Geometric artifacts reduction for cone-beam CT via L0-norm minimization without dedicated phantoms.

PubMed

Gong, Changcheng; Cai, Yufang; Zeng, Li

2018-01-01

For cone-beam computed tomography (CBCT), transversal shifts of the rotation center exist inevitably, which will result in geometric artifacts in CT images. In this work, we propose a novel geometric calibration method for CBCT, which can also be used in micro-CT. The symmetry property of the sinogram is used for the first calibration, and then L0-norm of the gradient image from the reconstructed image is used as the cost function to be minimized for the second calibration. An iterative search method is adopted to pursue the local minimum of the L0-norm minimization problem. The transversal shift value is updated with affirmatory step size within a search range determined by the first calibration. In addition, graphic processing unit (GPU)-based FDK algorithm and acceleration techniques are designed to accelerate the calibration process of the presented new method. In simulation experiments, the mean absolute difference (MAD) and the standard deviation (SD) of the transversal shift value were less than 0.2 pixels between the noise-free and noisy projection images, which indicated highly accurate calibration applying the new calibration method. In real data experiments, the smaller entropies of the corrected images also indicated that higher resolution image was acquired using the corrected projection data and the textures were well protected. Study results also support the feasibility of applying the proposed method to other imaging modalities.

The seesaw space, a vector space to identify and characterize large-scale structures at 1 AU

NASA Astrophysics Data System (ADS)

Lara, A.; Niembro, T.

2017-12-01

We introduce the seesaw space, an orthonormal space formed by the local and the global fluctuations of any of the four basic solar parameters: velocity, density, magnetic field and temperature at any heliospheric distance. The fluctuations compare the standard deviation of a moving average of three hours against the running average of the parameter in a month (consider as the local fluctuations) and in a year (global fluctuations) We created this new vectorial spaces to identify the arrival of transients to any spacecraft without the need of an observer. We applied our method to the one-minute resolution data of WIND spacecraft from 1996 to 2016. To study the behavior of the seesaw norms in terms of the solar cycle, we computed annual histograms and fixed piecewise functions formed by two log-normal distributions and observed that one of the distributions is due to large-scale structures while the other to the ambient solar wind. The norm values in which the piecewise functions change vary in terms of the solar cycle. We compared the seesaw norms of each of the basic parameters due to the arrival of coronal mass ejections, co-rotating interaction regions and sector boundaries reported in literature. High seesaw norms are due to large-scale structures. We found three critical values of the norms that can be used to determined the arrival of coronal mass ejections. We present as well general comparisons of the norms during the two maxima and the minimum solar cycle periods and the differences of the norms due to large-scale structures depending on each period.

Support Minimized Inversion of Acoustic and Elastic Wave Scattering

NASA Astrophysics Data System (ADS)

Safaeinili, Ali

Inversion of limited data is common in many areas of NDE such as X-ray Computed Tomography (CT), Ultrasonic and eddy current flaw characterization and imaging. In many applications, it is common to have a bias toward a solution with minimum (L^2)^2 norm without any physical justification. When it is a priori known that objects are compact as, say, with cracks and voids, by choosing "Minimum Support" functional instead of the minimum (L^2)^2 norm, an image can be obtained that is equally in agreement with the available data, while it is more consistent with what is most probably seen in the real world. We have utilized a minimum support functional to find a solution with the smallest volume. This inversion algorithm is most successful in reconstructing objects that are compact like voids and cracks. To verify this idea, we first performed a variational nonlinear inversion of acoustic backscatter data using minimum support objective function. A full nonlinear forward model was used to accurately study the effectiveness of the minimized support inversion without error due to the linear (Born) approximation. After successful inversions using a full nonlinear forward model, a linearized acoustic inversion was developed to increase speed and efficiency in imaging process. The results indicate that by using minimum support functional, we can accurately size and characterize voids and/or cracks which otherwise might be uncharacterizable. An extremely important feature of support minimized inversion is its ability to compensate for unknown absolute phase (zero-of-time). Zero-of-time ambiguity is a serious problem in the inversion of the pulse-echo data. The minimum support inversion was successfully used for the inversion of acoustic backscatter data due to compact scatterers without the knowledge of the zero-of-time. The main drawback to this type of inversion is its computer intensiveness. In order to make this type of constrained inversion available for common use, work needs to be performed in three areas: (1) exploitation of state-of-the-art parallel computation, (2) improvement of theoretical formulation of the scattering process for better computation efficiency, and (3) development of better methods for guiding the non-linear inversion. (Abstract shortened by UMI.).

New Approaches to Minimum-Energy Design of Integer- and Fractional-Order Perfect Control Algorithms

NASA Astrophysics Data System (ADS)

Hunek, Wojciech P.; Wach, Łukasz

2017-10-01

In this paper the new methods concerning the energy-based minimization of the perfect control inputs is presented. For that reason the multivariable integer- and fractional-order models are applied which can be used for describing a various real world processes. Up to now, the classical approaches have been used in forms of minimum-norm/least squares inverses. Notwithstanding, the above-mentioned tool do not guarantee the optimal control corresponding to optimal input energy. Therefore the new class of inversebased methods has been introduced, in particular the new σ- and H-inverse of nonsquare parameter and polynomial matrices. Thus a proposed solution remarkably outperforms the typical ones in systems where the control runs can be understood in terms of different physical quantities, for example heat and mass transfer, electricity etc. A simulation study performed in Matlab/Simulink environment confirms the big potential of the new energy-based approaches.

An experimental clinical evaluation of EIT imaging with ℓ1 data and image norms.

PubMed

Mamatjan, Yasin; Borsic, Andrea; Gürsoy, Doga; Adler, Andy

2013-09-01

Electrical impedance tomography (EIT) produces an image of internal conductivity distributions in a body from current injection and electrical measurements at surface electrodes. Typically, image reconstruction is formulated using regularized schemes in which ℓ2-norms are used for both data misfit and image prior terms. Such a formulation is computationally convenient, but favours smooth conductivity solutions and is sensitive to outliers. Recent studies highlighted the potential of ℓ1-norm and provided the mathematical basis to improve image quality and robustness of the images to data outliers. In this paper, we (i) extended a primal-dual interior point method (PDIPM) algorithm to 2.5D EIT image reconstruction to solve ℓ1 and mixed ℓ1/ℓ2 formulations efficiently, (ii) evaluated the formulation on clinical and experimental data, and (iii) developed a practical strategy to select hyperparameters using the L-curve which requires minimum user-dependence. The PDIPM algorithm was evaluated using clinical and experimental scenarios on human lung and dog breathing with known electrode errors, which requires a rigorous regularization and causes the failure of reconstruction with an ℓ2-norm solution. The results showed that an ℓ1 solution is not only more robust to unavoidable measurement errors in a clinical setting, but it also provides high contrast resolution on organ boundaries.

MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters.

PubMed

Hincapié, Ana-Sofía; Kujala, Jan; Mattout, Jérémie; Daligault, Sebastien; Delpuech, Claude; Mery, Domingo; Cosmelli, Diego; Jerbi, Karim

2016-01-01

Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation.

MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters

PubMed Central

Hincapié, Ana-Sofía; Kujala, Jan; Mattout, Jérémie; Daligault, Sebastien; Delpuech, Claude; Mery, Domingo; Cosmelli, Diego; Jerbi, Karim

2016-01-01

Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation. PMID:27092179

Design of optimally normal minimum gain controllers by continuation method

NASA Technical Reports Server (NTRS)

Lim, K. B.; Juang, J.-N.; Kim, Z. C.

1989-01-01

A measure of the departure from normality is investigated for system robustness. An attractive feature of the normality index is its simplicity for pole placement designs. To allow a tradeoff between system robustness and control effort, a cost function consisting of the sum of a norm of weighted gain matrix and a normality index is minimized. First- and second-order necessary conditions for the constrained optimization problem are derived and solved by a Newton-Raphson algorithm imbedded into a one-parameter family of neighboring zero problems. The method presented allows the direct computation of optimal gains in terms of robustness and control effort for pole placement problems.

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

System identification using Nuclear Norm & Tabu Search optimization

NASA Astrophysics Data System (ADS)

Ahmed, Asif A.; Schoen, Marco P.; Bosworth, Ken W.

2018-01-01

In recent years, subspace System Identification (SI) algorithms have seen increased research, stemming from advanced minimization methods being applied to the Nuclear Norm (NN) approach in system identification. These minimization algorithms are based on hard computing methodologies. To the authors’ knowledge, as of now, there has been no work reported that utilizes soft computing algorithms to address the minimization problem within the nuclear norm SI framework. A linear, time-invariant, discrete time system is used in this work as the basic model for characterizing a dynamical system to be identified. The main objective is to extract a mathematical model from collected experimental input-output data. Hankel matrices are constructed from experimental data, and the extended observability matrix is employed to define an estimated output of the system. This estimated output and the actual - measured - output are utilized to construct a minimization problem. An embedded rank measure assures minimum state realization outcomes. Current NN-SI algorithms employ hard computing algorithms for minimization. In this work, we propose a simple Tabu Search (TS) algorithm for minimization. TS algorithm based SI is compared with the iterative Alternating Direction Method of Multipliers (ADMM) line search optimization based NN-SI. For comparison, several different benchmark system identification problems are solved by both approaches. Results show improved performance of the proposed SI-TS algorithm compared to the NN-SI ADMM algorithm.

Developing Uncertainty Models for Robust Flutter Analysis Using Ground Vibration Test Data

NASA Technical Reports Server (NTRS)

Potter, Starr; Lind, Rick; Kehoe, Michael W. (Technical Monitor)

2001-01-01

A ground vibration test can be used to obtain information about structural dynamics that is important for flutter analysis. Traditionally, this information#such as natural frequencies of modes#is used to update analytical models used to predict flutter speeds. The ground vibration test can also be used to obtain uncertainty models, such as natural frequencies and their associated variations, that can update analytical models for the purpose of predicting robust flutter speeds. Analyzing test data using the -norm, rather than the traditional 2-norm, is shown to lead to a minimum-size uncertainty description and, consequently, a least-conservative robust flutter speed. This approach is demonstrated using ground vibration test data for the Aerostructures Test Wing. Different norms are used to formulate uncertainty models and their associated robust flutter speeds to evaluate which norm is least conservative.

Robust method to detect and locate local earthquakes by means of amplitude measurements.

NASA Astrophysics Data System (ADS)

del Puy Papí Isaba, María; Brückl, Ewald

2016-04-01

In this study we present a robust new method to detect and locate medium and low magnitude local earthquakes. This method is based on an empirical model of the ground motion obtained from amplitude data of earthquakes in the area of interest, which were located using traditional methods. The first step of our method is the computation of maximum resultant ground velocities in sliding time windows covering the whole period of interest. In the second step, these maximum resultant ground velocities are back-projected to every point of a grid covering the whole area of interest while applying the empirical amplitude - distance relations. We refer to these back-projected ground velocities as pseudo-magnitudes. The number of operating seismic stations in the local network equals the number of pseudo-magnitudes at each grid-point. Our method introduces the new idea of selecting the minimum pseudo-magnitude at each grid-point for further analysis instead of searching for a minimum of the L2 or L1 norm. In case no detectable earthquake occurred, the spatial distribution of the minimum pseudo-magnitudes constrains the magnitude of weak earthquakes hidden in the ambient noise. In the case of a detectable local earthquake, the spatial distribution of the minimum pseudo-magnitudes shows a significant maximum at the grid-point nearest to the actual epicenter. The application of our method is restricted to the area confined by the convex hull of the seismic station network. Additionally, one must ensure that there are no dead traces involved in the processing. Compared to methods based on L2 and even L1 norms, our new method is almost wholly insensitive to outliers (data from locally disturbed seismic stations). A further advantage is the fast determination of the epicenter and magnitude of a seismic event located within a seismic network. This is possible due to the method of obtaining and storing a back-projected matrix, independent of the registered amplitude, for each seismic station. As a direct consequence, we are able to save computing time for the calculation of the final back-projected maximum resultant amplitude at every grid-point. The capability of the method was demonstrated firstly using synthetic data. In the next step, this method was applied to data of 43 local earthquakes of low and medium magnitude (1.7 < magnitude scale < 4.3). These earthquakes were recorded and detected by the seismic network ALPAACT (seismological and geodetic monitoring of Alpine PAnnonian ACtive Tectonics) in the period 2010/06/11 to 2013/09/20. Data provided by the ALPAACT network is used in order to understand seismic activity in the Mürz Valley - Semmering - Vienna Basin transfer fault system in Austria and what makes it such a relatively high earthquake hazard and risk area. The method will substantially support our efforts to involve scholars from polytechnic schools in seismological work within the Sparkling Science project Schools & Quakes.

Distance estimation and collision prediction for on-line robotic motion planning

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1992-01-01

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem is incorporated into the framework of an in-line motion-planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning, the deterministic problem where the information about the objects is assumed to be certain is examined. L(1) or L(infinity) norms are used to represent distance and the problem becomes a linear programming problem. The stochastic problem is formulated where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: First, filtering of the distance between the robot and the moving object at the present time. Second, prediction of the minimum distance in the future in order to predict the collision time.

Eigenvalue assignment by minimal state-feedback gain in LTI multivariable systems

NASA Astrophysics Data System (ADS)

Ataei, Mohammad; Enshaee, Ali

2011-12-01

In this article, an improved method for eigenvalue assignment via state feedback in the linear time-invariant multivariable systems is proposed. This method is based on elementary similarity operations, and involves mainly utilisation of vector companion forms, and thus is very simple and easy to implement on a digital computer. In addition to the controllable systems, the proposed method can be applied for the stabilisable ones and also systems with linearly dependent inputs. Moreover, two types of state-feedback gain matrices can be achieved by this method: (1) the numerical one, which is unique, and (2) the parametric one, in which its parameters are determined in order to achieve a gain matrix with minimum Frobenius norm. The numerical examples are presented to demonstrate the advantages of the proposed method.

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.

An Optimization-Based Method for Feature Ranking in Nonlinear Regression Problems.

PubMed

Bravi, Luca; Piccialli, Veronica; Sciandrone, Marco

2017-04-01

In this paper, we consider the feature ranking problem, where, given a set of training instances, the task is to associate a score with the features in order to assess their relevance. Feature ranking is a very important tool for decision support systems, and may be used as an auxiliary step of feature selection to reduce the high dimensionality of real-world data. We focus on regression problems by assuming that the process underlying the generated data can be approximated by a continuous function (for instance, a feedforward neural network). We formally state the notion of relevance of a feature by introducing a minimum zero-norm inversion problem of a neural network, which is a nonsmooth, constrained optimization problem. We employ a concave approximation of the zero-norm function, and we define a smooth, global optimization problem to be solved in order to assess the relevance of the features. We present the new feature ranking method based on the solution of instances of the global optimization problem depending on the available training data. Computational experiments on both artificial and real data sets are performed, and point out that the proposed feature ranking method is a valid alternative to existing methods in terms of effectiveness. The obtained results also show that the method is costly in terms of CPU time, and this may be a limitation in the solution of large-dimensional problems.

Detection of inter-patient left and right bundle branch block heartbeats in ECG using ensemble classifiers

PubMed Central

2014-01-01

Background Left bundle branch block (LBBB) and right bundle branch block (RBBB) not only mask electrocardiogram (ECG) changes that reflect diseases but also indicate important underlying pathology. The timely detection of LBBB and RBBB is critical in the treatment of cardiac diseases. Inter-patient heartbeat classification is based on independent training and testing sets to construct and evaluate a heartbeat classification system. Therefore, a heartbeat classification system with a high performance evaluation possesses a strong predictive capability for unknown data. The aim of this study was to propose a method for inter-patient classification of heartbeats to accurately detect LBBB and RBBB from the normal beat (NORM). Methods This study proposed a heartbeat classification method through a combination of three different types of classifiers: a minimum distance classifier constructed between NORM and LBBB; a weighted linear discriminant classifier between NORM and RBBB based on Bayesian decision making using posterior probabilities; and a linear support vector machine (SVM) between LBBB and RBBB. Each classifier was used with matching features to obtain better classification performance. The final types of the test heartbeats were determined using a majority voting strategy through the combination of class labels from the three classifiers. The optimal parameters for the classifiers were selected using cross-validation on the training set. The effects of different lead configurations on the classification results were assessed, and the performance of these three classifiers was compared for the detection of each pair of heartbeat types. Results The study results showed that a two-lead configuration exhibited better classification results compared with a single-lead configuration. The construction of a classifier with good performance between each pair of heartbeat types significantly improved the heartbeat classification performance. The results showed a sensitivity of 91.4% and a positive predictive value of 37.3% for LBBB and a sensitivity of 92.8% and a positive predictive value of 88.8% for RBBB. Conclusions A multi-classifier ensemble method was proposed based on inter-patient data and demonstrated a satisfactory classification performance. This approach has the potential for application in clinical practice to distinguish LBBB and RBBB from NORM of unknown patients. PMID:24903422

Code Samples Used for Complexity and Control

NASA Astrophysics Data System (ADS)

Ivancevic, Vladimir G.; Reid, Darryn J.

2015-11-01

The following sections are included: * MathematicaⓇ Code * Generic Chaotic Simulator * Vector Differential Operators * NLS Explorer * 2C++ Code * C++ Lambda Functions for Real Calculus * Accelerometer Data Processor * Simple Predictor-Corrector Integrator * Solving the BVP with the Shooting Method * Linear Hyperbolic PDE Solver * Linear Elliptic PDE Solver * Method of Lines for a Set of the NLS Equations * C# Code * Iterative Equation Solver * Simulated Annealing: A Function Minimum * Simple Nonlinear Dynamics * Nonlinear Pendulum Simulator * Lagrangian Dynamics Simulator * Complex-Valued Crowd Attractor Dynamics * Freeform Fortran Code * Lorenz Attractor Simulator * Complex Lorenz Attractor * Simple SGE Soliton * Complex Signal Presentation * Gaussian Wave Packet * Hermitian Matrices * Euclidean L2-Norm * Vector/Matrix Operations * Plain C-Code: Levenberg-Marquardt Optimizer * Free Basic Code: 2D Crowd Dynamics with 3000 Agents

Joint L1 and Total Variation Regularization for Fluorescence Molecular Tomography

PubMed Central

Dutta, Joyita; Ahn, Sangtae; Li, Changqing; Cherry, Simon R.; Leahy, Richard M.

2012-01-01

Fluorescence molecular tomography (FMT) is an imaging modality that exploits the specificity of fluorescent biomarkers to enable 3D visualization of molecular targets and pathways in vivo in small animals. Owing to the high degree of absorption and scattering of light through tissue, the FMT inverse problem is inherently illconditioned making image reconstruction highly susceptible to the effects of noise and numerical errors. Appropriate priors or penalties are needed to facilitate reconstruction and to restrict the search space to a specific solution set. Typically, fluorescent probes are locally concentrated within specific areas of interest (e.g., inside tumors). The commonly used L2 norm penalty generates the minimum energy solution, which tends to be spread out in space. Instead, we present here an approach involving a combination of the L1 and total variation norm penalties, the former to suppress spurious background signals and enforce sparsity and the latter to preserve local smoothness and piecewise constancy in the reconstructed images. We have developed a surrogate-based optimization method for minimizing the joint penalties. The method was validated using both simulated and experimental data obtained from a mouse-shaped phantom mimicking tissue optical properties and containing two embedded fluorescent sources. Fluorescence data was collected using a 3D FMT setup that uses an EMCCD camera for image acquisition and a conical mirror for full-surface viewing. A range of performance metrics were utilized to evaluate our simulation results and to compare our method with the L1, L2, and total variation norm penalty based approaches. The experimental results were assessed using Dice similarity coefficients computed after co-registration with a CT image of the phantom. PMID:22390906

On the structure of critical energy levels for the cubic focusing NLS on star graphs

NASA Astrophysics Data System (ADS)

Adami, Riccardo; Cacciapuoti, Claudio; Finco, Domenico; Noja, Diego

2012-05-01

We provide information on a non-trivial structure of phase space of the cubic nonlinear Schrödinger (NLS) on a three-edge star graph. We prove that, in contrast to the case of the standard NLS on the line, the energy associated with the cubic focusing Schrödinger equation on the three-edge star graph with a free (Kirchhoff) vertex does not attain a minimum value on any sphere of constant L2-norm. We moreover show that the only stationary state with prescribed L2-norm is indeed a saddle point.

Regularized minimum I-divergence methods for the inverse blackbody radiation problem

NASA Astrophysics Data System (ADS)

Choi, Kerkil; Lanterman, Aaron D.; Shin, Jaemin

2006-08-01

This paper proposes iterative methods for estimating the area temperature distribution of a blackbody from its total radiated power spectrum measurements. This is called the inverse blackbody radiation problem. This problem is inherently ill-posed due to the characteristics of the kernel in the underlying integral equation given by Planck's law. The functions involved in the problem are all non-negative. Csiszár's I-divergence is an information-theoretic discrepancy measure between two non-negative functions. We derive iterative methods for minimizing Csiszár's I-divergence between the measured power spectrum and the power spectrum arising from the estimate according to the integral equation. Due to the ill-posedness of the problem, unconstrained algorithms often produce poor estimates, especially when the measurements are corrupted by noise. To alleviate this difficulty, we apply regularization methods to our algorithms. Penalties based on Shannon's entropy, the L1-norm and Good's roughness are chosen to suppress the undesirable artefacts. When a penalty is applied, the pertinent optimization that needs to be performed at each iteration is no longer trivial. In particular, Good's roughness causes couplings between estimate components. To handle this issue, we adapt Green's one-step-late method. This choice is based on the important fact that our minimum I-divergence algorithms can be interpreted as asymptotic forms of certain expectation-maximization algorithms. The effectiveness of our methods is illustrated via various numerical experiments.

Detection of inter-patient left and right bundle branch block heartbeats in ECG using ensemble classifiers.

PubMed

Huang, Huifang; Liu, Jie; Zhu, Qiang; Wang, Ruiping; Hu, Guangshu

2014-06-05

Left bundle branch block (LBBB) and right bundle branch block (RBBB) not only mask electrocardiogram (ECG) changes that reflect diseases but also indicate important underlying pathology. The timely detection of LBBB and RBBB is critical in the treatment of cardiac diseases. Inter-patient heartbeat classification is based on independent training and testing sets to construct and evaluate a heartbeat classification system. Therefore, a heartbeat classification system with a high performance evaluation possesses a strong predictive capability for unknown data. The aim of this study was to propose a method for inter-patient classification of heartbeats to accurately detect LBBB and RBBB from the normal beat (NORM). This study proposed a heartbeat classification method through a combination of three different types of classifiers: a minimum distance classifier constructed between NORM and LBBB; a weighted linear discriminant classifier between NORM and RBBB based on Bayesian decision making using posterior probabilities; and a linear support vector machine (SVM) between LBBB and RBBB. Each classifier was used with matching features to obtain better classification performance. The final types of the test heartbeats were determined using a majority voting strategy through the combination of class labels from the three classifiers. The optimal parameters for the classifiers were selected using cross-validation on the training set. The effects of different lead configurations on the classification results were assessed, and the performance of these three classifiers was compared for the detection of each pair of heartbeat types. The study results showed that a two-lead configuration exhibited better classification results compared with a single-lead configuration. The construction of a classifier with good performance between each pair of heartbeat types significantly improved the heartbeat classification performance. The results showed a sensitivity of 91.4% and a positive predictive value of 37.3% for LBBB and a sensitivity of 92.8% and a positive predictive value of 88.8% for RBBB. A multi-classifier ensemble method was proposed based on inter-patient data and demonstrated a satisfactory classification performance. This approach has the potential for application in clinical practice to distinguish LBBB and RBBB from NORM of unknown patients.

Mathematical models of the simplest fuzzy PI/PD controllers with skewed input and output fuzzy sets.

PubMed

Mohan, B M; Sinha, Arpita

2008-07-01

This paper unveils mathematical models for fuzzy PI/PD controllers which employ two skewed fuzzy sets for each of the two-input variables and three skewed fuzzy sets for the output variable. The basic constituents of these models are Gamma-type and L-type membership functions for each input, trapezoidal/triangular membership functions for output, intersection/algebraic product triangular norm, maximum/drastic sum triangular conorm, Mamdani minimum/Larsen product/drastic product inference method, and center of sums defuzzification method. The existing simplest fuzzy PI/PD controller structures derived via symmetrical fuzzy sets become special cases of the mathematical models revealed in this paper. Finally, a numerical example along with its simulation results are included to demonstrate the effectiveness of the simplest fuzzy PI controllers.

A z-gradient array for simultaneous multi-slice excitation with a single-band RF pulse.

PubMed

Ertan, Koray; Taraghinia, Soheil; Sadeghi, Alireza; Atalar, Ergin

2018-07-01

Multi-slice radiofrequency (RF) pulses have higher specific absorption rates, more peak RF power, and longer pulse durations than single-slice RF pulses. Gradient field design techniques using a z-gradient array are investigated for exciting multiple slices with a single-band RF pulse. Two different field design methods are formulated to solve for the required current values of the gradient array elements for the given slice locations. The method requirements are specified, optimization problems are formulated for the minimum current norm and an analytical solution is provided. A 9-channel z-gradient coil array driven by independent, custom-designed gradient amplifiers is used to validate the theory. Performance measures such as normalized slice thickness error, gradient strength per unit norm current, power dissipation, and maximum amplitude of the magnetic field are provided for various slice locations and numbers of slices. Two and 3 slices are excited by a single-band RF pulse in simulations and phantom experiments. The possibility of multi-slice excitation with a single-band RF pulse using a z-gradient array is validated in simulations and phantom experiments. Magn Reson Med 80:400-412, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

PubMed Central

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

PubMed

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

Adaptation to an extraordinary environment by evolution of phenotypic plasticity and genetic assimilation.

PubMed

Lande, Russell

2009-07-01

Adaptation to a sudden extreme change in environment, beyond the usual range of background environmental fluctuations, is analysed using a quantitative genetic model of phenotypic plasticity. Generations are discrete, with time lag tau between a critical period for environmental influence on individual development and natural selection on adult phenotypes. The optimum phenotype, and genotypic norms of reaction, are linear functions of the environment. Reaction norm elevation and slope (plasticity) vary among genotypes. Initially, in the average background environment, the character is canalized with minimum genetic and phenotypic variance, and no correlation between reaction norm elevation and slope. The optimal plasticity is proportional to the predictability of environmental fluctuations over time lag tau. During the first generation in the new environment the mean fitness suddenly drops and the mean phenotype jumps towards the new optimum phenotype by plasticity. Subsequent adaptation occurs in two phases. Rapid evolution of increased plasticity allows the mean phenotype to closely approach the new optimum. The new phenotype then undergoes slow genetic assimilation, with reduction in plasticity compensated by genetic evolution of reaction norm elevation in the original environment.

Comparison of imaging modalities and source-localization algorithms in locating the induced activity during deep brain stimulation of the STN.

PubMed

Mideksa, K G; Singh, A; Hoogenboom, N; Hellriegel, H; Krause, H; Schnitzler, A; Deuschl, G; Raethjen, J; Schmidt, G; Muthuraman, M

2016-08-01

One of the most commonly used therapy to treat patients with Parkinson's disease (PD) is deep brain stimulation (DBS) of the subthalamic nucleus (STN). Identifying the most optimal target area for the placement of the DBS electrodes have become one of the intensive research area. In this study, the first aim is to investigate the capabilities of different source-analysis techniques in detecting deep sources located at the sub-cortical level and validating it using the a-priori information about the location of the source, that is, the STN. Secondly, we aim at an investigation of whether EEG or MEG is best suited in mapping the DBS-induced brain activity. To do this, simultaneous EEG and MEG measurement were used to record the DBS-induced electromagnetic potentials and fields. The boundary-element method (BEM) have been used to solve the forward problem. The position of the DBS electrodes was then estimated using the dipole (moving, rotating, and fixed MUSIC), and current-density-reconstruction (CDR) (minimum-norm and sLORETA) approaches. The source-localization results from the dipole approaches demonstrated that the fixed MUSIC algorithm best localizes deep focal sources, whereas the moving dipole detects not only the region of interest but also neighboring regions that are affected by stimulating the STN. The results from the CDR approaches validated the capability of sLORETA in detecting the STN compared to minimum-norm. Moreover, the source-localization results using the EEG modality outperformed that of the MEG by locating the DBS-induced activity in the STN.

Fraction of exhaled nitric oxide (FeNO ) norms in healthy North African children 5-16 years old.

PubMed

Rouatbi, Sonia; Alqodwa, Ashraf; Ben Mdella, Samia; Ben Saad, Helmi

2013-10-01

(i) To identify factors that influence the FeNO values in healthy North African, Arab children aged 6-16 years; (ii) to test the applicability and reliability of the previously published FeNO norms; and (iii) if needed, to establish FeNO norms in this population, and to prospectively assess its reliability. This was a cross-sectional analytical study. A convenience sample of healthy Tunisian children, aged 6-16 years was recruited. First subjects have responded to two questionnaires, and then FeNO levels were measured by an online method with electrochemical analyzer (Medisoft, Sorinnes [Dinant], Belgium). Anthropometric and spirometric data were collected. Simple and a multiple linear regressions were determined. The 95% confidence interval (95% CI) and upper limit of normal (ULN) were defined. Two hundred eleven children (107 boys) were retained. Anthropometric data, gender, socioeconomic level, obesity or puberty status, and sports activity were not independent influencing variables. Total sample FeNO data appeared to be influenced only by maximum mid expiratory flow (l sec(-1) ; r(2)  = 0.0236, P = 0.0516). For boys, only 1st second forced expiratory volume (l) explains a slight (r(2)  = 0.0451) but significant FeNO variability (P = 0.0281). For girls, FeNO was not significantly correlated with any children determined data. For North African/Arab children, FeNO values were significantly lower than in other populations and the available published FeNO norms did not reliably predict FeNO in our population. The mean ± SD (95% CI ULN, minimum-maximum) of FeNO (ppb) for the total sample was 5.0 ± 2.9 (5.4, 1.0-17.0). For North African, Arab children of any age, any FeNO value greater than 17.0 ppb may be considered abnormal. Finally, in an additional group of children prospectively assessed, we found no child with a FeNO higher than 17.0 ppb. Our FeNO norms enrich the global repository of FeNO norms the pediatrician can use to choose the most appropriate norms based on children's location or ethnicity. © 2012 Wiley Periodicals, Inc.

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.

The use of portable equipment for the activity concentration index determination of building materials: method validation and survey of building materials on the Belgian market.

PubMed

Stals, M; Verhoeven, S; Bruggeman, M; Pellens, V; Schroeyers, W; Schreurs, S

2014-01-01

The Euratom BSS requires that in the near future (2015) the building materials for application in dwellings or buildings such as offices or workshops are screened for NORM nuclides. The screening tool is the activity concentration index (ACI). Therefore it is expected that a large number of building materials will be screened for NORM and thus require ACI determination. Nowadays, the proposed standard for determination of building material ACI is a laboratory analyses technique with high purity germanium spectrometry and 21 days equilibrium delay. In this paper, the B-NORM method for determination of building material ACI is assessed as a faster method that can be performed on-site, alternative to the aforementioned standard method. The B-NORM method utilizes a LaBr3(Ce) scintillation probe to obtain the spectral data. Commercially available software was applied to comprehensively take into account the factors determining the counting efficiency. The ACI was determined by interpreting the gamma spectrum from (226)Ra and its progeny; (232)Th progeny and (40)K. In order to assess the accuracy of the B-NORM method, a large selection of samples was analyzed by a certified laboratory and the results were compared with the B-NORM results. The results obtained with the B-NORM method were in good correlation with the results obtained by the certified laboratory, indicating that the B-NORM method is an appropriate screening method to assess building material ACI. The B-NORM method was applied to analyze more than 120 building materials on the Belgian market. No building materials that exceed the proposed reference level of 1 mSv/year were encountered. Copyright © 2013 Elsevier Ltd. All rights reserved.

Visual tracking based on the sparse representation of the PCA subspace

NASA Astrophysics Data System (ADS)

Chen, Dian-bing; Zhu, Ming; Wang, Hui-li

2017-09-01

We construct a collaborative model of the sparse representation and the subspace representation. First, we represent the tracking target in the principle component analysis (PCA) subspace, and then we employ an L 1 regularization to restrict the sparsity of the residual term, an L 2 regularization term to restrict the sparsity of the representation coefficients, and an L 2 norm to restrict the distance between the reconstruction and the target. Then we implement the algorithm in the particle filter framework. Furthermore, an iterative method is presented to get the global minimum of the residual and the coefficients. Finally, an alternative template update scheme is adopted to avoid the tracking drift which is caused by the inaccurate update. In the experiment, we test the algorithm on 9 sequences, and compare the results with 5 state-of-art methods. According to the results, we can conclude that our algorithm is more robust than the other methods.

Demographically corrected norms for the Brief Visuospatial Memory Test-revised and Hopkins Verbal Learning Test-revised in monolingual Spanish speakers from the U.S.-Mexico border region.

PubMed

Cherner, M; Suarez, P; Lazzaretto, D; Fortuny, L Artiola I; Mindt, Monica Rivera; Dawes, S; Marcotte, Thomas; Grant, I; Heaton, R

2007-03-01

The large number of primary Spanish speakers both in the United States and the world makes it imperative that appropriate neuropsychological assessment instruments be available to serve the needs of these populations. In this article we describe the norming process for Spanish speakers from the U.S.-Mexico border region on the Brief Visuospatial Memory Test-revised and the Hopkins Verbal Learning Test-revised. We computed the rates of impairment that would be obtained by applying the original published norms for these tests to raw scores from the normative sample, and found substantial overestimates compared to expected rates. As expected, these overestimates were most salient at the lowest levels of education, given the under-representation of poorly educated subjects in the original normative samples. Results suggest that demographically corrected norms derived from healthy Spanish-speaking adults with a broad range of education, are less likely to result in diagnostic errors. At minimum, demographic corrections for the tests in question should include the influence of literacy or education, in addition to the traditional adjustments for age. Because the age range of our sample was limited, the norms presented should not be applied to elderly populations.

Robust Principal Component Analysis Regularized by Truncated Nuclear Norm for Identifying Differentially Expressed Genes.

PubMed

Wang, Ya-Xuan; Gao, Ying-Lian; Liu, Jin-Xing; Kong, Xiang-Zhen; Li, Hai-Jun

2017-09-01

Identifying differentially expressed genes from the thousands of genes is a challenging task. Robust principal component analysis (RPCA) is an efficient method in the identification of differentially expressed genes. RPCA method uses nuclear norm to approximate the rank function. However, theoretical studies showed that the nuclear norm minimizes all singular values, so it may not be the best solution to approximate the rank function. The truncated nuclear norm is defined as the sum of some smaller singular values, which may achieve a better approximation of the rank function than nuclear norm. In this paper, a novel method is proposed by replacing nuclear norm of RPCA with the truncated nuclear norm, which is named robust principal component analysis regularized by truncated nuclear norm (TRPCA). The method decomposes the observation matrix of genomic data into a low-rank matrix and a sparse matrix. Because the significant genes can be considered as sparse signals, the differentially expressed genes are viewed as the sparse perturbation signals. Thus, the differentially expressed genes can be identified according to the sparse matrix. The experimental results on The Cancer Genome Atlas data illustrate that the TRPCA method outperforms other state-of-the-art methods in the identification of differentially expressed genes.

The roles of outlet density and norms in alcohol use disorder.

PubMed

Ahern, Jennifer; Balzer, Laura; Galea, Sandro

2015-06-01

Alcohol outlet density and norms shape alcohol consumption. However, due to analytic challenges we do not know: (a) if alcohol outlet density and norms also shape alcohol use disorder, and (b) whether they act in combination to shape disorder. We applied a new targeted minimum loss-based estimator for rare outcomes (rTMLE) to a general population sample from New York City (N = 4000) to examine the separate and combined relations of neighborhood alcohol outlet density and norms around drunkenness with alcohol use disorder. Alcohol use disorder was assessed using the World Mental Health Comprehensive International Diagnostic Interview (WMH-CIDI) alcohol module. Confounders included demographic and socioeconomic characteristics, as well as history of drinking prior to residence in the current neighborhood. Alcohol use disorder prevalence was 1.78%. We found a marginal risk difference for alcohol outlet density of 0.88% (95% CI 0.00-1.77%), and for norms of 2.05% (95% CI 0.89-3.21%), adjusted for confounders. While each exposure had a substantial relation with alcohol use disorder, there was no evidence of additive interaction between the exposures. Results indicate that the neighborhood environment shapes alcohol use disorder. Despite the lack of additive interaction, each exposure had a substantial relation with alcohol use disorder and our findings suggest that alteration of outlet density and norms together would likely be more effective than either one alone. Important next steps include development and testing of multi-component intervention approaches aiming to modify alcohol outlet density and norms toward reducing alcohol use disorder. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM☆

PubMed Central

López, J.D.; Litvak, V.; Espinosa, J.J.; Friston, K.; Barnes, G.R.

2014-01-01

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy—an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. PMID:24041874

The impact of initialization procedures on unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization

NASA Astrophysics Data System (ADS)

Masalmah, Yahya M.; Vélez-Reyes, Miguel

2007-04-01

The authors proposed in previous papers the use of the constrained Positive Matrix Factorization (cPMF) to perform unsupervised unmixing of hyperspectral imagery. Two iterative algorithms were proposed to compute the cPMF based on the Gauss-Seidel and penalty approaches to solve optimization problems. Results presented in previous papers have shown the potential of the proposed method to perform unsupervised unmixing in HYPERION and AVIRIS imagery. The performance of iterative methods is highly dependent on the initialization scheme. Good initialization schemes can improve convergence speed, whether or not a global minimum is found, and whether or not spectra with physical relevance are retrieved as endmembers. In this paper, different initializations using random selection, longest norm pixels, and standard endmembers selection routines are studied and compared using simulated and real data.

Efficient l1 -norm-based low-rank matrix approximations for large-scale problems using alternating rectified gradient method.

PubMed

Kim, Eunwoo; Lee, Minsik; Choi, Chong-Ho; Kwak, Nojun; Oh, Songhwai

2015-02-01

Low-rank matrix approximation plays an important role in the area of computer vision and image processing. Most of the conventional low-rank matrix approximation methods are based on the l2 -norm (Frobenius norm) with principal component analysis (PCA) being the most popular among them. However, this can give a poor approximation for data contaminated by outliers (including missing data), because the l2 -norm exaggerates the negative effect of outliers. Recently, to overcome this problem, various methods based on the l1 -norm, such as robust PCA methods, have been proposed for low-rank matrix approximation. Despite the robustness of the methods, they require heavy computational effort and substantial memory for high-dimensional data, which is impractical for real-world problems. In this paper, we propose two efficient low-rank factorization methods based on the l1 -norm that find proper projection and coefficient matrices using the alternating rectified gradient method. The proposed methods are applied to a number of low-rank matrix approximation problems to demonstrate their efficiency and robustness. The experimental results show that our proposals are efficient in both execution time and reconstruction performance unlike other state-of-the-art methods.

Selection and testing of reference genes for accurate RT-qPCR in rice seedlings under iron toxicity.

PubMed

Santos, Fabiane Igansi de Castro Dos; Marini, Naciele; Santos, Railson Schreinert Dos; Hoffman, Bianca Silva Fernandes; Alves-Ferreira, Marcio; de Oliveira, Antonio Costa

2018-01-01

Reverse Transcription quantitative PCR (RT-qPCR) is a technique for gene expression profiling with high sensibility and reproducibility. However, to obtain accurate results, it depends on data normalization by using endogenous reference genes whose expression is constitutive or invariable. Although the technique is widely used in plant stress analyzes, the stability of reference genes for iron toxicity in rice (Oryza sativa L.) has not been thoroughly investigated. Here, we tested a set of candidate reference genes for use in rice under this stressful condition. The test was performed using four distinct methods: NormFinder, BestKeeper, geNorm and the comparative ΔCt. To achieve reproducible and reliable results, Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines were followed. Valid reference genes were found for shoot (P2, OsGAPDH and OsNABP), root (OsEF-1a, P8 and OsGAPDH) and root+shoot (OsNABP, OsGAPDH and P8) enabling us to perform further reliable studies for iron toxicity in both indica and japonica subspecies. The importance of the study of other than the traditional endogenous genes for use as normalizers is also shown here.

Selection and testing of reference genes for accurate RT-qPCR in rice seedlings under iron toxicity

PubMed Central

dos Santos, Fabiane Igansi de Castro; Marini, Naciele; dos Santos, Railson Schreinert; Hoffman, Bianca Silva Fernandes; Alves-Ferreira, Marcio

2018-01-01

Reverse Transcription quantitative PCR (RT-qPCR) is a technique for gene expression profiling with high sensibility and reproducibility. However, to obtain accurate results, it depends on data normalization by using endogenous reference genes whose expression is constitutive or invariable. Although the technique is widely used in plant stress analyzes, the stability of reference genes for iron toxicity in rice (Oryza sativa L.) has not been thoroughly investigated. Here, we tested a set of candidate reference genes for use in rice under this stressful condition. The test was performed using four distinct methods: NormFinder, BestKeeper, geNorm and the comparative ΔCt. To achieve reproducible and reliable results, Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines were followed. Valid reference genes were found for shoot (P2, OsGAPDH and OsNABP), root (OsEF-1a, P8 and OsGAPDH) and root+shoot (OsNABP, OsGAPDH and P8) enabling us to perform further reliable studies for iron toxicity in both indica and japonica subspecies. The importance of the study of other than the traditional endogenous genes for use as normalizers is also shown here. PMID:29494624

Using Structural Equation Modeling to Assess Functional Connectivity in the Brain: Power and Sample Size Considerations

ERIC Educational Resources Information Center

Sideridis, Georgios; Simos, Panagiotis; Papanicolaou, Andrew; Fletcher, Jack

2014-01-01

The present study assessed the impact of sample size on the power and fit of structural equation modeling applied to functional brain connectivity hypotheses. The data consisted of time-constrained minimum norm estimates of regional brain activity during performance of a reading task obtained with magnetoencephalography. Power analysis was first…

A Truncated Nuclear Norm Regularization Method Based on Weighted Residual Error for Matrix Completion.

PubMed

Qing Liu; Zhihui Lai; Zongwei Zhou; Fangjun Kuang; Zhong Jin

2016-01-01

Low-rank matrix completion aims to recover a matrix from a small subset of its entries and has received much attention in the field of computer vision. Most existing methods formulate the task as a low-rank matrix approximation problem. A truncated nuclear norm has recently been proposed as a better approximation to the rank of matrix than a nuclear norm. The corresponding optimization method, truncated nuclear norm regularization (TNNR), converges better than the nuclear norm minimization-based methods. However, it is not robust to the number of subtracted singular values and requires a large number of iterations to converge. In this paper, a TNNR method based on weighted residual error (TNNR-WRE) for matrix completion and its extension model (ETNNR-WRE) are proposed. TNNR-WRE assigns different weights to the rows of the residual error matrix in an augmented Lagrange function to accelerate the convergence of the TNNR method. The ETNNR-WRE is much more robust to the number of subtracted singular values than the TNNR-WRE, TNNR alternating direction method of multipliers, and TNNR accelerated proximal gradient with Line search methods. Experimental results using both synthetic and real visual data sets show that the proposed TNNR-WRE and ETNNR-WRE methods perform better than TNNR and Iteratively Reweighted Nuclear Norm (IRNN) methods.

Inversion of Magnetic Measurements of the CHAMP Satellite Over the Pannonian Basin

NASA Technical Reports Server (NTRS)

Kis, K. I.; Taylor, P. T.; Wittmann, G.; Toronyi, B.; Puszta, S.

2011-01-01

The Pannonian Basin is a deep intra-continental basin that formed as part of the Alpine orogeny. In order to study the nature of the crustal basement we used the long-wavelength magnetic anomalies acquired by the CHAMP satellite. The anomalies were distributed in a spherical shell, some 107,927 data recorded between January 1 and December 31 of 2008. They covered the Pannonian Basin and its vicinity. These anomaly data were interpolated into a spherical grid of 0.5 x 0.5, at the elevation of 324 km by the Gaussian weight function. The vertical gradient of these total magnetic anomalies was also computed and mapped to the surface of a sphere at 324 km elevation. The former spherical anomaly data at 425 km altitude were downward continued to 324 km. To interpret these data at the elevation of 324 km we used an inversion method. A polygonal prism forward model was used for the inversion. The minimum problem was solved numerically by the Simplex and Simulated annealing methods; a L2 norm in the case of Gaussian distribution parameters and a L1 norm was used in the case of Laplace distribution parameters. We INTERPRET THAT the magnetic anomaly WAS produced by several sources and the effect of the sable magnetization of the exsolution of hemo-ilmenite minerals in the upper crustal metamorphic rocks.

Robust cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain dynamics

NASA Astrophysics Data System (ADS)

Li, Keqiang; Gao, Feng; Li, Shengbo Eben; Zheng, Yang; Gao, Hongbo

2017-12-01

This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range.With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.

Simultaneous travel time tomography for updating both velocity and reflector geometry in triangular/tetrahedral cell model

NASA Astrophysics Data System (ADS)

Bai, Chao-ying; He, Lei-yu; Li, Xing-wang; Sun, Jia-yu

2018-05-01

To conduct forward and simultaneous inversion in a complex geological model, including an irregular topography (or irregular reflector or velocity anomaly), we in this paper combined our previous multiphase arrival tracking method (referred as triangular shortest-path method, TSPM) in triangular (2D) or tetrahedral (3D) cell model and a linearized inversion solver (referred to as damped minimum norms and constrained least squares problem solved using the conjugate gradient method, DMNCLS-CG) to formulate a simultaneous travel time inversion method for updating both velocity and reflector geometry by using multiphase arrival times. In the triangular/tetrahedral cells, we deduced the partial derivative of velocity variation with respective to the depth change of reflector. The numerical simulation results show that the computational accuracy can be tuned to a high precision in forward modeling and the irregular velocity anomaly and reflector geometry can be accurately captured in the simultaneous inversion, because the triangular/tetrahedral cell can be easily used to stitch the irregular topography or subsurface interface.

Simultaneous travel time tomography for updating both velocity and reflector geometry in triangular/tetrahedral cell model

NASA Astrophysics Data System (ADS)

Bai, Chao-ying; He, Lei-yu; Li, Xing-wang; Sun, Jia-yu

2017-12-01

To conduct forward and simultaneous inversion in a complex geological model, including an irregular topography (or irregular reflector or velocity anomaly), we in this paper combined our previous multiphase arrival tracking method (referred as triangular shortest-path method, TSPM) in triangular (2D) or tetrahedral (3D) cell model and a linearized inversion solver (referred to as damped minimum norms and constrained least squares problem solved using the conjugate gradient method, DMNCLS-CG) to formulate a simultaneous travel time inversion method for updating both velocity and reflector geometry by using multiphase arrival times. In the triangular/tetrahedral cells, we deduced the partial derivative of velocity variation with respective to the depth change of reflector. The numerical simulation results show that the computational accuracy can be tuned to a high precision in forward modeling and the irregular velocity anomaly and reflector geometry can be accurately captured in the simultaneous inversion, because the triangular/tetrahedral cell can be easily used to stitch the irregular topography or subsurface interface.

Generalizations of Tikhonov's regularized method of least squares to non-Euclidean vector norms

NASA Astrophysics Data System (ADS)

Volkov, V. V.; Erokhin, V. I.; Kakaev, V. V.; Onufrei, A. Yu.

2017-09-01

Tikhonov's regularized method of least squares and its generalizations to non-Euclidean norms, including polyhedral, are considered. The regularized method of least squares is reduced to mathematical programming problems obtained by "instrumental" generalizations of the Tikhonov lemma on the minimal (in a certain norm) solution of a system of linear algebraic equations with respect to an unknown matrix. Further studies are needed for problems concerning the development of methods and algorithms for solving reduced mathematical programming problems in which the objective functions and admissible domains are constructed using polyhedral vector norms.

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,…

Local descriptive body weight and dietary norms, food availability, and 10-year change in glycosylated haemoglobin in an Australian population-based biomedical cohort.

PubMed

Carroll, Suzanne J; Paquet, Catherine; Howard, Natasha J; Coffee, Neil T; Adams, Robert J; Taylor, Anne W; Niyonsenga, Theo; Daniel, Mark

2017-02-02

Individual-level health outcomes are shaped by environmental risk conditions. Norms figure prominently in socio-behavioural theories yet spatial variations in health-related norms have rarely been investigated as environmental risk conditions. This study assessed: 1) the contributions of local descriptive norms for overweight/obesity and dietary behaviour to 10-year change in glycosylated haemoglobin (HbA 1c ), accounting for food resource availability; and 2) whether associations between local descriptive norms and HbA 1c were moderated by food resource availability. HbA 1c , representing cardiometabolic risk, was measured three times over 10 years for a population-based biomedical cohort of adults in Adelaide, South Australia. Residential environmental exposures were defined using 1600 m participant-centred road-network buffers. Local descriptive norms for overweight/obesity and insufficient fruit intake (proportion of residents with BMI ≥ 25 kg/m 2 [n = 1890] or fruit intake of <2 serves/day [n = 1945], respectively) were aggregated from responses to a separate geocoded population survey. Fast-food and healthful food resource availability (counts) were extracted from a retail database. Separate sets of multilevel models included different predictors, one local descriptive norm and either fast-food or healthful food resource availability, with area-level education and individual-level covariates (age, sex, employment status, education, marital status, and smoking status). Interactions between local descriptive norms and food resource availability were tested. HbA 1c concentration rose over time. Local descriptive norms for overweight/obesity and insufficient fruit intake predicted greater rates of increase in HbA 1c . Neither fast-food nor healthful food resource availability were associated with change in HbA 1c . Greater healthful food resource availability reduced the rate of increase in HbA 1c concentration attributed to the overweight/obesity norm. Local descriptive health-related norms, not food resource availability, predicted 10-year change in HbA 1c . Null findings for food resource availability may reflect a sufficiency or minimum threshold level of resources such that availability poses no barrier to obtaining healthful or unhealthful foods for this region. However, the influence of local descriptive norms varied according to food resource availability in effects on HbA 1c . Local descriptive health-related norms have received little attention thus far but are important influences on individual cardiometabolic risk. Further research is needed to explore how local descriptive norms contribute to chronic disease risk and outcomes.

MNE software for processing MEG and EEG data

PubMed Central

Gramfort, A.; Luessi, M.; Larson, E.; Engemann, D.; Strohmeier, D.; Brodbeck, C.; Parkkonen, L.; Hämäläinen, M.

2013-01-01

Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time–frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne. PMID:24161808

Diallel analysis for sex-linked and maternal effects.

PubMed

Zhu, J; Weir, B S

1996-01-01

Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

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.;

An Improved Measure of Cognitive Salience in Free Listing Tasks: A Marshallese Example

ERIC Educational Resources Information Center

Robbins, Michael C.; Nolan, Justin M.; Chen, Diana

2017-01-01

A new free-list measure of cognitive salience, B', is presented, which includes both list position and list frequency. It surpasses other extant measures by being normed to vary between a maximum of 1 and a minimum of 0, thereby making it useful for comparisons irrespective of list length or number of respondents. An illustration of its…

Determining genetic erosion in fourteen Picea chihuahuana Martínez populations.

Treesearch

C.Z. Quiñones-Pérez; C. Wehenkel

2017-01-01

Picea chihuahuana is an endemic species in Mexico and is considered endangered, according to the Mexican Official Norm (NOM-ECOL-059-2010). This species covers a total area of no more than 300 ha located in at least 40 sites along the Sierra Madre Occidental in Durango and Chihuahua states. A minimum of 42,600 individuals has been estimated,...

Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM.

PubMed

López, J D; Litvak, V; Espinosa, J J; Friston, K; Barnes, G R

2014-01-01

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy-an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. © 2013. Published by Elsevier Inc. All rights reserved.

Variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction

NASA Astrophysics Data System (ADS)

Li, Shuo; Wang, Hui; Wang, Liyong; Yu, Xiangzhou; Yang, Le

2018-01-01

The uneven illumination phenomenon reduces the quality of remote sensing image and causes interference in the subsequent processing and applications. A variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction is proposed. The L1 norm and the L2 norm are adopted to constrain the textures and details of reflectance image and the smoothness of the illumination image, respectively. The problem of separating the illumination image from the reflectance image is transformed into the optimal solution of the variational model. In order to accelerate the solution, the split Bregman method is used to decompose the variational model into three subproblems, which are calculated by alternate iteration. Two groups of experiments are implemented on two synthetic images and three real remote sensing images. Compared with the variational Retinex method with single-norm constraint and the Mask method, the proposed method performs better in both visual evaluation and quantitative measurements. The proposed method can effectively eliminate the uneven illumination while maintaining the textures and details of the remote sensing image. Moreover, the proposed method using split Bregman method is more than 10 times faster than the method with the steepest descent method.

On epicardial potential reconstruction using regularization schemes with the L1-norm data term.

PubMed

Shou, Guofa; Xia, Ling; Liu, Feng; Jiang, Mingfeng; Crozier, Stuart

2011-01-07

The electrocardiographic (ECG) inverse problem is ill-posed and usually solved by regularization schemes. These regularization methods, such as the Tikhonov method, are often based on the L2-norm data and constraint terms. However, L2-norm-based methods inherently provide smoothed inverse solutions that are sensitive to measurement errors, and also lack the capability of localizing and distinguishing multiple proximal cardiac electrical sources. This paper presents alternative regularization schemes employing the L1-norm data term for the reconstruction of epicardial potentials (EPs) from measured body surface potentials (BSPs). During numerical implementation, the iteratively reweighted norm algorithm was applied to solve the L1-norm-related schemes, and measurement noises were considered in the BSP data. The proposed L1-norm data term-based regularization schemes (with L1 and L2 penalty terms of the normal derivative constraint (labelled as L1TV and L1L2)) were compared with the L2-norm data terms (Tikhonov with zero-order and normal derivative constraints, labelled as ZOT and FOT, and the total variation method labelled as L2TV). The studies demonstrated that, with averaged measurement noise, the inverse solutions provided by the L1L2 and FOT algorithms have less relative error values. However, when larger noise occurred in some electrodes (for example, signal lost during measurement), the L1TV and L1L2 methods can obtain more accurate EPs in a robust manner. Therefore the L1-norm data term-based solutions are generally less perturbed by measurement noises, suggesting that the new regularization scheme is promising for providing practical ECG inverse solutions.

Nuclear norm-based 2-DPCA for extracting features from images.

PubMed

Zhang, Fanlong; Yang, Jian; Qian, Jianjun; Xu, Yong

2015-10-01

The 2-D principal component analysis (2-DPCA) is a widely used method for image feature extraction. However, it can be equivalently implemented via image-row-based principal component analysis. This paper presents a structured 2-D method called nuclear norm-based 2-DPCA (N-2-DPCA), which uses a nuclear norm-based reconstruction error criterion. The nuclear norm is a matrix norm, which can provide a structured 2-D characterization for the reconstruction error image. The reconstruction error criterion is minimized by converting the nuclear norm-based optimization problem into a series of F-norm-based optimization problems. In addition, N-2-DPCA is extended to a bilateral projection-based N-2-DPCA (N-B2-DPCA). The virtue of N-B2-DPCA over N-2-DPCA is that an image can be represented with fewer coefficients. N-2-DPCA and N-B2-DPCA are applied to face recognition and reconstruction and evaluated using the Extended Yale B, CMU PIE, FRGC, and AR databases. Experimental results demonstrate the effectiveness of the proposed methods.

Selection and Validation of Appropriate Reference Genes for qRT-PCR Analysis in Isatis indigotica Fort.

PubMed Central

Li, Tao; Wang, Jing; Lu, Miao; Zhang, Tianyi; Qu, Xinyun; Wang, Zhezhi

2017-01-01

Due to its sensitivity and specificity, real-time quantitative PCR (qRT-PCR) is a popular technique for investigating gene expression levels in plants. Based on the Minimum Information for Publication of Real-Time Quantitative PCR Experiments (MIQE) guidelines, it is necessary to select and validate putative appropriate reference genes for qRT-PCR normalization. In the current study, three algorithms, geNorm, NormFinder, and BestKeeper, were applied to assess the expression stability of 10 candidate reference genes across five different tissues and three different abiotic stresses in Isatis indigotica Fort. Additionally, the IiYUC6 gene associated with IAA biosynthesis was applied to validate the candidate reference genes. The analysis results of the geNorm, NormFinder, and BestKeeper algorithms indicated certain differences for the different sample sets and different experiment conditions. Considering all of the algorithms, PP2A-4 and TUB4 were recommended as the most stable reference genes for total and different tissue samples, respectively. Moreover, RPL15 and PP2A-4 were considered to be the most suitable reference genes for abiotic stress treatments. The obtained experimental results might contribute to improved accuracy and credibility for the expression levels of target genes by qRT-PCR normalization in I. indigotica. PMID:28702046

Chromotomography for a rotating-prism instrument using backprojection, then filtering.

PubMed

Deming, Ross W

2006-08-01

A simple closed-form solution is derived for reconstructing a 3D spatial-chromatic image cube from a set of chromatically dispersed 2D image frames. The algorithm is tailored for a particular instrument in which the dispersion element is a matching set of mechanically rotated direct vision prisms positioned between a lens and a focal plane array. By using a linear operator formalism to derive the Tikhonov-regularized pseudoinverse operator, it is found that the unique minimum-norm solution is obtained by applying the adjoint operator, followed by 1D filtering with respect to the chromatic variable. Thus the filtering and backprojection (adjoint) steps are applied in reverse order relative to an existing method. Computational efficiency is provided by use of the fast Fourier transform in the filtering step.

EEG minimum-norm estimation compared with MEG dipole fitting in the localization of somatosensory sources at S1.

PubMed

Komssi, S; Huttunen, J; Aronen, H J; Ilmoniemi, R J

2004-03-01

Dipole models, which are frequently used in attempts to solve the electromagnetic inverse problem, require explicit a priori assumptions about the cerebral current sources. This is not the case for solutions based on minimum-norm estimates. In the present study, we evaluated the spatial accuracy of the L2 minimum-norm estimate (MNE) in realistic noise conditions by assessing its ability to localize sources of evoked responses at the primary somatosensory cortex (SI). Multichannel somatosensory evoked potentials (SEPs) and magnetic fields (SEFs) were recorded in 5 subjects while stimulating the median and ulnar nerves at the left wrist. A Tikhonov-regularized L2-MNE, constructed on a spherical surface from the SEP signals, was compared with an equivalent current dipole (ECD) solution obtained from the SEFs. Primarily tangential current sources accounted for both SEP and SEF distributions at around 20 ms (N20/N20m) and 70 ms (P70/P70m), which deflections were chosen for comparative analysis. The distances between the locations of the maximum current densities obtained from MNE and the locations of ECDs were on the average 12-13 mm for both deflections and nerves stimulated. In accordance with the somatotopical order of SI, both the MNE and ECD tended to localize median nerve activation more laterally than ulnar nerve activation for the N20/N20m deflection. Simulation experiments further indicated that, with a proper estimate of the source depth and with a good fit of the head model, the MNE can reach a mean accuracy of 5 mm in 0.2-microV root-mean-square noise. When compared with previously reported localizations based on dipole modelling of SEPs, it appears that equally accurate localization of S1 can be obtained with the MNE. MNE can be used to verify parametric source modelling results. Having a relatively good localization accuracy and requiring minimal assumptions, the MNE may be useful for the localization of poorly known activity distributions and for tracking activity changes between brain areas as a function of time.

Analysis of programming properties and the row-column generation method for 1-norm support vector machines.

PubMed

Zhang, Li; Zhou, WeiDa

2013-12-01

This paper deals with fast methods for training a 1-norm support vector machine (SVM). First, we define a specific class of linear programming with many sparse constraints, i.e., row-column sparse constraint linear programming (RCSC-LP). In nature, the 1-norm SVM is a sort of RCSC-LP. In order to construct subproblems for RCSC-LP and solve them, a family of row-column generation (RCG) methods is introduced. RCG methods belong to a category of decomposition techniques, and perform row and column generations in a parallel fashion. Specially, for the 1-norm SVM, the maximum size of subproblems of RCG is identical with the number of Support Vectors (SVs). We also introduce a semi-deleting rule for RCG methods and prove the convergence of RCG methods when using the semi-deleting rule. Experimental results on toy data and real-world datasets illustrate that it is efficient to use RCG to train the 1-norm SVM, especially in the case of small SVs. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Sparse filtering with the generalized lp/lq norm and its applications to the condition monitoring of rotating machinery

NASA Astrophysics Data System (ADS)

Jia, Xiaodong; Zhao, Ming; Di, Yuan; Li, Pin; Lee, Jay

2018-03-01

Sparsity is becoming a more and more important topic in the area of machine learning and signal processing recently. One big family of sparse measures in current literature is the generalized lp /lq norm, which is scale invariant and is widely regarded as normalized lp norm. However, the characteristics of the generalized lp /lq norm are still less discussed and its application to the condition monitoring of rotating devices has been still unexplored. In this study, we firstly discuss the characteristics of the generalized lp /lq norm for sparse optimization and then propose a method of sparse filtering with the generalized lp /lq norm for the purpose of impulsive signature enhancement. Further driven by the trend of industrial big data and the need of reducing maintenance cost for industrial equipment, the proposed sparse filter is customized for vibration signal processing and also implemented on bearing and gearbox for the purpose of condition monitoring. Based on the results from the industrial implementations in this paper, the proposed method has been found to be a promising tool for impulsive feature enhancement, and the superiority of the proposed method over previous methods is also demonstrated.

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.

Application of L1-norm regularization to epicardial potential reconstruction based on gradient projection.

PubMed

Wang, Liansheng; Qin, Jing; Wong, Tien Tsin; Heng, Pheng Ann

2011-10-07

The epicardial potential (EP)-targeted inverse problem of electrocardiography (ECG) has been widely investigated as it is demonstrated that EPs reflect underlying myocardial activity. It is a well-known ill-posed problem as small noises in input data may yield a highly unstable solution. Traditionally, L2-norm regularization methods have been proposed to solve this ill-posed problem. But the L2-norm penalty function inherently leads to considerable smoothing of the solution, which reduces the accuracy of distinguishing abnormalities and locating diseased regions. Directly using the L1-norm penalty function, however, may greatly increase computational complexity due to its non-differentiability. We propose an L1-norm regularization method in order to reduce the computational complexity and make rapid convergence possible. Variable splitting is employed to make the L1-norm penalty function differentiable based on the observation that both positive and negative potentials exist on the epicardial surface. Then, the inverse problem of ECG is further formulated as a bound-constrained quadratic problem, which can be efficiently solved by gradient projection in an iterative manner. Extensive experiments conducted on both synthetic data and real data demonstrate that the proposed method can handle both measurement noise and geometry noise and obtain more accurate results than previous L2- and L1-norm regularization methods, especially when the noises are large.

Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications.

PubMed

Shang, Fanhua; Cheng, James; Liu, Yuanyuan; Luo, Zhi-Quan; Lin, Zhouchen

2017-09-04

The heavy-tailed distributions of corrupted outliers and singular values of all channels in low-level vision have proven effective priors for many applications such as background modeling, photometric stereo and image alignment. And they can be well modeled by a hyper-Laplacian. However, the use of such distributions generally leads to challenging non-convex, non-smooth and non-Lipschitz problems, and makes existing algorithms very slow for large-scale applications. Together with the analytic solutions to Lp-norm minimization with two specific values of p, i.e., p=1/2 and p=2/3, we propose two novel bilinear factor matrix norm minimization models for robust principal component analysis. We first define the double nuclear norm and Frobenius/nuclear hybrid norm penalties, and then prove that they are in essence the Schatten-1/2 and 2/3 quasi-norms, respectively, which lead to much more tractable and scalable Lipschitz optimization problems. Our experimental analysis shows that both our methods yield more accurate solutions than original Schatten quasi-norm minimization, even when the number of observations is very limited. Finally, we apply our penalties to various low-level vision problems, e.g. moving object detection, image alignment and inpainting, and show that our methods usually outperform the state-of-the-art methods.

Norm overlap between many-body states: Uncorrelated overlap between arbitrary Bogoliubov product states

NASA Astrophysics Data System (ADS)

Bally, B.; Duguet, T.

2018-02-01

Background: State-of-the-art multi-reference energy density functional calculations require the computation of norm overlaps between different Bogoliubov quasiparticle many-body states. It is only recently that the efficient and unambiguous calculation of such norm kernels has become available under the form of Pfaffians [L. M. Robledo, Phys. Rev. C 79, 021302 (2009), 10.1103/PhysRevC.79.021302]. Recently developed particle-number-restored Bogoliubov coupled-cluster (PNR-BCC) and particle-number-restored Bogoliubov many-body perturbation (PNR-BMBPT) ab initio theories [T. Duguet and A. Signoracci, J. Phys. G 44, 015103 (2017), 10.1088/0954-3899/44/1/015103] make use of generalized norm kernels incorporating explicit many-body correlations. In PNR-BCC and PNR-BMBPT, the Bogoliubov states involved in the norm kernels differ specifically via a global gauge rotation. Purpose: The goal of this work is threefold. We wish (i) to propose and implement an alternative to the Pfaffian method to compute unambiguously the norm overlap between arbitrary Bogoliubov quasiparticle states, (ii) to extend the first point to explicitly correlated norm kernels, and (iii) to scrutinize the analytical content of the correlated norm kernels employed in PNR-BMBPT. Point (i) constitutes the purpose of the present paper while points (ii) and (iii) are addressed in a forthcoming paper. Methods: We generalize the method used in another work [T. Duguet and A. Signoracci, J. Phys. G 44, 015103 (2017), 10.1088/0954-3899/44/1/015103] in such a way that it is applicable to kernels involving arbitrary pairs of Bogoliubov states. The formalism is presently explicated in detail in the case of the uncorrelated overlap between arbitrary Bogoliubov states. The power of the method is numerically illustrated and benchmarked against known results on the basis of toy models of increasing complexity. Results: The norm overlap between arbitrary Bogoliubov product states is obtained under a closed-form expression allowing its computation without any phase ambiguity. The formula is physically intuitive, accurate, and versatile. It equally applies to norm overlaps between Bogoliubov states of even or odd number parity. Numerical applications illustrate these features and provide a transparent representation of the content of the norm overlaps. Conclusions: The complex norm overlap between arbitrary Bogoliubov states is computed, without any phase ambiguity, via elementary linear algebra operations. The method can be used in any configuration mixing of orthogonal and non-orthogonal product states. Furthermore, the closed-form expression extends naturally to correlated overlaps at play in PNR-BCC and PNR-BMBPT. As such, the straight overlap between Bogoliubov states is the zero-order reduction of more involved norm kernels to be studied in a forthcoming paper.

When Do Laws Matter? National Minimum-Age-of-Marriage Laws, Child Rights, and Adolescent Fertility, 1989–2007

PubMed Central

Kim, Minzee; Longhofer, Wesley; Boyle, Elizabeth Heger; Nyseth, Hollie

2014-01-01

Using the case of adolescent fertility, we ask the questions of whether and when national laws have an effect on outcomes above and beyond the effects of international law and global organizing. To answer these questions, we utilize a fixed-effect time-series regression model to analyze the impact of minimum-age-of-marriage laws in 115 poor- and middle-income countries from 1989 to 2007. We find that countries with strict laws setting the minimum age of marriage at 18 experienced the most dramatic decline in rates of adolescent fertility. Trends in countries that set this age at 18 but allowed exceptions (for example, marriage with parental consent) were indistinguishable from countries that had no such minimum-age-of-marriage law. Thus, policies that adhere strictly to global norms are more likely to elicit desired outcomes. The article concludes with a discussion of what national law means in a diffuse global system where multiple actors and institutions make the independent effect of law difficult to identify. PMID:25525281

Linear discriminant analysis based on L1-norm maximization.

PubMed

Zhong, Fujin; Zhang, Jiashu

2013-08-01

Linear discriminant analysis (LDA) is a well-known dimensionality reduction technique, which is widely used for many purposes. However, conventional LDA is sensitive to outliers because its objective function is based on the distance criterion using L2-norm. This paper proposes a simple but effective robust LDA version based on L1-norm maximization, which learns a set of local optimal projection vectors by maximizing the ratio of the L1-norm-based between-class dispersion and the L1-norm-based within-class dispersion. The proposed method is theoretically proved to be feasible and robust to outliers while overcoming the singular problem of the within-class scatter matrix for conventional LDA. Experiments on artificial datasets, standard classification datasets and three popular image databases demonstrate the efficacy of the proposed method.

L1-norm kernel discriminant analysis via Bayes error bound optimization for robust feature extraction.

PubMed

Zheng, Wenming; Lin, Zhouchen; Wang, Haixian

2014-04-01

A novel discriminant analysis criterion is derived in this paper under the theoretical framework of Bayes optimality. In contrast to the conventional Fisher's discriminant criterion, the major novelty of the proposed one is the use of L1 norm rather than L2 norm, which makes it less sensitive to the outliers. With the L1-norm discriminant criterion, we propose a new linear discriminant analysis (L1-LDA) method for linear feature extraction problem. To solve the L1-LDA optimization problem, we propose an efficient iterative algorithm, in which a novel surrogate convex function is introduced such that the optimization problem in each iteration is to simply solve a convex programming problem and a close-form solution is guaranteed to this problem. Moreover, we also generalize the L1-LDA method to deal with the nonlinear robust feature extraction problems via the use of kernel trick, and hereafter proposed the L1-norm kernel discriminant analysis (L1-KDA) method. Extensive experiments on simulated and real data sets are conducted to evaluate the effectiveness of the proposed method in comparing with the state-of-the-art methods.

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

Unseren, M.A.

This report proposes a method for resolving the kinematic redundancy of a serial link manipulator moving in a three-dimensional workspace. The underspecified problem of solving for the joint velocities based on the classical kinematic velocity model is transformed into a well-specified problem. This is accomplished by augmenting the original model with additional equations which relate a new vector variable quantifying the redundant degrees of freedom (DOF) to the joint velocities. The resulting augmented system yields a well specified solution for the joint velocities. Methods for selecting the redundant DOF quantifying variable and the transformation matrix relating it to the jointmore » velocities are presented so as to obtain a minimum Euclidean norm solution for the joint velocities. The approach is also applied to the problem of resolving the kinematic redundancy at the acceleration level. Upon resolving the kinematic redundancy, a rigid body dynamical model governing the gross motion of the manipulator is derived. A control architecture is suggested which according to the model, decouples the Cartesian space DOF and the redundant DOF.« less

Standard setting: comparison of two methods.

PubMed

George, Sanju; Haque, M Sayeed; Oyebode, Femi

2006-09-14

The outcome of assessments is determined by the standard-setting method used. There is a wide range of standard-setting methods and the two used most extensively in undergraduate medical education in the UK are the norm-reference and the criterion-reference methods. The aims of the study were to compare these two standard-setting methods for a multiple-choice question examination and to estimate the test-retest and inter-rater reliability of the modified Angoff method. The norm-reference method of standard-setting (mean minus 1 SD) was applied to the 'raw' scores of 78 4th-year medical students on a multiple-choice examination (MCQ). Two panels of raters also set the standard using the modified Angoff method for the same multiple-choice question paper on two occasions (6 months apart). We compared the pass/fail rates derived from the norm reference and the Angoff methods and also assessed the test-retest and inter-rater reliability of the modified Angoff method. The pass rate with the norm-reference method was 85% (66/78) and that by the Angoff method was 100% (78 out of 78). The percentage agreement between Angoff method and norm-reference was 78% (95% CI 69% - 87%). The modified Angoff method had an inter-rater reliability of 0.81-0.82 and a test-retest reliability of 0.59-0.74. There were significant differences in the outcomes of these two standard-setting methods, as shown by the difference in the proportion of candidates that passed and failed the assessment. The modified Angoff method was found to have good inter-rater reliability and moderate test-retest reliability.

Phase unwrapping methods of corner reflector DInSAR monitoring slow ground deformation

NASA Astrophysics Data System (ADS)

Fu, Wenxue; Guo, Xiaofang; Tian, Qingjiu

2007-06-01

Difference interferometric Synthetic aperture radar (DInSAR) has turned out to be a very powerful technique for the measurement of land deformations, but it requires the observed area to be correlated, and coherence degradation will seriously affect the quality of interferogram. Corner reflector DInSAR (CRDInSAR) is a new technique in recently years, which can compensate for the limitation of the classical DInSAR. Due to the stable amplitude and phase performance of the reflector, the interferometric phase difference of the reflector can be used to monitor or measure the small and slowly ground deformation for the cases of large geometrical baseline and large time interval between acquisitions. Phase unwrapping is the process where the absolute phase is reconstructed from its principal value as accurately as possible. It is a key step in the analysis of DInSAR. The classical phase unwrapping methods are either of path following type or of minimum-norm type. However, if the coherence of the two images is very low, the both methods will get error result. In application of CRDInSAR, due to the scattered points, the phase unwrapping of corner reflectors is only dealt with on a sparse grid, so all the reflectors are connected with Delaunay triangulation firstly, which can be used to define neighboring points and elementary cycles. When the monitoring ground deformation is slow, that is unwrapped neighboring-CR phase gradients are supposed to equal their wrapped-phase counterparts, then path-following method and Phase unwrapping using Coefficient of Elevation-Phase-Relation can be used to phase unwrapping. However, in the cases of unwrapped gradients exceeding one-half cycle, minimum cost flow (MCF) method can be used to unwrap the interferogram.

Global Sliding Mode Control for the Bank-to-Turn of Hypersonic Glide Vehicle

NASA Astrophysics Data System (ADS)

Zhang, J.; Yu, Y. F.; Yan, P. P.; Fan, Y. H.; Guo, X. W.

2017-03-01

The technology of Bank-to-Turn has been recognized as an attractive direction due to their significance for the control of hypersonic glide vehicle. Strong coupling existing among pitch, yaw and roll channel was a great challenge for banking to turn, and thus a novel global sliding mode controller was designed for hypersonic glider in this paper. Considering the coupling among channels as interference, we can use invariance principle of sliding mode motion to realize the decoupling control. The global sliding mode control system could eliminate the stage of reaching, which can lead to the realization of whole systematic process decoupling control. When the global sliding mode factor was designed, a minimum norm pole assignment method of the sliding mode matrix was introduced to improve the robustness of the system. The method of continuity of symbolic function was adopted to overcome the chatter, which furtherly modify the transient performance of the system. The simulation results show that this method has good performance of three channel decoupling control and guidance command tracking. And it can meet the requirements of the dynamic performance of the system.

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

Khosla, D.; Singh, M.

The estimation of three-dimensional dipole current sources on the cortical surface from the measured magnetoencephalogram (MEG) is a highly under determined inverse problem as there are many {open_quotes}feasible{close_quotes} images which are consistent with the MEG data. Previous approaches to this problem have concentrated on the use of weighted minimum norm inverse methods. While these methods ensure a unique solution, they often produce overly smoothed solutions and exhibit severe sensitivity to noise. In this paper we explore the maximum entropy approach to obtain better solutions to the problem. This estimation technique selects that image from the possible set of feasible imagesmore » which has the maximum entropy permitted by the information available to us. In order to account for the presence of noise in the data, we have also incorporated a noise rejection or likelihood term into our maximum entropy method. This makes our approach mirror a Bayesian maximum a posteriori (MAP) formulation. Additional information from other functional techniques like functional magnetic resonance imaging (fMRI) can be incorporated in the proposed method in the form of a prior bias function to improve solutions. We demonstrate the method with experimental phantom data from a clinical 122 channel MEG system.« less

Segmentation of tumor ultrasound image in HIFU therapy based on texture and boundary encoding

NASA Astrophysics Data System (ADS)

Zhang, Dong; Xu, Menglong; Quan, Long; Yang, Yan; Qin, Qianqing; Zhu, Wenbin

2015-02-01

It is crucial in high intensity focused ultrasound (HIFU) therapy to detect the tumor precisely with less manual intervention for enhancing the therapy efficiency. Ultrasound image segmentation becomes a difficult task due to signal attenuation, speckle effect and shadows. This paper presents an unsupervised approach based on texture and boundary encoding customized for ultrasound image segmentation in HIFU therapy. The approach oversegments the ultrasound image into some small regions, which are merged by using the principle of minimum description length (MDL) afterwards. Small regions belonging to the same tumor are clustered as they preserve similar texture features. The mergence is completed by obtaining the shortest coding length from encoding textures and boundaries of these regions in the clustering process. The tumor region is finally selected from merged regions by a proposed algorithm without manual interaction. The performance of the method is tested on 50 uterine fibroid ultrasound images from HIFU guiding transducers. The segmentations are compared with manual delineations to verify its feasibility. The quantitative evaluation with HIFU images shows that the mean true positive of the approach is 93.53%, the mean false positive is 4.06%, the mean similarity is 89.92%, the mean norm Hausdorff distance is 3.62% and the mean norm maximum average distance is 0.57%. The experiments validate that the proposed method can achieve favorable segmentation without manual initialization and effectively handle the poor quality of the ultrasound guidance image in HIFU therapy, which indicates that the approach is applicable in HIFU therapy.

Reconstructing cortical current density by exploring sparseness in the transform domain

NASA Astrophysics Data System (ADS)

Ding, Lei

2009-05-01

In the present study, we have developed a novel electromagnetic source imaging approach to reconstruct extended cortical sources by means of cortical current density (CCD) modeling and a novel EEG imaging algorithm which explores sparseness in cortical source representations through the use of L1-norm in objective functions. The new sparse cortical current density (SCCD) imaging algorithm is unique since it reconstructs cortical sources by attaining sparseness in a transform domain (the variation map of cortical source distributions). While large variations are expected to occur along boundaries (sparseness) between active and inactive cortical regions, cortical sources can be reconstructed and their spatial extents can be estimated by locating these boundaries. We studied the SCCD algorithm using numerous simulations to investigate its capability in reconstructing cortical sources with different extents and in reconstructing multiple cortical sources with different extent contrasts. The SCCD algorithm was compared with two L2-norm solutions, i.e. weighted minimum norm estimate (wMNE) and cortical LORETA. Our simulation data from the comparison study show that the proposed sparse source imaging algorithm is able to accurately and efficiently recover extended cortical sources and is promising to provide high-accuracy estimation of cortical source extents.

Robust and Efficient Biomolecular Clustering of Tumor Based on ${p}$ -Norm Singular Value Decomposition.

PubMed

Kong, Xiang-Zhen; Liu, Jin-Xing; Zheng, Chun-Hou; Hou, Mi-Xiao; Wang, Juan

2017-07-01

High dimensionality has become a typical feature of biomolecular data. In this paper, a novel dimension reduction method named p-norm singular value decomposition (PSVD) is proposed to seek the low-rank approximation matrix to the biomolecular data. To enhance the robustness to outliers, the Lp-norm is taken as the error function and the Schatten p-norm is used as the regularization function in the optimization model. To evaluate the performance of PSVD, the Kmeans clustering method is then employed for tumor clustering based on the low-rank approximation matrix. Extensive experiments are carried out on five gene expression data sets including two benchmark data sets and three higher dimensional data sets from the cancer genome atlas. The experimental results demonstrate that the PSVD-based method outperforms many existing methods. Especially, it is experimentally proved that the proposed method is more efficient for processing higher dimensional data with good robustness, stability, and superior time performance.

Validation of self-directed learning instrument and establishment of normative data for nursing students in taiwan: using polytomous item response theory.

PubMed

Cheng, Su-Fen; Lee-Hsieh, Jane; Turton, Michael A; Lin, Kuan-Chia

2014-06-01

Little research has investigated the establishment of norms for nursing students' self-directed learning (SDL) ability, recognized as an important capability for professional nurses. An item response theory (IRT) approach was used to establish norms for SDL abilities valid for the different nursing programs in Taiwan. The purposes of this study were (a) to use IRT with a graded response model to reexamine the SDL instrument, or the SDLI, originally developed by this research team using confirmatory factor analysis and (b) to establish SDL ability norms for the four different nursing education programs in Taiwan. Stratified random sampling with probability proportional to size was used. A minimum of 15% of students from the four different nursing education degree programs across Taiwan was selected. A total of 7,879 nursing students from 13 schools were recruited. The research instrument was the 20-item SDLI developed by Cheng, Kuo, Lin, and Lee-Hsieh (2010). IRT with the graded response model was used with a two-parameter logistic model (discrimination and difficulty) for the data analysis, calculated using MULTILOG. Norms were established using percentile rank. Analysis of item information and test information functions revealed that 18 items exhibited very high discrimination and two items had high discrimination. The test information function was higher in this range of scores, indicating greater precision in the estimate of nursing student SDL. Reliability fell between .80 and .94 for each domain and the SDLI as a whole. The total information function shows that the SDLI is appropriate for all nursing students, except for the top 2.5%. SDL ability norms were established for each nursing education program and for the nation as a whole. IRT is shown to be a potent and useful methodology for scale evaluation. The norms for SDL established in this research will provide practical standards for nursing educators and students in Taiwan.

Reference genes for reverse transcription quantitative PCR in canine brain tissue.

PubMed

Stassen, Quirine E M; Riemers, Frank M; Reijmerink, Hannah; Leegwater, Peter A J; Penning, Louis C

2015-12-09

In the last decade canine models have been used extensively to study genetic causes of neurological disorders such as epilepsy and Alzheimer's disease and unravel their pathophysiological pathways. Reverse transcription quantitative polymerase chain reaction is a sensitive and inexpensive method to study expression levels of genes involved in disease processes. Accurate normalisation with stably expressed so-called reference genes is crucial for reliable expression analysis. Following the minimum information for publication of quantitative real-time PCR experiments precise guidelines, the expression of ten frequently used reference genes, namely YWHAZ, HMBS, B2M, SDHA, GAPDH, HPRT, RPL13A, RPS5, RPS19 and GUSB was evaluated in seven brain regions (frontal lobe, parietal lobe, occipital lobe, temporal lobe, thalamus, hippocampus and cerebellum) and whole brain of healthy dogs. The stability of expression varied between different brain areas. Using the GeNorm and Normfinder software HMBS, GAPDH and HPRT were the most reliable reference genes for whole brain. Furthermore based on GeNorm calculations it was concluded that as little as two to three reference genes are sufficient to obtain reliable normalisation, irrespective the brain area. Our results amend/extend the limited previously published data on canine brain reference genes. Despite the excellent expression stability of HMBS, GAPDH and HRPT, the evaluation of expression stability of reference genes must be a standard and integral part of experimental design and subsequent data analysis.

Robot map building based on fuzzy-extending DSmT

NASA Astrophysics Data System (ADS)

Li, Xinde; Huang, Xinhan; Wu, Zuyu; Peng, Gang; Wang, Min; Xiong, Youlun

2007-11-01

With the extensive application of mobile robots in many different fields, map building in unknown environments has been one of the principal issues in the field of intelligent mobile robot. However, Information acquired in map building presents characteristics of uncertainty, imprecision and even high conflict, especially in the course of building grid map using sonar sensors. In this paper, we extended DSmT with Fuzzy theory by considering the different fuzzy T-norm operators (such as Algebraic Product operator, Bounded Product operator, Einstein Product operator and Default minimum operator), in order to develop a more general and flexible combinational rule for more extensive application. At the same time, we apply fuzzy-extended DSmT to mobile robot map building with the help of new self-localization method based on neighboring field appearance matching( -NFAM), to make the new tool more robust in very complex environment. An experiment is conducted to reconstruct the map with the new tool in indoor environment, in order to compare their performances in map building with four T-norm operators, when Pioneer II mobile robot runs along the same trace. Finally, a conclusion is reached that this study develops a new idea to extend DSmT, also provides a new approach for autonomous navigation of mobile robot, and provides a human-computer interactive interface to manage and manipulate the robot remotely.

Norms for 10,491 Spanish words for five discrete emotions: Happiness, disgust, anger, fear, and sadness.

PubMed

Stadthagen-González, Hans; Ferré, Pilar; Pérez-Sánchez, Miguel A; Imbault, Constance; Hinojosa, José Antonio

2017-09-18

The discrete emotion theory proposes that affective experiences can be reduced to a limited set of universal "basic" emotions, most commonly identified as happiness, sadness, anger, fear, and disgust. Here we present norms for 10,491 Spanish words for those five discrete emotions collected from a total of 2,010 native speakers, making it the largest set of norms for discrete emotions in any language to date. When used in conjunction with the norms from Hinojosa, Martínez-García et al. (Behavior Research Methods, 48, 272-284, 2016) and Ferré, Guasch, Martínez-García, Fraga, & Hinojosa (Behavior Research Methods, 49, 1082-1094, 2017), researchers now have access to ratings of discrete emotions for 13,633 Spanish words. Our norms show a high degree of inter-rater reliability and correlate highly with those from Ferré et al. (2017). Our exploration of the relationship between the five discrete emotions and relevant lexical and emotional variables confirmed findings of previous studies conducted with smaller datasets. The availability of such large set of norms will greatly facilitate the study of emotion, language and related fields. The norms are available as supplementary materials to this article.

Nearest Neighbor Averaging and its Effect on the Critical Level and Minimum Detectable Concentration for Scanning Radiological Survey Instruments that Perform Facility Release Surveys.

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

Fournier, Sean Donovan; Beall, Patrick S; Miller, Mark L

2014-08-01

Through the SNL New Mexico Small Business Assistance (NMSBA) program, several Sandia engineers worked with the Environmental Restoration Group (ERG) Inc. to verify and validate a novel algorithm used to determine the scanning Critical Level (L c ) and Minimum Detectable Concentration (MDC) (or Minimum Detectable Areal Activity) for the 102F scanning system. Through the use of Monte Carlo statistical simulations the algorithm mathematically demonstrates accuracy in determining the L c and MDC when a nearest-neighbor averaging (NNA) technique was used. To empirically validate this approach, SNL prepared several spiked sources and ran a test with the ERG 102F instrumentmore » on a bare concrete floor known to have no radiological contamination other than background naturally occurring radioactive material (NORM). The tests conclude that the NNA technique increases the sensitivity (decreases the L c and MDC) for high-density data maps that are obtained by scanning radiological survey instruments.« less

Effects of Visual Complexity and Sublexical Information in the Occipitotemporal Cortex in the Reading of Chinese Phonograms: A Single-Trial Analysis with MEG

ERIC Educational Resources Information Center

Hsu, Chun-Hsien; Lee, Chia-Ying; Marantz, Alec

2011-01-01

We employ a linear mixed-effects model to estimate the effects of visual form and the linguistic properties of Chinese characters on M100 and M170 MEG responses from single-trial data of Chinese and English speakers in a Chinese lexical decision task. Cortically constrained minimum-norm estimation is used to compute the activation of M100 and M170…

Error analysis of finite element method for Poisson–Nernst–Planck equations

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

Sun, Yuzhou; Sun, Pengtao; Zheng, Bin

A priori error estimates of finite element method for time-dependent Poisson-Nernst-Planck equations are studied in this work. We obtain the optimal error estimates in L∞(H1) and L2(H1) norms, and suboptimal error estimates in L∞(L2) norm, with linear element, and optimal error estimates in L∞(L2) norm with quadratic or higher-order element, for both semi- and fully discrete finite element approximations. Numerical experiments are also given to validate the theoretical results.

Discriminant locality preserving projections based on L1-norm maximization.

PubMed

Zhong, Fujin; Zhang, Jiashu; Li, Defang

2014-11-01

Conventional discriminant locality preserving projection (DLPP) is a dimensionality reduction technique based on manifold learning, which has demonstrated good performance in pattern recognition. However, because its objective function is based on the distance criterion using L2-norm, conventional DLPP is not robust to outliers which are present in many applications. This paper proposes an effective and robust DLPP version based on L1-norm maximization, which learns a set of local optimal projection vectors by maximizing the ratio of the L1-norm-based locality preserving between-class dispersion and the L1-norm-based locality preserving within-class dispersion. The proposed method is proven to be feasible and also robust to outliers while overcoming the small sample size problem. The experimental results on artificial datasets, Binary Alphadigits dataset, FERET face dataset and PolyU palmprint dataset have demonstrated the effectiveness of the proposed method.

Interpersonal communication as an agent of normative influence: a mixed method study among the urban poor in India.

PubMed

Rimal, Rajiv N; Sripad, Pooja; Speizer, Ilene S; Calhoun, Lisa M

2015-08-12

Although social norms are thought to play an important role in couples' reproductive decisions, only limited theoretical or empirical guidance exists on how the underlying process works. Using the theory of normative social behavior (TNSB), through a mixed-method design, we investigated the role played by injunctive norms and interpersonal discussion in the relationship between descriptive norms and use of modern contraceptive methods among the urban poor in India. Data from a household survey (N = 11,811) were used to test the underlying theoretical propositions, and focus group interviews among men and women were then conducted to obtain more in-depth knowledge about decision-making processes related to modern contraceptive use. Spousal influence and interpersonal communication emerged as key factors in decision-making, waning in the later years of marriage, and they also moderated the influence of descriptive norms on behaviors. Norms around contraceptive use, which varied by parity, are rapidly changing with the country's urbanization and increased access to health information. Open interpersonal discussion, community norms, and perspectives are integral in enabling women and couples to use modern family planning to meet their current fertility desires and warrant sensitivity in the design of family planning policy and programs.

American Sign Language/English bilingual model: a longitudinal study of academic growth.

PubMed

Lange, Cheryl M; Lane-Outlaw, Susan; Lange, William E; Sherwood, Dyan L

2013-10-01

This study examines reading and mathematics academic growth of deaf and hard-of-hearing students instructed through an American Sign Language (ASL)/English bilingual model. The study participants were exposed to the model for a minimum of 4 years. The study participants' academic growth rates were measured using the Northwest Evaluation Association's Measure of Academic Progress assessment and compared with a national-normed group of grade-level peers that consisted primarily of hearing students. The study also compared academic growth for participants by various characteristics such as gender, parents' hearing status, and secondary disability status and examined the academic outcomes for students after a minimum of 4 years of instruction in an ASL/English bilingual model. The findings support the efficacy of the ASL/English bilingual model.

Do "Clicker" Educational Sessions Enhance the Effectiveness of a Social Norms Marketing Campaign?

ERIC Educational Resources Information Center

Killos, Lydia F.; Hancock, Linda C.; McGann, Amanda Wattenmaker; Keller, Adrienne E.

2010-01-01

Objective: Social norms campaigns are a cost-effective way to reduce high-risk drinking on college campuses. This study compares effectiveness of a "standard" social norms media (SNM) campaign for those with and without exposure to additional educational sessions using audience response technology ("clickers"). Methods: American College Health…

Norm Block Sample Sizes: A Review of 17 Individually Administered Intelligence Tests

ERIC Educational Resources Information Center

Norfolk, Philip A.; Farmer, Ryan L.; Floyd, Randy G.; Woods, Isaac L.; Hawkins, Haley K.; Irby, Sarah M.

2015-01-01

The representativeness, recency, and size of norm samples strongly influence the accuracy of inferences drawn from their scores. Inadequate norm samples may lead to inflated or deflated scores for individuals and poorer prediction of developmental and academic outcomes. The purpose of this study was to apply Kranzler and Floyd's method for…

The Influence of Social Norms on Flu Vaccination among African American and White Adults

ERIC Educational Resources Information Center

Quinn, Sandra Crouse; Hilyard, Karen M.; Jamison, Amelia M.; An, Ji; Hancock, Gregory R.; Musa, Donald; Freimuth, Vicki S.

2017-01-01

Adult influenza vaccination rates remain suboptimal, particularly among African Americans. Social norms may influence vaccination behavior, but little research has focused on influenza vaccine and almost no research has focused on racially-specific norms. This mixed methods investigation utilizes qualitative interviews and focus groups (n = 118)…

Reconstruction algorithms based on l1-norm and l2-norm for two imaging models of fluorescence molecular tomography: a comparative study.

PubMed

Yi, Huangjian; Chen, Duofang; Li, Wei; Zhu, Shouping; Wang, Xiaorui; Liang, Jimin; Tian, Jie

2013-05-01

Fluorescence molecular tomography (FMT) is an important imaging technique of optical imaging. The major challenge of the reconstruction method for FMT is the ill-posed and underdetermined nature of the inverse problem. In past years, various regularization methods have been employed for fluorescence target reconstruction. A comparative study between the reconstruction algorithms based on l1-norm and l2-norm for two imaging models of FMT is presented. The first imaging model is adopted by most researchers, where the fluorescent target is of small size to mimic small tissue with fluorescent substance, as demonstrated by the early detection of a tumor. The second model is the reconstruction of distribution of the fluorescent substance in organs, which is essential to drug pharmacokinetics. Apart from numerical experiments, in vivo experiments were conducted on a dual-modality FMT/micro-computed tomography imaging system. The experimental results indicated that l1-norm regularization is more suitable for reconstructing the small fluorescent target, while l2-norm regularization performs better for the reconstruction of the distribution of fluorescent substance.

English semantic word-pair norms and a searchable Web portal for experimental stimulus creation.

PubMed

Buchanan, Erin M; Holmes, Jessica L; Teasley, Marilee L; Hutchison, Keith A

2013-09-01

As researchers explore the complexity of memory and language hierarchies, the need to expand normed stimulus databases is growing. Therefore, we present 1,808 words, paired with their features and concept-concept information, that were collected using previously established norming methods (McRae, Cree, Seidenberg, & McNorgan Behavior Research Methods 37:547-559, 2005). This database supplements existing stimuli and complements the Semantic Priming Project (Hutchison, Balota, Cortese, Neely, Niemeyer, Bengson, & Cohen-Shikora 2010). The data set includes many types of words (including nouns, verbs, adjectives, etc.), expanding on previous collections of nouns and verbs (Vinson & Vigliocco Journal of Neurolinguistics 15:317-351, 2008). We describe the relation between our and other semantic norms, as well as giving a short review of word-pair norms. The stimuli are provided in conjunction with a searchable Web portal that allows researchers to create a set of experimental stimuli without prior programming knowledge. When researchers use this new database in tandem with previous norming efforts, precise stimuli sets can be created for future research endeavors.

High resolution beamforming on large aperture vertical line arrays: Processing synthetic data

NASA Astrophysics Data System (ADS)

Tran, Jean-Marie Q.; Hodgkiss, William S.

1990-09-01

This technical memorandum studies the beamforming of large aperture line arrays deployed vertically in the water column. The work concentrates on the use of high resolution techniques. Two processing strategies are envisioned: (1) full aperture coherent processing which offers in theory the best processing gain; and (2) subaperture processing which consists in extracting subapertures from the array and recombining the angular spectra estimated from these subarrays. The conventional beamformer, the minimum variance distortionless response (MVDR) processor, the multiple signal classification (MUSIC) algorithm and the minimum norm method are used in this study. To validate the various processing techniques, the ATLAS normal mode program is used to generate synthetic data which constitute a realistic signals environment. A deep-water, range-independent sound velocity profile environment, characteristic of the North-East Pacific, is being studied for two different 128 sensor arrays: a very long one cut for 30 Hz and operating at 20 Hz; and a shorter one cut for 107 Hz and operating at 100 Hz. The simulated sound source is 5 m deep. The full aperture and subaperture processing are being implemented with curved and plane wavefront replica vectors. The beamforming results are examined and compared to the ray-theory results produced by the generic sonar model.

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

Suppressing multiples using an adaptive multichannel filter based on L1-norm

NASA Astrophysics Data System (ADS)

Shi, Ying; Jing, Hongliang; Zhang, Wenwu; Ning, Dezhi

2017-08-01

Adaptive subtraction is an important link for removing surface-related multiples in the wave equation-based method. In this paper, we propose an adaptive multichannel subtraction method based on the L1-norm. We achieve enhanced compensation for the mismatch between the input seismogram and the predicted multiples in terms of the amplitude, phase, frequency band, and travel time. Unlike the conventional L2-norm, the proposed method does not rely on the assumption that the primary and the multiples are orthogonal, and also takes advantage of the fact that the L1-norm is more robust when dealing with outliers. In addition, we propose a frequency band extension via modulation to reconstruct the high frequencies to compensate for the frequency misalignment. We present a parallel computing scheme to accelerate the subtraction algorithm on graphic processing units (GPUs), which significantly reduces the computational cost. The synthetic and field seismic data tests show that the proposed method effectively suppresses the multiples.

Development of fast measurements of concentration of NORM U-238 by HPGe

NASA Astrophysics Data System (ADS)

Cha, Seokki; Kim, Siu; Kim, Geehyun

2017-02-01

Naturally Occureed Radioactive Material (NORM) generated from the origin of earth can be found all around us and even people who are not engaged in the work related to radiation have been exposed to unnecessary radiation. This NORM has a potential risk provided that is concentrated or transformed by artificial activities. Likewise, a development of fast measruement method of NORM is emerging to prevent the radiation exposure of the general public and person engaged in the work related to the type of business related thereto who uses the material in which NORM is concentrated or transfromed. Based on such a background, many of countries have tried to manage NORM and carried out regulatory legislation. To effienctly manage NORM, there is need for developing new measurement to quickly and accurately analyze the nuclide and concentration. In this study, development of the fast and reliable measurement was carried out. In addition to confirming the reliability of the fast measurement, we have obtained results that can suggest the possibility of developing another fast measurement. Therefore, as a follow-up, it is possible to develop another fast analytical measurement afterwards. The results of this study will be very useful for the regulatory system to manage NORM. In this study, a review of two indirect measurement methods of NORM U-238 that has used HPGe on the basis of the equilibrium theory of relationships of mother and daughter nuclide at decay-chain of NORM U-238 has been carried out. For comparative study(in order to know reliabily), direct measurement that makes use of alpha spectrometer with complicated pre-processing process was implemented.

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

General Population Norms about Child Abuse and Neglect and Associations with Childhood Experiences

ERIC Educational Resources Information Center

Bensley, L.; Ruggles, D.; Simmons, K.W.; Harris, C.; Williams, K.; Putvin, T.; Allen, M.

2004-01-01

Background:: A variety of definitions of child abuse and neglect exist. However, little is known about norms in the general population as to what constitutes child abuse and neglect or how perceived norms may be related to personal experiences. Methods:: We conducted a random-digit-dialed telephone survey of 504 Washington State adults.…

The Benefits of Latent Variable Modeling to Develop Norms for a Translated Version of a Standardized Scale

ERIC Educational Resources Information Center

Seo, Hyojeong; Shaw, Leslie A.; Shogren, Karrie A.; Lang, Kyle M.; Little, Todd D.

2017-01-01

This article demonstrates the use of structural equation modeling to develop norms for a translated version of a standardized scale, the Supports Intensity Scale-Children's Version (SIS-C). The latent variable norming method proposed is useful when the standardization sample for a translated version is relatively small to derive norms…

Attitudes and Descriptive Norms of Alcohol-Related Problems as Predictors of Alcohol Use among College Students

ERIC Educational Resources Information Center

Sheppard, Meg E.; Usdan, Stuart L.; Higginbotham, John C.; Cremeens-Matthews, Jennifer L.

2016-01-01

Background: The purpose of this study is to identify predictors of alcohol use based on personal values and several constructs from the Integrated Behavioral Model (i.e., attitudes, injunctive norms and descriptive norms) among undergraduate college students. Methods: A cross sectional study design was used with a convenience sample of college…

Primal-dual convex optimization in large deformation diffeomorphic metric mapping: LDDMM meets robust regularizers

NASA Astrophysics Data System (ADS)

Hernandez, Monica

2017-12-01

This paper proposes a method for primal-dual convex optimization in variational large deformation diffeomorphic metric mapping problems formulated with robust regularizers and robust image similarity metrics. The method is based on Chambolle and Pock primal-dual algorithm for solving general convex optimization problems. Diagonal preconditioning is used to ensure the convergence of the algorithm to the global minimum. We consider three robust regularizers liable to provide acceptable results in diffeomorphic registration: Huber, V-Huber and total generalized variation. The Huber norm is used in the image similarity term. The primal-dual equations are derived for the stationary and the non-stationary parameterizations of diffeomorphisms. The resulting algorithms have been implemented for running in the GPU using Cuda. For the most memory consuming methods, we have developed a multi-GPU implementation. The GPU implementations allowed us to perform an exhaustive evaluation study in NIREP and LPBA40 databases. The experiments showed that, for all the considered regularizers, the proposed method converges to diffeomorphic solutions while better preserving discontinuities at the boundaries of the objects compared to baseline diffeomorphic registration methods. In most cases, the evaluation showed a competitive performance for the robust regularizers, close to the performance of the baseline diffeomorphic registration methods.

A New Expanded Mixed Element Method for Convection-Dominated Sobolev Equation

PubMed Central

Wang, Jinfeng; Li, Hong; Fang, Zhichao

2014-01-01

We propose and analyze a new expanded mixed element method, whose gradient belongs to the simple square integrable space instead of the classical H(div; Ω) space of Chen's expanded mixed element method. We study the new expanded mixed element method for convection-dominated Sobolev equation, prove the existence and uniqueness for finite element solution, and introduce a new expanded mixed projection. We derive the optimal a priori error estimates in L 2-norm for the scalar unknown u and a priori error estimates in (L 2)2-norm for its gradient λ and its flux σ. Moreover, we obtain the optimal a priori error estimates in H 1-norm for the scalar unknown u. Finally, we obtained some numerical results to illustrate efficiency of the new method. PMID:24701153

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.

Reduction of speckle noise from optical coherence tomography images using multi-frame weighted nuclear norm minimization method

NASA Astrophysics Data System (ADS)

Thapa, Damber; Raahemifar, Kaamran; Lakshminarayanan, Vasudevan

2015-12-01

In this paper, we propose a speckle noise reduction method for spectral-domain optical coherence tomography (SD-OCT) images called multi-frame weighted nuclear norm minimization (MWNNM). This method is a direct extension of weighted nuclear norm minimization (WNNM) in the multi-frame framework since an adequately denoised image could not be achieved with single-frame denoising methods. The MWNNM method exploits multiple B-scans collected from a small area of a SD-OCT volumetric image, and then denoises and averages them together to obtain a high signal-to-noise ratio B-scan. The results show that the image quality metrics obtained by denoising and averaging only five nearby B-scans with MWNNM method is considerably better than those of the average image obtained by registering and averaging 40 azimuthally repeated B-scans.

A Graph-based Approach to Auditing RxNorm

PubMed Central

Bodenreider, Olivier; Peters, Lee B.

2009-01-01

Objectives RxNorm is a standardized nomenclature for clinical drug entities developed by the National Library of Medicine. In this paper, we audit relations in RxNorm for consistency and completeness through the systematic analysis of the graph of its concepts and relationships. Methods The representation of multi-ingredient drugs is normalized in order to make it compatible with that of single-ingredient drugs. All meaningful paths between two nodes in the type graph are computed and instantiated. Alternate paths are automatically compared and manually inspected in case of inconsistency. Results The 115 meaningful paths identified in the type graph can be grouped into 28 groups with respect to start and end nodes. Of the 19 groups of alternate paths (i.e., with two or more paths) between the start and end nodes, 9 (47%) exhibit inconsistencies. Overall, 28 (24%) of the 115 paths are inconsistent with other alternate paths. A total of 348 inconsistencies were identified in the April 2008 version of RxNorm and reported to the RxNorm team, of which 215 (62%) had been corrected in the January 2009 version of RxNorm. Conclusion The inconsistencies identified involve missing nodes (93), missing links (17), extraneous links (237) and one case of mix-up between two ingredients. Our auditing method proved effective in identifying a limited number of errors that had defeated the quality assurance mechanisms currently in place in the RxNorm production system. Some recommendations for the development of RxNorm are provided. PMID:19394440

Interval-valued intuitionistic fuzzy matrix games based on Archimedean t-conorm and t-norm

NASA Astrophysics Data System (ADS)

Xia, Meimei

2018-04-01

Fuzzy game theory has been applied in many decision-making problems. The matrix game with interval-valued intuitionistic fuzzy numbers (IVIFNs) is investigated based on Archimedean t-conorm and t-norm. The existing matrix games with IVIFNs are all based on Algebraic t-conorm and t-norm, which are special cases of Archimedean t-conorm and t-norm. In this paper, the intuitionistic fuzzy aggregation operators based on Archimedean t-conorm and t-norm are employed to aggregate the payoffs of players. To derive the solution of the matrix game with IVIFNs, several mathematical programming models are developed based on Archimedean t-conorm and t-norm. The proposed models can be transformed into a pair of primal-dual linear programming models, based on which, the solution of the matrix game with IVIFNs is obtained. It is proved that the theorems being valid in the exiting matrix game with IVIFNs are still true when the general aggregation operator is used in the proposed matrix game with IVIFNs. The proposed method is an extension of the existing ones and can provide more choices for players. An example is given to illustrate the validity and the applicability of the proposed method.

Time-domain prefilter design for enhanced tracking and vibration suppression in machine motion control

NASA Astrophysics Data System (ADS)

Cole, Matthew O. T.; Shinonawanik, Praween; Wongratanaphisan, Theeraphong

2018-05-01

Structural flexibility can impact negatively on machine motion control systems by causing unmeasured positioning errors and vibration at locations where accurate motion is important for task execution. To compensate for these effects, command signal prefiltering may be applied. In this paper, a new FIR prefilter design method is described that combines finite-time vibration cancellation with dynamic compensation properties. The time-domain formulation exploits the relation between tracking error and the moment values of the prefilter impulse response function. Optimal design solutions for filters having minimum H2 norm are derived and evaluated. The control approach does not require additional actuation or sensing and can be effective even without complete and accurate models of the machine dynamics. Results from implementation and testing on an experimental high-speed manipulator having a Delta robot architecture with directionally compliant end-effector are presented. The results show the importance of prefilter moment values for tracking performance and confirm that the proposed method can achieve significant reductions in both peak and RMS tracking error, as well as settling time, for complex motion patterns.

Input relegation control for gross motion of a kinematically redundant manipulator

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

Unseren, M.A.

1992-10-01

This report proposes a method for resolving the kinematic redundancy of a serial link manipulator moving in a three-dimensional workspace. The underspecified problem of solving for the joint velocities based on the classical kinematic velocity model is transformed into a well-specified problem. This is accomplished by augmenting the original model with additional equations which relate a new vector variable quantifying the redundant degrees of freedom (DOF) to the joint velocities. The resulting augmented system yields a well specified solution for the joint velocities. Methods for selecting the redundant DOF quantifying variable and the transformation matrix relating it to the jointmore » velocities are presented so as to obtain a minimum Euclidean norm solution for the joint velocities. The approach is also applied to the problem of resolving the kinematic redundancy at the acceleration level. Upon resolving the kinematic redundancy, a rigid body dynamical model governing the gross motion of the manipulator is derived. A control architecture is suggested which according to the model, decouples the Cartesian space DOF and the redundant DOF.« less

An ACC Design Method for Achieving Both String Stability and Ride Comfort

NASA Astrophysics Data System (ADS)

Yamamura, Yoshinori; Seto, Yoji; Nishira, Hikaru; Kawabe, Taketoshi

An investigation was made of a method for designing adaptive cruise control (ACC) so as to achieve a headway distance response that feels natural to the driver while at the same time obtaining high levels of both string stability and ride comfort. With this design method, the H∞ norm is adopted as the index of string stability. Additionally, two norms are introduced for evaluating ride comfort and natural vehicle behavior. The relationship between these three norms and headway distance response characteristics was analyzed, and an evaluation method was established for achieving high levels of the various performance characteristics required of ACC. An ACC system designed with this method was evaluated in driving tests conducted on a proving ground course, and the results confirmed that it achieved the targeted levels of string stability, ride comfort and natural vehicle behavior.

Effective gene prediction by high resolution frequency estimator based on least-norm solution technique

PubMed Central

2014-01-01

Linear algebraic concept of subspace plays a significant role in the recent techniques of spectrum estimation. In this article, the authors have utilized the noise subspace concept for finding hidden periodicities in DNA sequence. With the vast growth of genomic sequences, the demand to identify accurately the protein-coding regions in DNA is increasingly rising. Several techniques of DNA feature extraction which involves various cross fields have come up in the recent past, among which application of digital signal processing tools is of prime importance. It is known that coding segments have a 3-base periodicity, while non-coding regions do not have this unique feature. One of the most important spectrum analysis techniques based on the concept of subspace is the least-norm method. The least-norm estimator developed in this paper shows sharp period-3 peaks in coding regions completely eliminating background noise. Comparison of proposed method with existing sliding discrete Fourier transform (SDFT) method popularly known as modified periodogram method has been drawn on several genes from various organisms and the results show that the proposed method has better as well as an effective approach towards gene prediction. Resolution, quality factor, sensitivity, specificity, miss rate, and wrong rate are used to establish superiority of least-norm gene prediction method over existing method. PMID:24386895

Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data.

PubMed

Liu, Yuanyuan; Shang, Fanhua; Jiao, Licheng; Cheng, James; Cheng, Hong

2015-11-01

In recent years, low-rank tensor completion (LRTC) problems have received a significant amount of attention in computer vision, data mining, and signal processing. The existing trace norm minimization algorithms for iteratively solving LRTC problems involve multiple singular value decompositions of very large matrices at each iteration. Therefore, they suffer from high computational cost. In this paper, we propose a novel trace norm regularized CANDECOMP/PARAFAC decomposition (TNCP) method for simultaneous tensor decomposition and completion. We first formulate a factor matrix rank minimization model by deducing the relation between the rank of each factor matrix and the mode- n rank of a tensor. Then, we introduce a tractable relaxation of our rank function, and then achieve a convex combination problem of much smaller-scale matrix trace norm minimization. Finally, we develop an efficient algorithm based on alternating direction method of multipliers to solve our problem. The promising experimental results on synthetic and real-world data validate the effectiveness of our TNCP method. Moreover, TNCP is significantly faster than the state-of-the-art methods and scales to larger problems.

Full Waveform Inversion Using Student's t Distribution: a Numerical Study for Elastic Waveform Inversion and Simultaneous-Source Method

NASA Astrophysics Data System (ADS)

Jeong, Woodon; Kang, Minji; Kim, Shinwoong; Min, Dong-Joo; Kim, Won-Ki

2015-06-01

Seismic full waveform inversion (FWI) has primarily been based on a least-squares optimization problem for data residuals. However, the least-squares objective function can suffer from its weakness and sensitivity to noise. There have been numerous studies to enhance the robustness of FWI by using robust objective functions, such as l 1-norm-based objective functions. However, the l 1-norm can suffer from a singularity problem when the residual wavefield is very close to zero. Recently, Student's t distribution has been applied to acoustic FWI to give reasonable results for noisy data. Student's t distribution has an overdispersed density function compared with the normal distribution, and is thus useful for data with outliers. In this study, we investigate the feasibility of Student's t distribution for elastic FWI by comparing its basic properties with those of the l 2-norm and l 1-norm objective functions and by applying the three methods to noisy data. Our experiments show that the l 2-norm is sensitive to noise, whereas the l 1-norm and Student's t distribution objective functions give relatively stable and reasonable results for noisy data. When noise patterns are complicated, i.e., due to a combination of missing traces, unexpected outliers, and random noise, FWI based on Student's t distribution gives better results than l 1- and l 2-norm FWI. We also examine the application of simultaneous-source methods to acoustic FWI based on Student's t distribution. Computing the expectation of the coefficients of gradient and crosstalk noise terms and plotting the signal-to-noise ratio with iteration, we were able to confirm that crosstalk noise is suppressed as the iteration progresses, even when simultaneous-source FWI is combined with Student's t distribution. From our experiments, we conclude that FWI based on Student's t distribution can retrieve subsurface material properties with less distortion from noise than l 1- and l 2-norm FWI, and the simultaneous-source method can be adopted to improve the computational efficiency of FWI based on Student's t distribution.

Uranium Mining and Norm in North America-Some Perspectives on Occupational Radiation Exposure.

PubMed

Brown, Steven H; Chambers, Douglas B

2017-07-01

All soils and rocks contain naturally occurring radioactive materials (NORM). Many ores and raw materials contain relatively elevated levels of natural radionuclides, and processing such materials can further increase the concentrations of naturally occurring radionuclides. In the U.S., these materials are sometimes referred to as technologically-enhanced naturally occurring radioactive materials (TENORM). Examples of NORM minerals include uranium ores, monazite (a source of rare earth minerals), and phosphate rock used to produce phosphate fertilizer. The processing of these materials has the potential to result in above-background radiation exposure to workers. Following a brief review of the sources and potential for worker exposure from NORM in these varied industries, this paper will then present an overview of uranium mining and recovery in North America, including discussion on the mining methods currently being used for both conventional (underground, open pit) and in situ leach (ISL), also referred to as In Situ Recovery (ISR), and the production of NORM materials and wastes associated with these uranium recovery methods. The radiological composition of the NORM products and wastes produced and recent data on radiological exposures received by workers in the North American uranium recovery industry are then described. The paper also identifies the responsible government agencies in the U.S. and Canada assigned the authority to regulate and control occupational exposure from these NORM materials.

Dating Norms and Dating Violence among Ninth Graders in Northeast Georgia: Reports from Student Surveys and Focus Groups

ERIC Educational Resources Information Center

Reeves, Patricia M.; Orpinas, Pamela

2012-01-01

This mixed-methods study describes the norms supporting male-to-female and female-to-male dating violence in a diverse sample of ninth graders. The quantitative study, based on student surveys (n = 624), compared norms supporting dating violence by sex, race/ethnicity, and dating status, and it examined the relation between dating violence norms…

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.

A ℓ2, 1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD.

PubMed

Cao, Peng; Liu, Xiaoli; Zhang, Jian; Li, Wei; Zhao, Dazhe; Huang, Min; Zaiane, Osmar

2017-03-01

The aim of this paper is to describe a novel algorithm for False Positive Reduction in lung nodule Computer Aided Detection(CAD). In this paper, we describes a new CT lung CAD method which aims to detect solid nodules. Specially, we proposed a multi-kernel classifier with a ℓ 2, 1 norm regularizer for heterogeneous feature fusion and selection from the feature subset level, and designed two efficient strategies to optimize the parameters of kernel weights in non-smooth ℓ 2, 1 regularized multiple kernel learning algorithm. The first optimization algorithm adapts a proximal gradient method for solving the ℓ 2, 1 norm of kernel weights, and use an accelerated method based on FISTA; the second one employs an iterative scheme based on an approximate gradient descent method. The results demonstrates that the FISTA-style accelerated proximal descent method is efficient for the ℓ 2, 1 norm formulation of multiple kernel learning with the theoretical guarantee of the convergence rate. Moreover, the experimental results demonstrate the effectiveness of the proposed methods in terms of Geometric mean (G-mean) and Area under the ROC curve (AUC), and significantly outperforms the competing methods. The proposed approach exhibits some remarkable advantages both in heterogeneous feature subsets fusion and classification phases. Compared with the fusion strategies of feature-level and decision level, the proposed ℓ 2, 1 norm multi-kernel learning algorithm is able to accurately fuse the complementary and heterogeneous feature sets, and automatically prune the irrelevant and redundant feature subsets to form a more discriminative feature set, leading a promising classification performance. Moreover, the proposed algorithm consistently outperforms the comparable classification approaches in the literature. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Setting the bar: divergent sociocultural norms for women's and men's ideal appearance in real-world contexts.

PubMed

Buote, Vanessa M; Wilson, Anne E; Strahan, Erin J; Gazzola, Stephanie B; Papps, Fiona

2011-09-01

Research suggests that exposure to sociocultural norms for idealized appearance can reduce both women's and men's body satisfaction. Despite comparable effects for both genders in the lab, in the "real-world" women's body satisfaction is chronically lower than men's. Real-world gender differences may arise from discrepancies in men's and women's everyday exposure to norms. Across eight studies using a variety of content analysis, survey, and experimental methods, we examine differences in sociocultural norms for ideal appearance pertaining to women and men in "daily life" contexts. We demonstrate that appearance norms encountered by women in daily life are more rigid, homogenous and pervasive than those for men, and that more messages implying the attainability of the ideal appearance are directed at women. Finally, experimental results show that homogeneous, rigid norms (like those typically encountered by women) are more harmful to body image than heterogeneous, flexible norms (like those typically encountered by men). Copyright © 2011 Elsevier Ltd. All rights reserved.

On the complexity and approximability of some Euclidean optimal summing problems

NASA Astrophysics Data System (ADS)

Eremeev, A. V.; Kel'manov, A. V.; Pyatkin, A. V.

2016-10-01

The complexity status of several well-known discrete optimization problems with the direction of optimization switching from maximum to minimum is analyzed. The task is to find a subset of a finite set of Euclidean points (vectors). In these problems, the objective functions depend either only on the norm of the sum of the elements from the subset or on this norm and the cardinality of the subset. It is proved that, if the dimension of the space is a part of the input, then all these problems are strongly NP-hard. Additionally, it is shown that, if the space dimension is fixed, then all the problems are NP-hard even for dimension 2 (on a plane) and there are no approximation algorithms with a guaranteed accuracy bound for them unless P = NP. It is shown that, if the coordinates of the input points are integer, then all the problems can be solved in pseudopolynomial time in the case of a fixed space dimension.

Social Support and Peer Norms Scales for Physical Activity in Adolescents

PubMed Central

Ling, Jiying; Robbins, Lorraine B.; Resnicow, Ken; Bakhoya, Marion

2015-01-01

Objectives To evaluate psychometric properties of a Social Support and Peer Norms Scale in 5th-7th grade urban girls. Methods Baseline data from 509 girls and test-retest data from another 94 girls in the Midwestern US were used. Results Cronbach's alpha was .83 for the Social Support Scale and .72 for the Peer Norms Scale, whereas test-re-test reliability was .78 for both scales. Exploratory factor analysis suggested a single factor structure for the Social Support Scale, and a 3-factor structure for the Peer Norms Scale. Social support was correlated with accelerometer-measured physical activity (r = .13, p = .006), and peer norms (r = .50, p < .0001). Conclusions Both scales have adequate psychometric properties. PMID:25207514

An L1-norm phase constraint for half-Fourier compressed sensing in 3D MR imaging.

PubMed

Li, Guobin; Hennig, Jürgen; Raithel, Esther; Büchert, Martin; Paul, Dominik; Korvink, Jan G; Zaitsev, Maxim

2015-10-01

In most half-Fourier imaging methods, explicit phase replacement is used. In combination with parallel imaging, or compressed sensing, half-Fourier reconstruction is usually performed in a separate step. The purpose of this paper is to report that integration of half-Fourier reconstruction into iterative reconstruction minimizes reconstruction errors. The L1-norm phase constraint for half-Fourier imaging proposed in this work is compared with the L2-norm variant of the same algorithm, with several typical half-Fourier reconstruction methods. Half-Fourier imaging with the proposed phase constraint can be seamlessly combined with parallel imaging and compressed sensing to achieve high acceleration factors. In simulations and in in-vivo experiments half-Fourier imaging with the proposed L1-norm phase constraint enables superior performance both reconstruction of image details and with regard to robustness against phase estimation errors. The performance and feasibility of half-Fourier imaging with the proposed L1-norm phase constraint is reported. Its seamless combination with parallel imaging and compressed sensing enables use of greater acceleration in 3D MR imaging.

Legislation on ethical issues: towards an interactive paradigm.

PubMed

van der Berg, W; Brom, F W A

2000-03-01

In this article, we sketch a new approach to law and ethics. The traditional paradigm, exemplified in the debate on liberal moralism, becomes increasingly inadequate. Its basic assumptions are that there are clear moral norms of positive or critical morality, and that making statutory norms is an effective methods to have citizens conform to those norms. However, for many ethical issues that are on the legislative agenda, e.g. with respect to bioethics and anti-discrimination law, the moral norms are controversial, vague or still evolving. Moreover, law proves not to be a very effective instrument. Therefore, we need a new paradigm, both for descriptive and for normative analysis. This interactive paradigm, as a normative position, can be summarised in two theses. The process of legislation on ethical issues should be structured as a process of interaction between the legislature and society, or relevant sectors of society, so that the development of new moral norms and the development of new legal norms may reinforce each other. And legislation on ethical issues should be designed in such a way that it is an effective form of communication which, moreover, facilitates an ongoing moral debate and an ongoing reflection of such issues, because this is the best method to ensure that the practice remains oriented to the ideals and values the law tries to realise.

Safe Ride Standards for Casualty Evacuation Using Unmanned Aerial Vehicles (Normes de transport sans danger pour l’evacuation des blesses par vehicules aeriens sans pilote)

DTIC Science & Technology

2012-12-01

requirements as part of an overall medical support concept In this document several potential CONOPS proposals are added as food for thought (see Chapter 4...safe flight minimums for manned flight; • En route or terminal environment (landing zone) is contaminated by an industrial spill or by a CBRN event...Further, the U.S. Food and Drug Administration (FDA) and other national/international medical regulatory authorities have requirements for portable

A Discontinuous Petrov-Galerkin Methodology for Adaptive Solutions to the Incompressible Navier-Stokes Equations

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

Roberts, Nathan V.; Demkowiz, Leszek; Moser, Robert

2015-11-15

The discontinuous Petrov-Galerkin methodology with optimal test functions (DPG) of Demkowicz and Gopalakrishnan [18, 20] guarantees the optimality of the solution in an energy norm, and provides several features facilitating adaptive schemes. Whereas Bubnov-Galerkin methods use identical trial and test spaces, Petrov-Galerkin methods allow these function spaces to differ. In DPG, test functions are computed on the fly and are chosen to realize the supremum in the inf-sup condition; the method is equivalent to a minimum residual method. For well-posed problems with sufficiently regular solutions, DPG can be shown to converge at optimal rates—the inf-sup constants governing the convergence aremore » mesh-independent, and of the same order as those governing the continuous problem [48]. DPG also provides an accurate mechanism for measuring the error, and this can be used to drive adaptive mesh refinements. We employ DPG to solve the steady incompressible Navier-Stokes equations in two dimensions, building on previous work on the Stokes equations, and focusing particularly on the usefulness of the approach for automatic adaptivity starting from a coarse mesh. We apply our approach to a manufactured solution due to Kovasznay as well as the lid-driven cavity flow, backward-facing step, and flow past a cylinder problems.« less

A Distributed Learning Method for ℓ1-Regularized Kernel Machine over Wireless Sensor Networks

PubMed Central

Ji, Xinrong; Hou, Cuiqin; Hou, Yibin; Gao, Fang; Wang, Shulong

2016-01-01

In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates ℓ1 norm regularization (ℓ1-regularized) is investigated, and a novel distributed learning algorithm for the ℓ1-regularized kernel minimum mean squared error (KMSE) machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN) test platform further shows the advantages of the proposed algorithm with respect to communication cost. PMID:27376298

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

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

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

Reduced rank regression via adaptive nuclear norm penalization

PubMed Central

Chen, Kun; Dong, Hongbo; Chan, Kung-Sik

2014-01-01

Summary We propose an adaptive nuclear norm penalization approach for low-rank matrix approximation, and use it to develop a new reduced rank estimation method for high-dimensional multivariate regression. The adaptive nuclear norm is defined as the weighted sum of the singular values of the matrix, and it is generally non-convex under the natural restriction that the weight decreases with the singular value. However, we show that the proposed non-convex penalized regression method has a global optimal solution obtained from an adaptively soft-thresholded singular value decomposition. The method is computationally efficient, and the resulting solution path is continuous. The rank consistency of and prediction/estimation performance bounds for the estimator are established for a high-dimensional asymptotic regime. Simulation studies and an application in genetics demonstrate its efficacy. PMID:25045172

Norms and stigma regarding pregnancy decisions during an unintended pregnancy: Development and predictors of scales among young women in the U.S. South

PubMed Central

Turan, Bulent; Stringer, Kristi L.; Helova, Anna; White, Kari; Cockrill, Kate; Turan, Janet M.

2017-01-01

Background Norms and stigma regarding pregnancy decisions (parenting, adoption, and abortion) are salient to maternal well-being, particularly for groups disproportionately affected by unintended pregnancy. However, there are few validated measures of individual-level perceptions of norms and stigma around pregnancy decisions. Additionally, little is known about variation in the content of norms regarding pregnancy decisions, and in stigma related to violations of these norms, across socio-demographic groups. Methods To create measures of perceived norms and stigma around pregnancy decisions, we developed and pre-tested 97 survey items using a mixed methods approach. The resulting survey was administered to 642 young adult women recruited from health department clinics and a public university campus in Birmingham, Alabama. Principal components factor analyses, reliability analyses, independent t-tests, and correlation analyses were conducted to establish the reliability and validity of scales. Additionally, multiple linear regression was used to identify demographic predictors of higher scale scores. Results Factor analyses revealed four subscales for each pregnancy decision: conditional acceptability, anticipated reactions, stereotypes/misperceptions, and attitudes. The total scales and their subscales demonstrated good internal reliability (alpha coefficients 0.72–0.94). The mean scores for each scale were significantly associated with each other, with related measures, and differed by sociodemographic characteristics. Specifically, in adjusted analyses, women in the university setting and White women expressed more negative attitudes and stigma around parenting. Minority women endorsed more negative norms and stigma around adoption. Finally, women from the health department, White women, and religious women expressed more negative norms and stigma around abortion. Conclusion Findings suggest that our multidimensional measures have good psychometric properties in our sample of young women in the U.S. South, and highlight the importance of conceptualizing and measuring norms and stigmas around all pregnancy decisions. These scales may be of use in research on pregnancy decision-making and evaluation of stigma-reduction interventions. PMID:28328960

Community Norms, Enforcement Of Minimum Legal Drinking Age Laws, Personal Beliefs And Underage Drinking: An Explanatory Model

PubMed Central

Grube, Joel W.; Paschall, Mallie J.

2009-01-01

Strategies to enforce underage drinking laws are aimed at reducing youth access to alcohol from commercial and social sources and deterring its possession and use. However, little is known about the processes through which enforcement strategies may affect underage drinking. The purpose of the current study is to present and test a conceptual model that specifies possible direct and indirect relationships among adolescents’ perception of community alcohol norms, enforcement of underage drinking laws, personal beliefs (perceived parental disapproval of alcohol use, perceived alcohol availability, perceived drinking by peers, perceived harm and personal disapproval of alcohol use), and their past-30-day alcohol use. This study used data from 17,830 middle and high school students who participated in the 2007 Oregon Health Teens Survey. Structural equations modeling indicated that perceived community disapproval of adolescents’ alcohol use was directly and positively related to perceived local police enforcement of underage drinking laws. In addition, adolescents’ personal beliefs appeared to mediate the relationship between perceived enforcement of underage drinking laws and past-30-day alcohol use. Enforcement of underage drinking laws appeared to partially mediate the relationship between perceived community disapproval and personal beliefs related to alcohol use. Results of this study suggests that environmental prevention efforts to reduce underage drinking should target adults’ attitudes and community norms about underage drinking as well as the beliefs of youth themselves. PMID:20135210

Mixed model approaches for diallel analysis based on a bio-model.

PubMed

Zhu, J; Weir, B S

1996-12-01

A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

Application of Fuzzy TOPSIS for evaluating machining techniques using sustainability metrics

NASA Astrophysics Data System (ADS)

Digalwar, Abhijeet K.

2018-04-01

Sustainable processes and techniques are getting increased attention over the last few decades due to rising concerns over the environment, improved focus on productivity and stringency in environmental as well as occupational health and safety norms. The present work analyzes the research on sustainable machining techniques and identifies techniques and parameters on which sustainability of a process is evaluated. Based on the analysis these parameters are then adopted as criteria’s to evaluate different sustainable machining techniques such as Cryogenic Machining, Dry Machining, Minimum Quantity Lubrication (MQL) and High Pressure Jet Assisted Machining (HPJAM) using a fuzzy TOPSIS framework. In order to facilitate easy arithmetic, the linguistic variables represented by fuzzy numbers are transformed into crisp numbers based on graded mean representation. Cryogenic machining was found to be the best alternative sustainable technique as per the fuzzy TOPSIS framework adopted. The paper provides a method to deal with multi criteria decision making problems in a complex and linguistic environment.

Minimum Sobolev norm interpolation of scattered derivative data

NASA Astrophysics Data System (ADS)

Chandrasekaran, S.; Gorman, C. H.; Mhaskar, H. N.

2018-07-01

We study the problem of reconstructing a function on a manifold satisfying some mild conditions, given data of the values and some derivatives of the function at arbitrary points on the manifold. While the problem of finding a polynomial of two variables with total degree ≤n given the values of the polynomial and some of its derivatives at exactly the same number of points as the dimension of the polynomial space is sometimes impossible, we show that such a problem always has a solution in a very general situation if the degree of the polynomials is sufficiently large. We give estimates on how large the degree should be, and give explicit constructions for such a polynomial even in a far more general case. As the number of sampling points at which the data is available increases, our polynomials converge to the target function on the set where the sampling points are dense. Numerical examples in single and double precision show that this method is stable, efficient, and of high-order.

Global synchronization of complex dynamical networks through digital communication with limited data rate.

PubMed

Wang, Yan-Wu; Bian, Tao; Xiao, Jiang-Wen; Wen, Changyun

2015-10-01

This paper studies the global synchronization of complex dynamical network (CDN) under digital communication with limited bandwidth. To realize the digital communication, the so-called uniform-quantizer-sets are introduced to quantize the states of nodes, which are then encoded and decoded by newly designed encoders and decoders. To meet the requirement of the bandwidth constraint, a scaling function is utilized to guarantee the quantizers having bounded inputs and thus achieving bounded real-time quantization levels. Moreover, a new type of vector norm is introduced to simplify the expression of the bandwidth limit. Through mathematical induction, a sufficient condition is derived to ensure global synchronization of the CDNs. The lower bound on the sum of the real-time quantization levels is analyzed for different cases. Optimization method is employed to relax the requirements on the network topology and to determine the minimum of such lower bound for each case, respectively. Simulation examples are also presented to illustrate the established results.

An exploratory cluster randomised trial of a university halls of residence based social norms intervention in Wales, UK

PubMed Central

2012-01-01

Background Excessive alcohol consumption amongst university students has received increasing attention. A social norms approach to reducing drinking behaviours has met with some success in the USA. Such an approach is based on the assumption that student's perceptions of the norms of their peers are highly influential, but that these perceptions are often incorrect. Social norms interventions therefore aim to correct these inaccurate perceptions, and in turn, to change behaviours. However, UK studies are scarce and it is increasingly recognised that social norm interventions need to be supported by socio ecological approaches that address the wider determinants of behaviour. Objectives To describe the research design for an exploratory trial examining the acceptability, hypothesised process of change and implementation of a social norm marketing campaign designed to correct misperceptions of normative alcohol use and reduce levels of misuse, implemented alongside a university wide alcohol harm reduction toolkit. It also assesses the feasibility of a potential large scale effectiveness trial by providing key trial design parameters including randomisation, recruitment and retention, contamination, data collection methods, outcome measures and intracluster correlations. Methods/design The study adopts an exploratory cluster randomised controlled trial design with halls of residence as the unit of allocation, and a nested mixed methods process evaluation. Four Welsh (UK) universities participated in the study, with residence hall managers consenting to implementation of the trial in 50 university owned campus based halls of residence. Consenting halls were randomised to either a phased multi channel social norm marketing campaign addressing normative discrepancies (n = 25 intervention) or normal practice (n = 25 control). The primary outcome is alcohol consumption (units per week) measured using the Daily Drinking Questionnaire. Secondary outcomes assess frequency of alcohol consumption, higher risk drinking, alcohol related problems and change in perceptions of alcohol-related descriptive and injunctive norms. Data will be collected for all 50 halls at 4 months follow up through a cross-sectional on line and postal survey of approximately 4000 first year students. The process evaluation will explore the acceptability and implementation of the social norms intervention and toolkit and hypothesised process of change including awareness, receptivity and normative changes. Discussion Exploratory trials such as this are essential to inform future definitive trials by providing crucial methodological parameters and guidance on designing and implementing optimum interventions. Trial registration number ISRCTN: ISRCTN48556384 PMID:22414293

Method and matter in the social sciences: Umbilically tied to the Enlightenment.

PubMed

Beit-Hallahmi, Benjamin

2015-01-01

This commentary deals with the nonconformity of academics and the ethos of social science. Academics in all fields deviate from majority norms in politics and religion, and this deviance may be essential to the academic mind and to academic norms. The Enlightenment legacy inspires both methods and subject matter in academic work, and severing ties with it may be impossible.

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.

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.

Geochemical signature of NORM waste in Brazilian oil and gas industry.

PubMed

De-Paula-Costa, G T; Guerrante, I C; Costa-de-Moura, J; Amorim, F C

2018-09-01

The Brazilian Nuclear Energy Agency (CNEN) is responsible for any radioactive waste storage and disposal in the country. The storage of radioactive waste is carried out in the facilities under CNEN regulation and its disposal is operated, managed and controlled by the CNEN. Oil NORM (Naturally Occurring Radioactive Materials) in this article refers to waste coming from oil exploitation. Oil NORM has called much attention during the last decades, mostly because it is not possible to determine its primary source due to the actual absence of a regulatory control mechanism. There is no efficient regulatory tool which allows determining the origin of such NORM wastes even among those facilities under regulatory control. This fact may encourage non-authorized radioactive material transportation, smuggling and terrorism. The aim of this project is to provide a geochemical signature for oil NORM waste using its naturally occurring isotopic composition to identify its origin. The here proposed method is the modeling of radioisotopes normally present in oil pipe contamination such as 228 Ac, 214 Bi and 214 Pb analyzed by gamma spectrometry. The specific activities of elements from different decay series are plotted in a scatter diagram. This method was successfully tested with gamma spectrometry analyses of oil sludge NORM samples from four different sources obtained from Petrobras reports for the Campos Basin/Brazil. Copyright © 2018 Elsevier Ltd. All rights reserved.

Automated ambiguity estimation for VLBI Intensive sessions using L1-norm

NASA Astrophysics Data System (ADS)

Kareinen, Niko; Hobiger, Thomas; Haas, Rüdiger

2016-12-01

Very Long Baseline Interferometry (VLBI) is a space-geodetic technique that is uniquely capable of direct observation of the angle of the Earth's rotation about the Celestial Intermediate Pole (CIP) axis, namely UT1. The daily estimates of the difference between UT1 and Coordinated Universal Time (UTC) provided by the 1-h long VLBI Intensive sessions are essential in providing timely UT1 estimates for satellite navigation systems and orbit determination. In order to produce timely UT1 estimates, efforts have been made to completely automate the analysis of VLBI Intensive sessions. This involves the automatic processing of X- and S-band group delays. These data contain an unknown number of integer ambiguities in the observed group delays. They are introduced as a side-effect of the bandwidth synthesis technique, which is used to combine correlator results from the narrow channels that span the individual bands. In an automated analysis with the c5++ software the standard approach in resolving the ambiguities is to perform a simplified parameter estimation using a least-squares adjustment (L2-norm minimisation). We implement L1-norm as an alternative estimation method in c5++. The implemented method is used to automatically estimate the ambiguities in VLBI Intensive sessions on the Kokee-Wettzell baseline. The results are compared to an analysis set-up where the ambiguity estimation is computed using the L2-norm. For both methods three different weighting strategies for the ambiguity estimation are assessed. The results show that the L1-norm is better at automatically resolving the ambiguities than the L2-norm. The use of the L1-norm leads to a significantly higher number of good quality UT1-UTC estimates with each of the three weighting strategies. The increase in the number of sessions is approximately 5% for each weighting strategy. This is accompanied by smaller post-fit residuals in the final UT1-UTC estimation step.

Probabilistic maturation reaction norms assessed from mark–recaptures of wild fish in their natural habitat

PubMed Central

Olsen, Esben M; Serbezov, Dimitar; Vøllestad, Leif A

2014-01-01

Reaction norms are a valuable tool in evolutionary biology. Lately, the probabilistic maturation reaction norm approach, describing probabilities of maturing at combinations of age and body size, has been much applied for testing whether phenotypic changes in exploited populations of fish are mainly plastic or involving an evolutionary component. However, due to typical field data limitations, with imperfect knowledge about individual life histories, this demographic method still needs to be assessed. Using 13 years of direct mark–recapture observations on individual growth and maturation in an intensively sampled population of brown trout (Salmo trutta), we show that the probabilistic maturation reaction norm approach may perform well even if the assumption of equal survival of juvenile and maturing fish does not hold. Earlier studies have pointed out that growth effects may confound the interpretation of shifts in maturation reaction norms, because this method in its basic form deals with body size rather than growth. In our case, however, we found that juvenile body size, rather than annual growth, was more strongly associated with maturation. Viewed against earlier studies, our results also underscore the challenges of generalizing life-history patterns among species and populations. PMID:24967078

Determinants of Aggression Toward Sexual Minorities in a Community Sample

PubMed Central

Parrott, Dominic J.; Peterson, John L.; Bakeman, Roger

2011-01-01

Objective Sexual prejudice and masculine gender role stress were examined as mediators of the associations between adherence to different male gender norms and aggression toward sexual minorities. This study also sought to extend past research to a community sample and employ multiple methods to assess aggression. Method Participants were 199 heterosexual men between the ages of 18–30 who were recruited from a large southeastern United States city. Participants completed measures of adherence to male gender role norms, sexual prejudice, masculine gender role stress, and aggression toward sexual minorities. Results Associations between adherence to the status and antifemininity norms and aggression toward sexual minorities were mediated by sexual prejudice, but not masculine gender role stress. The portion of unique association between adherence to the antifemininity norm and aggression toward sexual minorities was about three times larger than the portion mediated by sexual prejudice and masculine gender role stress. Conclusions Findings provide the first multivariate evidence from a community-based sample for determinants of aggression toward sexual minorities motivated by gender role enforcement. These data support intervention programming and preventative intervention studies aimed at reducing sexual prejudice and facilitating less stereotypic attitudes about the male gender role, particularly surrounding the antifemininity norm. PMID:21479161

Experimental/clinical evaluation of EIT image reconstruction with l1 data and image norms

NASA Astrophysics Data System (ADS)

Mamatjan, Yasin; Borsic, Andrea; Gürsoy, Doga; Adler, Andy

2013-04-01

Electrical impedance tomography (EIT) image reconstruction is ill-posed, and the spatial resolution of reconstructed images is low due to the diffuse propagation of current and limited number of independent measurements. Generally, image reconstruction is formulated using a regularized scheme in which l2 norms are preferred for both the data misfit and image prior terms due to computational convenience which result in smooth solutions. However, recent work on a Primal Dual-Interior Point Method (PDIPM) framework showed its effectiveness in dealing with the minimization problem. l1 norms on data and regularization terms in EIT image reconstruction address both problems of reconstruction with sharp edges and dealing with measurement errors. We aim for a clinical and experimental evaluation of the PDIPM method by selecting scenarios (human lung and dog breathing) with known electrode errors, which require a rigorous regularization and cause the failure of reconstructions with l2 norm. Results demonstrate the applicability of PDIPM algorithms, especially l1 data and regularization norms for clinical applications of EIT showing that l1 solution is not only more robust to measurement errors in clinical setting, but also provides high contrast resolution on organ boundaries.

Punish and voice: punishment enhances cooperation when combined with norm-signalling.

PubMed

Andrighetto, Giulia; Brandts, Jordi; Conte, Rosaria; Sabater-Mir, Jordi; Solaz, Hector; Villatoro, Daniel

2013-01-01

Material punishment has been suggested to play a key role in sustaining human cooperation. Experimental findings, however, show that inflicting mere material costs does not always increase cooperation and may even have detrimental effects. Indeed, ethnographic evidence suggests that the most typical punishing strategies in human ecologies (e.g., gossip, derision, blame and criticism) naturally combine normative information with material punishment. Using laboratory experiments with humans, we show that the interaction of norm communication and material punishment leads to higher and more stable cooperation at a lower cost for the group than when used separately. In this work, we argue and provide experimental evidence that successful human cooperation is the outcome of the interaction between instrumental decision-making and the norm psychology humans are provided with. Norm psychology is a cognitive machinery to detect and reason upon norms that is characterized by a salience mechanism devoted to track how much a norm is prominent within a group. We test our hypothesis both in the laboratory and with an agent-based model. The agent-based model incorporates fundamental aspects of norm psychology absent from previous work. The combination of these methods allows us to provide an explanation for the proximate mechanisms behind the observed cooperative behaviour. The consistency between the two sources of data supports our hypothesis that cooperation is a product of norm psychology solicited by norm-signalling and coercive devices.

Social anxiety and cannabis-related impairment: The synergistic influences of peer and parent descriptive and injunctive normative perceptions

PubMed Central

Foster, Dawn W.; Garey, Lorra; Buckner, Julia D.; Zvolensky, Michael J.

2016-01-01

Objectives 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. Methods 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 × parent injunctive norms × peer norms interaction terms on cannabis use behaviors. Results 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. Conclusions The present work suggest 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. PMID:27144526

Punish and Voice: Punishment Enhances Cooperation when Combined with Norm-Signalling

PubMed Central

Andrighetto, Giulia; Brandts, Jordi; Conte, Rosaria; Sabater-Mir, Jordi; Solaz, Hector; Villatoro, Daniel

2013-01-01

Material punishment has been suggested to play a key role in sustaining human cooperation. Experimental findings, however, show that inflicting mere material costs does not always increase cooperation and may even have detrimental effects. Indeed, ethnographic evidence suggests that the most typical punishing strategies in human ecologies (e.g., gossip, derision, blame and criticism) naturally combine normative information with material punishment. Using laboratory experiments with humans, we show that the interaction of norm communication and material punishment leads to higher and more stable cooperation at a lower cost for the group than when used separately. In this work, we argue and provide experimental evidence that successful human cooperation is the outcome of the interaction between instrumental decision-making and the norm psychology humans are provided with. Norm psychology is a cognitive machinery to detect and reason upon norms that is characterized by a salience mechanism devoted to track how much a norm is prominent within a group. We test our hypothesis both in the laboratory and with an agent-based model. The agent-based model incorporates fundamental aspects of norm psychology absent from previous work. The combination of these methods allows us to provide an explanation for the proximate mechanisms behind the observed cooperative behaviour. The consistency between the two sources of data supports our hypothesis that cooperation is a product of norm psychology solicited by norm-signalling and coercive devices. PMID:23776441

Variance in State Protection from Exposure to NORM and TENORM Wastes Generated During Unconventional Oil and Gas Operations: Where We Are and Where We Need to Go.

PubMed

Ann Glass Geltman, Elizabeth; LeClair, Nichole

2018-01-01

Radioactive materials for the medical, technological, and industrial sectors have been effectively regulated in the United States since as early as 1962. The steady increase in the exploration and production of shale gas in recent years has led to concerns about exposures to Naturally Occurring Radioactive Materials (NORM) and Technologically Enhanced Naturally Occurring Radioactive Materials (TENORM) in oil and gas waste streams. This study applied policy surveillance methods to conduct a cross-sectional fifty-state survey of law and regulations of NORM and TENORM waste from oil and gas operations. Results indicated that seventeen states drafted express regulations to reduce exposure to oil and gas NORM and TENORM waste. States with active oil and gas drilling that lack regulations controlling exposure to NORM and TENORM may leave the public and workers susceptible to adverse health effects from radiation. The study concludes with recommendations in regard to regulating oil and gas NORM and TENORM waste.

Successfully recruiting, surveying, and retaining college students: a description of methods for the Risk, Religiosity, and Emerging Adulthood Study.

PubMed

Berry, Devon M; Bass, Colleen P

2012-12-01

The selection of methods that purposefully reflect the norms of the target population increases the likelihood of effective recruitment, data collection, and retention. In the case of research among college students, researchers' appreciation of college student norms might be skewed by unappreciated generational and developmental differences. Our purpose in this article is to illustrate how attention to the generational and developmental characteristics of college students enhanced the methods of the Risk, Religiosity, and Emerging Adulthood study. We address the following challenges related to research with college students: recruitment, communication, data collection, and retention. Solutions incorporating Internet-based applications (e.g., Facebook) and sensitivity to the generational norms of participants (e.g., multiple means of communication) are described in detail. Copyright © 2012 Wiley Periodicals, Inc.

On the sparseness of 1-norm support vector machines.

PubMed

Zhang, Li; Zhou, Weida

2010-04-01

There is some empirical evidence available showing that 1-norm Support Vector Machines (1-norm SVMs) have good sparseness; however, both how good sparseness 1-norm SVMs can reach and whether they have a sparser representation than that of standard SVMs are not clear. In this paper we take into account the sparseness of 1-norm SVMs. Two upper bounds on the number of nonzero coefficients in the decision function of 1-norm SVMs are presented. First, the number of nonzero coefficients in 1-norm SVMs is at most equal to the number of only the exact support vectors lying on the +1 and -1 discriminating surfaces, while that in standard SVMs is equal to the number of support vectors, which implies that 1-norm SVMs have better sparseness than that of standard SVMs. Second, the number of nonzero coefficients is at most equal to the rank of the sample matrix. A brief review of the geometry of linear programming and the primal steepest edge pricing simplex method are given, which allows us to provide the proof of the two upper bounds and evaluate their tightness by experiments. Experimental results on toy data sets and the UCI data sets illustrate our analysis. Copyright 2009 Elsevier Ltd. All rights reserved.

Color TV: total variation methods for restoration of vector-valued images.

PubMed

Blomgren, P; Chan, T F

1998-01-01

We propose a new definition of the total variation (TV) norm for vector-valued functions that can be applied to restore color and other vector-valued images. The new TV norm has the desirable properties of 1) not penalizing discontinuities (edges) in the image, 2) being rotationally invariant in the image space, and 3) reducing to the usual TV norm in the scalar case. Some numerical experiments on denoising simple color images in red-green-blue (RGB) color space are presented.

Human rights education in patient care.

PubMed

Erdman, Joanna N

2017-01-01

This article explores how human rights education in the health professions can build knowledge, change culture, and empower advocacy. Through a study of educational initiatives in the field, the article analyzes different methods by which health professionals come to see the relevance of human rights norms for their work, to habituate these norms in everyday practice, and to espouse these norms in advocacy for social justice. The article seeks to show the transformative potential of education for human rights in patient care.

A Gaussian-based rank approximation for subspace clustering

NASA Astrophysics Data System (ADS)

Xu, Fei; Peng, Chong; Hu, Yunhong; He, Guoping

2018-04-01

Low-rank representation (LRR) has been shown successful in seeking low-rank structures of data relationships in a union of subspaces. Generally, LRR and LRR-based variants need to solve the nuclear norm-based minimization problems. Beyond the success of such methods, it has been widely noted that the nuclear norm may not be a good rank approximation because it simply adds all singular values of a matrix together and thus large singular values may dominant the weight. This results in far from satisfactory rank approximation and may degrade the performance of lowrank models based on the nuclear norm. In this paper, we propose a novel nonconvex rank approximation based on the Gaussian distribution function, which has demanding properties to be a better rank approximation than the nuclear norm. Then a low-rank model is proposed based on the new rank approximation with application to motion segmentation. Experimental results have shown significant improvements and verified the effectiveness of our method.

Evaluating the implementation of RxNorm in ambulatory electronic prescriptions

PubMed Central

Ward-Charlerie, Stacy; Rupp, Michael T; Kilbourne, John; Amin, Vishal P; Ruiz, Joshua

2016-01-01

Objective RxNorm is a standardized drug nomenclature maintained by the National Library of Medicine that has been recommended as an alternative to the National Drug Code (NDC) terminology for use in electronic prescribing. The objective of this study was to evaluate the implementation of RxNorm in ambulatory care electronic prescriptions (e-prescriptions). Methods We analyzed a random sample of 49 997 e-prescriptions that were received by 7391 locations of a national retail pharmacy chain during a single day in April 2014. The e-prescriptions in the sample were generated by 37 801 ambulatory care prescribers using 519 different e-prescribing software applications. Results We found that 97.9% of e-prescriptions in the study sample could be accurately represented by an RxNorm identifier. However, RxNorm identifiers were actually used as drug identifiers in only 16 433 (33.0%) e-prescriptions. Another 431 (2.5%) e-prescriptions that used RxNorm identifiers had a discrepancy in the corresponding Drug Database Code qualifier field or did not have a qualifier (Term Type) at all. In 10 e-prescriptions (0.06%), the free-text drug description and the RxNorm concept unique identifier pointed to completely different drug concepts, and in 7 e-prescriptions (0.04%), the NDC and RxNorm drug identifiers pointed to completely different drug concepts. Discussion The National Library of Medicine continues to enhance the RxNorm terminology and expand its scope. This study illustrates the need for technology vendors to improve their implementation of RxNorm; doing so will accelerate the adoption of RxNorm as the preferred alternative to using the NDC terminology in e-prescribing. PMID:26510879

Social Goals and Grade as Moderators of Social Normative Influences on Adolescent Alcohol Use

PubMed Central

Meisel, Samuel N.; Colder, Craig R.

2016-01-01

Background The literature distinguishes two types of social normative influences on adolescent alcohol use, descriptive norms (perceived peer alcohol use) and injunctive norms (perceived approval of drinking). Although theoretical formulations suggest variability in the salience and influence of descriptive and injunctive norms, little is understood regarding for whom and when social norms influence adolescent drinking. Strong agentic and communal social goals were hypothesized to moderate the influence of descriptive and injunctive norms on early adolescent alcohol use, respectively. Developmental changes were also expected, such that these moderating effects were expected to get stronger at later grades. Methods This longitudinal study included 387 adolescents and 4 annual assessments (spanning 6th to 10th grade). Participants completed questionnaire measures of social goals, social norms, and alcohol use at each wave. Results Multilevel logistic regressions were used to test prospective associations. As hypothesized, descriptive norms predicted increases in the probability of alcohol use for adolescents with strong agentic goals, but only in later grades. Injunctive norms were associated with increases in the probability of drinking for adolescents with low communal goals at earlier grades, whereas injunctive norms were associated with an increased probability of drinking for adolescents with either low or high communal goals at later grades. Although not hypothesized, descriptive norms predicted increases in the probability of drinking for adolescents high in communal goals in earlier grades whereas descriptive norms predicted drinking for adolescents characterized by low communal goals in later grades. Conclusions The current study highlights the importance of social goals when considering social normative influences on alcohol use in early and middle adolescence. These findings have implications for whom and when normative feedback interventions might be most effective during this developmental period. PMID:26554341

Macro-level Age Norms for the Timing of Sexual Initiation and Adolescents’ Early Sexual Initiation in 17 European Countries

PubMed Central

Madkour, Aubrey Spriggs; de Looze, Margaretha; Ma, Ping; Halpern, Carolyn Tucker; Farhat, Tilda; ter Bogt, Tom F. M.; Ehlinger, Virginie; Nic Gabhainn, Saoirse; Currie, Candace; Godeau, Emmanuelle

2014-01-01

Purpose To examine the relationship between country-level age norms for sexual initiation timing and early sexual initiation (ESI) among adolescent boys and girls. Methods Nationally-representative data from 17 countries that participated in the 2006/07 European Social Survey (ESS-3, n=33,092) and the 2005/06 Health Behaviour in School-Aged Children Study (HBSC, n=27,702) were analyzed. Age norms were measured as the average country-level response to an item asking the age at which ESS respondents believed someone is too young to have sexual intercourse. HBSC respondents (aged 14-16) self-reported age at sexual initiation which we defined as early (<15 years) or not (≥15 years or no initiation). Control variables included age, family affluence, perceived socioeconomic status, family living arrangement, substance use, school attachment, and country-level legal age of consent. Multivariable three-level logistic models with random intercepts were run separately by sex. Results In multivariable analyses, higher overall age norms were associated with reduced likelihood of ESI among girls (AOR 0.60, 95% CI 0.45-0.79); associations with ESI were stronger for parent cohort (ages 31-65) norms (AOR 0.37, 95% CI 0.23-0.58) than for peer cohort (ages 15-20) norms (AOR 0.60, 95% CI 0.49-0.74). For boys, overall norms were also significantly negatively associated with ESI (AOR 0.68, 95% CI 0.46-0.99), as were parent cohort norms (AOR 0.66, 95% CI 0.45-0.96). Peer cohort norms were not significantly related to boys’ ESI. Conclusion Macro-level cultural norms may impact adolescents’ sexual initiation timing. Research exploring the sexual health outcomes of early initiators in countries with contrasting age norms is warranted. PMID:24508092

Reliable estimation of orbit errors in spaceborne SAR interferometry. The network approach

NASA Astrophysics Data System (ADS)

Bähr, Hermann; Hanssen, Ramon F.

2012-12-01

An approach to improve orbital state vectors by orbit error estimates derived from residual phase patterns in synthetic aperture radar interferograms is presented. For individual interferograms, an error representation by two parameters is motivated: the baseline error in cross-range and the rate of change of the baseline error in range. For their estimation, two alternatives are proposed: a least squares approach that requires prior unwrapping and a less reliable gridsearch method handling the wrapped phase. In both cases, reliability is enhanced by mutual control of error estimates in an overdetermined network of linearly dependent interferometric combinations of images. Thus, systematic biases, e.g., due to unwrapping errors, can be detected and iteratively eliminated. Regularising the solution by a minimum-norm condition results in quasi-absolute orbit errors that refer to particular images. For the 31 images of a sample ENVISAT dataset, orbit corrections with a mutual consistency on the millimetre level have been inferred from 163 interferograms. The method itself qualifies by reliability and rigorous geometric modelling of the orbital error signal but does not consider interfering large scale deformation effects. However, a separation may be feasible in a combined processing with persistent scatterer approaches or by temporal filtering of the estimates.

Scalable learning method for feedforward neural networks using minimal-enclosing-ball approximation.

PubMed

Wang, Jun; Deng, Zhaohong; Luo, Xiaoqing; Jiang, Yizhang; Wang, Shitong

2016-06-01

Training feedforward neural networks (FNNs) is one of the most critical issues in FNNs studies. However, most FNNs training methods cannot be directly applied for very large datasets because they have high computational and space complexity. In order to tackle this problem, the CCMEB (Center-Constrained Minimum Enclosing Ball) problem in hidden feature space of FNN is discussed and a novel learning algorithm called HFSR-GCVM (hidden-feature-space regression using generalized core vector machine) is developed accordingly. In HFSR-GCVM, a novel learning criterion using L2-norm penalty-based ε-insensitive function is formulated and the parameters in the hidden nodes are generated randomly independent of the training sets. Moreover, the learning of parameters in its output layer is proved equivalent to a special CCMEB problem in FNN hidden feature space. As most CCMEB approximation based machine learning algorithms, the proposed HFSR-GCVM training algorithm has the following merits: The maximal training time of the HFSR-GCVM training is linear with the size of training datasets and the maximal space consumption is independent of the size of training datasets. The experiments on regression tasks confirm the above conclusions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sun-Direction Estimation Using a Partially Underdetermined Set of Coarse Sun Sensors

NASA Astrophysics Data System (ADS)

O'Keefe, Stephen A.; Schaub, Hanspeter

2015-09-01

A comparison of different methods to estimate the sun-direction vector using a partially underdetermined set of cosine-type coarse sun sensors (CSS), while simultaneously controlling the attitude towards a power-positive orientation, is presented. CSS are commonly used in performing power-positive sun-pointing and are attractive due to their relative inexpensiveness, small size, and reduced power consumption. For this study only CSS and rate gyro measurements are available, and the sensor configuration does not provide global triple coverage required for a unique sun-direction calculation. The methods investigated include a vector average method, a combination of least squares and minimum norm criteria, and an extended Kalman filter approach. All cases are formulated such that precise ground calibration of the CSS is not required. Despite significant biases in the state dynamics and measurement models, Monte Carlo simulations show that an extended Kalman filter approach, despite the underdetermined sensor coverage, can provide degree-level accuracy of the sun-direction vector both with and without a control algorithm running simultaneously. If no rate gyro measurements are available, and rates are partially estimated from CSS, the EKF performance degrades as expected, but is still able to achieve better than 10∘ accuracy using only CSS measurements.

How many infants are temperamentally difficult? Comparing norms from the Revised Infant Temperament Questionnaire to a population sample of UK infants.

PubMed

Chong, Shiau Yun; Chittleborough, Catherine R; Gregory, Tess; Lynch, John W; Smithers, Lisa G

2015-08-01

The original norms for the Revised Infant Temperament Questionnaire (RITQ) were published in 1978 and were based on a small sample from the US. The aim of this study is to compare temperament scores from the original RITQ against scores from a large population-based cohort of infants from the UK. This study consists of 10,937 infants from the Avon Longitudinal Study of Parents and Children (ALSPAC) born between April 1991 and December 1992 in the southwest of England. Infant temperament at 6 months of age was reported by parents using the adapted RITQ. Responses were scored according to the RITQ manual and then categorized into temperament groups (easy, intermediate low, intermediate high, and difficult) using either the RITQ norms or norms derived from the data. The scores for each temperament subscale and the proportion of children in each temperament group were compared across the two methods. Subscale scores for the ALSPAC sample were higher (more "difficult") than the RITQ norms for rhythmicity, approach, adaptability, intensity, and distractibility. When RITQ norms were applied, 24% infants were categorized as difficult and 25% as easy, compared with 15% difficult and 38% easy when ALSPAC norms were used. There are discrepancies between RITQ norms and the ALSPAC norms which resulted in differences in the distribution of temperament groups. There is a need to re-examine RITQ norms and categorization for use in primary care practice and contemporary population-based studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Using Facebook to deliver a social norm intervention to reduce problem drinking at university.

PubMed

Ridout, Brad; Campbell, Andrew

2014-11-01

University students usually overestimate peer alcohol use, resulting in them 'drinking up' to perceived norms. Social norms theory suggests correcting these inflated perceptions can reduce alcohol consumption. Recent findings by the current authors show portraying oneself as 'a drinker' is considered by many students to be a socially desirable component of their Facebook identity, perpetuating an online culture that normalises binge drinking. However, social networking sites have yet to be utilised in social norms interventions. Actual and perceived descriptive and injunctive drinking norms were collected from 244 university students. Ninety-five students screened positive for hazardous drinking and were randomly allocated to a control group or intervention group that received social norms feedback via personalised Facebook private messages over three sessions. At 1 month post-intervention, the quantity and frequency of alcohol consumed by intervention group during the previous month had significantly reduced compared with baseline and controls. Reductions were maintained 3 months post-intervention. Intervention group perceived drinking norms were significantly more accurate post-intervention. This is the first study to test the feasibility of using Facebook to deliver social norms interventions. Correcting misperceptions of peer drinking norms resulted in clinically significant reductions in alcohol use. Facebook has many advantages over traditional social norms delivery, providing an innovative method for tackling problem drinking at university. These results have implications for the use of Facebook to deliver positive messages about safe alcohol use to students, which may counter the negative messages regarding alcohol normally seen on Facebook. © 2014 Australasian Professional Society on Alcohol and other Drugs.

Joint Smoothed l₀-Norm DOA Estimation Algorithm for Multiple Measurement Vectors in MIMO Radar.

PubMed

Liu, Jing; Zhou, Weidong; Juwono, Filbert H

2017-05-08

Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement vector (MMV) case. In this paper, a novel fast sparse DOA estimation algorithm, named the joint smoothed l 0 -norm algorithm, is proposed for multiple measurement vectors in multiple-input multiple-output (MIMO) radar. To eliminate the white or colored Gaussian noises, the new method first obtains a low-complexity high-order cumulants based data matrix. Then, the proposed algorithm designs a joint smoothed function tailored for the MMV case, based on which joint smoothed l 0 -norm sparse representation framework is constructed. Finally, for the MMV-based joint smoothed function, the corresponding gradient-based sparse signal reconstruction is designed, thus the DOA estimation can be achieved. The proposed method is a fast sparse representation algorithm, which can solve the MMV problem and perform well for both white and colored Gaussian noises. The proposed joint algorithm is about two orders of magnitude faster than the l 1 -norm minimization based methods, such as l 1 -SVD (singular value decomposition), RV (real-valued) l 1 -SVD and RV l 1 -SRACV (sparse representation array covariance vectors), and achieves better DOA estimation performance.

Improving the Nulling Beamformer Using Subspace Suppression.

PubMed

Rana, Kunjan D; Hämäläinen, Matti S; Vaina, Lucia M

2018-01-01

Magnetoencephalography (MEG) captures the magnetic fields generated by neuronal current sources with sensors outside the head. In MEG analysis these current sources are estimated from the measured data to identify the locations and time courses of neural activity. Since there is no unique solution to this so-called inverse problem, multiple source estimation techniques have been developed. The nulling beamformer (NB), a modified form of the linearly constrained minimum variance (LCMV) beamformer, is specifically used in the process of inferring interregional interactions and is designed to eliminate shared signal contributions, or cross-talk, between regions of interest (ROIs) that would otherwise interfere with the connectivity analyses. The nulling beamformer applies the truncated singular value decomposition (TSVD) to remove small signal contributions from a ROI to the sensor signals. However, ROIs with strong crosstalk will have high separating power in the weaker components, which may be removed by the TSVD operation. To address this issue we propose a new method, the nulling beamformer with subspace suppression (NBSS). This method, controlled by a tuning parameter, reweights the singular values of the gain matrix mapping from source to sensor space such that components with high overlap are reduced. By doing so, we are able to measure signals between nearby source locations with limited cross-talk interference, allowing for reliable cortical connectivity analysis between them. In two simulations, we demonstrated that NBSS reduces cross-talk while retaining ROIs' signal power, and has higher separating power than both the minimum norm estimate (MNE) and the nulling beamformer without subspace suppression. We also showed that NBSS successfully localized the auditory M100 event-related field in primary auditory cortex, measured from a subject undergoing an auditory localizer task, and suppressed cross-talk in a nearby region in the superior temporal sulcus.

Bayesian estimation of realized stochastic volatility model by Hybrid Monte Carlo algorithm

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2014-03-01

The hybrid Monte Carlo algorithm (HMCA) is applied for Bayesian parameter estimation of the realized stochastic volatility (RSV) model. Using the 2nd order minimum norm integrator (2MNI) for the molecular dynamics (MD) simulation in the HMCA, we find that the 2MNI is more efficient than the conventional leapfrog integrator. We also find that the autocorrelation time of the volatility variables sampled by the HMCA is very short. Thus it is concluded that the HMCA with the 2MNI is an efficient algorithm for parameter estimations of the RSV model.

A modified two-layer iteration via a boundary point approach to generalized multivalued pseudomonotone mixed variational inequalities.

PubMed

Saddeek, Ali Mohamed

2017-01-01

Most mathematical models arising in stationary filtration processes as well as in the theory of soft shells can be described by single-valued or generalized multivalued pseudomonotone mixed variational inequalities with proper convex nondifferentiable functionals. Therefore, for finding the minimum norm solution of such inequalities, the current paper attempts to introduce a modified two-layer iteration via a boundary point approach and to prove its strong convergence. The results here improve and extend the corresponding recent results announced by Badriev, Zadvornov and Saddeek (Differ. Equ. 37:934-942, 2001).

On the functional optimization of a certain class of nonstationary spatial functions

USGS Publications Warehouse

Christakos, G.; Paraskevopoulos, P.N.

1987-01-01

Procedures are developed in order to obtain optimal estimates of linear functionals for a wide class of nonstationary spatial functions. These procedures rely on well-established constrained minimum-norm criteria, and are applicable to multidimensional phenomena which are characterized by the so-called hypothesis of inherentity. The latter requires elimination of the polynomial, trend-related components of the spatial function leading to stationary quantities, and also it generates some interesting mathematics within the context of modelling and optimization in several dimensions. The arguments are illustrated using various examples, and a case study computed in detail. ?? 1987 Plenum Publishing Corporation.

Wired: Energy Drinks, Jock Identity, Masculine Norms, and Risk Taking

ERIC Educational Resources Information Center

Miller, Kathleen E.

2008-01-01

Objective: The author examined gendered links among sport-related identity, endorsement of conventional masculine norms, risk taking, and energy-drink consumption. Participants: The author surveyed 795 undergraduate students enrolled in introductory-level courses at a public university. Methods: The author conducted linear regression analyses of…

Computer-Delivered Social Norm Message Increases Pain Tolerance

PubMed Central

Pulvers, Kim; Schroeder, Jacquelyn; Limas, Eleuterio F.; Zhu, Shu-Hong

2013-01-01

Background Few experimental studies have been conducted on social determinants of pain tolerance. Purpose This study tests a brief, computer-delivered social norm message for increasing pain tolerance. Methods Healthy young adults (N=260; 44 % Caucasian; 27 % Hispanic) were randomly assigned into a 2 (social norm)×2 (challenge) cold pressor study, stratified by gender. They received standard instructions or standard instructions plus a message that contained artifically elevated information about typical performance of others. Results Those receiving a social norm message displayed significantly higher pain tolerance, F(1, 255)=26.95, p<.001, ηp2=.10 and pain threshold F(1, 244)=9.81, p=.002, ηp2=.04, but comparable pain intensity, p>.05. There were no interactions between condition and gender on any outcome variables, p>.05. Conclusions Social norms can significantly increase pain tolerance, even with a brief verbal message delivered by a video. PMID:24146086

Computationally efficient control allocation

NASA Technical Reports Server (NTRS)

Durham, Wayne (Inventor)

2001-01-01

A computationally efficient method for calculating near-optimal solutions to the three-objective, linear control allocation problem is disclosed. The control allocation problem is that of distributing the effort of redundant control effectors to achieve some desired set of objectives. The problem is deemed linear if control effectiveness is affine with respect to the individual control effectors. The optimal solution is that which exploits the collective maximum capability of the effectors within their individual physical limits. Computational efficiency is measured by the number of floating-point operations required for solution. The method presented returned optimal solutions in more than 90% of the cases examined; non-optimal solutions returned by the method were typically much less than 1% different from optimal and the errors tended to become smaller than 0.01% as the number of controls was increased. The magnitude of the errors returned by the present method was much smaller than those that resulted from either pseudo inverse or cascaded generalized inverse solutions. The computational complexity of the method presented varied linearly with increasing numbers of controls; the number of required floating point operations increased from 5.5 i, to seven times faster than did the minimum-norm solution (the pseudoinverse), and at about the same rate as did the cascaded generalized inverse solution. The computational requirements of the method presented were much better than that of previously described facet-searching methods which increase in proportion to the square of the number of controls.

Fast and accurate matrix completion via truncated nuclear norm regularization.

PubMed

Hu, Yao; Zhang, Debing; Ye, Jieping; Li, Xuelong; He, Xiaofei

2013-09-01

Recovering a large matrix from a small subset of its entries is a challenging problem arising in many real applications, such as image inpainting and recommender systems. Many existing approaches formulate this problem as a general low-rank matrix approximation problem. Since the rank operator is nonconvex and discontinuous, most of the recent theoretical studies use the nuclear norm as a convex relaxation. One major limitation of the existing approaches based on nuclear norm minimization is that all the singular values are simultaneously minimized, and thus the rank may not be well approximated in practice. In this paper, we propose to achieve a better approximation to the rank of matrix by truncated nuclear norm, which is given by the nuclear norm subtracted by the sum of the largest few singular values. In addition, we develop a novel matrix completion algorithm by minimizing the Truncated Nuclear Norm. We further develop three efficient iterative procedures, TNNR-ADMM, TNNR-APGL, and TNNR-ADMMAP, to solve the optimization problem. TNNR-ADMM utilizes the alternating direction method of multipliers (ADMM), while TNNR-AGPL applies the accelerated proximal gradient line search method (APGL) for the final optimization. For TNNR-ADMMAP, we make use of an adaptive penalty according to a novel update rule for ADMM to achieve a faster convergence rate. Our empirical study shows encouraging results of the proposed algorithms in comparison to the state-of-the-art matrix completion algorithms on both synthetic and real visual datasets.

Robust Ambiguity Estimation for an Automated Analysis of the Intensive Sessions

NASA Astrophysics Data System (ADS)

Kareinen, Niko; Hobiger, Thomas; Haas, Rüdiger

2016-12-01

Very Long Baseline Interferometry (VLBI) is a unique space-geodetic technique that can directly determine the Earth's phase of rotation, namely UT1. The daily estimates of the difference between UT1 and Coordinated Universal Time (UTC) are computed from one-hour long VLBI Intensive sessions. These sessions are essential for providing timely UT1 estimates for satellite navigation systems. To produce timely UT1 estimates, efforts have been made to completely automate the analysis of VLBI Intensive sessions. This requires automated processing of X- and S-band group delays. These data often contain an unknown number of integer ambiguities in the observed group delays. In an automated analysis with the c5++ software the standard approach in resolving the ambiguities is to perform a simplified parameter estimation using a least-squares adjustment (L2-norm minimization). We implement the robust L1-norm with an alternative estimation method in c5++. The implemented method is used to automatically estimate the ambiguities in VLBI Intensive sessions for the Kokee-Wettzell baseline. The results are compared to an analysis setup where the ambiguity estimation is computed using the L2-norm. Additionally, we investigate three alternative weighting strategies for the ambiguity estimation. The results show that in automated analysis the L1-norm resolves ambiguities better than the L2-norm. The use of the L1-norm leads to a significantly higher number of good quality UT1-UTC estimates with each of the three weighting strategies.

Stochastic Least-Squares Petrov--Galerkin Method for Parameterized Linear Systems

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

Lee, Kookjin; Carlberg, Kevin; Elman, Howard C.

Here, we consider the numerical solution of parameterized linear systems where the system matrix, the solution, and the right-hand side are parameterized by a set of uncertain input parameters. We explore spectral methods in which the solutions are approximated in a chosen finite-dimensional subspace. It has been shown that the stochastic Galerkin projection technique fails to minimize any measure of the solution error. As a remedy for this, we propose a novel stochatic least-squares Petrov--Galerkin (LSPG) method. The proposed method is optimal in the sense that it produces the solution that minimizes a weightedmore » $$\\ell^2$$-norm of the residual over all solutions in a given finite-dimensional subspace. Moreover, the method can be adapted to minimize the solution error in different weighted $$\\ell^2$$-norms by simply applying a weighting function within the least-squares formulation. In addition, a goal-oriented seminorm induced by an output quantity of interest can be minimized by defining a weighting function as a linear functional of the solution. We establish optimality and error bounds for the proposed method, and extensive numerical experiments show that the weighted LSPG method outperforms other spectral methods in minimizing corresponding target weighted norms.« less

Implementing Social Norm Pedagogy to Impact Students' Personal Health Behavior

ERIC Educational Resources Information Center

Kramer, Mary M.; Stover, Sheri

2015-01-01

This quantitative exploratory research study describes the incorporation of Social Norms as a unique pedagogical method in an undergraduate Health Behaviors course (N = 32). With the use of an audience response system (clickers), students anonymously answered health-behavior related questions. Aggregate data from the class was compared to state…

Abstinence, Social Norms, and Drink Responsibly Messages: A Comparison Study

ERIC Educational Resources Information Center

Glassman, Tavis J.; Kruger, Jessica Sloan; Deakins, Bethany A.; Paprzycki, Peter; Blavos, Alexis A.; Hutzelman, Erin N.; Diehr, Aaron

2016-01-01

Objective: The purpose of this study was to determine which type of prevention message (abstinence, social norms, or responsible drinking) was most effective at reducing alcohol consumption. Participants: The subjects from this study included 194 college students from a public university. Methods: Researchers employed a quasi-experimental design,…

L1-norm locally linear representation regularization multi-source adaptation learning.

PubMed

Tao, Jianwen; Wen, Shiting; Hu, Wenjun

2015-09-01

In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.

Longitudinal Relationships Among Perceived Injunctive and Descriptive Norms and Marijuana Use

PubMed Central

Napper, Lucy E.; Kenney, Shannon R.; Hummer, Justin F.; Fiorot, Sara; LaBrie, Joseph W.

2016-01-01

Objective: The current study uses longitudinal data to examine the relative influence of perceived descriptive and injunctive norms for proximal and distal referents on marijuana use. Method: Participants were 740 undergraduate students (67% female) who completed web-based surveys at two time points 12 months apart. Time 1 measures included reports of marijuana use, approval, perceived descriptive norms, and perceived injunctive norms for the typical student, close friends, and parents. At Time 2, students reported on their marijuana use. Results: Results of a path analysis suggest that, after we controlled for Time 1 marijuana use, greater perceived friend approval indirectly predicted Time 2 marijuana use as mediated by personal approval. Greater perceived parental approval was both indirectly and directly associated with greater marijuana use at follow-up. Perceived typical-student descriptive norms were neither directly nor indirectly related to Time 2 marijuana use. Conclusions: The findings support the role of proximal injunctive norms in predicting college student marijuana use up to 12 months later. The results indicate the potential importance of developing normative interventions that incorporate the social influences of proximal referents. PMID:27172578

The Association Between Masculinity and Nonsuicidal Self-Injury.

PubMed

Green, Jonathan D; Kearns, Jaclyn C; Ledoux, Annie M; Addis, Michael E; Marx, Brian P

2018-01-01

Several known risk factors for nonsuicidal self-injury (NSSI), such as negative emotionality and deficits in emotion skills, are also associated with masculinity. Researchers and clinicians suggest that masculine norms around emotional control and self-reliance may make men more likely to engage in self-harm. Masculinity has also been implicated as a potential risk factor for suicide and other self-damaging behaviors. However, the association between masculinity and NSSI has yet to be explored. In the current study, a sample of 912 emerging adults from two universities in the Northeastern United States completed a web-based questionnaire assessing adherence to masculine norms, engagement in NSSI, and known risk factors for NSSI (demographics and number of self-injurers known). Stronger adherence to masculine norms predicted chronic NSSI (five or more episodes throughout the life span) above and beyond other known risk factors. Adherence to masculine norms was related to methods of NSSI. Clinical implications are discussed, including discussions of masculine norms in treatment settings. Future research should examine what specific masculine norms are most closely linked to NSSI and other self-damaging behaviors.

The role of efficacy and moral outrage norms in creating the potential for international development activism through group-based interaction.

PubMed

Thomas, Emma F; McGarty, Craig A

2009-03-01

This paper adopts an intergroup perspective on helping as collective action to explore the ways to boost motivation amongst people in developed countries to join the effort to combat poverty and preventable disease in developing countries. Following van Zomeren, Spears, Leach, and Fischer's (2004) model of collective action, we investigated the role of norms about an emotional response (moral outrage) and beliefs about efficacy in motivating commitment to take action amongst members of advantaged groups. Norms about outrage and efficacy were harnessed to an opinion-based group identity (Bliuc, McGarty, Reynolds, & Muntele, 2007) and explored in the context of a novel group-based interaction method. Results showed that the group-based interaction boosted commitment to action especially when primed with an (injunctive) outrage norm. This norm stimulated a range of related effects including increased identification with the pro-international development opinion-based group, and higher efficacy beliefs. Results provide an intriguing instance of the power of group interaction (particularly where strengthened with emotion norms) to bolster commitment to positive social change.

Hessian Schatten-norm regularization for linear inverse problems.

PubMed

Lefkimmiatis, Stamatios; Ward, John Paul; Unser, Michael

2013-05-01

We introduce a novel family of invariant, convex, and non-quadratic functionals that we employ to derive regularized solutions of ill-posed linear inverse imaging problems. The proposed regularizers involve the Schatten norms of the Hessian matrix, which are computed at every pixel of the image. They can be viewed as second-order extensions of the popular total-variation (TV) semi-norm since they satisfy the same invariance properties. Meanwhile, by taking advantage of second-order derivatives, they avoid the staircase effect, a common artifact of TV-based reconstructions, and perform well for a wide range of applications. To solve the corresponding optimization problems, we propose an algorithm that is based on a primal-dual formulation. A fundamental ingredient of this algorithm is the projection of matrices onto Schatten norm balls of arbitrary radius. This operation is performed efficiently based on a direct link we provide between vector projections onto lq norm balls and matrix projections onto Schatten norm balls. Finally, we demonstrate the effectiveness of the proposed methods through experimental results on several inverse imaging problems with real and simulated data.

Reconstructing the duty of water: a study of emergent norms in socio-hydrology

NASA Astrophysics Data System (ADS)

Wescoat, J. L., Jr.

2013-06-01

This paper assesses changing norms of water use known as the duty of water. It is a case study in historical socio-hydrology, a line of research useful for anticipating changing social values with respect to water. The duty of water is currently defined as the amount of water reasonably required to irrigate a substantial crop with careful management and without waste on a given tract of land. The historical section of the paper traces this concept back to late-18th century analysis of steam engine efficiencies for mine dewatering in Britain. A half-century later, British irrigation engineers fundamentally altered the concept of duty to plan large-scale canal irrigation systems in northern India at an average duty of 218 acres per cubic foot per second (cfs). They justified this extensive irrigation standard (i.e., low water application rate over large areas) with a suite of social values that linked famine prevention with revenue generation and territorial control. Several decades later irrigation engineers in the western US adapted the duty of water concept to a different socio-hydrologic system and norms, using it to establish minimum standards for water rights appropriation (e.g., only 40 to 80 acres per cfs). The final section shows that while the duty of water concept has now been eclipsed by other measures and standards of water efficiency, it may have continuing relevance for anticipating if not predicting emerging social values with respect to water.

Selection and Evaluation of Potential Reference Genes for Gene Expression Analysis in the Brown Planthopper, Nilaparvata lugens (Hemiptera: Delphacidae) Using Reverse-Transcription Quantitative PCR

PubMed Central

Zhu, Xun; Wan, Hu; Shakeel, Muhammad; Zhan, Sha; Jin, Byung-Rae; Li, Jianhong

2014-01-01

The brown planthopper (BPH), Nilaparvata lugens (Hemiptera, Delphacidae), is one of the most important rice pests. Abundant genetic studies on BPH have been conducted using reverse-transcription quantitative real-time PCR (qRT-PCR). Using qRT-PCR, the expression levels of target genes are calculated on the basis of endogenous controls. These genes need to be appropriately selected by experimentally assessing whether they are stably expressed under different conditions. However, such studies on potential reference genes in N. lugens are lacking. In this paper, we presented a systematic exploration of eight candidate reference genes in N. lugens, namely, actin 1 (ACT), muscle actin (MACT), ribosomal protein S11 (RPS11), ribosomal protein S15e (RPS15), alpha 2-tubulin (TUB), elongation factor 1 delta (EF), 18S ribosomal RNA (18S), and arginine kinase (AK) and used four alternative methods (BestKeeper, geNorm, NormFinder, and the delta Ct method) to evaluate the suitability of these genes as endogenous controls. We examined their expression levels among different experimental factors (developmental stage, body part, geographic population, temperature variation, pesticide exposure, diet change, and starvation) following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments) guidelines. Based on the results of RefFinder, which integrates four currently available major software programs to compare and rank the tested candidate reference genes, RPS15, RPS11, and TUB were found to be the most suitable reference genes in different developmental stages, body parts, and geographic populations, respectively. RPS15 was the most suitable gene under different temperature and diet conditions, while RPS11 was the most suitable gene under different pesticide exposure and starvation conditions. This work sheds light on establishing a standardized qRT-PCR procedure in N. lugens, and serves as a starting point for screening for reference genes for expression studies of related insects. PMID:24466124

Selection and evaluation of potential reference genes for gene expression analysis in the brown planthopper, Nilaparvata lugens (Hemiptera: Delphacidae) using reverse-transcription quantitative PCR.

PubMed

Yuan, Miao; Lu, Yanhui; Zhu, Xun; Wan, Hu; Shakeel, Muhammad; Zhan, Sha; Jin, Byung-Rae; Li, Jianhong

2014-01-01

The brown planthopper (BPH), Nilaparvata lugens (Hemiptera, Delphacidae), is one of the most important rice pests. Abundant genetic studies on BPH have been conducted using reverse-transcription quantitative real-time PCR (qRT-PCR). Using qRT-PCR, the expression levels of target genes are calculated on the basis of endogenous controls. These genes need to be appropriately selected by experimentally assessing whether they are stably expressed under different conditions. However, such studies on potential reference genes in N. lugens are lacking. In this paper, we presented a systematic exploration of eight candidate reference genes in N. lugens, namely, actin 1 (ACT), muscle actin (MACT), ribosomal protein S11 (RPS11), ribosomal protein S15e (RPS15), alpha 2-tubulin (TUB), elongation factor 1 delta (EF), 18S ribosomal RNA (18S), and arginine kinase (AK) and used four alternative methods (BestKeeper, geNorm, NormFinder, and the delta Ct method) to evaluate the suitability of these genes as endogenous controls. We examined their expression levels among different experimental factors (developmental stage, body part, geographic population, temperature variation, pesticide exposure, diet change, and starvation) following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments) guidelines. Based on the results of RefFinder, which integrates four currently available major software programs to compare and rank the tested candidate reference genes, RPS15, RPS11, and TUB were found to be the most suitable reference genes in different developmental stages, body parts, and geographic populations, respectively. RPS15 was the most suitable gene under different temperature and diet conditions, while RPS11 was the most suitable gene under different pesticide exposure and starvation conditions. This work sheds light on establishing a standardized qRT-PCR procedure in N. lugens, and serves as a starting point for screening for reference genes for expression studies of related insects.

A probabilistic approach for the estimation of earthquake source parameters from spectral inversion

NASA Astrophysics Data System (ADS)

Supino, M.; Festa, G.; Zollo, A.

2017-12-01

The amplitude spectrum of a seismic signal related to an earthquake source carries information about the size of the rupture, moment, stress and energy release. Furthermore, it can be used to characterize the Green's function of the medium crossed by the seismic waves. We describe the earthquake amplitude spectrum assuming a generalized Brune's (1970) source model, and direct P- and S-waves propagating in a layered velocity model, characterized by a frequency-independent Q attenuation factor. The observed displacement spectrum depends indeed on three source parameters, the seismic moment (through the low-frequency spectral level), the corner frequency (that is a proxy of the fault length) and the high-frequency decay parameter. These parameters are strongly correlated each other and with the quality factor Q; a rigorous estimation of the associated uncertainties and parameter resolution is thus needed to obtain reliable estimations.In this work, the uncertainties are characterized adopting a probabilistic approach for the parameter estimation. Assuming an L2-norm based misfit function, we perform a global exploration of the parameter space to find the absolute minimum of the cost function and then we explore the cost-function associated joint a-posteriori probability density function around such a minimum, to extract the correlation matrix of the parameters. The global exploration relies on building a Markov chain in the parameter space and on combining a deterministic minimization with a random exploration of the space (basin-hopping technique). The joint pdf is built from the misfit function using the maximum likelihood principle and assuming a Gaussian-like distribution of the parameters. It is then computed on a grid centered at the global minimum of the cost-function. The numerical integration of the pdf finally provides mean, variance and correlation matrix associated with the set of best-fit parameters describing the model. Synthetic tests are performed to investigate the robustness of the method and uncertainty propagation from the data-space to the parameter space. Finally, the method is applied to characterize the source parameters of the earthquakes occurring during the 2016-2017 Central Italy sequence, with the goal of investigating the source parameter scaling with magnitude.

Fast calculation of the `ILC norm' in iterative learning control

NASA Astrophysics Data System (ADS)

Rice, Justin K.; van Wingerden, Jan-Willem

2013-06-01

In this paper, we discuss and demonstrate a method for the exploitation of matrix structure in computations for iterative learning control (ILC). In Barton, Bristow, and Alleyne [International Journal of Control, 83(2), 1-8 (2010)], a special insight into the structure of the lifted convolution matrices involved in ILC is used along with a modified Lanczos method to achieve very fast computational bounds on the learning convergence, by calculating the 'ILC norm' in ? computational complexity. In this paper, we show how their method is equivalent to a special instance of the sequentially semi-separable (SSS) matrix arithmetic, and thus can be extended to many other computations in ILC, and specialised in some cases to even faster methods. Our SSS-based methodology will be demonstrated on two examples: a linear time-varying example resulting in the same ? complexity as in Barton et al., and a linear time-invariant example where our approach reduces the computational complexity to ?, thus decreasing the computation time, for an example, from the literature by a factor of almost 100. This improvement is achieved by transforming the norm computation via a linear matrix inequality into a check of positive definiteness - which allows us to further exploit the almost-Toeplitz properties of the matrix, and additionally provides explicit upper and lower bounds on the norm of the matrix, instead of the indirect Ritz estimate. These methods are now implemented in a MATLAB toolbox, freely available on the Internet.

Methods of Organizational Information Security

NASA Astrophysics Data System (ADS)

Martins, José; Dos Santos, Henrique

The principle objective of this article is to present a literature review for the methods used in the security of information at the level of organizations. Some of the principle problems are identified and a first group of relevant dimensions is presented for an efficient management of information security. The study is based on the literature review made, using some of the more relevant certified articles of this theme, in international reports and in the principle norms of management of information security. From the readings that were done, we identified some of the methods oriented for risk management, norms of certification and good practice of security of information. Some of the norms are oriented for the certification of the product or system and others oriented to the processes of the business. There are also studies with the proposal of Frameworks that suggest the integration of different approaches with the foundation of norms focused on technologies, in processes and taking into consideration the organizational and human environment of the organizations. In our perspective, the biggest contribute to the security of information is the development of a method of security of information for an organization in a conflicting environment. This should make available the security of information, against the possible dimensions of attack that the threats could exploit, through the vulnerability of the organizational actives. This method should support the new concepts of "Network centric warfare", "Information superiority" and "Information warfare" especially developed in this last decade, where information is seen simultaneously as a weapon and as a target.

Sparse nonnegative matrix factorization with ℓ0-constraints

PubMed Central

Peharz, Robert; Pernkopf, Franz

2012-01-01

Although nonnegative matrix factorization (NMF) favors a sparse and part-based representation of nonnegative data, there is no guarantee for this behavior. Several authors proposed NMF methods which enforce sparseness by constraining or penalizing the ℓ1-norm of the factor matrices. On the other hand, little work has been done using a more natural sparseness measure, the ℓ0-pseudo-norm. In this paper, we propose a framework for approximate NMF which constrains the ℓ0-norm of the basis matrix, or the coefficient matrix, respectively. For this purpose, techniques for unconstrained NMF can be easily incorporated, such as multiplicative update rules, or the alternating nonnegative least-squares scheme. In experiments we demonstrate the benefits of our methods, which compare to, or outperform existing approaches. PMID:22505792

Collective learning for the emergence of social norms in networked multiagent systems.

PubMed

Yu, Chao; Zhang, Minjie; Ren, Fenghui

2014-12-01

Social norms such as social rules and conventions play a pivotal role in sustaining system order by regulating and controlling individual behaviors toward a global consensus in large-scale distributed systems. Systematic studies of efficient mechanisms that can facilitate the emergence of social norms enable us to build and design robust distributed systems, such as electronic institutions and norm-governed sensor networks. This paper studies the emergence of social norms via learning from repeated local interactions in networked multiagent systems. A collective learning framework, which imitates the opinion aggregation process in human decision making, is proposed to study the impact of agent local collective behaviors on the emergence of social norms in a number of different situations. In the framework, each agent interacts repeatedly with all of its neighbors. At each step, an agent first takes a best-response action toward each of its neighbors and then combines all of these actions into a final action using ensemble learning methods. Extensive experiments are carried out to evaluate the framework with respect to different network topologies, learning strategies, numbers of actions, influences of nonlearning agents, and so on. Experimental results reveal some significant insights into the manipulation and control of norm emergence in networked multiagent systems achieved through local collective behaviors.

A class of systolizable IIR digital filters and its design for proper scaling and minimum output roundoff noise

NASA Technical Reports Server (NTRS)

Lei, Shaw-Min; Yao, Kung

1990-01-01

A class of infinite impulse response (IIR) digital filters with a systolizable structure is proposed and its synthesis is investigated. The systolizable structure consists of pipelineable regular modules with local connections and is suitable for VLSI implementation. It is capable of achieving high performance as well as high throughput. This class of filter structure provides certain degrees of freedom that can be used to obtain some desirable properties for the filter. Techniques of evaluating the internal signal powers and the output roundoff noise of the proposed filter structure are developed. Based upon these techniques, a well-scaled IIR digital filter with minimum output roundoff noise is designed using a local optimization approach. The internal signals of all the modes of this filter are scaled to unity in the l2-norm sense. Compared to the Rao-Kailath (1984) orthogonal digital filter and the Gray-Markel (1973) normalized-lattice digital filter, this filter has better scaling properties and lower output roundoff noise.

The Role of Issue Familiarity And Social Norms: Findings on New College Students’ Alcohol Use Intentions

PubMed Central

Rimal, Rajiv N.; Mollen, Saar

2013-01-01

Background Scholars in a variety of disciplines are interested in understanding the conditions under which social norms affect human behavior. Following the distinction made between descriptive and injunctive norms by the focus theory of normative conduct, the theory of normative social behavior predicts that the influence of descriptive norms on behavior is moderated by injunctive norms, outcome expectations, and group identity. We extended the theory by testing the proposition that the influence of descriptive norms on behavior would be greater under conditions of greater issue familiarity, defined as the ease with which one can cognitively access the behavior or behavioral issue. Design and Methods The model was tested in the domain of alcohol consumption intentions by conducting a survey among incoming students (n=719) to a large university in the United States. Data indicated that students in the sample were well representative of the university population. Results The influence of descriptive norms on behavioral intentions was moderated by issue familiarity, as predicted. Familiarity was a facilitator of behavior: the influence of descriptive norms on behavioral intentions was greater under conditions of high, rather than low, familiarity. The overall model explained 53% of the variance in alcohol consumption intentions. Conclusions Public health interventions promoting health behaviors need to take into account the extent to which the behaviors are familiar to the target audience. The influence of norms appears to be weaker when the behavior is unfamiliar or novel. Implications for theory and interventions for reducing alcohol consumption are discussed. PMID:25170478

The Effect of Descriptive Norms on Pregaming Frequency: Tests of Five Moderators

PubMed Central

Merrill, Jennifer E.; Kenney, Shannon R.; Carey, Kate B.

2016-01-01

Background Pregaming is highly prevalent on college campuses and associated with heightened levels of intoxication and risk of alcohol consequences. However, research examining the correlates of pregaming behavior is limited. Descriptive norms (i.e., perceptions about the prevalence or frequency of a behavior) are reliable and comparatively strong predictors of general drinking behavior, with recent evidence indicating that they are also associated with pregaming. Objectives We tested the hypothesis that higher descriptive norms for pregaming frequency would be associated with personal pregaming frequency. We also tested whether this effect would be stronger in the context of several theory-based moderators: female gender, higher injunctive norms (i.e., perceptions of others' attitudes toward a particular behavior), a more positive attitude toward pregaming, a stronger sense of identification with the drinking habits of other students, and stronger social comparison tendencies. Methods College student drinkers (N=198, 63% female) participated in an online survey assessing frequency of pregaming, descriptive norms, and hypothesized moderators. Results A multiple regression model revealed that higher descriptive norms, a more positive attitude toward pregaming, and stronger peer identification were significantly associated with greater pregaming frequency among drinkers. However, no moderators of the association between descriptive norms and pregaming frequency were observed. Conclusions/Importance Descriptive norms are robust predictors of pregaming behavior, for both genders and across levels of several potential moderators. Future research seeking to understand pregaming behavior should consider descriptive norms, as well as personal attitudes and identification with student peers, as targets of interventions designed to reduce pregaming. PMID:27070494

Descriptive and Injunctive Network Norms Associated with Non Medical Use of Prescription Drugs among Homeless Youth

PubMed Central

Barman-Adhikari, Anamika; Al Tayyib, Alia; Begun, Stephanie; Bowen, Elizabeth; Rice, Eric

2016-01-01

Background Nonmedical use of prescription drugs (NMUPD) among youth and young adults is being increasingly recognized as a significant public health problem. Homeless youth in particular are more likely to engage in NMUPD compared to housed youth. Studies suggest that network norms are strongly associated with a range of substance use behaviors. However, evidence regarding the association between network norms and NMUPD is scarce. We sought to understand whether social network norms of NMUPD are associated with engagement in NMUPD among homeless youth. Methods 1,046 homeless youth were recruited from three drop-in centers in Los Angeles, CA and were interviewed regarding their individual and social network characteristics. Multivariate logistic regression was employed to evaluate the significance of associations between social norms (descriptive and injunctive) and self-reported NMUPD. Results Approximately 25% of youth reported past 30-day NMUPD. However, more youth (32.28%) of youth believed that their network members engage in NMUPD, perhaps suggesting some pluralistic ignorance bias. Both descriptive and injunctive norms were associated with self-reported NMUPD among homeless youth. However, these varied by network type, with presence of NMUPD engaged street-based and home-based peers (descriptive norm) increasing the likelihood of NMUPD, while objections from family-members (injunctive norm) decreasing that likelihood. Conclusions Our findings suggest that, like other substance use behaviors, NMUPD is also influenced by youths’ perceptions of the behaviors of their social network members. Therefore, prevention and interventions programs designed to influence NMUPD might benefit from taking a social network norms approach. PMID:27563741

A comparative analysis of moral principles and behavioral norms in eight ethical codes relevant to health sciences librarianship, medical informatics, and the health professions

PubMed Central

Byrd, Gary D.; Winkelstein, Peter

2014-01-01

Objective: Based on the authors' shared interest in the interprofessional challenges surrounding health information management, this study explores the degree to which librarians, informatics professionals, and core health professionals in medicine, nursing, and public health share common ethical behavior norms grounded in moral principles. Methods: Using the “Principlism” framework from a widely cited textbook of biomedical ethics, the authors analyze the statements in the ethical codes for associations of librarians (Medical Library Association [MLA], American Library Association, and Special Libraries Association), informatics professionals (American Medical Informatics Association [AMIA] and American Health Information Management Association), and core health professionals (American Medical Association, American Nurses Association, and American Public Health Association). This analysis focuses on whether and how the statements in these eight codes specify core moral norms (Autonomy, Beneficence, Non-Maleficence, and Justice), core behavioral norms (Veracity, Privacy, Confidentiality, and Fidelity), and other norms that are empirically derived from the code statements. Results: These eight ethical codes share a large number of common behavioral norms based most frequently on the principle of Beneficence, then on Autonomy and Justice, but rarely on Non-Maleficence. The MLA and AMIA codes share the largest number of common behavioral norms, and these two associations also share many norms with the other six associations. Implications: The shared core of behavioral norms among these professions, all grounded in core moral principles, point to many opportunities for building effective interprofessional communication and collaboration regarding the development, management, and use of health information resources and technologies. PMID:25349543

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy.

PubMed

Grova, Christophe; Aiguabella, Maria; Zelmann, Rina; Lina, Jean-Marc; Hall, Jeffery A; Kobayashi, Eliane

2016-05-01

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Attitudes, Norms, and the Effect of Social Connectedness on Adolescent Sexual Risk Intention

ERIC Educational Resources Information Center

Cederbaum, Julie A.; Rodriguez, Aubrey J.; Sullivan, Kathrine; Gray, Kandice

2017-01-01

Background: Risky sexual behaviors put adolescents at increased risk of adverse outcomes. Parents, school-based adults, and peers play important roles in influencing these sex intentions. Methods: This work explored the influence of parent-child sex communication on adolescent attitudes, perceived norms, and intentions to have sex, including the…

Perceived Norms for Interactive Teaching and Their Relationship to Instructional Decision-Making: A Mixed Methods Study

ERIC Educational Resources Information Center

Hora, Matthew T.; Anderson, Craig

2012-01-01

Normative expectations for acceptable behaviors related to undergraduate instruction are known to exist within academic settings. Yet few studies have examined disciplinary variation in norms for interactive teaching, and their relationship to teaching practice, particularly from a cognitive perspective. This study examines these problems using…

A Psychometric Review of Norm-Referenced Tests Used to Assess Phonological Error Patterns

ERIC Educational Resources Information Center

Kirk, Celia; Vigeland, Laura

2014-01-01

Purpose: The authors provide a review of the psychometric properties of 6 norm-referenced tests designed to measure children's phonological error patterns. Three aspects of the tests' psychometric adequacy were evaluated: the normative sample, reliability, and validity. Method: The specific criteria used for determining the psychometric…

Structure-Based Low-Rank Model With Graph Nuclear Norm Regularization for Noise Removal.

PubMed

Ge, Qi; Jing, Xiao-Yuan; Wu, Fei; Wei, Zhi-Hui; Xiao, Liang; Shao, Wen-Ze; Yue, Dong; Li, Hai-Bo

2017-07-01

Nonlocal image representation methods, including group-based sparse coding and block-matching 3-D filtering, have shown their great performance in application to low-level tasks. The nonlocal prior is extracted from each group consisting of patches with similar intensities. Grouping patches based on intensity similarity, however, gives rise to disturbance and inaccuracy in estimation of the true images. To address this problem, we propose a structure-based low-rank model with graph nuclear norm regularization. We exploit the local manifold structure inside a patch and group the patches by the distance metric of manifold structure. With the manifold structure information, a graph nuclear norm regularization is established and incorporated into a low-rank approximation model. We then prove that the graph-based regularization is equivalent to a weighted nuclear norm and the proposed model can be solved by a weighted singular-value thresholding algorithm. Extensive experiments on additive white Gaussian noise removal and mixed noise removal demonstrate that the proposed method achieves a better performance than several state-of-the-art algorithms.

funtooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types.

PubMed

Oros Klein, Kathleen; Grinek, Stepan; Bernatsky, Sasha; Bouchard, Luigi; Ciampi, Antonio; Colmegna, Ines; Fortin, Jean-Philippe; Gao, Long; Hivert, Marie-France; Hudson, Marie; Kobor, Michael S; Labbe, Aurelie; MacIsaac, Julia L; Meaney, Michael J; Morin, Alexander M; O'Donnell, Kieran J; Pastinen, Tomi; Van Ijzendoorn, Marinus H; Voisin, Gregory; Greenwood, Celia M T

2016-02-15

DNA methylation patterns are well known to vary substantially across cell types or tissues. Hence, existing normalization methods may not be optimal if they do not take this into account. We therefore present a new R package for normalization of data from the Illumina Infinium Human Methylation450 BeadChip (Illumina 450 K) built on the concepts in the recently published funNorm method, and introducing cell-type or tissue-type flexibility. funtooNorm is relevant for data sets containing samples from two or more cell or tissue types. A visual display of cross-validated errors informs the choice of the optimal number of components in the normalization. Benefits of cell (tissue)-specific normalization are demonstrated in three data sets. Improvement can be substantial; it is strikingly better on chromosome X, where methylation patterns have unique inter-tissue variability. An R package is available at https://github.com/GreenwoodLab/funtooNorm, and has been submitted to Bioconductor at http://bioconductor.org. © The Author 2015. Published by Oxford University Press.

You can’t burn the house down because of one bedbug: a qualitative study of changing gender norms in the prevention of violence against women and girls in an urban informal settlement in India

PubMed Central

Daruwalla, Nayreen; Hate, Ketaki; Pinto, Preethi; Ambavkar, Gauri; Kakad, Bhaskar; Osrin, David

2017-01-01

Background: The contribution of structural inequalities and societal legitimisation to violence against women, which 30% of women in India survive each year, is widely accepted. There is a consensus that interventions should aim to change gender norms, particularly through community mobilisation. How this should be done is less clear. Methods: We did a qualitative study in a large informal settlement in Mumbai, an environment that characterises 41% of households. After reviewing the anonymised records of consultations with 1653 survivors of violence, we conducted 5 focus group discussions and 13 individual interviews with 71 women and men representing a range of age groups and communities. We based the interviews on fictitious biographical vignettes to elicit responses and develop an understanding of social norms. We wondered whether, in trying to change norms, we might exploit the disjunction between descriptive norms (beliefs about what others actually do) and injunctive norms (beliefs about what others think one ought to do), focusing program activities on evidence that descriptive norms are changing. Results: We found that descriptive and injunctive norms were relatively similar with regard to femininity, masculinity, the need for marriage and childbearing, resistance to separation and divorce, and disapproval of friendships between women and men. Some constraints on women’s dress and mobility were relaxing, but there were more substantial differences between descriptive and injunctive norms around women’s education, control of income and finances, and premarital sexual relationships. Conclusions: Programmatically, we hope to exploit these areas of mismatch in the context of injunctive norms generally inimical to violence against women. We propose that an under-appreciated strategy is expansion of the reference group: induction of relatively isolated women and men into broader social groups whose descriptive and injunctive norms do not tolerate violence PMID:29164180

The norms, rules and motivational values driving sustainable remediation of contaminated environments: A study of implementation.

PubMed

Prior, Jason

2016-02-15

Efforts to achieve sustainability are transforming the norms, rules and values that affect the remediation of contaminated environments. This is altering the ways in which remediation impacts on the total environment. Despite this transformation, few studies have provided systematic insights into the diverse norms and rules that drive the implementation of sustainable remediation at contaminated sites, and no studies have investigated how values motivate compliance with these norms and rules. This study is a systematic analysis of the rules, norms and motivational values embedded in sustainable remediation processes at three sites across Australia, using in-depth interviews conducted with 18 participants between 2011 and 2014, through the application of Crawford and Ostrom's Institutional Grammar and Schwartz's value framework. These approaches offered methods for identifying the rules, norms, and motivational values that guided participants' actions within remediation processes at these sites. The findings identify a core set of 16 norms and 18 rules (sanctions) used by participants to implement sustainable remediation at the sites. These norms and rules: define the position of participants within the process, provide means for incorporating sustainability into established remediation practices, and define the scope of outcomes that constitute sustainable remediation. The findings revealed that motivational values focused on public interest and self-interest influenced participants' compliance with norms and rules. The findings also found strong interdependence between the norms and rules (sanctions) within the remediation processes and the normative principles operating within the broader domain of environmental management and planning. The paper concludes with a discussion of: the system of norms operating within sustainable remediation (which far exceed those associated with ESD); their link, through rules (sanctions) to contemporary styles of regulatory enforcement; and the underlying balance of public-interest values and self-interest values that drives participants' involvement in sustainable remediation. Copyright © 2015 Elsevier B.V. All rights reserved.

You can't burn the house down because of one bedbug: a qualitative study of changing gender norms in the prevention of violence against women and girls in an urban informal settlement in India.

PubMed

Daruwalla, Nayreen; Hate, Ketaki; Pinto, Preethi; Ambavkar, Gauri; Kakad, Bhaskar; Osrin, David

2017-01-01

Background : The contribution of structural inequalities and societal legitimisation to violence against women, which 30% of women in India survive each year, is widely accepted. There is a consensus that interventions should aim to change gender norms, particularly through community mobilisation. How this should be done is less clear. Methods : We did a qualitative study in a large informal settlement in Mumbai, an environment that characterises 41% of households. After reviewing the anonymised records of consultations with 1653 survivors of violence, we conducted 5 focus group discussions and 13 individual interviews with 71 women and men representing a range of age groups and communities. We based the interviews on fictitious biographical vignettes to elicit responses and develop an understanding of social norms. We wondered whether, in trying to change norms, we might exploit the disjunction between descriptive norms (beliefs about what others actually do) and injunctive norms (beliefs about what others think one ought to do), focusing program activities on evidence that descriptive norms are changing. Results : We found that descriptive and injunctive norms were relatively similar with regard to femininity, masculinity, the need for marriage and childbearing, resistance to separation and divorce, and disapproval of friendships between women and men. Some constraints on women's dress and mobility were relaxing, but there were more substantial differences between descriptive and injunctive norms around women's education, control of income and finances, and premarital sexual relationships. Conclusions : Programmatically, we hope to exploit these areas of mismatch in the context of injunctive norms generally inimical to violence against women. We propose that an under-appreciated strategy is expansion of the reference group: induction of relatively isolated women and men into broader social groups whose descriptive and injunctive norms do not tolerate violence.

L1 norm based common spatial patterns decomposition for scalp EEG BCI.

PubMed

Li, Peiyang; Xu, Peng; Zhang, Rui; Guo, Lanjin; Yao, Dezhong

2013-08-06

Brain computer interfaces (BCI) is one of the most popular branches in biomedical engineering. It aims at constructing a communication between the disabled persons and the auxiliary equipments in order to improve the patients' life. In motor imagery (MI) based BCI, one of the popular feature extraction strategies is Common Spatial Patterns (CSP). In practical BCI situation, scalp EEG inevitably has the outlier and artifacts introduced by ocular, head motion or the loose contact of electrodes in scalp EEG recordings. Because outlier and artifacts are usually observed with large amplitude, when CSP is solved in view of L2 norm, the effect of outlier and artifacts will be exaggerated due to the imposing of square to outliers, which will finally influence the MI based BCI performance. While L1 norm will lower the outlier effects as proved in other application fields like EEG inverse problem, face recognition, etc. In this paper, we present a new CSP implementation using the L1 norm technique, instead of the L2 norm, to solve the eigen problem for spatial filter estimation with aim to improve the robustness of CSP to outliers. To evaluate the performance of our method, we applied our method as well as the standard CSP and the regularized CSP with Tikhonov regularization (TR-CSP), on both the peer BCI dataset with simulated outliers and the dataset from the MI BCI system developed in our group. The McNemar test is used to investigate whether the difference among the three CSPs is of statistical significance. The results of both the simulation and real BCI datasets consistently reveal that the proposed method has much higher classification accuracies than the conventional CSP and the TR-CSP. By combining L1 norm based Eigen decomposition into Common Spatial Patterns, the proposed approach can effectively improve the robustness of BCI system to EEG outliers and thus be potential for the actual MI BCI application, where outliers are inevitably introduced into EEG recordings.

Does Sexual Self-Concept Ambiguity Moderate Relations Among Perceived Peer Norms for Alcohol Use, Alcohol-Dependence Symptomatology, and HIV Risk-Taking Behavior?

PubMed Central

Talley, Amelia E; Brown, Jennifer L; Stevens, Angela K; Littlefield, Andrew K

2014-01-01

Objective: The current study examines the relation between peer descriptive norms for alcohol involvement and alcohol-dependence symptomatology and whether this relation differs as a function of sexual self-concept ambiguity (SSA). This study also examines the associations among peer descriptive norms for alcohol involvement, alcohol-dependence symptomatology, and lifetime HIV risk-taking behavior and how these relations are influenced by SSA. Method: Women between ages 18 and 30 years (N = 351; M = 20.96, SD = 2.92) completed an online survey assessing sexual self-concept, peer descriptive norms, alcohol-dependence symptomatology, and HIV risk-taking behaviors. Structural equation modeling was used to test hypotheses of interest. Results: There was a significant latent variable interaction between SSA and descriptive norms for peer alcohol use. There was a stronger positive relationship between peer descriptive norms for alcohol and alcohol-dependence symptomatology when SSA was higher compared with when SSA was lower. Both latent variables exhibited positive simple associations with alcohol-dependence symptoms. Peer descriptive norms for alcohol involvement directly and indirectly influenced HIV risk-taking behaviors, and the indirect influence was conditional based on SSA. Conclusions: The current findings illustrate complex, nuanced associations between perceived norms, identity-related self-concepts, and risky health behaviors from various domains. Future intervention efforts may be warranted to address both problem alcohol use and HIV-risk engagement among individuals with greater sexual self-concept ambiguity. PMID:25343661

A graph-based approach to auditing RxNorm.

PubMed

Bodenreider, Olivier; Peters, Lee B

2009-06-01

RxNorm is a standardized nomenclature for clinical drug entities developed by the National Library of Medicine. In this paper, we audit relations in RxNorm for consistency and completeness through the systematic analysis of the graph of its concepts and relationships. The representation of multi-ingredient drugs is normalized in order to make it compatible with that of single-ingredient drugs. All meaningful paths between two nodes in the type graph are computed and instantiated. Alternate paths are automatically compared and manually inspected in case of inconsistency. The 115 meaningful paths identified in the type graph can be grouped into 28 groups with respect to start and end nodes. Of the 19 groups of alternate paths (i.e., with two or more paths) between the start and end nodes, 9 (47%) exhibit inconsistencies. Overall, 28 (24%) of the 115 paths are inconsistent with other alternate paths. A total of 348 inconsistencies were identified in the April 2008 version of RxNorm and reported to the RxNorm team, of which 215 (62%) had been corrected in the January 2009 version of RxNorm. The inconsistencies identified involve missing nodes (93), missing links (17), extraneous links (237) and one case of mix-up between two ingredients. Our auditing method proved effective in identifying a limited number of errors that had defeated the quality assurance mechanisms currently in place in the RxNorm production system. Some recommendations for the development of RxNorm are provided.

Development and validation of an eating norms inventory. Americans' lay-beliefs about appropriate eating.

PubMed

Fisher, Robert J; Dubé, Laurette

2011-10-01

What do American adults believe about what, where, when, how much, and how often it is appropriate to eat? Such normative beliefs originate from family and friends through socialization processes, but they are also influenced by governments, educational institutions, and businesses. Norms therefore provide an important link between the social environment and individual attitudes and behaviors. This paper reports on five studies that identify, develop, and validate measures of normative beliefs about eating. In study 1 we use an inductive method to identify what American adults believe are appropriate or desirable eating behaviors. Studies 2 and 3 are used to purify and assess the discriminant and nomological validity of the proposed set of 18 unidimensional eating norms. Study 4 assesses predictive validity and finds that acting in a norm-consistent fashion is associated with lower Body Mass Index (BMI), and greater body satisfaction and subjective health. Study 5 assesses the underlying social desirability and perceived healthiness of the norms. Copyright © 2011 Elsevier Ltd. All rights reserved.

Gendered Cultural Identities: The Influences of Family and Privacy Boundaries, Subjective Norms, and Stigma Beliefs on Family Health History Communication.

PubMed

Hong, Soo Jung

2018-08-01

This study investigates the effects of cultural norms on family health history (FHH) communication in the American, Chinese, and Korean cultures. More particularly, this study focuses on perceived family boundaries, subjective norms, stigma beliefs, and privacy boundaries, including age and gender, that affect people's FHH communication. For data analyses, hierarchical multiple regression and logistic regression methods were employed. The results indicate that participants' subjective norms, stigma beliefs, and perceived family/privacy boundaries were positively associated with current FHH communication. Age- and gender-related privacy boundaries were negatively related to perceived privacy boundaries, however. Finally, the results show that gendered cultural identities have three-way interaction effects on two associations: (1) between perceived family boundaries and perceived privacy boundaries and (2) between perceived privacy boundaries and current FHH communication. The findings have meaningful implications for future cross-cultural studies on the roles of family systems, subjective norms, and stigma beliefs in FHH communication.

Bacterial reference genes for gene expression studies by RT-qPCR: survey and analysis.

PubMed

Rocha, Danilo J P; Santos, Carolina S; Pacheco, Luis G C

2015-09-01

The appropriate choice of reference genes is essential for accurate normalization of gene expression data obtained by the method of reverse transcription quantitative real-time PCR (RT-qPCR). In 2009, a guideline called the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) highlighted the importance of the selection and validation of more than one suitable reference gene for obtaining reliable RT-qPCR results. Herein, we searched the recent literature in order to identify the bacterial reference genes that have been most commonly validated in gene expression studies by RT-qPCR (in the first 5 years following publication of the MIQE guidelines). Through a combination of different search parameters with the text mining tool MedlineRanker, we identified 145 unique bacterial genes that were recently tested as candidate reference genes. Of these, 45 genes were experimentally validated and, in most of the cases, their expression stabilities were verified using the software tools geNorm and NormFinder. It is noteworthy that only 10 of these reference genes had been validated in two or more of the studies evaluated. An enrichment analysis using Gene Ontology classifications demonstrated that genes belonging to the functional categories of DNA Replication (GO: 0006260) and Transcription (GO: 0006351) rendered a proportionally higher number of validated reference genes. Three genes in the former functional class were also among the top five most stable genes identified through an analysis of gene expression data obtained from the Pathosystems Resource Integration Center. These results may provide a guideline for the initial selection of candidate reference genes for RT-qPCR studies in several different bacterial species.

Randomized Face-to-Face vs. Home Exercise Interventions in Pregnant Women with Gestational Diabetes

PubMed Central

DOWNS, Danielle Symons; DINALLO, Jennifer M.; BIRCH, Leann L.; PAUL, Ian M.; ULBRECHT, Jan S.

2017-01-01

Objectives Evaluate effects of a theoretically-based, semi-intensive (Face-to-Face; F2F) exercise intervention and minimum-contact (Home) exercise intervention to the standard care (Control) on exercise, its motivational determinants, blood glucose levels, and insulin use of pregnant women with gestational diabetes mellitus (GDM). Design Randomized control trial with two intervention arms and control (standard care). Method Participants (N=65) were randomized to a Control (standard prenatal care/GDM dietary counseling), Home (standard care + phone education/support + home exercise), or F2F (standard care + on-site education/support + guided exercise with instructor on 2 days/week) group from ~20 weeks gestation to delivery. Assessments of exercise and motivational determinants were obtained at baseline (20-weeks gestation) and follow-up (32-weeks gestation). Blood glucose levels (fasting/postprandial mg/dL) and insulin use were extrapolated from medical records. Results At the 32-week follow-up, the F2F group had significantly higher exercise min, pedometer steps/day, and motivational determinants (attitude, subjective norm, perceived control, intention) than controls (p’s < .05) and significantly higher exercise min and subjective norm than the Home group (p’s < .05); these effect sizes were medium-large (η2 = .11–.23). There was a medium effect (η2 = .13) on postprandial blood glucose at 36-weeks gestation with the F2F group having lower values than controls. Although not significant, the F2F group started insulin later (33 weeks gestation) than the Home (27 weeks) and Control (31 weeks) groups. Conclusion A theoretically-based, F2F exercise intervention has multiple health benefits and may be the necessary approach for promoting exercise motivation and behavior among GDM women. PMID:28428728

Selection of Valid Reference Genes for Reverse Transcription Quantitative PCR Analysis in Heliconius numata (Lepidoptera: Nymphalidae)

PubMed Central

Chouteau, Mathieu; Whibley, Annabel; Joron, Mathieu; Llaurens, Violaine

2016-01-01

Identifying the genetic basis of adaptive variation is challenging in non-model organisms and quantitative real time PCR. is a useful tool for validating predictions regarding the expression of candidate genes. However, comparing expression levels in different conditions requires rigorous experimental design and statistical analyses. Here, we focused on the neotropical passion-vine butterflies Heliconius, non-model species studied in evolutionary biology for their adaptive variation in wing color patterns involved in mimicry and in the signaling of their toxicity to predators. We aimed at selecting stable reference genes to be used for normalization of gene expression data in RT-qPCR analyses from developing wing discs according to the minimal guidelines described in Minimum Information for publication of Quantitative Real-Time PCR Experiments (MIQE). To design internal RT-qPCR controls, we studied the stability of expression of nine candidate reference genes (actin, annexin, eF1α, FK506BP, PolyABP, PolyUBQ, RpL3, RPS3A, and tubulin) at two developmental stages (prepupal and pupal) using three widely used programs (GeNorm, NormFinder and BestKeeper). Results showed that, despite differences in statistical methods, genes RpL3, eF1α, polyABP, and annexin were stably expressed in wing discs in late larval and pupal stages of Heliconius numata. This combination of genes may be used as a reference for a reliable study of differential expression in wings for instance for genes involved in important phenotypic variation, such as wing color pattern variation. Through this example, we provide general useful technical recommendations as well as relevant statistical strategies for evolutionary biologists aiming to identify candidate-genes involved adaptive variation in non-model organisms. PMID:27271971

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

Anikovsky, V.V.; Karzov, G.P.; Timofeev, B.T.

The paper demonstrates an insufficiency of some requirements native Norms (when comparing them with the foreign requirements for the consideration of calculating situations): (1) leak before break (LBB); (2) short cracks; (3) preliminary loading (warm prestressing). In particular, the paper presents (1) Comparison of native and foreign normative requirements (PNAE G-7-002-86, Code ASME, BS 1515, KTA) on permissible stress levels and specifically on the estimation of crack initiation and propagation; (2) comparison of RF and USA Norms of pressure vessel material acceptance and also data of pressure vessel hydrotests; (3) comparison of Norms on the presence of defects (RF andmore » USA) in NPP vessels, developments of defect schematization rules; foundation of a calculated defect (semi-axis correlation a/b) for pressure vessel and piping components: (4) sequence of defect estimation (growth of initial defects and critical crack sizes) proceeding from the concept LBB; (5) analysis of crack initiation and propagation conditions according to the acting Norms (including crack jumps); (6) necessity to correct estimation methods of ultimate states of brittle an ductile fracture and elastic-plastic region as applied to calculating situation: (a) LBB and (b) short cracks; (7) necessity to correct estimation methods of ultimate states with the consideration of static and cyclic loading (warm prestressing effect) of pressure vessel; estimation of the effect stability; (8) proposals on PNAE G-7-002-86 Norm corrections.« less

The Iterative Reweighted Mixed-Norm Estimate for Spatio-Temporal MEG/EEG Source Reconstruction.

PubMed

Strohmeier, Daniel; Bekhti, Yousra; Haueisen, Jens; Gramfort, Alexandre

2016-10-01

Source imaging based on magnetoencephalography (MEG) and electroencephalography (EEG) allows for the non-invasive analysis of brain activity with high temporal and good spatial resolution. As the bioelectromagnetic inverse problem is ill-posed, constraints are required. For the analysis of evoked brain activity, spatial sparsity of the neuronal activation is a common assumption. It is often taken into account using convex constraints based on the l 1 -norm. The resulting source estimates are however biased in amplitude and often suboptimal in terms of source selection due to high correlations in the forward model. In this work, we demonstrate that an inverse solver based on a block-separable penalty with a Frobenius norm per block and a l 0.5 -quasinorm over blocks addresses both of these issues. For solving the resulting non-convex optimization problem, we propose the iterative reweighted Mixed Norm Estimate (irMxNE), an optimization scheme based on iterative reweighted convex surrogate optimization problems, which are solved efficiently using a block coordinate descent scheme and an active set strategy. We compare the proposed sparse imaging method to the dSPM and the RAP-MUSIC approach based on two MEG data sets. We provide empirical evidence based on simulations and analysis of MEG data that the proposed method improves on the standard Mixed Norm Estimate (MxNE) in terms of amplitude bias, support recovery, and stability.

Effective dose evaluation of NORM-added consumer products using Monte Carlo simulations and the ICRP computational human phantoms.

PubMed

Lee, Hyun Cheol; Yoo, Do Hyeon; Testa, Mauro; Shin, Wook-Geun; Choi, Hyun Joon; Ha, Wi-Ho; Yoo, Jaeryong; Yoon, Seokwon; Min, Chul Hee

2016-04-01

The aim of this study is to evaluate the potential hazard of naturally occurring radioactive material (NORM) added consumer products. Using the Monte Carlo method, the radioactive products were simulated with ICRP reference phantom and the organ doses were calculated with the usage scenario. Finally, the annual effective doses were evaluated as lower than the public dose limit of 1mSv y(-1) for 44 products. It was demonstrated that NORM-added consumer products could be quantitatively assessed for the safety regulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

OPERATOR NORM INEQUALITIES BETWEEN TENSOR UNFOLDINGS ON THE PARTITION LATTICE

PubMed Central

Wang, Miaoyan; Duc, Khanh Dao; Fischer, Jonathan; Song, Yun S.

2017-01-01

Interest in higher-order tensors has recently surged in data-intensive fields, with a wide range of applications including image processing, blind source separation, community detection, and feature extraction. A common paradigm in tensor-related algorithms advocates unfolding (or flattening) the tensor into a matrix and applying classical methods developed for matrices. Despite the popularity of such techniques, how the functional properties of a tensor changes upon unfolding is currently not well understood. In contrast to the body of existing work which has focused almost exclusively on matricizations, we here consider all possible unfoldings of an order-k tensor, which are in one-to-one correspondence with the set of partitions of {1, …, k}. We derive general inequalities between the lp-norms of arbitrary unfoldings defined on the partition lattice. In particular, we demonstrate how the spectral norm (p = 2) of a tensor is bounded by that of its unfoldings, and obtain an improved upper bound on the ratio of the Frobenius norm to the spectral norm of an arbitrary tensor. For specially-structured tensors satisfying a generalized definition of orthogonal decomposability, we prove that the spectral norm remains invariant under specific subsets of unfolding operations. PMID:28286347

Perceptual dehumanization of faces is activated by norm violations and facilitates norm enforcement.

PubMed

Fincher, Katrina M; Tetlock, Philip E

2016-02-01

This article uses methods drawn from perceptual psychology to answer a basic social psychological question: Do people process the faces of norm violators differently from those of others--and, if so, what is the functional significance? Seven studies suggest that people process these faces different and the differential processing makes it easier to punish norm violators. Studies 1 and 2 use a recognition-recall paradigm that manipulated facial-inversion and spatial frequency to show that people rely upon face-typical processing less when they perceive norm violators' faces. Study 3 uses a facial composite task to demonstrate that the effect is actor dependent, not action dependent, and to suggest that configural processing is the mechanism of perceptual change. Studies 4 and 5 use offset faces to show that configural processing is only attenuated when they belong to perpetrators who are culpable. Studies 6 and 7 show that people find it easier to punish inverted faces and harder to punish faces displayed in low spatial frequency. Taken together, these data suggest a bidirectional flow of causality between lower-order perceptual and higher-order cognitive processes in norm enforcement. PsycINFO Database Record (c) 2016 APA, all rights reserved.

OPERATOR NORM INEQUALITIES BETWEEN TENSOR UNFOLDINGS ON THE PARTITION LATTICE.

PubMed

Wang, Miaoyan; Duc, Khanh Dao; Fischer, Jonathan; Song, Yun S

2017-05-01

Interest in higher-order tensors has recently surged in data-intensive fields, with a wide range of applications including image processing, blind source separation, community detection, and feature extraction. A common paradigm in tensor-related algorithms advocates unfolding (or flattening) the tensor into a matrix and applying classical methods developed for matrices. Despite the popularity of such techniques, how the functional properties of a tensor changes upon unfolding is currently not well understood. In contrast to the body of existing work which has focused almost exclusively on matricizations, we here consider all possible unfoldings of an order- k tensor, which are in one-to-one correspondence with the set of partitions of {1, …, k }. We derive general inequalities between the l p -norms of arbitrary unfoldings defined on the partition lattice. In particular, we demonstrate how the spectral norm ( p = 2) of a tensor is bounded by that of its unfoldings, and obtain an improved upper bound on the ratio of the Frobenius norm to the spectral norm of an arbitrary tensor. For specially-structured tensors satisfying a generalized definition of orthogonal decomposability, we prove that the spectral norm remains invariant under specific subsets of unfolding operations.

Using Goffman's theories of social interaction to reflect first-time mothers' experiences with the social norms of infant feeding.

PubMed

Brouwer, Marissa A; Drummond, Claire; Willis, Eileen

2012-10-01

Infant feeding, particularly breastfeeding, is an important public health issue because early feeding methods have been shown to influence health throughout childhood. We investigated how social norms influence first-time mothers' decisions around feeding methods. We conducted two in-depth interviews with 11 first-time mothers, the first 3 weeks after birth and the second 3 months following birth. We analyzed interview data using a third-level, thematic analysis, using Goffman's theories of social interaction to guide our analysis. Our results highlighted several issues surrounding breastfeeding in modern society. We propose that nursing mothers are conscious of adhering to social norms of being a good mother, but must also cope with societal views about presenting normal appearances when they need to feed their babies in public.

Estimating individual influences of behavioral intentions: an application of random-effects modeling to the theory of reasoned action.

PubMed

Hedeker, D; Flay, B R; Petraitis, J

1996-02-01

Methods are proposed and described for estimating the degree to which relations among variables vary at the individual level. As an example of the methods, M. Fishbein and I. Ajzen's (1975; I. Ajzen & M. Fishbein, 1980) theory of reasoned action is examined, which posits first that an individual's behavioral intentions are a function of 2 components: the individual's attitudes toward the behavior and the subjective norms as perceived by the individual. A second component of their theory is that individuals may weight these 2 components differently in assessing their behavioral intentions. This article illustrates the use of empirical Bayes methods based on a random-effects regression model to estimate these individual influences, estimating an individual's weighting of both of these components (attitudes toward the behavior and subjective norms) in relation to their behavioral intentions. This method can be used when an individual's behavioral intentions, subjective norms, and attitudes toward the behavior are all repeatedly measured. In this case, the empirical Bayes estimates are derived as a function of the data from the individual, strengthened by the overall sample data.

Multi-objective based spectral unmixing for hyperspectral images

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei

2017-02-01

Sparse hyperspectral unmixing assumes that each observed pixel can be expressed by a linear combination of several pure spectra in a priori library. Sparse unmixing is challenging, since it is usually transformed to a NP-hard l0 norm based optimization problem. Existing methods usually utilize a relaxation to the original l0 norm. However, the relaxation may bring in sensitive weighted parameters and additional calculation error. In this paper, we propose a novel multi-objective based algorithm to solve the sparse unmixing problem without any relaxation. We transform sparse unmixing to a multi-objective optimization problem, which contains two correlative objectives: minimizing the reconstruction error and controlling the endmember sparsity. To improve the efficiency of multi-objective optimization, a population-based randomly flipping strategy is designed. Moreover, we theoretically prove that the proposed method is able to recover a guaranteed approximate solution from the spectral library within limited iterations. The proposed method can directly deal with l0 norm via binary coding for the spectral signatures in the library. Experiments on both synthetic and real hyperspectral datasets demonstrate the effectiveness of the proposed method.

Assessment of the Anthropometric Accommodation Requirements of Non-Pilot Aircrew in the CC-150 Polaris, CP-140 Aurora, CH-149 Cormorant and CC-130 Hercules Aircraft (Exigences Anthropometriques Pour le Personnel Navigant dans le CC-150 Polaris, CP-140 Aurora, CH-149 Cormorant et CC-130 Hercules)

DTIC Science & Technology

2008-10-01

et planification en ressources humaines militaires a aboli la norme de taille minimum des Forces Canadiennes. On a conclu que "les...015; Defence R&D Canada – Toronto; October 2008. Introduction ou contexte : En février 2002, le directeur général – politiques et planification en...arming cables. ....................................................... 6 Figure 4 Reach of full throttle (left) and fire bottle T -handles (right

Is the Role of Equations in the Doing of Word Problems in School Algebra Changing? Initial Indications from Teacher Study Groups

ERIC Educational Resources Information Center

Chazan, Daniel; Sela, Hagit; Herbst, Patricio

2012-01-01

We illustrate a method, which is modeled on "breaching experiments," for studying tacit norms that govern classroom interaction around particular mathematical content. Specifically, this study explores norms that govern teachers' expectations for the doing of word problems in school algebra. Teacher study groups discussed representations of…

Bypassing the Limits of Ll Regularization: Convex Sparse Signal Processing Using Non-Convex Regularization

NASA Astrophysics Data System (ADS)

Parekh, Ankit

Sparsity has become the basis of some important signal processing methods over the last ten years. Many signal processing problems (e.g., denoising, deconvolution, non-linear component analysis) can be expressed as inverse problems. Sparsity is invoked through the formulation of an inverse problem with suitably designed regularization terms. The regularization terms alone encode sparsity into the problem formulation. Often, the ℓ1 norm is used to induce sparsity, so much so that ℓ1 regularization is considered to be `modern least-squares'. The use of ℓ1 norm, as a sparsity-inducing regularizer, leads to a convex optimization problem, which has several benefits: the absence of extraneous local minima, well developed theory of globally convergent algorithms, even for large-scale problems. Convex regularization via the ℓ1 norm, however, tends to under-estimate the non-zero values of sparse signals. In order to estimate the non-zero values more accurately, non-convex regularization is often favored over convex regularization. However, non-convex regularization generally leads to non-convex optimization, which suffers from numerous issues: convergence may be guaranteed to only a stationary point, problem specific parameters may be difficult to set, and the solution is sensitive to the initialization of the algorithm. The first part of this thesis is aimed toward combining the benefits of non-convex regularization and convex optimization to estimate sparse signals more effectively. To this end, we propose to use parameterized non-convex regularizers with designated non-convexity and provide a range for the non-convex parameter so as to ensure that the objective function is strictly convex. By ensuring convexity of the objective function (sum of data-fidelity and non-convex regularizer), we can make use of a wide variety of convex optimization algorithms to obtain the unique global minimum reliably. The second part of this thesis proposes a non-linear signal decomposition technique for an important biomedical signal processing problem: the detection of sleep spindles and K-complexes in human sleep electroencephalography (EEG). We propose a non-linear model for the EEG consisting of three components: (1) a transient (sparse piecewise constant) component, (2) a low-frequency component, and (3) an oscillatory component. The oscillatory component admits a sparse time-frequency representation. Using a convex objective function, we propose a fast non-linear optimization algorithm to estimate the three components in the proposed signal model. The low-frequency and oscillatory components are then used to estimate the K-complexes and sleep spindles respectively. The proposed detection method is shown to outperform several state-of-the-art automated sleep spindles detection methods.

Development and validation of qualitative SYBR®Green real-time PCR for detection and discrimination of Listeria spp. and Listeria monocytogenes.

PubMed

Barbau-Piednoir, Elodie; Botteldoorn, Nadine; Yde, Marc; Mahillon, Jacques; Roosens, Nancy H

2013-05-01

A combination of four qualitative SYBR®Green qPCR screening assays targeting two levels of discrimination: Listeria genus (except Listeria grayi) and Listeria monocytogenes, is presented. These assays have been developed to be run simultaneously using the same polymerase chain reaction (PCR) programme. The paper also proposes a new validation procedure to specifically validate qPCR assays applied to food microbiology according to two guidelines: the ISO 22118 norm and the "Definition of minimum performance requirements for analytical methods of GMO testing". The developed assays target the iap, prs and hlyA genes that belong to or neighbour the virulence cluster of Listeria spp. The selected primers were designed to amplify short fragments (60 to 103 bp) in order to obtain optimal PCR efficiency (between 97 and 107 % efficiency). The limit of detection of the SYBR®Green qPCR assays is two to five copies of target genes per qPCR reaction. These assays are highly accurate (98.08 and 100 % accuracy for the Listeria spp. and L. monocytogenes assays, respectively).

Application of generalized singular value decomposition to ionospheric tomography

NASA Astrophysics Data System (ADS)

Bhuyan, K.; Singh, S.; Bhuyan, P.

2004-10-01

The electron density distribution of the low- and mid-latitude ionosphere has been investigated by the computerized tomography technique using a Generalized Singular Value Decomposition (GSVD) based algorithm. Model ionospheric total electron content (TEC) data obtained from the International Reference Ionosphere 2001 and slant relative TEC data measured at a chain of three stations receiving transit satellite transmissions in Alaska, USA are used in this analysis. The issue of optimum efficiency of the GSVD algorithm in the reconstruction of ionospheric structures is being addressed through simulation of the equatorial ionization anomaly (EIA), in addition to its application to investigate complicated ionospheric density irregularities. Results show that the Generalized Cross Validation approach to find the regularization parameter and the corresponding solution gives a very good reconstructed image of the low-latitude ionosphere and the EIA within it. Provided that some minimum norm is fulfilled, the GSVD solution is found to be least affected by considerations, such as pixel size and number of ray paths. The method has also been used to investigate the behaviour of the mid-latitude ionosphere under magnetically quiet and disturbed conditions.

COMPARED TO WHAT? EARLY BRAIN OVERGROWTH IN AUTISM AND THE PERILS OF POPULATION NORMS

PubMed Central

Raznahan, Armin; Wallace, Gregory L; Antezana, Ligia; Greenstein, Dede; Lenroot, Rhoshel; Thurm, Audrey; Gozzi, Marta; Spence, Sarah; Martin, Alex; Swedo, Susan E; Giedd, Jay N

2013-01-01

Background Early brain overgrowth (EBO) in autism spectrum disorder (ASD) is amongst the best-replicated biological associations in psychiatry. Most positive reports have compared head circumference (HC) in ASD (an excellent proxy for early brain size) with well-known reference norms. We sought to reappraise evidence for the EBO hypothesis given (i) the recent proliferation of longitudinal HC studies in ASD, and (ii) emerging reports that several of the reference norms used to define EBO in ASD may be biased towards detecting HC overgrowth in contemporary samples of healthy children. Methods (1)Systematic review of all published HC studies in children with ASD. (2)Comparison of 330 longitudinally gathered HC measures between birth and 18 months from male children with autism(n=35) and typically developing controls(n=22). Results In systematic review, comparisons with locally recruited controls were significantly less likely to identify EBO in ASD than norm-based studies(p<0.006). Through systematic review and analysis of new data we replicate seminal reports of EBO in ASD relative to classical HC norms, but show that this overgrowth relative to norms is mimicked by patterns of HC growth age in a large contemporary community-based sample of US children(n~75,000). Controlling for known HC norm biases leaves inconsistent support for a subtle, later-emerging and sub-group specific pattern of EBO in clinically-ascertained ASD vs. community controls. Conclusions The best-replicated aspects of EBO reflect generalizable HC norm biases rather than disease-specific biomarkers. The potential HC norm biases we detail are not specific to ASD research, but apply throughout clinical and academic medicine. PMID:23706681

Estimation of the chemical rank for the three-way data: a principal norm vector orthogonal projection approach.

PubMed

Hong-Ping, Xie; Jian-Hui, Jiang; Guo-Li, Shen; Ru-Qin, Yu

2002-01-01

A new approach for estimating the chemical rank of the three-way array called the principal norm vector orthogonal projection method has been proposed. The method is based on the fact that the chemical rank of the three-way data array is equal to one of the column space of the unfolded matrix along the spectral or chromatographic mode. A vector with maximum Frobenius norm is selected among all the column vectors of the unfolded matrix as the principal norm vector (PNV). A transformation is conducted for the column vectors with an orthogonal projection matrix formulated by PNV. The mathematical rank of the column space of the residual matrix thus obtained should decrease by one. Such orthogonal projection is carried out repeatedly till the contribution of chemical species to the signal data is all deleted. At this time the decrease of the mathematical rank would equal that of the chemical rank, and the remaining residual subspace would entirely be due to the noise contribution. The chemical rank can be estimated easily by using an F-test. The method has been used successfully to the simulated HPLC-DAD type three-way data array and two real excitation-emission fluorescence data sets of amino acid mixtures and dye mixtures. The simulation with added relatively high level noise shows that the method is robust in resisting the heteroscedastic noise. The proposed algorithm is simple and easy to program with quite light computational burden.

Evaluating Level of Specificity of Normative Referents in Relation to Personal Drinking Behavior*

PubMed Central

Larimer, Mary E.; Kaysen, Debra L.; Lee, Christine M.; Kilmer, Jason R.; Lewis, Melissa A.; Dillworth, Tiara; Montoya, Heidi D.; Neighbors, Clayton

2009-01-01

Objective: Research has found perceived descriptive norms to be one of the strongest predictors of college student drinking, and several intervention approaches have incorporated normative feedback to correct misperceptions of peer drinking behavior. Little research has focused on the role of the reference group in normative perceptions. The current study sought to examine whether normative perceptions vary based on specificity of the reference group and whether perceived norms for more specific reference-group norms are related to individual drinking behavior. Method: Participants were first-year undergraduates (n = 1,276, 58% female) randomly selected from a university list of incoming students. Participants reported personal drinking behavior and perceived descriptive norms for eight reference groups, including typical student; same gender, ethnicity, or residence; and combinations of those reference groups (e.g., same gender and residence). Results: Findings indicated that participants distinguished among different reference groups in estimating descriptive drinking norms. Moreover, results indicated misperceptions in drinking norms were evident at all levels of specificity of the reference group. Additionally, findings showed perceived norms for more specific groups were uniquely related to participants' own drinking. Conclusions: These results suggest that providing normative feedback targeting at least one level of specificity to the participant (i.e., beyond what the “typical” student does) may be an important tool in normative feedback interventions. PMID:19538919

A new smoothing modified three-term conjugate gradient method for [Formula: see text]-norm minimization problem.

PubMed

Du, Shouqiang; Chen, Miao

2018-01-01

We consider a kind of nonsmooth optimization problems with [Formula: see text]-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems. Using smoothing approximate techniques, this kind of nonsmooth optimization problem can be transformed into a general unconstrained optimization problem, which can be solved by the proposed smoothing modified three-term conjugate gradient method. The smoothing modified three-term conjugate gradient method is based on Polak-Ribière-Polyak conjugate gradient method. For the Polak-Ribière-Polyak conjugate gradient method has good numerical properties, the proposed method possesses the sufficient descent property without any line searches, and it is also proved to be globally convergent. Finally, the numerical experiments show the efficiency of the proposed method.

Research in computational fluid dynamics and analysis of algorithms

NASA Technical Reports Server (NTRS)

Gottlieb, David

1992-01-01

Recently, higher-order compact schemes have seen increasing use in the DNS (Direct Numerical Simulations) of the Navier-Stokes equations. Although they do not have the spatial resolution of spectral methods, they offer significant increases in accuracy over conventional second order methods. They can be used on any smooth grid, and do not have an overly restrictive CFL dependence as compared with the O(N(exp -2)) CFL dependence observed in Chebyshev spectral methods on finite domains. In addition, they are generally more robust and less costly than spectral methods. The issue of the relative cost of higher-order schemes (accuracy weighted against physical and numerical cost) is a far more complex issue, depending ultimately on what features of the solution are sought and how accurately they must be resolved. In any event, the further development of the underlying stability theory of these schemes is important. The approach of devising suitable boundary clusters and then testing them with various stability techniques (such as finding the norm) is entirely the wrong approach when dealing with high-order methods. Very seldom are high-order boundary closures stable, making them difficult to isolate. An alternative approach is to begin with a norm which satisfies all the stability criteria for the hyperbolic system, and look for the boundary closure forms which will match the norm exactly. This method was used recently by Strand to isolate stable boundary closure schemes for the explicit central fourth- and sixth-order schemes. The norm used was an energy norm mimicking the norm for the differential equations. Further research should be devoted to BC for high order schemes in order to make sure that the results obtained are reliable. The compact fourth order and sixth order finite difference scheme had been incorporated into a code to simulate flow past circular cylinders. This code will serve as a verification of the full spectral codes. A detailed stability analysis by Carpenter (from the fluid Mechanics Division) and Gottlieb gave analytic conditions for stability as well as asymptotic stability. This had been incorporated in the code in form of stable boundary conditions. Effects of the cylinder rotations had been studied. The results differ from the known theoretical results. We are in the middle of analyzing the results. A detailed analysis of the effects of the heating of the cylinder on the shedding frequency had been studied using the above schemes. It has been found that the shedding frequency decreases when the wire was heated. Experimental work is being carried out to affirm this result.

From Abstract to Concrete Norms in Agent Institutions

NASA Technical Reports Server (NTRS)

Grossi, Davide; Dignum, Frank

2004-01-01

Norms specifying constraints over institutions are stated in such a form that allows them to regulate a wide range of situations over time without need for modification. To guarantee this stability, the formulation of norms need to abstract from a variety of concrete aspects, which are instead relevant for the actual operationalization of institutions. If agent institutions are to be built, which comply with a set of abstract requirements, how can those requirements be translated in more concrete constraints the impact of which can be described directly in the institution? In this work we make use of logical methods in order to provide a formal characterization of the translation rules that operate the connection between abstract and concrete norms. On the basis of this characterization, a comprehensive formalization of the notion of institution is also provided.

Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares.

PubMed

Zhang, Cheng; Zhang, Tao; Li, Ming; Peng, Chengtao; Liu, Zhaobang; Zheng, Jian

2016-06-18

In order to reduce the radiation dose of CT (computed tomography), compressed sensing theory has been a hot topic since it provides the possibility of a high quality recovery from the sparse sampling data. Recently, the algorithm based on DL (dictionary learning) was developed to deal with the sparse CT reconstruction problem. However, the existing DL algorithm focuses on the minimization problem with the L2-norm regularization term, which leads to reconstruction quality deteriorating while the sampling rate declines further. Therefore, it is essential to improve the DL method to meet the demand of more dose reduction. In this paper, we replaced the L2-norm regularization term with the L1-norm one. It is expected that the proposed L1-DL method could alleviate the over-smoothing effect of the L2-minimization and reserve more image details. The proposed algorithm solves the L1-minimization problem by a weighting strategy, solving the new weighted L2-minimization problem based on IRLS (iteratively reweighted least squares). Through the numerical simulation, the proposed algorithm is compared with the existing DL method (adaptive dictionary based statistical iterative reconstruction, ADSIR) and other two typical compressed sensing algorithms. It is revealed that the proposed algorithm is more accurate than the other algorithms especially when further reducing the sampling rate or increasing the noise. The proposed L1-DL algorithm can utilize more prior information of image sparsity than ADSIR. By transforming the L2-norm regularization term of ADSIR with the L1-norm one and solving the L1-minimization problem by IRLS strategy, L1-DL could reconstruct the image more exactly.

Total variation regularization for seismic waveform inversion using an adaptive primal dual hybrid gradient method

NASA Astrophysics Data System (ADS)

Yong, Peng; Liao, Wenyuan; Huang, Jianping; Li, Zhenchuan

2018-04-01

Full waveform inversion is an effective tool for recovering the properties of the Earth from seismograms. However, it suffers from local minima caused mainly by the limited accuracy of the starting model and the lack of a low-frequency component in the seismic data. Because of the high velocity contrast between salt and sediment, the relation between the waveform and velocity perturbation is strongly nonlinear. Therefore, salt inversion can easily get trapped in the local minima. Since the velocity of salt is nearly constant, we can make the most of this characteristic with total variation regularization to mitigate the local minima. In this paper, we develop an adaptive primal dual hybrid gradient method to implement total variation regularization by projecting the solution onto a total variation norm constrained convex set, through which the total variation norm constraint is satisfied at every model iteration. The smooth background velocities are first inverted and the perturbations are gradually obtained by successively relaxing the total variation norm constraints. Numerical experiment of the projection of the BP model onto the intersection of the total variation norm and box constraints has demonstrated the accuracy and efficiency of our adaptive primal dual hybrid gradient method. A workflow is designed to recover complex salt structures in the BP 2004 model and the 2D SEG/EAGE salt model, starting from a linear gradient model without using low-frequency data below 3 Hz. The salt inversion processes demonstrate that wavefield reconstruction inversion with a total variation norm and box constraints is able to overcome local minima and inverts the complex salt velocity layer by layer.

Workplace Substance-Use Norms as Predictors of Employee Substance Use and Impairment: A Survey of U.S. Workers*

PubMed Central

Frone, Michael R.; Brown, Amy L.

2010-01-01

Objective: Although much research has explored the relation of substance-use norms to substance use among college students, much less research has focused on employed adults and the workplace as a social context for social norms regarding substance use. This study explored the relation of descriptive and injunctive workplace substance-use norms regarding alcohol and illicit drug use to employee substance use. Both alcohol use and illicit drug use were explored, as well as overall and context-specific use and impairment. Method: Data were collected from a national probability sample of 2,430 employed adults (55% female) using a random-digit-dial telephone survey. Overall employee alcohol and illicit drug use were assessed, as well as use before work, use and impairment during the workday, and use after work. Results: After controlling for a number of potential covariates, injunctive norms regarding workplace alcohol and illicit drug use predicted substance use and impairment overall and across all contexts of use. Descriptive norms predicted alcohol and illicit drug use before and during work, as well as workplace impairment. Conclusions: This study shows that both workplace injunctive and descriptive norms are important predictors of substance use in the U.S. workforce. There were two general patterns, however, that were consistent across both alcohol and illicit drug use. Social norms marketing campaigns, therefore, may be a useful way for employers to target employee substance use. The present results also helped to integrate the results of several prior studies that employed narrower samples and measures. PMID:20553660

Making the transition to workload-based staffing: using the Workload Indicators of Staffing Need method in Uganda.

PubMed

Namaganda, Grace; Oketcho, Vincent; Maniple, Everd; Viadro, Claire

2015-08-31

Uganda's health workforce is characterized by shortages and inequitable distribution of qualified health workers. To ascertain staffing levels, Uganda uses fixed government-approved norms determined by facility type. This approach cannot distinguish between facilities of the same type that have different staffing needs. The Workload Indicators of Staffing Need (WISN) method uses workload to determine number and type of staff required in a given facility. The national WISN assessment sought to demonstrate the limitations of the existing norms and generate evidence to influence health unit staffing and staff deployment for efficient utilization of available scarce human resources. A national WISN assessment (September 2012) used purposive sampling to select 136 public health facilities in 33/112 districts. The study examined staffing requirements for five cadres (nursing assistants, nurses, midwives, clinical officers, doctors) at health centres II (n = 59), III (n = 53) and IV (n = 13) and hospitals (n = 11). Using health management information system workload data (1 July 2010-30 June 2011), the study compared current and required staff, assessed workload pressure and evaluated the adequacy of the existing staffing norms. By the WISN method, all three types of health centres had fewer nurses (42-70%) and midwives (53-67%) than required and consequently exhibited high workload pressure (30-58%) for those cadres. Health centres IV and hospitals lacked doctors (39-42%) but were adequately staffed with clinical officers. All facilities displayed overstaffing of nursing assistants. For all cadres at health centres III and IV other than nursing assistants, the fixed norms or existing staffing or both fell short of the WISN staffing requirements, with, for example, only half as many nurses and midwives as required. The WISN results demonstrate the inadequacies of existing staffing norms, particularly for health centres III and IV. The results provide an evidence base to reshape policy, adopt workload-based norms, review scopes of practice and target human resource investments. In the near term, the government could redistribute existing health workers to improve staffing equity in line with the WISN results. Longer term revision of staffing norms and investments to effectively reflect actual workloads and ensure provision of quality services at all levels is needed.

A fast linearized conservative finite element method for the strongly coupled nonlinear fractional Schrödinger equations

NASA Astrophysics Data System (ADS)

Li, Meng; Gu, Xian-Ming; Huang, Chengming; Fei, Mingfa; Zhang, Guoyu

2018-04-01

In this paper, a fast linearized conservative finite element method is studied for solving the strongly coupled nonlinear fractional Schrödinger equations. We prove that the scheme preserves both the mass and energy, which are defined by virtue of some recursion relationships. Using the Sobolev inequalities and then employing the mathematical induction, the discrete scheme is proved to be unconditionally convergent in the sense of L2-norm and H α / 2-norm, which means that there are no any constraints on the grid ratios. Then, the prior bound of the discrete solution in L2-norm and L∞-norm are also obtained. Moreover, we propose an iterative algorithm, by which the coefficient matrix is independent of the time level, and thus it leads to Toeplitz-like linear systems that can be efficiently solved by Krylov subspace solvers with circulant preconditioners. This method can reduce the memory requirement of the proposed linearized finite element scheme from O (M2) to O (M) and the computational complexity from O (M3) to O (Mlog ⁡ M) in each iterative step, where M is the number of grid nodes. Finally, numerical results are carried out to verify the correction of the theoretical analysis, simulate the collision of two solitary waves, and show the utility of the fast numerical solution techniques.

Automatic extraction of property norm-like data from large text corpora.

PubMed

Kelly, Colin; Devereux, Barry; Korhonen, Anna

2014-01-01

Traditional methods for deriving property-based representations of concepts from text have focused on either extracting only a subset of possible relation types, such as hyponymy/hypernymy (e.g., car is-a vehicle) or meronymy/metonymy (e.g., car has wheels), or unspecified relations (e.g., car--petrol). We propose a system for the challenging task of automatic, large-scale acquisition of unconstrained, human-like property norms from large text corpora, and discuss the theoretical implications of such a system. We employ syntactic, semantic, and encyclopedic information to guide our extraction, yielding concept-relation-feature triples (e.g., car be fast, car require petrol, car cause pollution), which approximate property-based conceptual representations. Our novel method extracts candidate triples from parsed corpora (Wikipedia and the British National Corpus) using syntactically and grammatically motivated rules, then reweights triples with a linear combination of their frequency and four statistical metrics. We assess our system output in three ways: lexical comparison with norms derived from human-generated property norm data, direct evaluation by four human judges, and a semantic distance comparison with both WordNet similarity data and human-judged concept similarity ratings. Our system offers a viable and performant method of plausible triple extraction: Our lexical comparison shows comparable performance to the current state-of-the-art, while subsequent evaluations exhibit the human-like character of our generated properties.

Norms and stigma around unintended pregnancy in Alabama: Associations with recent contraceptive use and dual method use among young women.

PubMed

Rice, Whitney S; Turan, Bulent; White, Kari; Turan, Janet M

2017-12-14

The role of unintended pregnancy norms and stigma in contraceptive use among young women is understudied. This study investigated relationships between anticipated reactions from others, perceived stigma, and endorsed stigma concerning unintended pregnancy, with any and dual contraceptive use in this population. From November 2014 to October 2015, young women aged 18-24 years (n = 390) and at risk for unintended pregnancy and sexually transmitted infections participated in a survey at a university and public health clinics in Alabama. Multivariable regression models examined associations of unintended pregnancy norms and stigma with contraceptive use, adjusted for demographic and psychosocial characteristics. Compared to nonusers, more any and dual method users, were White, nulliparous, and from the university and had higher income. In adjusted models, anticipated disapproval of unintended pregnancy by close others was associated with greater contraceptive use (adjusted Odds Ratio [aOR] = 1.54, 95 percent confidence interval [CI] = 1.03-2.30), and endorsement of stigma concerning unintended pregnancy was associated with lower odds of dual method use (aOR = 0.71, 95 percent CI = 0.51-1.00). Unintended pregnancy norms and stigma were associated with contraceptive behavior among young women in Alabama. Findings suggest the potential to promote effective contraceptive use in this population by leveraging close relationships and addressing endorsed stigma.

Research to Establish the Validity, Reliability, and Clinical Utility of a Comprehensive Language Assessment of Mandarin

ERIC Educational Resources Information Center

Liu, Xueman Lucy; de Villiers, Jill; Ning, Chunyan; Rolfhus, Eric; Hutchings, Teresa; Lee, Wendy; Jiang, Fan; Zhang, Yi Wen

2017-01-01

Purpose: With no existing gold standard for comparison, challenges arise for establishing the validity of a new standardized Mandarin language assessment normed in mainland China. Method: A new assessment, Diagnostic Receptive and Expressive Assessment of Mandarin (DREAM), was normed with a stratified sample of 969 children ages 2;6 (years;months)…

Children's Judgments of Inequitable Distributions That Conform to Gender Norms

ERIC Educational Resources Information Center

Conry-Murray, Clare

2015-01-01

To evaluate whether distributions by sex are judged to be unfair, children at ages 6, 8, and 10, and adults (N = 96), judged an authority distributing items to children by using different methods (i.e., randomly or by sex), types of items (i.e., related or unrelated to gender norms), and differences in the equivalency of the items (i.e.,…

Mayo's Older American Normative Studies: Separate Norms for WMS-R Logical Memory Stories.

ERIC Educational Resources Information Center

Smith, Glenn E.; Wong, Jennifer S.; Ivnik, Robert J.; Malec, James F.

1997-01-01

Norms are presented for persons ages 56 to 93 years for each story from the Logical Memory subtests of the revised edition of the Wechsler Memory Scale following the methods used for other Mayo's Older American Normative Studies. Means and standard deviations are presented for 3-year interval age groups from age 61 to 88. (SLD)

Stable Reference Gene Selection for RT-qPCR Analysis in Nonviruliferous and Viruliferous Frankliniella occidentalis.

PubMed

Yang, Chunxiao; Li, Hui; Pan, Huipeng; Ma, Yabin; Zhang, Deyong; Liu, Yong; Zhang, Zhanhong; Zheng, Changying; Chu, Dong

2015-01-01

Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) is a reliable technique for measuring and evaluating gene expression during variable biological processes. To facilitate gene expression studies, normalization of genes of interest relative to stable reference genes is crucial. The western flower thrips Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae), the main vector of tomato spotted wilt virus (TSWV), is a destructive invasive species. In this study, the expression profiles of 11 candidate reference genes from nonviruliferous and viruliferous F. occidentalis were investigated. Five distinct algorithms, geNorm, NormFinder, BestKeeper, the ΔCt method, and RefFinder, were used to determine the performance of these genes. geNorm, NormFinder, BestKeeper, and RefFinder identified heat shock protein 70 (HSP70), heat shock protein 60 (HSP60), elongation factor 1 α, and ribosomal protein l32 (RPL32) as the most stable reference genes, and the ΔCt method identified HSP60, HSP70, RPL32, and heat shock protein 90 as the most stable reference genes. Additionally, two reference genes were sufficient for reliable normalization in nonviruliferous and viruliferous F. occidentalis. This work provides a foundation for investigating the molecular mechanisms of TSWV and F. occidentalis interactions.

Moving Forward with School Nutrition Policies: A Case Study of Policy Adherence in Nova Scotia.

PubMed

McIsaac, Jessie-Lee D; Shearer, Cindy L; Veugelers, Paul J; Kirk, Sara F L

2015-12-01

Many Canadian school jurisdictions have developed nutrition policies to promote health and improve the nutritional status of children, but research is needed to clarify adherence, guide practice-related decisions, and move policy action forward. The purpose of this research was to evaluate policy adherence with a review of online lunch menus of elementary schools in Nova Scotia (NS) while also providing transferable evidence for other jurisdictions. School menus in NS were scanned and a list of commonly offered items were categorized, according to minimum, moderate, or maximum nutrition categories in the NS policy. The results of the menu review showed variability in policy adherence that depended on food preparation practices by schools. Although further research is needed to clarify preparation practices, the previously reported challenges of healthy food preparations (e.g., cost, social norms) suggest that many schools in NS are likely not able to use these healthy preparations, signifying potential noncompliance to the policy. Leadership and partnerships are needed among researchers, policy makers, and nutrition practitioners to address the complexity of issues related to food marketing and social norms that influence school food environments to inspire a culture where healthy and nutritious food is available and accessible to children.

Quantitative Comparison of Minimum Inductance and Minimum Power Algorithms for the Design of Shim Coils for Small Animal Imaging

PubMed Central

HUDSON, PARISA; HUDSON, STEPHEN D.; HANDLER, WILLIAM B.; SCHOLL, TIMOTHY J.; CHRONIK, BLAINE A.

2010-01-01

High-performance shim coils are required for high-field magnetic resonance imaging and spectroscopy. Complete sets of high-power and high-performance shim coils were designed using two different methods: the minimum inductance and the minimum power target field methods. A quantitative comparison of shim performance in terms of merit of inductance (ML) and merit of resistance (MR) was made for shim coils designed using the minimum inductance and the minimum power design algorithms. In each design case, the difference in ML and the difference in MR given by the two design methods was <15%. Comparison of wire patterns obtained using the two design algorithms show that minimum inductance designs tend to feature oscillations within the current density; while minimum power designs tend to feature less rapidly varying current densities and lower power dissipation. Overall, the differences in coil performance obtained by the two methods are relatively small. For the specific case of shim systems customized for small animal imaging, the reduced power dissipation obtained when using the minimum power method is judged to be more significant than the improvements in switching speed obtained from the minimum inductance method. PMID:20411157

Cultural influence on crowding norms in outdoor recreation: a comparative analysis of visitors to national parks in Turkey and the United States.

PubMed

Sayan, Selcuk; Krymkowski, Daniel H; Manning, Robert E; Valliere, William A; Rovelstad, Ellen L

2013-08-01

Formulation of standards of quality in parks and outdoor recreation can be guided by normative theory and related empirical methods. We apply this approach to measure the acceptability of a range of use levels in national parks in Turkey and the United States. Using statistical methods for comparing norm curves across contexts, we find significant differences among Americans, British, and Turkish respondents. In particular, American and British respondents were substantially less tolerant of seeing other visitors and demonstrated higher norm intensity than Turkish respondents. We discuss the role of culture in explaining these findings, paying particular attention to Turkey as a traditional "contact culture" and the conventional emphasis on solitude and escape in American environmental history and policy. We conclude with a number of recommendations to stimulate more research on the relationship between culture and outdoor recreation.

Mixed H(2)/H(sub infinity): Control with output feedback compensators using parameter optimization

NASA Technical Reports Server (NTRS)

Schoemig, Ewald; Ly, Uy-Loi

1992-01-01

Among the many possible norm-based optimization methods, the concept of H-infinity optimal control has gained enormous attention in the past few years. Here the H-infinity framework, based on the Small Gain Theorem and the Youla Parameterization, effectively treats system uncertainties in the control law synthesis. A design approach involving a mixed H(sub 2)/H-infinity norm strives to combine the advantages of both methods. This advantage motivates researchers toward finding solutions to the mixed H(sub 2)/H-infinity control problem. The approach developed in this research is based on a finite time cost functional that depicts an H-infinity bound control problem in a H(sub 2)-optimization setting. The goal is to define a time-domain cost function that optimizes the H(sub 2)-norm of a system with an H-infinity-constraint function.

Mixed H2/H(infinity)-Control with an output-feedback compensator using parameter optimization

NASA Technical Reports Server (NTRS)

Schoemig, Ewald; Ly, Uy-Loi

1992-01-01

Among the many possible norm-based optimization methods, the concept of H-infinity optimal control has gained enormous attention in the past few years. Here the H-infinity framework, based on the Small Gain Theorem and the Youla Parameterization, effectively treats system uncertainties in the control law synthesis. A design approach involving a mixed H(sub 2)/H-infinity norm strives to combine the advantages of both methods. This advantage motivates researchers toward finding solutions to the mixed H(sub 2)/H-infinity control problem. The approach developed in this research is based on a finite time cost functional that depicts an H-infinity bound control problem in a H(sub 2)-optimization setting. The goal is to define a time-domain cost function that optimizes the H(sub 2)-norm of a system with an H-infinity-constraint function.

Parents and friends both matter: simultaneous and interactive influences of parents and friends on European schoolchildren’s energy balance-related behaviours – the ENERGY cross-sectional study

PubMed Central

2014-01-01

Background The family, and parents in particular, are considered the most important influencers regarding children’s energy-balance related behaviours (EBRBs). When children become older and gain more behavioural autonomy regarding different behaviours, the parental influences may become less important and peer influences may gain importance. Therefore the current study aims to investigate simultaneous and interactive associations of family rules, parent and friend norms and modelling with soft drink intake, TV viewing, daily breakfast consumption and sport participation among schoolchildren across Europe. Methods A school-based cross-sectional survey in eight countries across Europe among 10–12 year old schoolchildren. Child questionnaires were used to assess EBRBs (soft drink intake, TV viewing, breakfast consumption, sport participation), and potential determinants of these behaviours as perceived by the child, including family rules, parental and friend norms and modelling. Linear and logistic regression analyses (n = 7811) were applied to study the association of parental (norms, modelling and rules) and friend influences (norm and modelling) with the EBRBs. In addition, potential moderating effects of parental influences on the associations of friend influences with the EBRBs were studied by including interaction terms. Results Children reported more unfavourable friend norms and modelling regarding soft drink intake and TV viewing, while they reported more favourable friend and parental norms and modelling for breakfast consumption and physical activity. Perceived friend and parental norms and modelling were significantly positively associated with soft drink intake, breakfast consumption, physical activity (only modelling) and TV time. Across the different behaviours, ten significant interactions between parental and friend influencing variables were found and suggested a weaker association of friend norms and modelling when rules were in place. Conclusion Parental and friends norm and modelling are associated with schoolchildren’s energy balance-related behaviours. Having family rules or showing favourable parental modelling and norms seems to reduce the potential unfavourable associations of friends’ norms and modelling with the EBRBs. PMID:25001090

Examining social norm impacts on obesity and eating behaviors among US school children based on agent-based model.

PubMed

Wang, Youfa; Xue, Hong; Chen, Hsin-jen; Igusa, Takeru

2014-09-06

Although the importance of social norms in affecting health behaviors is widely recognized, the current understanding of the social norm effects on obesity is limited due to data and methodology limitations. This study aims to use nontraditional innovative systems methods to examine: a) the effects of social norms on school children's BMI growth and fruit and vegetable (FV) consumption, and b) the effects of misperceptions of social norms on US children's BMI growth. We built an agent-based model (ABM) in a utility maximization framework and parameterized the model based on empirical longitudinal data collected in a US nationally representative study, the Early Childhood Longitudinal Study - Kindergarten Cohort (ECLS-K), to test potential mechanisms of social norm affecting children's BMI growth and FV consumption. Intraclass correlation coefficients (ICC) for BMI were 0.064-0.065, suggesting that children's BMI were similar within each school. The correlation between observed and ABM-predicted BMI was 0.87, indicating the validity of our ABM. Our simulations suggested the follow-the-average social norm acts as an endogenous stabilizer, which automatically adjusts positive and negative deviance of an individual's BMI from the group mean of a social network. One unit of BMI below the social average may lead to 0.025 unit increase in BMI per year for each child; asymmetrically, one unit of BMI above the social average, may only cause 0.015 unit of BMI reduction. Gender difference was apparent. Social norms have less impact on weight reduction among girls, and a greater impact promoting weight increase among boys. Our simulation also showed misperception of the social norm would push up the mean BMI and cause the distribution to be more skewed to the left. Our simulation results did not provide strong support for the role of social norms on FV consumption. Social norm influences US children's BMI growth. High obesity prevalence will lead to a continuous increase in children's BMI due to increased socially acceptable mean BMI. Interventions promoting healthy body image and desirable socially acceptable BMI should be implemented to control childhood obesity epidemic.

Path planning for assembly of strut-based structures. Thesis

NASA Technical Reports Server (NTRS)

Muenger, Rolf

1991-01-01

A path planning method with collision avoidance for a general single chain nonredundant or redundant robot is proposed. Joint range boundary overruns are also avoided. The result is a sequence of joint vectors which are passed to a trajectory planner. A potential field algorithm in joint space computes incremental joint vectors delta-q = delta-q(sub a) + delta-q(sub c) + delta-q(sub r). Adding delta-q to the robot's current joint vector leads to the next step in the path. Delta-q(sub a) is obtained by computing the minimum norm solution of the underdetermined linear system J delta-q(sub a) = x(sub a) where x(sub a) is a translational and rotational force vector that attracts the robot to its goal position and orientation. J is the manipulator Jacobian. Delta-q(sub c) is a collision avoidance term encompassing collisions between the robot (links and payload) and obstacles in the environment as well as collisions among links and payload of the robot themselves. It is obtained in joint space directly. Delta-q(sub r) is a function of the current joint vector and avoids joint range overruns. A higher level discrete search over candidate safe positions is used to provide alternatives in case the potential field algorithm encounters a local minimum and thus fails to reach the goal. The best first search algorithm A* is used for graph search. Symmetry properties of the payload and equivalent rotations are exploited to further enlarge the number of alternatives passed to the potential field algorithm.

A simple DVH generation technique for various radiotherapy treatment planning systems for an independent information system

NASA Astrophysics Data System (ADS)

Min, Byung Jun; Nam, Heerim; Jeong, Il Sun; Lee, Hyebin

2015-07-01

In recent years, the use of a picture archiving and communication system (PACS) for radiation therapy has become the norm in hospital environments and has been suggested for collecting and managing data using Digital Imaging and Communication in Medicine (DICOM) objects from different treatment planning systems (TPSs). However, some TPSs do not provide the ability to export the dose-volume histogram (DVH) in text or other format. In addition, plan review systems for various TPSs often allow DVH recalculations with different algorithms. These algorithms result in inevitable discrepancies between the values obtained with the recalculation and those obtained with TPS itself. The purpose of this study was to develop a simple method for generating reproducible DVH values by using the TPSs. Treatment planning information, including structures and delivered dose, was exported in the DICOM format from the Eclipse v8.9 or the Pinnacle v9.6 planning systems. The supersampling and trilinear interpolation methods were employed to calculate the DVH data from 35 treatment plans. The discrepancies between the DVHs extracted from each TPS and those extracted by using the proposed calculation method were evaluated with respect to the supersampling ratio. The volume, minimum dose, maximum dose, and mean dose were compared. The variations in DVHs from multiple TPSs were compared by using the MIM software v6.1, which is a commercially available treatment planning comparison tool. The overall comparisons of the volume, minimum dose, maximum dose, and mean dose showed that the proposed method generated relatively smaller discrepancies compared with TPS than the MIM software did compare with the TPS. As the structure volume decreased, the overall percent difference increased. The largest difference was observed in small organs such as the eye ball, eye lens, and optic nerve which had volume below 10 cc. A simple and useful technique was developed to generate a DVH with an acceptable error from a proprietary TPS. This study provides a convenient and common framework that will allow the use of a single well-managed storage solution for an independent information system.

Reproducing normative and marginalized masculinities: adolescent male popularity and the outcast.

PubMed

Phillips, Debby A

2005-09-01

Every day, in professional work and in our personal lives, we reproduce by words and behaviors particular understandings of life and how it works. This includes understandings about what is 'normal' and 'not normal' masculinity and who are 'normal' and 'not normal' boys and men. Being marginalized or outcast from the norm is rarely a free choice. The language that constructs normal and abnormal is not innocent and does not simply arrive in our minds transparently reflected in our behavior or in our client advice or student education. Examining words and behaviors from adolescent boys and from media sources, this research explores the role of cultural discourses in producing normative and marginalized masculinities. It builds upon recent scholarship that questions cultural prescriptions for masculinity and traditional male norms. Feminist, poststructural, psychoanalytic discourse analysis and multiple methods were used to explore links between cultural discourses of masculinity and performativity of masculinity. Practices of heterosexuality, homophobia, athleticism, economic privilege, toughness, and violence provided pathways toward achieving and/or maintaining status as the hegemonic masculine norm in adolescence. 'Popularity' signified the norm and 'outcasts' from the norm signified marginalized masculinities.

Social anxiety and social norms in individualistic and collectivistic countries

PubMed Central

Schreier, Sina-Simone; Heinrichs, Nina; Alden, Lynn; Rapee, Ronald M.; Hofmann, Stefan G.; Chen, Junwen; Ja Oh, Kyung; Bögels, Susan

2010-01-01

Background Social anxiety is assumed to be related to cultural norms across countries. Heinrichs and colleagues [1] compared individualistic and collectivistic countries and found higher social anxiety and more positive attitudes toward socially avoidant behaviors in collectivistic than in individualistic countries. However, the authors failed to include Latin American countries in the collectivistic group. Methods To provide support for these earlier results within an extended sample of collectivistic countries, 478 undergraduate students from individualistic countries were compared with 388 undergraduate students from collectivistic countries (including East Asian and Latin American) via self report of social anxiety and social vignettes assessing social norms. Results As expected, the results of Heinrichs and colleagues [1] were replicated for the individualistic and Asian countries but not for Latin American countries. Latin American countries displayed the lowest social anxiety levels, whereas the collectivistic East Asian group displayed the highest. Conclusions These findings indicate that while culture-mediated social norms affect social anxiety and might help to shed light on the etiology of social anxiety disorder, the dimension of individualism-collectivism may not fully capture the relevant norms. PMID:21049538

Dutch taboo norms.

PubMed

Roest, Sander A; Visser, Tessa A; Zeelenberg, René

2018-04-01

This article provides norms for general taboo, personal taboo, insult, valence, and arousal for 672 Dutch words, including 202 taboo words. Norms were collected using a 7-point Likert scale and based on ratings by psychology students from the Erasmus University Rotterdam in The Netherlands. The sample consisted of 87 psychology students (58 females, 29 males). We obtained high reliability based on split-half analyses. Our norms show high correlations with arousal and valence ratings collected by another Dutch word-norms study (Moors et al.,, Behavior Research Methods, 45, 169-177, 2013). Our results show that the previously found quadratic relation (i.e., U-shaped pattern) between valence and arousal also holds when only taboo words are considered. Additionally, words rated high on taboo tended to be rated low on valence, but some words related to sex rated high on both taboo and valence. Words that rated high on taboo rated high on insult, again with the exception of words related to sex many of which rated low on insult. Finally, words rated high on taboo and insult rated high on arousal. The Dutch Taboo Norms (DTN) database is a useful tool for researchers interested in the effects of taboo words on cognitive processing. The data associated with this paper can be accessed via the Open Science Framework ( https://osf.io/vk782/ ).

Testing three pathways to substance use and delinquency among low-income African American adolescents☆

PubMed Central

Marotta, Phillip L.; Voisin, Dexter R.

2017-01-01

Objective Mounting literature suggests that parental monitoring, risky peer norms, and future orientation correlate with illicit drug use and delinquency. However, few studies have investigated these constructs simultaneously in a single statistical model with low income African American youth. This study examined parental monitoring, peer norms and future orientation as primary pathways to drug use and delinquent behaviors in a large sample of African American urban adolescents. Methods A path model tested direct paths from peer norms, parental monitoring, and future orientation to drug use and delinquency outcomes after adjusting for potential confounders such as age, socioeconomic, and sexual orientation in a sample of 541 African American youth. Results Greater scores on measures of risky peer norms were associated with heightened risk of delinquency with an effect size that was twice in magnitude compared to the protective effects of future orientation. Regarding substance use, greater perceived risky peer norms correlated with the increased likelihood of substance use with a standardized effect size 3.33 times in magnitude compared to the protective effects of parental monitoring. Conclusions Findings from this study suggest that interventions targeting risky peer norms among adolescent African American youth may correlate with a greater impact on reductions in substance use and delinquency than exclusively targeting parental monitoring or future orientation. PMID:28974824

Control of NORM at Eugene Island 341-A

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

Shuler, P.J.; Baudoin, D.A.; Weintritt, D.J.

1995-12-31

A field study at Eugene island 341-A, an offshore production platform in the Gulf of Mexico, was conducted to develop strategies for the cost-effective prevention of NORM (Naturally Occurring Radioactive Materials) deposits. The specific objectives of this study were to: (1) Determine the root cause for the NORM deposits at this facility, utilizing different diagnostic techniques. (2) Consider all engineering options that are designed to prevent NORM from forming. (3) Determine the most cost-effective engineering solution. An overall objective was to generalize the diagnostics and control methods developed for Eugene Island 341-A to other oil and gas production facilities, especiallymore » to platforms located in the Gulf of Mexico. This study determined that the NORM deposits found at Eugene Island 341-A stem from commingling incompatible produced waters at the surface. Wells completed in Sand Block A have a water containing a relatively high concentration of barium, while those formation brines in Sand Blocks B and C are high in sulfate. When these waters mix at the start of the fluid treatment facilities on the platform, barium sulfate forms. Radium that is present in the produced brines co-precipitates with the barium, thereby creating a radioactive barium sulfate scale deposit (NORM).« less

Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining.

PubMed

Cheng, Wenlong; Zhao, Mingbo; Xiong, Naixue; Chui, Kwok Tai

2017-07-15

Parsimony, including sparsity and low-rank, has shown great importance for data mining in social networks, particularly in tasks such as segmentation and recognition. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with convex l ₁-norm or nuclear norm constraints. However, the obtained results by convex optimization are usually suboptimal to solutions of original sparse or low-rank problems. In this paper, a novel robust subspace segmentation algorithm has been proposed by integrating l p -norm and Schatten p -norm constraints. Our so-obtained affinity graph can better capture local geometrical structure and the global information of the data. As a consequence, our algorithm is more generative, discriminative and robust. An efficient linearized alternating direction method is derived to realize our model. Extensive segmentation experiments are conducted on public datasets. The proposed algorithm is revealed to be more effective and robust compared to five existing algorithms.

Accreditation of medical laboratories in Croatia--experiences of the Institute of Clinical Chemistry, University Hospital "Merkur", Zagreb.

PubMed

Flegar-Mestrić, Zlata; Nazor, Aida; Perkov, Sonja; Surina, Branka; Kardum-Paro, Mirjana Mariana; Siftar, Zoran; Sikirica, Mirjana; Sokolić, Ivica; Ozvald, Ivan; Vidas, Zeljko

2010-03-01

Since 2003 when the international norm for implementation of quality management in medical laboratories (EN ISO 15189, Medical laboratories--Particular requirements for quality and competence) was established and accepted, accreditation has become practical, generally accepted method of quality management and confirmation of technical competence of medical laboratories in the whole world. This norm has been translated into Croatian and accepted by the Croatian Institute for Norms as Croatian norm. Accreditation is carried out on voluntary basis by the Croatian Accreditation Agency that has up to now accredited two clinical medical biochemical laboratories in the Republic of Croatia. Advantages of accredited laboratory lie in its documented management system, constant improvement and training, reliability of test results, establishing users' trust in laboratory services, test results comparability and interlaboratory (international) test results acceptance by adopting the concept of metrological traceability in laboratory medicine.

The Linearized Bregman Method for Frugal Full-waveform Inversion with Compressive Sensing and Sparsity-promoting

NASA Astrophysics Data System (ADS)

Chai, Xintao; Tang, Genyang; Peng, Ronghua; Liu, Shaoyong

2018-03-01

Full-waveform inversion (FWI) reconstructs the subsurface properties from acquired seismic data via minimization of the misfit between observed and simulated data. However, FWI suffers from considerable computational costs resulting from the numerical solution of the wave equation for each source at each iteration. To reduce the computational burden, constructing supershots by combining several sources (aka source encoding) allows mitigation of the number of simulations at each iteration, but it gives rise to crosstalk artifacts because of interference between the individual sources of the supershot. A modified Gauss-Newton FWI (MGNFWI) approach showed that as long as the difference between the initial and true models permits a sparse representation, the ℓ _1-norm constrained model updates suppress subsampling-related artifacts. However, the spectral-projected gradient ℓ _1 (SPGℓ _1) algorithm employed by MGNFWI is rather complicated that makes its implementation difficult. To facilitate realistic applications, we adapt a linearized Bregman (LB) method to sparsity-promoting FWI (SPFWI) because of the efficiency and simplicity of LB in the framework of ℓ _1-norm constrained optimization problem and compressive sensing. Numerical experiments performed with the BP Salt model, the Marmousi model and the BG Compass model verify the following points. The FWI result with LB solving ℓ _1-norm sparsity-promoting problem for the model update outperforms that generated by solving ℓ _2-norm problem in terms of crosstalk elimination and high-fidelity results. The simpler LB method performs comparably and even superiorly to the complicated SPGℓ _1 method in terms of computational efficiency and model quality, making the LB method a viable alternative for realistic implementations of SPFWI.

Willingness to Drink as a Function of Peer Offers and Peer Norms in Early Adolescence

PubMed Central

Jackson, Kristina M; Roberts, Megan E; Colby, Suzanne M; Barnett, Nancy P; Abar, Caitlin C; Merrill, Jennifer E

2014-01-01

Objective: The goal of this study was to explore the effect of subjective peer norms on adolescents’ willingness to drink and whether this association was moderated by sensitivity to peer approval, prior alcohol use, and gender. Method: The sample was 1,023 middle-school students (52% female; 76% White; 12% Hispanic; Mage = 12.22 years) enrolled in a prospective study of drinking initiation and progression. Using web-based surveys, participants reported on their willingness to drink alcohol if offered by (a) a best friend or (b) a classmate, peer norms for two referent groups (close friends and classmates), history of sipping or consuming a full drink of alcohol, and sensitivity to peer approval (extreme peer orientation). Items were re-assessed at two follow-ups (administered 6 months apart). Results: Multilevel models revealed that measures of peer norms were significantly associated with both willingness outcomes, with the greatest prediction by descriptive norms. The association between norms and willingness was magnified for girls, those with limited prior experience with alcohol, and youths with low sensitivity to peer approval. Conclusions: Social norms appear to play a key role in substance use decisions and are relevant when considering more reactive behaviors that reflect willingness to drink under conducive circumstances. Prevention programs might target individuals with higher willingness, particularly girls who perceive others to be drinking and youths who have not yet sipped alcohol but report a higher perceived prevalence of alcohol consumption among both friends and peers. PMID:24766752

A Theoretical Approach to Norm Ecosystems: Two Adaptive Architectures of Indirect Reciprocity Show Different Paths to the Evolution of Cooperation

NASA Astrophysics Data System (ADS)

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

2018-02-01

Indirect reciprocity is one of the basic mechanisms to sustain mutual cooperation, by which beneficial acts are returned, not by the recipient, but by third parties. This mechanism relies on the ability of individuals to know the past actions of others, and to assess those actions. There are many different systems of assessing others, which can be interpreted as rudimentary social norms (i.e., views on what is “good” or “bad”). In this paper, impacts of different adaptive architectures, i.e., ways for individuals to adapt to environments, on indirect reciprocity are investigated. We examine two representative architectures: one based on replicator dynamics and the other on genetic algorithm. Different from the replicator dynamics, the genetic algorithm requires describing the mixture of all possible norms in the norm space under consideration. Therefore, we also propose an analytic method to study norm ecosystems in which all possible second order social norms potentially exist and compete. The analysis reveals that the different adaptive architectures show different paths to the evolution of cooperation. Especially we find that so called Stern-Judging, one of the best studied norms in the literature, exhibits distinct behaviors in both architectures. On one hand, in the replicator dynamics, Stern-Judging remains alive and gets a majority steadily when the population reaches a cooperative state. On the other hand, in the genetic algorithm, it gets a majority only temporarily and becomes extinct in the end.

A Comparative Study of Performance in the Conners' Continuous Performance Test between Brazilian and North American Children

ERIC Educational Resources Information Center

Miranda, Monica Carolina; Sinnes, Elaine Girao; Pompeia, Sabine; Bueno, Orlando Francisco Amodeo

2008-01-01

Objective: The present study investigated the performance of Brazilian children in the Continuous Performance Test, CPT-II, and compared results to those of the norms obtained in the United States. Method: The U.S. norms were compared to those of a Brazilian sample composed of 6- to 11-year-olds separated into 4 age-groups (half boys) that…

Generalized Higher Order Orthogonal Iteration for Tensor Learning and Decomposition.

PubMed

Liu, Yuanyuan; Shang, Fanhua; Fan, Wei; Cheng, James; Cheng, Hong

2016-12-01

Low-rank tensor completion (LRTC) has successfully been applied to a wide range of real-world problems. Despite the broad, successful applications, existing LRTC methods may become very slow or even not applicable for large-scale problems. To address this issue, a novel core tensor trace-norm minimization (CTNM) method is proposed for simultaneous tensor learning and decomposition, and has a much lower computational complexity. In our solution, first, the equivalence relation of trace norm of a low-rank tensor and its core tensor is induced. Second, the trace norm of the core tensor is used to replace that of the whole tensor, which leads to two much smaller scale matrix TNM problems. Finally, an efficient alternating direction augmented Lagrangian method is developed to solve our problems. Our CTNM formulation needs only O((R N +NRI)log(√{I N })) observations to reliably recover an N th-order I×I×…×I tensor of n -rank (r,r,…,r) , compared with O(rI N-1 ) observations required by those tensor TNM methods ( I > R ≥ r ). Extensive experimental results show that CTNM is usually more accurate than them, and is orders of magnitude faster.

On Quantile Regression in Reproducing Kernel Hilbert Spaces with Data Sparsity Constraint

PubMed Central

Zhang, Chong; Liu, Yufeng; Wu, Yichao

2015-01-01

For spline regressions, it is well known that the choice of knots is crucial for the performance of the estimator. As a general learning framework covering the smoothing splines, learning in a Reproducing Kernel Hilbert Space (RKHS) has a similar issue. However, the selection of training data points for kernel functions in the RKHS representation has not been carefully studied in the literature. In this paper we study quantile regression as an example of learning in a RKHS. In this case, the regular squared norm penalty does not perform training data selection. We propose a data sparsity constraint that imposes thresholding on the kernel function coefficients to achieve a sparse kernel function representation. We demonstrate that the proposed data sparsity method can have competitive prediction performance for certain situations, and have comparable performance in other cases compared to that of the traditional squared norm penalty. Therefore, the data sparsity method can serve as a competitive alternative to the squared norm penalty method. Some theoretical properties of our proposed method using the data sparsity constraint are obtained. Both simulated and real data sets are used to demonstrate the usefulness of our data sparsity constraint. PMID:27134575

Direction of Arrival Estimation for MIMO Radar via Unitary Nuclear Norm Minimization

PubMed Central

Wang, Xianpeng; Huang, Mengxing; Wu, Xiaoqin; Bi, Guoan

2017-01-01

In this paper, we consider the direction of arrival (DOA) estimation issue of noncircular (NC) source in multiple-input multiple-output (MIMO) radar and propose a novel unitary nuclear norm minimization (UNNM) algorithm. In the proposed method, the noncircular properties of signals are used to double the virtual array aperture, and the real-valued data are obtained by utilizing unitary transformation. Then a real-valued block sparse model is established based on a novel over-complete dictionary, and a UNNM algorithm is formulated for recovering the block-sparse matrix. In addition, the real-valued NC-MUSIC spectrum is used to design a weight matrix for reweighting the nuclear norm minimization to achieve the enhanced sparsity of solutions. Finally, the DOA is estimated by searching the non-zero blocks of the recovered matrix. Because of using the noncircular properties of signals to extend the virtual array aperture and an additional real structure to suppress the noise, the proposed method provides better performance compared with the conventional sparse recovery based algorithms. Furthermore, the proposed method can handle the case of underdetermined DOA estimation. Simulation results show the effectiveness and advantages of the proposed method. PMID:28441770

An experimental study on the effects of peer drinking norms on adolescents’ drinker prototypes

PubMed Central

Teunissen, Hanneke A.; Spijkerman, Renske; Cohen, Geoffrey L.; Prinstein, Mitchell J.; Engels, Rutger C.M.E.; Scholte, Ron H.J.

2015-01-01

Background Adolescents form impressions about the type of peers who drink (i.e., drinker prototypes). The evaluation of, and perceived similarity to these prototypes are related to adolescents’ drinking. Peer drinking norms play an important role in the formation of prototypes. We experimentally examined whether manipulation of peer norms changed the evaluation of and perceived similarity to drinker prototypes and whether these changes were moderated by peers’ popularity. Methods In a pre-test, we assessed heavy drinker, moderate drinker and abstainer prototypes, drinking behaviors and peer-perceived popularity among 599 adolescents. Additionally, 88 boys from this sample participated in a simulated chat room, in which they interacted with peers from school. These peers were in fact pre-programmed e-confederates, who were either popular or unpopular and who communicated either pro-alcohol or anti-alcohol norms. After the chat room interaction we assessed participants’ drinker prototypes. Results Participants exposed to anti-alcohol norms were more negative about, and perceived themselves as less similar to heavy drinker prototypes, than participants exposed to pro-alcohol norms. We found no effects of peer norms on moderate drinker and abstainer prototypes. Effects were not moderated by peers’ popularity. We did find a main effect of popularity on perceived similarity to all prototypes. This indicated that participants rated themselves as more similar to heavy and moderate drinker prototypes and less similar to abstainer prototypes when they interacted with unpopular peers than with popular peers. Conclusions Exposure to anti-alcohol norms of peers leads adolescents to form more negative prototypes of the heavy drinker. This could be an important finding for prevention and intervention programs aimed to reduce alcohol consumption among adolescents. PMID:24104050

Norms for developmental milestones using VABS-II and association with anthropometric measures among apparently healthy urban Indian preschool children.

PubMed

Selvam, Sumithra; Thomas, Tinku; Shetty, Priya; Zhu, Jianjun; Raman, Vijaya; Khanna, Deepti; Mehra, Ruchika; Kurpad, Anura V; Srinivasan, Krishnamachari

2016-12-01

Assessment of developmental milestones based on locally developed norms is critical for accurate estimate of overall development of a child's cognitive, behavioral, social, and emotional development. A cross-sectional study was done to develop age specific norms for developmental milestones using Vineland Adaptive Behavior Scales (VABS-II) (Sparrow, Cicchetti, & Balla, 2005) for apparently healthy children from 2 to 5 years from urban Bangalore, India, and to examine its association with anthropometric measures. Mothers (or caregivers) of 412 children participated in the study. Age-specific norms using inferential norming method and adaptive levels for all domains and subdomains were derived. Low adaptive level, also called delayed developmental milestone, was observed in 2.3% of the children, specifically 2.7% in motor and daily living skills and 2.4% in communication skills. When these children were assessed on the existing U.S. norms, there was a significant overestimation of delayed development in socialization and motor skills, whereas delay in communication and daily living skills were underestimated (all p < .01). Multiple linear regression revealed that stunted and underweight children had significantly lower developmental scores for communication and motor skills compared with normal children (β coefficient ranges from 2.6-5.3; all p < .01). In the absence of Indian normative data for VABS-II in preschool children, the prevalence of developmental delay could either be under- or overestimated using Western norms. Thus, locally referenced norms are critical for reliable assessments of development in children. Stunted and underweight children are more likely to have poorer developmental scores compared with healthy children. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Alcohol Use Disorders and Perceived Drinking Norms: Ethnic Differences in Israeli Adults

PubMed Central

Shmulewitz, Dvora; Wall, Melanie M.; Keyes, Katherine M.; Aharonovich, Efrat; Aivadyan, Christina; Greenstein, Eliana; Spivak, Baruch; Weizman, Abraham; Frisch, Amos; Hasin, Deborah

2012-01-01

Objective: Individuals’ perceptions of drinking acceptability in their society (perceived injunctive drinking norms) are widely assumed to explain ethnic group differences in drinking and alcohol use disorders (AUDs), but this has never been formally tested. Immigrants to Israel from the former Soviet Union (FSU) are more likely to drink and report AUD symptoms than other Israelis. We tested perceived drinking norms as a mediator of differences between FSU immigrants and other Israelis in drinking and AUDs. Method: Adult household residents (N = 1,349) selected from the Israeli population register were assessed with a structured interview measuring drinking, AUD symptoms, and perceived drinking norms. Regression analyses were used to produce odds ratios (OR) and risk ratios (RR) and 95% confidence intervals (CI) to test differences between FSU immigrants and other Israelis on binary and graded outcomes. Mediation of FSU effects by perceived drinking norms was tested with bootstrapping procedures. Results: FSU immigrants were more likely than other Israelis to be current drinkers (OR = 2.39, CI [1.61, 3.55]), have higher maximum number of drinks per day (RR = 1.88, CI [1.64, 2.16]), have any AUD (OR = 1.75, CI [1.16, 2.64]), score higher on a continuous measure of AUD (RR = 1.44, CI [1.12, 1.84]), and perceive more permissive drinking norms (p < .0001). For all four drinking variables, the FSU group effect was at least partially mediated by perceived drinking norms. Conclusions: This is the first demonstration that drinking norms mediate ethnic differences in AUDs. This work contributes to understanding ethnic group differences in drinking and AUDs, potentially informing etiologic research and public policy aimed at reducing alcohol-related harm. PMID:23036217

Time Series Imputation via L1 Norm-Based Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Kalantari, Mahdi; Yarmohammadi, Masoud; Hassani, Hossein; Silva, Emmanuel Sirimal

Missing values in time series data is a well-known and important problem which many researchers have studied extensively in various fields. In this paper, a new nonparametric approach for missing value imputation in time series is proposed. The main novelty of this research is applying the L1 norm-based version of Singular Spectrum Analysis (SSA), namely L1-SSA which is robust against outliers. The performance of the new imputation method has been compared with many other established methods. The comparison is done by applying them to various real and simulated time series. The obtained results confirm that the SSA-based methods, especially L1-SSA can provide better imputation in comparison to other methods.

OCT despeckling via weighted nuclear norm constrained non-local low-rank representation

NASA Astrophysics Data System (ADS)

Tang, Chang; Zheng, Xiao; Cao, Lijuan

2017-10-01

As a non-invasive imaging modality, optical coherence tomography (OCT) plays an important role in medical sciences. However, OCT images are always corrupted by speckle noise, which can mask image features and pose significant challenges for medical analysis. In this work, we propose an OCT despeckling method by using non-local, low-rank representation with weighted nuclear norm constraint. Unlike previous non-local low-rank representation based OCT despeckling methods, we first generate a guidance image to improve the non-local group patches selection quality, then a low-rank optimization model with a weighted nuclear norm constraint is formulated to process the selected group patches. The corrupted probability of each pixel is also integrated into the model as a weight to regularize the representation error term. Note that each single patch might belong to several groups, hence different estimates of each patch are aggregated to obtain its final despeckled result. Both qualitative and quantitative experimental results on real OCT images show the superior performance of the proposed method compared with other state-of-the-art speckle removal techniques.

On the Directional Dependence and Null Space Freedom in Uncertainty Bound Identification

NASA Technical Reports Server (NTRS)

Lim, K. B.; Giesy, D. P.

1997-01-01

In previous work, the determination of uncertainty models via minimum norm model validation is based on a single set of input and output measurement data. Since uncertainty bounds at each frequency is directionally dependent for multivariable systems, this will lead to optimistic uncertainty levels. In addition, the design freedom in the uncertainty model has not been utilized to further reduce uncertainty levels. The above issues are addressed by formulating a min- max problem. An analytical solution to the min-max problem is given to within a generalized eigenvalue problem, thus avoiding a direct numerical approach. This result will lead to less conservative and more realistic uncertainty models for use in robust control.

Observations of non-linear plasmon damping in dense plasmas

NASA Astrophysics Data System (ADS)

Witte, B. B. L.; Sperling, P.; French, M.; Recoules, V.; Glenzer, S. H.; Redmer, R.

2018-05-01

We present simulations using finite-temperature density-functional-theory molecular-dynamics to calculate dynamic dielectric properties in warm dense aluminum. The comparison between exchange-correlation functionals in the Perdew, Burke, Ernzerhof approximation, Strongly Constrained and Appropriately Normed Semilocal Density Functional, and Heyd, Scuseria, Ernzerhof (HSE) approximation indicates evident differences in the electron transition energies, dc conductivity, and Lorenz number. The HSE calculations show excellent agreement with x-ray scattering data [Witte et al., Phys. Rev. Lett. 118, 225001 (2017)] as well as dc conductivity and absorption measurements. These findings demonstrate non-Drude behavior of the dynamic conductivity above the Cooper minimum that needs to be taken into account to determine optical properties in the warm dense matter regime.

The primary prevention of alcohol problems: a critical review of the research literature.

PubMed

Moskowitz, J M

1989-01-01

The research evaluating the effects of programs and policies in reducing the incidence of alcohol problems is critically reviewed. Four types of preventive interventions are examined including: (1) policies affecting the physical, economic and social availability of alcohol (e.g., minimum legal drinking age, price and advertising of alcohol), (2) formal social controls on alcohol-related behavior (e.g., drinking-driving laws), (3) primary prevention programs (e.g., school-based alcohol education), and (4) environmental safety measures (e.g., automobile airbags). The research generally supports the efficacy of three alcohol-specific policies: raising the minimum legal drinking age to 21, increasing alcohol taxes and increasing the enforcement of drinking-driving laws. Also, research suggests that various environmental safety measures reduce the incidence of alcohol-related trauma. In contrast, little evidence currently exists to support the efficacy of primary prevention programs. However, a systems perspective of prevention suggests that prevention programs may become more efficacious after widespread adoption of prevention policies that lead to shifts in social norms regarding use of beverage alcohol.

Misinformation, mistrust, and mistreatment: family planning among Bolivian market women.

PubMed

Schuler, S R; Choque, M E; Rance, S

1994-01-01

Results of an ethnographic study suggest that, despite stereotypes to the contrary, urban Aymara women in Bolivia want to regulate their fertility, and sociocultural norms support fertility regulation. However, the norms also make such regulation difficult to achieve. One barrier is a deep suspicion of modern medicine and medical practitioners, who are not seen as reliable sources of information. This suspicion is reinforced when the quality of health services is inadequate. Among urban Aymara, the level of acceptability of most modern methods of contraception is low. Many would prefer to use traditional methods, even when use of these methods entails considerable sacrifice and risk of conflict with their partners, unwanted pregnancies, and recourse to unsafe abortion.

Access, engagement, networks, and norms: Dimensions of social capital at work in a first grade classroom

NASA Astrophysics Data System (ADS)

Wexler-Robock, Stephanie

Social capital refers to access and use of resources available through one's networks to solve problems, and the norms that reflect inclusive or exclusive access to those networks and resources. Research has found positive relationships between social capital, academic achievement, and attainment. Studies, however, have generally examined social capital through factors that occur outside the classroom; students who have social capital, acquired through their family and community relationships, seem to be more successful academically. Limited research has explored what if any factors within the classroom might impact the production, and nature of social capital, or its workings in a classroom. The purpose of this study was to explore the workings and nature of classroom social capital, including its possible relationships to engagement and cognition among 5 student participants. Using methods of qualitative data collection, mixed methods were used to analyze information resources, participants' networking, student work, and classroom discourse. Eight interdependent networking factors and 3 overarching patterns of norms were discovered. The networking factors reflected the structure, content, processes, purposes, and acceptability of participants' networking. The norms, also working interdependently, appeared to promote or inhibit among other things, engagement in networking, help seeking, access, sharing, and intertextual use of diverse, often complex sources of information. Through interaction of the 8 factors and 3 overarching norms, ongoing outcomes of networking appeared to include the creation of bridging (inclusive) and bonding (exclusive) forms of social capital, and depth of scientific conceptual understanding, in this case, about birds. Bridging social capital appeared related to willingness to engage in strong and weak tie networking, help seeking, intertextuality, and possibly to mastery goal orientation for all participants, regardless of reading level. Expository sources more so than narrative texts generated intertextually dense, social and cognitive networks, often between members with weak ties. Together the networking factors and norms shed light on the way discourse, resources, and practice might impact social capital, suggesting that forms of social capital may be produced, accumulated, and depleted by factors and norms that are open to variation and occur within the classroom.

Methodology for the development of normative data for Spanish-speaking pediatric populations.

PubMed

Rivera, D; Arango-Lasprilla, J C

2017-01-01

To describe the methodology utilized to calculate reliability and the generation of norms for 10 neuropsychological tests for children in Spanish-speaking countries. The study sample consisted of over 4,373 healthy children from nine countries in Latin America (Chile, Cuba, Ecuador, Guatemala, Honduras, Mexico, Paraguay, Peru, and Puerto Rico) and Spain. Inclusion criteria for all countries were to have between 6 to 17 years of age, an Intelligence Quotient of≥80 on the Test of Non-Verbal Intelligence (TONI-2), and score of <19 on the Children's Depression Inventory. Participants completed 10 neuropsychological tests. Reliability and norms were calculated for all tests. Test-retest analysis showed excellent or good- reliability on all tests (r's>0.55; p's<0.001) except M-WCST perseverative errors whose coefficient magnitude was fair. All scores were normed using multiple linear regressions and standard deviations of residual values. Age, age2, sex, and mean level of parental education (MLPE) were included as predictors in the models by country. The non-significant variables (p > 0.05) were removed and the analysis were run again. This is the largest Spanish-speaking children and adolescents normative study in the world. For the generation of normative data, the method based on linear regression models and the standard deviation of residual values was used. This method allows determination of the specific variables that predict test scores, helps identify and control for collinearity of predictive variables, and generates continuous and more reliable norms than those of traditional methods.

Stable Reference Gene Selection for RT-qPCR Analysis in Nonviruliferous and Viruliferous Frankliniella occidentalis

PubMed Central

Pan, Huipeng; Ma, Yabin; Zhang, Deyong; Liu, Yong; Zhang, Zhanhong; Zheng, Changying; Chu, Dong

2015-01-01

Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) is a reliable technique for measuring and evaluating gene expression during variable biological processes. To facilitate gene expression studies, normalization of genes of interest relative to stable reference genes is crucial. The western flower thrips Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae), the main vector of tomato spotted wilt virus (TSWV), is a destructive invasive species. In this study, the expression profiles of 11 candidate reference genes from nonviruliferous and viruliferous F. occidentalis were investigated. Five distinct algorithms, geNorm, NormFinder, BestKeeper, the ΔC t method, and RefFinder, were used to determine the performance of these genes. geNorm, NormFinder, BestKeeper, and RefFinder identified heat shock protein 70 (HSP70), heat shock protein 60 (HSP60), elongation factor 1 α, and ribosomal protein l32 (RPL32) as the most stable reference genes, and the ΔC t method identified HSP60, HSP70, RPL32, and heat shock protein 90 as the most stable reference genes. Additionally, two reference genes were sufficient for reliable normalization in nonviruliferous and viruliferous F. occidentalis. This work provides a foundation for investigating the molecular mechanisms of TSWV and F. occidentalis interactions. PMID:26244556

Seismic data restoration with a fast L1 norm trust region method

NASA Astrophysics Data System (ADS)

Cao, Jingjie; Wang, Yanfei

2014-08-01

Seismic data restoration is a major strategy to provide reliable wavefield when field data dissatisfy the Shannon sampling theorem. Recovery by sparsity-promoting inversion often get sparse solutions of seismic data in a transformed domains, however, most methods for sparsity-promoting inversion are line-searching methods which are efficient but are inclined to obtain local solutions. Using trust region method which can provide globally convergent solutions is a good choice to overcome this shortcoming. A trust region method for sparse inversion has been proposed, however, the efficiency should be improved to suitable for large-scale computation. In this paper, a new L1 norm trust region model is proposed for seismic data restoration and a robust gradient projection method for solving the sub-problem is utilized. Numerical results of synthetic and field data demonstrate that the proposed trust region method can get excellent computation speed and is a viable alternative for large-scale computation.

Least-squares finite element methods for compressible Euler equations

NASA Technical Reports Server (NTRS)

Jiang, Bo-Nan; Carey, G. F.

1990-01-01

A method based on backward finite differencing in time and a least-squares finite element scheme for first-order systems of partial differential equations in space is applied to the Euler equations for gas dynamics. The scheme minimizes the L-sq-norm of the residual within each time step. The method naturally generates numerical dissipation proportional to the time step size. An implicit method employing linear elements has been implemented and proves robust. For high-order elements, computed solutions based on the L-sq method may have oscillations for calculations at similar time step sizes. To overcome this difficulty, a scheme which minimizes the weighted H1-norm of the residual is proposed and leads to a successful scheme with high-degree elements. Finally, a conservative least-squares finite element method is also developed. Numerical results for two-dimensional problems are given to demonstrate the shock resolution of the methods and compare different approaches.

Concave 1-norm group selection

PubMed Central

Jiang, Dingfeng; Huang, Jian

2015-01-01

Grouping structures arise naturally in many high-dimensional problems. Incorporation of such information can improve model fitting and variable selection. Existing group selection methods, such as the group Lasso, require correct membership. However, in practice it can be difficult to correctly specify group membership of all variables. Thus, it is important to develop group selection methods that are robust against group mis-specification. Also, it is desirable to select groups as well as individual variables in many applications. We propose a class of concave \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$1$\\end{document}-norm group penalties that is robust to grouping structure and can perform bi-level selection. A coordinate descent algorithm is developed to calculate solutions of the proposed group selection method. Theoretical convergence of the algorithm is proved under certain regularity conditions. Comparison with other methods suggests the proposed method is the most robust approach under membership mis-specification. Simulation studies and real data application indicate that the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$1$\\end{document}-norm concave group selection approach achieves better control of false discovery rates. An R package grppenalty implementing the proposed method is available at CRAN. PMID:25417206

Assessment for the management of NORM wastes in conventional hazardous and nonhazardous waste landfills.

PubMed

Mora, Juan C; Baeza, Antonio; Robles, Beatriz; Sanz, Javier

2016-06-05

Naturally Occurring Radioactive Materials (NORM) wastes are generated in huge quantities in several industries and their management has been carried out under considerations of industrial non-radioactive wastes, before the concern on the radioactivity content was included in the legislation. Therefore these wastes were conditioned using conventional methods and the waste disposals were designed to isolate toxic elements from the environment for long periods of time. Spanish regulation for these conventional toxic waste disposals includes conditions that assure adequate isolation to minimize the impact of the wastes to the environment in present and future conditions. After 1996 the radiological impact of the management of NORM wastes is considered and all the aspects related with natural radiations and the radiological control regarding the management of residues from NORM industries were developed in the new regulation. One option to be assessed is the disposal of NORM wastes in hazardous and non-hazardous waste disposals, as was done before this new regulation. This work analyses the management of NORM wastes in these landfills to derive the masses that can be disposed without considerable radiological impact. Generic dose assessments were carried out under highly conservative hypothesis and a discussion on the uncertainty and variability sources was included to provide consistency to the calculations. Copyright © 2016 Elsevier B.V. All rights reserved.

Mapping Partners Master Drug Dictionary to RxNorm using an NLP-based approach.

PubMed

Zhou, Li; Plasek, Joseph M; Mahoney, Lisa M; Chang, Frank Y; DiMaggio, Dana; Rocha, Roberto A

2012-08-01

To develop an automated method based on natural language processing (NLP) to facilitate the creation and maintenance of a mapping between RxNorm and a local medication terminology for interoperability and meaningful use purposes. We mapped 5961 terms from Partners Master Drug Dictionary (MDD) and 99 of the top prescribed medications to RxNorm. The mapping was conducted at both term and concept levels using an NLP tool, called MTERMS, followed by a manual review conducted by domain experts who created a gold standard mapping. The gold standard was used to assess the overall mapping between MDD and RxNorm and evaluate the performance of MTERMS. Overall, 74.7% of MDD terms and 82.8% of the top 99 terms had an exact semantic match to RxNorm. Compared to the gold standard, MTERMS achieved a precision of 99.8% and a recall of 73.9% when mapping all MDD terms, and a precision of 100% and a recall of 72.6% when mapping the top prescribed medications. The challenges and gaps in mapping MDD to RxNorm are mainly due to unique user or application requirements for representing drug concepts and the different modeling approaches inherent in the two terminologies. An automated approach based on NLP followed by human expert review is an efficient and feasible way for conducting dynamic mapping. Copyright © 2011 Elsevier Inc. All rights reserved.

Sexual orientation, minority stress, social norms, and substance use among racially diverse adolescents.

PubMed

Mereish, Ethan H; Goldbach, Jeremy T; Burgess, Claire; DiBello, Angelo M

2017-09-01

Sexual minority adolescents are more likely than their heterosexual peers to use substances. This study tested factors that contribute to sexual orientation disparities in substance use among racially and ethnically diverse adolescents. Specifically, we examined how both minority stress (i.e., homophobic bullying) and social norms (i.e., descriptive and injunctive norms) may account for sexual orientation disparities in recent and lifetime use of four substances: tobacco, alcohol, marijuana, and prescription drugs. A probability sample of middle and high school students (N=3012; aged 11-18 years old; 71.2% racial and ethnic minorities) using random cluster methods was obtained in a mid-size school district in the Southeastern United States. Sexual minority adolescents were more likely than heterosexual adolescents to use substances, experience homophobic bullying, and report higher descriptive norms for close friends and more permissive injunctive norms for friends and parents. While accounting for sociodemographic characteristics, multiple mediation models concurrently testing all mediators indicated that higher descriptive and more permissive injunctive norms were significant mediators of the associations between sexual orientation and recent and lifetime use of the four substances, whereas homophobic bullying was not a significant mediator of the associations between sexual orientation and recent and lifetime use of any of the substances. Descriptive and injunctive norms, in conjunction with minority stress, are important to consider in explaining sexual orientation disparities in substance use among racially diverse adolescents. These results have implications for substance use interventions among sexual minority adolescents. Copyright © 2017 Elsevier B.V. All rights reserved.

Descriptive Drinking Norms: For Whom Does Reference Group Matter?*

PubMed Central

Larimer, Mary E.; Neighbors, Clayton; LaBrie, Joseph W.; Atkins, David C.; Lewis, Melissa A.; Lee, Christine M.; Kilmer, Jason R.; Kaysen, Debra L.; Pedersen, Eric r.; Montoya, Heidi; Hodge, Kimberley; Desai, Sruti; Hummer, Justin F.; Walter, Theresa

2011-01-01

Objective: Perceived descriptive drinking norms often differ from actual norms and are positively related to personal consumption. However, it is not clear how normative perceptions vary with specificity of the reference group. Are drinking norms more accurate and more closely related to drinking behavior as reference group specificity increases? Do these relationships vary as a function of participant demographics? The present study examined the relationship between perceived descriptive norms and drinking behavior by ethnicity (Asian or White), sex, and fraternity/sorority status. Method: Participants were 2,699 (58% female) White (75%) or Asian (25%) undergraduates from two universities who reported their own alcohol use and perceived descriptive norms for eight reference groups: "typical student"; same sex, ethnicity, or fraternity/sorority status; and all combinations of these three factors. Results: Participants generally reported the highest perceived norms for the most distal reference group (typical student), with perceptions becoming more accurate as individuals' similarity to the reference group increased. Despite increased accuracy, participants perceived that all reference groups drank more than was actually the case. Across specific subgroups (fraternity/sorority members and men) different patterns emerged. Fraternity/sorority members reliably reported higher estimates of drinking for reference groups that included fraternity/ sorority status, and, to a lesser extent, men reported higher estimates for reference groups that included men. Conclusions: The results suggest that interventions targeting normative misperceptions may need to provide feedback based on participant demography or group membership. Although reference group-specific feedback may be important for some subgroups, typical student feedback provides the largest normative discrepancy for the majority of students. PMID:21906510

A methodology for building culture and gender norms into intervention: an example from Mumbai, India.

PubMed

Kostick, Kristin M; Schensul, Stephen L; Singh, Rajendra; Pelto, Pertti; Saggurti, Niranjan

2011-05-01

This paper responds to the call for culturally-relevant intervention research by introducing a methodology for identifying community norms and resources in order to more effectively implement sustainable interventions strategies. Results of an analysis of community norms, specifically attitudes toward gender equity, are presented from an HIV/STI research and intervention project in a low-income community in Mumbai, India (2008-2012). Community gender norms were explored because of their relevance to sexual risk in settings characterized by high levels of gender inequity. This paper recommends approaches that interventionists and social scientists can take to incorporate cultural insights into formative assessments and project implementation These approaches include how to (1) examine modal beliefs and norms and any patterned variation within the community; (2) identify and assess variation in cultural beliefs and norms among community members (including leaders, social workers, members of civil society and the religious sector); and (3) identify differential needs among sectors of the community and key types of individuals best suited to help formulate and disseminate culturally-relevant intervention messages. Using a multi-method approach that includes the progressive translation of qualitative interviews into a quantitative survey of cultural norms, along with an analysis of community consensus, we outline a means for measuring variation in cultural expectations and beliefs about gender relations in an urban community in Mumbai. Results illustrate how intervention strategies and implementation can benefit from an organic (versus a priori and/or stereotypical) approach to cultural characteristics and analysis of community resources and vulnerabilities. Copyright © 2011 Elsevier Ltd. All rights reserved.

A methodology for building culture and gender norms into intervention: An example from Mumbai, India

PubMed Central

Schensul, Stephen L.; Singh, Rajendra; Pelto, Pertti; Saggurti, Niranjan

2011-01-01

This paper responds to the call for culturally relevant intervention research by introducing a methodology for identifying community norms and resources in order to more effectively implement sustainable interventions strategies. Results of an analysis of community norms, specifically attitudes toward gender equity, are presented from an HIV/STI research and intervention project in a low income community in Mumbai, India (2008–2012). Community gender norms were explored because of their relevance to sexual risk in settings characterized by high levels of gender inequity. This paper recommends approaches that interventionists and social scientists can take to incorporate cultural insights into formative assessments and project implementation These approaches include how to (1) examine modal beliefs and norms and any patterned variation within the community; (2) identify and assess variation in cultural beliefs and norms among community members (including leaders, social workers, members of civil society and the religious sector); and (3) identify differential needs among sectors of the community and key types of individuals best suited to help formulate and disseminate culturally relevant intervention messages. Using a multi-method approach that includes the progressive translation of qualitative interviews into a quantitative survey of cultural norms, along with an analysis of community consensus, we outline a means for measuring variation in cultural expectations and beliefs about gender relations in an urban community in Mumbai. Results illustrate how intervention strategies and implementation can benefit from an organic (versus a priori and/or stereotypical) approach to cultural characteristics and analysis of community resources and vulnerabilities. PMID:21524835

Secular versus religious norms against smoking: Which is more important as a driver of quitting behaviour among Muslim Malaysian and Buddhist Thai smokers?

PubMed Central

Yong, Hua-Hie; Savvas, Steven; Borland, Ron; Thrasher, James; Sirirassamee, Buppha; Omar, Maizurah

2012-01-01

Purpose This paper prospectively examined two kinds of social normative beliefs about smoking, secular versus religious norms, to determine their relative importance in influencing quitting behaviour among Muslim Malaysian and Buddhist Thai smokers. Methods Data come from 2166 Muslim Malaysian and 2463 Buddhist Thai adult smokers who participated in the first three waves of the International Tobacco Control Southeast Asia project. Respondents were followed up about 18 months later with replenishment. Respondents were asked at baseline about whether their society disapproved of smoking and whether their religion discouraged smoking and those recontacted at follow-up were asked about their quitting activity. Results Majority of both religious groups perceived that their religion discouraged smoking (78% Muslim Malaysians and 86% Buddhist Thais) but considerably more Buddhist Thais than Muslim Malaysians perceived that their society disapproved of smoking (80% versus 25%). Among Muslim Malaysians, religious, but not societal, norms had an independent effect on quit attempts. By contrast, among the Buddhist Thais, while both normative beliefs had an independent positive effect on quit attempts, the effect was greater for societal norms. The two kinds of normative beliefs, however, were unrelated to quit success among those who tried. Conclusions The findings suggest that religious norms about smoking may play a greater role than secular norms in driving behaviour change in an environment like Malaysia where tobacco control has been relatively weak until more recently but in the context of a strong tobacco control environment like Thailand, secular norms about smoking becomes the dominant force. PMID:22302214

Double temporal sparsity based accelerated reconstruction of compressively sensed resting-state fMRI.

PubMed

Aggarwal, Priya; Gupta, Anubha

2017-12-01

A number of reconstruction methods have been proposed recently for accelerated functional Magnetic Resonance Imaging (fMRI) data collection. However, existing methods suffer with the challenge of greater artifacts at high acceleration factors. This paper addresses the issue of accelerating fMRI collection via undersampled k-space measurements combined with the proposed method based on l 1 -l 1 norm constraints, wherein we impose first l 1 -norm sparsity on the voxel time series (temporal data) in the transformed domain and the second l 1 -norm sparsity on the successive difference of the same temporal data. Hence, we name the proposed method as Double Temporal Sparsity based Reconstruction (DTSR) method. The robustness of the proposed DTSR method has been thoroughly evaluated both at the subject level and at the group level on real fMRI data. Results are presented at various acceleration factors. Quantitative analysis in terms of Peak Signal-to-Noise Ratio (PSNR) and other metrics, and qualitative analysis in terms of reproducibility of brain Resting State Networks (RSNs) demonstrate that the proposed method is accurate and robust. In addition, the proposed DTSR method preserves brain networks that are important for studying fMRI data. Compared to the existing methods, the DTSR method shows promising potential with an improvement of 10-12 dB in PSNR with acceleration factors upto 3.5 on resting state fMRI data. Simulation results on real data demonstrate that DTSR method can be used to acquire accelerated fMRI with accurate detection of RSNs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Scheduling policies of intelligent sensors and sensor/actuators in flexible structures

NASA Astrophysics Data System (ADS)

Demetriou, Michael A.; Potami, Raffaele

2006-03-01

In this note, we revisit the problem of actuator/sensor placement in large civil infrastructures and flexible space structures within the context of spatial robustness. The positioning of these devices becomes more important in systems employing wireless sensor and actuator networks (WSAN) for improved control performance and for rapid failure detection. The ability of the sensing and actuating devices to possess the property of spatial robustness results in reduced control energy and therefore the spatial distribution of disturbances is integrated into the location optimization measures. In our studies, the structure under consideration is a flexible plate clamped at all sides. First, we consider the case of sensor placement and the optimization scheme attempts to produce those locations that minimize the effects of the spatial distribution of disturbances on the state estimation error; thus the sensor locations produce state estimators with minimized disturbance-to-error transfer function norms. A two-stage optimization procedure is employed whereby one first considers the open loop system and the spatial distribution of disturbances is found that produces the maximal effects on the entire open loop state. Once this "worst" spatial distribution of disturbances is found, the optimization scheme subsequently finds the locations that produce state estimators with minimum transfer function norms. In the second part, we consider the collocated actuator/sensor pairs and the optimization scheme produces those locations that result in compensators with the smallest norms of the disturbance-to-state transfer functions. Going a step further, an intelligent control scheme is presented which, at each time interval, activates a subset of the actuator/sensor pairs in order provide robustness against spatiotemporally moving disturbances and minimize power consumption by keeping some sensor/actuators in sleep mode.

Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm.

PubMed

Belilovsky, Eugene; Gkirtzou, Katerina; Misyrlis, Michail; Konova, Anna B; Honorio, Jean; Alia-Klein, Nelly; Goldstein, Rita Z; Samaras, Dimitris; Blaschko, Matthew B

2015-12-01

We explore various sparse regularization techniques for analyzing fMRI data, such as the ℓ1 norm (often called LASSO in the context of a squared loss function), elastic net, and the recently introduced k-support norm. Employing sparsity regularization allows us to handle the curse of dimensionality, a problem commonly found in fMRI analysis. In this work we consider sparse regularization in both the regression and classification settings. We perform experiments on fMRI scans from cocaine-addicted as well as healthy control subjects. We show that in many cases, use of the k-support norm leads to better predictive performance, solution stability, and interpretability as compared to other standard approaches. We additionally analyze the advantages of using the absolute loss function versus the standard squared loss which leads to significantly better predictive performance for the regularization methods tested in almost all cases. Our results support the use of the k-support norm for fMRI analysis and on the clinical side, the generalizability of the I-RISA model of cocaine addiction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gender norms among "Landless" youth: evidence for the social practice of nursing.

PubMed

Zanatta, Luiz Fabiano; Ruiz-Cantero, Maria Tereza; Chilet-Rossel, Elisa; Álvarez-Dardet, Carlos; Brêtas, José Roberto da Silva

2017-01-01

Objective Analyzing the relationship between socio-demographic characteristics of youth from the Landless Rural Workers' Movement in Brazil (MST) regarding the prevalence ratio being in accordance with gender norms. Method A cross-sectional study conducted during a Journey of Agroecology carried out in the State of Paraná with young people (15 to 29 years) of both genders. Data collection was conducted through questionnaires. Data analysis compared variables regarding gender norms with sociodemographic variables, and a Prevalence Ratio (PR) was calculated with a confidence interval (CI) set at 95% in order to determine this relationship. Results The study sample was comprised of 147 young people. A higher prevalence was found in accordance with gender norms (PR with CI at 95%) among women compared to men, and that sociodemographic characteristics (lower education level, those living in occupation camps, who do not have white skin and with religious belief) were social indicators for such positioning among both genders. Conclusion The byproduct of a patriarchal gender system has led more young girls to internalization and a reaffirmation of gender norms, highlighting an important field for social nursing practices in order to contribute to the transformation of this reality.

Nonlinear gamma correction via normed bicoherence minimization in optical fringe projection metrology

NASA Astrophysics Data System (ADS)

Kamagara, Abel; Wang, Xiangzhao; Li, Sikun

2018-03-01

We propose a method to compensate for the projector intensity nonlinearity induced by gamma effect in three-dimensional (3-D) fringe projection metrology by extending high-order spectra analysis and bispectral norm minimization to digital sinusoidal fringe pattern analysis. The bispectrum estimate allows extraction of vital signal information features such as spectral component correlation relationships in fringe pattern images. Our approach exploits the fact that gamma introduces high-order harmonic correlations in the affected fringe pattern image. Estimation and compensation of projector nonlinearity is realized by detecting and minimizing the normed bispectral coherence of these correlations. The proposed technique does not require calibration information and technical knowledge or specification of fringe projection unit. This is promising for developing a modular and calibration-invariant model for intensity nonlinear gamma compensation in digital fringe pattern projection profilometry. Experimental and numerical simulation results demonstrate this method to be efficient and effective in improving the phase measuring accuracies with phase-shifting fringe pattern projection profilometry.

The weakest t-norm based intuitionistic fuzzy fault-tree analysis to evaluate system reliability.

PubMed

Kumar, Mohit; Yadav, Shiv Prasad

2012-07-01

In this paper, a new approach of intuitionistic fuzzy fault-tree analysis is proposed to evaluate system reliability and to find the most critical system component that affects the system reliability. Here weakest t-norm based intuitionistic fuzzy fault tree analysis is presented to calculate fault interval of system components from integrating expert's knowledge and experience in terms of providing the possibility of failure of bottom events. It applies fault-tree analysis, α-cut of intuitionistic fuzzy set and T(ω) (the weakest t-norm) based arithmetic operations on triangular intuitionistic fuzzy sets to obtain fault interval and reliability interval of the system. This paper also modifies Tanaka et al.'s fuzzy fault-tree definition. In numerical verification, a malfunction of weapon system "automatic gun" is presented as a numerical example. The result of the proposed method is compared with the listing approaches of reliability analysis methods. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource

PubMed Central

Ananiadou, Sophia

2016-01-01

Biomedical literature articles and narrative content from Electronic Health Records (EHRs) both constitute rich sources of disease-phenotype information. Phenotype concepts may be mentioned in text in multiple ways, using phrases with a variety of structures. This variability stems partly from the different backgrounds of the authors, but also from the different writing styles typically used in each text type. Since EHR narrative reports and literature articles contain different but complementary types of valuable information, combining details from each text type can help to uncover new disease-phenotype associations. However, the alternative ways in which the same concept may be mentioned in each source constitutes a barrier to the automatic integration of information. Accordingly, identification of the unique concepts represented by phrases in text can help to bridge the gap between text types. We describe our development of a novel method, PhenoNorm, which integrates a number of different similarity measures to allow automatic linking of phenotype concept mentions to known concepts in the UMLS Metathesaurus, a biomedical terminological resource. PhenoNorm was developed using the PhenoCHF corpus—a collection of literature articles and narratives in EHRs, annotated for phenotypic information relating to congestive heart failure (CHF). We evaluate the performance of PhenoNorm in linking CHF-related phenotype mentions to Metathesaurus concepts, using a newly enriched version of PhenoCHF, in which each phenotype mention has an expert-verified link to a concept in the UMLS Metathesaurus. We show that PhenoNorm outperforms a number of alternative methods applied to the same task. Furthermore, we demonstrate PhenoNorm’s wider utility, by evaluating its ability to link mentions of various other types of medically-related information, occurring in texts covering wider subject areas, to concepts in different terminological resources. We show that PhenoNorm can maintain performance levels, and that its accuracy compares favourably to other methods applied to these tasks. PMID:27643689

SF-36v2 norms and its' discriminative properties among healthy households of tuberculosis patients in Malaysia.

PubMed

Atif, Muhammad; Sulaiman, Syed Azhar Syed; Shafie, Asrul Akmal; Asif, Muhammad; Ahmad, Nafees

2013-10-01

The aim of the study was to obtain norms of the SF-36v2 health survey and the association of summary component scores with socio-demographic variables in healthy households of tuberculosis (TB) patients. All household members (18 years and above; healthy; literate) of registered tuberculosis patients who came for contact tracing during March 2010 to February 2011 at the respiratory clinic of Penang General Hospital were invited to complete the SF-36v2 health survey using the official translation of the questionnaire in Malay, Mandarin, Tamil and English. Scoring of the questionnaire was done using Quality Metric's QM Certified Scoring Software version 4. Multivariate analysis was conducted to uncover the predictors of physical and mental health. A total of 649 eligible respondents were approached, while 525 agreed to participate in the study (response rate = 80.1 %). Out of consenting respondents, 46.5 % were male and only 5.3 % were over 75 years. Internal consistencies met the minimum criteria (α > 0.7). Reliability coefficients of the scales were always less than their own reliability coefficients. Mean physical component summary scale scores were equivalent to United States general population norms. However, there was a difference of more than three norm-based scoring points for mean mental component summary scores indicating poor mental health. A notable proportion of the respondents was at the risk of depression. Respondents aged 75 years and above (p = 0.001; OR 32.847), widow (p = 0.013; OR 2.599) and postgraduates (p < 0.001; OR 7.865) were predictors of poor physical health while unemployment (p = 0.033; OR 1.721) was the only predictor of poor mental health. The SF-36v2 is a valid instrument to assess HRQoL among the households of TB patients. Study findings indicate the existence of poor mental health and risk of depression among family caregivers of TB patients. We therefore recommend that caregivers of TB patients to be offered intensive support and special attention to cope with these emotional problems.

Theoretical and Practical Issues of the Implementation of International Norms on Human Rights to the National Legislation (the Example of the Republic of Azerbaijan)

ERIC Educational Resources Information Center

Aliyev, Subhan F.

2016-01-01

The purpose of the study is to analyze the features of the implementation of international norms on human rights to the national law system of the Republic of Azerbaijan. Using the method of the critical analysis of national legislative framework on human rights, the authors argue that there are some certain problems connected with the application…

Control Allocation with Load Balancing

NASA Technical Reports Server (NTRS)

Bodson, Marc; Frost, Susan A.

2009-01-01

Next generation aircraft with a large number of actuators will require advanced control allocation methods to compute the actuator commands needed to follow desired trajectories while respecting system constraints. Previously, algorithms were proposed to minimize the l1 or l2 norms of the tracking error and of the actuator deflections. The paper discusses the alternative choice of the l(infinity) norm, or sup norm. Minimization of the control effort translates into the minimization of the maximum actuator deflection (min-max optimization). The paper shows how the problem can be solved effectively by converting it into a linear program and solving it using a simplex algorithm. Properties of the algorithm are also investigated through examples. In particular, the min-max criterion results in a type of load balancing, where the load is th desired command and the algorithm balances this load among various actuators. The solution using the l(infinity) norm also results in better robustness to failures and to lower sensitivity to nonlinearities in illustrative examples.

Competitive testing of health behavior theories: how do benefits, barriers, subjective norm, and intention influence mammography behavior?

PubMed Central

Murphy, Caitlin C.; Vernon, Sally W.; Diamond, Pamela M.; Tiro, Jasmin A.

2013-01-01

Background Competitive hypothesis testing may explain differences in predictive power across multiple health behavior theories. Purpose We tested competing hypotheses of the Health Belief Model (HBM) and Theory of Reasoned Action (TRA) to quantify pathways linking subjective norm, benefits, barriers, intention, and mammography behavior. Methods We analyzed longitudinal surveys of women veterans randomized to the control group of a mammography intervention trial (n=704). We compared direct, partial mediation, and full mediation models with Satorra-Bentler χ2 difference testing. Results Barriers had a direct and indirect negative effect on mammography behavior; intention only partially mediated barriers. Benefits had little to no effect on behavior and intention; however, it was negatively correlated with barriers. Subjective norm directly affected behavior and indirectly affected intention through barriers. Conclusions Our results provide empiric support for different assertions of HBM and TRA. Future interventions should test whether building subjective norm and reducing negative attitudes increases regular mammography. PMID:23868613

A novel surrogate-based approach for optimal design of electromagnetic-based circuits

NASA Astrophysics Data System (ADS)

Hassan, Abdel-Karim S. O.; Mohamed, Ahmed S. A.; Rabie, Azza A.; Etman, Ahmed S.

2016-02-01

A new geometric design centring approach for optimal design of central processing unit-intensive electromagnetic (EM)-based circuits is introduced. The approach uses norms related to the probability distribution of the circuit parameters to find distances from a point to the feasible region boundaries by solving nonlinear optimization problems. Based on these normed distances, the design centring problem is formulated as a max-min optimization problem. A convergent iterative boundary search technique is exploited to find the normed distances. To alleviate the computation cost associated with the EM-based circuits design cycle, space-mapping (SM) surrogates are used to create a sequence of iteratively updated feasible region approximations. In each SM feasible region approximation, the centring process using normed distances is implemented, leading to a better centre point. The process is repeated until a final design centre is attained. Practical examples are given to show the effectiveness of the new design centring method for EM-based circuits.

Regularized Filters for L1-Norm-Based Common Spatial Patterns.

PubMed

Wang, Haixian; Li, Xiaomeng

2016-02-01

The l1 -norm-based common spatial patterns (CSP-L1) approach is a recently developed technique for optimizing spatial filters in the field of electroencephalogram (EEG)-based brain computer interfaces. The l1 -norm-based expression of dispersion in CSP-L1 alleviates the negative impact of outliers. In this paper, we further improve the robustness of CSP-L1 by taking into account noise which does not necessarily have as large a deviation as with outliers. The noise modelling is formulated by using the waveform length of the EEG time course. With the noise modelling, we then regularize the objective function of CSP-L1, in which the l1-norm is used in two folds: one is the dispersion and the other is the waveform length. An iterative algorithm is designed to resolve the optimization problem of the regularized objective function. A toy illustration and the experiments of classification on real EEG data sets show the effectiveness of the proposed method.

Low-illumination image denoising method for wide-area search of nighttime sea surface

NASA Astrophysics Data System (ADS)

Song, Ming-zhu; Qu, Hong-song; Zhang, Gui-xiang; Tao, Shu-ping; Jin, Guang

2018-05-01

In order to suppress complex mixing noise in low-illumination images for wide-area search of nighttime sea surface, a model based on total variation (TV) and split Bregman is proposed in this paper. A fidelity term based on L1 norm and a fidelity term based on L2 norm are designed considering the difference between various noise types, and the regularization mixed first-order TV and second-order TV are designed to balance the influence of details information such as texture and edge for sea surface image. The final detection result is obtained by using the high-frequency component solved from L1 norm and the low-frequency component solved from L2 norm through wavelet transform. The experimental results show that the proposed denoising model has perfect denoising performance for artificially degraded and low-illumination images, and the result of image quality assessment index for the denoising image is superior to that of the contrastive models.

Patient loyalty model.

PubMed

Sumaedi, Sik; Bakti, I Gede Mahatma Yuda; Rakhmawati, Tri; Astrini, Nidya Judhi; Yarmen, Medi; Widianti, Tri

2015-07-06

This study aims to investigate the simultaneous effect of subjective norm, perceived behavioral control and trust on patient loyalty. The empirical data were collected through survey. The respondents of the survey are 157 patients of a health-care service institution in Bogor, Indonesia. Multiple regressions analysis was performed to test the conceptual model and the proposed hypotheses. The findings showed that subjective norm and trust influence patient loyalty positively. However, this research also found that perceived behavioral control does not influence patient loyalty significantly. The survey was only conducted at one health-care service institution in Bogor, Indonesia. In addition, convenience sampling method was used. These conditions may cause that the research results can not be generalized to the other contexts. Therefore, replication research is needed to test the stability of the findings in the other contexts. Health-care service institutions need to pay attention to trust and subjective norm to establish patient loyalty. This study is believed to be the first to develop and test patient loyalty model that includes subjective norm, perceived behavioral control and trust.

A better norm-referenced grading using the standard deviation criterion.

PubMed

Chan, Wing-shing

2014-01-01

The commonly used norm-referenced grading assigns grades to rank-ordered students in fixed percentiles. It has the disadvantage of ignoring the actual distance of scores among students. A simple norm-referenced grading via standard deviation is suggested for routine educational grading. The number of standard deviation of a student's score from the class mean was used as the common yardstick to measure achievement level. Cumulative probability of a normal distribution was referenced to help decide the amount of students included within a grade. RESULTS of the foremost 12 students from a medical examination were used for illustrating this grading method. Grading by standard deviation seemed to produce better cutoffs in allocating an appropriate grade to students more according to their differential achievements and had less chance in creating arbitrary cutoffs in between two similarly scored students than grading by fixed percentile. Grading by standard deviation has more advantages and is more flexible than grading by fixed percentile for norm-referenced grading.

Wired: Energy Drinks, Jock Identity, Masculine Norms, and Risk Taking

PubMed Central

Miller, Kathleen E.

2008-01-01

Objective The author examined gendered links among sport-related identity, endorsement of conventional masculine norms, risk taking, and energy-drink consumption. Participants The author surveyed 795 undergraduate students enrolled in introductory-level courses at a public university. Methods The author conducted linear regression analyses of energy-drink consumption frequencies on sociodemographic characteristics, jock identity, masculine norms, and risk-taking behavior. Results Of participants, 39% consumed an energy drink in the past month, with more frequent use by men (2.49 d/month) than by women (1.22 d/month). Strength of jock identity was positively associated with frequency of energy-drink consumption; this relationship was mediated by both masculine norms and risk-taking behavior. Conclusions Sport-related identity, masculinity, and risk taking are components of the emerging portrait of a toxic jock identity, which may signal an elevated risk for health-compromising behaviors. College undergraduates’ frequent consumption of Red Bull and comparable energy drinks should be recognized as a potential predictor of toxic jock identity. PMID:18400659

Brief Report: Investigating Uncertainty in the Minimum Mortality Temperature: Methods and Application to 52 Spanish Cities.

PubMed

Tobías, Aurelio; Armstrong, Ben; Gasparrini, Antonio

2017-01-01

The minimum mortality temperature from J- or U-shaped curves varies across cities with different climates. This variation conveys information on adaptation, but ability to characterize is limited by the absence of a method to describe uncertainty in estimated minimum mortality temperatures. We propose an approximate parametric bootstrap estimator of confidence interval (CI) and standard error (SE) for the minimum mortality temperature from a temperature-mortality shape estimated by splines. The coverage of the estimated CIs was close to nominal value (95%) in the datasets simulated, although SEs were slightly high. Applying the method to 52 Spanish provincial capital cities showed larger minimum mortality temperatures in hotter cities, rising almost exactly at the same rate as annual mean temperature. The method proposed for computing CIs and SEs for minimums from spline curves allows comparing minimum mortality temperatures in different cities and investigating their associations with climate properly, allowing for estimation uncertainty.

Reconstructing source terms from atmospheric concentration measurements: Optimality analysis of an inversion technique

NASA Astrophysics Data System (ADS)

Turbelin, Grégory; Singh, Sarvesh Kumar; Issartel, Jean-Pierre

2014-12-01

In the event of an accidental or intentional contaminant release in the atmosphere, it is imperative, for managing emergency response, to diagnose the release parameters of the source from measured data. Reconstruction of the source information exploiting measured data is called an inverse problem. To solve such a problem, several techniques are currently being developed. The first part of this paper provides a detailed description of one of them, known as the renormalization method. This technique, proposed by Issartel (2005), has been derived using an approach different from that of standard inversion methods and gives a linear solution to the continuous Source Term Estimation (STE) problem. In the second part of this paper, the discrete counterpart of this method is presented. By using matrix notation, common in data assimilation and suitable for numerical computing, it is shown that the discrete renormalized solution belongs to a family of well-known inverse solutions (minimum weighted norm solutions), which can be computed by using the concept of generalized inverse operator. It is shown that, when the weight matrix satisfies the renormalization condition, this operator satisfies the criteria used in geophysics to define good inverses. Notably, by means of the Model Resolution Matrix (MRM) formalism, we demonstrate that the renormalized solution fulfils optimal properties for the localization of single point sources. Throughout the article, the main concepts are illustrated with data from a wind tunnel experiment conducted at the Environmental Flow Research Centre at the University of Surrey, UK.

Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction

NASA Astrophysics Data System (ADS)

Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng

2017-01-01

Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.

Development of an effective dose coefficient database using a computational human phantom and Monte Carlo simulations to evaluate exposure dose for the usage of NORM-added consumer products.

PubMed

Yoo, Do Hyeon; Shin, Wook-Geun; Lee, Jaekook; Yeom, Yeon Soo; Kim, Chan Hyeong; Chang, Byung-Uck; Min, Chul Hee

2017-11-01

After the Fukushima accident in Japan, the Korean Government implemented the "Act on Protective Action Guidelines Against Radiation in the Natural Environment" to regulate unnecessary radiation exposure to the public. However, despite the law which came into effect in July 2012, an appropriate method to evaluate the equivalent and effective doses from naturally occurring radioactive material (NORM) in consumer products is not available. The aim of the present study is to develop and validate an effective dose coefficient database enabling the simple and correct evaluation of the effective dose due to the usage of NORM-added consumer products. To construct the database, we used a skin source method with a computational human phantom and Monte Carlo (MC) simulation. For the validation, the effective dose was compared between the database using interpolation method and the original MC method. Our result showed a similar equivalent dose across the 26 organs and a corresponding average dose between the database and the MC calculations of < 5% difference. The differences in the effective doses were even less, and the result generally show that equivalent and effective doses can be quickly calculated with the database with sufficient accuracy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Online Detection of Broken Rotor Bar Fault in Induction Motors by Combining Estimation of Signal Parameters via Min-norm Algorithm and Least Square Method

NASA Astrophysics Data System (ADS)

Wang, Pan-Pan; Yu, Qiang; Hu, Yong-Jun; Miao, Chang-Xin

2017-11-01

Current research in broken rotor bar (BRB) fault detection in induction motors is primarily focused on a high-frequency resolution analysis of the stator current. Compared with a discrete Fourier transformation, the parametric spectrum estimation technique has a higher frequency accuracy and resolution. However, the existing detection methods based on parametric spectrum estimation cannot realize online detection, owing to the large computational cost. To improve the efficiency of BRB fault detection, a new detection method based on the min-norm algorithm and least square estimation is proposed in this paper. First, the stator current is filtered using a band-pass filter and divided into short overlapped data windows. The min-norm algorithm is then applied to determine the frequencies of the fundamental and fault characteristic components with each overlapped data window. Next, based on the frequency values obtained, a model of the fault current signal is constructed. Subsequently, a linear least squares problem solved through singular value decomposition is designed to estimate the amplitudes and phases of the related components. Finally, the proposed method is applied to a simulated current and an actual motor, the results of which indicate that, not only parametric spectrum estimation technique.

Sparsity-Aware DOA Estimation Scheme for Noncircular Source in MIMO Radar.

PubMed

Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Qi; Liu, Jing

2016-04-14

In this paper, a novel sparsity-aware direction of arrival (DOA) estimation scheme for a noncircular source is proposed in multiple-input multiple-output (MIMO) radar. In the proposed method, the reduced-dimensional transformation technique is adopted to eliminate the redundant elements. Then, exploiting the noncircularity of signals, a joint sparsity-aware scheme based on the reweighted l1 norm penalty is formulated for DOA estimation, in which the diagonal elements of the weight matrix are the coefficients of the noncircular MUSIC-like (NC MUSIC-like) spectrum. Compared to the existing l1 norm penalty-based methods, the proposed scheme provides higher angular resolution and better DOA estimation performance. Results from numerical experiments are used to show the effectiveness of our proposed method.

Russian norms for name agreement, image agreement for the colorized version of the Snodgrass and Vanderwart pictures and age of acquisition, conceptual familiarity, and imageability scores for modal object names.

PubMed

Tsaparina, Diana; Bonin, Patrick; Méot, Alain

2011-12-01

The aim of the present study was to provide Russian normative data for the Snodgrass and Vanderwart (Behavior Research Methods, Instruments, & Computers, 28, 516-536, 1980) colorized pictures (Rossion & Pourtois, Perception, 33, 217-236, 2004). The pictures were standardized on name agreement, image agreement, conceptual familiarity, imageability, and age of acquisition. Objective word frequency and objective visual complexity measures are also provided for the most common names associated with the pictures. Comparative analyses between our results and the norms obtained in other, similar studies are reported. The Russian norms may be downloaded from the Psychonomic Society supplemental archive.

[The characterization of biosolids produced by the San Fernando wastewater treatment plant in Itagui, Antioquia, Colombia].

PubMed

Bedoya-Urrego, Katherine; Acevedo-Ruíz, José M; Peláez-Jaramillo, Carlos A; Agudelo-López, Sonia Del Pilar

2013-01-01

ABSTRACT Objective This study was aimed at evaluating pertinent physicochemical and microbiological (bacteria and parasites) parameters regarding the biosolids produced by the San Fernando wastewater treatment plant (WWTP) in Itagui, Antioquia, Colombia. Methods Twelve samples were collected and evaluated every month from January to December during 2010. The chemical, physical and microbiological tests followed the protocol described in Colombian technical guideline 5167. The protocol described in Mexican official Norm 004 (with some modifications) was used for identifying helminth ova and assessing their viability. Results All samples proved positive for Ascarislumbricoides, viable ova count ranging from 4 to 22 eggs/2gTS. Both Salmonella and Enterobacteriawere detected in all samples evaluated, the latter having 3,000 colony forming unit (CFU)/g minimum concentration. Biosolid sample values met the heavy metal concentration requirement established by national guidelines. There was no statistical association between rainfall and the pathogen's presence in the biosolids. Conclusion Our results suggested that the biosolids being produced by the San Fernando wastewater treatment plant (WWTP) could be used as organic fertilizer; however they should be treated/sanitized to meet the stipulations in Colombian technical guideline 5167.

Social vision: sustained perceptual enhancement of affective facial cues in social anxiety

PubMed Central

McTeague, Lisa M.; Shumen, Joshua R.; Wieser, Matthias J.; Lang, Peter J.; Keil, Andreas

2010-01-01

Heightened perception of facial cues is at the core of many theories of social behavior and its disorders. In the present study, we continuously measured electrocortical dynamics in human visual cortex, as evoked by happy, neutral, fearful, and angry faces. Thirty-seven participants endorsing high versus low generalized social anxiety (upper and lower tertiles of 2,104 screened undergraduates) viewed naturalistic faces flickering at 17.5 Hz to evoke steady-state visual evoked potentials (ssVEPs), recorded from 129 scalp electrodes. Electrophysiological data were evaluated in the time-frequency domain after linear source space projection using the minimum norm method. Source estimation indicated an early visual cortical origin of the face-evoked ssVEP, which showed sustained amplitude enhancement for emotional expressions specifically in individuals with pervasive social anxiety. Participants in the low symptom group showed no such sensitivity, and a correlational analysis across the entire sample revealed a strong relationship between self-reported interpersonal anxiety/avoidance and enhanced visual cortical response amplitude for emotional, versus neutral expressions. This pattern was maintained across the 3500 ms viewing epoch, suggesting that temporally sustained, heightened perceptual bias towards affective facial cues is associated with generalized social anxiety. PMID:20832490

Matched Field Processing Based on Least Squares with a Small Aperture Hydrophone Array.

PubMed

Wang, Qi; Wang, Yingmin; Zhu, Guolei

2016-12-30

The receiver hydrophone array is the signal front-end and plays an important role in matched field processing, which usually covers the whole water column from the sea surface to the bottom. Such a large aperture array is very difficult to realize. To solve this problem, an approach called matched field processing based on least squares with a small aperture hydrophone array is proposed, which decomposes the received acoustic fields into depth function matrix and amplitudes of the normal modes at the beginning. Then all the mode amplitudes are estimated using the least squares in the sense of minimum norm, and the amplitudes estimated are used to recalculate the received acoustic fields of the small aperture array, which means the recalculated ones contain more environmental information. In the end, lots of numerical experiments with three small aperture arrays are processed in the classical shallow water, and the performance of matched field passive localization is evaluated. The results show that the proposed method can make the recalculated fields contain more acoustic information of the source, and the performance of matched field passive localization with small aperture array is improved, so the proposed algorithm is proved to be effective.

Matched Field Processing Based on Least Squares with a Small Aperture Hydrophone Array

PubMed Central

Wang, Qi; Wang, Yingmin; Zhu, Guolei

2016-01-01

The receiver hydrophone array is the signal front-end and plays an important role in matched field processing, which usually covers the whole water column from the sea surface to the bottom. Such a large aperture array is very difficult to realize. To solve this problem, an approach called matched field processing based on least squares with a small aperture hydrophone array is proposed, which decomposes the received acoustic fields into depth function matrix and amplitudes of the normal modes at the beginning. Then all the mode amplitudes are estimated using the least squares in the sense of minimum norm, and the amplitudes estimated are used to recalculate the received acoustic fields of the small aperture array, which means the recalculated ones contain more environmental information. In the end, lots of numerical experiments with three small aperture arrays are processed in the classical shallow water, and the performance of matched field passive localization is evaluated. The results show that the proposed method can make the recalculated fields contain more acoustic information of the source, and the performance of matched field passive localization with small aperture array is improved, so the proposed algorithm is proved to be effective. PMID:28042828

Benefits and risks of adopting the global code of practice for recreational fisheries

USGS Publications Warehouse

Arlinghaus, Robert; Beard, T. Douglas; Cooke, Steven J.; Cowx, Ian G.

2012-01-01

Recreational fishing constitutes the dominant or sole use of many fish stocks, particularly in freshwater ecosystems in Western industrialized countries. However, despite their social and economic importance, recreational fisheries are generally guided by local or regional norms and standards, with few comprehensive policy and development frameworks existing across jurisdictions. We argue that adoption of a recently developed Global Code of Practice (CoP) for Recreational Fisheries can provide benefits for moving recreational fisheries toward sustainability on a global scale. The CoP is a voluntary document, specifically framed toward recreational fisheries practices and issues, thereby complementing and extending the United Nation's Code of Conduct for Responsible Fisheries by the Food and Agricultural Organization. The CoP for Recreational Fisheries describes the minimum standards of environmentally friendly, ethically appropriate, and—depending on local situations—socially acceptable recreational fishing and its management. Although many, if not all, of the provisions presented in the CoP are already addressed through national fisheries legislation and state-based fisheries management regulations in North America, adopting a common framework for best practices in recreational fisheries across multiple jurisdictions would further promote their long-term viability in the face of interjurisdictional angler movements and some expanding threats to the activity related to shifting sociopolitical norms.

Minimal norm constrained interpolation. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Irvine, L. D.

1985-01-01

In computational fluid dynamics and in CAD/CAM, a physical boundary is usually known only discreetly and most often must be approximated. An acceptable approximation preserves the salient features of the data such as convexity and concavity. In this dissertation, a smooth interpolant which is locally concave where the data are concave and is locally convex where the data are convex is described. The interpolant is found by posing and solving a minimization problem whose solution is a piecewise cubic polynomial. The problem is solved indirectly by using the Peano Kernal theorem to recast it into an equivalent minimization problem having the second derivative of the interpolant as the solution. This approach leads to the solution of a nonlinear system of equations. It is shown that Newton's method is an exceptionally attractive and efficient method for solving the nonlinear system of equations. Examples of shape-preserving interpolants, as well as convergence results obtained by using Newton's method are also shown. A FORTRAN program to compute these interpolants is listed. The problem of computing the interpolant of minimal norm from a convex cone in a normal dual space is also discussed. An extension of de Boor's work on minimal norm unconstrained interpolation is presented.

Low-rank structure learning via nonconvex heuristic recovery.

PubMed

Deng, Yue; Dai, Qionghai; Liu, Risheng; Zhang, Zengke; Hu, Sanqing

2013-03-01

In this paper, we propose a nonconvex framework to learn the essential low-rank structure from corrupted data. Different from traditional approaches, which directly utilizes convex norms to measure the sparseness, our method introduces more reasonable nonconvex measurements to enhance the sparsity in both the intrinsic low-rank structure and the sparse corruptions. We will, respectively, introduce how to combine the widely used ℓp norm (0 < p < 1) and log-sum term into the framework of low-rank structure learning. Although the proposed optimization is no longer convex, it still can be effectively solved by a majorization-minimization (MM)-type algorithm, with which the nonconvex objective function is iteratively replaced by its convex surrogate and the nonconvex problem finally falls into the general framework of reweighed approaches. We prove that the MM-type algorithm can converge to a stationary point after successive iterations. The proposed model is applied to solve two typical problems: robust principal component analysis and low-rank representation. Experimental results on low-rank structure learning demonstrate that our nonconvex heuristic methods, especially the log-sum heuristic recovery algorithm, generally perform much better than the convex-norm-based method (0 < p < 1) for both data with higher rank and with denser corruptions.

Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.

PubMed

Alves, R S; Teodoro, P E; Farias, F C; Farias, F J C; Carvalho, L P; Rodrigues, J I S; Bhering, L L; Resende, M D V

2017-08-17

Cotton produces one of the most important textile fibers of the world and has great relevance in the world economy. It is an economically important crop in Brazil, which is the world's fifth largest producer. However, studies evaluating the genotype x environment (G x E) interactions in cotton are scarce in this country. Therefore, the goal of this study was to evaluate the G x E interactions in two important traits in cotton (fiber yield and fiber length) using the method proposed by Eberhart and Russell (simple linear regression) and reaction norm models (random regression). Eight trials with sixteen upland cotton genotypes, conducted in a randomized block design, were used. It was possible to identify a genotype with wide adaptability and stability for both traits. Reaction norm models have excellent theoretical and practical properties and led to more informative and accurate results than the method proposed by Eberhart and Russell and should, therefore, be preferred. Curves of genotypic values as a function of the environmental gradient, which predict the behavior of the genotypes along the environmental gradient, were generated. These curves make possible the recommendation to untested environmental levels.

Application of an improved minimum entropy deconvolution method for railway rolling element bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Yao; Zhou, Ning; Zhang, Weihua; Wang, Zhiwei

2018-07-01

Minimum entropy deconvolution is a widely-used tool in machinery fault diagnosis, because it enhances the impulse component of the signal. The filter coefficients that greatly influence the performance of the minimum entropy deconvolution are calculated by an iterative procedure. This paper proposes an improved deconvolution method for the fault detection of rolling element bearings. The proposed method solves the filter coefficients by the standard particle swarm optimization algorithm, assisted by a generalized spherical coordinate transformation. When optimizing the filters performance for enhancing the impulses in fault diagnosis (namely, faulty rolling element bearings), the proposed method outperformed the classical minimum entropy deconvolution method. The proposed method was validated in simulation and experimental signals from railway bearings. In both simulation and experimental studies, the proposed method delivered better deconvolution performance than the classical minimum entropy deconvolution method, especially in the case of low signal-to-noise ratio.

Winter ventilation rates at primary schools: comparison between Portugal and Finland.

PubMed

Canha, N; Almeida, S M; Freitas, M C; Täubel, M; Hänninen, O

2013-01-01

This study focused on examination of ventilation rates in classrooms with two different types of ventilation systems: natural and mechanical. Carbon dioxide (CO2) measurements were conducted in primary schools of Portugal characterized by natural ventilation and compared to Finland where mechanical ventilation is the norm. The winter period was selected since this season exerts a great influence in naturally ventilated classrooms, where opening of windows and doors occurs due to outdoor atmospheric conditions. The ventilation rates were calculated by monitoring CO2 concentrations generated by the occupants (used as a tracer gas) and application of the buildup phase method. A comparison between both countries' results was conducted with respect to ventilation rates and how these levels corresponded to national regulatory standards. Finnish primary schools (n = 2) registered a mean ventilation rate of 13.3 L/s per person, which is higher than the recommended ventilation standards. However, the Finnish classroom that presented the lowest ventilation rate (7.2 L/s per person) displayed short-term CO2 levels above 1200 ppm, which is the threshold limit value (TLV) recommended by national guidelines. The Portuguese classrooms (n = 2) showed low ventilation rates with mean values of 2.4 L/s per person, which is markedly lower than the minimum recommended value of 7 L/s per person as defined by ASHRAE and 20% less than the REHVA minimum of 3 L/s per person. Carbon dioxide levels of 1000 ppm, close to the TLV of 1200 ppm, were also reached in both Portuguese classrooms studied. The situation in Portugal indicates a potentially serious indoor air quality problem and strengthens the need for intervention to improve ventilation rates in naturally ventilated classrooms.

Comparison of data transformation procedures to enhance topographical accuracy in time-series analysis of the human EEG.

PubMed

Hauk, O; Keil, A; Elbert, T; Müller, M M

2002-01-30

We describe a methodology to apply current source density (CSD) and minimum norm (MN) estimation as pre-processing tools for time-series analysis of single trial EEG data. The performance of these methods is compared for the case of wavelet time-frequency analysis of simulated gamma-band activity. A reasonable comparison of CSD and MN on the single trial level requires regularization such that the corresponding transformed data sets have similar signal-to-noise ratios (SNRs). For region-of-interest approaches, it should be possible to optimize the SNR for single estimates rather than for the whole distributed solution. An effective implementation of the MN method is described. Simulated data sets were created by modulating the strengths of a radial and a tangential test dipole with wavelets in the frequency range of the gamma band, superimposed with simulated spatially uncorrelated noise. The MN and CSD transformed data sets as well as the average reference (AR) representation were subjected to wavelet frequency-domain analysis, and power spectra were mapped for relevant frequency bands. For both CSD and MN, the influence of noise can be sufficiently suppressed by regularization to yield meaningful information, but only MN represents both radial and tangential dipole sources appropriately as single peaks. Therefore, when relating wavelet power spectrum topographies to their neuronal generators, MN should be preferred.

Fetal over- and undernutrition differentially program thyroid axis adaptability in adult sheep

PubMed Central

Johnsen, L; Lyckegaard, N B; Khanal, P; Quistorff, B; Raun, K; Nielsen, M O

2018-01-01

Objective We aimed to test, whether fetal under- or overnutrition differentially program the thyroid axis with lasting effects on energy metabolism, and if early-life postnatal overnutrition modulates implications of prenatal programming. Design Twin-pregnant sheep (n = 36) were either adequately (NORM), under- (LOW; 50% of NORM) or overnourished (HIGH; 150% of energy and 110% of protein requirements) in the last-trimester of gestation. From 3 days-of-age to 6 months-of-age, twin lambs received a conventional (CONV) or an obesogenic, high-carbohydrate high-fat (HCHF) diet. Subgroups were slaughtered at 6-months-of-age. Remaining lambs were fed a low-fat diet until 2½ years-of-age (adulthood). Methods Serum hormone levels were determined at 6 months- and 2½ years-of-age. At 2½ years-of-age, feed intake capacity (intake over 4-h following 72-h fasting) was determined, and an intravenous thyroxine tolerance test (iTTT) was performed, including measurements of heart rate, rectal temperature and energy expenditure (EE). Results In the iTTT, the LOW and nutritionally mismatched NORM:HCHF and HIGH:CONV sheep increased serum T3, T3:T4 and T3:TSH less than NORM:CONV, whereas TSH was decreased less in HIGH, NORM:HCHF and LOW:HCHF. Early postnatal exposure to the HCHF diet decreased basal adult EE in NORM and HIGH, but not LOW, and increased adult feed intake capacity in NORM and LOW, but not HIGH. Conclusions: The iTTT revealed a differential programming of central and peripheral HPT axis function in response to late fetal malnutrition and an early postnatal obesogenic diet, with long-term implications for adult HPT axis adaptability and associated consequences for adiposity risk. PMID:29794141

Profiling structured product labeling with NDF-RT and RxNorm

PubMed Central

2012-01-01

Background Structured Product Labeling (SPL) is a document markup standard approved by Health Level Seven (HL7) and adopted by United States Food and Drug Administration (FDA) as a mechanism for exchanging drug product information. The SPL drug labels contain rich information about FDA approved clinical drugs. However, the lack of linkage to standard drug ontologies hinders their meaningful use. NDF-RT (National Drug File Reference Terminology) and NLM RxNorm as standard drug ontology were used to standardize and profile the product labels. Methods In this paper, we present a framework that intends to map SPL drug labels with existing drug ontologies: NDF-RT and RxNorm. We also applied existing categorical annotations from the drug ontologies to classify SPL drug labels into corresponding classes. We established the classification and relevant linkage for SPL drug labels using the following three approaches. First, we retrieved NDF-RT categorical information from the External Pharmacologic Class (EPC) indexing SPLs. Second, we used the RxNorm and NDF-RT mappings to classify and link SPLs with NDF-RT categories. Third, we profiled SPLs using RxNorm term type information. In the implementation process, we employed a Semantic Web technology framework, in which we stored the data sets from NDF-RT and SPLs into a RDF triple store, and executed SPARQL queries to retrieve data from customized SPARQL endpoints. Meanwhile, we imported RxNorm data into MySQL relational database. Results In total, 96.0% SPL drug labels were mapped with NDF-RT categories whereas 97.0% SPL drug labels are linked to RxNorm codes. We found that the majority of SPL drug labels are mapped to chemical ingredient concepts in both drug ontologies whereas a relatively small portion of SPL drug labels are mapped to clinical drug concepts. Conclusions The profiling outcomes produced by this study would provide useful insights on meaningful use of FDA SPL drug labels in clinical applications through standard drug ontologies such as NDF-RT and RxNorm. PMID:23256517

Adolescents’ Conformity to Their Peers’ Pro-Alcohol and Anti-Alcohol Norms: The Power of Popularity

PubMed Central

Teunissen, Hanneke A.; Spijkerman, Renske; Prinstein, Mitchell J.; Cohen, Geoffrey L.; Engels, Rutger C. M. E.; Scholte, Ron H. J.

2013-01-01

Background Research on adolescent development suggests that peer influence may play a key role in explaining adolescents’ willingness to drink, an important predictor of drinking initiation. However, experiments that thoroughly examine these peer influence effects are scarce. This study experimentally examined whether adolescents adapted their willingness to drink when confronted with the pro-alcohol and anti-alcohol norms of peers in a chat room session and whether these effects were moderated by the social status of peers. Methods We collected survey data on drinking behavior, social status, and willingness to drink among five hundred thirty-two 14- to 15-year-olds. Of this sample, 74 boys participated in a simulated Internet chat room session in which participants were confronted with preprogrammed pro-alcohol or anti-alcohol norms of “grade-mates” which were in fact preprogrammed e-confederates. Accordingly, we tested whether participants adapted their willingness to drink to the norms of these grade-mates. To test whether adaptations in participants’ willingness to drink would depend on grade-mates’ social status, we manipulated their level of popularity. Results The results indicated that adolescents adapted their willingness to drink substantially to the pro-alcohol (i.e., more willing to drink) as well as anti-alcohol (i.e., less willing to drink) norms of these peers. Adolescents were more influenced by high-status than low-status peers. Interestingly, the anti-alcohol norms of the popular peers seemed most influential in that adolescents were less willing to drink when they were confronted with the anti-alcohol norms of popular peers. Additionally, the adolescents internalized these anti-alcohol norms. Conclusions This study gives more insight into peer influence processes that encourage or discourage alcohol use. These results could be fundamental for the development of prevention and intervention programs to reduce alcohol use among the adolescents. PMID:22509937

Estimation of Leakage Potential of Selected Sites in Interstate and Tri-State Canals Using Geostatistical Analysis of Selected Capacitively Coupled Resistivity Profiles, Western Nebraska, 2004

USGS Publications Warehouse

Vrabel, Joseph; Teeple, Andrew; Kress, Wade H.

2009-01-01

With increasing demands for reliable water supplies and availability estimates, groundwater flow models often are developed to enhance understanding of surface-water and groundwater systems. Specific hydraulic variables must be known or calibrated for the groundwater-flow model to accurately simulate current or future conditions. Surface geophysical surveys, along with selected test-hole information, can provide an integrated framework for quantifying hydrogeologic conditions within a defined area. In 2004, the U.S. Geological Survey, in cooperation with the North Platte Natural Resources District, performed a surface geophysical survey using a capacitively coupled resistivity technique to map the lithology within the top 8 meters of the near-surface for 110 kilometers of the Interstate and Tri-State Canals in western Nebraska and eastern Wyoming. Assuming that leakage between the surface-water and groundwater systems is affected primarily by the sediment directly underlying the canal bed, leakage potential was estimated from the simple vertical mean of inverse-model resistivity values for depth levels with geometrically increasing layer thickness with depth which resulted in mean-resistivity values biased towards the surface. This method generally produced reliable results, but an improved analysis method was needed to account for situations where confining units, composed of less permeable material, underlie units with greater permeability. In this report, prepared by the U.S. Geological Survey in cooperation with the North Platte Natural Resources District, the authors use geostatistical analysis to develop the minimum-unadjusted method to compute a relative leakage potential based on the minimum resistivity value in a vertical column of the resistivity model. The minimum-unadjusted method considers the effects of homogeneous confining units. The minimum-adjusted method also is developed to incorporate the effect of local lithologic heterogeneity on water transmission. Seven sites with differing geologic contexts were selected following review of the capacitively coupled resistivity data collected in 2004. A reevaluation of these sites using the mean, minimum-unadjusted, and minimum-adjusted methods was performed to compare the different approaches for estimating leakage potential. Five of the seven sites contained underlying confining units, for which the minimum-unadjusted and minimum-adjusted methods accounted for the confining-unit effect. Estimates of overall leakage potential were lower for the minimum-unadjusted and minimum-adjusted methods than those estimated by the mean method. For most sites, the local heterogeneity adjustment procedure of the minimum-adjusted method resulted in slightly larger overall leakage-potential estimates. In contrast to the mean method, the two minimum-based methods allowed the least permeable areas to control the overall vertical permeability of the subsurface. The minimum-adjusted method refined leakage-potential estimation by additionally including local lithologic heterogeneity effects.

Globalization and eating disorder risk: Peer influence, perceived social norms, and adolescent disordered eating in Fiji

PubMed Central

Gerbasi, Margaret E.; Richards, Lauren K.; Thomas, Jennifer J.; Agnew-Blais, Jessica C.; Thompson-Brenner, Heather; Gilman, Stephen E.; Becker, Anne E.

2014-01-01

Objective The increasing global health burden imposed by eating disorders warrants close examination of social exposures associated with globalization that potentially elevate risk during the critical developmental period of adolescence in low- and middle-income countries (LMICs). The study aim was to investigate the association of peer influence and perceived social norms with adolescent eating pathology in Fiji, a LMIC undergoing rapid social change. Method We measured peer influence on eating concerns (with the Inventory of Peer Influence on Eating Concerns; IPIEC), perceived peer norms associated with disordered eating and body concerns, perceived community cultural norms, and individual cultural orientations in a representative sample of school-going ethnic Fijian adolescent girls (n=523). We then developed a multivariable linear regression model to examine their relation to eating pathology (measured by the Eating Disorder Examination-Questionnaire; EDE-Q). Results We found independent and statistically significant associations between both IPIEC scores and our proxy for perceived social norms specific to disordered eating (both p <.001) and EDE-Q global scores in a fully adjusted linear regression model. Discussion Study findings support the possibility that peer influence as well as perceived social norms relevant to disordered eating may elevate risk for disordered eating in Fiji, during the critical developmental period of adolescence. Replication and extension of these research findings in other populations undergoing rapid social transition—and where globalization is also influencing local social norms—may enrich etiologic models and inform strategies to mitigate risk. PMID:25139374

The research subject as wage earner.

PubMed

Anderson, James A; Weijer, Charles

2002-01-01

The practice of paying research subjects for participating in clinical trials has yet to receive an adequate moral analysis. Dickert and Grady argue for a wage payment model in which research subjects are paid an hourly wage based on that of unskilled laborers. If we accept this approach, what follows? Norms for just working conditions emerge from workplace legislation and political theory. All workers, including paid research subjects under Dickert and Grady's analysis, have a right to at least minimum wage, a standard work week, extra pay for overtime hours, a safe workplace, no fault compensation for work-related injury, and union organization. If we accept that paid research subjects are wage earners like any other, then the implications for changes to current practice are substantial.

Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring.

PubMed

Xiong, Naixue; Liu, Ryan Wen; Liang, Maohan; Wu, Di; Liu, Zhao; Wu, Huisi

2017-01-18

Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only one blurred image. Under many degraded imaging conditions, the blur kernel could be considered not only spatially sparse, but also piecewise smooth with the support of a continuous curve. By taking advantage of the hybrid sparse properties of the blur kernel, a hybrid regularization method is proposed in this paper to robustly and accurately estimate the blur kernel. The effectiveness of the proposed blur kernel estimation method is enhanced by incorporating both the L 1 -norm of kernel intensity and the squared L 2 -norm of the intensity derivative. Once the accurate estimation of the blur kernel is obtained, the original blind deblurring can be simplified to the direct deconvolution of blurred images. To guarantee robust non-blind deconvolution, a variational image restoration model is presented based on the L 1 -norm data-fidelity term and the total generalized variation (TGV) regularizer of second-order. All non-smooth optimization problems related to blur kernel estimation and non-blind deconvolution are effectively handled by using the alternating direction method of multipliers (ADMM)-based numerical methods. Comprehensive experiments on both synthetic and realistic datasets have been implemented to compare the proposed method with several state-of-the-art methods. The experimental comparisons have illustrated the satisfactory imaging performance of the proposed method in terms of quantitative and qualitative evaluations.

Moving force identification based on redundant concatenated dictionary and weighted l1-norm regularization

NASA Astrophysics Data System (ADS)

Pan, Chu-Dong; Yu, Ling; Liu, Huan-Lin; Chen, Ze-Peng; Luo, Wen-Feng

2018-01-01

Moving force identification (MFI) is an important inverse problem in the field of bridge structural health monitoring (SHM). Reasonable signal structures of moving forces are rarely considered in the existing MFI methods. Interaction forces are complex because they contain both slowly-varying harmonic and impact signals due to bridge vibration and bumps on a bridge deck, respectively. Therefore, the interaction forces are usually hard to be expressed completely and sparsely by using a single basis function set. Based on the redundant concatenated dictionary and weighted l1-norm regularization method, a hybrid method is proposed for MFI in this study. The redundant dictionary consists of both trigonometric functions and rectangular functions used for matching the harmonic and impact signal features of unknown moving forces. The weighted l1-norm regularization method is introduced for formulation of MFI equation, so that the signal features of moving forces can be accurately extracted. The fast iterative shrinkage-thresholding algorithm (FISTA) is used for solving the MFI problem. The optimal regularization parameter is appropriately chosen by the Bayesian information criterion (BIC) method. In order to assess the accuracy and the feasibility of the proposed method, a simply-supported beam bridge subjected to a moving force is taken as an example for numerical simulations. Finally, a series of experimental studies on MFI of a steel beam are performed in laboratory. Both numerical and experimental results show that the proposed method can accurately identify the moving forces with a strong robustness, and it has a better performance than the Tikhonov regularization method. Some related issues are discussed as well.

PEPAB Norm Development (PEPABNRM)

DTIC Science & Technology

1991-01-09

AD-A249 908A PEPAB NORM DEVELOPMENT (PEPABNRM) ANNUAL REPORT LESLIE CAROL MONTGOMERY PATRICIA A. DEUSTER S AYA V f JANUARY 9, 1991 S~ Supported by...Methods 14 C. Results 15 D . Discussion 16 III. DEVELOPMENT OF A COMPUTERIZED PHYSICAL ACTIVITY QUESTIONNAIRE 16 REFERENCES 20 TABLES 22 FIGURES 26 ANNUAL...group after the AC test was over 11 mM, even with the 30-sec rest inter- vals during which lactate could be removed. 3. Discussion In conclusion, the

Lp-Norm Regularization in Volumetric Imaging of Cardiac Current Sources

PubMed Central

Rahimi, Azar; Xu, Jingjia; Wang, Linwei

2013-01-01

Advances in computer vision have substantially improved our ability to analyze the structure and mechanics of the heart. In comparison, our ability to observe and analyze cardiac electrical activities is much limited. The progress to computationally reconstruct cardiac current sources from noninvasive voltage data sensed on the body surface has been hindered by the ill-posedness and the lack of a unique solution of the reconstruction problem. Common L2- and L1-norm regularizations tend to produce a solution that is either too diffused or too scattered to reflect the complex spatial structure of current source distribution in the heart. In this work, we propose a general regularization with Lp-norm (1 < p < 2) constraint to bridge the gap and balance between an overly smeared and overly focal solution in cardiac source reconstruction. In a set of phantom experiments, we demonstrate the superiority of the proposed Lp-norm method over its L1 and L2 counterparts in imaging cardiac current sources with increasing extents. Through computer-simulated and real-data experiments, we further demonstrate the feasibility of the proposed method in imaging the complex structure of excitation wavefront, as well as current sources distributed along the postinfarction scar border. This ability to preserve the spatial structure of source distribution is important for revealing the potential disruption to the normal heart excitation. PMID:24348735

Improving Generalization Based on l1-Norm Regularization for EEG-Based Motor Imagery Classification

PubMed Central

Zhao, Yuwei; Han, Jiuqi; Chen, Yushu; Sun, Hongji; Chen, Jiayun; Ke, Ang; Han, Yao; Zhang, Peng; Zhang, Yi; Zhou, Jin; Wang, Changyong

2018-01-01

Multichannel electroencephalography (EEG) is widely used in typical brain-computer interface (BCI) systems. In general, a number of parameters are essential for a EEG classification algorithm due to redundant features involved in EEG signals. However, the generalization of the EEG method is often adversely affected by the model complexity, considerably coherent with its number of undetermined parameters, further leading to heavy overfitting. To decrease the complexity and improve the generalization of EEG method, we present a novel l1-norm-based approach to combine the decision value obtained from each EEG channel directly. By extracting the information from different channels on independent frequency bands (FB) with l1-norm regularization, the method proposed fits the training data with much less parameters compared to common spatial pattern (CSP) methods in order to reduce overfitting. Moreover, an effective and efficient solution to minimize the optimization object is proposed. The experimental results on dataset IVa of BCI competition III and dataset I of BCI competition IV show that, the proposed method contributes to high classification accuracy and increases generalization performance for the classification of MI EEG. As the training set ratio decreases from 80 to 20%, the average classification accuracy on the two datasets changes from 85.86 and 86.13% to 84.81 and 76.59%, respectively. The classification performance and generalization of the proposed method contribute to the practical application of MI based BCI systems. PMID:29867307

Minimum Covers of Fixed Cardinality in Weighted Graphs.

ERIC Educational Resources Information Center

White, Lee J.

Reported is the result of research on combinatorial and algorithmic techniques for information processing. A method is discussed for obtaining minimum covers of specified cardinality from a given weighted graph. By the indicated method, it is shown that the family of minimum covers of varying cardinality is related to the minimum spanning tree of…

Method and Apparatus for Powered Descent Guidance

NASA Technical Reports Server (NTRS)

Acikmese, Behcet (Inventor); Blackmore, James C. L. (Inventor); Scharf, Daniel P. (Inventor)

2013-01-01

A method and apparatus for landing a spacecraft having thrusters with non-convex constraints is described. The method first computes a solution to a minimum error landing problem for a convexified constraints, then applies that solution to a minimum fuel landing problem for convexified constraints. The result is a solution that is a minimum error and minimum fuel solution that is also a feasible solution to the analogous system with non-convex thruster constraints.

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…

I am not "umqwayito'': a qualitative study of peer pressure and sexual risk behaviour among young adolescents in Cape Town, South Africa.

PubMed

Selikow, Terry-Ann; Ahmed, Nazeema; Flisher, Alan J; Mathews, Catherine; Mukoma, Wanjiru

2009-06-01

Young people in South Africa are susceptible to HIV infection. They are vulnerable to peer pressure to have sex, but little is known about how peer pressure operates. The aim of the study was to understand how negative peer pressure increases high risk sexual behaviour among young adolescents in Cape Town, South Africa. Qualitative research methods were used. Eight focus groups were conducted with young people between the ages of 13 and 14 years. Peer pressure among both boys and girls undermines healthy social norms and HIV prevention messages to abstain, be faithful, use a condom and delay sexual debut. HIV prevention projects need to engage with peer pressure with the aim of changing harmful social norms into healthy norms. Increased communication with adults about sex is one way to decrease the impact of negative peer pressure. Peer education is a further mechanism by which trained peers can role model healthy social norms and challenge a peer culture that promotes high risk sexual behaviour. Successful HIV prevention interventions need to engage with the disconnect between educational messages and social messages and to exploit the gaps between awareness, decision making, norms, intentions and actions as spaces for positive interventions.

Resource Balancing Control Allocation

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Bodson, Marc

2010-01-01

Next generation aircraft with a large number of actuators will require advanced control allocation methods to compute the actuator commands needed to follow desired trajectories while respecting system constraints. Previously, algorithms were proposed to minimize the l1 or l2 norms of the tracking error and of the control effort. The paper discusses the alternative choice of using the l1 norm for minimization of the tracking error and a normalized l(infinity) norm, or sup norm, for minimization of the control effort. The algorithm computes the norm of the actuator deflections scaled by the actuator limits. Minimization of the control effort then translates into the minimization of the maximum actuator deflection as a percentage of its range of motion. The paper shows how the problem can be solved effectively by converting it into a linear program and solving it using a simplex algorithm. Properties of the algorithm are investigated through examples. In particular, the min-max criterion results in a type of resource balancing, where the resources are the control surfaces and the algorithm balances these resources to achieve the desired command. A study of the sensitivity of the algorithms to the data is presented, which shows that the normalized l(infinity) algorithm has the lowest sensitivity, although high sensitivities are observed whenever the limits of performance are reached.

The dimensional salience solution to the expectancy-value muddle: an extension.

PubMed

Newton, Joshua D; Newton, Fiona J; Ewing, Michael T

2014-01-01

The theory of reasoned action (TRA) specifies a set of expectancy-value, belief-based frameworks that underpin attitude (behavioural beliefs × outcome evaluations) and subjective norm (normative beliefs × motivation to comply). Unfortunately, the most common method for analysing these frameworks generates statistically uninterpretable findings, resulting in what has been termed the 'expectancy-value muddle'. Recently, however, a dimensional salience approach was found to resolve this muddle for the belief-based framework underpinning attitude. An online survey of 262 participants was therefore conducted to determine whether the dimensional salience approach could also be applied to the belief-based framework underpinning subjective norm. Results revealed that motivations to comply were greater for salient, as opposed to non-salient, social referents. The belief-based framework underpinning subjective norm was therefore represented by evaluating normative belief ratings for salient social referents. This modified framework was found to predict subjective norm, although predictions were greater when participants were forced to select five salient social referents rather than being free to select any number of social referents. These findings validate the use of the dimensional salience approach for examining the belief-based frameworks underpinning subjective norm. As such, this approach provides a complete solution to addressing the expectancy-value muddle in the TRA.

“Brave Men” and “Emotional Women”: A Theory-Guided Literature Review on Gender Bias in Health Care and Gendered Norms towards Patients with Chronic Pain

PubMed Central

Gremyr, Ida; Eriksson, Erik; Hensing, Gunnel

2018-01-01

Background Despite the large body of research on sex differences in pain, there is a lack of knowledge about the influence of gender in the patient-provider encounter. The purpose of this study was to review literature on gendered norms about men and women with pain and gender bias in the treatment of pain. The second aim was to analyze the results guided by the theoretical concepts of hegemonic masculinity and andronormativity. Methods A literature search of databases was conducted. A total of 77 articles met the inclusion criteria. The included articles were analyzed qualitatively, with an integrative approach. Results The included studies demonstrated a variety of gendered norms about men's and women's experience and expression of pain, their identity, lifestyle, and coping style. Gender bias in pain treatment was identified, as part of the patient-provider encounter and the professional's treatment decisions. It was discussed how gendered norms are consolidated by hegemonic masculinity and andronormativity. Conclusions Awareness about gendered norms is important, both in research and clinical practice, in order to counteract gender bias in health care and to support health-care professionals in providing more equitable care that is more capable to meet the need of all patients, men and women. PMID:29682130

Modeling and Experimental Validation for 3D mm-wave Radar Imaging

NASA Astrophysics Data System (ADS)

Ghazi, Galia

As the problem of identifying suicide bombers wearing explosives concealed under clothing becomes increasingly important, it becomes essential to detect suspicious individuals at a distance. Systems which employ multiple sensors to determine the presence of explosives on people are being developed. Their functions include observing and following individuals with intelligent video, identifying explosives residues or heat signatures on the outer surface of their clothing, and characterizing explosives using penetrating X-rays, terahertz waves, neutron analysis, or nuclear quadrupole resonance. At present, mm-wave radar is the only modality that can both penetrate and sense beneath clothing at a distance of 2 to 50 meters without causing physical harm. Unfortunately, current mm-wave radar systems capable of performing high-resolution, real-time imaging require using arrays with a large number of transmitting and receiving modules; therefore, these systems present undesired large size, weight and power consumption, as well as extremely complex hardware architecture. The overarching goal of this thesis is the development and experimental validation of a next generation inexpensive, high-resolution radar system that can distinguish security threats hidden on individuals located at 2-10 meters range. In pursuit of this goal, this thesis proposes the following contributions: (1) Development and experimental validation of a new current-based, high-frequency computational method to model large scattering problems (hundreds of wavelengths) involving lossy, penetrable and multi-layered dielectric and conductive structures, which is needed for an accurate characterization of the wave-matter interaction and EM scattering in the target region; (2) Development of combined Norm-1, Norm-2 regularized imaging algorithms, which are needed for enhancing the resolution of the images while using a minimum number of transmitting and receiving antennas; (3) Implementation and experimental validation of new calibration techniques, which are needed for coherent imaging with multistatic configurations; and (4) Investigation of novel compressive antennas, which spatially modulate the wavefield in order to enhance the information transfer efficiency between sampling and imaging regions and use of Compressive Sensing algorithms.

The effect of interview method on self-reported sexual behavior and perceptions of community norms in Botswana.

PubMed

Anglewicz, Philip; Gourvenec, Diana; Halldorsdottir, Iris; O'Kane, Cate; Koketso, Obakeng; Gorgens, Marelize; Kasper, Toby

2013-02-01

Since self-reports of sensitive behaviors play an important role in HIV/AIDS research, the accuracy of these measures has often been examined. In this paper we (1) examine the effect of three survey interview methods on self-reported sexual behavior and perceptions of community sexual norms in Botswana, and (2) introduce an interview method to research on self-reported sexual behavior in sub-Saharan Africa. Comparing across these three survey methods (face-to-face, ballot box, and randomized response), we find that ballot box and randomized response surveys both provide higher reports of sensitive behaviors; the results for randomized response are particularly strong. Within these overall patterns, however, there is variation by question type; additionally the effect of interview method differs by sex. We also examine interviewer effects to gain insight into the effectiveness of these interview methods, and our results suggest that caution be used when interpreting the differences between survey methods.

The design of L1-norm visco-acoustic wavefield extrapolators

NASA Astrophysics Data System (ADS)

Salam, Syed Abdul; Mousa, Wail A.

2018-04-01

Explicit depth frequency-space (f - x) prestack imaging is an attractive mechanism for seismic imaging. To date, the main focus of this method was data migration assuming an acoustic medium, but until now very little work assumed visco-acoustic media. Real seismic data usually suffer from attenuation and dispersion effects. To compensate for attenuation in a visco-acoustic medium, new operators are required. We propose using the L1-norm minimization technique to design visco-acoustic f - x extrapolators. To show the accuracy and compensation of the operators, prestack depth migration is performed on the challenging Marmousi model for both acoustic and visco-acoustic datasets. The final migrated images show that the proposed L1-norm extrapolation results in practically stable and improved resolution of the images.

Sparsity-Aware DOA Estimation Scheme for Noncircular Source in MIMO Radar

PubMed Central

Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Qi; Liu, Jing

2016-01-01

In this paper, a novel sparsity-aware direction of arrival (DOA) estimation scheme for a noncircular source is proposed in multiple-input multiple-output (MIMO) radar. In the proposed method, the reduced-dimensional transformation technique is adopted to eliminate the redundant elements. Then, exploiting the noncircularity of signals, a joint sparsity-aware scheme based on the reweighted l1 norm penalty is formulated for DOA estimation, in which the diagonal elements of the weight matrix are the coefficients of the noncircular MUSIC-like (NC MUSIC-like) spectrum. Compared to the existing l1 norm penalty-based methods, the proposed scheme provides higher angular resolution and better DOA estimation performance. Results from numerical experiments are used to show the effectiveness of our proposed method. PMID:27089345

42 CFR 456.235 - Description of methods and criteria: Continued stay review dates; length of stay modification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... must describe— (a) The methods and criteria, including norms if used, that the committee uses to assign...) The methods that the committee uses to modify an approved length of stay when the recipient's...

A method for the complete analysis of NORM building materials by γ-ray spectrometry using HPGe detectors.

PubMed

Quintana, B; Pedrosa, M C; Vázquez-Canelas, L; Santamaría, R; Sanjuán, M A; Puertas, F

2018-04-01

A methodology including software tools for analysing NORM building materials and residues by low-level gamma-ray spectrometry has been developed. It comprises deconvolution of gamma-ray spectra using the software GALEA with focus on the natural radionuclides and Monte Carlo simulations for efficiency and true coincidence summing corrections. The methodology has been tested on a range of building materials and validated against reference materials. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy

PubMed Central

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system. PMID:27835638

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

PubMed

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning.

PubMed

Gorban, A N; Mirkes, E M; Zinovyev, A

2016-12-01

Most of machine learning approaches have stemmed from the application of minimizing the mean squared distance principle, based on the computationally efficient quadratic optimization methods. However, when faced with high-dimensional and noisy data, the quadratic error functionals demonstrated many weaknesses including high sensitivity to contaminating factors and dimensionality curse. Therefore, a lot of recent applications in machine learning exploited properties of non-quadratic error functionals based on L 1 norm or even sub-linear potentials corresponding to quasinorms L p (0

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

Eigenbeam analysis of the diversity in bat biosonar beampatterns.

PubMed

Caspers, Philip; Müller, Rolf

2015-03-01

A quantitative analysis of the interspecific variability in bat biosonar beampatterns has been carried out on 267 numerical predictions of emission and reception beampatterns from 98 different species. Since these beampatterns did not share a common orientation, an alignment was necessary to analyze the variability in the shape of the patterns. To achieve this, beampatterns were aligned using a pairwise optimization framework based on a rotation-dependent cost function. The sum of the p-norms between beam-gain functions across frequency served as a figure of merit. For a representative subset of the data, it was found that all pairwise beampattern alignments resulted in a unique global minimum. This minimum was found to be contained in a subset of all possible beampattern rotations that could be predicted by the overall beam orientation. Following alignment, the beampatterns were decomposed into principal components. The average beampattern consisted of a symmetric, positionally static single lobe that narrows and became progressively asymmetric with increasing frequency. The first three "eigenbeams" controlled the beam width of the beampattern across frequency while higher rank eigenbeams account for symmetry and lobe motion. Reception and emission beampatterns could be distinguished (85% correct classification) based on the first 14 eigenbeams.

Hessian-based norm regularization for image restoration with biomedical applications.

PubMed

Lefkimmiatis, Stamatios; Bourquard, Aurélien; Unser, Michael

2012-03-01

We present nonquadratic Hessian-based regularization methods that can be effectively used for image restoration problems in a variational framework. Motivated by the great success of the total-variation (TV) functional, we extend it to also include second-order differential operators. Specifically, we derive second-order regularizers that involve matrix norms of the Hessian operator. The definition of these functionals is based on an alternative interpretation of TV that relies on mixed norms of directional derivatives. We show that the resulting regularizers retain some of the most favorable properties of TV, i.e., convexity, homogeneity, rotation, and translation invariance, while dealing effectively with the staircase effect. We further develop an efficient minimization scheme for the corresponding objective functions. The proposed algorithm is of the iteratively reweighted least-square type and results from a majorization-minimization approach. It relies on a problem-specific preconditioned conjugate gradient method, which makes the overall minimization scheme very attractive since it can be applied effectively to large images in a reasonable computational time. We validate the overall proposed regularization framework through deblurring experiments under additive Gaussian noise on standard and biomedical images.

Fixed-Order Mixed Norm Designs for Building Vibration Control

NASA Technical Reports Server (NTRS)

Whorton, Mark S.; Calise, Anthony J.

2000-01-01

This study investigates the use of H2, mu-synthesis, and mixed H2/mu methods to construct full order controllers and optimized controllers of fixed dimensions. The benchmark problem definition is first extended to include uncertainty within the controller bandwidth in the form of parametric uncertainty representative of uncertainty in the natural frequencies of the design model. The sensitivity of H2 design to unmodeled dynamics and parametric uncertainty is evaluated for a range of controller levels of authority. Next, mu-synthesis methods are applied to design full order compensators that are robust to both unmodeled dynamics and to parametric uncertainty. Finally, a set of mixed H2/mu compensators are designed which are optimized for a fixed compensator dimension. These mixed norm designs recover the H2 design performance levels while providing the same levels of robust stability as the mu designs. It is shown that designing with the mixed norm approach permits higher levels of controller authority for which the H2 designs are destabilizing. The benchmark problem is that of an active tendon system. The controller designs are all based on the use of acceleration feedback.

Group Decision Making Based on Heronian Aggregation Operators of Intuitionistic Fuzzy Numbers.

PubMed

Liu, Peide; Chen, Shyi-Ming

2017-09-01

Archimedean t -conorm and t -norm provide the general operational rules for intuitionistic fuzzy numbers (IFNs). The aggregation operators based on them can generalize most of the existing aggregation operators. At the same time, the Heronian mean (HM) has a significant advantage of considering interrelationships between the attributes. Therefore, it is very necessary to extend the HM based on IFNs and to construct intuitionistic fuzzy HM operators based on the Archimedean t -conorm and t -norm. In this paper, we first discuss intuitionistic fuzzy operational rules based on the Archimedean t -conorm and t -norm. Then, we propose the intuitionistic fuzzy Archimedean Heronian aggregation (IFAHA) operator and the intuitionistic fuzzy weight Archimedean Heronian aggregation (IFWAHA) operator. We also further discuss some properties and some special cases of these new operators. Moreover, we also propose a new multiple attribute group decision making (MAGDM) method based on the proposed IFAHA operator and the proposed IFWAHA operator. Finally, we use an illustrative example to show the MAGDM processes and to illustrate the effectiveness of the developed method.

Branch and bound algorithm for accurate estimation of analytical isotropic bidirectional reflectance distribution function models.

PubMed

Yu, Chanki; Lee, Sang Wook

2016-05-20

We present a reliable and accurate global optimization framework for estimating parameters of isotropic analytical bidirectional reflectance distribution function (BRDF) models. This approach is based on a branch and bound strategy with linear programming and interval analysis. Conventional local optimization is often very inefficient for BRDF estimation since its fitting quality is highly dependent on initial guesses due to the nonlinearity of analytical BRDF models. The algorithm presented in this paper employs L₁-norm error minimization to estimate BRDF parameters in a globally optimal way and interval arithmetic to derive our feasibility problem and lower bounding function. Our method is developed for the Cook-Torrance model but with several normal distribution functions such as the Beckmann, Berry, and GGX functions. Experiments have been carried out to validate the presented method using 100 isotropic materials from the MERL BRDF database, and our experimental results demonstrate that the L₁-norm minimization provides a more accurate and reliable solution than the L₂-norm minimization.

Systematic approach to characterisation of NORM in Thailand.

PubMed

Chanyotha, S; Kranrod, C; Pengvanich, P

2015-11-01

The aim of this article is to provide information on the systematic approach that has been developed for the measurement of natural radiation exposure and the characterisation of naturally occurring radioactive materials (NORM) in terms of occurrence and distribution in various industrial processes, including the produced waste from the mineral industries in Thailand. The approach can be adapted for various types of study areas. The importance of collaboration among research institutions is discussed. Some developments include 25 documents; the redesign of the field equipment, such as the gamma survey meter, for convenient access to conduct measurement in various study areas; the method to collect and analyse radon gas from a natural gas pipeline and the manganese dioxide fibre to adsorb radium on-site for laboratory analysis. The NORM project in Thailand has been carried out for more than 10 y to support the development of NORM regulation in Thailand. In the previous studies as well as current, international standards for action levels have been adopted for safety purpose. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Smoothed low rank and sparse matrix recovery by iteratively reweighted least squares minimization.

PubMed

Lu, Canyi; Lin, Zhouchen; Yan, Shuicheng

2015-02-01

This paper presents a general framework for solving the low-rank and/or sparse matrix minimization problems, which may involve multiple nonsmooth terms. The iteratively reweighted least squares (IRLSs) method is a fast solver, which smooths the objective function and minimizes it by alternately updating the variables and their weights. However, the traditional IRLS can only solve a sparse only or low rank only minimization problem with squared loss or an affine constraint. This paper generalizes IRLS to solve joint/mixed low-rank and sparse minimization problems, which are essential formulations for many tasks. As a concrete example, we solve the Schatten-p norm and l2,q-norm regularized low-rank representation problem by IRLS, and theoretically prove that the derived solution is a stationary point (globally optimal if p,q ≥ 1). Our convergence proof of IRLS is more general than previous one that depends on the special properties of the Schatten-p norm and l2,q-norm. Extensive experiments on both synthetic and real data sets demonstrate that our IRLS is much more efficient.

Prepublication disclosure of scientific results: Norms, competition, and commercial orientation

PubMed Central

2018-01-01

On the basis of a survey of 7103 active faculty researchers in nine fields, we examine the extent to which scientists disclose prepublication results, and when they do, why? Except in two fields, more scientists disclose results before publication than not, but there is significant variation in their reasons to disclose, in the frequency of such disclosure, and in withholding crucial results when making public presentations. They disclose results for feedback and credit and to attract collaborators. Particularly in formulaic fields, scientists disclose to attract new researchers to the field independent of collaboration and to deter others from working on their exact problem. A probability model shows that 70% of field variation in disclosure is related to differences in respondent beliefs about norms, competition, and commercialization. Our results suggest new research directions—for example, do the problems addressed or the methods of scientific production themselves shape norms and competition? Are the levels we observe optimal or simply path-dependent? What is the interplay of norms, competition, and commercialization in disclosure and the progress of science? PMID:29774233

Mitigating nonlinearity in full waveform inversion using scaled-Sobolev pre-conditioning

NASA Astrophysics Data System (ADS)

Zuberi, M. AH; Pratt, R. G.

2018-04-01

The Born approximation successfully linearizes seismic full waveform inversion if the background velocity is sufficiently accurate. When the background velocity is not known it can be estimated by using model scale separation methods. A frequently used technique is to separate the spatial scales of the model according to the scattering angles present in the data, by using either first- or second-order terms in the Born series. For example, the well-known `banana-donut' and the `rabbit ear' shaped kernels are, respectively, the first- and second-order Born terms in which at least one of the scattering events is associated with a large angle. Whichever term of the Born series is used, all such methods suffer from errors in the starting velocity model because all terms in the Born series assume that the background Green's function is known. An alternative approach to Born-based scale separation is to work in the model domain, for example, by Gaussian smoothing of the update vectors, or some other approach for separation by model wavenumbers. However such model domain methods are usually based on a strict separation in which only the low-wavenumber updates are retained. This implies that the scattered information in the data is not taken into account. This can lead to the inversion being trapped in a false (local) minimum when sharp features are updated incorrectly. In this study we propose a scaled-Sobolev pre-conditioning (SSP) of the updates to achieve a constrained scale separation in the model domain. The SSP is obtained by introducing a scaled Sobolev inner product (SSIP) into the measure of the gradient of the objective function with respect to the model parameters. This modified measure seeks reductions in the L2 norm of the spatial derivatives of the gradient without changing the objective function. The SSP does not rely on the Born prediction of scale based on scattering angles, and requires negligible extra computational cost per iteration. Synthetic examples from the Marmousi model show that the constrained scale separation using SSP is able to keep the background updates in the zone of attraction of the global minimum, in spite of using a poor starting model in which conventional methods fail.

Improved sparse decomposition based on a smoothed L0 norm using a Laplacian kernel to select features from fMRI data.

PubMed

Zhang, Chuncheng; Song, Sutao; Wen, Xiaotong; Yao, Li; Long, Zhiying

2015-04-30

Feature selection plays an important role in improving the classification accuracy of multivariate classification techniques in the context of fMRI-based decoding due to the "few samples and large features" nature of functional magnetic resonance imaging (fMRI) data. Recently, several sparse representation methods have been applied to the voxel selection of fMRI data. Despite the low computational efficiency of the sparse representation methods, they still displayed promise for applications that select features from fMRI data. In this study, we proposed the Laplacian smoothed L0 norm (LSL0) approach for feature selection of fMRI data. Based on the fast sparse decomposition using smoothed L0 norm (SL0) (Mohimani, 2007), the LSL0 method used the Laplacian function to approximate the L0 norm of sources. Results of the simulated and real fMRI data demonstrated the feasibility and robustness of LSL0 for the sparse source estimation and feature selection. Simulated results indicated that LSL0 produced more accurate source estimation than SL0 at high noise levels. The classification accuracy using voxels that were selected by LSL0 was higher than that by SL0 in both simulated and real fMRI experiment. Moreover, both LSL0 and SL0 showed higher classification accuracy and required less time than ICA and t-test for the fMRI decoding. LSL0 outperformed SL0 in sparse source estimation at high noise level and in feature selection. Moreover, LSL0 and SL0 showed better performance than ICA and t-test for feature selection. Copyright © 2015 Elsevier B.V. All rights reserved.

Changes in Perceived Filial Obligation Norms Among Coresident Family Caregivers in Japan

PubMed Central

Tsutsui, Takako; Muramatsu, Naoko; Higashino, Sadanori

2014-01-01

Purpose of the Study: Japan introduced a nationwide long-term care insurance (LTCI) system in 2000, making long-term care (LTC) a right for older adults regardless of income and family availability. To shed light on its implications for family caregiving, we investigated perceived filial obligation norms among coresident primary family caregivers before and after the policy change. Design and Methods: Descriptive and multiple regression analyses were conducted to examine changes in perceived filial obligation norms and its subdimensions (financial, physical, and emotional support), using 2-wave panel survey data of coresident primary family caregivers (N = 611) in 1 city. The baseline survey was conducted in 1999, and a follow-up survey 2 years later. Results: On average, perceived filial obligation norms declined (p < .05). Daughters-in-law had the most significant declines (global and physical: p < .01, emotional: p < .05) among family caregivers. In particular, physical support, which Japan’s LTC reform targeted, declined significantly among daughters and daughters-in-law (p < .01). Multiple regression analysis indicated that daughters-in-law had significantly lower perceived filial obligation norms after the policy introduction than sons and daughters (p < .01 and p < .05, respectively), controlling for the baseline filial obligation and situational factors. Implications: Our research indicates declining roles of daughters-in-law in elder care during Japan’s LTCI system implementation period. Further international efforts are needed to design and implement longitudinal studies that help promote understanding of the interplay among national LTC policies, social changes, and caregiving norms and behaviors. PMID:24009170

Neighbourhood social capital as a moderator between individual cognitions and sports behaviour among Dutch adolescents.

PubMed

Prins, R G; Beenackers, M A; Boog, M C; Van Lenthe, F J; Brug, J; Oenema, A

2014-03-01

This study aimed to explore whether individual cognitions and neighbourhood social capital strengthen each other in their relation with engaging in sports at least three times per week. Cross-sectional analyses on data from the last wave of the YouRAction trial (2009-2010, Rotterdam, the Netherlands; baseline response: 98%) were conducted. In total 1129 had data on the last wave questionnaire (93%) and 832 of them had complete data on a self-administered questionnaire on frequency of sports participation, perceived neighbourhood social capital, cognitions (attitude, subjective norm, perceived behavioural control and intention toward sport participation) and demographics. Ecometric methods were used to aggregate perceived neighbourhood social capital to the neighbourhood level. Multilevel logistic regression analyses (neighbourhood and individual as levels) were conducted to examine associations of cognitions, neighbourhood social capital and the social capital by individual cognition interaction with fit norm compliance. If the interaction was significant, simple slopes analyses were conducted to decompose interaction effects. It was found that neighbourhood social capital was significantly associated with fit norm compliance (OR: 5.40; 95% CI: 1.13-25.74). Moreover, neighbourhood social capital moderated the association of attitude, perceived behavioural control and intention with fit norm compliance. The simple slope analyses visualized that the associations of cognitions with fit norm compliance were stronger in case of more neighbourhood social capital. Hence, higher levels of neighbourhood social capital strengthen the associations of attitude, perceived behavioural control and intention in their association with fit norm compliance. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Tensor completion for estimating missing values in visual data.

PubMed

Liu, Ji; Musialski, Przemyslaw; Wonka, Peter; Ye, Jieping

2013-01-01

In this paper, we propose an algorithm to estimate missing values in tensors of visual data. The values can be missing due to problems in the acquisition process or because the user manually identified unwanted outliers. Our algorithm works even with a small amount of samples and it can propagate structure to fill larger missing regions. Our methodology is built on recent studies about matrix completion using the matrix trace norm. The contribution of our paper is to extend the matrix case to the tensor case by proposing the first definition of the trace norm for tensors and then by building a working algorithm. First, we propose a definition for the tensor trace norm that generalizes the established definition of the matrix trace norm. Second, similarly to matrix completion, the tensor completion is formulated as a convex optimization problem. Unfortunately, the straightforward problem extension is significantly harder to solve than the matrix case because of the dependency among multiple constraints. To tackle this problem, we developed three algorithms: simple low rank tensor completion (SiLRTC), fast low rank tensor completion (FaLRTC), and high accuracy low rank tensor completion (HaLRTC). The SiLRTC algorithm is simple to implement and employs a relaxation technique to separate the dependent relationships and uses the block coordinate descent (BCD) method to achieve a globally optimal solution; the FaLRTC algorithm utilizes a smoothing scheme to transform the original nonsmooth problem into a smooth one and can be used to solve a general tensor trace norm minimization problem; the HaLRTC algorithm applies the alternating direction method of multipliers (ADMMs) to our problem. Our experiments show potential applications of our algorithms and the quantitative evaluation indicates that our methods are more accurate and robust than heuristic approaches. The efficiency comparison indicates that FaLTRC and HaLRTC are more efficient than SiLRTC and between FaLRTC an- HaLRTC the former is more efficient to obtain a low accuracy solution and the latter is preferred if a high-accuracy solution is desired.

26 CFR 1.412(c)(1)-3 - Applying the minimum funding requirements to restored plans.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 26 Internal Revenue 5 2013-04-01 2013-04-01 false Applying the minimum funding requirements to..., Stock Bonus Plans, Etc. § 1.412(c)(1)-3 Applying the minimum funding requirements to restored plans. (a) In general—(1) Restoration method. The restoration method is a funding method that adapts the...

Exploring L1 model space in search of conductivity bounds for the MT problem

NASA Astrophysics Data System (ADS)

Wheelock, B. D.; Parker, R. L.

2013-12-01

Geophysical inverse problems of the type encountered in electromagnetic techniques are highly non-unique. As a result, any single inverted model, though feasible, is at best inconclusive and at worst misleading. In this paper, we use modified inversion methods to establish bounds on electrical conductivity within a model of the earth. Our method consists of two steps, each making use of the 1-norm in model regularization. Both 1-norm minimization problems are framed without approximation as non-negative least-squares (NNLS) problems. First, we must identify a parsimonious set of regions within the model for which upper and lower bounds on average conductivity will be sought. This is accomplished by minimizing the 1-norm of spatial variation, which produces a model with a limited number of homogeneous regions; in fact, the number of homogeneous regions will never be greater than the number of data, regardless of the number of free parameters supplied. The second step establishes bounds for each of these regions with pairs of inversions. The new suite of inversions also uses a 1-norm penalty, but applied to the conductivity values themselves, rather than the spatial variation thereof. In the bounding step we use the 1-norm of our model parameters because it is proportional to average conductivity. For a lower bound on average conductivity, the 1-norm within a bounding region is minimized. For an upper bound on average conductivity, the 1-norm everywhere outside a bounding region is minimized. The latter minimization has the effect of concentrating conductance into the bounding region. Taken together, these bounds are a measure of the uncertainty in the associated region of our model. Starting with a blocky inverse solution is key in the selection of the bounding regions. Of course, there is a tradeoff between resolution and uncertainty: an increase in resolution (smaller bounding regions), results in greater uncertainty (wider bounds). Minimization of the 1-norm of spatial variation delivers the fewest possible regions defined by a mean conductivity, the quantity we wish to bound. Thus, these regions present a natural set for which the most narrow and discriminating bounds can be found. For illustration, we apply these techniques to synthetic magnetotelluric (MT) data sets resulting from one-dimensional (1D) earth models. In each case we find that with realistic data coverage, any single inverted model can often stray from the truth, while the computed bounds on an encompassing region contain both the inverted and the true conductivities, indicating that our measure of model uncertainty is robust. Such estimates of uncertainty for conductivity can then be translated to bounds on important petrological parameters such as mineralogy, porosity, saturation, and fluid type.

Adaptive low-rank subspace learning with online optimization for robust visual tracking.

PubMed

Liu, Risheng; Wang, Di; Han, Yuzhuo; Fan, Xin; Luo, Zhongxuan

2017-04-01

In recent years, sparse and low-rank models have been widely used to formulate appearance subspace for visual tracking. However, most existing methods only consider the sparsity or low-rankness of the coefficients, which is not sufficient enough for appearance subspace learning on complex video sequences. Moreover, as both the low-rank and the column sparse measures are tightly related to all the samples in the sequences, it is challenging to incrementally solve optimization problems with both nuclear norm and column sparse norm on sequentially obtained video data. To address above limitations, this paper develops a novel low-rank subspace learning with adaptive penalization (LSAP) framework for subspace based robust visual tracking. Different from previous work, which often simply decomposes observations as low-rank features and sparse errors, LSAP simultaneously learns the subspace basis, low-rank coefficients and column sparse errors to formulate appearance subspace. Within LSAP framework, we introduce a Hadamard production based regularization to incorporate rich generative/discriminative structure constraints to adaptively penalize the coefficients for subspace learning. It is shown that such adaptive penalization can significantly improve the robustness of LSAP on severely corrupted dataset. To utilize LSAP for online visual tracking, we also develop an efficient incremental optimization scheme for nuclear norm and column sparse norm minimizations. Experiments on 50 challenging video sequences demonstrate that our tracker outperforms other state-of-the-art methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Documenting Collective Development in Online Settings

ERIC Educational Resources Information Center

Dean, Chrystal; Silverman, Jason

2015-01-01

In this paper the authors explored the question of collective understanding in online mathematics education settings and presented a brief overview of traditional methods for documenting norms and collective mathematical practices. A method for documenting collective development was proposed that builds on existing methods and frameworks yet is…

Thematic relatedness production norms for 100 object concepts.

PubMed

Jouravlev, Olessia; McRae, Ken

2016-12-01

Knowledge of thematic relations is an area of increased interest in semantic memory research because it is crucial to many cognitive processes. One methodological issue that researchers face is how to identify pairs of thematically related concepts that are well-established in semantic memory for most people. In this article, we review existing methods of assessing thematic relatedness and provide thematic relatedness production norming data for 100 object concepts. In addition, 1,174 related concept pairs obtained from the production norms were classified as reflecting one of the five subtypes of relations: attributive, argument, coordinate, locative, and temporal. The database and methodology will be useful for researchers interested in the effects of thematic knowledge on language processing, analogical reasoning, similarity judgments, and memory. These data will also benefit researchers interested in investigating potential processing differences among the five types of semantic relations.

NanoStringNormCNV: pre-processing of NanoString CNV data.

PubMed

Sendorek, Dorota H; Lalonde, Emilie; Yao, Cindy Q; Sabelnykova, Veronica Y; Bristow, Robert G; Boutros, Paul C

2018-03-15

The NanoString System is a well-established technology for measuring RNA and DNA abundance. Although it can estimate copy number variation, relatively few tools support analysis of these data. To address this gap, we created NanoStringNormCNV, an R package for pre-processing and copy number variant calling from NanoString data. This package implements algorithms for pre-processing, quality-control, normalization and copy number variation detection. A series of reporting and data visualization methods support exploratory analyses. To demonstrate its utility, we apply it to a new dataset of 96 genes profiled on 41 prostate tumour and 24 matched normal samples. NanoStringNormCNV is implemented in R and is freely available at http://labs.oicr.on.ca/boutros-lab/software/nanostringnormcnv. paul.boutros@oicr.on.ca. Supplementary data are available at Bioinformatics online.

Eleven Years of Data on the Jefferson Scale of Empathy-Medical Student Version (JSE-S): Proxy Norm Data and Tentative Cutoff Scores

PubMed Central

Hojat, Mohammadreza; Gonnella, Joseph S.

2015-01-01

Objective This study was designed to provide typical descriptive statistics, score distributions and percentile ranks of the Jefferson Scale of Empathy-Medical Student version (JSE-S) of male and female medical school matriculants to serve as proxy norm data and tentative cutoff scores. Subjects and Methods The participants were 2,637 students (1,336 women and 1,301 men) who matriculated at Sidney Kimmel (formerly Jefferson) Medical College between 2002 and 2012, and completed the JSE at the beginning of medical school. Information extracted from descriptive statistics, score distributions and percentile ranks for male and female matriculants were used to develop proxy norm data and tentative cutoff scores. Results The score distributions of the JSE tended to be moderately skewed and platykurtic. Women obtained a significantly higher mean score (116.2 ± 9.7) than men (112.3 ± 10.8) on the JSE-S (t2,635 = 9.9, p < 0.01). It was suggested that percentile ranks can be used as proxy norm data. The tentative cutoff score to identify low scorers was ≤95 for men and ≤100 for women. Conclusions Our findings provide norm data and cutoff scores for admission decisions under certain conditions and for identifying students in need of enhancing their empathy. PMID:25924560

Preliminary demonstration of a robust controller design method

NASA Technical Reports Server (NTRS)

Anderson, L. R.

1980-01-01

Alternative computational procedures for obtaining a feedback control law which yields a control signal based on measurable quantitites are evaluated. The three methods evaluated are: (1) the standard linear quadratic regulator design model; (2) minimization of the norm of the feedback matrix, k via nonlinear programming subject to the constraint that the closed loop eigenvalues be in a specified domain in the complex plane; and (3) maximize the angles between the closed loop eigenvectors in combination with minimizing the norm of K also via the constrained nonlinear programming. The third or robust design method was chosen to yield a closed loop system whose eigenvalues are insensitive to small changes in the A and B matrices. The relationship between orthogonality of closed loop eigenvectors and the sensitivity of closed loop eigenvalues is described. Computer programs are described.

MUSQA: a CS method to build a multi-standard quality management system

NASA Astrophysics Data System (ADS)

Cros, Elizabeth; Sneed, Isabelle

2002-07-01

CS Communication & Systèmes, through its long quality management experience, has been able to build and evolve its Quality Management System according to clients requirements, norms, standards and models (ISO, DO178, ECSS, CMM, ...), evolving norms (transition from ISO 9001:1994 to ISO 9001:2000) and the TQM approach, being currently deployed. The aim of this paper is to show how, from this enriching and instructive experience, CS has defined and formalised its method: MuSQA (Multi-Standard Quality Approach). This method allows to built a new Quality Management System or simplify and unify an existing one. MuSQA objective is to provide any organisation with an open Quality Management System, which is able to evolve easily and turns to be a useful instrument for everyone, operational as well as non-operational staff.

[Selection of reference genes of Siraitia grosvenorii by real-time PCR].

PubMed

Tu, Dong-ping; Mo, Chang-ming; Ma, Xiao-jun; Zhao, Huan; Tang, Qi; Huang, Jie; Pan, Li-mei; Wei, Rong-chang

2015-01-01

Siraitia grosvenorii is a traditional Chinese medicine also as edible food. This study selected six candidate reference genes by real-time quantitative PCR, the expression stability of the candidate reference genes in the different samples was analyzed by using the software and methods of geNorm, NormFinder, BestKeeper, Delta CT method and RefFinder, reference genes for S. grosvenorii were selected for the first time. The results showed that 18SrRNA expressed most stable in all samples, was the best reference gene in the genetic analysis. The study has a guiding role for the analysis of gene expression using qRT-PCR methods, providing a suitable reference genes to ensure the results in the study on differential expressed gene in synthesis and biological pathways, also other genes of S. grosvenorii.

26 CFR 1.412(c)(1)-3T - Applying the minimum funding requirements to restored plans (temporary).

Code of Federal Regulations, 2013 CFR

2013-04-01

... 26 Internal Revenue 5 2013-04-01 2013-04-01 false Applying the minimum funding requirements to...-Sharing, Stock Bonus Plans, Etc. § 1.412(c)(1)-3T Applying the minimum funding requirements to restored plans (temporary). (a) In general—(1) Restoration method. The restoration method is a funding method...

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

SU-F-18C-14: Hessian-Based Norm Penalty for Weighted Least-Square CBCT Reconstruction

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

Sun, T; Sun, N; Tan, S

Purpose: To develop a Hessian-based norm penalty for cone-beam CT (CBCT) reconstruction that has a similar ability in suppressing noise as the total variation (TV) penalty while avoiding the staircase effect and better preserving low-contrast objects. Methods: We extended the TV penalty to a Hessian-based norm penalty based on the Frobenius norm of the Hessian matrix of an image for CBCT reconstruction. The objective function was constructed using the penalized weighted least-square (PWLS) principle. An effective algorithm was developed to minimize the objective function using a majorization-minimization (MM) approach. We evaluated and compared the proposed penalty with the TV penaltymore » on a CatPhan 600 phantom and an anthropomorphic head phantom, each acquired at a low-dose protocol (10mA/10ms) and a high-dose protocol (80mA/12ms). For both penalties, contrast-to-noise (CNR) in four low-contrast regions-of-interest (ROIs) and the full-width-at-half-maximum (FWHM) of two point-like objects in constructed images were calculated and compared. Results: In the experiment of CatPhan 600 phantom, the Hessian-based norm penalty has slightly higher CNRs and approximately equivalent FWHM values compared with the TV penalty. In the experiment of the anthropomorphic head phantom at the low-dose protocol, the TV penalty result has several artificial piece-wise constant areas known as the staircase effect while in the Hessian-based norm penalty the image appears smoother and more similar to that of the FDK result using the high-dose protocol. Conclusion: The proposed Hessian-based norm penalty has a similar performance in suppressing noise to the TV penalty, but has a potential advantage in suppressing the staircase effect and preserving low-contrast objects. This work was supported in part by National Natural Science Foundation of China (NNSFC), under Grant Nos. 60971112 and 61375018, and Fundamental Research Funds for the Central Universities, under Grant No. 2012QN086.« less

Are social norms associated with smoking in French university students? A survey report on smoking correlates

PubMed Central

Riou França, Lionel; Dautzenberg, Bertrand; Falissard, Bruno; Reynaud, Michel

2009-01-01

Background Knowledge of the correlates of smoking is a first step to successful prevention interventions. The social norms theory hypothesises that students' smoking behaviour is linked to their perception of norms for use of tobacco. This study was designed to test the theory that smoking is associated with perceived norms, controlling for other correlates of smoking. Methods In a pencil-and-paper questionnaire, 721 second-year students in sociology, medicine, foreign language or nursing studies estimated the number of cigarettes usually smoked in a month. 31 additional covariates were included as potential predictors of tobacco use. Multiple imputation was used to deal with missing values among covariates. The strength of the association of each variable with tobacco use was quantified by the inclusion frequencies of the variable in 1000 bootstrap sample backward selections. Being a smoker and the number of cigarettes smoked by smokers were modelled separately. Results We retain 8 variables to predict the risk of smoking and 6 to predict the quantities smoked by smokers. The risk of being a smoker is increased by cannabis use, binge drinking, being unsupportive of smoke-free universities, perceived friends' approval of regular smoking, positive perceptions about tobacco, a high perceived prevalence of smoking among friends, reporting not being disturbed by people smoking in the university, and being female. The quantity of cigarettes smoked by smokers is greater for smokers reporting never being disturbed by smoke in the university, unsupportive of smoke-free universities, perceiving that their friends approve of regular smoking, having more negative beliefs about the tobacco industry, being sociology students and being among the older students. Conclusion Other substance use, injunctive norms (friends' approval) and descriptive norms (friends' smoking prevalence) are associated with tobacco use. University-based prevention campaigns should take multiple substance use into account and focus on the norms most likely to have an impact on student smoking. PMID:19341453

A New Linearized Crank-Nicolson Mixed Element Scheme for the Extended Fisher-Kolmogorov Equation

PubMed Central

Wang, Jinfeng; Li, Hong; He, Siriguleng; Gao, Wei

2013-01-01

We present a new mixed finite element method for solving the extended Fisher-Kolmogorov (EFK) equation. We first decompose the EFK equation as the two second-order equations, then deal with a second-order equation employing finite element method, and handle the other second-order equation using a new mixed finite element method. In the new mixed finite element method, the gradient ∇u belongs to the weaker (L 2(Ω))2 space taking the place of the classical H(div; Ω) space. We prove some a priori bounds for the solution for semidiscrete scheme and derive a fully discrete mixed scheme based on a linearized Crank-Nicolson method. At the same time, we get the optimal a priori error estimates in L 2 and H 1-norm for both the scalar unknown u and the diffusion term w = −Δu and a priori error estimates in (L 2)2-norm for its gradient χ = ∇u for both semi-discrete and fully discrete schemes. PMID:23864831

A new linearized Crank-Nicolson mixed element scheme for the extended Fisher-Kolmogorov equation.

PubMed

Wang, Jinfeng; Li, Hong; He, Siriguleng; Gao, Wei; Liu, Yang

2013-01-01

We present a new mixed finite element method for solving the extended Fisher-Kolmogorov (EFK) equation. We first decompose the EFK equation as the two second-order equations, then deal with a second-order equation employing finite element method, and handle the other second-order equation using a new mixed finite element method. In the new mixed finite element method, the gradient ∇u belongs to the weaker (L²(Ω))² space taking the place of the classical H(div; Ω) space. We prove some a priori bounds for the solution for semidiscrete scheme and derive a fully discrete mixed scheme based on a linearized Crank-Nicolson method. At the same time, we get the optimal a priori error estimates in L² and H¹-norm for both the scalar unknown u and the diffusion term w = -Δu and a priori error estimates in (L²)²-norm for its gradient χ = ∇u for both semi-discrete and fully discrete schemes.

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.

Muslim women's narratives about bodily change and care during critical illness: a qualitative study.

PubMed

Zeilani, Ruqayya; Seymour, Jane E

2012-03-01

To explore experiences of Jordanian Muslim women in relation to bodily change during critical illness. A longitudinal narrative approach was used. A purposive sample of 16 Jordanian women who had spent a minimum of 48 hr in intensive care participated in one to three interviews over a 6-month period. Three main categories emerged from the analysis: the dependent body reflects changes in the women's bodily strength and performance, as they moved from being care providers into those in need of care; this was associated with experiences of a sense of paralysis, shame, and burden. The social body reflects the essential contribution that family help or nurses' support (as a proxy for family) made to women's adjustment to bodily change and their ability to make sense of their illness. The cultural body reflects the effect of cultural norms and Islamic beliefs on the women's interpretation of their experiences and relates to the women's understandings of bodily modesty. This study illustrates, by in-depth focus on Muslim women's narratives, the complex interrelationship between religious beliefs, cultural norms, and the experiences and meanings of bodily changes during critical illness. This article provides insights into vital aspects of Muslim women's needs and preferences for nursing care. It highlights the importance of including an assessment of culture and spiritual aspects when nursing critically ill patients. © 2011 Sigma Theta Tau International.

Effects of vocal training on singing and speaking voice characteristics in vocally healthy adults and children based on choral and nonchoral data.

PubMed

Siupsinskiene, Nora; Lycke, Hugo

2011-07-01

This prospective cross-sectional study examines the effects of voice training on vocal capabilities in vocally healthy age and gender differentiated groups measured by voice range profile (VRP) and speech range profile (SRP). Frequency and intensity measurements of the VRP and SRP using standard singing and speaking voice protocols were derived from 161 trained choir singers (21 males, 59 females, and 81 prepubescent children) and from 188 nonsingers (38 males, 89 females, and 61 children). When compared with nonsingers, both genders of trained adult and child singers exhibited increased mean pitch range, highest frequency, and VRP area in high frequencies (P<0.05). Female singers and child singers also showed significantly increased mean maximum voice intensity, intensity range, and total VRP area. The logistic regression analysis showed that VRP pitch range, highest frequency, maximum voice intensity, and maximum-minimum intensity range, and SRP slope of speaking curve were the key predictors of voice training. Age, gender, and voice training differentiated norms of VRP and SRP parameters are presented. Significant positive effect of voice training on vocal capabilities, mostly singing voice, was confirmed. The presented norms for trained singers, with key parameters differentiated by gender and age, are suggested for clinical practice of otolaryngologists and speech-language pathologists. Copyright © 2011 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Mapping visual stimuli to perceptual decisions via sparse decoding of mesoscopic neural activity.

PubMed

Sajda, Paul

2010-01-01

In this talk I will describe our work investigating sparse decoding of neural activity, given a realistic mapping of the visual scene to neuronal spike trains generated by a model of primary visual cortex (V1). We use a linear decoder which imposes sparsity via an L1 norm. The decoder can be viewed as a decoding neuron (linear summation followed by a sigmoidal nonlinearity) in which there are relatively few non-zero synaptic weights. We find: (1) the best decoding performance is for a representation that is sparse in both space and time, (2) decoding of a temporal code results in better performance than a rate code and is also a better fit to the psychophysical data, (3) the number of neurons required for decoding increases monotonically as signal-to-noise in the stimulus decreases, with as little as 1% of the neurons required for decoding at the highest signal-to-noise levels, and (4) sparse decoding results in a more accurate decoding of the stimulus and is a better fit to psychophysical performance than a distributed decoding, for example one imposed by an L2 norm. We conclude that sparse coding is well-justified from a decoding perspective in that it results in a minimum number of neurons and maximum accuracy when sparse representations can be decoded from the neural dynamics.

Fast and Adaptive Sparse Precision Matrix Estimation in High Dimensions

PubMed Central

Liu, Weidong; Luo, Xi

2014-01-01

This paper proposes a new method for estimating sparse precision matrices in the high dimensional setting. It has been popular to study fast computation and adaptive procedures for this problem. We propose a novel approach, called Sparse Column-wise Inverse Operator, to address these two issues. We analyze an adaptive procedure based on cross validation, and establish its convergence rate under the Frobenius norm. The convergence rates under other matrix norms are also established. This method also enjoys the advantage of fast computation for large-scale problems, via a coordinate descent algorithm. Numerical merits are illustrated using both simulated and real datasets. In particular, it performs favorably on an HIV brain tissue dataset and an ADHD resting-state fMRI dataset. PMID:25750463

Time-stable overset grid method for hyperbolic problems using summation-by-parts operators

NASA Astrophysics Data System (ADS)

Sharan, Nek; Pantano, Carlos; Bodony, Daniel J.

2018-05-01

A provably time-stable method for solving hyperbolic partial differential equations arising in fluid dynamics on overset grids is presented in this paper. The method uses interface treatments based on the simultaneous approximation term (SAT) penalty method and derivative approximations that satisfy the summation-by-parts (SBP) property. Time-stability is proven using energy arguments in a norm that naturally relaxes to the standard diagonal norm when the overlap reduces to a traditional multiblock arrangement. The proposed overset interface closures are time-stable for arbitrary overlap arrangements. The information between grids is transferred using Lagrangian interpolation applied to the incoming characteristics, although other interpolation schemes could also be used. The conservation properties of the method are analyzed. Several one-, two-, and three-dimensional, linear and non-linear numerical examples are presented to confirm the stability and accuracy of the method. A performance comparison between the proposed SAT-based interface treatment and the commonly-used approach of injecting the interpolated data onto each grid is performed to highlight the efficacy of the SAT method.

Association between physician supply, local practice norms, and outpatient visit rates

PubMed Central

Yasaitis, Laura C.; Bynum, Julie P.W.; Skinner, Jonathan S.

2013-01-01

Background There is considerable regional variation in Medicare outpatient visit rates; such variations may be the consequence of patient health, race/ethnicity differences, patient preferences, or physician supply and beliefs about the efficacy of frequently scheduled visits. Objective To test associations between varying regional Medicare outpatient visit rates and beneficiaries’ health, race/ethnicity, preferences, and physician practice norms and supply. Methods We used Medicare claims from 2006 and 2007, and data from national surveys of three different groups in 2005 – Medicare beneficiaries, cardiologists, and primary care physicians. Regression analysis tested explanations for outpatient visit rates: patient health (self-reported and hierarchical condition category (HCC) score), self-reported race/ethnicity, preferences for care, and local physician practice norms and supply in beneficiaries’ Hospital Referral Regions (HRRs) of residence. Results Beneficiaries in the highest quintile of HCC scores experienced 4.99 more visits than those in the lowest. Beneficiaries who were black experienced 2.14 fewer visits than others with similar health and preferences. Higher care-seeking preferences were marginally significantly associated with more visits, while education and poverty were insignificant. HRRs with high physician supply and high frequency practice norms were associated with 2.04 additional visits per year, while HRRs with high supply but low frequency norms were associated with 1.45 additional visits. Adjusting for all individual beneficiary covariates explained less than 20% of the original associations between visit rates and physician supply and practice norms. Conclusion Medicare beneficiaries’ health status, race, and preferences help explain individual office visit frequency; in particular, African-American patients appear to experience lower access to care. Yet, these factors explain a small fraction of the observed regional differences associated with physician supply and beliefs about the appropriate frequency of office visits. PMID:23666491

Household Debt and Relation to Intimate Partner Violence and Husbands' Attitudes Toward Gender Norms: A Study Among Young Married Couples in Rural Maharashtra, India

PubMed Central

Donta, Balaiah; Dasgupta, Anindita; Ghule, Mohan; Battala, Madhusudana; Nair, Saritha; Silverman, Jay G.; Jadhav, Arun; Palaye, Prajakta; Saggurti, Niranjan; Raj, Anita

2015-01-01

Objective Evidence has linked economic hardship with increased intimate partner violence (IPV) perpetration among males. However, less is known about how economic debt or gender norms related to men's roles in relationships or the household, which often underlie IPV perpetration, intersect in or may explain these associations. We assessed the intersection of economic debt, attitudes toward gender norms, and IPV perpetration among married men in India. Methods Data were from the evaluation of a family planning intervention among young married couples (n=1,081) in rural Maharashtra, India. Crude and adjusted logistic regression models for dichotomous outcome variables and linear regression models for continuous outcomes were used to examine debt in relation to husbands' attitudes toward gender-based norms (i.e., beliefs supporting IPV and beliefs regarding male dominance in relationships and the household), as well as sexual and physical IPV perpetration. Results Twenty percent of husbands reported debt. In adjusted linear regression models, debt was associated with husbands' attitudes supportive of IPV (b=0.015, p=0.004) and norms supporting male dominance in relationships and the household (b=0.006, p=0.003). In logistic regression models adjusted for relevant demographics, debt was associated with perpetration of physical IPV (adjusted odds ratio [AOR] = 1.4, 95% confidence interval [CI] 1.1, 1.9) and sexual IPV (AOR=1.6, 95% CI 1.1, 2.1) from husbands. These findings related to debt and relation to IPV were slightly attenuated when further adjusted for men's attitudes toward gender norms. Conclusion Findings suggest the need for combined gender equity and economic promotion interventions to address high levels of debt and related IPV reported among married couples in rural India. PMID:26556938

Parent and Grandparent Marijuana Use and Child Substance Use and Norms

PubMed Central

Bailey, Jennifer A.; Hill, Karl G.; Guttmannova, Katarina; Epstein, Marina; Abbott, Robert D.; Steeger, Christine M.; Skinner, Martie L.

2016-01-01

Purpose Using prospective longitudinal data from 3 generations, this study seeks to test whether and how parent and grandparent marijuana use (current and prior) predicts an increased likelihood of child cigarette, alcohol, and marijuana use. Methods Using multilevel modeling of prospective data spanning 3 generations (N = 306 families, children ages 6-22), this study tested associations between grandparent (G1) and parent (G2) marijuana use and child (G3) past-year cigarette, alcohol, and marijuana use. Analyses tested whether G3 substance-related norms mediated these associations. Current G1 and G2 marijuana use was examined, as was G2 high school and early adult use and G1 marijuana use when G2 parents were in early adolescence. Controls included G2 age at G3 birth, G2 education and depression, and G3 gender. Results G2 current marijuana use predicted a higher likelihood of G3 alcohol and marijuana use, but was not related to the probability of G3 cigarette use. G3's perceptions of their parents' norms and G2 current marijuana use both contributed independently to the likelihood of G3 alcohol and marijuana use when included in the same model. G3 children's own norms and their perceptions of friends' norms mediated the link between G2 current marijuana use and G3 alcohol and marijuana use. Conclusions Results are discussed in light of the growing trend toward marijuana legalization. To the extent that parent marijuana use increases under legalization, we can expect more youth to use alcohol and marijuana and to have norms that favor substance use. PMID:27265424

What can we talk about, in which language, in what way and with whom? Sami patients' experiences of language choice and cultural norms in mental health treatment

PubMed Central

Dagsvold, Inger; Møllersen, Snefrid; Stordahl, Vigdis

2015-01-01

Background The Sami in Norway have a legal right to receive health services adapted to Sami language and culture. This calls for a study of the significance of language choice and cultural norms in Sami patients’ encounters with mental health services. Objectives To explore the significance of language and cultural norms in communication about mental health topics experienced by Sami patients receiving mental health treatment to enhance our understanding of linguistic and cultural adaptation of health services. Methods Data were collected through individual interviews with 4 Sami patients receiving mental health treatment in Northern Norway. A systematic text reduction and a thematic analysis were employed. Findings Two themes were identified: (I) Language choice is influenced by language competence, with whom one talks and what one talks about. Bilingualism was a resource and natural part of the participants’ lives, but there were limited possibilities to speak Sami in encounters with health services. A professional working relationship was placed on an equal footing with the possibility to speak Sami. (II) Cultural norms influence what one talks about, in what way and to whom. However, norms could be bypassed, by talking about norm-regulated topics in Norwegian with health providers. Conclusion Sami patients’ language choice in different communication situations is influenced by a complexity of social and cultural factors. Sami patients have varying opinions about and preferences for what they can talk about, in which language, in what way and with whom. Bilingualism and knowledge about both Sami and Norwegian culture provide latitude and enhanced possibilities for both patients and the health services. The challenge for the health services is to allow for and safeguard such individual variations within the cultural framework of the patients. PMID:25976741

Clinical value of the VMI supplemental tests: a modified replication study.

PubMed

Avi-Itzhak, Tamara; Obler, Doris Richard

2008-10-01

To carry out a modified replication of the study performed by Kulp and Sortor evaluating the clinical value of the information provided by Beery's visual-motor supplemental tests of Visual Perception (VP) and Motor Coordination (MC) in normally developed children. The objectives were to (a) estimate the correlations among the three tests scores; (b) assess the predictive power of the VP and MC scores in explaining the variance in Visual-Motor Integration (VMI) scores; and (c) examine whether poor performance on the VMI is related to poor performance on VP or MC. METHODS.: A convenience sample of 71 children ages 4 and 5 years (M = 4.62 +/- 0.43) participated in the study. The supplemental tests significantly (F = 9.59; dF = 2; p < or = 0. 001) explained 22% of the variance in VMI performance. Only VP was significantly related to VMI (beta = 0.39; T = 3.49) accounting for the total amount of explained variance. Using the study population norms, 11 children (16% of total sample) did poorly on the VMI; of those 11, 73% did poorly on the VP, and none did poorly on the MC. None of these 11 did poorly on both the VP and MC. Nine percent of total sample who did poorly on the VP performed within the norm on the VMI. Thirteen percent who performed poorly on the MC performed within the norm on the VMI. Using the VMI published norms, 14 children (20% of total sample) who did poorly on the VP performed within the norm on the VMI. Forty-eight percent who did poorly on MC performed within the norm on the VMI. Findings supported Kulp and Sortor's conclusions that each area should be individually evaluated during visual-perceptual assessment of children regardless of performance on the VMI.

An exploratory cluster randomised trial of a university halls of residence based social norms marketing campaign to reduce alcohol consumption among 1st year students

PubMed Central

2013-01-01

Aims This exploratory trial examines the feasibility of implementing a social norms marketing campaign to reduce student drinking in universities in Wales, and evaluating it using cluster randomised trial methodology. Methods Fifty residence halls in 4 universities in Wales were randomly assigned to intervention or control arms. Web and paper surveys were distributed to students within these halls (n = 3800), assessing exposure/contamination, recall of and evaluative responses to intervention messages, perceived drinking norms and personal drinking behaviour. Measures included the Drinking Norms Rating Form, the Daily Drinking Questionnaire and AUDIT-C. Results A response rate of 15% (n = 554) was achieved, varying substantially between sites. Intervention posters were seen by 80% and 43% of students in intervention and control halls respectively, with most remaining materials seen by a minority in both groups. Intervention messages were rated as credible and relevant by little more than half of students, though fewer felt they would influence their behaviour, with lighter drinkers more likely to perceive messages as credible. No differences in perceived norms were observed between intervention and control groups. Students reporting having seen intervention materials reported lower descriptive and injunctive norms than those who did not. Conclusions Attention is needed to enhancing exposure, credibility and perceived relevance of intervention messages, particularly among heavier drinkers, before definitive evaluation can be recommended. A definitive evaluation would need to consider how it would achieve sufficient response rates, whilst hall-level cluster randomisation appears subject to a significant degree of contamination. Trial registration ISRCTN: ISRCTN48556384 PMID:23594918

Reliable change indices and standardized regression-based change score norms for evaluating neuropsychological change in children with epilepsy.

PubMed

Busch, Robyn M; Lineweaver, Tara T; Ferguson, Lisa; Haut, Jennifer S

2015-06-01

Reliable change indices (RCIs) and standardized regression-based (SRB) change score norms permit evaluation of meaningful changes in test scores following treatment interventions, like epilepsy surgery, while accounting for test-retest reliability, practice effects, score fluctuations due to error, and relevant clinical and demographic factors. Although these methods are frequently used to assess cognitive change after epilepsy surgery in adults, they have not been widely applied to examine cognitive change in children with epilepsy. The goal of the current study was to develop RCIs and SRB change score norms for use in children with epilepsy. Sixty-three children with epilepsy (age range: 6-16; M=10.19, SD=2.58) underwent comprehensive neuropsychological evaluations at two time points an average of 12 months apart. Practice effect-adjusted RCIs and SRB change score norms were calculated for all cognitive measures in the battery. Practice effects were quite variable across the neuropsychological measures, with the greatest differences observed among older children, particularly on the Children's Memory Scale and Wisconsin Card Sorting Test. There was also notable variability in test-retest reliabilities across measures in the battery, with coefficients ranging from 0.14 to 0.92. Reliable change indices and SRB change score norms for use in assessing meaningful cognitive change in children following epilepsy surgery are provided for measures with reliability coefficients above 0.50. This is the first study to provide RCIs and SRB change score norms for a comprehensive neuropsychological battery based on a large sample of children with epilepsy. Tables to aid in evaluating cognitive changes in children who have undergone epilepsy surgery are provided for clinical use. An Excel sheet to perform all relevant calculations is also available to interested clinicians or researchers. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

NASA Astrophysics Data System (ADS)

Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

2018-06-01

Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be extended to any subsequent brain connectivity analyses used to construct the associated dynamic brain networks.

WEAK GALERKIN METHODS FOR SECOND ORDER ELLIPTIC INTERFACE PROBLEMS

PubMed Central

MU, LIN; WANG, JUNPING; WEI, GUOWEI; YE, XIU; ZHAO, SHAN

2013-01-01

Weak Galerkin methods refer to general finite element methods for partial differential equations (PDEs) in which differential operators are approximated by their weak forms as distributions. Such weak forms give rise to desirable flexibilities in enforcing boundary and interface conditions. A weak Galerkin finite element method (WG-FEM) is developed in this paper for solving elliptic PDEs with discontinuous coefficients and interfaces. Theoretically, it is proved that high order numerical schemes can be designed by using the WG-FEM with polynomials of high order on each element. Extensive numerical experiments have been carried to validate the WG-FEM for solving second order elliptic interface problems. High order of convergence is numerically confirmed in both L2 and L∞ norms for the piecewise linear WG-FEM. Special attention is paid to solve many interface problems, in which the solution possesses a certain singularity due to the nonsmoothness of the interface. A challenge in research is to design nearly second order numerical methods that work well for problems with low regularity in the solution. The best known numerical scheme in the literature is of order O(h) to O(h1.5) for the solution itself in L∞ norm. It is demonstrated that the WG-FEM of the lowest order, i.e., the piecewise constant WG-FEM, is capable of delivering numerical approximations that are of order O(h1.75) to O(h2) in the L∞ norm for C1 or Lipschitz continuous interfaces associated with a C1 or H2 continuous solution. PMID:24072935

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.

Reconstructing the duty of water: a study of emergent norms in socio-hydrology

NASA Astrophysics Data System (ADS)

Wescoat, J. L., Jr.

2013-12-01

This paper assesses the changing norms of water use known as the duty of water. It is a case study in historical socio-hydrology, or more precisely the history of socio-hydrologic ideas, a line of research that is useful for interpreting and anticipating changing social values with respect to water. The duty of water is currently defined as the amount of water reasonably required to irrigate a substantial crop with careful management and without waste on a given tract of land. The historical section of the paper traces this concept back to late 18th century analysis of steam engine efficiencies for mine dewatering in Britain. A half-century later, British irrigation engineers fundamentally altered the concept of duty to plan large-scale canal irrigation systems in northern India at an average duty of 218 acres per cubic foot per second (cfs). They justified this extensive irrigation standard (i.e., low water application rate over large areas) with a suite of social values that linked famine prevention with revenue generation and territorial control. The duty of water concept in this context articulated a form of political power, as did related irrigation engineering concepts such as "command" and "regime". Several decades later irrigation engineers in the western US adapted the duty of water concept to a different socio-hydrologic system and norms, using it to establish minimum standards for private water rights appropriation (e.g., only 40 to 80 acres per cfs). While both concepts of duty addressed socio-economic values associated with irrigation, the western US linked duty with justifications for, and limits of, water ownership. The final sections show that while the duty of water concept has been eclipsed in practice by other measures, standards, and values of water use efficiency, it has continuing relevance for examining ethical duties and for anticipating, if not predicting, emerging social values with respect to water.

Estimating Effects with Rare Outcomes and High Dimensional Covariates: Knowledge is Power

PubMed Central

Ahern, Jennifer; Galea, Sandro; van der Laan, Mark

2016-01-01

Many of the secondary outcomes in observational studies and randomized trials are rare. Methods for estimating causal effects and associations with rare outcomes, however, are limited, and this represents a missed opportunity for investigation. In this article, we construct a new targeted minimum loss-based estimator (TMLE) for the effect or association of an exposure on a rare outcome. We focus on the causal risk difference and statistical models incorporating bounds on the conditional mean of the outcome, given the exposure and measured confounders. By construction, the proposed estimator constrains the predicted outcomes to respect this model knowledge. Theoretically, this bounding provides stability and power to estimate the exposure effect. In finite sample simulations, the proposed estimator performed as well, if not better, than alternative estimators, including a propensity score matching estimator, inverse probability of treatment weighted (IPTW) estimator, augmented-IPTW and the standard TMLE algorithm. The new estimator yielded consistent estimates if either the conditional mean outcome or the propensity score was consistently estimated. As a substitution estimator, TMLE guaranteed the point estimates were within the parameter range. We applied the estimator to investigate the association between permissive neighborhood drunkenness norms and alcohol use disorder. Our results highlight the potential for double robust, semiparametric efficient estimation with rare events and high dimensional covariates. PMID:28529839

42 CFR 456.134 - Description of methods and criteria: Subsequent continued stay review dates; length of stay...

Code of Federal Regulations, 2010 CFR

2010-10-01

... modification. The UR plan must describe— (a) The methods and criteria, including norms if used, that the... the committee uses to modify an approved length of stay when the recipient's condition or treatment...

Multivariable frequency domain identification via 2-norm minimization

NASA Technical Reports Server (NTRS)

Bayard, David S.

1992-01-01

The author develops a computational approach to multivariable frequency domain identification, based on 2-norm minimization. In particular, a Gauss-Newton (GN) iteration is developed to minimize the 2-norm of the error between frequency domain data and a matrix fraction transfer function estimate. To improve the global performance of the optimization algorithm, the GN iteration is initialized using the solution to a particular sequentially reweighted least squares problem, denoted as the SK iteration. The least squares problems which arise from both the SK and GN iterations are shown to involve sparse matrices with identical block structure. A sparse matrix QR factorization method is developed to exploit the special block structure, and to efficiently compute the least squares solution. A numerical example involving the identification of a multiple-input multiple-output (MIMO) plant having 286 unknown parameters is given to illustrate the effectiveness of the algorithm.

Social Influences on Use of Cigarettes, E-Cigarettes, and Hookah by College Students

PubMed Central

Noland, Melody; Ickes, Melinda. J.; Rayens, Mary Kay; Butler, Karen; Wiggins, Amanda T.; Hahn, Ellen J.

2016-01-01

Objectives (1) Compare social norms and perceived peer use between college student cigarette, e-cigarette and/or hookah users and nonusers; and (2) Determine variables associated with social influences. Participants Undergraduate students attending a large university in the Southeast U.S. (N=511). Methods An April 2013 online survey assessed use of three types of tobacco, social norms, perception of peer use, number of smokers in life, exposure to secondhand smoke, and demographic characteristics. Results Participants indicated greater acceptance of emerging tobacco products than for cigarettes and consistently overestimated the percent of peers who use various tobacco products. Males and current users had higher social norm scores for all three forms of tobacco. Conclusion To counter marketing of alternative tobacco products, education about the dangers of their use needs to be implemented across college campuses as part of a comprehensive tobacco control strategy that also includes tobacco-free campus policies. PMID:26822236

Talking about health: correction employees' assessments of obstacles to healthy living.

PubMed

Morse, Tim; Dussetschleger, Jeffrey; Warren, Nicholas; Cherniack, Martin

2011-09-01

Describe health risks/obstacles to health among correctional employees. Mixed-methods approach combined results from four focus groups, 10 interviews, 335 surveys, and 197 physical assessments. Obesity levels were higher than national averages (40.7% overweight and 43.3% obese), with higher levels associated with job tenure, male gender, and working off-shift. Despite widespread concern about the lack of fitness, leisure exercise was higher than national norms. Respondents had higher levels of hypertension than national norms, with 31% of men and 25.8% of women hypertensive compared with 17.1% and 15.1% for national norms. Stress levels were elevated. Officers related their stress to concerns about security, administrative requirements, and work/family imbalance. High stress levels are reflected in elevated levels of hypertension. Correctional employees are at high risk for chronic disease, and environmental changes are needed to reduce risk factors. (C)2011The American College of Occupational and Environmental Medicine

[The influence of hepatoprotector 2-ethylthiobenzimidazole hydrobromide (bemithyl) on the content of glycogen in cirrhotic rat liver hepatocytes located in various microenvironments].

PubMed

Kudriavtseva, M V; Bezborodkina, N N; Okovityĭ, S V; Kudriavtsev, B N

2004-01-01

Using absorption and fluorescent cytophotometry methods, glycogen contents were studied in hepatocytes located in liver lobules and in hepatocytes, which make the general population of these cells in normal and cirrhotic rat liver. In cirrhosis, the content of glycogen in hepatocytes located in lobules obviously rises in comparison with the norm, but to a lesser degree, than in hepatocytes making the general population of these cells in cirrhotic liver. The content of glycogen in hepatocytes, located in lobules of pathologically changed liver in bemithyl treated rats, did not differ from the norm. At the same time, the glycogen content in hepatocytes, representing the general population of these cells in cirrhotically altered bemithyl injected rat liver, remained higher than in the norm. The data obtained indicate that distinctions in particular cell microinvironment, obviously present in cirrhotic liver, render essential influence on hepatocyte functional activity.

A Study of Fixed-Order Mixed Norm Designs for a Benchmark Problem in Structural Control

NASA Technical Reports Server (NTRS)

Whorton, Mark S.; Calise, Anthony J.; Hsu, C. C.

1998-01-01

This study investigates the use of H2, p-synthesis, and mixed H2/mu methods to construct full-order controllers and optimized controllers of fixed dimensions. The benchmark problem definition is first extended to include uncertainty within the controller bandwidth in the form of parametric uncertainty representative of uncertainty in the natural frequencies of the design model. The sensitivity of H2 design to unmodelled dynamics and parametric uncertainty is evaluated for a range of controller levels of authority. Next, mu-synthesis methods are applied to design full-order compensators that are robust to both unmodelled dynamics and to parametric uncertainty. Finally, a set of mixed H2/mu compensators are designed which are optimized for a fixed compensator dimension. These mixed norm designs recover the H, design performance levels while providing the same levels of robust stability as the u designs. It is shown that designing with the mixed norm approach permits higher levels of controller authority for which the H, designs are destabilizing. The benchmark problem is that of an active tendon system. The controller designs are all based on the use of acceleration feedback.

The Aspects About of Objectively Appraisals of Modeling Gypsum Quality and Composites of Phonic-Absorbent and Orthopedic on Base of Gypsum

NASA Astrophysics Data System (ADS)

Pop, P. A.; Ungur, P. A.; Lazar, L.; Marcu, F.

2009-11-01

The EU Norms about of protection environment, outside and inside ambient, and human health demands has lead at obtain of new materials on the base of airborne material, with high thermo and phonic-absorbent properties, porous and lightweight. The α and β-modeling gypsum plaster quality and lightweight depend on many factors as: fabrication process, granulation, roast temperature, work temperature, environment, additives used, breakage, etc. Also, the objectively appraisal of modeling gypsum quality depends of proper tests methods selection, which are legislated in norms, standards and recommendations. In Romanian Standards SR EN 13279-1/2005 and SR EN 13279-2/2005, adaptable from EU Norms EN 13279-1/2004 and EN 13279-2/2004, the characteristics gypsum family tests are well specification, as: granule-metric analysis, determination of water/plaster ratio, setting time, mechanical characteristics, adhesions and water restrain. For plaster with special use (phonic-absorbent and orthopedic materials, etc.) these determinations are not concluding, being necessary more parameters finding, as: elastic constant, phonic-absorbent coefficient, porosity, working, etc., which is imposed the completion of norms and standards with new determinations.

Visual body size norms and the under‐detection of overweight and obesity

PubMed Central

Robinson, E.

2017-01-01

Summary Objectives The weight status of men with overweight and obesity tends to be visually underestimated, but visual recognition of female overweight and obesity has not been formally examined. The aims of the present studies were to test whether people can accurately recognize both male and female overweight and obesity and to examine a visual norm‐based explanation for why weight status is underestimated. Methods The present studies examine whether both male and female overweight and obesity are visually underestimated (Study 1), whether body size norms predict when underestimation of weight status occurs (Study 2) and whether visual exposure to heavier body weights adjusts visual body size norms and results in underestimation of weight status (Study 3). Results The weight status of men and women with overweight and obesity was consistently visually underestimated (Study 1). Body size norms predicted underestimation of weight status (Study 2) and in part explained why visual exposure to heavier body weights caused underestimation of overweight (Study 3). Conclusions The under‐detection of overweight and obesity may have been in part caused by exposure to larger body sizes resulting in an upwards shift in the range of body sizes that are perceived as being visually ‘normal’. PMID:29479462

Autoregressive model in the Lp norm space for EEG analysis.

PubMed

Li, Peiyang; Wang, Xurui; Li, Fali; Zhang, Rui; Ma, Teng; Peng, Yueheng; Lei, Xu; Tian, Yin; Guo, Daqing; Liu, Tiejun; Yao, Dezhong; Xu, Peng

2015-01-30

The autoregressive (AR) model is widely used in electroencephalogram (EEG) analyses such as waveform fitting, spectrum estimation, and system identification. In real applications, EEGs are inevitably contaminated with unexpected outlier artifacts, and this must be overcome. However, most of the current AR models are based on the L2 norm structure, which exaggerates the outlier effect due to the square property of the L2 norm. In this paper, a novel AR object function is constructed in the Lp (p≤1) norm space with the aim to compress the outlier effects on EEG analysis, and a fast iteration procedure is developed to solve this new AR model. The quantitative evaluation using simulated EEGs with outliers proves that the proposed Lp (p≤1) AR can estimate the AR parameters more robustly than the Yule-Walker, Burg and LS methods, under various simulated outlier conditions. The actual application to the resting EEG recording with ocular artifacts also demonstrates that Lp (p≤1) AR can effectively address the outliers and recover a resting EEG power spectrum that is more consistent with its physiological basis. Copyright © 2014 Elsevier B.V. All rights reserved.

Legislating Change? Responses to Criminalizing Female Genital Cutting in Senegal

PubMed Central

Shell-Duncan, Bettina; Hernlund, Ylva; Wander, Katherine; Moreau, Amadou

2014-01-01

Although the international community has recently promoted legislation as an important reform strategy for ending female genital cutting (FGC), there exist divergent views on its potential effects. Supporters argue that legal prohibition of FGC has a general deterrent effect, while others argue legislation can be perceived as coercive, and derail local efforts to end the practice. This study examines the range of responses observed in rural Senegal, where a 1999 anti-FGC law was imposed on communities in which the practice was being actively contested and targeted for elimination. Drawing on data from a mixed-methods study, we analyze responses in relation to two leading theories on social regulation, the law and economics and law and society paradigms, which make divergent predictions on the interplay between social norms and legal norms. Among supporters of FGC, legal norms ran counter to social norms, and did little to deter the practice, and in some instances incited reactance or drove the practice underground. Conversely, where FGC was being contested, legislation served to strengthen the stance of those contemplating or favoring abandonment. We conclude that legislation can complement other reform strategies by creating an “enabling environment” that supports those who have or wish to abandon FGC. PMID:24771947

Poisson image reconstruction with Hessian Schatten-norm regularization.

PubMed

Lefkimmiatis, Stamatios; Unser, Michael

2013-11-01

Poisson inverse problems arise in many modern imaging applications, including biomedical and astronomical ones. The main challenge is to obtain an estimate of the underlying image from a set of measurements degraded by a linear operator and further corrupted by Poisson noise. In this paper, we propose an efficient framework for Poisson image reconstruction, under a regularization approach, which depends on matrix-valued regularization operators. In particular, the employed regularizers involve the Hessian as the regularization operator and Schatten matrix norms as the potential functions. For the solution of the problem, we propose two optimization algorithms that are specifically tailored to the Poisson nature of the noise. These algorithms are based on an augmented-Lagrangian formulation of the problem and correspond to two variants of the alternating direction method of multipliers. Further, we derive a link that relates the proximal map of an l(p) norm with the proximal map of a Schatten matrix norm of order p. This link plays a key role in the development of one of the proposed algorithms. Finally, we provide experimental results on natural and biological images for the task of Poisson image deblurring and demonstrate the practical relevance and effectiveness of the proposed framework.

Nurses' intentions to provide continuous labor support to women.

PubMed

Payant, Laura; Davies, Barbara; Graham, Ian D; Peterson, Wendy E; Clinch, Jennifer

2008-01-01

To examine the determinants of nurses' intentions to practice continuous labor support. A descriptive survey based on the Theory of Planned Behavior. A large, urban Canadian hospital with 2 sites and 7,000 births per year. Ninety-seven registered nurses from 2 birthing units. Scores measuring nurses' attitudes, subjective norms, and intentions regarding continuous labor support for women with epidural analgesia were significantly lower than those for women without epidural analgesia (p<.0001). Multiple regression analyses revealed that previous labor support courses, subjective norms, and perceived behavioral control explained 55% of the variance in nurses' intentions to provide continuous labor support to women without epidural analgesia while 88% of the variance in intentions to provide continuous labor support to women with epidural analgesia was explained by subjective norms and attitudes. Subjective norms made the most significant contribution to the variance in nurses' intentions to provide continuous labor support. Top perceived organizational barriers to continuous labor support included unit acuity and method of patient assignment. Nurses' intentions to provide continuous labor support are lower for women receiving epidural analgesia and are influenced by the perceived social pressures on their unit. Nurses view organizational barriers as important factors influencing their ability to provide continuous labor support.

IFSM fractal image compression with entropy and sparsity constraints: A sequential quadratic programming approach

NASA Astrophysics Data System (ADS)

Kunze, Herb; La Torre, Davide; Lin, Jianyi

2017-01-01

We consider the inverse problem associated with IFSM: Given a target function f , find an IFSM, such that its fixed point f ¯ is sufficiently close to f in the Lp distance. Forte and Vrscay [1] showed how to reduce this problem to a quadratic optimization model. In this paper, we extend the collage-based method developed by Kunze, La Torre and Vrscay ([2][3][4]), by proposing the minimization of the 1-norm instead of the 0-norm. In fact, optimization problems involving the 0-norm are combinatorial in nature, and hence in general NP-hard. To overcome these difficulties, we introduce the 1-norm and propose a Sequential Quadratic Programming algorithm to solve the corresponding inverse problem. As in Kunze, La Torre and Vrscay [3] in our formulation, the minimization of collage error is treated as a multi-criteria problem that includes three different and conflicting criteria i.e., collage error, entropy and sparsity. This multi-criteria program is solved by means of a scalarization technique which reduces the model to a single-criterion program by combining all objective functions with different trade-off weights. The results of some numerical computations are presented.

Examining the Unique Influence of Interpersonal and Intrapersonal Drinking Perceptions on Alcohol Consumption Among College Students*

PubMed Central

Mallett, Kimberly A.; Bachrach, Rachel L.; Turrisi, Rob

2009-01-01

Objective: Interventions for college student drinking often incorporate interpersonal factors such as descriptive and/or injunctive norms to correct misperceptions about campus drinking (e.g., BASICS [Brief Alcohol Screening and Intervention for College Students] and social-norms campaigns). Some interventions also focus on intra-personal factors of alcohol consumption, which can be considered as one's own perception of drinking, one's attitude toward drinking, and one's intended outcome related to drinking. The current study sought to extend previous work by examining relationships between both inter- and intrapersonal perceptions of drinking and reported drinking behavior. Method: College students (N = 303) completed questionnaires assessing drinking behaviors, perceptions of other students' attitudes toward drinking (i.e., injunctive norms), their perception of the quantity and frequency of student/friend drinking (i.e., descriptive norms), and their attitudes and perceptions toward their own alcohol consumption (i.e., intrapersonal factors). Results: Multiple regressions were used to analyze the unique influence between inter- and intrapersonal drinking perceptions and drinking behavior. Conclusions: Among the interpersonal perceptions of drinking, only closest friend's drinking significantly predicted alcohol consumption, whereas all three intrapersonal factors significantly predicted alcohol consumption. Suggestions for enhancing college student drinking interventions are discussed. PMID:19261229

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…

Neural source dynamics of brain responses to continuous stimuli: Speech processing from acoustics to comprehension.

PubMed

Brodbeck, Christian; Presacco, Alessandro; Simon, Jonathan Z

2018-05-15

Human experience often involves continuous sensory information that unfolds over time. This is true in particular for speech comprehension, where continuous acoustic signals are processed over seconds or even minutes. We show that brain responses to such continuous stimuli can be investigated in detail, for magnetoencephalography (MEG) data, by combining linear kernel estimation with minimum norm source localization. Previous research has shown that the requirement to average data over many trials can be overcome by modeling the brain response as a linear convolution of the stimulus and a kernel, or response function, and estimating a kernel that predicts the response from the stimulus. However, such analysis has been typically restricted to sensor space. Here we demonstrate that this analysis can also be performed in neural source space. We first computed distributed minimum norm current source estimates for continuous MEG recordings, and then computed response functions for the current estimate at each source element, using the boosting algorithm with cross-validation. Permutation tests can then assess the significance of individual predictor variables, as well as features of the corresponding spatio-temporal response functions. We demonstrate the viability of this technique by computing spatio-temporal response functions for speech stimuli, using predictor variables reflecting acoustic, lexical and semantic processing. Results indicate that processes related to comprehension of continuous speech can be differentiated anatomically as well as temporally: acoustic information engaged auditory cortex at short latencies, followed by responses over the central sulcus and inferior frontal gyrus, possibly related to somatosensory/motor cortex involvement in speech perception; lexical frequency was associated with a left-lateralized response in auditory cortex and subsequent bilateral frontal activity; and semantic composition was associated with bilateral temporal and frontal brain activity. We conclude that this technique can be used to study the neural processing of continuous stimuli in time and anatomical space with the millisecond temporal resolution of MEG. This suggests new avenues for analyzing neural processing of naturalistic stimuli, without the necessity of averaging over artificially short or truncated stimuli. Copyright © 2018 Elsevier Inc. All rights reserved.

Protecting the fair trial rights of mentally disordered defendants in criminal proceedings: Exploring the need for further EU action.

PubMed

Verbeke, Peter; Vermeulen, Gert; Meysman, Michaël; Vander Beken, Tom

2015-01-01

Using the new legal basis provided by the Lisbon Treaty, the Council of the European Union has endorsed the 2009 Procedural Roadmap for strengthening the procedural rights of suspected or accused persons in criminal proceedings. This Roadmap has so far resulted in six measures from which specific procedural minimum standards have been and will be adopted or negotiated. So far, only Measure E directly touches on the specific issue of vulnerable persons. This Measure has recently produced a tentative result through a Commission Recommendation on procedural safeguards for vulnerable persons in criminal proceedings. This contribution aims to discuss the need for the introduction of binding minimum standards throughout Europe to provide additional protection for mentally disordered defendants. The paper will examine whether or not the member states adhere to existing fundamental norms and standards in this context, and whether the application of these norms and standards should be made more uniform. For this purpose, the procedural situation of mentally disordered defendants in Belgium and England and Wales will be thoroughly explored. The research establishes that Belgian law is unsatisfactory in the light of the Strasbourg case law, and that the situation in practice in England and Wales indicates not only that there is justifiable doubt about whether fundamental principles are always adhered to, but also that these principles should become more anchored in everyday practice. It will therefore be argued that there is a need for putting Measure E into practice. The Commission Recommendation, though only suggestive, may serve as a necessary and inspirational vehicle to improve the procedural rights of mentally disordered defendants and to ensure that member states are able to cooperate within the mutual recognition framework without being challenged on the grounds that they are collaborating with peers who do not respect defendants' fundamental fair trial rights. Throughout this contribution the term 'defendant' will be used, and no difference will be made in terminology between suspected and accused persons. This contribution only covers the situation of mentally disordered adult defendants. Copyright © 2015 Elsevier Ltd. All rights reserved.

A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives.

PubMed

Algamal, Z Y; Lee, M H

2017-01-01

A high-dimensional quantitative structure-activity relationship (QSAR) classification model typically contains a large number of irrelevant and redundant descriptors. In this paper, a new design of descriptor selection for the QSAR classification model estimation method is proposed by adding a new weight inside L1-norm. The experimental results of classifying the anti-hepatitis C virus activity of thiourea derivatives demonstrate that the proposed descriptor selection method in the QSAR classification model performs effectively and competitively compared with other existing penalized methods in terms of classification performance on both the training and the testing datasets. Moreover, it is noteworthy that the results obtained in terms of stability test and applicability domain provide a robust QSAR classification model. It is evident from the results that the developed QSAR classification model could conceivably be employed for further high-dimensional QSAR classification studies.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

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.

A unified framework for penalized statistical muon tomography reconstruction with edge preservation priors of lp norm type

NASA Astrophysics Data System (ADS)

Yu, Baihui; Zhao, Ziran; Wang, Xuewu; Wu, Dufan; Zeng, Zhi; Zeng, Ming; Wang, Yi; Cheng, Jianping

2016-01-01

The Tsinghua University MUon Tomography facilitY (TUMUTY) has been built up and it is utilized to reconstruct the special objects with complex structure. Since fine image is required, the conventional Maximum likelihood Scattering and Displacement (MLSD) algorithm is employed. However, due to the statistical characteristics of muon tomography and the data incompleteness, the reconstruction is always instable and accompanied with severe noise. In this paper, we proposed a Maximum a Posterior (MAP) algorithm for muon tomography regularization, where an edge-preserving prior on the scattering density image is introduced to the object function. The prior takes the lp norm (p>0) of the image gradient magnitude, where p=1 and p=2 are the well-known total-variation (TV) and Gaussian prior respectively. The optimization transfer principle is utilized to minimize the object function in a unified framework. At each iteration the problem is transferred to solving a cubic equation through paraboloidal surrogating. To validate the method, the French Test Object (FTO) is imaged by both numerical simulation and TUMUTY. The proposed algorithm is used for the reconstruction where different norms are detailedly studied, including l2, l1, l0.5, and an l2-0.5 mixture norm. Compared with MLSD method, MAP achieves better image quality in both structure preservation and noise reduction. Furthermore, compared with the previous work where one dimensional image was acquired, we achieve the relatively clear three dimensional images of FTO, where the inner air hole and the tungsten shell is visible.

ESEA Title I Linking Project. Final Report.

ERIC Educational Resources Information Center

Holmes, Susan E.

The Rasch model for test score equating was compared with three other equating procedures as methods for implementing the norm referenced method (RMC Model A) of evaluating ESEA Title I projects. The Rasch model and its theoretical limitations were described. The three other equating methods used were: linear observed score equating, linear true…

A modified sparse reconstruction method for three-dimensional synthetic aperture radar image

NASA Astrophysics Data System (ADS)

Zhang, Ziqiang; Ji, Kefeng; Song, Haibo; Zou, Huanxin

2018-03-01

There is an increasing interest in three-dimensional Synthetic Aperture Radar (3-D SAR) imaging from observed sparse scattering data. However, the existing 3-D sparse imaging method requires large computing times and storage capacity. In this paper, we propose a modified method for the sparse 3-D SAR imaging. The method processes the collection of noisy SAR measurements, usually collected over nonlinear flight paths, and outputs 3-D SAR imagery. Firstly, the 3-D sparse reconstruction problem is transformed into a series of 2-D slices reconstruction problem by range compression. Then the slices are reconstructed by the modified SL0 (smoothed l0 norm) reconstruction algorithm. The improved algorithm uses hyperbolic tangent function instead of the Gaussian function to approximate the l0 norm and uses the Newton direction instead of the steepest descent direction, which can speed up the convergence rate of the SL0 algorithm. Finally, numerical simulation results are given to demonstrate the effectiveness of the proposed algorithm. It is shown that our method, compared with existing 3-D sparse imaging method, performs better in reconstruction quality and the reconstruction time.

Using a Descriptive Social Norm to Increase Vegetable Selection in Workplace Restaurant Settings

PubMed Central

2017-01-01

Objective: Recent work has shown that exposure to social norm messages may enhance the consumption of vegetables. However, the majority of this work has been conducted in laboratories, often with student populations. Little is known about whether this approach can be successfully used in other contexts. In this study, a poster featuring a message based on social norms was tested to examine whether it could increase and maintain the purchase of meals with vegetables in workplace restaurants. Method: A pretest–posttest design with 3 phases was used in 3 workplace restaurants in the United Kingdom. The first 2 weeks formed the preintervention phase, the second 2 weeks the intervention phase, and the last 2 weeks the postintervention phase. During the intervention phase only, posters containing a social norm message relaying information about vegetable purchases of other diners were placed in each restaurant. The main outcome measure was the percentage of meals purchased with vegetables, which was analyzed using Pearson’s chi-squared test. Results: Participants were judged to be male (57%), not overweight (75%), and under the age of 60 (98%). The intervention was positively associated with the percentage of meals purchased with vegetables: baseline versus intervention (60% vs. 64% of meals purchased with vegetables; p < .01); intervention versus postintervention (64% vs. 67% of meals purchased with vegetables; p < .01); and baseline versus postintervention (60% vs. 67% of meals purchased with vegetables; p < .001). Conclusions: Social norm messages may increase the purchase of vegetables in workplace settings. PMID:28541071

Determinants of Fast Food Consumption among Iranian High School Students Based on Planned Behavior Theory

PubMed Central

Sharifirad, Gholamreza; Yarmohammadi, Parastoo; Azadbakht, Leila; Morowatisharifabad, Mohammad Ali; Hassanzadeh, Akbar

2013-01-01

Objective. This study was conducted to identify some factors (beliefs and norms) which are related to fast food consumption among high school students in Isfahan, Iran. We used the framework of the theory planned behavior (TPB) to predict this behavior. Subjects & Methods. Cross-sectional data were available from high school students (n = 521) who were recruited by cluster randomized sampling. All of the students completed a questionnaire assessing variables of standard TPB model including attitude, subjective norms, perceived behavior control (PBC), and the additional variables past behavior, actual behavior control (ABC). Results. The TPB variables explained 25.7% of the variance in intentions with positive attitude as the strongest (β = 0.31, P < 0.001) and subjective norms as the weakest (β = 0.29, P < 0.001) determinant. Concurrently, intentions accounted for 6% of the variance for fast food consumption. Past behavior and ABC accounted for an additional amount of 20.4% of the variance in fast food consumption. Conclusion. Overall, the present study suggests that the TPB model is useful in predicting related beliefs and norms to the fast food consumption among adolescents. Subjective norms in TPB model and past behavior in TPB model with additional variables (past behavior and actual behavior control) were the most powerful predictors of fast food consumption. Therefore, TPB model may be a useful framework for planning intervention programs to reduce fast food consumption by students. PMID:23936635

Social learning theory and the effects of living arrangement on heavy alcohol use: results from a national study of college students.

PubMed

Ward, Brian W; Gryczynski, Jan

2009-05-01

This study examined the relationship between living arrangement and heavy episodic drinking among college students in the United States. Using social learning theory as a framework, it was hypothesized that vicarious learning of peer and family alcohol-use norms would mediate the effects of living arrangement on heavy episodic drinking. Analyses were conducted using data from the 2001 Harvard School of Public Health College Alcohol Study, a national survey of full-time undergraduate students attending 4-year colleges or universities in the United States (N = 10,008). Logistic regression models examined the relationship between heavy episodic drinking and various measures of living arrangement and vicarious learning/social norms. Mediation of the effects of living arrangement was tested using both indirect and direct methods. Both student living arrangement and vicarious-learning/social-norm variables remained significant predictors of heavy episodic drinking in multivariate models when controlling for a variety of individual characteristics. Slight mediation of the effects of living arrangement on heavy episodic drinking by vicarious learning/social norms was confirmed for some measures. Although vicarious learning of social norms does appear to play a role in the association between living arrangement and alcohol use, other processes may underlie the relationship. These findings suggest that using theory alongside empirical evidence to inform the manipulation of living environments could present a promising policy strategy to reduce alcohol-related harm in collegiate contexts.

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.

14 CFR 25.149 - Minimum control speed.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Minimum control speed. 25.149 Section 25... Minimum control speed. (a) In establishing the minimum control speeds required by this section, the method... prevent a heading change of more than 20 degrees. (e) VMCG, the minimum control speed on the ground, is...

14 CFR 25.149 - Minimum control speed.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Minimum control speed. 25.149 Section 25... Minimum control speed. (a) In establishing the minimum control speeds required by this section, the method... prevent a heading change of more than 20 degrees. (e) VMCG, the minimum control speed on the ground, is...

75 FR 38770 - El Dorado County Resource Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-06

... criteria for project proposals, and establish methods for soliciting project proposals. DATES: The meeting... norms and operating guidelines, learn about successful RACs, discuss criteria for project proposals and establish methods for soliciting proposals. More information will be posted on the Eldorado National Forest...

Method of Menu Selection by Gaze Movement Using AC EOG Signals

NASA Astrophysics Data System (ADS)

Kanoh, Shin'ichiro; Futami, Ryoko; Yoshinobu, Tatsuo; Hoshimiya, Nozomu

A method to detect the direction and the distance of voluntary eye gaze movement from EOG (electrooculogram) signals was proposed and tested. In this method, AC-amplified vertical and horizontal transient EOG signals were classified into 8-class directions and 2-class distances of voluntary eye gaze movements. A horizontal and a vertical EOGs during eye gaze movement at each sampling time were treated as a two-dimensional vector, and the center of gravity of the sample vectors whose norms were more than 80% of the maximum norm was used as a feature vector to be classified. By the classification using the k-nearest neighbor algorithm, it was shown that the averaged correct detection rates on each subject were 98.9%, 98.7%, 94.4%, respectively. This method can avoid strict EOG-based eye tracking which requires DC amplification of very small signal. It would be useful to develop robust human interfacing systems based on menu selection for severely paralyzed patients.

Solution of Volterra and Fredholm Classes of Equations via Triangular Orthogonal Function (A Combination of Right Hand Triangular Function and Left Hand Triangular Function) and Hybrid Orthogonal Function (A Combination of Sample Hold Function and Right Hand Triangular Function)

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Anirban; Ganguly, Anindita; Chatterjee, Saumya Deep

2018-04-01

In this paper the authors have dealt with seven kinds of non-linear Volterra and Fredholm classes of equations. The authors have formulated an algorithm for solving the aforementioned equation types via Hybrid Function (HF) and Triangular Function (TF) piecewise-linear orthogonal approach. In this approach the authors have reduced integral equation or integro-differential equation into equivalent system of simultaneous non-linear equation and have employed either Newton's method or Broyden's method to solve the simultaneous non-linear equations. The authors have calculated the L2-norm error and the max-norm error for both HF and TF method for each kind of equations. Through the illustrated examples, the authors have shown that the HF based algorithm produces stable result, on the contrary TF-computational method yields either stable, anomalous or unstable results.

Convergence and stability of the exponential Euler method for semi-linear stochastic delay differential equations.

PubMed

Zhang, Ling

2017-01-01

The main purpose of this paper is to investigate the strong convergence and exponential stability in mean square of the exponential Euler method to semi-linear stochastic delay differential equations (SLSDDEs). It is proved that the exponential Euler approximation solution converges to the analytic solution with the strong order [Formula: see text] to SLSDDEs. On the one hand, the classical stability theorem to SLSDDEs is given by the Lyapunov functions. However, in this paper we study the exponential stability in mean square of the exact solution to SLSDDEs by using the definition of logarithmic norm. On the other hand, the implicit Euler scheme to SLSDDEs is known to be exponentially stable in mean square for any step size. However, in this article we propose an explicit method to show that the exponential Euler method to SLSDDEs is proved to share the same stability for any step size by the property of logarithmic norm.

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…

Sparse decomposition of seismic data and migration using Gaussian beams with nonzero initial curvature

NASA Astrophysics Data System (ADS)

Liu, Peng; Wang, Yanfei

2018-04-01

We study problems associated with seismic data decomposition and migration imaging. We first represent the seismic data utilizing Gaussian beam basis functions, which have nonzero curvature, and then consider the sparse decomposition technique. The sparse decomposition problem is an l0-norm constrained minimization problem. In solving the l0-norm minimization, a polynomial Radon transform is performed to achieve sparsity, and a fast gradient descent method is used to calculate the waveform functions. The waveform functions can subsequently be used for sparse Gaussian beam migration. Compared with traditional sparse Gaussian beam methods, the seismic data can be properly reconstructed employing fewer Gaussian beams with nonzero initial curvature. The migration approach described in this paper is more efficient than the traditional sparse Gaussian beam migration.

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…

Reactive Power Compensation Method Considering Minimum Effective Reactive Power Reserve

NASA Astrophysics Data System (ADS)

Gong, Yiyu; Zhang, Kai; Pu, Zhang; Li, Xuenan; Zuo, Xianghong; Zhen, Jiao; Sudan, Teng

2017-05-01

According to the calculation model of minimum generator reactive power reserve of power system voltage stability under the premise of the guarantee, the reactive power management system with reactive power compensation combined generator, the formation of a multi-objective optimization problem, propose a reactive power reserve is considered the minimum generator reactive power compensation optimization method. This method through the improvement of the objective function and constraint conditions, when the system load growth, relying solely on reactive power generation system can not meet the requirement of safe operation, increase the reactive power reserve to solve the problem of minimum generator reactive power compensation in the case of load node.

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

Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.).

PubMed

Huis, Rudy; Hawkins, Simon; Neutelings, Godfrey

2010-04-19

Quantitative real-time PCR (qRT-PCR) is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs). Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L). Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs) and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH) as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups.qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59). LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both geNorm-designated- and NormFinder-designated-reference genes. The use of 2 different statistical algorithms results in the identification of different combinations of flax HKGs for expression data normalization. Despite such differences, the use of geNorm-designated- and NormFinder-designated-reference genes enabled us to accurately compare the expression levels of a flax MYB gene in different organs and tissues. Our identification and validation of suitable flax HKGs will facilitate future developmental transcriptomic studies in this economically-important plant.

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.

Structural Change and Interaction Behavior in Multimodal Networks

DTIC Science & Technology

2010-07-30

S̃q~v = PD( ∑ p Sq→p)− 1 2~v, so λ and D( ∑ p Sq→p) − 1 2~v are an eigenvalue-eigenvector pair for P. By the Perron - Frobenius theorem, we know that λ... Frobenius norm, and α = 11+γ . The closed form solution is F ∗ p→q = (1 − α)(Inq − αS̃q)−1ATp→q [30, 26]. 4 Experiment We evaluated our method for...of mode Xp and the jth cluster of Xq. An approximate factorization is then achieved by minimizing a loss function comprised of the Frobenius norms of

Multi-task feature learning by using trace norm regularization

NASA Astrophysics Data System (ADS)

Jiangmei, Zhang; Binfeng, Yu; Haibo, Ji; Wang, Kunpeng

2017-11-01

Multi-task learning can extract the correlation of multiple related machine learning problems to improve performance. This paper considers applying the multi-task learning method to learn a single task. We propose a new learning approach, which employs the mixture of expert model to divide a learning task into several related sub-tasks, and then uses the trace norm regularization to extract common feature representation of these sub-tasks. A nonlinear extension of this approach by using kernel is also provided. Experiments conducted on both simulated and real data sets demonstrate the advantage of the proposed approach.

Knowledge Discovery from Databases: An Introductory Review.

ERIC Educational Resources Information Center

Vickery, Brian

1997-01-01

Introduces new procedures being used to extract knowledge from databases and discusses rationales for developing knowledge discovery methods. Methods are described for such techniques as classification, clustering, and the detection of deviations from pre-established norms. Examines potential uses of knowledge discovery in the information field.…

Emergence and Evolution of Cooperation Under Resource Pressure

PubMed Central

Pereda, María; Zurro, Débora; Santos, José I.; Briz i Godino, Ivan; Álvarez, Myrian; Caro, Jorge; Galán, José M.

2017-01-01

We study the influence that resource availability has on cooperation in the context of hunter-gatherer societies. This paper proposes a model based on archaeological and ethnographic research on resource stress episodes, which exposes three different cooperative regimes according to the relationship between resource availability in the environment and population size. The most interesting regime represents moderate survival stress in which individuals coordinate in an evolutionary way to increase the probabilities of survival and reduce the risk of failing to meet the minimum needs for survival. Populations self-organise in an indirect reciprocity system in which the norm that emerges is to share the part of the resource that is not strictly necessary for survival, thereby collectively lowering the chances of starving. Our findings shed further light on the emergence and evolution of cooperation in hunter-gatherer societies. PMID:28362000

Which patients do I treat? An experimental study with economists and physicians

PubMed Central

2012-01-01

This experiment investigates decisions made by prospective economists and physicians in an allocation problem which can be framed either medically or neutrally. The potential recipients differ with respect to their minimum needs as well as to how much they benefit from a treatment. We classify the allocators as either 'selfish', 'Rawlsian', or 'maximizing the number of recipients'. Economists tend to maximize their own payoff, whereas the physicians' choices are more in line with maximizing the number of recipients and with Rawlsianism. Regarding the framing, we observe that professional norms surface more clearly in familiar settings. Finally, we scrutinize how the probability of being served and the allocated quantity depend on a recipient's characteristics as well as on the allocator type. JEL Classification: A13, I19, C91, C72 PMID:22827912

Emergence and Evolution of Cooperation Under Resource Pressure.

PubMed

Pereda, María; Zurro, Débora; Santos, José I; Briz I Godino, Ivan; Álvarez, Myrian; Caro, Jorge; Galán, José M

2017-03-31

We study the influence that resource availability has on cooperation in the context of hunter-gatherer societies. This paper proposes a model based on archaeological and ethnographic research on resource stress episodes, which exposes three different cooperative regimes according to the relationship between resource availability in the environment and population size. The most interesting regime represents moderate survival stress in which individuals coordinate in an evolutionary way to increase the probabilities of survival and reduce the risk of failing to meet the minimum needs for survival. Populations self-organise in an indirect reciprocity system in which the norm that emerges is to share the part of the resource that is not strictly necessary for survival, thereby collectively lowering the chances of starving. Our findings shed further light on the emergence and evolution of cooperation in hunter-gatherer societies.

Computation of Optimal Actuator/Sensor Locations

DTIC Science & Technology

2013-12-26

weighting matrices Q = I and R = 0.01, and a minimum variance LQ-cost (with V = I ), a plot of the L2 norm of the control signal versus actuator...0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.05 0.1 0.15 0.2 0.25 actuator location lin ea r− qu ad ra tic c os t ( re la tiv e) Q = I , R = 100 Q... I , R = 1 Q = I , R = 0.01 Q = I , R = 0.0001 (a) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 actuator location lin

Emergence and Evolution of Cooperation Under Resource Pressure

NASA Astrophysics Data System (ADS)

Pereda, María; Zurro, Débora; Santos, José I.; Briz I Godino, Ivan; Álvarez, Myrian; Caro, Jorge; Galán, José M.

2017-03-01

We study the influence that resource availability has on cooperation in the context of hunter-gatherer societies. This paper proposes a model based on archaeological and ethnographic research on resource stress episodes, which exposes three different cooperative regimes according to the relationship between resource availability in the environment and population size. The most interesting regime represents moderate survival stress in which individuals coordinate in an evolutionary way to increase the probabilities of survival and reduce the risk of failing to meet the minimum needs for survival. Populations self-organise in an indirect reciprocity system in which the norm that emerges is to share the part of the resource that is not strictly necessary for survival, thereby collectively lowering the chances of starving. Our findings shed further light on the emergence and evolution of cooperation in hunter-gatherer societies.

SPEQTACLE: An automated generalized fuzzy C-means algorithm for tumor delineation in PET

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

Lapuyade-Lahorgue, Jérôme; Visvikis, Dimitris; Hatt, Mathieu, E-mail: hatt@univ-brest.fr

Purpose: Accurate tumor delineation in positron emission tomography (PET) images is crucial in oncology. Although recent methods achieved good results, there is still room for improvement regarding tumors with complex shapes, low signal-to-noise ratio, and high levels of uptake heterogeneity. Methods: The authors developed and evaluated an original clustering-based method called spatial positron emission quantification of tumor—Automatic Lp-norm estimation (SPEQTACLE), based on the fuzzy C-means (FCM) algorithm with a generalization exploiting a Hilbertian norm to more accurately account for the fuzzy and non-Gaussian distributions of PET images. An automatic and reproducible estimation scheme of the norm on an image-by-image basismore » was developed. Robustness was assessed by studying the consistency of results obtained on multiple acquisitions of the NEMA phantom on three different scanners with varying acquisition parameters. Accuracy was evaluated using classification errors (CEs) on simulated and clinical images. SPEQTACLE was compared to another FCM implementation, fuzzy local information C-means (FLICM) and fuzzy locally adaptive Bayesian (FLAB). Results: SPEQTACLE demonstrated a level of robustness similar to FLAB (variability of 14% ± 9% vs 14% ± 7%, p = 0.15) and higher than FLICM (45% ± 18%, p < 0.0001), and improved accuracy with lower CE (14% ± 11%) over both FLICM (29% ± 29%) and FLAB (22% ± 20%) on simulated images. Improvement was significant for the more challenging cases with CE of 17% ± 11% for SPEQTACLE vs 28% ± 22% for FLAB (p = 0.009) and 40% ± 35% for FLICM (p < 0.0001). For the clinical cases, SPEQTACLE outperformed FLAB and FLICM (15% ± 6% vs 37% ± 14% and 30% ± 17%, p < 0.004). Conclusions: SPEQTACLE benefitted from the fully automatic estimation of the norm on a case-by-case basis. This promising approach will be extended to multimodal images and multiclass estimation in future developments.« less

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.

Setting Standards for Minimum Competency Tests.

ERIC Educational Resources Information Center

Mehrens, William A.

Some general questions about minimum competency tests are discussed, and various methods of setting standards are reviewed with major attention devoted to those methods used for dichotomizing a continuum. Methods reviewed under the heading of Absolute Judgments of Test Content include Nedelsky's, Angoff's, Ebel's, and Jaeger's. These methods are…

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

Integrated beam orientation and scanning-spot optimization in intensity-modulated proton therapy for brain and unilateral head and neck tumors.

PubMed

Gu, Wenbo; O'Connor, Daniel; Nguyen, Dan; Yu, Victoria Y; Ruan, Dan; Dong, Lei; Sheng, Ke

2018-04-01

Intensity-Modulated Proton Therapy (IMPT) is the state-of-the-art method of delivering proton radiotherapy. Previous research has been mainly focused on optimization of scanning spots with manually selected beam angles. Due to the computational complexity, the potential benefit of simultaneously optimizing beam orientations and spot pattern could not be realized. In this study, we developed a novel integrated beam orientation optimization (BOO) and scanning-spot optimization algorithm for intensity-modulated proton therapy (IMPT). A brain chordoma and three unilateral head-and-neck patients with a maximal target size of 112.49 cm 3 were included in this study. A total number of 1162 noncoplanar candidate beams evenly distributed across 4π steradians were included in the optimization. For each candidate beam, the pencil-beam doses of all scanning spots covering the PTV and a margin were calculated. The beam angle selection and spot intensity optimization problem was formulated to include three terms: a dose fidelity term to penalize the deviation of PTV and OAR doses from ideal dose distribution; an L1-norm sparsity term to reduce the number of active spots and improve delivery efficiency; a group sparsity term to control the number of active beams between 2 and 4. For the group sparsity term, convex L2,1-norm and nonconvex L2,1/2-norm were tested. For the dose fidelity term, both quadratic function and linearized equivalent uniform dose (LEUD) cost function were implemented. The optimization problem was solved using the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). The IMPT BOO method was tested on three head-and-neck patients and one skull base chordoma patient. The results were compared with IMPT plans created using column generation selected beams or manually selected beams. The L2,1-norm plan selected spatially aggregated beams, indicating potential degeneracy using this norm. L2,1/2-norm was able to select spatially separated beams and achieve smaller deviation from the ideal dose. In the L2,1/2-norm plans, the [mean dose, maximum dose] of OAR were reduced by an average of [2.38%, 4.24%] and[2.32%, 3.76%] of the prescription dose for the quadratic and LEUD cost function, respectively, compared with the IMPT plan using manual beam selection while maintaining the same PTV coverage. The L2,1/2 group sparsity plans were dosimetrically superior to the column generation plans as well. Besides beam orientation selection, spot sparsification was observed. Generally, with the quadratic cost function, 30%~60% spots in the selected beams remained active. With the LEUD cost function, the percentages of active spots were in the range of 35%~85%.The BOO-IMPT run time was approximately 20 min. This work shows the first IMPT approach integrating noncoplanar BOO and scanning-spot optimization in a single mathematical framework. This method is computationally efficient, dosimetrically superior and produces delivery-friendly IMPT plans. © 2018 American Association of Physicists in Medicine.

Young adults' contraceptive knowledge, norms and attitudes: associations with risk of unintended pregnancy.

PubMed

Frost, Jennifer J; Lindberg, Laura Duberstein; Finer, Lawrence B

2012-06-01

Women aged 18-29 have higher rates of unintended pregnancy than any other age-group. Information is needed to understand what characteristics are associated with risky contraceptive use practices among this population and to develop new strategies for reducing these women's risk of unintended pregnancy. Data related to unintended pregnancy risk were collected from a nationally representative sample of 1,800 unmarried women and men aged 18-29 surveyed by telephone in 2009. Among those at risk of unintended pregnancy, multiple logistic regression was used to assess associations between contraceptive knowledge, norms and attitudes and selected risky contraceptive behaviors. More than half of young men and a quarter of young women received low scores on contraceptive knowledge, and six in 10 underestimated the effectiveness of oral contraceptives. Among women, for each correct response on a contraceptive knowledge scale, the odds of expecting to have unprotected sex in the next three months decreased by 9%, of currently using a hormonal or long-acting reversible method increased by 17%, and of using no method decreased by 17%. Fear of side effects, norms and attitudes that favor nonmarital pregnancy or undervalue the importance of contraception, pregnancy ambivalence and mistrust of government's role in promoting contraception were also associated with one or more risky contraceptive use behaviors. Programs to increase young adults' knowledge about contraceptive methods and use are urgently needed. Given the demonstrated link between method knowledge and contraceptive behaviors, such programs may be useful in addressing risky behavior in this population. Copyright © 2012 by the Guttmacher Institute.

Change detection of medical images using dictionary learning techniques and PCA

NASA Astrophysics Data System (ADS)

Nika, Varvara; Babyn, Paul; Zhu, Hongmei

2014-03-01

Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of MRI scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. In this paper we present the Eigen-Block Change Detection algorithm (EigenBlockCD). It performs local registration and identifies the changes between consecutive MR images of the brain. Blocks of pixels from baseline scan are used to train local dictionaries that are then used to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between L1 and L2 norms as two possible similarity measures in the EigenBlockCD. We show the advantages of L2 norm over L1 norm theoretically and numerically. We also demonstrate the performance of the EigenBlockCD algorithm for detecting changes of MR images and compare our results with those provided in recent literature. Experimental results with both simulated and real MRI scans show that the EigenBlockCD outperforms the previous methods. It detects clinical changes while ignoring the changes due to patient's position and other acquisition artifacts.

An accurate method to measure alpha-emitting natural radionuclides in atmospheric filters: Application in two NORM industries

NASA Astrophysics Data System (ADS)

Lozano, R. L.; Bolívar, J. P.; San Miguel, E. G.; García-Tenorio, R.; Gázquez, M. J.

2011-12-01

In this work, an accurate method for the measurement of natural alpha-emitting radionuclides from aerosols collected in air filters is presented and discussed in detail. The knowledge of the levels of several natural alpha-emitting radionuclides (238U, 234U, 232Th, 230Th, 228Th, 226Ra and 210Po) in atmospheric aerosols is essential not only for a better understanding of the several atmospheric processes and changes, but also for a proper evaluation of the potential doses, which can inadvertently be received by the population via inhalation. The proposed method takes into account the presence of intrinsic amounts of these radionuclides in the matrices of the quartz filters used, as well as the possible variation in the humidity of the filters throughout the collection process. In both cases, the corrections necessary in order to redress these levels have been evaluated and parameterized. Furthermore, a detailed study has been performed into the optimisation of the volume of air to be sampled in order to increase the accuracy in the determination of the radionuclides. The method as a whole has been applied for the determination of the activity concentrations of U- and Th-isotopes in aerosols collected at two NORM (Naturally Occurring Radioactive Material) industries located in the southwest of Spain. Based on the levels found, a conservative estimation has been performed to yield the additional committed effective doses to which the workers are potentially susceptible due to inhalation of anthropogenic material present in the environment of these two NORM industries.

Saudi views on consenting for research on medical records and leftover tissue samples

PubMed Central

2010-01-01

Background Consenting for retrospective medical records-based research (MR) and leftover tissue-based research (TR) continues to be controversial. Our objective was to survey Saudis attending outpatient clinics at a tertiary care hospital on their personal preference and perceptions of norm and current practice in relation to consenting for MR and TR. Methods We surveyed 528 Saudis attending clinics at a tertiary care hospital in Saudi Arabia to explore their preferences and perceptions of norm and current practice. The respondents selected one of 7 options from each of 6 questionnaires. Results Respondents' mean (SD) age was 33 (11) years, 42% were males, 56% were patients, 84% had ≥ secondary school education, and 10% had previously volunteered for research. Respectively, 40% and 49% perceived that the norm is to conduct MR and TR without consent and 38% and 37% with general or proposal-specific consent; the rest objected to such research. There was significant difference in the distribution of choices according to health status (patients vs. companions) for MR (adjusted Kruskal-Wallis test P = 0.03) but not to age group, gender, education level, or previous participation in research (unadjusted P = 0.02 - 0.59). The distributions of perceptions of current practice and norm were similar (unadjusted Marginal Homogeneity test P = 0.44 for MR and P = 0.89 for TR), whereas the distributions of preferences and perceptions of norm were different (adjusted P = 0.09 for MR and P = 0.02 for TR). The distributions of perceptions of norm, preferences, and perceptions of current practice for MR were significantly different from those of TR (adjusted P < 0.009 for all). Conclusions We conclude that: 1) there is a considerable diversity among Saudi views regarding consenting for retrospective research which may be related to health status, 2) the distribution of perceptions of norm was similar to the distribution of perceptions of current practice but different from that of preferences, and 3) MR and TR are perceived differently in regard to consenting. PMID:20955580

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.

Sugar in the Gourd: Preserving Appalachian Traditions.

ERIC Educational Resources Information Center

Brown, Tom

1983-01-01

The Appalachian Folk Music Project developed methods to teach folk music in the schools. Authentic material was identified and teaching methods appropriate to rural Appalachia were selected. Departures from the norm included teaching of instruments like the dulcimer, harmonica, and fiddle and the use of folk models whenever possible. (CS)

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.

Executive Functioning Skills in Preschool-Age Children With Cochlear Implants

PubMed Central

Beer, Jessica; Kronenberger, William G.; Castellanos, Irina; Colson, Bethany G.; Henning, Shirley C.; Pisoni, David B.

2014-01-01

Purpose The purpose of this study was to determine whether deficits in executive functioning (EF) in children with cochlear implants (CIs) emerge as early as the preschool years. Method Two groups of children ages 3 to 6 years participated in this cross-sectional study: 24 preschoolers who had CIs prior to 36 months of age and 21 preschoolers with normal hearing (NH). All were tested on normed measures of working memory, inhibition-concentration, and organization-integration. Parents completed a normed rating scale of problem behaviors related to EF. Comparisons of EF skills of children with CIs were made to peers with NH and to published nationally representative norms. Results Preschoolers with CIs showed significantly poorer performance on inhibition-concentration and working memory compared with peers with NH and with national norms. No group differences were found in visual memory or organization-integration. When data were controlled for language, differences in performance measures of EF remained, whereas differences in parent-reported problems with EF were no longer significant. Hearing history was generally unrelated to EF. Conclusions This is the first study to demonstrate that EF deficits found in older children with CIs begin to emerge as early as preschool years. The ability to detect these deficits early has important implications for early intervention and habilitation after cochlear implantation. PMID:24686747

Taking It Like a Man: Masculine Role Norms as Moderators of the Racial Discrimination–Depressive Symptoms Association Among African American Men

PubMed Central

2012-01-01

Objectives. I examined the association between everyday racial discrimination and depressive symptoms and explored the moderating role of 2 dimensions of masculine role norms, restrictive emotionality and self-reliance. Methods. Cross-sectional survey data from 674 African American men aged 18 years and older recruited primarily from barbershops in 4 US regions (2003–2010) were used. Direct and moderated associations were assessed with multivariate linear regression analyses for the overall sample and different age groups. Models were adjusted for recruitment site, sociodemographics, masculine role norms salience, and general social stress. Results. Everyday racial discrimination was associated with more depressive symptoms across all age groups. Higher restrictive emotionality was associated with more depressive symptoms among men aged 18 to 29 and 30 to 39 years. Self-reliance was associated with fewer depressive symptoms among men aged 18 to 29 years and 40 years and older. The positive association between everyday racial discrimination and depressive symptoms was stronger among men with high restrictive emotionality, but this moderated effect was limited to men older than 30 years. Conclusions. Interventions designed to reduce African American men’s depression instigated by racism should be life-course specific and address masculine role norms that encourage emotion restriction. PMID:22401515

Social Cognitive Mediators of Sociodemographic Differences in Colorectal Cancer Screening Uptake

PubMed Central

Lo, Siu Hing; Waller, Jo; Vrinten, Charlotte; Kobayashi, Lindsay; von Wagner, Christian

2015-01-01

Background. This study examined if and how sociodemographic differences in colorectal cancer (CRC) screening uptake can be explained by social cognitive factors. Methods. Face-to-face interviews were conducted with individuals aged 60–70 years (n = 1309) living in England as part of a population-based omnibus survey. Results. There were differences in screening uptake by SES, marital status, ethnicity, and age but not by gender. Perceived barriers (stand. b = −0.40, p < 0.001), social norms (stand. b = 0.33, p < 0.001), and screening knowledge (stand. b = 0.17, p < 0.001) had independent associations with uptake. SES differences in uptake were mediated through knowledge, social norms, and perceived barriers. Ethnic differences were mediated through knowledge. Differences in uptake by marital status were primarily mediated through social norms and to a lesser extent through knowledge. Age differences were largely unmediated, except for a small mediated effect via social norms. Conclusions. Sociodemographic differences in CRC screening uptake were largely mediated through social cognitive factors. Impact. Our findings suggest that multifaceted interventions might be needed to reduce socioeconomic inequalities. Ethnic differences might be reduced through improved screening knowledge. Normative interventions could emphasise screening as an activity endorsed by important others outside the immediate family to appeal to a wider audience. PMID:26504782

Influences of sex, age, and education on attitudes toward gender inequitable norms and practices in South Sudan

PubMed Central

Scott, Jennifer; Hacker, Michele; Averbach, Sarah; Modest, Anna M.; Cornish, Sarah; Spencer, Danielle; Murphy, Maureen; Parmar, Parveen

2014-01-01

Background Prolonged conflict in South Sudan exacerbated gender disparities and inequities. This study assessed differences in attitudes toward gender inequitable norms and practices by sex, age, and education to inform programming. Methods Applying community-based participatory research methodology, 680 adult respondents, selected by quota sampling, were interviewed in seven South Sudanese communities from 2009 to 2011. The verbally administered survey assessed attitudes using the Gender Equitable Men scale. Data were stratified by sex, age, and education. Results Of 680 respondents, 352 were female, 326 were male, and two did not report their sex. The majority of respondents agreed with gender inequitable household roles, but the majority disagreed with gender inequitable practices (i.e. early marriage, forced marriage, and inequitable education of girls). Respondents who reported no education were more likely than those who reported any education to agree with gender inequitable practices (all p<0.03) except for forced marriage (p=0.07), and few significant differences were observed when these responses were stratified by sex and age. Conclusion The study reveals agreement with gender inequitable norms in the household, but an overall disagreement with gender inequitable practices in sampled communities. The findings support that education of both women and men may promote gender equitable norms and practices. PMID:25026024

Beyond Picture Naming: Norms and Patient Data for a Verb Generation Task**

PubMed Central

Kurland, Jacquie; Reber, Alisson; Stokes, Polly

2014-01-01

Purpose The current study aimed to: 1) acquire a set of verb generation to picture norms; and 2) probe its utility as an outcomes measure in aphasia treatment. Method Fifty healthy volunteers participated in Phase I, the verb generation normative sample. They generated verbs for 218 pictures of common objects (ISI=5s). In Phase II, four persons with aphasia (PWA) generated verbs for 60 objects (ISI=10s). Their stimuli consisted of objects which were: 1) recently trained (for object naming; n=20); 2) untrained (a control set; n=20); or 3) from a set of pictures named correctly at baseline (n=20). Verb generation was acquired twice: two months into, and following, a six-month home practice program. Results No objects elicited perfect verb agreement in the normed sample. Stimuli with the highest percent agreement were mostly artifacts and dominant verbs primary functional associates. Although not targeted in treatment or home practice, PWA mostly improved performance in verb generation post-practice. Conclusions A set of clinically and experimentally useful verb generation norms was acquired for a subset of the Snodgrass and Vanderwart (1980) picture set. More cognitively demanding than confrontation naming, this task may help to fill the sizeable gap between object picture naming and propositional speech. PMID:24686752