as a motivating technique, favouring injunctive norms (what is typically approved or disapproved) over descriptive norms (what is typically done). Here, we investigate an upside to including descriptive norms in health and safety appeals. Because descriptive norms are easy to process and understand, they should provide a heuristic to guide behaviour in those individuals who lack the interest or motivation to reflect on the advocated behaviour more deeply. When those descriptive norms are positive - suggesting that what is done is consistent with what ought to be done - including them in campaigns should be particularly beneficial at influencing this low-involvement segment. We test this proposition via research examining booster seat use amongst parents with children of booster seat age, and find that incorporating positive descriptive norms into a related campaign is particularly impactful for parents who report low involvement in the topic of booster seat safety. Descriptive norms are easy to state and easy to understand, and our research suggests that these norms resonate with low involvement individuals. As a result, we recommend incorporating descriptive norms when possible into health and safety campaigns. Copyright © 2016. Published by Elsevier Ltd.

Social Norms and Adolescents' Sexual Health: An Introduction for Practitioners Working in Low and Mid-income African countries.

PubMed

Cislaghi, Beniamino; Shakya, Holly

2018-03-01

Donors, practitioners and scholars are increasingly interested in harnessing the potential of social norms theory to improve adolescents' sexual and reproductive health outcomes. However, social norms theory is multifaceted, and its application in field interventions is complex. An introduction to social norms that will be beneficial for those who intend to integrate a social norms perspective in their work to improve adolescents' sexual health in Africa is presented. First three main schools of thought on social norms, looking at the theoretical standpoint of each, are discussed. Next, the difference between two important types of social norms (descriptive and injunctive) is explained and then the concept of a -reference group‖ is examined. The difference between social and gender norms are then considered, highlighting how this difference is motivated by existing yet contrasting approaches to norms (in social psychology and gender theory). In the last section, existing evidence on the role that social norms play in influencing adolescents' sexual and reproductive health are reviewed. Conclusions call for further research and action to understand how norms affecting adolescents' sexual and reproductive health and rights (SRHR) can be changed in sub-Saharan Africa.

The Multiscale Robin Coupled Method for flows in porous media

NASA Astrophysics Data System (ADS)

Guiraldello, Rafael T.; Ausas, Roberto F.; Sousa, Fabricio S.; Pereira, Felipe; Buscaglia, Gustavo C.

2018-02-01

A multiscale mixed method aiming at the accurate approximation of velocity and pressure fields in heterogeneous porous media is proposed. The procedure is based on a new domain decomposition method in which the local problems are subject to Robin boundary conditions. The domain decomposition procedure is defined in terms of two independent spaces on the skeleton of the decomposition, corresponding to interface pressures and fluxes, that can be chosen with great flexibility to accommodate local features of the underlying permeability fields. The well-posedness of the new domain decomposition procedure is established and its connection with the method of Douglas et al. (1993) [12], is identified, also allowing us to reinterpret the known procedure as an optimized Schwarz (or Two-Lagrange-Multiplier) method. The multiscale property of the new domain decomposition method is indicated, and its relation with the Multiscale Mortar Mixed Finite Element Method (MMMFEM) and the Multiscale Hybrid-Mixed (MHM) Finite Element Method is discussed. Numerical simulations are presented aiming at illustrating several features of the new method. Initially we illustrate the possibility of switching from MMMFEM to MHM by suitably varying the Robin condition parameter in the new multiscale method. Then we turn our attention to realistic flows in high-contrast, channelized porous formations. We show that for a range of values of the Robin condition parameter our method provides better approximations for pressure and velocity than those computed with either the MMMFEM and the MHM. This is an indication that our method has the potential to produce more accurate velocity fields in the presence of rough, realistic permeability fields of petroleum reservoirs.

Multi-scale gyrokinetic simulations of an Alcator C-Mod, ELM-y H-mode plasma

NASA Astrophysics Data System (ADS)

Howard, N. T.; Holland, C.; White, A. E.; Greenwald, M.; Rodriguez-Fernandez, P.; Candy, J.; Creely, A. J.

2018-01-01

High fidelity, multi-scale gyrokinetic simulations capable of capturing both ion ({k}θ {ρ }s∼ { O }(1.0)) and electron-scale ({k}θ {ρ }e∼ { O }(1.0)) turbulence were performed in the core of an Alcator C-Mod ELM-y H-mode discharge which exhibits reactor-relevant characteristics. These simulations, performed with all experimental inputs and realistic ion to electron mass ratio ({({m}i/{m}e)}1/2=60.0) provide insight into the physics fidelity that may be needed for accurate simulation of the core of fusion reactor discharges. Three multi-scale simulations and series of separate ion and electron-scale simulations performed using the GYRO code (Candy and Waltz 2003 J. Comput. Phys. 186 545) are presented. As with earlier multi-scale results in L-mode conditions (Howard et al 2016 Nucl. Fusion 56 014004), both ion and multi-scale simulations results are compared with experimentally inferred ion and electron heat fluxes, as well as the measured values of electron incremental thermal diffusivities—indicative of the experimental electron temperature profile stiffness. Consistent with the L-mode results, cross-scale coupling is found to play an important role in the simulation of these H-mode conditions. Extremely stiff ion-scale transport is observed in these high-performance conditions which is shown to likely play and important role in the reproduction of measurements of perturbative transport. These results provide important insight into the role of multi-scale plasma turbulence in the core of reactor-relevant plasmas and establish important constraints on the the fidelity of models needed for predictive simulations.

Examining Coherency Scales, Substructure, and Propagation of Whistler Mode Chorus Elements With Magnetospheric Multiscale (MMS)

NASA Astrophysics Data System (ADS)

Turner, D. L.; Lee, J. H.; Claudepierre, S. G.; Fennell, J. F.; Blake, J. B.; Jaynes, A. N.; Leonard, T.; Wilder, F. D.; Ergun, R. E.; Baker, D. N.; Cohen, I. J.; Mauk, B. H.; Strangeway, R. J.; Hartley, D. P.; Kletzing, C. A.; Breuillard, H.; Le Contel, O.; Khotyaintsev, Yu. V.; Torbert, R. B.; Allen, R. C.; Burch, J. L.; Santolik, O.

2017-11-01

Whistler mode chorus waves are a naturally occurring electromagnetic emission observed in Earth's magnetosphere. Here, for the first time, data from NASA's Magnetospheric Multiscale (MMS) mission were used to analyze chorus waves in detail, including the calculation of chorus wave normal vectors, fi>k. A case study was examined from a period of substorm activity around the time of a conjunction between the MMS constellation and NASA's Van Allen Probes mission on 07 April 2016. Chorus wave activity was simultaneously observed by all six spacecraft over a broad range of L shells (5.5 < L < 8.5), magnetic local time (06:00 < MLT < 09:00), and magnetic latitude (-32° < MLAT < -15°), implying a large chorus active region. Eight chorus elements and their substructure were analyzed in detail with MMS. These chorus elements were all lower band and rising tone emissions, right-handed and nearly circularly polarized, and propagating away from the magnetic equator when they were observed at MMS (MLAT -31°). Most of the elements had "hook"-like signatures on their wave power spectra, characterized by enhanced wave power at flat or falling frequency following the peak, and all the elements exhibited complex and well-organized substructure observed consistently at all four MMS spacecraft at separations up to 70 km (60 km perpendicular and 38 km parallel to the background magnetic field). The waveforms in field-aligned coordinates also demonstrated that these waves were all phase coherent, allowing for the direct calculation of fi>k. Error estimates on calculated fi>k revealed that the plane wave approximation was valid for six of the eight elements and most of the subelements. The wave normal vectors were within 20-30° from the direction antiparallel to the background field for all elements and changed from subelement to subelement through at least two of the eight elements. The azimuthal angle of fi>k in the perpendicular plane was oriented earthward and was oblique to that of the Poynting vector, which has implications for the validity of cold plasma theory.

Brain responses to social norms: Meta-analyses of fMRI studies.

PubMed

Zinchenko, Oksana; Arsalidou, Marie

2018-02-01

Social norms have a critical role in everyday decision-making, as frequent interaction with others regulates our behavior. Neuroimaging studies show that social-based and fairness-related decision-making activates an inconsistent set of areas, which sometimes includes the anterior insula, anterior cingulate cortex, and others lateral prefrontal cortices. Social-based decision-making is complex and variability in findings may be driven by socio-cognitive activities related to social norms. To distinguish among social-cognitive activities related to social norms, we identified 36 eligible articles in the functional magnetic resonance imaging (fMRI) literature, which we separate into two categories (a) social norm representation and (b) norm violations. The majority of original articles (>60%) used tasks associated with fairness norms and decision-making, such as ultimatum game, dictator game, or prisoner's dilemma; the rest used tasks associated to violation of moral norms, such as scenarios and sentences of moral depravity ratings. Using quantitative meta-analyses, we report common and distinct brain areas that show concordance as a function of category. Specifically, concordance in ventromedial prefrontal regions is distinct to social norm representation processing, whereas concordance in right insula, dorsolateral prefrontal, and dorsal cingulate cortices is distinct to norm violation processing. We propose a neurocognitive model of social norms for healthy adults, which could help guide future research in social norm compliance and mechanisms of its enforcement. © 2017 Wiley Periodicals, Inc.

Collective action and the evolution of social norm internalization

PubMed Central

Gavrilets, Sergey; Richerson, Peter J.

2017-01-01

Human behavior is strongly affected by culturally transmitted norms and values. Certain norms are internalized (i.e., acting according to a norm becomes an end in itself rather than merely a tool in achieving certain goals or avoiding social sanctions). Humans’ capacity to internalize norms likely evolved in our ancestors to simplify solving certain challenges—including social ones. Here we study theoretically the evolutionary origins of the capacity to internalize norms. In our models, individuals can choose to participate in collective actions as well as punish free riders. In making their decisions, individuals attempt to maximize a utility function in which normative values are initially irrelevant but play an increasingly important role if the ability to internalize norms emerges. Using agent-based simulations, we show that norm internalization evolves under a wide range of conditions so that cooperation becomes “instinctive.” Norm internalization evolves much more easily and has much larger effects on behavior if groups promote peer punishment of free riders. Promoting only participation in collective actions is not effective. Typically, intermediate levels of norm internalization are most frequent but there are also cases with relatively small frequencies of “oversocialized” individuals willing to make extreme sacrifices for their groups no matter material costs, as well as “undersocialized” individuals completely immune to social norms. Evolving the ability to internalize norms was likely a crucial step on the path to large-scale human cooperation. PMID:28533363

Collective action and the evolution of social norm internalization.

PubMed

Gavrilets, Sergey; Richerson, Peter J

2017-06-06

Human behavior is strongly affected by culturally transmitted norms and values. Certain norms are internalized (i.e., acting according to a norm becomes an end in itself rather than merely a tool in achieving certain goals or avoiding social sanctions). Humans' capacity to internalize norms likely evolved in our ancestors to simplify solving certain challenges-including social ones. Here we study theoretically the evolutionary origins of the capacity to internalize norms. In our models, individuals can choose to participate in collective actions as well as punish free riders. In making their decisions, individuals attempt to maximize a utility function in which normative values are initially irrelevant but play an increasingly important role if the ability to internalize norms emerges. Using agent-based simulations, we show that norm internalization evolves under a wide range of conditions so that cooperation becomes "instinctive." Norm internalization evolves much more easily and has much larger effects on behavior if groups promote peer punishment of free riders. Promoting only participation in collective actions is not effective. Typically, intermediate levels of norm internalization are most frequent but there are also cases with relatively small frequencies of "oversocialized" individuals willing to make extreme sacrifices for their groups no matter material costs, as well as "undersocialized" individuals completely immune to social norms. Evolving the ability to internalize norms was likely a crucial step on the path to large-scale human cooperation.

Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations

PubMed Central

Brocke, Ekaterina; Bhalla, Upinder S.; Djurfeldt, Mikael; Hellgren Kotaleski, Jeanette; Hanke, Michael

2016-01-01

Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience. PMID:27672364

Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations.

PubMed

Brocke, Ekaterina; Bhalla, Upinder S; Djurfeldt, Mikael; Hellgren Kotaleski, Jeanette; Hanke, Michael

2016-01-01

Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience.

NORM management in the oil and gas industry.

PubMed

Cowie, M; Mously, K; Fageeha, O; Nassar, R

2012-01-01

It has been established that naturally occurring radioactive material (NORM) may accumulate at various locations along the oil and gas production process. Components such as wellheads, separation vessels, pumps, and other processing equipment can become contaminated with NORM, and NORM can accumulate in the form of sludge, scale, scrapings, and other waste media. This can create a potential radiation hazard to workers, the general public, and the environment if certain controls are not established. Saudi Aramco has developed NORM management guidelines, and is implementing a comprehensive strategy to address all aspects of NORM management that aim to enhance NORM monitoring; control of NORM-contaminated equipment; control of NORM waste handling and disposal; and protection, awareness, and training of workers. The benefits of shared knowledge, best practice, and experience across the oil and gas industry are seen as key to the establishment of common guidance. This paper outlines Saudi Aramco's experience in the development of a NORM management strategy, and its goals of establishing common guidance throughout the oil and gas industry. Copyright © 2012. Published by Elsevier Ltd.

Extensive theoretical/numerical comparative studies on H2 and generalised H2 norms in sampled-data systems

NASA Astrophysics Data System (ADS)

Kim, Jung Hoon; Hagiwara, Tomomichi

2017-11-01

This paper is concerned with linear time-invariant (LTI) sampled-data systems (by which we mean sampled-data systems with LTI generalised plants and LTI controllers) and studies their H2 norms from the viewpoint of impulse responses and generalised H2 norms from the viewpoint of the induced norms from L2 to L∞. A new definition of the H2 norm of LTI sampled-data systems is first introduced through a sort of intermediate standpoint of those for the existing two definitions. We then establish unified treatment of the three definitions of the H2 norm through a matrix function G(τ) defined on the sampling interval [0, h). This paper next considers the generalised H2 norms, in which two types of the L∞ norm of the output are considered as the temporal supremum magnitude under the spatial 2-norm and ∞-norm of a vector-valued function. We further give unified treatment of the generalised H2 norms through another matrix function F(θ) which is also defined on [0, h). Through a close connection between G(τ) and F(θ), some theoretical relationships between the H2 and generalised H2 norms are provided. Furthermore, appropriate extensions associated with the treatment of G(τ) and F(θ) to the closed interval [0, h] are discussed to facilitate numerical computations and comparisons of the H2 and generalised H2 norms. Through theoretical and numerical studies, it is shown that the two generalised H2 norms coincide with neither of the three H2 norms of LTI sampled-data systems even though all the five definitions coincide with each other when single-output continuous-time LTI systems are considered as a special class of LTI sampled-data systems. To summarise, this paper clarifies that the five control performance measures are mutually related with each other but they are also intrinsically different from each other.

Alcohol Expectancies, Perceived Norms and Drinking Behavior among College Students: Examining the Reciprocal Determinism Hypothesis

PubMed Central

Wardell, Jeffrey D.; Read, Jennifer P.

2012-01-01

Social learning mechanisms, such as descriptive norms for drinking behavior (norms) and positive alcohol expectancies (PAEs), play a major role in college student alcohol use. According to the principle of reciprocal determinism (Bandura, 1977), norms and PAEs should be reciprocally associated with alcohol use, each influencing one another over time. However, the nature of these prospective relationships for college students is in need of further investigation. This study provided the first examination of the unique reciprocal associations among norms, PAEs, and drinking together in a single model. PAEs become more stable with age, whereas norms are likely to be more dynamic upon college entry. Thus, we hypothesized that alcohol use would show stronger reciprocal associations with norms than with PAEs for college students. Students (N=557; 67% female) completed online measures of PAEs, norms and quantity and frequency of alcohol use in September of their first (T1), second (T2), and third (T3) years of college. Reciprocal associations were analyzed using a cross-lagged panel design. PAEs had unidirectional influences on frequency and quantity of alcohol use, with no prospective effects from alcohol use to PAEs. Reciprocal associations were observed between norms and alcohol use, but only for quantity and not frequency. Specifically, drinking quantity prospectively predicted quantity norms and quantity norms prospectively predicted drinking quantity. This effect was observed across both years in the model. These findings support the reciprocal determinism hypothesis for norms but not for PAEs in college students, and may help to inform norm-based interventions. PMID:23088403

Alcohol expectancies, perceived norms, and drinking behavior among college students: examining the reciprocal determinism hypothesis.

PubMed

Wardell, Jeffrey D; Read, Jennifer P

2013-03-01

Social learning mechanisms, such as descriptive norms for drinking behavior (norms) and positive alcohol expectancies (PAEs), play a major role in college student alcohol use. According to the principle of reciprocal determinism (Bandura, 1977), norms and PAEs should be reciprocally associated with alcohol use, each influencing one another over time. However, the nature of these prospective relationships for college students is in need of further investigation. This study provided the first examination of the unique reciprocal associations among norms, PAEs, and drinking together in a single model. PAEs become more stable with age, whereas norms are likely to be more dynamic upon college entry. Thus, we hypothesized that alcohol use would show stronger reciprocal associations with norms than with PAEs for college students. Students (N = 557; 67% women) completed online measures of PAEs, norms, and quantity and frequency of alcohol use in September of their first (T1), second (T2), and third (T3) years of college. Reciprocal associations were analyzed using a cross-lagged panel design. PAEs had unidirectional influences on frequency and quantity of alcohol use, with no prospective effects from alcohol use to PAEs. Reciprocal associations were observed between norms and alcohol use, but only for quantity and not for frequency. Specifically, drinking quantity prospectively predicted quantity norms and quantity norms prospectively predicted drinking quantity. This effect was observed across both years in the model. These findings support the reciprocal determinism hypothesis for norms but not for PAEs in college students and may help to inform norm-based interventions. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

A Liver-centric Multiscale Modeling Framework for Xenobiotics

EPA Science Inventory

We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study foc...

Regulating Gender Performances: Power and Gender Norms in Faculty Work

ERIC Educational Resources Information Center

Lester, Jaime

2011-01-01

Despite the steady increase of women in faculty positions over the last few decades and the research on gender norms in the academy, what remains unclear is why many female faculty continue to conform to gender norms despite their acknowledgement of the discriminatory nature of these norms, their dissatisfaction performing the norms, and the lack…

Explaining Fertility Norms in the Netherlands: The Influence of Sociodemographics, Family Networks, and Life Course Events on Pronatalism

ERIC Educational Resources Information Center

Noordhuizen, Suzanne; de Graaf, Paul M.; Sieben, Inge

2011-01-01

This study advances our understanding of fertility norms by examining whether fertility norms remain stable over time. In addition, this article also investigates whether these norms are influenced by (a) sociodemographic background characteristics; (b) fertility norms of close family members: partners, siblings, parents, and children; and (c)…

Identity in agent-based models : modeling dynamic multiscale social processes.

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

Ozik, J.; Sallach, D. L.; Macal, C. M.

Identity-related issues play central roles in many current events, including those involving factional politics, sectarianism, and tribal conflicts. Two popular models from the computational-social-science (CSS) literature - the Threat Anticipation Program and SharedID models - incorporate notions of identity (individual and collective) and processes of identity formation. A multiscale conceptual framework that extends some ideas presented in these models and draws other capabilities from the broader CSS literature is useful in modeling the formation of political identities. The dynamic, multiscale processes that constitute and transform social identities can be mapped to expressive structures of the framework

A MULTISCALE FRAMEWORK FOR THE STOCHASTIC ASSIMILATION AND MODELING OF UNCERTAINTY ASSOCIATED NCF COMPOSITE MATERIALS

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

Mehrez, Loujaine; Ghanem, Roger; McAuliffe, Colin

multiscale framework to construct stochastic macroscopic constitutive material models is proposed. A spectral projection approach, specifically polynomial chaos expansion, has been used to construct explicit functional relationships between the homogenized properties and input parameters from finer scales. A homogenization engine embedded in Multiscale Designer, software for composite materials, has been used for the upscaling process. The framework is demonstrated using non-crimp fabric composite materials by constructing probabilistic models of the homogenized properties of a non-crimp fabric laminate in terms of the input parameters together with the homogenized properties from finer scales.

Rough Set Approach to Incomplete Multiscale Information System

PubMed Central

Yang, Xibei; Qi, Yong; Yu, Dongjun; Yu, Hualong; Song, Xiaoning; Yang, Jingyu

2014-01-01

Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852

An Overview of the State of the Art in Atomistic and Multiscale Simulation of Fracture

NASA Technical Reports Server (NTRS)

Saether, Erik; Yamakov, Vesselin; Phillips, Dawn R.; Glaessgen, Edward H.

2009-01-01

The emerging field of nanomechanics is providing a new focus in the study of the mechanics of materials, particularly in simulating fundamental atomic mechanisms involved in the initiation and evolution of damage. Simulating fundamental material processes using first principles in physics strongly motivates the formulation of computational multiscale methods to link macroscopic failure to the underlying atomic processes from which all material behavior originates. This report gives an overview of the state of the art in applying concurrent and sequential multiscale methods to analyze damage and failure mechanisms across length scales.

The multiscale nature of magnetic pattern on the solar surface

NASA Astrophysics Data System (ADS)

Scardigli, S.; Del Moro, D.; Berrilli, F.

Multiscale magnetic underdense regions (voids) appear in high resolution magnetograms of quiet solar surface. These regions may be considered a signature of the underlying convective structure. The study of the associated pattern paves the way for the study of turbulent convective scales from granular to global. In order to address the question of magnetic pattern driven by turbulent convection we used a novel automatic void detection method to calculate void distributions. The absence of preferred scales of organization in the calculated distributions supports the multiscale nature of flows on the solar surface and the absence of preferred convective scales.

A real-time multi-scale 2D Gaussian filter based on FPGA

NASA Astrophysics Data System (ADS)

Luo, Haibo; Gai, Xingqin; Chang, Zheng; Hui, Bin

2014-11-01

Multi-scale 2-D Gaussian filter has been widely used in feature extraction (e.g. SIFT, edge etc.), image segmentation, image enhancement, image noise removing, multi-scale shape description etc. However, their computational complexity remains an issue for real-time image processing systems. Aimed at this problem, we propose a framework of multi-scale 2-D Gaussian filter based on FPGA in this paper. Firstly, a full-hardware architecture based on parallel pipeline was designed to achieve high throughput rate. Secondly, in order to save some multiplier, the 2-D convolution is separated into two 1-D convolutions. Thirdly, a dedicate first in first out memory named as CAFIFO (Column Addressing FIFO) was designed to avoid the error propagating induced by spark on clock. Finally, a shared memory framework was designed to reduce memory costs. As a demonstration, we realized a 3 scales 2-D Gaussian filter on a single ALTERA Cyclone III FPGA chip. Experimental results show that, the proposed framework can computing a Multi-scales 2-D Gaussian filtering within one pixel clock period, is further suitable for real-time image processing. Moreover, the main principle can be popularized to the other operators based on convolution, such as Gabor filter, Sobel operator and so on.

Multiscale model reduction for shale gas transport in poroelastic fractured media

NASA Astrophysics Data System (ADS)

Akkutlu, I. Yucel; Efendiev, Yalchin; Vasilyeva, Maria; Wang, Yuhe

2018-01-01

Inherently coupled flow and geomechanics processes in fractured shale media have implications for shale gas production. The system involves highly complex geo-textures comprised of a heterogeneous anisotropic fracture network spatially embedded in an ultra-tight matrix. In addition, nonlinearities due to viscous flow, diffusion, and desorption in the matrix and high velocity gas flow in the fractures complicates the transport. In this paper, we develop a multiscale model reduction approach to couple gas flow and geomechanics in fractured shale media. A Discrete Fracture Model (DFM) is used to treat the complex network of fractures on a fine grid. The coupled flow and geomechanics equations are solved using a fixed stress-splitting scheme by solving the pressure equation using a continuous Galerkin method and the displacement equation using an interior penalty discontinuous Galerkin method. We develop a coarse grid approximation and coupling using the Generalized Multiscale Finite Element Method (GMsFEM). GMsFEM constructs the multiscale basis functions in a systematic way to capture the fracture networks and their interactions with the shale matrix. Numerical results and an error analysis is provided showing that the proposed approach accurately captures the coupled process using a few multiscale basis functions, i.e. a small fraction of the degrees of freedom of the fine-scale problem.

Multiscale deformation behavior for multilayered steel by in-situ FE-SEM

NASA Astrophysics Data System (ADS)

Tanaka, Y.; Kishimoto, S.; Yin, F.; Kobayashi, M.; Tomimatsu, T.; Kagawa, K.

2010-03-01

The multi-scale deformation behavior of multi-layered steel during tensile loading was investigated by in-situ FE-SEM observation coupled with multi-scale pattern. The material used was multi-layered steel sheet consisting of martensitic and austenitic stainless steel layers. Prior to in-situ tensile testing, the multi-scale pattern combined with a grid and random dots were fabricated by electron beam lithography on the polished surface in the area of 1 mm2 to facilitate direct observation of multi-scale deformation. Both of the grids with pitches of 10 μm and a random speckle pattern ranging from 200 nm to a few μm sizes were drawn onto the specimen surface at same location. The electron moiré method was applied to measure the strain distribution in the deformed specimens at a millimeter scale and digital images correlation method was applied to measure the in-plane deformation and strain distribution at a micron meter scale acquired before and after at various increments of straining. The results showed that the plastic deformation in the austenitic stainless steel layer was larger than the martensitic steel layer at millimeter scale. However, heterogeneous intrinsic grain-scale plastic deformation was clearly observed and it increased with increasing the plastic deformation.

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

Multiscale Granger causality

NASA Astrophysics Data System (ADS)

Faes, Luca; Nollo, Giandomenico; Stramaglia, Sebastiano; Marinazzo, Daniele

2017-10-01

In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. While methods to assess the dynamic complexity of individual processes at different time scales are well established, multiscale analysis of directed interactions has never been formalized theoretically, and empirical evaluations are complicated by practical issues such as filtering and downsampling. Here we extend the very popular measure of Granger causality (GC), a prominent tool for assessing directed lagged interactions between joint processes, to quantify information transfer across multiple time scales. We show that the multiscale processing of a vector autoregressive (AR) process introduces a moving average (MA) component, and describe how to represent the resulting ARMA process using state space (SS) models and to combine the SS model parameters for computing exact GC values at arbitrarily large time scales. We exploit the theoretical formulation to identify peculiar features of multiscale GC in basic AR processes, and demonstrate with numerical simulations the much larger estimation accuracy of the SS approach compared to pure AR modeling of filtered and downsampled data. The improved computational reliability is exploited to disclose meaningful multiscale patterns of information transfer between global temperature and carbon dioxide concentration time series, both in paleoclimate and in recent years.

Revisiting of Multiscale Static Analysis of Notched Laminates Using the Generalized Method of Cells

NASA Technical Reports Server (NTRS)

Naghipour Ghezeljeh, Paria; Arnold, Steven M.; Pineda, Evan J.

2016-01-01

Composite material systems generally exhibit a range of behavior on different length scales (from constituent level to macro); therefore, a multiscale framework is beneficial for the design and engineering of these material systems. The complex nature of the observed composite failure during experiments suggests the need for a three-dimensional (3D) multiscale model to attain a reliable prediction. However, the size of a multiscale three-dimensional finite element model can become prohibitively large and computationally costly. Two-dimensional (2D) models are preferred due to computational efficiency, especially if many different configurations have to be analyzed for an in-depth damage tolerance and durability design study. In this study, various 2D and 3D multiscale analyses will be employed to conduct a detailed investigation into the tensile failure of a given multidirectional, notched carbon fiber reinforced polymer laminate. Threedimensional finite element analysis is typically considered more accurate than a 2D finite element model, as compared with experiments. Nevertheless, in the absence of adequate mesh refinement, large differences may be observed between a 2D and 3D analysis, especially for a shear-dominated layup. This observed difference has not been widely addressed in previous literature and is the main focus of this paper.

Blood Flow: Multi-scale Modeling and Visualization (July 2011)

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

None

2011-01-01

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations. This animation presents early results of two studies used in the development of a multi-scale visualization methodology. The fisrt illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each bloodmore » cell is represented by a mesh, small spheres show a sub-set of particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. In the second we investigate the process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of an aneruysm. Simulation was performed on Kraken at the National Institute for Computational Sciences. Visualization was produced using resources of the Argonne Leadership Computing Facility at Argonne National Laboratory.« less

Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement

PubMed Central

Han, Zhenyu; Sun, Shouzheng; Fu, Hongya; Fu, Yunzhong

2017-01-01

Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro–meso–scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy–enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy–enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates. PMID:28869520

Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement.

PubMed

Han, Zhenyu; Sun, Shouzheng; Fu, Hongya; Fu, Yunzhong

2017-09-03

Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro-meso-scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy-enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy-enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates.

Multiscale information modelling for heart morphogenesis

NASA Astrophysics Data System (ADS)

Abdulla, T.; Imms, R.; Schleich, J. M.; Summers, R.

2010-07-01

Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.

Multiscale Magnetic Underdense Regions on the Solar Surface: Granular and Mesogranular Scales

NASA Astrophysics Data System (ADS)

Berrilli, F.; Scardigli, S.; Giordano, S.

2013-02-01

The Sun is a non-equilibrium, dissipative system subject to an energy flow that originates in its core. Convective overshooting motions create temperature and velocity structures that show a temporal and spatial multiscale evolution. As a result, photospheric structures are generally considered to be a direct manifestation of convective plasma motions. The plasma flows in the photosphere govern the motion of single magnetic elements. These elements are arranged in typical patterns, which are observed as a variety of multiscale magnetic patterns. High-resolution magnetograms of the quiet solar surface revealed the presence of multiscale magnetic underdense regions in the solar photosphere, commonly called voids, which may be considered to be a signature of the underlying convective structure. The analysis of such patterns paves the way for the investigation of all turbulent convective scales, from granular to global. In order to address the question of magnetic structures driven by turbulent convection at granular and mesogranular scales, we used a voids-detection method. The computed distribution of void length scales shows an exponential behavior at scales between 2 and 10 Mm and the absence of features at mesogranular scales. The absence of preferred scales of organization in the 2 - 10 Mm range supports the multiscale nature of flows on the solar surface and the absence of a mesogranular convective scale.

Covariance, correlation matrix, and the multiscale community structure of networks.

PubMed

Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing

2010-07-01

Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.

Time lag and communication in changing unpopular norms.

PubMed

Gërxhani, Klarita; Bruggeman, Jeroen

2015-01-01

Humans often coordinate their social lives through norms. When a large majority of people are dissatisfied with an existing norm, it seems obvious that they will change it. Often, however, this does not occur. We investigate how a time lag between individual support of a norm change and the change itself hinders such change, related to the critical mass of supporters needed to effectuate the change, and the (im)possibility of communicating about it. To isolate these factors, we utilize a laboratory experiment. As predicted, we find unambiguous effects of time lag on precluding norm change; a higher threshold for a critical mass does so as well. Communication facilitates choosing superior norms but it does not necessarily lead to norm change when the uncertainty on whether there will be a norm change in the future is high. Communication seems to help coordination on actions at the present but not the future. Hence, the uncertainty driven by time lag makes individuals choose the status quo, here the unpopular norm.

Contests versus Norms: Implications of Contest-Based and Norm-Based Intervention Techniques

PubMed Central

Bergquist, Magnus; Nilsson, Andreas; Hansla, André

2017-01-01

Interventions using either contests or norms can promote environmental behavioral change. Yet research on the implications of contest-based and norm-based interventions is lacking. Based on Goal-framing theory, we suggest that a contest-based intervention frames a gain goal promoting intensive but instrumental behavioral engagement. In contrast, the norm-based intervention was expected to frame a normative goal activating normative obligations for targeted and non-targeted behavior and motivation to engage in pro-environmental behaviors in the future. In two studies participants (n = 347) were randomly assigned to either a contest- or a norm-based intervention technique. Participants in the contest showed more intensive engagement in both studies. Participants in the norm-based intervention tended to report higher intentions for future energy conservation (Study 1) and higher personal norms for non-targeted pro-environmental behaviors (Study 2). These findings suggest that contest-based intervention technique frames a gain goal, while norm-based intervention frames a normative goal. PMID:29218026

Contests versus Norms: Implications of Contest-Based and Norm-Based Intervention Techniques.

PubMed

Bergquist, Magnus; Nilsson, Andreas; Hansla, André

2017-01-01

Interventions using either contests or norms can promote environmental behavioral change. Yet research on the implications of contest-based and norm-based interventions is lacking. Based on Goal-framing theory, we suggest that a contest-based intervention frames a gain goal promoting intensive but instrumental behavioral engagement. In contrast, the norm-based intervention was expected to frame a normative goal activating normative obligations for targeted and non-targeted behavior and motivation to engage in pro-environmental behaviors in the future. In two studies participants ( n = 347) were randomly assigned to either a contest- or a norm-based intervention technique. Participants in the contest showed more intensive engagement in both studies. Participants in the norm-based intervention tended to report higher intentions for future energy conservation (Study 1) and higher personal norms for non-targeted pro-environmental behaviors (Study 2). These findings suggest that contest-based intervention technique frames a gain goal, while norm-based intervention frames a normative goal.

Norms as Group-Level Constructs: Investigating School-Level Teen Pregnancy Norms and Behaviors.

PubMed

Mollborn, Stefanie; Domingue, Benjamin W; Boardman, Jason D

2014-09-01

Social norms are a group-level phenomenon, but past quantitative research has rarely measured them in the aggregate or considered their group-level properties. We used the school-based design of the National Longitudinal Study of Adolescent Health to measure normative climates regarding teen pregnancy across 75 U.S. high schools. We distinguished between the strength of a school's norm against teen pregnancy and the consensus around that norm. School-level norm strength and dissensus were strongly (r = -0.65) and moderately (r = 0.34) associated with pregnancy prevalence within schools, respectively. Normative climate partially accounted for observed racial differences in school pregnancy prevalence, but norms were a stronger predictor than racial composition. As hypothesized, schools with both a stronger average norm against teen pregnancy and greater consensus around the norm had the lowest pregnancy prevalence. Results highlight the importance of group-level normative processes and of considering the local school environment when designing policies to reduce teen pregnancy.

Time Lag and Communication in Changing Unpopular Norms

PubMed Central

Gërxhani, Klarita; Bruggeman, Jeroen

2015-01-01

Humans often coordinate their social lives through norms. When a large majority of people are dissatisfied with an existing norm, it seems obvious that they will change it. Often, however, this does not occur. We investigate how a time lag between individual support of a norm change and the change itself hinders such change, related to the critical mass of supporters needed to effectuate the change, and the (im)possibility of communicating about it. To isolate these factors, we utilize a laboratory experiment. As predicted, we find unambiguous effects of time lag on precluding norm change; a higher threshold for a critical mass does so as well. Communication facilitates choosing superior norms but it does not necessarily lead to norm change when the uncertainty on whether there will be a norm change in the future is high. Communication seems to help coordination on actions at the present but not the future. Hence, the uncertainty driven by time lag makes individuals choose the status quo, here the unpopular norm. PMID:25880200

A Review of Norms and Normative Multiagent Systems

PubMed Central

Mahmoud, Moamin A.; Ahmad, Mohd Sharifuddin; Mustapha, Aida

2014-01-01

Norms and normative multiagent systems have become the subjects of interest for many researchers. Such interest is caused by the need for agents to exploit the norms in enhancing their performance in a community. The term norm is used to characterize the behaviours of community members. The concept of normative multiagent systems is used to facilitate collaboration and coordination among social groups of agents. Many researches have been conducted on norms that investigate the fundamental concepts, definitions, classification, and types of norms and normative multiagent systems including normative architectures and normative processes. However, very few researches have been found to comprehensively study and analyze the literature in advancing the current state of norms and normative multiagent systems. Consequently, this paper attempts to present the current state of research on norms and normative multiagent systems and propose a norm's life cycle model based on the review of the literature. Subsequently, this paper highlights the significant areas for future work. PMID:25110739

Robust subspace clustering via joint weighted Schatten-p norm and Lq norm minimization

NASA Astrophysics Data System (ADS)

Zhang, Tao; Tang, Zhenmin; Liu, Qing

2017-05-01

Low-rank representation (LRR) has been successfully applied to subspace clustering. However, the nuclear norm in the standard LRR is not optimal for approximating the rank function in many real-world applications. Meanwhile, the L21 norm in LRR also fails to characterize various noises properly. To address the above issues, we propose an improved LRR method, which achieves low rank property via the new formulation with weighted Schatten-p norm and Lq norm (WSPQ). Specifically, the nuclear norm is generalized to be the Schatten-p norm and different weights are assigned to the singular values, and thus it can approximate the rank function more accurately. In addition, Lq norm is further incorporated into WSPQ to model different noises and improve the robustness. An efficient algorithm based on the inexact augmented Lagrange multiplier method is designed for the formulated problem. Extensive experiments on face clustering and motion segmentation clearly demonstrate the superiority of the proposed WSPQ over several state-of-the-art methods.

Norms as Group-Level Constructs: Investigating School-Level Teen Pregnancy Norms and Behaviors

PubMed Central

Mollborn, Stefanie; Domingue, Benjamin W.; Boardman, Jason D.

2015-01-01

Social norms are a group-level phenomenon, but past quantitative research has rarely measured them in the aggregate or considered their group-level properties. We used the school-based design of the National Longitudinal Study of Adolescent Health to measure normative climates regarding teen pregnancy across 75 U.S. high schools. We distinguished between the strength of a school's norm against teen pregnancy and the consensus around that norm. School-level norm strength and dissensus were strongly (r = -0.65) and moderately (r = 0.34) associated with pregnancy prevalence within schools, respectively. Normative climate partially accounted for observed racial differences in school pregnancy prevalence, but norms were a stronger predictor than racial composition. As hypothesized, schools with both a stronger average norm against teen pregnancy and greater consensus around the norm had the lowest pregnancy prevalence. Results highlight the importance of group-level normative processes and of considering the local school environment when designing policies to reduce teen pregnancy. PMID:26074628

NORM Management in the Oil & Gas Industry

NASA Astrophysics Data System (ADS)

Cowie, Michael; Mously, Khalid; Fageeha, Osama; Nassar, Rafat

2008-08-01

It has been established that Naturally Occurring Radioactive Materials (NORM) accumulates at various locations along the oil/gas production process. Components such as wellheads, separation vessels, pumps, and other processing equipment can become NORM contaminated, and NORM can accumulate in sludge and other waste media. Improper handling and disposal of NORM contaminated equipment and waste can create a potential radiation hazard to workers and the environment. Saudi Aramco Environmental Protection Department initiated a program to identify the extent, form and level of NORM contamination associated with the company operations. Once identified the challenge of managing operations which had a NORM hazard was addressed in a manner that gave due consideration to workers and environmental protection as well as operations' efficiency and productivity. The benefits of shared knowledge, practice and experience across the oil & gas industry are seen as key to the establishment of common guidance on NORM management. This paper outlines Saudi Aramco's experience in the development of a NORM management strategy and its goals of establishing common guidance throughout the oil and gas industry.

Fibrous tissues growth and remodeling: Evolutionary micro-mechanical theory

NASA Astrophysics Data System (ADS)

Lanir, Yoram

2017-10-01

Living fibrous tissues are composite materials having the unique ability to adapt their size, shape, structure and mechanical properties in response to external loading. This adaptation, termed growth and remodeling (G&R), occurs throughout life and is achieved via cell-induced turnover of tissue constituents where some are degraded and new ones are produced. Realistic mathematical modeling of G&R provides insight into the basic processes, allows for hypotheses testing, and constitutes an essential tool for establishing clinical thresholds of pathological remodeling and for the production of tissue substitutes aimed to achieve target structure and properties. In this study, a general 3D micro-mechanical multi-scale theory of G&R in fibrous tissue was developed which connects between the evolution of the tissue structure and properties, and the underlying mechano-biological turnover events of its constituents. This structural approach circumvents a fundamental obstacle in modeling growth mechanics since the growth motion is not bijective. The model was realized for a flat tissue under two biaxial external loadings using data-based parameter values. The predictions show close similarity to characteristics of remodeled adult tissue including its structure, anisotropic and non-linear mechanical properties, and the onset of in situ pre-strain and pre-stress. The results suggest that these important features of living fibrous tissues evolve as they grow.

How preschoolers react to norm violations is associated with culture.

PubMed

Gampe, Anja; Daum, Moritz M

2018-01-01

Children from the age of 3years understand social norms as such and enforce these norms in interactions with others. Differences in parental and institutional education across cultures make it likely that children receive divergent information about how to act in cases of norm violations. In the current study, we investigated whether cultural values are associated with the ways in which children react to norm violations. We tested 80 bicultural 3-year-olds with a norm enforcement paradigm and analyzed their reactions to norm violations. The reactions were correlated to the children's parental cultural values using the Global Leadership and Organizational Behavior Effectiveness (GLOBE) scales, and these results show that parental culture was associated with children's reactions to norm violations. The three strongest correlations were found for institutional collectivism, performance orientation, and assertiveness. Copyright © 2017 Elsevier Inc. All rights reserved.

Perceived peer drinking norms and responsible drinking in UK university settings.

PubMed

Robinson, Eric; Jones, Andrew; Christiansen, Paul; Field, Matt

2014-09-01

Heavy drinking is common among students at UK universities. US students overestimate how much their peers drink and correcting this through the use of social norm messages may promote responsible drinking. We tested whether there is an association between perceived campus drinking norms and usual drinking behavior in UK university students and whether norm messages about responsible drinking correct normative misperceptions and increase students' intentions to drink responsibly. 1,020 UK university students took part in an online study. Participants were exposed to one of five message types: a descriptive norm, an injunctive norm, a descriptive and injunctive norm, or one of two control messages. Message credibility was assessed. Afterwards participants completed measures of intentions to drink responsibly and we measured usual drinking habits and perceptions of peer drinking. Perceptions of peer drinking were associated modestly with usual drinking behavior, whereby participants who believed other students drank responsibly also drank responsibly. Norm messages changed normative perceptions, but not in the target population of participants who underestimated responsible drinking in their peers at baseline. Norm messages did not increase intentions to drink responsibly and although based on accurate data, norm messages were not seen as credible. In this UK based study, although perceived social norms about peer drinking were associated with individual differences in drinking habits, campus wide norm messages about responsible drinking did not affect students' intentions to drink more responsibly. More research is required to determine if this approach can be applied to UK settings.

The Role of Perceived Injunctive Alcohol Norms in Adolescent Drinking Behavior

PubMed Central

Pedersen, Eric R.; Osilla, Karen Chan; Miles, Jeremy N.V.; Tucker, Joan S.; Ewing, Brett A.; Shih, Regina A.; D’Amico, Elizabeth J.

2016-01-01

Peers have a major influence on youth during adolescence, and perceptions about peer alcohol use (perceived norms) are often associated with personal drinking behavior among youth. Most of the research on perceived norms among adolescents focuses on perceived descriptive norms only, or perceptions about peers’ behavior, and correcting these perceptions are a major focus of many prevention programs with adolescents. In contrast, perceived injunctive norms, which are personal perceptions about peers’ attitudes regarding the acceptability of behaviors, have been minimally examined in the adolescent drinking literature. Yet correcting perceptions about these perceived peer attitudes may be an important component to include in prevention programs with youth. Using a sample of 2,493 high school-aged youth (mean age = 17.3), we assessed drinking behavior (past year use; past month frequency, quantity, and peak drinks), drinking consequences, and perceived descriptive and injunctive norms to examine the relationships of perceived injunctive and descriptive norms on adolescent drinking behavior. Findings indicated that although perceived descriptive norms were associated with some drinking outcomes (past year use; past month frequency; past month quantity; peak drinks), perceived injunctive norms were associated with all drinking outcomes, including outcomes of consequences, even after controlling for perceived descriptive norms. Findings suggest that consideration of perceived injunctive norms may be important in models of adolescent drinking. Prevention programs that do not include injunctive norms feedback may miss an important opportunity to enhance effectiveness of such prevention programs targeting adolescent alcohol use. PMID:27978424

An Abbreviated Tool for Assessing Feminine Norm Conformity: Psychometric Properties of the Conformity to Feminine Norms Inventory-45

ERIC Educational Resources Information Center

Parent, Mike C.; Moradi, Bonnie

2011-01-01

The Conformity to Feminine Norms Inventory-45 (CFNI-45; Parent & Moradi, 2010) is an important tool for assessing level of conformity to feminine gender norms and for investigating the implications of such norms for women's functioning. The authors of the present study assessed the factor structure, measurement invariance, reliability, and…

Prosocial norms as a positive youth development construct: a conceptual review.

PubMed

Siu, Andrew M H; Shek, Daniel T L; Law, Ben

2012-01-01

Prosocial norms like reciprocity, social responsibility, altruism, and volunteerism are ethical standards and beliefs that youth development programs often want to promote. This paper reviews evolutionary, social-cognitive, and developmental theories of prosocial development and analyzes how young people learn and adopt prosocial norms. The paper showed that very few current theories explicitly address the issue of how prosocial norms, in form of feelings of moral obligations, may be challenged by a norm of self-interest and social circumstances when prosocial acts are needed. It is necessary to develop theories which put prosocial norms as a central construct, and a new social cognitive theory of norm activation has the potential to help us understand how prosocial norms may be applied. This paper also highlights how little we know about young people perceiving and receiving prosocial norms and how influential of school policies and peer influence on the prosocial development. Lastly, while training of interpersonal competence (e.g., empathy, moral reasoning, etc.) was commonly used in the youth development, their effectiveness was not systematically evaluated. It will also be interesting to examine how computer and information technology or video games may be used in e-learning of prosocial norms.

Shifting more than the goal posts: developing classroom norms of inquiry-based learning in mathematics

NASA Astrophysics Data System (ADS)

Makar, Katie; Fielding-Wells, Jill

2018-03-01

The 3-year study described in this paper aims to create new knowledge about inquiry norms in primary mathematics classrooms. Mathematical inquiry addresses complex problems that contain ambiguities, yet classroom environments often do not adopt norms that promote curiosity, risk-taking and negotiation needed to productively engage with complex problems. Little is known about how teachers and students initiate, develop and maintain norms of mathematical inquiry in primary classrooms. The research question guiding this study is, "How do classroom norms develop that facilitate student learning in primary classrooms which practice mathematical inquiry?" The project will (1) analyse a video archive of inquiry lessons to identify signature practices that enhance productive classroom norms of mathematical inquiry and facilitate learning, (2) engage expert inquiry teachers to collaborate to identify and design strategies for assisting teachers to develop and sustain norms over time that are conducive to mathematical inquiry and (3) support and study teachers new to mathematical inquiry adopting these practices in their classrooms. Anticipated outcomes include identification and illustration of classroom norms of mathematical inquiry, signature practices linked to these norms and case studies of primary teachers' progressive development of classroom norms of mathematical inquiry and how they facilitate learning.

Modeling the relationship between descriptive norms and behaviors: a test and extension of the theory of normative social behavior (TNSB).

PubMed

Rimal, Rajiv N

2008-01-01

Informed by the theory of normative social behavior, this article sought to determine the underlying mediating and moderating factors in the relationship between descriptive norms and behavioral intentions. Furthermore, the theory was extended by asking whether and what role behavioral identity played in normative influences. Simulating the central message of norms-based interventions to reduce college students' alcohol consumption, in this field experiment, descriptive norms were manipulated by informing half of the students (n = 665) that their peers consumed less alcohol than they might believe. Others (n = 672) were not provided any norms information. students' injunctive norms, outcome expectations, group identity, behavioral identity, and behavioral intention surrounding alcohol consumption were then measured. Exposure to the low-norms information resulted in a significant drop in estimates of the prevalence of consumption. Injunctive norms and outcome expectations partially mediated and also moderated the relationship between descriptive norms and behavioral intentions. Group identity and behavioral identity also moderated the relationship between descriptive norms and behavioral intentions, but the effect size was relatively small for group identity. Implications for health campaigns are also discussed.

Prosocial Norms as a Positive Youth Development Construct: A Conceptual Review

PubMed Central

Siu, Andrew M. H.; Shek, Daniel T. L.; Law, Ben

2012-01-01

Prosocial norms like reciprocity, social responsibility, altruism, and volunteerism are ethical standards and beliefs that youth development programs often want to promote. This paper reviews evolutionary, social-cognitive, and developmental theories of prosocial development and analyzes how young people learn and adopt prosocial norms. The paper showed that very few current theories explicitly address the issue of how prosocial norms, in form of feelings of moral obligations, may be challenged by a norm of self-interest and social circumstances when prosocial acts are needed. It is necessary to develop theories which put prosocial norms as a central construct, and a new social cognitive theory of norm activation has the potential to help us understand how prosocial norms may be applied. This paper also highlights how little we know about young people perceiving and receiving prosocial norms and how influential of school policies and peer influence on the prosocial development. Lastly, while training of interpersonal competence (e.g., empathy, moral reasoning, etc.) was commonly used in the youth development, their effectiveness was not systematically evaluated. It will also be interesting to examine how computer and information technology or video games may be used in e-learning of prosocial norms. PMID:22666157

Not just the norm: exemplar-based models also predict face aftereffects.

PubMed

Ross, David A; Deroche, Mickael; Palmeri, Thomas J

2014-02-01

The face recognition literature has considered two competing accounts of how faces are represented within the visual system: Exemplar-based models assume that faces are represented via their similarity to exemplars of previously experienced faces, while norm-based models assume that faces are represented with respect to their deviation from an average face, or norm. Face identity aftereffects have been taken as compelling evidence in favor of a norm-based account over an exemplar-based account. After a relatively brief period of adaptation to an adaptor face, the perceived identity of a test face is shifted toward a face with attributes opposite to those of the adaptor, suggesting an explicit psychological representation of the norm. Surprisingly, despite near universal recognition that face identity aftereffects imply norm-based coding, there have been no published attempts to simulate the predictions of norm- and exemplar-based models in face adaptation paradigms. Here, we implemented and tested variations of norm and exemplar models. Contrary to common claims, our simulations revealed that both an exemplar-based model and a version of a two-pool norm-based model, but not a traditional norm-based model, predict face identity aftereffects following face adaptation.

Adaptation and perceptual norms

NASA Astrophysics Data System (ADS)

Webster, Michael A.; Yasuda, Maiko; Haber, Sara; Leonard, Deanne; Ballardini, Nicole

2007-02-01

We used adaptation to examine the relationship between perceptual norms--the stimuli observers describe as psychologically neutral, and response norms--the stimulus levels that leave visual sensitivity in a neutral or balanced state. Adapting to stimuli on opposite sides of a neutral point (e.g. redder or greener than white) biases appearance in opposite ways. Thus the adapting stimulus can be titrated to find the unique adapting level that does not bias appearance. We compared these response norms to subjectively defined neutral points both within the same observer (at different retinal eccentricities) and between observers. These comparisons were made for visual judgments of color, image focus, and human faces, stimuli that are very different and may depend on very different levels of processing, yet which share the property that for each there is a well defined and perceptually salient norm. In each case the adaptation aftereffects were consistent with an underlying sensitivity basis for the perceptual norm. Specifically, response norms were similar to and thus covaried with the perceptual norm, and under common adaptation differences between subjectively defined norms were reduced. These results are consistent with models of norm-based codes and suggest that these codes underlie an important link between visual coding and visual experience.

Not Just the Norm: Exemplar-Based Models also Predict Face Aftereffects

PubMed Central

Ross, David A.; Deroche, Mickael; Palmeri, Thomas J.

2014-01-01

The face recognition literature has considered two competing accounts of how faces are represented within the visual system: Exemplar-based models assume that faces are represented via their similarity to exemplars of previously experienced faces, while norm-based models assume that faces are represented with respect to their deviation from an average face, or norm. Face identity aftereffects have been taken as compelling evidence in favor of a norm-based account over an exemplar-based account. After a relatively brief period of adaptation to an adaptor face, the perceived identity of a test face is shifted towards a face with opposite attributes to the adaptor, suggesting an explicit psychological representation of the norm. Surprisingly, despite near universal recognition that face identity aftereffects imply norm-based coding, there have been no published attempts to simulate the predictions of norm- and exemplar-based models in face adaptation paradigms. Here we implemented and tested variations of norm and exemplar models. Contrary to common claims, our simulations revealed that both an exemplar-based model and a version of a two-pool norm-based model, but not a traditional norm-based model, predict face identity aftereffects following face adaptation. PMID:23690282

Social influences among young drivers on talking on the mobile phone while driving.

PubMed

Riquelme, Hernan E; Al-Sammak, Fawaz Saleh; Rios, Rosa E

2010-04-01

This study set out to measure the influence of injunctive, subjective, verbal, and behavioral norms on talking on a mobile phone while driving. In particular it examines social influences that have been neglected in past research, namely, injunctive norms and explicit verbal and behavioral norms communicated by law enforcers with regard to using a mobile phone when driving. All four types of social norms have rarely been used in studies of this social phenomenon, except for occasional exceptions drawing on Ajzen's theory of planned behavior, which addresses only one: subjective norms. Regression analysis of data collected from young drivers from 217 questionnaires is used to predict the intention of motorists to continue talking on their mobile phones while driving. Selective interaction effects, the purpose of the call, and injunctive and subjective norms were included. The results show that the explicit verbal and behavioral law enforcement norms, the subjective norms, and the interaction of the injunctive norm with the purpose of the call are significant predictors of the unlawful behavior. The results taken together seem to imply that social marketing is likely to encounter difficulty in changing behavior because the subjective norm (what others think I should do) coupled with the lack of enforcement (verbal norms) play important roles in maintaining the unlawful behavior. Moreover, the perception that talking on the mobile phone while driving is acceptable behavior (injunctive norm) in conjunction with the purpose of the call create further challenges to social marketers. The results have implications on policy makers and enforcers. Law enforcers should do their job to prevent the wrong behavior in the first place. In addition, campaigns may be directed to convince the target audience about the false norms and use persuasive communication to emphasize the potential costs of maintaining the unlawful behavior.

How embarrassing! The behavioral and neural correlates of processing social norm violations

PubMed Central

van Steenbergen, Henk; Kreuk, Tanja; van der Wee, Nic J. A.; Westenberg, P. Michiel

2017-01-01

Social norms are important for human social interactions, and violations of these norms are evaluated partly on the intention of the actor. Here, we describe the revised Social Norm Processing Task (SNPT-R), a paradigm enabling the study of behavioral and neural responses to intended and unintended social norm violations among both adults and adolescents. We investigated how participants (adolescents and adults, n = 87) rate intentional and unintentional social norm violations with respect to inappropriateness and embarrassment, and we examined the brain activation patterns underlying the processing of these transgressions in an independent sample of 21 adults using functional Magnetic Resonance Imaging (fMRI). We hypothesized to find activation within the medial prefrontal cortex, temporo-parietal cortex and orbitofrontal cortex in response to both intentional and unintentional social norm violations, with more pronounced activation for the intentional social norm violations in these regions and in the amygdala. Participants’ ratings confirmed the hypothesis that the three types of stories are evaluated differently with respect to intentionality: intentional social norm violations were rated as the most inappropriate and most embarrassing. Furthermore, fMRI results showed that reading stories on intentional and unintentional social norm violations evoked activation within the frontal pole, the paracingulate gyrus and the superior frontal gyrus. In addition, processing unintentional social norm violations was associated with activation in, among others, the orbitofrontal cortex, middle frontal gyrus and superior parietal lobule, while reading intentional social norm violations was related to activation in the left amygdala. These regions have been previously implicated in thinking about one’s self, thinking about others and moral reasoning. Together, these findings indicate that the SNPT-R could serve as a useful paradigm for examining social norm processing, both at the behavioral and the neural level. PMID:28441460

How gender- and violence-related norms affect self-esteem among adolescent refugee girls living in Ethiopia.

PubMed

Stark, L; Asghar, K; Seff, I; Cislaghi, B; Yu, G; Tesfay Gessesse, T; Eoomkham, J; Assazenew Baysa, A; Falb, K

2018-01-01

Evidence suggests adolescent self-esteem is influenced by beliefs of how individuals in their reference group perceive them. However, few studies examine how gender- and violence-related social norms affect self-esteem among refugee populations. This paper explores relationships between gender inequitable and victim-blaming social norms, personal attitudes, and self-esteem among adolescent girls participating in a life skills program in three Ethiopian refugee camps. Ordinary least squares multivariable regression analysis was used to assess the associations between attitudes and social norms, and self-esteem. Key independent variables of interest included a scale measuring personal attitudes toward gender inequitable norms, a measure of perceived injunctive norms capturing how a girl believed her family and community would react if she was raped, and a peer-group measure of collective descriptive norms surrounding gender inequity. The key outcome variable, self-esteem, was measured using the Rosenberg self-esteem scale. Girl's personal attitudes toward gender inequitable norms were not significantly predictive of self-esteem at endline, when adjusting for other covariates. Collective peer norms surrounding the same gender inequitable statements were significantly predictive of self-esteem at endline ( ß  = -0.130; p   =  0.024). Additionally, perceived injunctive norms surrounding family and community-based sanctions for victims of forced sex were associated with a decline in self-esteem at endline ( ß  = -0.103; p   =  0.014). Significant findings for collective descriptive norms and injunctive norms remained when controlling for all three constructs simultaneously. Findings suggest shifting collective norms around gender inequity, particularly at the community and peer levels, may sustainably support the safety and well-being of adolescent girls in refugee settings.

COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (ONE ATMOSPHERE)

EPA Science Inventory

This task supports ORD's strategy by providing responsive technical support of EPA's mission and provides credible state of the art air quality models and guidance. This research effort is to develop and improve the Community Multiscale Air Quality (CMAQ) modeling system, a mu...

MULTISCALE AIR QUALITY SIMULATION PLATFORM (MAQSIP): INITIAL APPLICATIONS AND PERFORMANCE FOR TROPOSPHERIC OZONE AND PARTICULATE MATTER

EPA Science Inventory

This manuscript provides an overview of the formulation, process considerations, and performance for simulating tropospheric ozone and particulate matter distributions of the Multiscale Air Quality Simulation Platform (MAQSIP). MAQSIP is a comprehensive atmospheric chemistry/tran...

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

Multiscale modeling methods in biomechanics.

PubMed

Bhattacharya, Pinaki; Viceconti, Marco

2017-05-01

More and more frequently, computational biomechanics deals with problems where the portion of physical reality to be modeled spans over such a large range of spatial and temporal dimensions, that it is impossible to represent it as a single space-time continuum. We are forced to consider multiple space-time continua, each representing the phenomenon of interest at a characteristic space-time scale. Multiscale models describe a complex process across multiple scales, and account for how quantities transform as we move from one scale to another. This review offers a set of definitions for this emerging field, and provides a brief summary of the most recent developments on multiscale modeling in biomechanics. Of all possible perspectives, we chose that of the modeling intent, which vastly affect the nature and the structure of each research activity. To the purpose we organized all papers reviewed in three categories: 'causal confirmation,' where multiscale models are used as materializations of the causation theories; 'predictive accuracy,' where multiscale modeling is aimed to improve the predictive accuracy; and 'determination of effect,' where multiscale modeling is used to model how a change at one scale manifests in an effect at another radically different space-time scale. Consistent with how the volume of computational biomechanics research is distributed across application targets, we extensively reviewed papers targeting the musculoskeletal and the cardiovascular systems, and covered only a few exemplary papers targeting other organ systems. The review shows a research subdomain still in its infancy, where causal confirmation papers remain the most common. WIREs Syst Biol Med 2017, 9:e1375. doi: 10.1002/wsbm.1375 For further resources related to this article, please visit the WIREs website. © 2017 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

Changing Gender Norms and Marriage Dynamics in the United States.

PubMed

Pessin, Léa

2018-02-01

Using a regional measure of gender norms from the General Social Surveys together with marital histories from the Panel Study of Income Dynamics, this study explored how gender norms were associated with women's marriage dynamics between 1968 and 2012. Results suggested that a higher prevalence of egalitarian gender norms predicted a decline in marriage formation. This decline was, however, only true for women without a college degree. For college-educated women, the association between gender norms and marriage formation became positive when gender egalitarianism prevailed. The findings also revealed an inverted U-shaped relationship between gender norms and divorce: an initial increase in divorce was observed when gender norms were predominantly traditional. The association, however, reversed as gender norms became egalitarian. No differences by education were found for divorce. The findings partially support the gender revolution framework but also highlight greater barriers to marriage for low-educated women as societies embrace gender equality.

Bundles of Norms About Teen Sex and Pregnancy.

PubMed

Mollborn, Stefanie; Sennott, Christie

2015-09-01

Teen pregnancy is a cultural battleground in struggles over morality, education, and family. At its heart are norms about teen sex, contraception, pregnancy, and abortion. Analyzing 57 interviews with college students, we found that "bundles" of related norms shaped the messages teens hear. Teens did not think their communities encouraged teen sex or pregnancy, but normative messages differed greatly, with either moral or practical rationalizations. Teens readily identified multiple norms intended to regulate teen sex, contraception, abortion, childbearing, and the sanctioning of teen parents. Beyond influencing teens' behavior, norms shaped teenagers' public portrayals and post hoc justifications of their behavior. Although norm bundles are complex to measure, participants could summarize them succinctly. These bundles and their conflicting behavioral prescriptions create space for human agency in negotiating normative pressures. The norm bundles concept has implications for teen pregnancy prevention policies and can help revitalize social norms for understanding health behaviors. © The Author(s) 2014.

Norm stability at Alcatraz Island: Effects of time and changing conditions

Treesearch

William Valliere; Robert Manning

2010-01-01

Research suggests that visitors often have norms about the resource and social conditions acceptable in a park and that understanding such norms can be useful for park management. Most studies of norms use data from cross-sectional surveys, and little is known about how norms may change over time. To explore this issue, we conducted a study in 2007 to determine whether...

Social Norms in the Development of Adolescent Substance Use: A Longitudinal Analysis of the International Youth Development Study

PubMed Central

Eisenberg, Marla E.; Toumbourou, John W.; Catalano, Richard F.; Hemphill, Sheryl A.

2014-01-01

Identifying specific aspects of peer social norms that influence adolescent substance use may assist international prevention efforts. This study examines two aggregated measures of social norms in the school setting and their predictive association with substance (alcohol, tobacco and marijuana) use 2 years later in a large cross-national population-based cohort of adolescents. The primary hypothesis is that in Grade 7 both “injunctive” school norms (where students associate substance use with “coolness”) and “descriptive” norms (where student substance use is common) will predict Grade 9 substance use. Data come from the International Youth Development Study, including 2,248 students (51.2 % female) in the US and Australia attending 121 schools in Grade 7. Independent variables included injunctive norms (aggregating measures of school-wide coolness ratings of each substance use) and descriptive norms (aggregating the prevalence of school substance use) in Grade 7. Dependent variables included binge drinking and current use of alcohol, tobacco and marijuana in Grade 9. Associations between each type of school-wide social norm and substance use behaviors in Grade 9 were tested using multilevel logistic regression, adjusting for covariates. In unadjusted models, both injunctive and descriptive norms each significantly predicted subsequent substance use. In fully adjusted models, injunctive norms were no longer significantly associated with Grade 9 use, but descriptive norms remained significantly associated with tobacco and marijuana use in the expected direction. The findings identify descriptive social norms in the school context as a particularly important area to address in adolescent substance use prevention efforts. PMID:24633850

Necessary, Yet Dissociable Contributions of the Insular and Ventromedial Prefrontal Cortices to Norm Adaptation: Computational and Lesion Evidence in Humans

PubMed Central

Gu, Xiaosi; Wang, Xingchao; Hula, Andreas; Wang, Shiwei; Xu, Shuai; Lohrenz, Terry M.; Knight, Robert T.; Gao, Zhixian; Dayan, Peter

2015-01-01

Social norms and their enforcement are fundamental to human societies. The ability to detect deviations from norms and to adapt to norms in a changing environment is therefore important to individuals' normal social functioning. Previous neuroimaging studies have highlighted the involvement of the insular and ventromedial prefrontal (vmPFC) cortices in representing norms. However, the necessity and dissociability of their involvement remain unclear. Using model-based computational modeling and neuropsychological lesion approaches, we examined the contributions of the insula and vmPFC to norm adaptation in seven human patients with focal insula lesions and six patients with focal vmPFC lesions, in comparison with forty neurologically intact controls and six brain-damaged controls. There were three computational signals of interest as participants played a fairness game (ultimatum game): sensitivity to the fairness of offers, sensitivity to deviations from expected norms, and the speed at which people adapt to norms. Significant group differences were assessed using bootstrapping methods. Patients with insula lesions displayed abnormally low adaptation speed to norms, yet detected norm violations with greater sensitivity than controls. Patients with vmPFC lesions did not have such abnormalities, but displayed reduced sensitivity to fairness and were more likely to accept the most unfair offers. These findings provide compelling computational and lesion evidence supporting the necessary, yet dissociable roles of the insula and vmPFC in norm adaptation in humans: the insula is critical for learning to adapt when reality deviates from norm expectations, and that the vmPFC is important for valuation of fairness during social exchange. PMID:25589742

Multiscale Modeling of Deformation Twinning Based on Field Theory of Multiscale Plasticity (FTMP)

DTIC Science & Technology

2013-09-01

of the deformation twinning: nucleation, growth (into, e.g., lenticular shapes), lattice rotation (satisfying the mirror symmetry), the attendant...Nucleation and subsequent growth into lenticular shapes is realistically captured. • Stress-strain responses accompanied by serration and overall softening

Recent Enhancements to the Community Multiscale Air Quality Modeling System (CMAQ)

EPA Science Inventory

EPA’s Office of Research and Development, Computational Exposure Division held a webinar on January 31, 2017 to present the recent scientific and computational updates made by EPA to the Community Multi-Scale Air Quality Model (CMAQ). Topics covered included: (1) Improveme...

Multiscale quantification of tissue spiculation and distortion for detection of architectural distortion and spiculated mass in mammography

NASA Astrophysics Data System (ADS)

Lao, Zhiqiang; Zheng, Xin

2011-03-01

This paper proposes a multiscale method to quantify tissue spiculation and distortion in mammography CAD systems that aims at improving the sensitivity in detecting architectural distortion and spiculated mass. This approach addresses the difficulty of predetermining the neighborhood size for feature extraction in characterizing lesions demonstrating spiculated mass/architectural distortion that may appear in different sizes. The quantification is based on the recognition of tissue spiculation and distortion pattern using multiscale first-order phase portrait model in texture orientation field generated by Gabor filter bank. A feature map is generated based on the multiscale quantification for each mammogram and two features are then extracted from the feature map. These two features will be combined with other mass features to provide enhanced discriminate ability in detecting lesions demonstrating spiculated mass and architectural distortion. The efficiency and efficacy of the proposed method are demonstrated with results obtained by applying the method to over 500 cancer cases and over 1000 normal cases.

Time irreversibility of financial time series based on higher moments and multiscale Kullback-Leibler divergence

NASA Astrophysics Data System (ADS)

Li, Jinyang; Shang, Pengjian

2018-07-01

Irreversibility is an important property of time series. In this paper, we propose the higher moments and multiscale Kullback-Leibler divergence to analyze time series irreversibility. The higher moments Kullback-Leibler divergence (HMKLD) can amplify irreversibility and make the irreversibility variation more obvious. Therefore, many time series whose irreversibility is hard to be found are also able to show the variations. We employ simulated data and financial stock data to test and verify this method, and find that HMKLD of stock data is growing in the form of fluctuations. As for multiscale Kullback-Leibler divergence (MKLD), it is very complex in the dynamic system, so that exploring the law of simulation and stock system is difficult. In conventional multiscale entropy method, the coarse-graining process is non-overlapping, however we apply a different coarse-graining process and obtain a surprising discovery. The result shows when the scales are 4 and 5, their entropy is nearly similar, which demonstrates MKLD is efficient to display characteristics of time series irreversibility.

Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

NASA Technical Reports Server (NTRS)

Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.

2015-01-01

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite while the effect on the axial properties is shown to be insignificant.

Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

NASA Technical Reports Server (NTRS)

Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.

2015-01-01

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

Mechanical Properties of Graphene Nanoplatelet Carbon Fiber Epoxy Hybrid Composites: Multiscale Modeling and Experiments

NASA Technical Reports Server (NTRS)

Hadden, Cameron M.; Klimek-McDonald, Danielle R.; Pineda, Evan J.; King, Julie A.; Reichanadter, Alex M.; Miskioglu, Ibrahim; Gowtham, S.; Odegard, Gregory M.

2015-01-01

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

Multiscale multifractal time irreversibility analysis of stock markets

NASA Astrophysics Data System (ADS)

Jiang, Chenguang; Shang, Pengjian; Shi, Wenbin

2016-11-01

Time irreversibility is one of the most important properties of nonstationary time series. Complex time series often demonstrate even multiscale time irreversibility, such that not only the original but also coarse-grained time series are asymmetric over a wide range of scales. We study the multiscale time irreversibility of time series. In this paper, we develop a method called multiscale multifractal time irreversibility analysis (MMRA), which allows us to extend the description of time irreversibility to include the dependence on the segment size and statistical moments. We test the effectiveness of MMRA in detecting multifractality and time irreversibility of time series generated from delayed Henon map and binomial multifractal model. Then we employ our method to the time irreversibility analysis of stock markets in different regions. We find that the emerging market has higher multifractality degree and time irreversibility compared with developed markets. In this sense, the MMRA method may provide new angles in assessing the evolution stage of stock markets.

Image classification using multiscale information fusion based on saliency driven nonlinear diffusion filtering.

PubMed

Hu, Weiming; Hu, Ruiguang; Xie, Nianhua; Ling, Haibin; Maybank, Stephen

2014-04-01

In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the diffusion process converges, and the image at a midscale. Our algorithm emphasizes the foreground features, which are important for image classification. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford 102 flowers dataset; and 3) the Oxford 17 flowers dataset, with high classification rates.

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

Perdikaris, Paris, E-mail: parisp@mit.edu; Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process takingmore » place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.« less

Data fusion of multi-scale representations for structural damage detection

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-01-01

Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

Multiscale analysis of replication technique efficiency for 3D roughness characterization of manufactured surfaces

NASA Astrophysics Data System (ADS)

Jolivet, S.; Mezghani, S.; El Mansori, M.

2016-09-01

The replication of topography has been generally restricted to optimizing material processing technologies in terms of statistical and single-scale features such as roughness. By contrast, manufactured surface topography is highly complex, irregular, and multiscale. In this work, we have demonstrated the use of multiscale analysis on replicates of surface finish to assess the precise control of the finished replica. Five commercial resins used for surface replication were compared. The topography of five standard surfaces representative of common finishing processes were acquired both directly and by a replication technique. Then, they were characterized using the ISO 25178 standard and multiscale decomposition based on a continuous wavelet transform, to compare the roughness transfer quality at different scales. Additionally, atomic force microscope force modulation mode was used in order to compare the resins’ stiffness properties. The results showed that less stiff resins are able to replicate the surface finish along a larger wavelength band. The method was then tested for non-destructive quality control of automotive gear tooth surfaces.

Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

PubMed

Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

2017-04-01

This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

Towards the virtual artery: a multiscale model for vascular physiology at the physics-chemistry-biology interface.

PubMed

Hoekstra, Alfons G; Alowayyed, Saad; Lorenz, Eric; Melnikova, Natalia; Mountrakis, Lampros; van Rooij, Britt; Svitenkov, Andrew; Závodszky, Gábor; Zun, Pavel

2016-11-13

This discussion paper introduces the concept of the Virtual Artery as a multiscale model for arterial physiology and pathologies at the physics-chemistry-biology (PCB) interface. The cellular level is identified as the mesoscopic level, and we argue that by coupling cell-based models with other relevant models on the macro- and microscale, a versatile model of arterial health and disease can be composed. We review the necessary ingredients, both models of arteries at many different scales, as well as generic methods to compose multiscale models. Next, we discuss how this can be combined into the virtual artery. Finally, we argue that the concept of models at the PCB interface could or perhaps should become a powerful paradigm, not only as in our case for studying physiology, but also for many other systems that have such PCB interfaces.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Authors.

Refined composite multivariate generalized multiscale fuzzy entropy: A tool for complexity analysis of multichannel signals

NASA Astrophysics Data System (ADS)

Azami, Hamed; Escudero, Javier

2017-01-01

Multiscale entropy (MSE) is an appealing tool to characterize the complexity of time series over multiple temporal scales. Recent developments in the field have tried to extend the MSE technique in different ways. Building on these trends, we propose the so-called refined composite multivariate multiscale fuzzy entropy (RCmvMFE) whose coarse-graining step uses variance (RCmvMFEσ2) or mean (RCmvMFEμ). We investigate the behavior of these multivariate methods on multichannel white Gaussian and 1/ f noise signals, and two publicly available biomedical recordings. Our simulations demonstrate that RCmvMFEσ2 and RCmvMFEμ lead to more stable results and are less sensitive to the signals' length in comparison with the other existing multivariate multiscale entropy-based methods. The classification results also show that using both the variance and mean in the coarse-graining step offers complexity profiles with complementary information for biomedical signal analysis. We also made freely available all the Matlab codes used in this paper.

High-resolution time-frequency representation of EEG data using multi-scale wavelets

NASA Astrophysics Data System (ADS)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.

Numerical Simulations of a Multiscale Model of Stratified Langmuir Circulation

NASA Astrophysics Data System (ADS)

Malecha, Ziemowit; Chini, Gregory; Julien, Keith

2012-11-01

Langmuir circulation (LC), a prominent form of wind and surface-wave driven shear turbulence in the ocean surface boundary layer (BL), is commonly modeled using the Craik-Leibovich (CL) equations, a phase-averaged variant of the Navier-Stokes (NS) equations. Although surface-wave filtering renders the CL equations more amenable to simulation than are the instantaneous NS equations, simulations in wide domains, hundreds of times the BL depth, currently earn the ``grand challenge'' designation. To facilitate simulations of LC in such spatially-extended domains, we have derived multiscale CL equations by exploiting the scale separation between submesoscale and BL flows in the upper ocean. The numerical algorithm for simulating this multiscale model resembles super-parameterization schemes used in meteorology, but retains a firm mathematical basis. We have validated our algorithm and here use it to perform multiscale simulations of the interaction between LC and upper ocean density stratification. ZMM, GPC, KJ gratefully acknowledge funding from NSF CMG Award 0934827.

Quantifying complexity of financial short-term time series by composite multiscale entropy measure

NASA Astrophysics Data System (ADS)

Niu, Hongli; Wang, Jun

2015-05-01

It is significant to study the complexity of financial time series since the financial market is a complex evolved dynamic system. Multiscale entropy is a prevailing method used to quantify the complexity of a time series. Due to its less reliability of entropy estimation for short-term time series at large time scales, a modification method, the composite multiscale entropy, is applied to the financial market. To qualify its effectiveness, its applications in the synthetic white noise and 1 / f noise with different data lengths are reproduced first in the present paper. Then it is introduced for the first time to make a reliability test with two Chinese stock indices. After conducting on short-time return series, the CMSE method shows the advantages in reducing deviations of entropy estimation and demonstrates more stable and reliable results when compared with the conventional MSE algorithm. Finally, the composite multiscale entropy of six important stock indices from the world financial markets is investigated, and some useful and interesting empirical results are obtained.

Multiscale synchrony behaviors of paired financial time series by 3D multi-continuum percolation

NASA Astrophysics Data System (ADS)

Wang, M.; Wang, J.; Wang, B. T.

2018-02-01

Multiscale synchrony behaviors and nonlinear dynamics of paired financial time series are investigated, in an attempt to study the cross correlation relationships between two stock markets. A random stock price model is developed by a new system called three-dimensional (3D) multi-continuum percolation system, which is utilized to imitate the formation mechanism of price dynamics and explain the nonlinear behaviors found in financial time series. We assume that the price fluctuations are caused by the spread of investment information. The cluster of 3D multi-continuum percolation represents the cluster of investors who share the same investment attitude. In this paper, we focus on the paired return series, the paired volatility series, and the paired intrinsic mode functions which are decomposed by empirical mode decomposition. A new cross recurrence quantification analysis is put forward, combining with multiscale cross-sample entropy, to investigate the multiscale synchrony of these paired series from the proposed model. The corresponding research is also carried out for two China stock markets as comparison.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Multiscale structure of time series revealed by the monotony spectrum.

PubMed

Vamoş, Călin

2017-03-01

Observation of complex systems produces time series with specific dynamics at different time scales. The majority of the existing numerical methods for multiscale analysis first decompose the time series into several simpler components and the multiscale structure is given by the properties of their components. We present a numerical method which describes the multiscale structure of arbitrary time series without decomposing them. It is based on the monotony spectrum defined as the variation of the mean amplitude of the monotonic segments with respect to the mean local time scale during successive averagings of the time series, the local time scales being the durations of the monotonic segments. The maxima of the monotony spectrum indicate the time scales which dominate the variations of the time series. We show that the monotony spectrum can correctly analyze a diversity of artificial time series and can discriminate the existence of deterministic variations at large time scales from the random fluctuations. As an application we analyze the multifractal structure of some hydrological time series.

Multiscale microstructures and improved thermoelectric performance of Mg2(Si0.4Sn0.6)Sbx solid solutions

NASA Astrophysics Data System (ADS)

Zhang, Xin; Liu, Hongliang; Li, Songhao; Zhang, Feipeng; Lu, Qingmei; Li, Jingfeng

2014-03-01

A series of Sb-doped Mg2(Si0.4Sn0.6)Sbx (0 ≤ x ≤ 0.025) solid solutions were prepared by an induction melting, Melt Spinning (MS) and Spark Plasma Sintering (SPS) method, namely the non-equilibrium technique MS-SPS, using bulks of Magnesium, Silicon, Tin, and Antimony as raw materials. The non-equilibrium technique generates the unique multiscale microstructures of samples containing micronscale grains and nanoscale precipitates, the multiscale microstructures remarkably make the lattice thermal conductivities decreased, particularly for samples with the nanoscale precipitates having the size of 10-20 nm. Meanwhile, Sb-doping greatly increased the electrical performance of samples. Consequently, the Sb-doping combined with the multiscale microstructures strategy remarkably improves the overall thermoelectric (TE) performance of Sb doped samples, and a high dimensionless figure of merit (ZT) value of up to 1.25 at 723 K is obtained with Mg2(Si0.4Sn0.6)Sb0.02 sample in a relatively wide temperature range.

Adaptive multiscale processing for contrast enhancement

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Song, Shuwu; Fan, Jian; Huda, Walter; Honeyman, Janice C.; Steinbach, Barbara G.

1993-07-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

Spatial adaptive sampling in multiscale simulation

NASA Astrophysics Data System (ADS)

Rouet-Leduc, Bertrand; Barros, Kipton; Cieren, Emmanuel; Elango, Venmugil; Junghans, Christoph; Lookman, Turab; Mohd-Yusof, Jamaludin; Pavel, Robert S.; Rivera, Axel Y.; Roehm, Dominic; McPherson, Allen L.; Germann, Timothy C.

2014-07-01

In a common approach to multiscale simulation, an incomplete set of macroscale equations must be supplemented with constitutive data provided by fine-scale simulation. Collecting statistics from these fine-scale simulations is typically the overwhelming computational cost. We reduce this cost by interpolating the results of fine-scale simulation over the spatial domain of the macro-solver. Unlike previous adaptive sampling strategies, we do not interpolate on the potentially very high dimensional space of inputs to the fine-scale simulation. Our approach is local in space and time, avoids the need for a central database, and is designed to parallelize well on large computer clusters. To demonstrate our method, we simulate one-dimensional elastodynamic shock propagation using the Heterogeneous Multiscale Method (HMM); we find that spatial adaptive sampling requires only ≈ 50 ×N0.14 fine-scale simulations to reconstruct the stress field at all N grid points. Related multiscale approaches, such as Equation Free methods, may also benefit from spatial adaptive sampling.

From Norm Adoption to Norm Internalization

NASA Astrophysics Data System (ADS)

Conte, Rosaria; Andrighetto, Giulia; Villatoro, Daniel

In this presentation, advances in modeling the mental dynamics of norms will be presented. In particular, the process from norm-adoption, possibly yielding new normative goals, to different forms of norm compliance will be focused upon, including norm internalization, which is at study in social-behavioral sciences and moral philosophy since long. Of late, the debate was revamped within the rationality approach pointing to the role of norm internalization as a less costly and more reliable enforcement system than social control. So far, poor attention was paid to the mental underpinnings of internalization. In this presentation, a rich cognitive model of different types, degrees and factors of internalization is shown. The initial implementation of this model on EMIL-A, a normative agent architecture developed and applied to the.

Two conditions for equivalence of 0-norm solution and 1-norm solution in sparse representation.

PubMed

Li, Yuanqing; Amari, Shun-Ichi

2010-07-01

In sparse representation, two important sparse solutions, the 0-norm and 1-norm solutions, have been receiving much of attention. The 0-norm solution is the sparsest, however it is not easy to obtain. Although the 1-norm solution may not be the sparsest, it can be easily obtained by the linear programming method. In many cases, the 0-norm solution can be obtained through finding the 1-norm solution. Many discussions exist on the equivalence of the two sparse solutions. This paper analyzes two conditions for the equivalence of the two sparse solutions. The first condition is necessary and sufficient, however, difficult to verify. Although the second is necessary but is not sufficient, it is easy to verify. In this paper, we analyze the second condition within the stochastic framework and propose a variant. We then prove that the equivalence of the two sparse solutions holds with high probability under the variant of the second condition. Furthermore, in the limit case where the 0-norm solution is extremely sparse, the second condition is also a sufficient condition with probability 1.

Evaluating metrics of local topographic position for multiscale geomorphometric analysis

NASA Astrophysics Data System (ADS)

Newman, D. R.; Lindsay, J. B.; Cockburn, J. M. H.

2018-07-01

The field of geomorphometry has increasingly moved towards the use of multiscale analytical techniques, due to the availability of fine-resolution digital elevation models (DEMs) and the inherent scale-dependency of many DEM-derived attributes such as local topographic position (LTP). LTP is useful for landform and soils mapping and numerous other environmental applications. Multiple LTP metrics have been proposed and applied in the literature; however, elevation percentile (EP) is notable for its robustness to elevation error and applicability to non-Gaussian local elevation distributions, both of which are common characteristics of DEM data sets. Multiscale LTP analysis involves the estimation of spatial patterns using a range of neighborhood sizes, traditionally achieved by applying spatial filtering techniques with varying kernel sizes. While EP can be demonstrated to provide accurate estimates of LTP, the computationally intensive method of its calculation makes it unsuited to multiscale LTP analysis, particularly at large neighborhood sizes or with fine-resolution DEMs. This research assessed the suitability of three LTP metrics for multiscale terrain characterization by quantifying their computational efficiency and by comparing their ability to approximate EP spatial patterns under varying topographic conditions. The tested LTP metrics included: deviation from mean elevation (DEV), percent elevation range (PER), and the novel relative topographic position (RTP) index. The results demonstrated that DEV, calculated using the integral image technique, offers fast and scale-invariant computation. DEV spatial patterns were strongly correlated with EP (r2 range of 0.699 to 0.967) under all tested topographic conditions. RTP was also a strong predictor of EP (r2 range of 0.594 to 0.917). PER was the weakest predictor of EP (r2 range of 0.031 to 0.801) without offering a substantial improvement in computational efficiency over RTP. PER was therefore determined to be unsuitable for most multiscale applications. It was concluded that the scale-invariant property offered by the integral image used by the DEV method counters the minor losses in robustness compared to EP, making DEV the optimal LTP metric for multiscale applications.

Multi-scale modelling of rubber-like materials and soft tissues: an appraisal

PubMed Central

Puglisi, G.

2016-01-01

We survey, in a partial way, multi-scale approaches for the modelling of rubber-like and soft tissues and compare them with classical macroscopic phenomenological models. Our aim is to show how it is possible to obtain practical mathematical models for the mechanical behaviour of these materials incorporating mesoscopic (network scale) information. Multi-scale approaches are crucial for the theoretical comprehension and prediction of the complex mechanical response of these materials. Moreover, such models are fundamental in the perspective of the design, through manipulation at the micro- and nano-scales, of new polymeric and bioinspired materials with exceptional macroscopic properties. PMID:27118927

A perspective on modeling the multiscale response of energetic materials

NASA Astrophysics Data System (ADS)

Rice, Betsy M.

2017-01-01

The response of an energetic material to insult is perhaps one of the most difficult processes to model due to concurrent chemical and physical phenomena occurring over scales ranging from atomistic to continuum. Unraveling the interdependencies of these complex processes across the scales through modeling can only be done within a multiscale framework. In this paper, I will describe progress in the development of a predictive, experimentally validated multiscale reactive modeling capability for energetic materials at the Army Research Laboratory. I will also describe new challenges and research opportunities that have arisen in the course of our development which should be pursued in the future.

Report of the proceedings of the Colloquium and Workshop on Multiscale Coupled Modeling

NASA Technical Reports Server (NTRS)

Koch, Steven E. (Editor)

1993-01-01

The Colloquium and Workshop on Multiscale Coupled Modeling was held for the purpose of addressing modeling issues of importance to planning for the Cooperative Multiscale Experiment (CME). The colloquium presentations attempted to assess the current ability of numerical models to accurately simulate the development and evolution of mesoscale cloud and precipitation systems and their cycling of water substance, energy, and trace species. The primary purpose of the workshop was to make specific recommendations for the improvement of mesoscale models prior to the CME, their coupling with cloud, cumulus ensemble, hydrology, air chemistry models, and the observational requirements to initialize and verify these models.

The Role of Values, Moral Norms, and Descriptive Norms in Building Occupant Responses to an Energy-Efficiency Pilot Program and to Framing of Related Messages

ERIC Educational Resources Information Center

Arpan, Laura M.; Barooah, Prabir; Subramany, Rahul

2015-01-01

This study examined building occupants' responses associated with an occupant-based energy-efficiency pilot in a university building. The influence of occupants' values and norms as well as effects of two educational message frames (descriptive vs. moral norms cues) on program support were tested. Occupants' personal moral norm to conserve energy…

Clarifying the contribution of subjective norm to predicting leisure-time exercise.

PubMed

Okun, Morris A; Karoly, Paul; Lutz, Rafer

2002-01-01

To clarify the contribution of subjective norm to exercise intention and behavior by considering the influence of descriptive as well as injunctive social norms related to family and friends. A sample of 530 college students completed a questionnaire that assessed descriptive and injunctive social norms related to family and to friends, perceived behavioral control, attitude, intention, and leisure-time exercise. Friend descriptive social norm was a significant predictor of both intention (p<.05) and leisure-time exercise (p<.001). Descriptive norms should be incorporated into tests of the theory of planned behavior in the exercise domain.

Social influence in the theory of planned behaviour: the role of descriptive, injunctive, and in-group norms.

PubMed

White, Katherine M; Smith, Joanne R; Terry, Deborah J; Greenslade, Jaimi H; McKimmie, Blake M

2009-03-01

The present research investigated three approaches to the role of norms in the theory of planned behaviour (TPB). Two studies examined the proposed predictors of intentions to engage in household recycling (Studies 1 and 2) and reported recycling behaviour (Study 1). Study 1 tested the impact of descriptive and injunctive norms (personal and social) and the moderating role of self-monitoring on norm-intention relations. Study 2 examined the role of group norms and group identification and the moderating role of collective self on norm-intention relations. Both studies demonstrated support for the TPB and the inclusion of additional normative variables: attitudes; perceived behavioural control; descriptive; and personal injunctive norms (but not social injunctive norm) emerged as significant independent predictors of intentions. There was no evidence that the impact of norms on intentions varied as a function of the dispositional variables of self-monitoring (Study 1) or the collective self (Study 2). There was support, however, for the social identity approach to attitude-behaviour relations in that group norms predicted recycling intentions, particularly for individuals who identified strongly with the group. The results of these two studies highlight the critical role of social influence processes within the TPB and the attitude-behaviour context.

COMMUNITY MULTISCALE AIR QUALITY ( CMAQ ) MODEL - QUALITY ASSURANCE AND VERSION CONTROL

EPA Science Inventory

This presentation will be given to the EPA Exposure Modeling Workgroup on January 24, 2006. The quality assurance and version control procedures for the Community Multiscale Air Quality (CMAQ) Model are presented. A brief background of CMAQ is given, then issues related to qual...

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model

EPA Science Inventory

Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. In this study, the Community Multiscale Air Quality (CMAQ) model is updated to enhance fine mode SSA emissions,...

Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Evaluation of the Community Multi-scale Air Quality Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL AEROSOL COMPONENT 1: MODEL DESCRIPTION

EPA Science Inventory

The aerosol component of the Community Multiscale Air Quality (CMAQ) model is designed to be an efficient and economical depiction of aerosol dynamics in the atmosphere. The approach taken represents the particle size distribution as the superposition of three lognormal subdis...

Evaluation of the Community Multiscale Air Quality model version 5.1

EPA Science Inventory

The Community Multiscale Air Quality model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Atmospheric Modeling and Analysis Division (AMAD) of the U.S. Environment...

Industrial process system assessment: bridging process engineering and life cycle assessment through multiscale modeling.

EPA Science Inventory

The Industrial Process System Assessment (IPSA) methodology is a multiple step allocation approach for connecting information from the production line level up to the facility level and vice versa using a multiscale model of process systems. The allocation procedure assigns inpu...

Multiscale Path Metrics for the Analysis of Discrete Geometric Structures

DTIC Science & Technology

2017-11-30

Report: Multiscale Path Metrics for the Analysis of Discrete Geometric Structures The views, opinions and/or findings contained in this report are those...Analysis of Discrete Geometric Structures Report Term: 0-Other Email: tomasi@cs.duke.edu Distribution Statement: 1-Approved for public release

Cloud processing of gases and aerosols in the Community Multiscale Air Quality (CMAQ) model: Impacts of extended chemistry

EPA Science Inventory

Clouds and fogs can significantly impact the concentration and distribution of atmospheric gases and aerosols through chemistry, scavenging, and transport. This presentation summarizes the representation of cloud processes in the Community Multiscale Air Quality (CMAQ) modeling ...

Multi-scale habitat selection modeling: A review and outlook

Treesearch

Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

2016-01-01

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

Wavelet-based multiscale performance analysis: An approach to assess and improve hydrological models

NASA Astrophysics Data System (ADS)

Rathinasamy, Maheswaran; Khosa, Rakesh; Adamowski, Jan; ch, Sudheer; Partheepan, G.; Anand, Jatin; Narsimlu, Boini

2014-12-01

The temporal dynamics of hydrological processes are spread across different time scales and, as such, the performance of hydrological models cannot be estimated reliably from global performance measures that assign a single number to the fit of a simulated time series to an observed reference series. Accordingly, it is important to analyze model performance at different time scales. Wavelets have been used extensively in the area of hydrological modeling for multiscale analysis, and have been shown to be very reliable and useful in understanding dynamics across time scales and as these evolve in time. In this paper, a wavelet-based multiscale performance measure for hydrological models is proposed and tested (i.e., Multiscale Nash-Sutcliffe Criteria and Multiscale Normalized Root Mean Square Error). The main advantage of this method is that it provides a quantitative measure of model performance across different time scales. In the proposed approach, model and observed time series are decomposed using the Discrete Wavelet Transform (known as the à trous wavelet transform), and performance measures of the model are obtained at each time scale. The applicability of the proposed method was explored using various case studies-both real as well as synthetic. The synthetic case studies included various kinds of errors (e.g., timing error, under and over prediction of high and low flows) in outputs from a hydrologic model. The real time case studies investigated in this study included simulation results of both the process-based Soil Water Assessment Tool (SWAT) model, as well as statistical models, namely the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods. For the SWAT model, data from Wainganga and Sind Basin (India) were used, while for the Wavelet Volterra, ANN and ARMA models, data from the Cauvery River Basin (India) and Fraser River (Canada) were used. The study also explored the effect of the choice of the wavelets in multiscale model evaluation. It was found that the proposed wavelet-based performance measures, namely the MNSC (Multiscale Nash-Sutcliffe Criteria) and MNRMSE (Multiscale Normalized Root Mean Square Error), are a more reliable measure than traditional performance measures such as the Nash-Sutcliffe Criteria (NSC), Root Mean Square Error (RMSE), and Normalized Root Mean Square Error (NRMSE). Further, the proposed methodology can be used to: i) compare different hydrological models (both physical and statistical models), and ii) help in model calibration.

Misperception of Peer Weight Norms and Its Association with Overweight and Underweight Status among Adolescents

PubMed Central

Perkins, Jessica M.; Perkins, H. W.; Craig, David W.

2014-01-01

Previous research has revealed pervasive misperceptions of peer norms for a variety of behaviors among adolescents such as alcohol use, smoking, and bullying, and that these misperceptions are predictors of personal behavior. Similarly, misperception of peer weight norms may be a pervasive and important risk factor for adolescent weight status. Thus, the comparative association of actual and perceived peer weight norms is examined in relation to personal weight status. Secondary school students in 40 middle and high schools (n=40,328) were surveyed about their perceptions of the peer weight norm for same gender and grade within their school. Perceived norms were compared to aggregate self-reports of weight for these same groups. Overestimation of peer weight norms by more than 5% occurred among 26% of males and 20% of females (by 22 and 16 pounds on average, respectively). Underestimation occurred among 38% of males as well as females (by 16 and 13 pounds on average, respectively). Personal overweight status based on body mass index (BMI) was much more prevalent among respondents who overestimated peer weight norms as was personal underweight status among respondents who underestimated norms. Perception of the peer norm was the strongest predictor of personal BMI among all personal and school variables examined for both male and female students. Thus, reducing misperceived weight norms should be given more attention as a potential avenue for preventing obesity and eating disorders. PMID:24488532

How culture gets embrained: Cultural differences in event-related potentials of social norm violations.

PubMed

Mu, Yan; Kitayama, Shinobu; Han, Shihui; Gelfand, Michele J

2015-12-15

Humans are unique among all species in their ability to develop and enforce social norms, but there is wide variation in the strength of social norms across human societies. Despite this fundamental aspect of human nature, there has been surprisingly little research on how social norm violations are detected at the neurobiological level. Building on the emerging field of cultural neuroscience, we combine noninvasive electroencephalography (EEG) with a new social norm violation paradigm to examine the neural mechanisms underlying the detection of norm violations and how they vary across cultures. EEG recordings from Chinese and US participants (n = 50) showed consistent negative deflection of event-related potential around 400 ms (N400) over the central and parietal regions that served as a culture-general neural marker of detecting norm violations. The N400 at the frontal and temporal regions, however, was only observed among Chinese but not US participants, illustrating culture-specific neural substrates of the detection of norm violations. Further, the frontal N400 predicted a variety of behavioral and attitudinal measurements related to the strength of social norms that have been found at the national and state levels, including higher culture superiority and self-control but lower creativity. There were no cultural differences in the N400 induced by semantic violation, suggesting a unique cultural influence on social norm violation detection. In all, these findings provided the first evidence, to our knowledge, for the neurobiological foundations of social norm violation detection and its variation across cultures.

Cannabis Use Behaviors and Social Anxiety: The Roles of Perceived Descriptive and Injunctive Social Norms

PubMed Central

Ecker, Anthony H.; Buckner, Julia D.

2014-01-01

Objective: Individuals with greater social anxiety are particularly vulnerable to cannabis-related impairment. Descriptive norms (beliefs about others’ use) and injunctive norms (beliefs regarding others’ approval of risky use) may be particularly relevant to cannabis-related behaviors among socially anxious persons if they use cannabis for fear of evaluation for deviating from what they believe to be normative behaviors. Yet, little research has examined the impact of these social norms on the relationships between social anxiety and cannabis use behaviors. Method: The current study investigated whether the relationships of social anxiety to cannabis use and use-related problems varied as a function of social norms. The sample comprised 230 (63.0% female) current cannabis-using undergraduates. Results: Injunctive norms (regarding parents, not friends) moderated the relationship between social anxiety and cannabis-related problem severity. Post hoc probing indicated that among participants with higher (but not lower) social anxiety, those with greater norm endorsement reported the most severe impairment. Injunctive norms (parents) also moderated the relationship between social anxiety and cannabis use frequency such that those with higher social anxiety and lower norm endorsement used cannabis less frequently. Descriptive norms did not moderate the relationship between social anxiety and cannabis use frequency. Conclusions: Socially anxious cannabis users appear to be especially influenced by beliefs regarding parents’ approval of risky cannabis use. Results underscore the importance of considering reference groups and the specific types of norms in understanding factors related to cannabis use behaviors among this vulnerable population. PMID:24411799

Validation of nonlinear gyrokinetic simulations of L- and I-mode plasmas on Alcator C-Mod

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

Creely, A. J.; Howard, N. T.; Rodriguez-Fernandez, P.

New validation of global, nonlinear, ion-scale gyrokinetic simulations (GYRO) is carried out for L- and I-mode plasmas on Alcator C-Mod, utilizing heat fluxes, profile stiffness, and temperature fluctuations. Previous work at C-Mod found that ITG/TEM-scale GYRO simulations can match both electron and ion heat fluxes within error bars in I-mode [White PoP 2015], suggesting that multi-scale (cross-scale coupling) effects [Howard PoP 2016] may be less important in I-mode than in L-mode. New results presented here, however, show that global, nonlinear, ion-scale GYRO simulations are able to match the experimental ion heat flux, but underpredict electron heat flux (at most radii),more » electron temperature fluctuations, and perturbative thermal diffusivity in both L- and I-mode. Linear addition of electron heat flux from electron scale runs does not resolve this discrepancy. These results indicate that single-scale simulations do not sufficiently describe the I-mode core transport, and that multi-scale (coupled electron- and ion-scale) transport models are needed. In conclusion a preliminary investigation with multi-scale TGLF, however, was unable to resolve the discrepancy between ion-scale GYRO and experimental electron heat fluxes and perturbative diffusivity, motivating further work with multi-scale GYRO simulations and a more comprehensive study with multi-scale TGLF.« less

Multiscale equation-free algorithms for molecular dynamics

NASA Astrophysics Data System (ADS)

Abi Mansour, Andrew

Molecular dynamics is a physics-based computational tool that has been widely employed to study the dynamics and structure of macromolecules and their assemblies at the atomic scale. However, the efficiency of molecular dynamics simulation is limited because of the broad spectrum of timescales involved. To overcome this limitation, an equation-free algorithm is presented for simulating these systems using a multiscale model cast in terms of atomistic and coarse-grained variables. Both variables are evolved in time in such a way that the cross-talk between short and long scales is preserved. In this way, the coarse-grained variables guide the evolution of the atom-resolved states, while the latter provide the Newtonian physics for the former. While the atomistic variables are evolved using short molecular dynamics runs, time advancement at the coarse-grained level is achieved with a scheme that uses information from past and future states of the system while accounting for both the stochastic and deterministic features of the coarse-grained dynamics. To complete the multiscale cycle, an atom-resolved state consistent with the updated coarse-grained variables is recovered using algorithms from mathematical optimization. This multiscale paradigm is extended to nanofluidics using concepts from hydrodynamics, and it is demonstrated for macromolecular and nanofluidic systems. A toolkit is developed for prototyping these algorithms, which are then implemented within the GROMACS simulation package and released as an open source multiscale simulator.

Simulated shift work in rats perturbs multiscale regulation of locomotor activity

PubMed Central

Hsieh, Wan-Hsin; Escobar, Carolina; Yugay, Tatiana; Lo, Men-Tzung; Pittman-Polletta, Benjamin; Salgado-Delgado, Roberto; Scheer, Frank A. J. L.; Shea, Steven A.; Buijs, Ruud M.; Hu, Kun

2014-01-01

Motor activity possesses a multiscale regulation that is characterized by fractal activity fluctuations with similar structure across a wide range of timescales spanning minutes to hours. Fractal activity patterns are disturbed in animals after ablating the master circadian pacemaker (suprachiasmatic nucleus, SCN) and in humans with SCN dysfunction as occurs with aging and in dementia, suggesting the crucial role of the circadian system in the multiscale activity regulation. We hypothesized that the normal synchronization between behavioural cycles and the SCN-generated circadian rhythms is required for multiscale activity regulation. To test the hypothesis, we studied activity fluctuations of rats in a simulated shift work protocol that was designed to force animals to be active during the habitual resting phase of the circadian/daily cycle. We found that these animals had gradually decreased mean activity level and reduced 24-h activity rhythm amplitude, indicating disturbed circadian and behavioural cycles. Moreover, these animals had disrupted fractal activity patterns as characterized by more random activity fluctuations at multiple timescales from 4 to 12 h. Intriguingly, these activity disturbances exacerbated when the shift work schedule lasted longer and persisted even in the normal days (without forced activity) following the shift work. The disrupted circadian and fractal patterns resemble those of SCN-lesioned animals and of human patients with dementia, suggesting a detrimental impact of shift work on multiscale activity regulation. PMID:24829282

Multi-Scale Morphological Analysis of Conductance Signals in Vertical Upward Gas-Liquid Two-Phase Flow

NASA Astrophysics Data System (ADS)

Lian, Enyang; Ren, Yingyu; Han, Yunfeng; Liu, Weixin; Jin, Ningde; Zhao, Junying

2016-11-01

The multi-scale analysis is an important method for detecting nonlinear systems. In this study, we carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We first use a recurrence plot to recognise flow patterns in vertical upward gas-liquid two-phase pipe flow from measured signals. Then we apply a multi-scale morphological analysis based on the first-order difference scatter plot to investigate the signals captured from the vertical upward gas-liquid two-phase flow loop test. We find that the invariant scaling exponent extracted from the multi-scale first-order difference scatter plot with the bisector of the second-fourth quadrant as the reference line is sensitive to the inhomogeneous distribution characteristics of the flow structure, and the variation trend of the exponent is helpful to understand the process of breakup and coalescence of the gas phase. In addition, we explore the dynamic mechanism influencing the inhomogeneous distribution of the gas phase in terms of adaptive optimal kernel time-frequency representation. The research indicates that the system energy is a factor influencing the distribution of the gas phase and the multi-scale morphological analysis based on the first-order difference scatter plot is an effective method for indicating the inhomogeneous distribution of the gas phase in gas-liquid two-phase flow.

A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

NASA Astrophysics Data System (ADS)

Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

Can fractal objects operate as efficient inline mixers?

NASA Astrophysics Data System (ADS)

Laizet, Sylvain; Vassilicos, John; Turbulence, Mixing; Flow Control Group Team

2011-11-01

Recently, Hurst & Vassilicos, PoF 2007, Seoud & Vassilicos, PoF 2007, Mazellier & Vassilicos, PoF, 2010 used different multiscale grids to generate turbulence in a wind tunnel and have shown that complex multiscale boundary/initial conditions can drastically influence the behaviour of a turbulent flow, but that the detailled specific nature of the multiscale geometry matters too. Multiscale (fractal) objects can be designed to be immersed in any fluid flow where there is a need to control and design the turbulence generated by the object. Different types of multiscale objects can be designed as different types of energy-efficient mixers with varying degrees of high turbulent intensities, small pressure drop and downstream distance from the grid where the turbulence is most vigorous. Here, we present a 3D DNS study of the stirring and mixing of a passive scalar by turbulence generated with either a fractal square grid or a regular grid in the presence of a mean scalar gradient. The results show that: (1) there is a linear increase for the passive scalar variance for both grids, (2) the passive scalar variance is ten times bigger for the fractal grid, (3) the passive scalar flux is constant after the production region for both grids, (4) the passive scalar flux is enhanced by an order of magnitude for the fractal grid. We acknowledge support from EPSRC, UK.

Validation of nonlinear gyrokinetic simulations of L- and I-mode plasmas on Alcator C-Mod

DOE PAGES

Creely, A. J.; Howard, N. T.; Rodriguez-Fernandez, P.; ...

2017-03-02

New validation of global, nonlinear, ion-scale gyrokinetic simulations (GYRO) is carried out for L- and I-mode plasmas on Alcator C-Mod, utilizing heat fluxes, profile stiffness, and temperature fluctuations. Previous work at C-Mod found that ITG/TEM-scale GYRO simulations can match both electron and ion heat fluxes within error bars in I-mode [White PoP 2015], suggesting that multi-scale (cross-scale coupling) effects [Howard PoP 2016] may be less important in I-mode than in L-mode. New results presented here, however, show that global, nonlinear, ion-scale GYRO simulations are able to match the experimental ion heat flux, but underpredict electron heat flux (at most radii),more » electron temperature fluctuations, and perturbative thermal diffusivity in both L- and I-mode. Linear addition of electron heat flux from electron scale runs does not resolve this discrepancy. These results indicate that single-scale simulations do not sufficiently describe the I-mode core transport, and that multi-scale (coupled electron- and ion-scale) transport models are needed. In conclusion a preliminary investigation with multi-scale TGLF, however, was unable to resolve the discrepancy between ion-scale GYRO and experimental electron heat fluxes and perturbative diffusivity, motivating further work with multi-scale GYRO simulations and a more comprehensive study with multi-scale TGLF.« less

Multiscale analysis of structure development in expanded starch snacks

NASA Astrophysics Data System (ADS)

van der Sman, R. G. M.; Broeze, J.

2014-11-01

In this paper we perform a multiscale analysis of the food structuring process of the expansion of starchy snack foods like keropok, which obtains a solid foam structure. In particular, we want to investigate the validity of the hypothesis of Kokini and coworkers, that expansion is optimal at the moisture content, where the glass transition and the boiling line intersect. In our analysis we make use of several tools, (1) time scale analysis from the field of physical transport phenomena, (2) the scale separation map (SSM) developed within a multiscale simulation framework of complex automata, (3) the supplemented state diagram (SSD), depicting phase transition and glass transition lines, and (4) a multiscale simulation model for the bubble expansion. Results of the time scale analysis are plotted in the SSD, and give insight into the dominant physical processes involved in expansion. Furthermore, the results of the time scale analysis are used to construct the SSM, which has aided us in the construction of the multiscale simulation model. Simulation results are plotted in the SSD. This clearly shows that the hypothesis of Kokini is qualitatively true, but has to be refined. Our results show that bubble expansion is optimal for moisture content, where the boiling line for gas pressure of 4 bars intersects the isoviscosity line of the critical viscosity 106 Pa.s, which runs parallel to the glass transition line.

Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart

PubMed Central

Amr, Ali; Neumann, Dominik; Georgescu, Bogdan; Seegerer, Philipp; Kamen, Ali; Haas, Jan; Frese, Karen S.; Irawati, Maria; Wirsz, Emil; King, Vanessa; Buss, Sebastian; Mereles, Derliz; Zitron, Edgar; Keller, Andreas; Katus, Hugo A.; Comaniciu, Dorin; Meder, Benjamin

2015-01-01

Background Despite modern pharmacotherapy and advanced implantable cardiac devices, overall prognosis and quality of life of HF patients remain poor. This is in part due to insufficient patient stratification and lack of individualized therapy planning, resulting in less effective treatments and a significant number of non-responders. Methods and Results State-of-the-art clinical phenotyping was acquired, including magnetic resonance imaging (MRI) and biomarker assessment. An individualized, multi-scale model of heart function covering cardiac anatomy, electrophysiology, biomechanics and hemodynamics was estimated using a robust framework. The model was computed on n=46 HF patients, showing for the first time that advanced multi-scale models can be fitted consistently on large cohorts. Novel multi-scale parameters derived from the model of all cases were analyzed and compared against clinical parameters, cardiac imaging, lab tests and survival scores to evaluate the explicative power of the model and its potential for better patient stratification. Model validation was pursued by comparing clinical parameters that were not used in the fitting process against model parameters. Conclusion This paper illustrates how advanced multi-scale models can complement cardiovascular imaging and how they could be applied in patient care. Based on obtained results, it becomes conceivable that, after thorough validation, such heart failure models could be applied for patient management and therapy planning in the future, as we illustrate in one patient of our cohort who received CRT-D implantation. PMID:26230546

3D deblending of simultaneous source data based on 3D multi-scale shaping operator

NASA Astrophysics Data System (ADS)

Zu, Shaohuan; Zhou, Hui; Mao, Weijian; Gong, Fei; Huang, Weilin

2018-04-01

We propose an iterative three-dimensional (3D) deblending scheme using 3D multi-scale shaping operator to separate 3D simultaneous source data. The proposed scheme is based on the property that signal is coherent, whereas interference is incoherent in some domains, e.g., common receiver domain and common midpoint domain. In two-dimensional (2D) blended record, the coherency difference of signal and interference is in only one spatial direction. Compared with 2D deblending, the 3D deblending can take more sparse constraints into consideration to obtain better performance, e.g., in 3D common receiver gather, the coherency difference is in two spatial directions. Furthermore, with different levels of coherency, signal and interference distribute in different scale curvelet domains. In both 2D and 3D blended records, most coherent signal locates in coarse scale curvelet domain, while most incoherent interference distributes in fine scale curvelet domain. The scale difference is larger in 3D deblending, thus, we apply the multi-scale shaping scheme to further improve the 3D deblending performance. We evaluate the performance of 3D and 2D deblending with the multi-scale and global shaping operators, respectively. One synthetic and one field data examples demonstrate the advantage of the 3D deblending with 3D multi-scale shaping operator.

Jimmy's baby doll and Jenny's truck: young children's reasoning about gender norms.

PubMed

Conry-Murray, Clare; Turiel, Elliot

2012-01-01

To assess the flexibility of reasoning about gender, children ages 4, 6, and 8 years (N = 72) were interviewed about gender norms when different domains were highlighted. The majority of participants at all ages judged a reversal of gender norms in a different cultural context to be acceptable. They also judged gender norms as a matter of personal choice and they negatively evaluated a rule enforcing gender norms in schools. Older children were more likely to show flexibility than younger children. Justifications obtained from 6- and 8-year-olds showed that they considered adherence to gender norms a matter of personal choice and they viewed the rule enforcing gender norms as unfair. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.

Correlation between the norm and the geometry of minimal networks

NASA Astrophysics Data System (ADS)

Laut, I. L.

2017-05-01

The paper is concerned with the inverse problem of the minimal Steiner network problem in a normed linear space. Namely, given a normed space in which all minimal networks are known for any finite point set, the problem is to describe all the norms on this space for which the minimal networks are the same as for the original norm. We survey the available results and prove that in the plane a rotund differentiable norm determines a distinctive set of minimal Steiner networks. In a two-dimensional space with rotund differentiable norm the coordinates of interior vertices of a nondegenerate minimal parametric network are shown to vary continuously under small deformations of the boundary set, and the turn direction of the network is determined. Bibliography: 15 titles.

An algorithm for solving the system-level problem in multilevel optimization

NASA Technical Reports Server (NTRS)

Balling, R. J.; Sobieszczanski-Sobieski, J.

1994-01-01

A multilevel optimization approach which is applicable to nonhierarchic coupled systems is presented. The approach includes a general treatment of design (or behavior) constraints and coupling constraints at the discipline level through the use of norms. Three different types of norms are examined: the max norm, the Kreisselmeier-Steinhauser (KS) norm, and the 1(sub p) norm. The max norm is recommended. The approach is demonstrated on a class of hub frame structures which simulate multidisciplinary systems. The max norm is shown to produce system-level constraint functions which are non-smooth. A cutting-plane algorithm is presented which adequately deals with the resulting corners in the constraint functions. The algorithm is tested on hub frames with increasing number of members (which simulate disciplines), and the results are summarized.

How do social norms influence prosocial development?

PubMed

House, Bailey R

2018-04-01

Humans are both highly prosocial and extremely sensitive to social norms, and some theories suggest that norms are necessary to account for uniquely human forms of prosocial behavior and cooperation. Understanding how norms influence prosocial behavior is thus essential if we are to describe the psychology and development of prosocial behavior. In this article I review recent research from across the social sciences that provides (1) a theoretical model of how norms influence prosocial behavior, (2) empirical support for the model based on studies with adults and children, and (3) predictions about the psychological mechanisms through which norms shape prosocial behavior. I conclude by discussing the need for future studies into how prosocial behavior develops through emerging interactions between culturally varying norms, social cognition, emotions, and potentially genes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spanish semantic feature production norms for 400 concrete concepts.

PubMed

Vivas, Jorge; Vivas, Leticia; Comesaña, Ana; Coni, Ana García; Vorano, Agostina

2017-06-01

Semantic feature production norms provide many quantitative measures of different feature and concept variables that are necessary to solve some debates surrounding the nature of the organization, both normal and pathological, of semantic memory. Despite the current existence of norms for different languages, there are still no published norms in Spanish. This article presents a new set of norms collected from 810 participants for 400 living and nonliving concepts among Spanish speakers. These norms consist of empirical collections of features that participants used to describe the concepts. Four files were elaborated: a concept-feature file, a concept-concept matrix, a feature-feature matrix, and a significantly correlated features file. We expect that these norms will be useful for researchers in the fields of experimental psychology, neuropsychology, and psycholinguistics.

Necessary, yet dissociable contributions of the insular and ventromedial prefrontal cortices to norm adaptation: computational and lesion evidence in humans.

PubMed

Gu, Xiaosi; Wang, Xingchao; Hula, Andreas; Wang, Shiwei; Xu, Shuai; Lohrenz, Terry M; Knight, Robert T; Gao, Zhixian; Dayan, Peter; Montague, P Read

2015-01-14

Social norms and their enforcement are fundamental to human societies. The ability to detect deviations from norms and to adapt to norms in a changing environment is therefore important to individuals' normal social functioning. Previous neuroimaging studies have highlighted the involvement of the insular and ventromedial prefrontal (vmPFC) cortices in representing norms. However, the necessity and dissociability of their involvement remain unclear. Using model-based computational modeling and neuropsychological lesion approaches, we examined the contributions of the insula and vmPFC to norm adaptation in seven human patients with focal insula lesions and six patients with focal vmPFC lesions, in comparison with forty neurologically intact controls and six brain-damaged controls. There were three computational signals of interest as participants played a fairness game (ultimatum game): sensitivity to the fairness of offers, sensitivity to deviations from expected norms, and the speed at which people adapt to norms. Significant group differences were assessed using bootstrapping methods. Patients with insula lesions displayed abnormally low adaptation speed to norms, yet detected norm violations with greater sensitivity than controls. Patients with vmPFC lesions did not have such abnormalities, but displayed reduced sensitivity to fairness and were more likely to accept the most unfair offers. These findings provide compelling computational and lesion evidence supporting the necessary, yet dissociable roles of the insula and vmPFC in norm adaptation in humans: the insula is critical for learning to adapt when reality deviates from norm expectations, and that the vmPFC is important for valuation of fairness during social exchange. Copyright © 2015 Gu et al.

European Top Managers' Age-Related Workplace Norms and Their Organizations' Recruitment and Retention Practices Regarding Older Workers.

PubMed

Oude Mulders, Jaap; Henkens, Kène; Schippers, Joop

2017-10-01

Top managers guide organizational strategy and practices, but their role in the employment of older workers is understudied. We study the effects that age-related workplace norms of top managers have on organizations' recruitment and retention practices regarding older workers. We investigate two types of age-related workplace norms, namely age equality norms (whether younger and older workers should be treated equally) and retirement age norms (when older workers are expected to retire) while controlling for organizational and national contexts. Data collected among top managers of 1,088 organizations from six European countries were used for the study. Logistic regression models were run to estimate the effects of age-related workplace norms on four different organizational outcomes: (a) recruiting older workers, (b) encouraging working until normal retirement age, (c) encouraging working beyond normal retirement age, and (d) rehiring retired former employees. Age-related workplace norms of top managers affect their organizations' practices, but in different ways. Age equality norms positively affect practices before the boundary of normal retirement age (Outcomes a and b), whereas retirement age norms positively affect practices after the boundary of normal retirement age (Outcomes c and d). Changing age-related workplace norms of important actors in organizations may be conducive to better employment opportunities and a higher level of employment participation of older workers. However, care should be taken to target the right types of norms, since targeting different norms may yield different outcomes. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Descriptive drinking norms in Native American and non-Hispanic White college students.

PubMed

Hagler, Kylee J; Pearson, Matthew R; Venner, Kamilla L; Greenfield, Brenna L

2017-09-01

College students tend to overestimate how much their peers drink, which is associated with higher personal alcohol use. However, research has not yet examined if this phenomenon holds true among Native American (NA) college students. This study examined associations between descriptive norms and alcohol use/consequences in a sample of NA and non-Hispanic White (NHW) college students. NA (n=147, 78.6% female) and NHW (n=246, 67.8% female) undergraduates completed an online survey. NAs NHWs showed similar descriptive norms such that the "typical college student," "typical NA student," and "typical NHW student" were perceived to drink more than "best friends." "Best friends" descriptive norms (i.e., estimations of how many drinks per week were consumed by participants' best friends) were the most robust predictors of alcohol use/consequences. Effect size estimates of the associations between drinking norms and participants' alcohol use were consistently positive and ranged from r=0.25 to r=0.51 across the four reference groups. Negative binomial hurdle models revealed that all descriptive norms tended to predict drinking, and "best friends" drinking norms predicted alcohol consequences. Apart from one interaction effect, likely due to familywise error rate, these associations were not qualified by interactions with racial/ethnic group. We found similar patterns between NAs and NHWs both in the pattern of descriptive norms across reference groups and in the strength of associations between descriptive norms and alcohol use/consequences. Although these results suggest that descriptive norms operate similarly among NAs as other college students, additional research is needed to identify whether other norms (e.g., injunctive norms) operate similarly across NA and NHW students. Copyright © 2017. Published by Elsevier Ltd.

Linearized Alternating Direction Method of Multipliers for Constrained Nonconvex Regularized Optimization

DTIC Science & Technology

2016-11-22

structure of the graph, we replace the ℓ1- norm by the nonconvex Capped -ℓ1 norm , and obtain the Generalized Capped -ℓ1 regularized logistic regression...X. M. Yuan. Linearized augmented lagrangian and alternating direction methods for nuclear norm minimization. Mathematics of Computation, 82(281):301...better approximations of ℓ0- norm theoretically and computationally beyond ℓ1- norm , for example, the compressive sensing (Xiao et al., 2011). The

A Meta-Analysis of the Relations Between Three Types of Peer Norms and Adolescent Sexual Behavior.

PubMed

van de Bongardt, Daphne; Reitz, Ellen; Sandfort, Theo; Deković, Maja

2015-08-01

The aim of the present meta-analysis was to investigate the associations between three types of peer norms-descriptive norms (peer sexual behaviors), injunctive norms (peer sexual attitudes), and peer pressure to have sex-and two adolescent sexual behavior outcomes (sexual activity and sexual risk behavior). Adolescent sexual activity was more strongly associated with descriptive norms (ESrfixed=.40) than with injunctive norms (ESrfixed=.22) or peer pressure (ESrfixed=.10). Compared with the sexual activity outcome, the effect size for descriptive norms (peer sexual risk behavior) for sexual risk behavior was smaller (ESrfixed=.11). Age, gender, peer type, and socio-cultural context significantly moderated these associations. Additional analyses of longitudinal studies suggested that selection effects were stronger than socialization effects. These findings offer empirical support for the conceptual distinction between three types of peer norms and hold important implications for theory, research, and intervention strategies. © 2014 by the Society for Personality and Social Psychology, Inc.

The normative environment for substance use among American Indian students and white students attending schools on or near reservations.

PubMed

Swaim, Randall C; Stanley, Linda R; Beauvais, Fred

2013-01-01

American Indian and White students who attended the same schools located on or near reservations were surveyed to determine the comparative normative environment for substance use. Descriptive norms increased and student injunctive norms decreased across grade in school. Female students reported higher levels of descriptive norms compared to male students. For marijuana use, a substantial decrease in student injunctive norms occurred between grades 8 and 10. Adult injunctive norms were perceived by female students to be higher than those perceived by male students, particularly among American Indian females. Somewhat surprisingly, 8th grade White female students reported high descriptive norms for inhalant use compared to 8th grade American Indian students. Overall, however, higher descriptive norms and lower injunctive norms among American Indian youth suggested that their risk for substance use is higher compared to White students because of the normative environment created by peers, family, and other adults. © 2013 American Orthopsychiatric Association.

Social influence in child care centers: a test of the theory of normative social behavior.

PubMed

Lapinski, Maria Knight; Anderson, Jenn; Shugart, Alicia; Todd, Ewen

2014-01-01

Child care centers are a unique context for studying communication about the social and personal expectations about health behaviors. The theory of normative social behavior (TNSB; Rimal & Real, 2005 ) provides a framework for testing the role of social and psychological influences on handwashing behaviors among child care workers. A cross-sectional survey of child care workers in 21 centers indicates that outcome expectations and group identity increase the strength of the relationship between descriptive norms and handwashing behavior. Injunctive norms also moderate the effect of descriptive norms on handwashing behavior such that when strong injunctive norms are reported, descriptive norms are positively related to handwashing, but when weak injunctive norms are reported, descriptive norms are negatively related to handwashing. The findings suggest that communication interventions in child care centers can focus on strengthening injunctive norms in order to increase handwashing behaviors in child care centers. The findings also suggest that the theory of normative social behavior can be useful in organizational contexts.

Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Overview and Evaluation of the Community Multiscale Air Quality Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

SHORT RANGE ENSEMBLE Products

Science.gov Websites

- CONUS Double Resolution (Lambert Conformal - 40km) NEMS Non-hydrostatic Multiscale Model on the B grid AWIPS grid 212 Regional - CONUS Double Resolution (Lambert Conformal - 40km) NEMS Non-hydrostatic 132 - Double Resolution (Lambert Conformal - 16km) NEMS Non-hydrostatic Multiscale Model on the B grid

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was ...

Multiscale characterization and mechanical modeling of an Al-Zn-Mg electron beam weld

NASA Astrophysics Data System (ADS)

Puydt, Quentin; Flouriot, Sylvain; Ringeval, Sylvain; Parry, Guillaume; De Geuser, Frédéric; Deschamps, Alexis

Welding of precipitation hardening alloys results in multi-scale microstructural heterogeneities, from the hardening nano-scale precipitates to the micron-scale solidification structures and to the component geometry. This heterogeneity results in a complex mechanical response, with gradients in strength, stress triaxiality and damage initiation sites.

Riparian ecosystems and buffers - multiscale structure, function, and management: introduction

Treesearch

Kathleen A. Dwire; Richard R. Lowrance

2006-01-01

Given the importance of issues related to improved understanding and management of riparian ecosystems and buffers, the American Water Resources Association (AWRA) sponsored a Summer Specialty Conference in June 2004 at Olympic Valley, California, entitled 'Riparian Ecosystems and Buffers: Multiscale Structure, Function, and Management.' The primary objective...

Incremental Testing of the Community Multiscale Air Quality (CMAQ) Modeling System Version 4.7

EPA Science Inventory

This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to obse...

Extending the Applicability of the Community Multiscale Air Quality Model to Hemispheric Scales: Motivation, Challenges, and Progress

EPA Science Inventory

The adaptation of the Community Multiscale Air Quality (CMAQ) modeling system to simulate O₃, particulate matter, and related precursor distributions over the northern hemisphere is presented. Hemispheric simulations with CMAQ and the Weather Research and Forecasting (...

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modeled processes were examined and enhanced to suitably represent the extended space and timesca...

Predicting Australian adults' sun-safe behaviour: examining the role of personal and social norms.

PubMed

White, Katherine M; Starfelt, Louise C; Young, Ross McD; Hawkes, Anna L; Leske, Stuart; Hamilton, Kyra

2015-05-01

To address the scarcity of comprehensive, theory-based research in the Australian context, this study, using a theory of planned behaviour (TPB) framework, investigated the role of personal and social norms to identify the key predictors of adult Australians' sun-safe intentions and behaviour. The study used a prospective design with two waves of data collection, 1 week apart. Participants were 816 adults (48.2% men) aged between 18 and 88 years recruited from urban, regional, and rural areas of Australia. At baseline, participants completed a questionnaire assessing the standard TPB predictors (attitude, subjective norm, and perceived behavioural control [PBC]), past behaviour, behavioural intention, and additional measures of group norm for the referent groups of friends and family, image norm, personal norm, personal choice/responsibility, and Australian identity. Seventy-one per cent of the participants (n = 577) reported on their sun-safe behaviour in the subsequent week. Via path modelling, past behaviour, attitude, group norm (friends), personal norm, and personal choice/responsibility emerged as independent predictors of intentions which, in turn, predicted sun-safe behaviour prospectively. Past behaviour, but not PBC, had direct effects on sun-safe behaviour. The model explained 61.6% and 43.9% of the variance in intention and behaviour, respectively. This study provides support for the use of a comprehensive theoretical decision-making model to explain Australian adults' sun-safe intentions and behaviours and identifies viable targets for health-promoting messages in this high-risk context. Statement of contribution What is already known on this subject? Identifying determinants of sun-safe behaviour is vital in high-risk cancer areas like Australia. For young Australians, friendship group norm is a key influence of intentions and behaviour. Little is known about drivers of sun safety, especially norms, among Australian adults in general. What does this study add? This study drew on qualitative data and reconceptualized norms for Australians' sun-safe decisions. Friendship group norm and personal norm, not family group norm, influence sun-safe intentions. Perceived responsibility and choice to be sun safe also impact on people's intentions. © 2014 The British Psychological Society.

Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

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

Stander, Nielen; Basudhar, Anirban; Basu, Ushnish

2015-09-14

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project tomore » develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.« less

Social Norms: Do We Love Norms Too Much?

PubMed

Bell, David C; Cox, Mary L

2015-03-01

Social norms are often cited as the cause of many social phenomena, especially as an explanation for prosocial family and relationship behaviors. And yet maybe we love the idea of social norms too much, as suggested by our failure to subject them to rigorous test. Compared to the detail in social norms theoretical orientations, there is very little detail in tests of normative theories. To provide guidance to researchers who invoke social norms as explanations, we catalog normative orientations that have been proposed to account for consistent patterns of action. We call on researchers to conduct tests of normative theories and the processes such theories assert.

Social Norms: Do We Love Norms Too Much?

PubMed Central

Bell, David C.; Cox, Mary L.

2014-01-01

Social norms are often cited as the cause of many social phenomena, especially as an explanation for prosocial family and relationship behaviors. And yet maybe we love the idea of social norms too much, as suggested by our failure to subject them to rigorous test. Compared to the detail in social norms theoretical orientations, there is very little detail in tests of normative theories. To provide guidance to researchers who invoke social norms as explanations, we catalog normative orientations that have been proposed to account for consistent patterns of action. We call on researchers to conduct tests of normative theories and the processes such theories assert. PMID:25937833

The Centre for Speech, Language and the Brain (CSLB) concept property norms.

PubMed

Devereux, Barry J; Tyler, Lorraine K; Geertzen, Jeroen; Randall, Billi

2014-12-01

Theories of the representation and processing of concepts have been greatly enhanced by models based on information available in semantic property norms. This information relates both to the identity of the features produced in the norms and to their statistical properties. In this article, we introduce a new and large set of property norms that are designed to be a more flexible tool to meet the demands of many different disciplines interested in conceptual knowledge representation, from cognitive psychology to computational linguistics. As well as providing all features listed by 2 or more participants, we also show the considerable linguistic variation that underlies each normalized feature label and the number of participants who generated each variant. Our norms are highly comparable with the largest extant set (McRae, Cree, Seidenberg, & McNorgan, 2005) in terms of the number and distribution of features. In addition, we show how the norms give rise to a coherent category structure. We provide these norms in the hope that the greater detail available in the Centre for Speech, Language and the Brain norms should further promote the development of models of conceptual knowledge. The norms can be downloaded at www.csl.psychol.cam.ac.uk/propertynorms.

The malleability of injunctive norms among college students.

PubMed

Prince, Mark A; Carey, Kate B

2010-11-01

Alcohol use among college students has been associated with injunctive norms, which refer to the perceived acceptability of excessive drinking, and descriptive norms, which refer to perceptions of actual drinking. The purpose of this study was to examine the effect of a brief injunctive norms manipulation on both injunctive and descriptive norms about drinking alcohol and to explore differences in the malleability of norms across referent groups, sex, and gender role. Participants were 265 undergraduates (43% male, 70% freshmen) who completed a web-based survey for course credit. A randomly selected half was exposed to a page of information-based feedback about typical student injunctive norms. Relative to the control condition, the manipulation produced lower injunctive and descriptive norms related to typical students' drinking but no change in either type of norm related to close friends. Femininity was associated with less permissive normative beliefs about the acceptability of excessive drinking whereas masculinity was associated with elevated perceptions of peer drinking, but neither sex nor gender role moderated the manipulation effect. We conclude that perceptions of peer approval of drinking are malleable with a very brief information-based manipulation. Copyright 2010 Elsevier Ltd. All rights reserved.

Minority acculturation and peer rejection: Costs of acculturation misfit with peer-group norms.

PubMed

Celeste, Laura; Meeussen, Loes; Verschueren, Karine; Phalet, Karen

2016-09-01

How do minority adolescents' personal acculturation preferences and peer norms of acculturation affect their social inclusion in school? Turkish and Moroccan minority adolescents (N = 681) reported their preferences for heritage culture maintenance, mainstream culture adoption, and their experiences of peer rejection as a key indicator of adjustment problems. Additionally, we aggregated peer acculturation norms of maintenance and adoption within ethnically diverse classrooms (N = 230 in 50 Belgian schools), distinguishing between co-ethnic (Turkish or Moroccan classmates only, N = 681) and cross-ethnic norms (also including N = 1,930 other classmates). Cross-ethnic peer-group norms (of adoption and maintenance) and co-ethnic norms (of maintenance, marginally) predicted minority experiences of peer rejection (controlling for ethnic composition). Moreover, misfit of minorities' own acculturation preferences with both cross-ethnic and co-ethnic peer-group norms was harmful. When cross-ethnic norms stressed adoption, 'integrationist' minority youth - who combined culture adoption with maintenance - experienced most peer rejection. Yet, when co-ethnic peers stressed maintenance, 'assimilationist' minority youth experienced most rejection. In conclusion, acculturation misfit with peer-group norms is a risk factor for minority inclusion in ethnically diverse environments. © 2016 The British Psychological Society.

Four year-olds use norm-based coding for face identity.

PubMed

Jeffery, Linda; Read, Ainsley; Rhodes, Gillian

2013-05-01

Norm-based coding, in which faces are coded as deviations from an average face, is an efficient way of coding visual patterns that share a common structure and must be distinguished by subtle variations that define individuals. Adults and school-aged children use norm-based coding for face identity but it is not yet known if pre-school aged children also use norm-based coding. We reasoned that the transition to school could be critical in developing a norm-based system because school places new demands on children's face identification skills and substantially increases experience with faces. Consistent with this view, face identification performance improves steeply between ages 4 and 7. We used face identity aftereffects to test whether norm-based coding emerges between these ages. We found that 4 year-old children, like adults, showed larger face identity aftereffects for adaptors far from the average than for adaptors closer to the average, consistent with use of norm-based coding. We conclude that experience prior to age 4 is sufficient to develop a norm-based face-space and that failure to use norm-based coding cannot explain 4 year-old children's poor face identification skills. Copyright © 2013 Elsevier B.V. All rights reserved.

Discourses with potential to disrupt traditional nursing education: Nursing teachers' talk about norm-critical competence.

PubMed

Tengelin, Ellinor; Dahlborg-Lyckhage, Elisabeth

2017-01-01

This paper describes the discourses underlying nursing teachers' talk about their own norm-critical competence. Norm criticism is an approach that promotes awareness and criticism of the norms and power structures that exert an excluding effect in society in general and in the healthcare encounter in particular. Given the unequal relationships that can exist in healthcare, for example relationships shaped by racism, sexism and classism, a norm-critical approach to nursing education would help illuminate these matters. The studied empirical material consisted of focus group interviews. Nursing teachers discussed their norm-critical competence based on the university course "Norm-Aware Caring" in which they had recently participated. Through a critical discourse analysis, three discourses were identified in their talk, all of which had the potential to disrupt traditional, normative nursing education. However, in all three discourses there was an underlying discourse of normality, clearly positioning the teachers as exemplifying the "normal." The binary constructed between normality and otherness contradicts a basic tenet of the norm-critical approach and may hamper the development of genuine norm-critical competence in nursing education. © 2016 John Wiley & Sons Ltd.

Norm compliance and self-reported health among Swedish adolescents.

PubMed

Nygren, Karina; Janlert, Urban; Nygren, Lennart

2011-02-01

This study examines the relationship between norm compliance and self-reported health in adolescents, and how this differs between genders. Our specific aim was to investigate if extremely high norm compliance revealed any particular health patterns. This empirical study used a web-based survey from 2005, which was distributed to all students (n = 5,066) in years 7-9 of compulsory school within six municipalities in northern Sweden. The respondents answered questions about their general health as well as specific health problems such as headaches, stomach ache, sleeping difficulties and stress. Compliance was measured according to different norm-related behaviour, such as truancy, crime and use of tobacco, alcohol and narcotics. The majority of respondents reported good health and norm-compliant behaviour. Girls reported more health problems than boys, a difference that increased with age. Those who were more norm compliant reported better health, fewer somatic complaints and less stress, which goes against our initial hypothesis that extremely high norm compliance and self-reported ill-health are related. There seemed to be a stronger relationship between self-reported health and norm compliance for girls than boys, in absolute terms. The results clearly show a relationship between norm compliance and health, and suggest inequalities between genders.

Human substantia nigra and ventral tegmental area involvement in computing social error signals during the ultimatum game

PubMed Central

Hétu, Sébastien; Luo, Yi; D’Ardenne, Kimberlee; Lohrenz, Terry

2017-01-01

Abstract As models of shared expectations, social norms play an essential role in our societies. Since our social environment is changing constantly, our internal models of it also need to change. In humans, there is mounting evidence that neural structures such as the insula and the ventral striatum are involved in detecting norm violation and updating internal models. However, because of methodological challenges, little is known about the possible involvement of midbrain structures in detecting norm violation and updating internal models of our norms. Here, we used high-resolution cardiac-gated functional magnetic resonance imaging and a norm adaptation paradigm in healthy adults to investigate the role of the substantia nigra/ventral tegmental area (SN/VTA) complex in tracking signals related to norm violation that can be used to update internal norms. We show that the SN/VTA codes for the norm’s variance prediction error (PE) and norm PE with spatially distinct regions coding for negative and positive norm PE. These results point to a common role played by the SN/VTA complex in supporting both simple reward-based and social decision making. PMID:28981876

Being modest makes you feel bad: effects of the modesty norm and mortality salience on self-esteem in a collectivistic culture.

PubMed

Du, Hongfei; Jonas, Eva

2015-02-01

Terror management research shows that existential terror motivates people to live up to social norms. According to terror management theory (TMT), people can achieve a sense of self-worth through compliance with social norms. However, this has not yet been empirically tested. Modesty has long been known as an important social norm in Eastern cultures, such as China, Japan, and Korea. The current research examined whether conforming to the modesty norm in response to reminders of death concerns increases self-esteem for Chinese. In Study 1, following the modesty norm (i.e., explicit self-effacement) led to decreased implicit self-esteem, however, this was only the case if mortality was salient. In Study 2, violating the modesty norm (i.e., explicit self-enhancement) increased implicit self-esteem - however - again, this was only the case when mortality was salient. These findings indicate that self-esteem cannot be maintained through compliance with the modesty norm. Implications of this research for understanding the interplay between self-esteem and social norms in terror management processes are discussed. © 2014 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Attitudes, norms, identity and environmental behaviour: using an expanded theory of planned behaviour to predict participation in a kerbside recycling programme.

PubMed

Nigbur, Dennis; Lyons, Evanthia; Uzzell, David

2010-06-01

In an effort to contribute to greater understanding of norms and identity in the theory of planned behaviour, an extended model was used to predict residential kerbside recycling, with self-identity, personal norms, neighbourhood identification, and injunctive and descriptive social norms as additional predictors. Data from a field study (N=527) using questionnaire measures of predictor variables and an observational measure of recycling behaviour supported the theory. Intentions predicted behaviour, while attitudes, perceived control, and the personal norm predicted intention to recycle. The interaction between neighbourhood identification and injunctive social norms in turn predicted personal norms. Self-identity and the descriptive social norm significantly added to the original theory in predicting intentions as well as behaviour directly. A replication survey on the self-reported recycling behaviours of a random residential sample (N=264) supported the model obtained previously. These findings offer a useful extension of the theory of planned behaviour and some practicable suggestions for pro-recycling interventions. It may be productive to appeal to self-identity by making people feel like recyclers, and to stimulate both injunctive and descriptive norms in the neighbourhood.

Parochial altruism in humans.

PubMed

Bernhard, Helen; Fischbacher, Urs; Fehr, Ernst

2006-08-24

Social norms and the associated altruistic behaviours are decisive for the evolution of human cooperation and the maintenance of social order, and they affect family life, politics and economic interactions. However, as altruistic norm compliance and norm enforcement often emerge in the context of inter-group conflicts, they are likely to be shaped by parochialism--a preference for favouring the members of one's ethnic, racial or language group. We have conducted punishment experiments, which allow 'impartial' observers to punish norm violators, with indigenous groups in Papua New Guinea. Here we show that these experiments confirm the prediction of parochialism. We found that punishers protect ingroup victims--who suffer from a norm violation--much more than they do outgroup victims, regardless of the norm violator's group affiliation. Norm violators also expect that punishers will be lenient if the latter belong to their social group. As a consequence, norm violations occur more often if the punisher and the norm violator belong to the same group. Our results are puzzling for evolutionary multi-level selection theories based on selective group extinction as well as for theories of individual selection; they also indicate the need to explicitly examine the interactions between individuals stemming from different groups in evolutionary models.

Variation in reaction norms: Statistical considerations and biological interpretation.

PubMed

Morrissey, Michael B; Liefting, Maartje

2016-09-01

Analysis of reaction norms, the functions by which the phenotype produced by a given genotype depends on the environment, is critical to studying many aspects of phenotypic evolution. Different techniques are available for quantifying different aspects of reaction norm variation. We examine what biological inferences can be drawn from some of the more readily applicable analyses for studying reaction norms. We adopt a strongly biologically motivated view, but draw on statistical theory to highlight strengths and drawbacks of different techniques. In particular, consideration of some formal statistical theory leads to revision of some recently, and forcefully, advocated opinions on reaction norm analysis. We clarify what simple analysis of the slope between mean phenotype in two environments can tell us about reaction norms, explore the conditions under which polynomial regression can provide robust inferences about reaction norm shape, and explore how different existing approaches may be used to draw inferences about variation in reaction norm shape. We show how mixed model-based approaches can provide more robust inferences than more commonly used multistep statistical approaches, and derive new metrics of the relative importance of variation in reaction norm intercepts, slopes, and curvatures. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

When is best-worst best? A comparison of best-worst scaling, numeric estimation, and rating scales for collection of semantic norms.

PubMed

Hollis, Geoff; Westbury, Chris

2018-02-01

Large-scale semantic norms have become both prevalent and influential in recent psycholinguistic research. However, little attention has been directed towards understanding the methodological best practices of such norm collection efforts. We compared the quality of semantic norms obtained through rating scales, numeric estimation, and a less commonly used judgment format called best-worst scaling. We found that best-worst scaling usually produces norms with higher predictive validities than other response formats, and does so requiring less data to be collected overall. We also found evidence that the various response formats may be producing qualitatively, rather than just quantitatively, different data. This raises the issue of potential response format bias, which has not been addressed by previous efforts to collect semantic norms, likely because of previous reliance on a single type of response format for a single type of semantic judgment. We have made available software for creating best-worst stimuli and scoring best-worst data. We also made available new norms for age of acquisition, valence, arousal, and concreteness collected using best-worst scaling. These norms include entries for 1,040 words, of which 1,034 are also contained in the ANEW norms (Bradley & Lang, Affective norms for English words (ANEW): Instruction manual and affective ratings (pp. 1-45). Technical report C-1, the center for research in psychophysiology, University of Florida, 1999).

Reliance on God, prayer, and religion reduces influence of perceived norms on drinking.

PubMed

Neighbors, Clayton; Brown, Garrett A; Dibello, Angelo M; Rodriguez, Lindsey M; Foster, Dawn W

2013-05-01

Previous research has shown that perceived social norms are among the strongest predictors of drinking among young adults. Research has also consistently found religiousness to be protective against risk and negative health behaviors. The present research evaluates the extent to which reliance on God, prayer, and religion moderates the association between perceived social norms and drinking. Participants (n = 1,124 undergraduate students) completed a cross-sectional survey online, which included measures of perceived norms, religious values, and drinking. Perceived norms were assessed by asking participants their perceptions of typical student drinking. Drinking outcomes included drinks per week, drinking frequency, and typical quantity consumed. Regression analyses indicated that religiousness and perceived norms had significant unique associations in opposite directions for all three drinking outcomes. Significant interactions were evident between religiousness and perceived norms in predicting drinks per week, frequency, and typical quantity. In each case, the interactions indicated weaker associations between norms and drinking among those who assigned greater importance to religiousness. The extent of the relationship between perceived social norms and drinking was buffered by the degree to which students identified with religiousness. A growing body of literature has shown interventions including personalized feedback regarding social norms to be an effective strategy in reducing drinking among college students. The present research suggests that incorporating religious or spiritual values into student interventions may be a promising direction to pursue.

Brief motivational intervention for college drinking: the synergistic impact of social anxiety and perceived drinking norms.

PubMed

Terlecki, Meredith A; Buckner, Julia D; Larimer, Mary E; Copeland, Amy L

2012-12-01

Despite the efficacy of Brief Alcohol Screening and Intervention for College Students (BASICS), students with higher social anxiety appear vulnerable to poorer outcomes. A possible explanation for these outcomes is that corrective normative feedback (an active component of BASICS) may be less effective for socially anxious students if their beliefs about others' drinking are less malleable because of intense fear of negative evaluation for deviating from perceived drinking norms. This study evaluated whether socially anxious students demonstrated less change in perceived norms during BASICS. We also examined whether change in norm endorsement moderated the relation between social anxiety and BASICS outcomes. Undergraduates (n = 52) who underwent BASICS completed measures of drinking, social anxiety, and perceived norms at baseline and 4 weeks post-BASICS. Higher social anxiety was related to less change in norm endorsement after receiving BASICS. Change in perceived norms during treatment moderated the relation between social anxiety and follow-up drinking. Among students with smaller change in norm endorsement after BASICS, higher social anxiety was related to heavier follow-up drinking. Among students with greater changes to norm endorsement during BASICS, the effect of social anxiety was nonsignificant. Results suggest that corrective perceived norms interventions may be less effective among socially anxious students, contributing to continued heavy drinking. Development of social anxiety-specific BASICS components warrants attention. 2013 APA, all rights reserved

Brief Motivational Intervention for College Drinking: The Synergistic Impact of Social Anxiety and Perceived Drinking Norms

PubMed Central

Terlecki, Meredith A.; Buckner, Julia D.; Larimer, Mary E.; Copeland, Amy L.

2012-01-01

Despite the efficacy of Brief Alcohol Screening and Intervention for College Students (BASICS), students with higher social anxiety appear vulnerable to poorer outcomes. A possible explanation for these outcomes is that corrective normative feedback (an active component of BASICS) may be less effective for socially anxious students if their beliefs about others’ drinking are less malleable due to intense fear of negative evaluation for deviating from perceived drinking norms. This study evaluated whether socially anxious students demonstrated less change in perceived norms during BASICS. We also examined whether change in norm endorsement moderated the relation between social anxiety and BASICS outcomes. Undergraduates (N = 52) who underwent BASICS completed measures of drinking, social anxiety, and perceived norms at baseline and 4-weeks post-BASICS. Higher social anxiety was related to less change in norm endorsement after receiving BASICS. Change in perceived norms during treatment moderated the relation between social anxiety and follow-up drinking. Among students with smaller change in norm endorsement after BASICS, higher social anxiety was related to heavier follow-up drinking. Among students with greater changes to norm endorsement during BASICS, the effect of social anxiety was non-significant. Results suggest that corrective perceived norms interventions may be less effective among socially anxious students, contributing to continued heavy drinking. Development of social anxiety-specific BASICS components warrants attention. PMID:22612254

Meta-analyses of the relationship between conformity to masculine norms and mental health-related outcomes.

PubMed

Wong, Y Joel; Ho, Moon-Ho Ringo; Wang, Shu-Yi; Miller, I S Keino

2017-01-01

Despite theoretical postulations that individuals' conformity to masculine norms is differentially related to mental health-related outcomes depending on a variety of contexts, there has not been any systematic synthesis of the empirical research on this topic. Therefore, the authors of this study conducted meta-analyses of the relationships between conformity to masculine norms (as measured by the Conformity to Masculine Norms Inventory-94 and other versions of this scale) and mental health-related outcomes using 78 samples and 19,453 participants. Conformity to masculine norms was modestly and unfavorably associated with mental health as well as moderately and unfavorably related to psychological help seeking. The authors also identified several moderation effects. Conformity to masculine norms was more strongly correlated with negative social functioning than with psychological indicators of negative mental health. Conformity to the specific masculine norms of self-reliance, power over women, and playboy were unfavorably, robustly, and consistently related to mental health-related outcomes, whereas conformity to the masculine norm of primacy of work was not significantly related to any mental health-related outcome. These findings highlight the need for researchers to disaggregate the generic construct of conformity to masculine norms and to focus instead on specific dimensions of masculine norms and their differential associations with other outcomes. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Reliance on God, Prayer, and Religion Reduces Influence of Perceived Norms on Drinking

PubMed Central

Neighbors, Clayton; Brown, Garrett A.; Dibello, Angelo M.; Rodriguez, Lindsey M.; Foster, Dawn W.

2013-01-01

Objective: Previous research has shown that perceived social norms are among the strongest predictors of drinking among young adults. Research has also consistently found religiousness to be protective against risk and negative health behaviors. The present research evaluates the extent to which reliance on God, prayer, and religion moderates the association between perceived social norms and drinking. Method: Participants (n = 1,124 undergraduate students) completed a cross-sectional survey online, which included measures of perceived norms, religious values, and drinking. Perceived norms were assessed by asking participants their perceptions of typical student drinking. Drinking outcomes included drinks per week, drinking frequency, and typical quantity consumed. Results: Regression analyses indicated that religiousness and perceived norms had significant unique associations in opposite directions for all three drinking outcomes. Significant interactions were evident between religiousness and perceived norms in predicting drinks per week, frequency, and typical quantity. In each case, the interactions indicated weaker associations between norms and drinking among those who assigned greater importance to religiousness. Conclusions: The extent of the relationship between perceived social norms and drinking was buffered by the degree to which students identified with religiousness. A growing body of literature has shown interventions including personalized feedback regarding social norms to be an effective strategy in reducing drinking among college students. The present research suggests that incorporating religious or spiritual values into student interventions may be a promising direction to pursue. PMID:23490564

Quantifying social norms: by coupling the ecosystem management concept and semi-quantitative sociological methods

NASA Astrophysics Data System (ADS)

Zhang, D.; Xu, H.

2012-12-01

Over recent decades, human-induced environmental changes have steadily and rapidly grown in intensity and impact to where they now often exceed natural impacts. As one of important components of human activities, social norms play key roles in environmental and natural resources management. But the lack of relevant quantitative data about social norms greatly limits our scientific understanding of the complex linkages between humans and nature, and hampers our solving of pressing environmental and social problems. In this study, we built a quantified method by coupling the ecosystem management concept, semi-quantitative sociological methods and mathematical statistics. We got the quantified value of social norms from two parts, whether the content of social norms coincide with the concept of ecosystem management (content value) and how about the performance after social norms were put into implementation (implementation value) . First, we separately identified 12 core elements of ecosystem management and 16 indexes of social norms, and then matched them one by one. According to their matched degree, we got the content value of social norms. Second, we selected 8 key factors that can represent the performance of social norms after they were put into implementation, and then we got the implementation value by Delph method. Adding these two parts values, we got the final value of each social norms. Third, we conducted a case study in Heihe river basin, the second largest inland river in China, by selecting 12 official edicts related to the river basin ecosystem management of Heihe River Basin. By doing so, we first got the qualified data of social norms which can be directly applied to the research that involved observational or experimental data collection of natural processes. Second, each value was supported by specific contents, so it can assist creating a clear road map for building or revising management and policy guidelines. For example, in this case study, the final quantified data of each social norm showed highly positive correlations with their content value rather than their implementation value, which implied the final value of social norms are mainly affected by the content of social norms. And the implementation of social norms had reached a relatively high degree compare to their theoretical maxvalue (from 71.29% to 80.25%) because of the compelling force of themselves, while the content value of social norms is so weak (from 16.69% to 30.62%) that urgently need to be improved. Third, the method can be extended to quantify the social norms of other ecosystems and further contributed to our understanding of the Coupled Human and Natural Systems and sustainability research.;

Mortality salience increases personal relevance of the norm of reciprocity.

PubMed

Schindler, Simon; Reinhard, Marc-André; Stahlberg, Dagmar

2012-10-01

Research on terror management theory found evidence that people under mortality salience strive to live up to salient cultural norms and values, like egalitarianism, pacifism, or helpfulness. A basic, strongly internalized norm in most human societies is the norm of reciprocity: people should support those who supported them (i.e., positive reciprocity), and people should injure those who injured them (i.e., negative reciprocity), respectively. In an experiment (N = 98; 47 women, 51 men), mortality salience overall significantly increased personal relevance of the norm of reciprocity (M = 4.45, SD = 0.65) compared to a control condition (M = 4.19, SD = 0.59). Specifically, under mortality salience there was higher motivation to punish those who treated them unfavourably (negative norm of reciprocity). Unexpectedly, relevance of the norm of positive reciprocity remained unaffected by mortality salience. Implications and limitations are discussed.

Predicting Drinking Behavior and Alcohol-Related Problems Among Fraternity and Sorority Members: Examining the Role of Descriptive and Injunctive Norms

PubMed Central

Larimer, Mary E.; Turner, Aaron P.; Mallett, Kimberly A.; Geisner, Irene Markman

2010-01-01

The authors examined the relation between Greek students’ perceptions of alcohol consumption in their pledge classes (descriptive norms) and acceptability of drinking (injunctive norms) and the ability of these normative influences to predict drinking behavior, alcohol-related negative consequences, and symptoms of alcohol dependence concurrently and prospectively over 1 year. Participants were 279 men and 303 women recruited from incoming pledge classes of 12 fraternities and 6 sororities, who completed measures of descriptive and injunctive norms, alcohol use, and consequences. Results revealed that descriptive norms significantly predicted concurrent drinking. After controlling for baseline drinking, injunctive norms significantly predicted drinking 1 year later and predicted alcohol-related consequences and dependency symptoms at baseline and follow-up. The potential to incorporate injunctive norms into preventive interventions is discussed. PMID:15482075

The "is" and the "ought": How do perceived social norms influence safety behaviors at work?

PubMed

Fugas, Carla S; Meliá, José L; Silva, Silvia A

2011-01-01

Despite a widespread view that social norms have an important contextual influence on health attitudes and behaviors, the impact of normative influences on safety behaviors has received very little attention. The current study proposes that supervisors' and coworkers' descriptive and injunctive safety norms influence proactive and compliance safety behaviors. Longitudinal results from 132 workers in a passenger transportation company support the link between coworkers' descriptive safety norms (at Time 1) and proactive safety practices (at Time 2). Crystallization of supervisor' injunctive safety norms (at Time 2) moderated the effect of coworkers' descriptive safety norms (at Time 1) on self-reported proactive safety behavior (at Time 2). These findings emphasize the differences between supervisors' and coworkers' descriptive and injunctive norms as sources of social influence on compliance and proactive safety behavior.

Adolescents' physical activities and peer norms: the mediating role of self-efficacy.

PubMed

Lu, Frank J H; Lin, Ju-Han; Hsu, Ya-Wen; Chou, Chien-Chih; Wang, Erica T W; Yeh, Li-Chin

2014-04-01

The purpose of the present study was to examine the relations among adolescents' self-efficacy and social norms, and physical activity and whether self-efficacy mediated the relationship between social norms and physical activity. 400 junior high school students (202 boys, 198 girls, 2 not identified; M age = 15.3yr., SD = 0.6) completed a demographic questionnaire, the International Physical Activity Questionnaire (IPAQ), the Perceived Self-Efficacy in Physical Activity Scale, and the Physical Activity Social Norms Scale. Regression analyses indicated that both self-efficacy and social norms predicted physical activity. Self-efficacy fully mediated the relationship between peer norms and physical activity for boys but partially mediated the relationship for girls. An application of the results may be to foster self-efficacy and peer norms as a motivational strategy for supporting increased physical activity.

Improved dynamic MRI reconstruction by exploiting sparsity and rank-deficiency.

PubMed

Majumdar, Angshul

2013-06-01

In this paper we address the problem of dynamic MRI reconstruction from partially sampled K-space data. Our work is motivated by previous studies in this area that proposed exploiting the spatiotemporal correlation of the dynamic MRI sequence by posing the reconstruction problem as a least squares minimization regularized by sparsity and low-rank penalties. Ideally the sparsity and low-rank penalties should be represented by the l(0)-norm and the rank of a matrix; however both are NP hard penalties. The previous studies used the convex l(1)-norm as a surrogate for the l(0)-norm and the non-convex Schatten-q norm (0

Arbitrary norm support vector machines.

PubMed

Huang, Kaizhu; Zheng, Danian; King, Irwin; Lyu, Michael R

2009-02-01

Support vector machines (SVM) are state-of-the-art classifiers. Typically L2-norm or L1-norm is adopted as a regularization term in SVMs, while other norm-based SVMs, for example, the L0-norm SVM or even the L(infinity)-norm SVM, are rarely seen in the literature. The major reason is that L0-norm describes a discontinuous and nonconvex term, leading to a combinatorially NP-hard optimization problem. In this letter, motivated by Bayesian learning, we propose a novel framework that can implement arbitrary norm-based SVMs in polynomial time. One significant feature of this framework is that only a sequence of sequential minimal optimization problems needs to be solved, thus making it practical in many real applications. The proposed framework is important in the sense that Bayesian priors can be efficiently plugged into most learning methods without knowing the explicit form. Hence, this builds a connection between Bayesian learning and the kernel machines. We derive the theoretical framework, demonstrate how our approach works on the L0-norm SVM as a typical example, and perform a series of experiments to validate its advantages. Experimental results on nine benchmark data sets are very encouraging. The implemented L0-norm is competitive with or even better than the standard L2-norm SVM in terms of accuracy but with a reduced number of support vectors, -9.46% of the number on average. When compared with another sparse model, the relevance vector machine, our proposed algorithm also demonstrates better sparse properties with a training speed over seven times faster.

How culture gets embrained: Cultural differences in event-related potentials of social norm violations

PubMed Central

Mu, Yan; Kitayama, Shinobu; Han, Shihui; Gelfand, Michele J.

2015-01-01

Humans are unique among all species in their ability to develop and enforce social norms, but there is wide variation in the strength of social norms across human societies. Despite this fundamental aspect of human nature, there has been surprisingly little research on how social norm violations are detected at the neurobiological level. Building on the emerging field of cultural neuroscience, we combine noninvasive electroencephalography (EEG) with a new social norm violation paradigm to examine the neural mechanisms underlying the detection of norm violations and how they vary across cultures. EEG recordings from Chinese and US participants (n = 50) showed consistent negative deflection of event-related potential around 400 ms (N400) over the central and parietal regions that served as a culture-general neural marker of detecting norm violations. The N400 at the frontal and temporal regions, however, was only observed among Chinese but not US participants, illustrating culture-specific neural substrates of the detection of norm violations. Further, the frontal N400 predicted a variety of behavioral and attitudinal measurements related to the strength of social norms that have been found at the national and state levels, including higher culture superiority and self-control but lower creativity. There were no cultural differences in the N400 induced by semantic violation, suggesting a unique cultural influence on social norm violation detection. In all, these findings provided the first evidence, to our knowledge, for the neurobiological foundations of social norm violation detection and its variation across cultures. PMID:26621713

Social norms and prejudice against homosexuals.

PubMed

Pereira, Annelyse; Monteiro, Maria Benedicta; Camino, Leoncio

2009-11-01

Different studies regarding the role of norms on the expression of prejudice have shown that the anti-prejudice norm influences people to inhibit prejudice expressions. However, if norm pressure has led to a substantial decrease in the public expression of prejudice against certain targets (e.g., blacks, women, blind people), little theoretical and empirical attention has been paid to the role of this general norm regarding sexual minorities (e.g., prostitutes, lesbians and gays). In this sense, the issue we want to address is whether general anti-prejudice norms can reduce the expression of prejudice against homosexual individuals. In this research we investigate the effect of activating an anti-prejudice norm against homosexuals on blatant and subtle expressions of prejudice. The anti-prejudice norm was experimentally manipulated and its effects were observed on rejection to intimacy (blatant prejudice) and on positive-negative emotions (subtle prejudice) regarding homosexuals. 136 university students were randomly allocated to activated-norm and control conditions and completed a questionnaire that included norm manipulation and the dependent variables. A multivariate analysis of variance (MANOVA) as well as subsequent ANOVAS showed that only in the high normative pressure condition participants expressed less rejection to intimacy and less negative emotions against homosexuals, when compared to the simple norm-activation and the control conditions. Positive emotions, however, were similar both in the high normative pressure and the control conditions. We concluded that a high anti-prejudice pressure regarding homosexuals could reduce blatant prejudice but not subtle prejudice, considering that the expression of negative emotions decreased while the expression of positive emotions remained stable.

Perceived eating norms and children's eating behaviour: An informational social influence account.

PubMed

Sharps, Maxine; Robinson, Eric

2017-06-01

There is initial evidence that beliefs about the eating behaviour of others (perceived eating norms) can influence children's vegetable consumption, but little research has examined the mechanisms explaining this effect. In two studies we aimed to replicate the effect that perceived eating norms have on children's vegetable consumption, and to explore mechanisms which may underlie the influence of perceived eating norms on children's vegetable consumption. Study 1 investigated whether children follow perceived eating norms due to a desire to maintain personal feelings of social acceptance. Study 2 investigated whether perceived eating norms influence eating behaviour because eating norms provide information which can remove uncertainty about how to behave. Across both studies children were exposed to vegetable consumption information of other children and their vegetable consumption was examined. In both studies children were influenced by perceived eating norms, eating more when led to believe others had eaten a large amount compared to when led to believe others had eaten no vegetables. In Study 1, children were influenced by a perceived eating norm regardless of whether they felt sure or unsure that other children accepted them. In Study 2, children were most influenced by a perceived eating norm if they were eating in a novel context in which it may have been uncertain how to behave, as opposed to an eating context that children had already encountered. Perceived eating norms may influence children's eating behaviour by removing uncertainty about how to behave, otherwise known as informational social influence. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Norms about Nonmarital Pregnancy and Willingness to Provide Resources to Unwed Parents

ERIC Educational Resources Information Center

Mollborn, Stefanie

2009-01-01

Contested social norms underlie public concern about adults' and teenagers' nonmarital pregnancy. The original, vignette-based National Pregnancy Norms Survey (N = 812) measures these norms and related sanctions. Descriptive analyses report embarrassment at the prospect of a nonmarital pregnancy by age and gender of hypothetical prospective…

Cultural Norms and Nonverbal Communication: An Illustration

ERIC Educational Resources Information Center

Chang, Yanrong

2015-01-01

Nonverbal communication takes place in specific cultural contexts and is influenced by cultural norms. Cultural norms are "social rules for what certain types of people should and should not do" (Hall, 2005). Different cultures might have different norms for nonverbal behaviors in specific social, relational, and geographical contexts.…

Potential Applications of Social Norms Theory to Academic Advising

ERIC Educational Resources Information Center

Demetriou, Cynthia

2005-01-01

Since the mid-1990s, social norms theory has become prevalent in student development literature and research. Subsequently, social norms interventions to change student behavior have spread across campuses nationwide through marketing campaigns. Theorists and practitioners have applied the social norms approach to primarily health-related student…

Norm Theory: Comparing Reality to Its Alternatives.

ERIC Educational Resources Information Center

Kahneman, Daniel; Miller, Dale T.

1986-01-01

A theory of norms and normality is applied to some phenomena of emotional responses, social judgment, and conversations about causes. Norm theory is applied in analyses of enhanced emotional response to events that have abnormal causes, of generation of prediction from observations of behavior, and of the role of norms. (Author/LMO)

Fractal analysis of multiscale spatial autocorrelation among point data

USGS Publications Warehouse

De Cola, L.

1991-01-01

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

Multiscale free-space optical interconnects for intrachip global communication: motivation, analysis, and experimental validation.

PubMed

McFadden, Michael J; Iqbal, Muzammil; Dillon, Thomas; Nair, Rohit; Gu, Tian; Prather, Dennis W; Haney, Michael W

2006-09-01

The use of optical interconnects for communication between points on a microchip is motivated by system-level interconnect modeling showing the saturation of metal wire capacity at the global layer. Free-space optical solutions are analyzed for intrachip communication at the global layer. A multiscale solution comprising microlenses, etched compound slope microprisms, and a curved mirror is shown to outperform a single-scale alternative. Microprisms are designed and fabricated and inserted into an optical setup apparatus to experimentally validate the concept. The multiscale free-space system is shown to have the potential to provide the bandwidth density and configuration flexibility required for global communication in future generations of microchips.

A multiscale decomposition approach to detect abnormal vasculature in the optic disc.

PubMed

Agurto, Carla; Yu, Honggang; Murray, Victor; Pattichis, Marios S; Nemeth, Sheila; Barriga, Simon; Soliz, Peter

2015-07-01

This paper presents a multiscale method to detect neovascularization in the optic disc (NVD) using fundus images. Our method is applied to a manually selected region of interest (ROI) containing the optic disc. All the vessels in the ROI are segmented by adaptively combining contrast enhancement methods with a vessel segmentation technique. Textural features extracted using multiscale amplitude-modulation frequency-modulation, morphological granulometry, and fractal dimension are used. A linear SVM is used to perform the classification, which is tested by means of 10-fold cross-validation. The performance is evaluated using 300 images achieving an AUC of 0.93 with maximum accuracy of 88%. Copyright © 2015 Elsevier Ltd. All rights reserved.

X-Ray Phase Imaging for Breast Cancer Detection

DTIC Science & Technology

2010-09-01

regularization seeks the minimum- norm , least squares solution for phase retrieval. The retrieval result with Tikhonov regularization is still unsatisfactory...of norm , that can effectively reflect the accuracy of the retrieved data as an image, if ‖δ Ik+1−δ Ik‖ is less than a predefined threshold value β...pointed out that the proper norm for images is the total variation (TV) norm , which is the L1 norm of the gradient of the image function, and not the

Silence and table manners: when environments activate norms.

PubMed

Joly, Janneke F; Stapel, Diederik A; Lindenberg, Siegwart M

2008-08-01

Two studies tested the conditions under which an environment (e.g., library, restaurant) raises the relevance of environment-specific social norms (e.g., being quiet, using table manners). As hypothesized, the relevance of such norms is raised when environments are goal relevant ("I am going there later") and when they are humanized with people or the remnants of their presence (e.g., a glass of wine on a table). Two studies show that goal-relevant environments and humanized environments raise the perceived importance of norms (Study 1) and the intention to conform to norms (Study 2). Interestingly, in both studies, these effects reach beyond norms related to the environments used in the studies.

Cops or Robbers — a Bistable Society

NASA Astrophysics Data System (ADS)

Kułakowski, K.

The norm game described by Axelrod in 1985 was recently treated with the master equation formalism. Here we discuss the equations, where (i) those who break the norm cannot punish and those who punish cannot break the norm, (ii) the tendency to punish is suppressed if the majority breaks the norm. The second mechanism is new. For some values of the parameters the solution shows the saddle-point bifurcation. Then, two stable solutions are possible, where the majority breaks the norm or the majority punishes. This means, that the norm breaking can be discontinuous, when measured in the social scale. The bistable character is reproduced also with new computer simulations on the Erdös-Rényi directed network.

Using the RxNorm Web Services API for Quality Assurance Purposes

PubMed Central

Peters, Lee; Bodenreider, Olivier

2008-01-01

Auditing large, rapidly evolving terminological systems is still a challenge. In the case of RxNorm, a standardized nomenclature for clinical drugs, we argue that quality assurance processes can benefit from the recently released application programming interface (API) provided by RxNav. We demonstrate the usefulness of the API by performing a systematic comparison of alternative paths in the RxNorm graph, over several thousands of drug entities. This study revealed potential errors in RxNorm, currently under review. The results also prompted us to modify the implementation of RxNav to navigate the RxNorm graph more accurately. The RxNorm web services API used in this experiment is robust and fast. PMID:18999038

A meta-analysis of the relations between three types of peer norms and adolescent sexual behavior

PubMed Central

van de Bongardt, Daphne; Reitz, Ellen; Sandfort, Theo; Deković, Maja

2018-01-01

The aim of the present meta-analysis was to investigate the associations between three types of peer norms–descriptive norms (peer sexual behaviors), injunctive norms (peer sexual attitudes), and peer pressure to have sex–and two adolescent sexual behavior outcomes (sexual activity and sexual risk behavior). Adolescent sexual activity was more strongly associated with descriptive norms (ESrfixed = .40) than with injunctive norms (ESrfixed = .22) or peer pressure (ESrfixed = .10). Compared with the sexual activity outcome, the effect size for descriptive norms (peer sexual risk behavior) for sexual risk behavior was smaller (ESrfixed = .11). Age, gender, peer type, and socio-cultural context significantly moderated these associations. Additional analyses of longitudinal studies suggested that selection effects were stronger than socialization effects. These findings offer empirical support for the conceptual distinction between three types of peer norms and hold important implications for theory, research, and intervention strategies. PMID:25217363

Computational Substrates of Social Norm Enforcement by Unaffected Third Parties

PubMed Central

Zhong, Songfa; Chark, Robin; Hsu, Ming; Chew, Soo Hong

2016-01-01

Enforcement of social norms by impartial bystanders in the human species reveals a possibly unique capacity to sense and to enforce norms from a third party perspective. Such behavior, however, cannot be accounted by current computational models based on an egocentric notion of norms. Here, using a combination of model-based fMRI and third party punishment games, we show that brain regions previously implicated in egocentric norm enforcement critically extend to the important case of norm enforcement by unaffected third parties. Specifically, we found that responses in the ACC and insula cortex were positively associated with detection of distributional inequity, while those in the anterior DLPFC were associated with assessment of intentionality to the violator. Moreover, during sanction decisions, the subjective value of sanctions modulated activity in both vmPFC and rTPJ. These results shed light on the neurocomputational underpinnings of third party punishment and evolutionary origin of human norm enforcement. PMID:26825438

Masculinity and HIV: Dimensions of Masculine Norms that Contribute to Men's HIV-Related Sexual Behaviors.

PubMed

Fleming, Paul J; DiClemente, Ralph J; Barrington, Clare

2016-04-01

Numerous studies have documented a relationship between masculine norms and men's HIV-related sexual behaviors, but intervening upon this relationship requires a nuanced understanding of the specific aspects of masculine norms that shape men's sexual behaviors. We integrate theories on masculinities with empirical HIV research to identify specific dimensions of masculine norms that influence men's HIV-related sexual behaviors. We identify three major dimensions of masculine norms that shape men's sexual behavior: (1) uncontrollable male sex drive, (2) capacity to perform sexually, and (3) power over others. While the existing literature does help explain the relationship between masculine norms and men's sexual behaviors several gaps remain including: a recognition of context-specific masculinities, an interrogation of the positive influences of masculinity, adoption of an intersectional approach, assessment of changes in norms and behaviors over time, and rigorous evaluations of gender-transformative approaches. Addressing these gaps in future research may optimize prevention efforts.

Norms governing urban African American adolescents’ sexual and substance-using behavior

PubMed Central

Dolcini, M. Margaret; Catania, Joseph A.; Harper, Gary W.; Watson, Susan E.; Ellen, Jonathan M.; Towner, Senna L.

2013-01-01

Using a probability-based neighborhood sample of urban African American youth and a sample of their close friends (N = 202), we conducted a one-year longitudinal study to examine key questions regarding sexual and drug using norms. The results provide validation of social norms governing sexual behavior, condom use, and substance use among friendship groups. These norms had strong to moderate homogeneity; and both normative strength and homogeneity were relatively stable over a one-year period independent of changes in group membership. The data further suggest that sex and substance using norms may operate as a normative set. Similar to studies of adults, we identified three distinct “norm-based” social strata in our sample. Together, our findings suggest that the norms investigated are valid targets for health promotion efforts, and such efforts may benefit from tailoring programs to the normative sets that make up the different social strata in a given adolescent community. PMID:23072891

Young Children See a Single Action and Infer a Social Norm.

PubMed

Schmidt, Marco F H; Butler, Lucas P; Heinz, Julia; Tomasello, Michael

2016-10-01

Human social life depends heavily on social norms that prescribe and proscribe specific actions. Typically, young children learn social norms from adult instruction. In the work reported here, we showed that this is not the whole story: Three-year-old children are promiscuous normativists. In other words, they spontaneously inferred the presence of social norms even when an adult had done nothing to indicate such a norm in either language or behavior. And children of this age even went so far as to enforce these self-inferred norms when third parties "broke" them. These results suggest that children do not just passively acquire social norms from adult behavior and instruction; rather, they have a natural and proactive tendency to go from "is" to "ought." That is, children go from observed actions to prescribed actions and do not perceive them simply as guidelines for their own behavior but rather as objective normative rules applying to everyone equally.

Does neighborhood social cohesion modify the relationship between neighborhood social norms and smoking behaviors in Mexico?

PubMed

Lozano, Paula; Fleischer, Nancy L; Moore, Spencer; Shigematsu, Luz Myriam Reynales; Santillán, Edna Arillo; Thrasher, James F

2016-07-01

The aim of this study was to examine the separate and combined relationships of neighborhood social norms and neighborhood social cohesion with smoking behavior in a cohort of adult Mexican smokers. Neighborhood anti-smoking norms were measured as the proportion of residents in each neighborhood who believed that society disapproves of smoking. Perceived social cohesion was measured using a 5-item cohesion scale and aggregated to the neighborhood level. Higher neighborhood anti-smoking norms were associated with less successful quitting. Neighborhood social cohesion modified the relationship between neighborhood social norms and two smoking behaviors: smoking intensity and quit attempts. Residents of neighborhoods with weaker anti-smoking norms and higher social cohesion had lower smoking intensity and more quit attempts than residents living in other areas. Social cohesion may help buffer smoking behavior in areas with weak social norms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Local social norms and military sexual stressors: do senior officers' norms matter?

PubMed

Murdoch, Maureen; Pryor, John Barron; Polusny, Melissa Anderson; Gackstetter, Gary D; Ripley, Diane Cowper

2009-10-01

To examine the relative importance of harassment-tolerant norms emanating from troops senior officers, immediate supervisors, and units on troops' sexual stressor experiences and to see whether associations differed by sex. Cross-sectional survey of all 681 willing and confirmed active duty troops enrolled in the VA National Enrollment Database between 1998 and 2002. Findings extended an earlier analysis. After adjusting for other significant correlates, senior officers' perceived tolerance of sexual harassment was not associated with the severity of sexual harassment troops reported (p = 0.64) or with the numbers of sexual identity challenges they reported (p = 0.11). Harassment-tolerant norms emanating from troops' units and immediate supervisors were associated with reporting more severe sexual harassment and more sexual identity challenges (all p < 0.003). Findings generalized across sex. Senior officers' norms did not appear to affect troops' reports of military sexual stressors, but unit norms and immediate supervisors' norms did.

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

EPA Science Inventory

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used t...

REVIEW OF THE GOVERNING EQUATIONS, COMPUTATIONAL ALGORITHMS, AND OTHER COMPONENTS OF THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM

EPA Science Inventory

This article describes the governing equations, computational algorithms, and other components entering into the Community Multiscale Air Quality (CMAQ) modeling system. This system has been designed to approach air quality as a whole by including state-of-the-science capabiliti...

Observations and modeling of air quality trends over 1990-2010 across the northern hemisphere: China, the United States and Europe

EPA Science Inventory

Trends in air quality across the Northern Hemisphere over a 21-year period (1990–2010) were simulated using the Community Multiscale Air Quality (CMAQ) multiscale chemical transport model driven by meteorology from Weather Research and Forecasting WRF) simulations and internally ...

Comparing AMSR-E soil moisture estimates to the extended record of the U.S. Climate Reference Network (USCRN)

USDA-ARS?s Scientific Manuscript database

Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only...

DEVELOPMENT OF AN AGGREGATION AND EPISODE SELECTION SCHEME TO SUPPORT THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY MODEL

EPA Science Inventory

The development of an episode selection and aggregation approach, designed to support distributional estimation of use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700-hPa east-west and north-south...

Evaluation of the Community Multiscale Air Quality (CMAQ) modeling system against size-resolved measurements of inorganic particle composition across sites in North America

EPA Science Inventory

This work evaluates particle size-composition distributions simulated by the Community Multiscale Air Quality (CMAQ) model using Micro-Orifice Uniform Deposit Impactor (MOUDI) measurements at 18 sites across North America. Size-resolved measurements of particulate SO₄<...

Interpreting multiscale domains of tree cover disturbance patterns in North America

Treesearch

Kurt Riitters; Jennifer K. Costanza; Brian Buma

2017-01-01

Spatial patterns at multiple observation scales provide a framework to improve understanding of pattern-related phenomena. However, the metrics that are most sensitive to local patterns are least likely to exhibit consistent scaling relations with increasing extent (observation scale). A conceptual framework based on multiscale domains (i.e., geographic locations...

Models, Databases, and Simulation Tools Needed for the Realization of Integrated Computational Materials Engineering. Proceedings of the Symposium Held at Materials Science and Technology 2010

NASA Technical Reports Server (NTRS)

Arnold, Steven M. (Editor); Wong, Terry T. (Editor)

2011-01-01

Topics covered include: An Annotative Review of Multiscale Modeling and its Application to Scales Inherent in the Field of ICME; and A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures.

Multiscale Reactive Molecular Dynamics

DTIC Science & Technology

2012-08-15

biology cannot be described without considering electronic and nuclear-level dynamics and their coupling to slower, cooperative motions of the system ...coupling to slower, cooperative motions of the system . These inherently multiscale problems require computationally efficient and accurate methods to...condensed phase systems with computational efficiency orders of magnitudes greater than currently possible with ab initio simulation methods, thus

APPLICATION OF THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODEL SYSTEM TO SOS/NASHVILLE 1999

EPA Science Inventory

The Models-3 Community Multi-scale Air Quality (CMAQ) model, first released by the USEPA in 1999 (Byun and Ching. 1999), continues to be developed and evaluated. The principal components of the CMAQ system include a comprehensive emission processor known as the Sparse Matrix O...

Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin.

EPA Science Inventory

The Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models were used to simulate a 10 day high‐ozone episode observed during the 2013 Uinta Basin Winter Ozone Study (UBWOS). The baseline model had a large negative bias when compared to ozo...

Comparison of Single and Multi-Scale Method for Leaf and Wood Points Classification from Terrestrial Laser Scanning Data

NASA Astrophysics Data System (ADS)

Wei, Hongqiang; Zhou, Guiyun; Zhou, Junjie

2018-04-01

The classification of leaf and wood points is an essential preprocessing step for extracting inventory measurements and canopy characterization of trees from the terrestrial laser scanning (TLS) data. The geometry-based approach is one of the widely used classification method. In the geometry-based method, it is common practice to extract salient features at one single scale before the features are used for classification. It remains unclear how different scale(s) used affect the classification accuracy and efficiency. To assess the scale effect on the classification accuracy and efficiency, we extracted the single-scale and multi-scale salient features from the point clouds of two oak trees of different sizes and conducted the classification on leaf and wood. Our experimental results show that the balanced accuracy of the multi-scale method is higher than the average balanced accuracy of the single-scale method by about 10 % for both trees. The average speed-up ratio of single scale classifiers over multi-scale classifier for each tree is higher than 30.

A multiscale, model-based analysis of the multi-tissue interplay underlying blood glucose regulation in type I diabetes.

PubMed

Wadehn, Federico; Schaller, Stephan; Eissing, Thomas; Krauss, Markus; Kupfer, Lars

2016-08-01

A multiscale model for blood glucose regulation in diabetes type I patients is constructed by integrating detailed metabolic network models for fat, liver and muscle cells into a whole body physiologically-based pharmacokinetic/pharmacodynamic (pBPK/PD) model. The blood glucose regulation PBPK/PD model simulates the distribution and metabolization of glucose, insulin and glucagon on an organ and whole body level. The genome-scale metabolic networks in contrast describe intracellular reactions. The developed multiscale model is fitted to insulin, glucagon and glucose measurements of a 48h clinical trial featuring 6 subjects and is subsequently used to simulate (in silico) the influence of geneknockouts and drug-induced enzyme inhibitions on whole body blood glucose levels. Simulations of diabetes associated gene knockouts and impaired cellular glucose metabolism, resulted in elevated whole body blood-glucose levels, but also in a metabolic shift within the cell's reaction network. Such multiscale models have the potential to be employed in the exploration of novel drug-targets or to be integrated into control algorithms for artificial pancreas systems.

A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

NASA Astrophysics Data System (ADS)

Matouš, Karel; Geers, Marc G. D.; Kouznetsova, Varvara G.; Gillman, Andrew

2017-02-01

Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platform in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.

Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

NASA Astrophysics Data System (ADS)

Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

2017-10-01

A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

A FSI computational framework for vascular physiopathology: A novel flow-tissue multiscale strategy.

PubMed

Bianchi, Daniele; Monaldo, Elisabetta; Gizzi, Alessio; Marino, Michele; Filippi, Simonetta; Vairo, Giuseppe

2017-09-01

A novel fluid-structure computational framework for vascular applications is herein presented. It is developed by combining the double multi-scale nature of vascular physiopathology in terms of both tissue properties and blood flow. Addressing arterial tissues, they are modelled via a nonlinear multiscale constitutive rationale, based only on parameters having a clear histological and biochemical meaning. Moreover, blood flow is described by coupling a three-dimensional fluid domain (undergoing physiological inflow conditions) with a zero-dimensional model, which allows to reproduce the influence of the downstream vasculature, furnishing a realistic description of the outflow proximal pressure. The fluid-structure interaction is managed through an explicit time-marching approach, able to accurately describe tissue nonlinearities within each computational step for the fluid problem. A case study associated to a patient-specific aortic abdominal aneurysmatic geometry is numerically investigated, highlighting advantages gained from the proposed multiscale strategy, as well as showing soundness and effectiveness of the established framework for assessing useful clinical quantities and risk indexes. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

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

Matouš, Karel, E-mail: kmatous@nd.edu; Geers, Marc G.D.; Kouznetsova, Varvara G.

2017-02-01

Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platformmore » in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.« less

Multiscale entropy-based methods for heart rate variability complexity analysis

NASA Astrophysics Data System (ADS)

Silva, Luiz Eduardo Virgilio; Cabella, Brenno Caetano Troca; Neves, Ubiraci Pereira da Costa; Murta Junior, Luiz Otavio

2015-03-01

Physiologic complexity is an important concept to characterize time series from biological systems, which associated to multiscale analysis can contribute to comprehension of many complex phenomena. Although multiscale entropy has been applied to physiological time series, it measures irregularity as function of scale. In this study we purpose and evaluate a set of three complexity metrics as function of time scales. Complexity metrics are derived from nonadditive entropy supported by generation of surrogate data, i.e. SDiffqmax, qmax and qzero. In order to access accuracy of proposed complexity metrics, receiver operating characteristic (ROC) curves were built and area under the curves was computed for three physiological situations. Heart rate variability (HRV) time series in normal sinus rhythm, atrial fibrillation, and congestive heart failure data set were analyzed. Results show that proposed metric for complexity is accurate and robust when compared to classic entropic irregularity metrics. Furthermore, SDiffqmax is the most accurate for lower scales, whereas qmax and qzero are the most accurate when higher time scales are considered. Multiscale complexity analysis described here showed potential to assess complex physiological time series and deserves further investigation in wide context.

Multi-scale symbolic transfer entropy analysis of EEG

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-10-01

From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh

2017-10-01

Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.

Control of Thermo-Acoustics Instabilities: The Multi-Scale Extended Kalman Approach

NASA Technical Reports Server (NTRS)

Le, Dzu K.; DeLaat, John C.; Chang, Clarence T.

2003-01-01

"Multi-Scale Extended Kalman" (MSEK) is a novel model-based control approach recently found to be effective for suppressing combustion instabilities in gas turbines. A control law formulated in this approach for fuel modulation demonstrated steady suppression of a high-frequency combustion instability (less than 500Hz) in a liquid-fuel combustion test rig under engine-realistic conditions. To make-up for severe transport-delays on control effect, the MSEK controller combines a wavelet -like Multi-Scale analysis and an Extended Kalman Observer to predict the thermo-acoustic states of combustion pressure perturbations. The commanded fuel modulation is composed of a damper action based on the predicted states, and a tones suppression action based on the Multi-Scale estimation of thermal excitations and other transient disturbances. The controller performs automatic adjustments of the gain and phase of these actions to minimize the Time-Scale Averaged Variances of the pressures inside the combustion zone and upstream of the injector. The successful demonstration of Active Combustion Control with this MSEK controller completed an important NASA milestone for the current research in advanced combustion technologies.

Multiscale transparent electrode architecture for efficient light management and carrier collection in solar cells.

PubMed

Boccard, Mathieu; Battaglia, Corsin; Hänni, Simon; Söderström, Karin; Escarré, Jordi; Nicolay, Sylvain; Meillaud, Fanny; Despeisse, Matthieu; Ballif, Christophe

2012-03-14

The challenge for all photovoltaic technologies is to maximize light absorption, to convert photons with minimal losses into electric charges, and to efficiently extract them to the electrical circuit. For thin-film solar cells, all these tasks rely heavily on the transparent front electrode. Here we present a multiscale electrode architecture that allows us to achieve efficiencies as high as 14.1% with a thin-film silicon tandem solar cell employing only 3 μm of silicon. Our approach combines the versatility of nanoimprint lithography, the unusually high carrier mobility of hydrogenated indium oxide (over 100 cm(2)/V/s), and the unequaled light-scattering properties of self-textured zinc oxide. A multiscale texture provides light trapping over a broad wavelength range while ensuring an optimum morphology for the growth of high-quality silicon layers. A conductive bilayer stack guarantees carrier extraction while minimizing parasitic absorption losses. The tunability accessible through such multiscale electrode architecture offers unprecedented possibilities to address the trade-off between cell optical and electrical performance. © 2012 American Chemical Society

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

Multiscale analysis of information dynamics for linear multivariate processes.

PubMed

Faes, Luca; Montalto, Alessandro; Stramaglia, Sebastiano; Nollo, Giandomenico; Marinazzo, Daniele

2016-08-01

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using statespace (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors.

Deviancy from the Norms of Science: The Effects of Anomie and Alienation in the Academic Profession.

ERIC Educational Resources Information Center

Braxton, John M.

1993-01-01

A study applying anomie theory to behavior of college faculty, especially as alienation from the academic reward system results in deviation from professional norms of communality, disinterestedness, universalism, and organized skepticism, is reported. Implications for use of norms as interpretive devices, ambivalence of academics toward norms,…

Global Norms: Towards Some Guidelines for Aggregating Personality Norms across Countries

ERIC Educational Resources Information Center

Bartram, Dave

2008-01-01

The article discusses issues relating to the international use of personality inventories, especially those in which organizations make comparisons between people from differing cultures or countries or those with different languages. The focus is on the issue of norming and the use of national versus multinational norms. It is noted that…

On the Normed Space of Equivalence Classes of Fuzzy Numbers

PubMed Central

Lu, Chongxia; Zhang, Wei

2013-01-01

We study the norm induced by the supremum metric on the space of fuzzy numbers. And then we propose a method for constructing a norm on the quotient space of fuzzy numbers. This norm is very natural and works well with the induced metric on the quotient space. PMID:24072984

A Call for a New National Norming Methodology.

ERIC Educational Resources Information Center

Ligon, Glynn; Mangino, Evangelina

Issues related to achieving adequate national norms are reviewed, and a new methodology is proposed that would work to provide a true measure of national achievement levels on an annual basis and would enable reporting results in current-year norms. Statistical methodology and technology could combine to create a national norming process that…

Validity of Other-Gender-Normed Scales on the Kuder Occupational Interest Survey.

ERIC Educational Resources Information Center

Zytowski, Donald G.; Laing, Joan

1978-01-01

Investigated the relationship between KOIS twin scales normed separately on males and females for occupations and college majors. Rankings on own- and other-gender-normed scales correlated highly. The scales were approximately equal in predictive validity. Rankings on other-gender-normed scales provided an accurate estimate of expected rankings on…

Social Norms Shift Preferences for Healthy and Unhealthy Foods

PubMed Central

Templeton, Emma M.; Stanton, Michael V.; Zaki, Jamil

2016-01-01

This research investigated whether people change their food preferences and eating behavior in response to health-based social norms. One hundred twenty participants rated a series of healthy and unhealthy food images. After each rating, participants sometimes viewed a rating that ostensibly represented the average rating of previous participants. In fact, these average ratings were manipulated to convey a particular social norm. Participants either saw average ratings that favored healthy foods, favored unhealthy foods, or did not see any average ratings. Participants then re-rated those same food images after approximately ten minutes and again three days later. After the norm manipulation, participants were given the chance to take as many M&Ms as they wanted. Participants exposed to a healthy social norm consistently reported lower preferences for unhealthy foods as compared to participants in the other two conditions. This preference difference persisted three days after the social norm manipulation. However, health-based social norm manipulations did not influence the amount of M&Ms participants took. Although health-based social norm manipulations can influence stated food preferences, in this case they did not influence subsequent eating behavior. PMID:27861518

Aggression Norms in the Classroom Social Network: Contexts of Aggressive Behavior and Social Preference in Middle Childhood.

PubMed

Jackson, Daisy R; Cappella, Elise; Neal, Jennifer Watling

2015-12-01

In a cross-sectional sample of African-American 2nd-4th grade students (N = 681), we examine the moderating effects of classroom overt and relational aggression norms on peers' social acceptance of classmates who exhibit overt and relational aggression in urban schools. Extending theory and research on classroom norms, we integrate social network data to adjust aggression norms based on children's direct and indirect connections in the classroom. Results of multilevel models indicate that network-based classroom aggression norms moderated relations between children's aggressive behavior and their social preference. Specifically, children benefited socially when their form of aggressive behavior fit with what was normative in the classroom social context. The moderating effect of classroom aggression norms was stronger for the association between overt aggression and social preference than relational aggression and social preference. Relationally aggressive youth were socially preferred by peers regardless of the classroom norm, although this positive association was magnified in classrooms with higher levels of relational aggression. Future research focused on aggression norms within classroom social networks are discussed and implications for school prevention efforts are considered.

Perceived social norms and eating behaviour: An evaluation of studies and future directions.

PubMed

Robinson, Eric

2015-12-01

Social norms refer to what most people typically do or approve of. There has been some suggestion that perceived social norms may be an important influence on eating behaviour. We and others have shown that perceived social norms relating to very specific contexts can influence food intake (the amount of food consumed in a single sitting) in those contexts; these studies have predominantly sampled young female adults. Less research has examined whether perceived social norms predict dietary behaviour (the types of food people eat on a day to day basis); here, most evidence comes from cross-sectional studies, which have a number of limitations. A small number of intervention studies have started to explore whether perceived social norms can be used to encourage healthier eating with mixed results. The influence that perceived social norms have on objective measures of eating behaviour now needs to be examined using longitudinal methods in order to determine if social norms are an important influence on eating behaviour and/or can be used to promote meaningful behaviour change. Copyright © 2015 Elsevier Inc. All rights reserved.

One-norm geometric quantum discord and critical point estimation in the XY spin chain

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

Cheng, Chang-Cheng; Wang, Yao; Guo, Jin-Liang, E-mail: guojinliang80@163.com

2016-11-15

In contrast with entanglement and quantum discord (QD), we investigate the thermal quantum correlation in terms of Schatten one-norm geometric quantum discord (GQD) in the XY spin chain, and analyze their capabilities in detecting the critical point of quantum phase transition. We show that the one-norm GQD can reveal more properties about quantum correlation between two spins, especially for the long-range quantum correlation at finite temperature. Under the influences of site distance, anisotropy and temperature, one-norm GQD and its first derivative make it possible to detect the critical point efficiently for a general XY spin chain. - Highlights: • Comparingmore » with entanglement and QD, one-norm GQD is more robust versus the temperature. • One-norm GQD is more efficient in characterization of long-range quantum correlation between two distant qubits. • One-norm GQD performs well in highlighting the critical point of QPT at zero or low finite temperature. • One-norm GQD has a number of advantages over QD in detecting the critical point of the spin chain.« less

The many faces of manhood: examining masculine norms and health behaviors of young fathers across race.

PubMed

Gordon, Derrick M; Hawes, Samuel W; Reid, Allecia E; Callands, Tamora A; Magriples, Urania; Divney, Anna; Niccolai, Linda M; Kershaw, Trace

2013-09-01

This study examined the relationship between the traditional masculine norms ("status," "toughness" and "antifemininity") of 296 ethnically and racially diverse, young men transitioning to fatherhood and substance use (smoking, alcohol, marijuana, hard drugs) and health behaviors (diet, exercise). Participants were recruited from urban obstetric clinics in the Northeast United States. Logistic and multiple regression equations were constructed to examine the relationship between masculine norms and health behaviors. Moderator effects were also examined. Masculine norm "status" was most endorsed and "antifemininity" was least endorsed. African American young men had higher masculine norm scores than Latino and Whites. Different masculine norms were associated with health-promoting and health-undermining behaviors. Different racial groups who had higher scores on some masculine norms were more likely to engage in either health-promoting or health-undermining behaviors when compared with other ethnic groups in this study. These results observed different relationships between the traditional masculine norms measured and the substance use and health behaviors of diverse, young men transitioning to fatherhood. This may have implications for intervention strategies and future research.

Breaking the circle: challenging Western sociocultural norms for appearance influences young women's attention to appearance-related media.

PubMed

Mischner, Isabelle H S; van Schie, Hein T; Engels, Rutger C M E

2013-06-01

Paying attention to thin media models may negatively affect women's self-evaluation. This study aimed to reduce the amount of attention that young women give to appearance-related information by challenging the sociocultural norms for appearance, and studied the moderating role of self-esteem. Seventy-one college women either received norm-confirming, norm-challenging, or no information regarding the sociocultural norms for appearance. Subsequently, participants' visual attention to appearance-related and neutral advertisements was measured using an eye-tracker. The results demonstrate that when no information or norm-confirming information was received, women with lower self-esteem paid more attention to the appearance-related advertisements than women with higher self-esteem. Importantly however, when norm-challenging information was received, women with lower self-esteem paid significantly less attention to the appearance-related ads than women with lower self-esteem who did not receive this manipulation. These findings indicate that challenging the sociocultural norms for appearance can attenuate the amount of attention women give to appearance-related media. Copyright © 2013 Elsevier Ltd. All rights reserved.

Social Anxiety and Cannabis-Related Impairment: The Synergistic Influences of Peer and Parent Descriptive and Injunctive Normative Perceptions.

PubMed

Foster, Dawn W; Garey, Lorra; Buckner, Julia D; Zvolensky, Michael J

2016-06-06

Cannabis users, especially socially anxious cannabis users, are influenced by perceptions of other's use. The present study tested whether social anxiety interacted with perceptions about peer and parent beliefs to predict cannabis-related problems. Participants were 148 (36.5% female, 60.1% non-Hispanic Caucasian) current cannabis users aged 18-36 (M = 21.01, SD = 3.09) who completed measures of perceived descriptive and injunctive norms, social anxiety, and cannabis use behaviors. Hierarchical multiple regressions were employed to investigate the predictive value of the social anxiety X parent injunctive norms X peer norms interaction terms on cannabis use behaviors. Higher social anxiety was associated with more cannabis problems. A three-way interaction emerged between social anxiety, parent injunctive norms, and peer descriptive norms, with respect to cannabis problems. Social anxiety was positively related to more cannabis problems when parent injunctive norms were high (i.e., perceived approval) and peer descriptive norms were low. Results further showed that social anxiety was positively related to more cannabis problems regardless of parent injunctive norms. The present work suggests that it may be important to account for parent influences when addressing normative perceptions among young adult cannabis users. Additional research is needed to determine whether interventions incorporating feedback regarding parent norms impacts cannabis use frequency and problems.

Do Sexual Assault Bystander Interventions Change Men's Intentions? Applying the Theory of Normative Social Behavior to Predicting Bystander Outcomes.

PubMed

Mabry, Amanda; Turner, Monique Mitchell

2016-01-01

The high prevalence of sexual assault on college campuses has led to the implementation of health communication programs to prevent sexual assault. A few novel programs focus on primary prevention by targeting social norms related to gender and masculinity among men through bystander intervention. Guided by the theory of normative social behavior, this study sought to examine the relative effect of campaigns communicating positive versus negative injunctive norms and the interaction between exposure to such campaign messages and perceived descriptive norms and relevant cognitive moderators (e.g., outcome expectations, injunctive norms, group identity, ego involvement) among men. A 2 (high/low descriptive norms) × 2 (high/low moderator) × 3 (public service announcement) independent groups quasi-experimental design (N = 332) was used. Results indicated that messages communicating positive injunctive norms were most effective among men who were least likely to engage in bystander intervention. Furthermore, descriptive norms played a significant role in behavioral intentions, such that those with stronger norms were more likely to report intentions to engage in bystander behaviors in the future. Similarly, the moderators of aspiration, injunctive norms, social approval, and ego involvement had a significant positive effect on behavioral intentions. These findings have important implications for future message design strategy and audience segmentation.