Multi-Fidelity Framework for Modeling Combustion Instability

DTIC Science & Technology

2016-07-27

generated from the reduced-domain dataset. Evaluations of the framework are performed based on simplified test problems for a model rocket combustor showing...generated from the reduced-domain dataset. Evaluations of the framework are performed based on simplified test problems for a model rocket combustor...of Aeronautics and Astronautics and Associate Fellow AIAA. ‡ Professor Emeritus. § Senior Scientist, Rocket Propulsion Division and Senior Member

A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-09-01

Exascale-level simulations require fault-resilient algorithms that are robust against repeated and expected software and/or hardware failures during computations, which may render the simulation results unsatisfactory. If each processor can share some global information about the simulation from a coarse, limited accuracy but relatively costless auxiliary simulator we can effectively fill-in the missing spatial data at the required times by a statistical learning technique - multi-level Gaussian process regression, on the fly; this has been demonstrated in previous work [1]. Based on the previous work, we also employ another (nonlinear) statistical learning technique, Diffusion Maps, that detects computational redundancy in time and hence accelerate the simulation by projective time integration, giving the overall computation a "patch dynamics" flavor. Furthermore, we are now able to perform information fusion with multi-fidelity and heterogeneous data (including stochastic data). Finally, we set the foundations of a new framework in CFD, called patch simulation, that combines information fusion techniques from, in principle, multiple fidelity and resolution simulations (and even experiments) with a new adaptive timestep refinement technique. We present two benchmark problems (the heat equation and the Navier-Stokes equations) to demonstrate the new capability that statistical learning tools can bring to traditional scientific computing algorithms. For each problem, we rely on heterogeneous and multi-fidelity data, either from a coarse simulation of the same equation or from a stochastic, particle-based, more "microscopic" simulation. We consider, as such "auxiliary" models, a Monte Carlo random walk for the heat equation and a dissipative particle dynamics (DPD) model for the Navier-Stokes equations. More broadly, in this paper we demonstrate the symbiotic and synergistic combination of statistical learning, domain decomposition, and scientific computing in exascale simulations.

Parametric Modeling Investigation of a Radially-Staged Low-Emission Aviation Combustor

NASA Technical Reports Server (NTRS)

Heath, Christopher M.

2016-01-01

Aviation gas-turbine combustion demands high efficiency, wide operability and minimal trace gas emissions. Performance critical design parameters include injector geometry, combustor layout, fuel-air mixing and engine cycle conditions. The present investigation explores these factors and their impact on a radially staged low-emission aviation combustor sized for a next-generation 24,000-lbf-thrust engine. By coupling multi-fidelity computational tools, a design exploration was performed using a parameterized annular combustor sector at projected 100% takeoff power conditions. Design objectives included nitrogen oxide emission indices and overall combustor pressure loss. From the design space, an optimal configuration was selected and simulated at 7.1, 30 and 85% part-power operation, corresponding to landing-takeoff cycle idle, approach and climb segments. All results were obtained by solution of the steady-state Reynolds-averaged Navier-Stokes equations. Species concentrations were solved directly using a reduced 19-step reaction mechanism for Jet-A. Turbulence closure was obtained using a nonlinear K-epsilon model. This research demonstrates revolutionary combustor design exploration enabled by multi-fidelity physics-based simulation.

Orthogonal Gaussian process models

DOE PAGES

Plumlee, Matthew; Joseph, V. Roshan

2017-01-01

Gaussian processes models are widely adopted for nonparameteric/semi-parametric modeling. Identifiability issues occur when the mean model contains polynomials with unknown coefficients. Though resulting prediction is unaffected, this leads to poor estimation of the coefficients in the mean model, and thus the estimated mean model loses interpretability. This paper introduces a new Gaussian process model whose stochastic part is orthogonal to the mean part to address this issue. As a result, this paper also discusses applications to multi-fidelity simulations using data examples.

Orthogonal Gaussian process models

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

Plumlee, Matthew; Joseph, V. Roshan

Gaussian processes models are widely adopted for nonparameteric/semi-parametric modeling. Identifiability issues occur when the mean model contains polynomials with unknown coefficients. Though resulting prediction is unaffected, this leads to poor estimation of the coefficients in the mean model, and thus the estimated mean model loses interpretability. This paper introduces a new Gaussian process model whose stochastic part is orthogonal to the mean part to address this issue. As a result, this paper also discusses applications to multi-fidelity simulations using data examples.

Integration of Multifidelity Multidisciplinary Computer Codes for Design and Analysis of Supersonic Aircraft

NASA Technical Reports Server (NTRS)

Geiselhart, Karl A.; Ozoroski, Lori P.; Fenbert, James W.; Shields, Elwood W.; Li, Wu

2011-01-01

This paper documents the development of a conceptual level integrated process for design and analysis of efficient and environmentally acceptable supersonic aircraft. To overcome the technical challenges to achieve this goal, a conceptual design capability which provides users with the ability to examine the integrated solution between all disciplines and facilitates the application of multidiscipline design, analysis, and optimization on a scale greater than previously achieved, is needed. The described capability is both an interactive design environment as well as a high powered optimization system with a unique blend of low, mixed and high-fidelity engineering tools combined together in the software integration framework, ModelCenter. The various modules are described and capabilities of the system are demonstrated. The current limitations and proposed future enhancements are also discussed.

Multi-fidelity numerical simulations of shock/turbulent-boundary layer interaction with uncertainty quantification

NASA Astrophysics Data System (ADS)

Bermejo-Moreno, Ivan; Campo, Laura; Larsson, Johan; Emory, Mike; Bodart, Julien; Palacios, Francisco; Iaccarino, Gianluca; Eaton, John

2013-11-01

We study the interaction between an oblique shock wave and the turbulent boundary layers inside a nearly-square duct by combining wall-modeled LES, 2D and 3D RANS simulations, targeting the experiment of Campo, Helmer & Eaton, 2012 (nominal conditions: M = 2 . 05 , Reθ = 6 , 500). A primary objective is to quantify the effect of aleatory and epistemic uncertainties on the STBLI. Aleatory uncertainties considered include the inflow conditions (Mach number of the incoming air stream and thickness of the boundary layers) and perturbations of the duct geometry upstream of the interaction. The epistemic uncertainty under consideration focuses on the RANS turbulence model form by injecting perturbations in the Reynolds stress anisotropy in regions of the flow where the model assumptions (in particular, the Boussinesq eddy-viscosity hypothesis) may be invalid. These perturbations are then propagated through the flow solver into the solution. The uncertainty quantification (UQ) analysis is done through 2D and 3D RANS simulations, assessing the importance of the three-dimensional effects imposed by the nearly-square duct geometry. Wall-modeled LES are used to verify elements of the UQ methodology and to explore the flow features and physics of the STBLI for multiple shock strengths. Financial support from the United States Department of Energy under the PSAAP program is gratefully acknowledged.

A Multi-Fidelity Surrogate Model for the Equation of State for Mixtures of Real Gases

NASA Astrophysics Data System (ADS)

Ouellet, Frederick; Park, Chanyoung; Koneru, Rahul; Balachandar, S.; Rollin, Bertrand

2017-11-01

The explosive dispersal of particles is a complex multiphase and multi-species fluid flow problem. In these flows, the products of detonated explosives must be treated as real gases while the ideal gas equation of state is used for the ambient air. As the products expand outward, they mix with the air and create a region where both state equations must be satisfied. One of the most accurate, yet expensive, methods to handle this problem is an algorithm that iterates between both state equations until both pressure and thermal equilibrium are achieved inside of each computational cell. This work creates a multi-fidelity surrogate model to replace this process. This is achieved by using a Kriging model to produce a curve fit which interpolates selected data from the iterative algorithm. The surrogate is optimized for computing speed and model accuracy by varying the number of sampling points chosen to construct the model. The performance of the surrogate with respect to the iterative method is tested in simulations using a finite volume code. The model's computational speed and accuracy are analyzed to show the benefits of this novel approach. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program, under Contract No. DE-NA00023.

Analysis of a Multi-Fidelity Surrogate for Handling Real Gas Equations of State

NASA Astrophysics Data System (ADS)

Ouellet, Frederick; Park, Chanyoung; Rollin, Bertrand; Balachandar, S.

2017-06-01

The explosive dispersal of particles is a complex multiphase and multi-species fluid flow problem. In these flows, the detonation products of the explosive must be treated as real gas while the ideal gas equation of state is used for the surrounding air. As the products expand outward from the detonation point, they mix with ambient air and create a mixing region where both state equations must be satisfied. One of the most accurate, yet computationally expensive, methods to handle this problem is an algorithm that iterates between both equations of state until pressure and thermal equilibrium are achieved inside of each computational cell. This work aims to use a multi-fidelity surrogate model to replace this process. A Kriging model is used to produce a curve fit which interpolates selected data from the iterative algorithm using Bayesian statistics. We study the model performance with respect to the iterative method in simulations using a finite volume code. The model's (i) computational speed, (ii) memory requirements and (iii) computational accuracy are analyzed to show the benefits of this novel approach. Also, optimizing the combination of model accuracy and computational speed through the choice of sampling points is explained. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program as a Cooperative Agreement under the Predictive Science Academic Alliance Program under Contract No. DE-NA0002378.

Design Environment for Multifidelity and Multidisciplinary Components

NASA Technical Reports Server (NTRS)

Platt, Michael

2014-01-01

One of the greatest challenges when developing propulsion systems is predicting the interacting effects between the fluid loads, thermal loads, and structural deflection. The interactions between technical disciplines often are not fully analyzed, and the analysis in one discipline often uses a simplified representation of other disciplines as an input or boundary condition. For example, the fluid forces in an engine generate static and dynamic rotor deflection, but the forces themselves are dependent on the rotor position and its orbit. It is important to consider the interaction between the physical phenomena where the outcome of each analysis is heavily dependent on the inputs (e.g., changes in flow due to deflection, changes in deflection due to fluid forces). A rigid design process also lacks the flexibility to employ multiple levels of fidelity in the analysis of each of the components. This project developed and validated an innovative design environment that has the flexibility to simultaneously analyze multiple disciplines and multiple components with multiple levels of model fidelity. Using NASA's open-source multidisciplinary design analysis and optimization (OpenMDAO) framework, this multifaceted system will provide substantially superior capabilities to current design tools.

A Multi-Fidelity Surrogate Model for Handling Real Gas Equations of State

NASA Astrophysics Data System (ADS)

Ouellet, Frederick; Park, Chanyoung; Rollin, Bertrand; Balachandar, S."bala"

2016-11-01

The explosive dispersal of particles is an example of a complex multiphase and multi-species fluid flow problem. This problem has many engineering applications including particle-laden explosives. In these flows, the detonation products of the explosive cannot be treated as a perfect gas so a real gas equation of state is used to close the governing equations (unlike air, which uses the ideal gas equation for closure). As the products expand outward from the detonation point, they mix with ambient air and create a mixing region where both of the state equations must be satisfied. One of the more accurate, yet computationally expensive, methods to deal with this is a scheme that iterates between the two equations of state until pressure and thermal equilibrium are achieved inside of each computational cell. This work strives to create a multi-fidelity surrogate model of this process. We then study the performance of the model with respect to the iterative method by performing both gas-only and particle laden flow simulations using an Eulerian-Lagrangian approach with a finite volume code. Specifically, the model's (i) computational speed, (ii) memory requirements and (iii) computational accuracy are analyzed to show the benefits of this novel modeling approach. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program, under Contract No. DE-NA00023.

Development of Multidisciplinary, Multifidelity Analysis, Integration, and Optimization of Aerospace Vehicles

DTIC Science & Technology

2010-02-27

investigated in more detail. The intermediate level of fidelity, though more expensive, is then used to refine the analysis , add geometric detail, and...design stage is used to further refine the analysis , narrowing the design to a handful of options. Figure 1. Integrated Hierarchical Framework. In...computational structural and computational fluid modeling. For the structural analysis tool we used McIntosh Structural Dynamics’ finite element code CNEVAL

Leveraging Multi-Fidelity Models for Flexible Wing Systems

DTIC Science & Technology

2014-05-01

includes cataloging and defining of the various characteristics of insect wing morphology . His naming conventions of the venation are still in...J., 1992. Functional Morphology of Insect Wings. Annu. Rev. Entomol. 37, 113–140. doi:10.1146/annurev.en.37.010192.000553 Approved for public...FIGURES Figure Page Figure 1: Schematic illustration of a two-dimensional wing profile as a representative cross- section of an insect wing

Multi-fidelity uncertainty quantification in large-scale predictive simulations of turbulent flow

NASA Astrophysics Data System (ADS)

Geraci, Gianluca; Jofre-Cruanyes, Lluis; Iaccarino, Gianluca

2017-11-01

The performance characterization of complex engineering systems often relies on accurate, but computationally intensive numerical simulations. It is also well recognized that in order to obtain a reliable numerical prediction the propagation of uncertainties needs to be included. Therefore, Uncertainty Quantification (UQ) plays a fundamental role in building confidence in predictive science. Despite the great improvement in recent years, even the more advanced UQ algorithms are still limited to fairly simplified applications and only moderate parameter dimensionality. Moreover, in the case of extremely large dimensionality, sampling methods, i.e. Monte Carlo (MC) based approaches, appear to be the only viable alternative. In this talk we describe and compare a family of approaches which aim to accelerate the convergence of standard MC simulations. These methods are based on hierarchies of generalized numerical resolutions (multi-level) or model fidelities (multi-fidelity), and attempt to leverage the correlation between Low- and High-Fidelity (HF) models to obtain a more accurate statistical estimator without introducing additional HF realizations. The performance of these methods are assessed on an irradiated particle laden turbulent flow (PSAAP II solar energy receiver). This investigation was funded by the United States Department of Energy's (DoE) National Nuclear Security Administration (NNSA) under the Predicitive Science Academic Alliance Program (PSAAP) II at Stanford University.

Development of a Multifidelity Approach to Acoustic Liner Impedance Eduction

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Jones, Michael G.

2017-01-01

The use of acoustic liners has proven to be extremely effective in reducing aircraft engine fan noise transmission/radiation. However, the introduction of advanced fan designs and shorter engine nacelles has highlighted a need for novel acoustic liner designs that provide increased fan noise reduction over a broader frequency range. To achieve aggressive noise reduction goals, advanced broadband liner designs, such as zone liners and variable impedance liners, will likely depart from conventional uniform impedance configurations. Therefore, educing the impedance of these axial- and/or spanwise-variable impedance liners will require models that account for three-dimensional effects, thereby increasing computational expense. Thus, it would seem advantageous to investigate the use of multifidelity modeling approaches to impedance eduction for these advanced designs. This paper describes an extension of the use of the CDUCT-LaRC code to acoustic liner impedance eduction. The proposed approach is applied to a hardwall insert and conventional liner using simulated data. Educed values compare well with those educed using two extensively tested and validated approaches. The results are very promising and provide justification to further pursue the complementary use of CDUCT-LaRC with the currently used finite element codes to increase the efficiency of the eduction process for configurations involving three-dimensional effects.

Improving the Aircraft Design Process Using Web-Based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.; Follen, Gregory J. (Technical Monitor)

2000-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and multifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Error correction in multi-fidelity molecular dynamics simulations using functional uncertainty quantification

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

Reeve, Samuel Temple; Strachan, Alejandro, E-mail: strachan@purdue.edu

We use functional, Fréchet, derivatives to quantify how thermodynamic outputs of a molecular dynamics (MD) simulation depend on the potential used to compute atomic interactions. Our approach quantifies the sensitivity of the quantities of interest with respect to the input functions as opposed to its parameters as is done in typical uncertainty quantification methods. We show that the functional sensitivity of the average potential energy and pressure in isothermal, isochoric MD simulations using Lennard–Jones two-body interactions can be used to accurately predict those properties for other interatomic potentials (with different functional forms) without re-running the simulations. This is demonstrated undermore » three different thermodynamic conditions, namely a crystal at room temperature, a liquid at ambient pressure, and a high pressure liquid. The method provides accurate predictions as long as the change in potential can be reasonably described to first order and does not significantly affect the region in phase space explored by the simulation. The functional uncertainty quantification approach can be used to estimate the uncertainties associated with constitutive models used in the simulation and to correct predictions if a more accurate representation becomes available.« less

Hybrid Wing Body Planform Design with Vehicle Sketch Pad

NASA Technical Reports Server (NTRS)

Wells, Douglas P.; Olson, Erik D.

2011-01-01

The objective of this paper was to provide an update on NASA s current tools for design and analysis of hybrid wing body (HWB) aircraft with an emphasis on Vehicle Sketch Pad (VSP). NASA started HWB analysis using the Flight Optimization System (FLOPS). That capability is enhanced using Phoenix Integration's ModelCenter(Registered TradeMark). Model Center enables multifidelity analysis tools to be linked as an integrated structure. Two major components are linked to FLOPS as an example; a planform discretization tool and VSP. The planform discretization tool ensures the planform is smooth and continuous. VSP is used to display the output geometry. This example shows that a smooth & continuous HWB planform can be displayed as a three-dimensional model and rapidly sized and analyzed.

Design and multifidelity analysis of dual mode scramjet compression system using coupled NPSS and fluent simulation

NASA Astrophysics Data System (ADS)

Vijayakumar, Nandakumar

Hypersonic airbreathing engines mark a potential future development of the aerospace industry and immense efforts have been taken in gaining knowledge in them for the past decades. The physical phenomenon occurring at the hypersonic flow regime makes the design and performance prediction of a scramjet engine hard. Though cutting-edge simulation tools fight their way toward accurate prediction of the environment, the time consumed by the entire process in designing and analyzing a scramjet engine and its component may be exorbitant. A multi-fidelity approach for designing a scramjet with a cruising Mach number of 6 is detailed in this research where high-order simulations are applied according to the physics involved in the component. Two state-of-the-art simulation tools were used to take the aerodynamic and propulsion disciplines into account for realistic prediction of the individual components as well as the entire scramjet. The specific goal of this research is to create a virtual environment to design and analyze a hypersonic, two-dimensional, planar inlet and isolator to check its operability for a dual-mode scramjet engine. The dual mode scramjet engine starts at a Mach number of 3.5 where it operates as a ramjet and accelerates to Mach 6 to be operated as a scramjet engine. The intercomponent interaction between the compression components with the rest of the engine is studied by varying the fidelity of the numerical simulation according to the complexity of the situation. Efforts have been taken to track the transition Mach number as it switches from ramjet to scramjet. A complete scramjet assembly was built using the Numerical Propulsion Simulation System (NPSS) and the performance of the engine was evaluated for various scenarios. Different numerical techniques were opted for varying the fidelity of the analysis with the highest fidelity consisting of 2D RANS CFD simulation. The interaction between the NPSS elements with the CFD solver is governed by the top-level assembly solver of NPSS. The importance of intercomponent interactions are discussed. The methodology used in this research for design and analysis, should add up to provide an efficient way for estimating the design and off-design operating modes of a dual mode scramjet engine.

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

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

He, Xu; Tuo, Rui; Jeff Wu, C. F.

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

DOE PAGES

He, Xu; Tuo, Rui; Jeff Wu, C. F.

2017-01-31

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Wind Plant Power Optimization and Control under Uncertainty

NASA Astrophysics Data System (ADS)

Jha, Pankaj; Ulker, Demet; Hutchings, Kyle; Oxley, Gregory

2017-11-01

The development of optimized cooperative wind plant control involves the coordinated operation of individual turbines co-located within a wind plant to improve the overall power production. This is typically achieved by manipulating the trajectory and intensity of wake interactions between nearby turbines, thereby reducing wake losses. However, there are various types of uncertainties involved, such as turbulent inflow and microscale and turbine model input parameters. In a recent NREL-Envision collaboration, a controller that performs wake steering was designed and implemented for the Longyuan Rudong offshore wind plant in Jiangsu, China. The Rudong site contains 25 Envision EN136-4 MW turbines, of which a subset was selected for the field test campaign consisting of the front two rows for the northeasterly wind direction. In the first row, a turbine was selected as the reference turbine, providing comparison power data, while another was selected as the controlled turbine. This controlled turbine wakes three different turbines in the second row depending on the wind direction. A yaw misalignment strategy was designed using Envision's GWCFD, a multi-fidelity plant-scale CFD tool based on SOWFA with a generalized actuator disc (GAD) turbine model, which, in turn, was used to tune NREL's FLORIS model used for wake steering and yaw control optimization. The presentation will account for some associated uncertainties, such as those in atmospheric turbulence and wake profile.

Method of model reduction and multifidelity models for solute transport in random layered porous media

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

Xu, Zhijie; Tartakovsky, Alexandre M.

This work presents a hierarchical model for solute transport in bounded layered porous media with random permeability. The model generalizes the Taylor-Aris dispersion theory to stochastic transport in random layered porous media with a known velocity covariance function. In the hierarchical model, we represent (random) concentration in terms of its cross-sectional average and a variation function. We derive a one-dimensional stochastic advection-dispersion-type equation for the average concentration and a stochastic Poisson equation for the variation function, as well as expressions for the effective velocity and dispersion coefficient. We observe that velocity fluctuations enhance dispersion in a non-monotonic fashion: the dispersionmore » initially increases with correlation length λ, reaches a maximum, and decreases to zero at infinity. Maximum enhancement can be obtained at the correlation length about 0.25 the size of the porous media perpendicular to flow.« less

Gaussian functional regression for output prediction: Model assimilation and experimental design

NASA Astrophysics Data System (ADS)

Nguyen, N. C.; Peraire, J.

2016-03-01

In this paper, we introduce a Gaussian functional regression (GFR) technique that integrates multi-fidelity models with model reduction to efficiently predict the input-output relationship of a high-fidelity model. The GFR method combines the high-fidelity model with a low-fidelity model to provide an estimate of the output of the high-fidelity model in the form of a posterior distribution that can characterize uncertainty in the prediction. A reduced basis approximation is constructed upon the low-fidelity model and incorporated into the GFR method to yield an inexpensive posterior distribution of the output estimate. As this posterior distribution depends crucially on a set of training inputs at which the high-fidelity models are simulated, we develop a greedy sampling algorithm to select the training inputs. Our approach results in an output prediction model that inherits the fidelity of the high-fidelity model and has the computational complexity of the reduced basis approximation. Numerical results are presented to demonstrate the proposed approach.

Overview of Current Activities in Combustion Instability

DTIC Science & Technology

2015-10-02

and avoid liquid rocket engine combustion stability problems Approach:  1) Develop a  SOA  combustion stability software package  called Stable...phase II will invest in Multifidelity Tools and Methodologies – CSTD will develop a SOA combustion stability software package called Stable Combustion

Scalable High-order Methods for Multi-Scale Problems: Analysis, Algorithms and Application

DTIC Science & Technology

2016-02-26

Karniadakis, “Resilient algorithms for reconstructing and simulating gappy flow fields in CFD ”, Fluid Dynamic Research, vol. 47, 051402, 2015. 2. Y. Yu, H...simulation, domain decomposition, CFD , gappy data, estimation theory, and gap-tooth algorithm. 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...objective of this project was to develop a general CFD framework for multifidelity simula- tions to target multiscale problems but also resilience in

Numerical simulation and validation of helicopter blade-vortex interaction using coupled CFD/CSD and three levels of aerodynamic modeling

NASA Astrophysics Data System (ADS)

Amiraux, Mathieu

Rotorcraft Blade-Vortex Interaction (BVI) remains one of the most challenging flow phenomenon to simulate numerically. Over the past decade, the HART-II rotor test and its extensive experimental dataset has been a major database for validation of CFD codes. Its strong BVI signature, with high levels of intrusive noise and vibrations, makes it a difficult test for computational methods. The main challenge is to accurately capture and preserve the vortices which interact with the rotor, while predicting correct blade deformations and loading. This doctoral dissertation presents the application of a coupled CFD/CSD methodology to the problem of helicopter BVI and compares three levels of fidelity for aerodynamic modeling: a hybrid lifting-line/free-wake (wake coupling) method, with modified compressible unsteady model; a hybrid URANS/free-wake method; and a URANS-based wake capturing method, using multiple overset meshes to capture the entire flow field. To further increase numerical correlation, three helicopter fuselage models are implemented in the framework. The first is a high resolution 3D GPU panel code; the second is an immersed boundary based method, with 3D elliptic grid adaption; the last one uses a body-fitted, curvilinear fuselage mesh. The main contribution of this work is the implementation and systematic comparison of multiple numerical methods to perform BVI modeling. The trade-offs between solution accuracy and computational cost are highlighted for the different approaches. Various improvements have been made to each code to enhance physical fidelity, while advanced technologies, such as GPU computing, have been employed to increase efficiency. The resulting numerical setup covers all aspects of the simulation creating a truly multi-fidelity and multi-physics framework. Overall, the wake capturing approach showed the best BVI phasing correlation and good blade deflection predictions, with slightly under-predicted aerodynamic loading magnitudes. However, it proved to be much more expensive than the other two methods. Wake coupling with RANS solver had very good loading magnitude predictions, and therefore good acoustic intensities, with acceptable computational cost. The lifting-line based technique often had over-predicted aerodynamic levels, due to the degree of empiricism of the model, but its very short run-times, thanks to GPU technology, makes it a very attractive approach.

Multifidelity, multidisciplinary optimization of turbomachines with shock interaction

NASA Astrophysics Data System (ADS)

Joly, Michael Marie

Research on high-speed air-breathing propulsion aims at developing aircraft with antipodal range and space access. Before reaching high speed at high altitude, the flight vehicle needs to accelerate from takeoff to scramjet takeover. Air turbo rocket engines combine turbojet and rocket engine cycles to provide the necessary thrust in the so-called low-speed regime. Challenges related to turbomachinery components are multidisciplinary, since both the high compression ratio compressor and the powering high-pressure turbine operate in the transonic regime in compact environments with strong shock interactions. Besides, lightweight is vital to avoid hindering the scramjet operation. Recent progress in evolutionary computing provides aerospace engineers with robust and efficient optimization algorithms to address concurrent objectives. The present work investigates Multidisciplinary Design Optimization (MDO) of innovative transonic turbomachinery components. Inter-stage aerodynamic shock interaction in turbomachines are known to generate high-cycle fatigue on the rotor blades compromising their structural integrity. A soft-computing strategy is proposed to mitigate the vane downstream distortion, and shown to successfully attenuate the unsteady forcing on the rotor of a high-pressure turbine. Counter-rotation offers promising prospects to reduce the weight of the machine, with fewer stages and increased load per row. An integrated approach based on increasing level of fidelity and aero-structural coupling is then presented and allows achieving a highly loaded compact counter-rotating compressor.

Aeromechanics and Vehicle Configuration Demonstrations. Volume 2: Understanding Vehicle Sizing, Aeromechanics and Configuration Trades, Risks, and Issues for Next-Generations Access to Space Vehicles

DTIC Science & Technology

2014-01-01

and proportional correctors. The weighting function evaluates nearby data samples to determine the utility of each correction style , eliminating the...sparse methods may be of use. As for other multi-fidelity techniques, true cokriging in the style described by geo-statisticians[93] is beyond the...sampling style between sampling points predicted to fall near the contour and sampling points predicted to be farther from the contour but with

Initial Integration of Noise Prediction Tools for Acoustic Scattering Effects

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Burley, Casey L.; Tinetti, Ana; Rawls, John W.

2008-01-01

This effort provides an initial glimpse at NASA capabilities available in predicting the scattering of fan noise from a non-conventional aircraft configuration. The Aircraft NOise Prediction Program, Fast Scattering Code, and the Rotorcraft Noise Model were coupled to provide increased fidelity models of scattering effects on engine fan noise sources. The integration of these codes led to the identification of several keys issues entailed in applying such multi-fidelity approaches. In particular, for prediction at noise certification points, the inclusion of distributed sources leads to complications with the source semi-sphere approach. Computational resource requirements limit the use of the higher fidelity scattering code to predict radiated sound pressure levels for full scale configurations at relevant frequencies. And, the ability to more accurately represent complex shielding surfaces in current lower fidelity models is necessary for general application to scattering predictions. This initial step in determining the potential benefits/costs of these new methods over the existing capabilities illustrates a number of the issues that must be addressed in the development of next generation aircraft system noise prediction tools.

Surrogate based wind farm layout optimization using manifold mapping

NASA Astrophysics Data System (ADS)

Kaja Kamaludeen, Shaafi M.; van Zuijle, Alexander; Bijl, Hester

2016-09-01

High computational cost associated with the high fidelity wake models such as RANS or LES serves as a primary bottleneck to perform a direct high fidelity wind farm layout optimization (WFLO) using accurate CFD based wake models. Therefore, a surrogate based multi-fidelity WFLO methodology (SWFLO) is proposed. The surrogate model is built using an SBO method referred as manifold mapping (MM). As a verification, optimization of spacing between two staggered wind turbines was performed using the proposed surrogate based methodology and the performance was compared with that of direct optimization using high fidelity model. Significant reduction in computational cost was achieved using MM: a maximum computational cost reduction of 65%, while arriving at the same optima as that of direct high fidelity optimization. The similarity between the response of models, the number of mapping points and its position, highly influences the computational efficiency of the proposed method. As a proof of concept, realistic WFLO of a small 7-turbine wind farm is performed using the proposed surrogate based methodology. Two variants of Jensen wake model with different decay coefficients were used as the fine and coarse model. The proposed SWFLO method arrived at the same optima as that of the fine model with very less number of fine model simulations.

Multi-Fidelity Simulation of a Turbofan Engine With Results Zoomed Into Mini-Maps for a Zero-D Cycle Simulation

NASA Technical Reports Server (NTRS)

Turner, Mark G.; Reed, John A.; Ryder, Robert; Veres, Joseph P.

2004-01-01

A Zero-D cycle simulation of the GE90-94B high bypass turbofan engine has been achieved utilizing mini-maps generated from a high-fidelity simulation. The simulation utilizes the Numerical Propulsion System Simulation (NPSS) thermodynamic cycle modeling system coupled to a high-fidelity full-engine model represented by a set of coupled 3D computational fluid dynamic (CFD) component models. Boundary conditions from the balanced, steady state cycle model are used to define component boundary conditions in the full-engine model. Operating characteristics of the 3D component models are integrated into the cycle model via partial performance maps generated from the CFD flow solutions using one-dimensional mean line turbomachinery programs. This paper highlights the generation of the high-pressure compressor, booster, and fan partial performance maps, as well as turbine maps for the high pressure and low pressure turbine. These are actually "mini-maps" in the sense that they are developed only for a narrow operating range of the component. Results are compared between actual cycle data at a take-off condition and the comparable condition utilizing these mini-maps. The mini-maps are also presented with comparison to actual component data where possible.

A review of surrogate models and their application to groundwater modeling

NASA Astrophysics Data System (ADS)

Asher, M. J.; Croke, B. F. W.; Jakeman, A. J.; Peeters, L. J. M.

2015-08-01

The spatially and temporally variable parameters and inputs to complex groundwater models typically result in long runtimes which hinder comprehensive calibration, sensitivity, and uncertainty analysis. Surrogate modeling aims to provide a simpler, and hence faster, model which emulates the specified output of a more complex model in function of its inputs and parameters. In this review paper, we summarize surrogate modeling techniques in three categories: data-driven, projection, and hierarchical-based approaches. Data-driven surrogates approximate a groundwater model through an empirical model that captures the input-output mapping of the original model. Projection-based models reduce the dimensionality of the parameter space by projecting the governing equations onto a basis of orthonormal vectors. In hierarchical or multifidelity methods the surrogate is created by simplifying the representation of the physical system, such as by ignoring certain processes, or reducing the numerical resolution. In discussing the application to groundwater modeling of these methods, we note several imbalances in the existing literature: a large body of work on data-driven approaches seemingly ignores major drawbacks to the methods; only a fraction of the literature focuses on creating surrogates to reproduce outputs of fully distributed groundwater models, despite these being ubiquitous in practice; and a number of the more advanced surrogate modeling methods are yet to be fully applied in a groundwater modeling context.

Impact of Data Assimilation on Cost-Accuracy Tradeoff in Multi-Fidelity Models at the Example of an Infiltration Problem

NASA Astrophysics Data System (ADS)

Sinsbeck, Michael; Tartakovsky, Daniel

2015-04-01

Infiltration into top soil can be described by alternative models with different degrees of fidelity: Richards equation and the Green-Ampt model. These models typically contain uncertain parameters and forcings, rendering predictions of the state variables uncertain as well. Within the probabilistic framework, solutions of these models are given in terms of their probability density functions (PDFs) that, in the presence of data, can be treated as prior distributions. The assimilation of soil moisture data into model predictions, e.g., via a Bayesian updating of solution PDFs, poses a question of model selection: Given a significant difference in computational cost, is a lower-fidelity model preferable to its higher-fidelity counter-part? We investigate this question in the context of heterogeneous porous media, whose hydraulic properties are uncertain. While low-fidelity (reduced-complexity) models introduce a model error, their moderate computational cost makes it possible to generate more realizations, which reduces the (e.g., Monte Carlo) sampling or stochastic error. The ratio between these two errors determines the model with the smallest total error. We found assimilation of measurements of a quantity of interest (the soil moisture content, in our example) to decrease the model error, increasing the probability that the predictive accuracy of a reduced-complexity model does not fall below that of its higher-fidelity counterpart.

Multilevel UQ strategies for large-scale multiphysics applications: PSAAP II solar receiver

NASA Astrophysics Data System (ADS)

Jofre, Lluis; Geraci, Gianluca; Iaccarino, Gianluca

2017-06-01

Uncertainty quantification (UQ) plays a fundamental part in building confidence in predictive science. Of particular interest is the case of modeling and simulating engineering applications where, due to the inherent complexity, many uncertainties naturally arise, e.g. domain geometry, operating conditions, errors induced by modeling assumptions, etc. In this regard, one of the pacing items, especially in high-fidelity computational fluid dynamics (CFD) simulations, is the large amount of computing resources typically required to propagate incertitude through the models. Upcoming exascale supercomputers will significantly increase the available computational power. However, UQ approaches cannot entrust their applicability only on brute force Monte Carlo (MC) sampling; the large number of uncertainty sources and the presence of nonlinearities in the solution will make straightforward MC analysis unaffordable. Therefore, this work explores the multilevel MC strategy, and its extension to multi-fidelity and time convergence, to accelerate the estimation of the effect of uncertainties. The approach is described in detail, and its performance demonstrated on a radiated turbulent particle-laden flow case relevant to solar energy receivers (PSAAP II: Particle-laden turbulence in a radiation environment). Investigation funded by DoE's NNSA under PSAAP II.

Numerical Propulsion System Simulation Architecture

NASA Technical Reports Server (NTRS)

Naiman, Cynthia G.

2004-01-01

The Numerical Propulsion System Simulation (NPSS) is a framework for performing analysis of complex systems. Because the NPSS was developed using the object-oriented paradigm, the resulting architecture is an extensible and flexible framework that is currently being used by a diverse set of participants in government, academia, and the aerospace industry. NPSS is being used by over 15 different institutions to support rockets, hypersonics, power and propulsion, fuel cells, ground based power, and aerospace. Full system-level simulations as well as subsystems may be modeled using NPSS. The NPSS architecture enables the coupling of analyses at various levels of detail, which is called numerical zooming. The middleware used to enable zooming and distributed simulations is the Common Object Request Broker Architecture (CORBA). The NPSS Developer's Kit offers tools for the developer to generate CORBA-based components and wrap codes. The Developer's Kit enables distributed multi-fidelity and multi-discipline simulations, preserves proprietary and legacy codes, and facilitates addition of customized codes. The platforms supported are PC, Linux, HP, Sun, and SGI.

A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme

NASA Astrophysics Data System (ADS)

Ghoman, Satyajit S.

The main objective of this research is to develop an innovative multi-fidelity multi-disciplinary design, analysis and optimization suite that integrates certain solution generation codes and newly developed innovative tools to improve the overall optimization process. The research performed herein is divided into two parts: (1) the development of an MDAO framework by integration of variable fidelity physics-based computational codes, and (2) enhancements to such a framework by incorporating innovative features extending its robustness. The first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M 3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M 3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE. The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M 3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of fitness-driven retention. This strategy capitalizes on the advantages of evolutionary algorithm as well as POD-based reduced order modeling, while overcoming the shortcomings inherent with these techniques. When linked with M3 DOE, this strategy offers a computationally efficient methodology for problems with high level of complexity and a challenging design-space. This newly developed framework is demonstrated for its robustness on a nonconventional supersonic tailless air vehicle wing shape optimization problem.

Building a Practical Natural Laminar Flow Design Capability

NASA Technical Reports Server (NTRS)

Campbell, Richard L.; Lynde, Michelle N.

2017-01-01

A preliminary natural laminar flow (NLF) design method that has been developed and applied to supersonic and transonic wings with moderate-to-high leading-edge sweeps at flight Reynolds numbers is further extended and evaluated in this paper. The modular design approach uses a knowledge-based design module linked with different flow solvers and boundary layer stability analysis methods to provide a multifidelity capability for NLF analysis and design. An assessment of the effects of different options for stability analysis is included using pressures and geometry from an NLF wing designed for the Common Research Model (CRM). Several extensions to the design module are described, including multiple new approaches to design for controlling attachment line contamination and transition. Finally, a modification to the NLF design algorithm that allows independent control of Tollmien-Schlichting (TS) and cross flow (CF) modes is proposed. A preliminary evaluation of the TS-only option applied to the design of an NLF nacelle for the CRM is performed that includes the use of a low-fidelity stability analysis directly in the design module.

An efficient Bayesian data-worth analysis using a multilevel Monte Carlo method

NASA Astrophysics Data System (ADS)

Lu, Dan; Ricciuto, Daniel; Evans, Katherine

2018-03-01

Improving the understanding of subsurface systems and thus reducing prediction uncertainty requires collection of data. As the collection of subsurface data is costly, it is important that the data collection scheme is cost-effective. Design of a cost-effective data collection scheme, i.e., data-worth analysis, requires quantifying model parameter, prediction, and both current and potential data uncertainties. Assessment of these uncertainties in large-scale stochastic subsurface hydrological model simulations using standard Monte Carlo (MC) sampling or surrogate modeling is extremely computationally intensive, sometimes even infeasible. In this work, we propose an efficient Bayesian data-worth analysis using a multilevel Monte Carlo (MLMC) method. Compared to the standard MC that requires a significantly large number of high-fidelity model executions to achieve a prescribed accuracy in estimating expectations, the MLMC can substantially reduce computational costs using multifidelity approximations. Since the Bayesian data-worth analysis involves a great deal of expectation estimation, the cost saving of the MLMC in the assessment can be outstanding. While the proposed MLMC-based data-worth analysis is broadly applicable, we use it for a highly heterogeneous two-phase subsurface flow simulation to select an optimal candidate data set that gives the largest uncertainty reduction in predicting mass flow rates at four production wells. The choices made by the MLMC estimation are validated by the actual measurements of the potential data, and consistent with the standard MC estimation. But compared to the standard MC, the MLMC greatly reduces the computational costs.

Variable-Complexity Multidisciplinary Optimization on Parallel Computers

NASA Technical Reports Server (NTRS)

Grossman, Bernard; Mason, William H.; Watson, Layne T.; Haftka, Raphael T.

1998-01-01

This report covers work conducted under grant NAG1-1562 for the NASA High Performance Computing and Communications Program (HPCCP) from December 7, 1993, to December 31, 1997. The objective of the research was to develop new multidisciplinary design optimization (MDO) techniques which exploit parallel computing to reduce the computational burden of aircraft MDO. The design of the High-Speed Civil Transport (HSCT) air-craft was selected as a test case to demonstrate the utility of our MDO methods. The three major tasks of this research grant included: development of parallel multipoint approximation methods for the aerodynamic design of the HSCT, use of parallel multipoint approximation methods for structural optimization of the HSCT, mathematical and algorithmic development including support in the integration of parallel computation for items (1) and (2). These tasks have been accomplished with the development of a response surface methodology that incorporates multi-fidelity models. For the aerodynamic design we were able to optimize with up to 20 design variables using hundreds of expensive Euler analyses together with thousands of inexpensive linear theory simulations. We have thereby demonstrated the application of CFD to a large aerodynamic design problem. For the predicting structural weight we were able to combine hundreds of structural optimizations of refined finite element models with thousands of optimizations based on coarse models. Computations have been carried out on the Intel Paragon with up to 128 nodes. The parallel computation allowed us to perform combined aerodynamic-structural optimization using state of the art models of a complex aircraft configurations.

A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses

NASA Astrophysics Data System (ADS)

Yondo, Raul; Andrés, Esther; Valero, Eusebio

2018-01-01

Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-order) aerodynamic models or flight testing are some of the fundamental but complex steps in the various design phases of recent civil transport aircrafts. Current aircraft aerodynamic designs have increase in complexity (multidisciplinary, multi-objective or multi-fidelity) and need to address the challenges posed by the nonlinearity of the objective functions and constraints, uncertainty quantification in aerodynamic problems or the restrained computational budgets. With the aim to reduce the computational burden and generate low-cost but accurate models that mimic those full order models at different values of the design variables, Recent progresses have witnessed the introduction, in real-time and many-query analyses, of surrogate-based approaches as rapid and cheaper to simulate models. In this paper, a comprehensive and state-of-the art survey on common surrogate modeling techniques and surrogate-based optimization methods is given, with an emphasis on models selection and validation, dimensionality reduction, sensitivity analyses, constraints handling or infill and stopping criteria. Benefits, drawbacks and comparative discussions in applying those methods are described. Furthermore, the paper familiarizes the readers with surrogate models that have been successfully applied to the general field of fluid dynamics, but not yet in the aerospace industry. Additionally, the review revisits the most popular sampling strategies used in conducting physical and simulation-based experiments in aircraft aerodynamic design. Attractive or smart designs infrequently used in the field and discussions on advanced sampling methodologies are presented, to give a glance on the various efficient possibilities to a priori sample the parameter space. Closing remarks foster on future perspectives, challenges and shortcomings associated with the use of surrogate models by aircraft industrial aerodynamicists, despite their increased interest among the research communities.

Multi-fidelity and multi-disciplinary design optimization of supersonic business jets

NASA Astrophysics Data System (ADS)

Choi, Seongim

Supersonic jets have been drawing great attention after the end of service for the Concorde was announced on April of 2003. It is believed, however, that civilian supersonic aircraft may make a viable return in the business jet market. This thesis focuses on the design optimization of feasible supersonic business jet configurations. Preliminary design techniques for mitigation of ground sonic boom are investigated while ensuring that all relevant disciplinary constraints are satisfied (including aerodynamic performance, propulsion, stability & control and structures.) In order to achieve reasonable confidence in the resulting designs, high-fidelity simulations are required, making the entire design process both expensive and complex. In order to minimize the computational cost, surrogate/approximate models are constructed using a hierarchy of different fidelity analysis tools including PASS, A502/Panair and Euler/NS codes. Direct search methods such as Genetic Algorithms (GAs) and a nonlinear SIMPLEX are employed to designs in searches of large and noisy design spaces. A local gradient-based search method can be combined with these global search methods for small modifications of candidate optimum designs. The Mesh Adaptive Direct Search (MADS) method can also be used to explore the design space using a solution-adaptive grid refinement approach. These hybrid approaches, both in search methodology and surrogate model construction, are shown to result in designs with reductions in sonic boom and improved aerodynamic performance.

Optimizing Discharge Capacity of Li-O 2 Batteries by Design of Air-Electrode Porous Structure: Multifidelity Modeling and Optimization

DOE PAGES

Pan, Wenxiao; Yang, Xiu; Bao, Jie; ...

2017-01-01

We develop a new mathematical framework to study the optimal design of air electrode microstructures for lithium-oxygen (Li-O2) batteries. It can eectively reduce the number of expensive experiments for testing dierent air-electrodes, thereby minimizing the cost in the design of Li-O2 batteries. The design parameters to characterize an air-electrode microstructure include the porosity, surface-to-volume ratio, and parameters associated with the pore-size distribution. A surrogate model (also known as response surface) for discharge capacity is rst constructed as a function of these design parameters. The surrogate model is accurate and easy to evaluate such that an optimization can be performed basedmore » on it. In particular, a Gaussian process regression method, co-kriging, is employed due to its accuracy and eciency in predicting high-dimensional responses from a combination of multidelity data. Specically, a small amount of data from high-delity simulations are combined with a large number of data obtained from computationally ecient low-delity simulations. The high-delity simulation is based on a multiscale modeling approach that couples the microscale (pore-scale) and macroscale (device-scale) models. Whereas, the low-delity simulation is based on an empirical macroscale model. The constructed response surface provides quantitative understanding and prediction about how air electrode microstructures aect the discharge performance of Li-O2 batteries. The succeeding sensitivity analysis via Sobol indices and optimization via genetic algorithm ultimately oer a reliable guidance on the optimal design of air electrode microstructures. The proposed mathematical framework can be generalized to investigate other new energy storage techniques and materials.« less

Optimizing Discharge Capacity of Li-O 2 Batteries by Design of Air-Electrode Porous Structure: Multifidelity Modeling and Optimization

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

Pan, Wenxiao; Yang, Xiu; Bao, Jie

We develop a new mathematical framework to study the optimal design of air electrode microstructures for lithium-oxygen (Li-O2) batteries. It can eectively reduce the number of expensive experiments for testing dierent air-electrodes, thereby minimizing the cost in the design of Li-O2 batteries. The design parameters to characterize an air-electrode microstructure include the porosity, surface-to-volume ratio, and parameters associated with the pore-size distribution. A surrogate model (also known as response surface) for discharge capacity is rst constructed as a function of these design parameters. The surrogate model is accurate and easy to evaluate such that an optimization can be performed basedmore » on it. In particular, a Gaussian process regression method, co-kriging, is employed due to its accuracy and eciency in predicting high-dimensional responses from a combination of multidelity data. Specically, a small amount of data from high-delity simulations are combined with a large number of data obtained from computationally ecient low-delity simulations. The high-delity simulation is based on a multiscale modeling approach that couples the microscale (pore-scale) and macroscale (device-scale) models. Whereas, the low-delity simulation is based on an empirical macroscale model. The constructed response surface provides quantitative understanding and prediction about how air electrode microstructures aect the discharge performance of Li-O2 batteries. The succeeding sensitivity analysis via Sobol indices and optimization via genetic algorithm ultimately oer a reliable guidance on the optimal design of air electrode microstructures. The proposed mathematical framework can be generalized to investigate other new energy storage techniques and materials.« less

Initial Multidisciplinary Design and Analysis Framework

NASA Technical Reports Server (NTRS)

Ozoroski, L. P.; Geiselhart, K. A.; Padula, S. L.; Li, W.; Olson, E. D.; Campbell, R. L.; Shields, E. W.; Berton, J. J.; Gray, J. S.; Jones, S. M.;

The Airspace Concepts Evaluation System Architecture and System Plant

NASA Technical Reports Server (NTRS)

Windhorst, Robert; Meyn, Larry; Manikonda, Vikram; Carlos, Patrick; Capozzi, Brian

2006-01-01

The Airspace Concepts Evaluation System is a simulation of the National Airspace System. It includes models of flights, airports, airspaces, air traffic controls, traffic flow managements, and airline operation centers operating throughout the United States. It is used to predict system delays in response to future capacity and demand scenarios and perform benefits assessments of current and future airspace technologies and operational concepts. Facilitation of these studies requires that the simulation architecture supports plug and play of different air traffic control, traffic flow management, and airline operation center models and multi-fidelity modeling of flights, airports, and airspaces. The simulation is divided into two parts that are named, borrowing from classical control theory terminology, control and plant. The control consists of air traffic control, traffic flow management, and airline operation center models, and the plant consists of flight, airport, and airspace models. The plant can run open loop, in the absence of the control. However, undesired affects, such as conflicts and over congestions in the airspaces and airports, can occur. Different controls are applied, "plug and played", to the plant. A particular control is evaluated by analyzing how well it managed conflicts and congestions. Furthermore, the terminal area plants consist of models of airports and terminal airspaces. Each model consists of a set of nodes and links which are connected by the user to form a network. Nodes model runways, fixes, taxi intersections, gates, and/or other points of interest, and links model taxiways, departure paths, and arrival paths. Metering, flow distribution, and sequencing functions can be applied at nodes. Different fidelity model of how a flight transits are can be used by links. The fidelity of the model can be adjusted by the user by either changing the complexity of the node/link network-or the way that the link models how the flights transit from one node to the other.

Efficient Data-Worth Analysis Using a Multilevel Monte Carlo Method Applied in Oil Reservoir Simulations

NASA Astrophysics Data System (ADS)

Lu, D.; Ricciuto, D. M.; Evans, K. J.

2017-12-01

Data-worth analysis plays an essential role in improving the understanding of the subsurface system, in developing and refining subsurface models, and in supporting rational water resources management. However, data-worth analysis is computationally expensive as it requires quantifying parameter uncertainty, prediction uncertainty, and both current and potential data uncertainties. Assessment of these uncertainties in large-scale stochastic subsurface simulations using standard Monte Carlo (MC) sampling or advanced surrogate modeling is extremely computationally intensive, sometimes even infeasible. In this work, we propose efficient Bayesian analysis of data-worth using a multilevel Monte Carlo (MLMC) method. Compared to the standard MC that requires a significantly large number of high-fidelity model executions to achieve a prescribed accuracy in estimating expectations, the MLMC can substantially reduce the computational cost with the use of multifidelity approximations. As the data-worth analysis involves a great deal of expectation estimations, the cost savings from MLMC in the assessment can be very outstanding. While the proposed MLMC-based data-worth analysis is broadly applicable, we use it to a highly heterogeneous oil reservoir simulation to select an optimal candidate data set that gives the largest uncertainty reduction in predicting mass flow rates at four production wells. The choices made by the MLMC estimation are validated by the actual measurements of the potential data, and consistent with the estimation obtained from the standard MC. But compared to the standard MC, the MLMC greatly reduces the computational costs in the uncertainty reduction estimation, with up to 600 days cost savings when one processor is used.

Impact and Crashworthiness Characteristics of Venera Type Landers for Future Venus Missions

NASA Technical Reports Server (NTRS)

Schroeder, Kevin; Bayandor, Javid; Samareh, Jamshid

2016-01-01

In this paper an in-depth investigation of the structural design of the Venera 9-14 landers is explored. A complete reverse engineering of the Venera lander was required. The lander was broken down into its fundamental components and analyzed. This provided in-sights into the hidden features of the design. A trade study was performed to find the sensitivity of the lander's overall mass to the variation of several key parameters. For the lander's legs, the location, length, configuration, and number are all parameterized. The size of the impact ring, the radius of the drag plate, and other design features are also parameterized, and all of these features were correlated to the change of mass of the lander. A multi-fidelity design tool used for further investigation of the parameterized lander was developed. As a design was passed down from one level to the next, the fidelity, complexity, accuracy, and run time of the model increased. The low-fidelity model was a highly nonlinear analytical model developed to rapidly predict the mass of each design. The medium and high fidelity models utilized an explicit finite element framework to investigate the performance of various landers upon impact with the surface under a range of landing conditions. This methodology allowed for a large variety of designs to be investigated by the analytical model, which identified designs with the optimum structural mass to payload ratio. As promising designs emerged, investigations in the following higher fidelity models were focused on establishing their reliability and crashworthiness. The developed design tool efficiently modelled and tested the best concepts for any scenario based on critical Venusian mission requirements and constraints. Through this program, the strengths and weaknesses inherent in the Venera-Type landers were thoroughly investigated. Key features identified for the design of robust landers will be used as foundations for the development of the next generation of landers for future exploration missions to Venus.

Numerical Propulsion System Simulation

NASA Technical Reports Server (NTRS)

Naiman, Cynthia

2006-01-01

The NASA Glenn Research Center, in partnership with the aerospace industry, other government agencies, and academia, is leading the effort to develop an advanced multidisciplinary analysis environment for aerospace propulsion systems called the Numerical Propulsion System Simulation (NPSS). NPSS is a framework for performing analysis of complex systems. The initial development of NPSS focused on the analysis and design of airbreathing aircraft engines, but the resulting NPSS framework may be applied to any system, for example: aerospace, rockets, hypersonics, power and propulsion, fuel cells, ground based power, and even human system modeling. NPSS provides increased flexibility for the user, which reduces the total development time and cost. It is currently being extended to support the NASA Aeronautics Research Mission Directorate Fundamental Aeronautics Program and the Advanced Virtual Engine Test Cell (AVETeC). NPSS focuses on the integration of multiple disciplines such as aerodynamics, structure, and heat transfer with numerical zooming on component codes. Zooming is the coupling of analyses at various levels of detail. NPSS development includes capabilities to facilitate collaborative engineering. The NPSS will provide improved tools to develop custom components and to use capability for zooming to higher fidelity codes, coupling to multidiscipline codes, transmitting secure data, and distributing simulations across different platforms. These powerful capabilities extend NPSS from a zero-dimensional simulation tool to a multi-fidelity, multidiscipline system-level simulation tool for the full development life cycle.

An improved multilevel Monte Carlo method for estimating probability distribution functions in stochastic oil reservoir simulations

DOE PAGES

Lu, Dan; Zhang, Guannan; Webster, Clayton G.; ...

2016-12-30

In this paper, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challengemore » in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.« less

Modeling methods for merging computational and experimental aerodynamic pressure data

NASA Astrophysics Data System (ADS)

Haderlie, Jacob C.

This research describes a process to model surface pressure data sets as a function of wing geometry from computational and wind tunnel sources and then merge them into a single predicted value. The described merging process will enable engineers to integrate these data sets with the goal of utilizing the advantages of each data source while overcoming the limitations of both; this provides a single, combined data set to support analysis and design. The main challenge with this process is accurately representing each data source everywhere on the wing. Additionally, this effort demonstrates methods to model wind tunnel pressure data as a function of angle of attack as an initial step towards a merging process that uses both location on the wing and flow conditions (e.g., angle of attack, flow velocity or Reynold's number) as independent variables. This surrogate model of pressure as a function of angle of attack can be useful for engineers that need to predict the location of zero-order discontinuities, e.g., flow separation or normal shocks. Because, to the author's best knowledge, there is no published, well-established merging method for aerodynamic pressure data (here, the coefficient of pressure Cp), this work identifies promising modeling and merging methods, and then makes a critical comparison of these methods. Surrogate models represent the pressure data for both data sets. Cubic B-spline surrogate models represent the computational simulation results. Machine learning and multi-fidelity surrogate models represent the experimental data. This research compares three surrogates for the experimental data (sequential--a.k.a. online--Gaussian processes, batch Gaussian processes, and multi-fidelity additive corrector) on the merits of accuracy and computational cost. The Gaussian process (GP) methods employ cubic B-spline CFD surrogates as a model basis function to build a surrogate model of the WT data, and this usage of the CFD surrogate in building the WT data could serve as a "merging" because the resulting WT pressure prediction uses information from both sources. In the GP approach, this model basis function concept seems to place more "weight" on the Cp values from the wind tunnel (WT) because the GP surrogate uses the CFD to approximate the WT data values. Conversely, the computationally inexpensive additive corrector method uses the CFD B-spline surrogate to define the shape of the spanwise distribution of the Cp while minimizing prediction error at all spanwise locations for a given arc length position; this, too, combines information from both sources to make a prediction of the 2-D WT-based Cp distribution, but the additive corrector approach gives more weight to the CFD prediction than to the WT data. Three surrogate models of the experimental data as a function of angle of attack are also compared for accuracy and computational cost. These surrogates are a single Gaussian process model (a single "expert"), product of experts, and generalized product of experts. The merging approach provides a single pressure distribution that combines experimental and computational data. The batch Gaussian process method provides a relatively accurate surrogate that is computationally acceptable, and can receive wind tunnel data from port locations that are not necessarily parallel to a variable direction. On the other hand, the sequential Gaussian process and additive corrector methods must receive a sufficient number of data points aligned with one direction, e.g., from pressure port bands (tap rows) aligned with the freestream. The generalized product of experts best represents wind tunnel pressure as a function of angle of attack, but at higher computational cost than the single expert approach. The format of the application data from computational and experimental sources in this work precluded the merging process from including flow condition variables (e.g., angle of attack) in the independent variables, so the merging process is only conducted in the wing geometry variables of arc length and span. The merging process of Cp data allows a more "hands-off" approach to aircraft design and analysis, (i.e., not as many engineers needed to debate the Cp distribution shape) and generates Cp predictions at any location on the wing. However, the cost with these benefits are engineer time (learning how to build surrogates), computational time in constructing the surrogates, and surrogate accuracy (surrogates introduce error into data predictions). This dissertation effort used the Trap Wing / First AIAA CFD High-Lift Prediction Workshop as a relevant transonic wing with a multi-element high-lift system, and this work identified that the batch GP model for the WT data and the B-spline surrogate for the CFD might best be combined using expert belief weights to describe Cp as a function of location on the wing element surface. (Abstract shortened by ProQuest.).

Numerical Propulsion System Simulation: A Common Tool for Aerospace Propulsion Being Developed

NASA Technical Reports Server (NTRS)

Follen, Gregory J.; Naiman, Cynthia G.

2001-01-01

The NASA Glenn Research Center is developing an advanced multidisciplinary analysis environment for aerospace propulsion systems called the Numerical Propulsion System Simulation (NPSS). This simulation is initially being used to support aeropropulsion in the analysis and design of aircraft engines. NPSS provides increased flexibility for the user, which reduces the total development time and cost. It is currently being extended to support the Aviation Safety Program and Advanced Space Transportation. NPSS focuses on the integration of multiple disciplines such as aerodynamics, structure, and heat transfer with numerical zooming on component codes. Zooming is the coupling of analyses at various levels of detail. NPSS development includes using the Common Object Request Broker Architecture (CORBA) in the NPSS Developer's Kit to facilitate collaborative engineering. The NPSS Developer's Kit will provide the tools to develop custom components and to use the CORBA capability for zooming to higher fidelity codes, coupling to multidiscipline codes, transmitting secure data, and distributing simulations across different platforms. These powerful capabilities will extend NPSS from a zero-dimensional simulation tool to a multifidelity, multidiscipline system-level simulation tool for the full life cycle of an engine.

Development and application of incrementally complex tools for wind turbine aerodynamics

NASA Astrophysics Data System (ADS)

Gundling, Christopher H.

Advances and availability of computational resources have made wind farm design using simulation tools a reality. Wind farms are battling two issues, affecting the cost of energy, that will make or break many future investments in wind energy. The most significant issue is the power reduction of downstream turbines operating in the wake of upstream turbines. The loss of energy from wind turbine wakes is difficult to predict and the underestimation of energy losses due to wakes has been a common problem throughout the industry. The second issue is a shorter lifetime of blades and past failures of gearboxes due to increased fluctuations in the unsteady loading of waked turbines. The overall goal of this research is to address these problems by developing a platform for a multi-fidelity wind turbine aerodynamic performance and wake prediction tool. Full-scale experiments in the field have dramatically helped researchers understand the unique issues inside a large wind farm, but experimental methods can only be used to a limited extent due to the cost of such field studies and the size of wind farms. The uncertainty of the inflow is another inherent drawback of field experiments. Therefore, computational fluid dynamics (CFD) predictions, strategically validated using carefully performed wind farm field campaigns, are becoming a more standard design practice. The developed CFD models include a blade element model (BEM) code with a free-vortex wake, an actuator disk or line based method with large eddy simulations (LES) and a fully resolved rotor based method with detached eddy simulations (DES) and adaptive mesh refinement (AMR). To create more realistic simulations, performance of a one-way coupling between different mesoscale atmospheric boundary layer (ABL) models and the three microscale CFD solvers is tested. These methods are validated using data from incrementally complex test cases that include the NREL Phase VI wind tunnel test, the Sexbierum wind farm and the Lillgrund offshore wind farm. By cross-comparing the lowest complexity free-vortex method with the higher complexity methods, a fast and accurate simulation tool has been generated that can perform wind farm simulations in a few hours.

Development of Adaptive Model Refinement (AMoR) for Multiphysics and Multifidelity Problems

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

Turinsky, Paul

This project investigated the development and utilization of Adaptive Model Refinement (AMoR) for nuclear systems simulation applications. AMoR refers to utilization of several models of physical phenomena which differ in prediction fidelity. If the highest fidelity model is judged to always provide or exceeded the desired fidelity, than if one can determine the difference in a Quantity of Interest (QoI) between the highest fidelity model and lower fidelity models, one could utilize the fidelity model that would just provide the magnitude of the QoI desired. Assuming lower fidelity models require less computational resources, in this manner computational efficiency can bemore » realized provided the QoI value can be accurately and efficiently evaluated. This work utilized Generalized Perturbation Theory (GPT) to evaluate the QoI, by convoluting the GPT solution with the residual of the highest fidelity model determined using the solution from lower fidelity models. Specifically, a reactor core neutronics problem and thermal-hydraulics problem were studied to develop and utilize AMoR. The highest fidelity neutronics model was based upon the 3D space-time, two-group, nodal diffusion equations as solved in the NESTLE computer code. Added to the NESTLE code was the ability to determine the time-dependent GPT neutron flux. The lower fidelity neutronics model was based upon the point kinetics equations along with utilization of a prolongation operator to determine the 3D space-time, two-group flux. The highest fidelity thermal-hydraulics model was based upon the space-time equations governing fluid flow in a closed channel around a heat generating fuel rod. The Homogenous Equilibrium Mixture (HEM) model was used for the fluid and Finite Difference Method was applied to both the coolant and fuel pin energy conservation equations. The lower fidelity thermal-hydraulic model was based upon the same equations as used for the highest fidelity model but now with coarse spatial meshing, corrected somewhat by employing effective fuel heat conduction values. The effectiveness of switching between the highest fidelity model and lower fidelity model as a function of time was assessed using the neutronics problem. Based upon work completed to date, one concludes that the time switching is effective in annealing out differences between the highest and lower fidelity solutions. The effectiveness of using a lower fidelity GPT solution, along with a prolongation operator, to estimate the QoI was also assessed. The utilization of a lower fidelity GPT solution was done in an attempt to avoid the high computational burden associated with solving for the highest fidelity GPT solution. Based upon work completed to date, one concludes that the lower fidelity adjoint solution is not sufficiently accurate with regard to estimating the QoI; however, a formulation has been revealed that may provide a path for addressing this shortcoming.« less

Progress Toward Efficient Laminar Flow Analysis and Design

NASA Technical Reports Server (NTRS)

Campbell, Richard L.; Campbell, Matthew L.; Streit, Thomas

2011-01-01

A multi-fidelity system of computer codes for the analysis and design of vehicles having extensive areas of laminar flow is under development at the NASA Langley Research Center. The overall approach consists of the loose coupling of a flow solver, a transition prediction method and a design module using shell scripts, along with interface modules to prepare the input for each method. This approach allows the user to select the flow solver and transition prediction module, as well as run mode for each code, based on the fidelity most compatible with the problem and available resources. The design module can be any method that designs to a specified target pressure distribution. In addition to the interface modules, two new components have been developed: 1) an efficient, empirical transition prediction module (MATTC) that provides n-factor growth distributions without requiring boundary layer information; and 2) an automated target pressure generation code (ATPG) that develops a target pressure distribution that meets a variety of flow and geometry constraints. The ATPG code also includes empirical estimates of several drag components to allow the optimization of the target pressure distribution. The current system has been developed for the design of subsonic and transonic airfoils and wings, but may be extendable to other speed ranges and components. Several analysis and design examples are included to demonstrate the current capabilities of the system.

Multidisciplinary design and optimization (MDO) methodology for the aircraft conceptual design

NASA Astrophysics Data System (ADS)

Iqbal, Liaquat Ullah

An integrated design and optimization methodology has been developed for the conceptual design of an aircraft. The methodology brings higher fidelity Computer Aided Design, Engineering and Manufacturing (CAD, CAE and CAM) Tools such as CATIA, FLUENT, ANSYS and SURFCAM into the conceptual design by utilizing Excel as the integrator and controller. The approach is demonstrated to integrate with many of the existing low to medium fidelity codes such as the aerodynamic panel code called CMARC and sizing and constraint analysis codes, thus providing the multi-fidelity capabilities to the aircraft designer. The higher fidelity design information from the CAD and CAE tools for the geometry, aerodynamics, structural and environmental performance is provided for the application of the structured design methods such as the Quality Function Deployment (QFD) and the Pugh's Method. The higher fidelity tools bring the quantitative aspects of a design such as precise measurements of weight, volume, surface areas, center of gravity (CG) location, lift over drag ratio, and structural weight, as well as the qualitative aspects such as external geometry definition, internal layout, and coloring scheme early in the design process. The performance and safety risks involved with the new technologies can be reduced by modeling and assessing their impact more accurately on the performance of the aircraft. The methodology also enables the design and evaluation of the novel concepts such as the blended (BWB) and the hybrid wing body (HWB) concepts. Higher fidelity computational fluid dynamics (CFD) and finite element analysis (FEA) allow verification of the claims for the performance gains in aerodynamics and ascertain risks of structural failure due to different pressure distribution in the fuselage as compared with the tube and wing design. The higher fidelity aerodynamics and structural models can lead to better cost estimates that help reduce the financial risks as well. This helps in achieving better designs with reduced risk in lesser time and cost. The approach is shown to eliminate the traditional boundary between the conceptual and the preliminary design stages, combining the two into one consolidated preliminary design phase. Several examples for the validation and utilization of the Multidisciplinary Design and Optimization (MDO) Tool are presented using missions for the Medium and High Altitude Long Range/Endurance Unmanned Aerial Vehicles (UAVs).

Inverse Design of Low-Boom Supersonic Concepts Using Reversed Equivalent-Area Targets

NASA Technical Reports Server (NTRS)

Li, Wu; Rallabhand, Sriam

2011-01-01

A promising path for developing a low-boom configuration is a multifidelity approach that (1) starts from a low-fidelity low-boom design, (2) refines the low-fidelity design with computational fluid dynamics (CFD) equivalent-area (Ae) analysis, and (3) improves the design with sonic-boom analysis by using CFD off-body pressure distributions. The focus of this paper is on the third step of this approach, in which the design is improved with sonic-boom analysis through the use of CFD calculations. A new inverse design process for off-body pressure tailoring is formulated and demonstrated with a low-boom supersonic configuration that was developed by using the mixed-fidelity design method with CFD Ae analysis. The new inverse design process uses the reverse propagation of the pressure distribution (dp/p) from a mid-field location to a near-field location, converts the near-field dp/p into an equivalent-area distribution, generates a low-boom target for the reversed equivalent area (Ae,r) of the configuration, and modifies the configuration to minimize the differences between the configuration s Ae,r and the low-boom target. The new inverse design process is used to modify a supersonic demonstrator concept for a cruise Mach number of 1.6 and a cruise weight of 30,000 lb. The modified configuration has a fully shaped ground signature that has a perceived loudness (PLdB) value of 78.5, while the original configuration has a partially shaped aft signature with a PLdB of 82.3.

A multi-fidelity analysis selection method using a constrained discrete optimization formulation

NASA Astrophysics Data System (ADS)

Stults, Ian C.

The purpose of this research is to develop a method for selecting the fidelity of contributing analyses in computer simulations. Model uncertainty is a significant component of result validity, yet it is neglected in most conceptual design studies. When it is considered, it is done so in only a limited fashion, and therefore brings the validity of selections made based on these results into question. Neglecting model uncertainty can potentially cause costly redesigns of concepts later in the design process or can even cause program cancellation. Rather than neglecting it, if one were to instead not only realize the model uncertainty in tools being used but also use this information to select the tools for a contributing analysis, studies could be conducted more efficiently and trust in results could be quantified. Methods for performing this are generally not rigorous or traceable, and in many cases the improvement and additional time spent performing enhanced calculations are washed out by less accurate calculations performed downstream. The intent of this research is to resolve this issue by providing a method which will minimize the amount of time spent conducting computer simulations while meeting accuracy and concept resolution requirements for results. In many conceptual design programs, only limited data is available for quantifying model uncertainty. Because of this data sparsity, traditional probabilistic means for quantifying uncertainty should be reconsidered. This research proposes to instead quantify model uncertainty using an evidence theory formulation (also referred to as Dempster-Shafer theory) in lieu of the traditional probabilistic approach. Specific weaknesses in using evidence theory for quantifying model uncertainty are identified and addressed for the purposes of the Fidelity Selection Problem. A series of experiments was conducted to address these weaknesses using n-dimensional optimization test functions. These experiments found that model uncertainty present in analyses with 4 or fewer input variables could be effectively quantified using a strategic distribution creation method; if more than 4 input variables exist, a Frontier Finding Particle Swarm Optimization should instead be used. Once model uncertainty in contributing analysis code choices has been quantified, a selection method is required to determine which of these choices should be used in simulations. Because much of the selection done for engineering problems is driven by the physics of the problem, these are poor candidate problems for testing the true fitness of a candidate selection method. Specifically moderate and high dimensional problems' variability can often be reduced to only a few dimensions and scalability often cannot be easily addressed. For these reasons a simple academic function was created for the uncertainty quantification, and a canonical form of the Fidelity Selection Problem (FSP) was created. Fifteen best- and worst-case scenarios were identified in an effort to challenge the candidate selection methods both with respect to the characteristics of the tradeoff between time cost and model uncertainty and with respect to the stringency of the constraints and problem dimensionality. The results from this experiment show that a Genetic Algorithm (GA) was able to consistently find the correct answer, but under certain circumstances, a discrete form of Particle Swarm Optimization (PSO) was able to find the correct answer more quickly. To better illustrate how the uncertainty quantification and discrete optimization might be conducted for a "real world" problem, an illustrative example was conducted using gas turbine engines.

Fundamental Insights into Combustion Instability Predictions in Aerospace Propulsion

NASA Astrophysics Data System (ADS)

Huang, Cheng

Integrated multi-fidelity modeling has been performed for combustion instability in aerospace propulsion, which includes two levels of analysis: first, computational fluid dynamics (CFD) using hybrid RANS/LES simulations for underlying physics investigations (high-fidelity modeling); second, modal decomposition techniques for diagnostics (analysis & validation); third, development of flame response model using model reduction techniques for practical design applications (low-order model). For the high-fidelity modeling, the relevant CFD code development work is moving towards combustion instability prediction for liquid propulsion system. A laboratory-scale single-element lean direct injection (LDI) gas turbine combustor is used for configuration that produces self-excited combustion instability. The model gas turbine combustor is featured with an air inlet section, air plenum, swirler-venturi-injector assembly, combustion chamber, and exit nozzle. The combustor uses liquid fuel (Jet-A/FT-SPK) and heated air up to 800K. Combustion dynamics investigations are performed with the same geometry and operating conditions concurrently between the experiment and computation at both high (φ=0.6) and low (φ=0.36) equivalence ratios. The simulation is able to reach reasonable agreement with experiment measurements in terms of the pressure signal. Computational analyses are also performed using an acoustically-open geometry to investigate the characteristic hydrodynamics in the combustor with both constant and perturbed inlet mass flow rates. Two hydrodynamic modes are identified by using Dynamic Mode Decomposition (DMD) analysis: Vortex Breakdown Bubble (VBB) and swirling modes. Following that, the closed geometry simulation results are analyzed in three steps. In step one, a detailed cycle analysis shows two physically important couplings in the combustor: first, the acoustic compression enhances the spray drop breakup and vaporization, and generates more gaseous fuel for reaction; second, the acoustic compression couples with the unsteady hydrodynamics found in the open-geometry simulation, enhances the fuel/air mixing, and triggers a large amount of heat addition. In step two, a modal analysis using DMD extracts the dynamic features of important modes in the combustor, and identifies the presence of Precessing Vortex Core (PVC) mode and its nonlinear interactions with acoustic modes. Moreover, the DMD analysis helps to establish the couplings between the hydrodynamics and acoustics in terms of frequencies. In step 3, Rayleigh index analysis provides a quantitative assessment of acoustics/combustion couplings and identifies local regions for instability driving/damping. Two modal decomposition techniques, Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD), are assessed in terms of their capabilities in extracting important information from the original simulation dataset and in validating the computational results using the experiment measurement. A POD analysis provides a series of modes with decreasing energy content and it offers an efficient and optimized way to represent a large dataset. The frequency-based DMD technique provides modes that correspond to all single frequencies. For the low-order modeling, fundamental aspects are examined to study necessary conditions, criteria and approaches to develop a reduced-order model (ROM) that is able to represent generic combustion/flame responses, which then can be used in an engineering level tool to provide efficient predictions of combustion instability for practical design applications. Explorations are focused on model reduction techniques by using the so-called POD/Galerkin method. The method uses the numerical solutions of the model equations as the database for building a set of POD eigen-bases. Specifically, the numerical solutions are calculated by perturbing quantities of interest such as the inlet conditions. The POD-derived eigen-bases are, in turn, used in conjunction with a Galerkin procedure to reduce the governing partial differential equation to an ordinary differential equation, which constitutes the ROM. Once the ROM is established, it can then be used as a lower-order test-bed to predict detailed results within certain parametric ranges at a fraction of the cost of solving the full governing equations. A detailed assessment is performed on the method in two parts. In part one, a one-dimensional scalar reaction-advection model equation is used for fundamental investigations, which include verification of the POD eigen-basis calculation and of the ROM development procedure. Moreover, certain criteria during ROM development are established: 1. a necessary number of POD modes that should be included to guarantee a stable ROM; 2. the need for the numerical discretization scheme to be consistent between the original CFD and the developed ROM. Furthermore, the predictive capabilities of the resulting ROM are evaluated to test its limits and to validate the values of applying broadband forcing in improving the ROM performance. In part two, the exploration is extended to a vector system of equations. Using the one-dimensional Euler equation is used as a model equation. A numerical stability issue is identified during the ROM development, the cause of which is further studied and attributed to the normalization methods implemented to generate coupled POD eigen-bases for vector variables. (Abstract shortened by UMI.).

Bayesian Variable Selection for Hierarchical Gene-Environment and Gene-Gene Interactions

PubMed Central

Liu, Changlu; Ma, Jianzhong; Amos, Christopher I.

2014-01-01

We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions and gene by environment interactions in the same model. Our approach incorporates the natural hierarchical structure between the main effects and interaction effects into a mixture model, such that our methods tend to remove the irrelevant interaction effects more effectively, resulting in more robust and parsimonious models. We consider both strong and weak hierarchical models. For a strong hierarchical model, both of the main effects between interacting factors must be present for the interactions to be considered in the model development, while for a weak hierarchical model, only one of the two main effects is required to be present for the interaction to be evaluated. Our simulation results show that the proposed strong and weak hierarchical mixture models work well in controlling false positive rates and provide a powerful approach for identifying the predisposing effects and interactions in gene-environment interaction studies, in comparison with the naive model that does not impose this hierarchical constraint in most of the scenarios simulated. We illustrated our approach using data for lung cancer and cutaneous melanoma. PMID:25154630

Interactive Model-Centric Systems Engineering (IMCSE) Phase 5

DTIC Science & Technology

2018-02-28

Conducting Program Team Launches ................................................................................................. 12 Informing Policy...research advances knowledge relevant to human interaction with models and model-generated information . Figure 1 highlights several questions the...stakeholders interact using models and model generated information ; facets of human interaction with visualizations and large data sets; and underlying

Optimal Scaling of Interaction Effects in Generalized Linear Models

ERIC Educational Resources Information Center

van Rosmalen, Joost; Koning, Alex J.; Groenen, Patrick J. F.

2009-01-01

Multiplicative interaction models, such as Goodman's (1981) RC(M) association models, can be a useful tool for analyzing the content of interaction effects. However, most models for interaction effects are suitable only for data sets with two or three predictor variables. Here, we discuss an optimal scaling model for analyzing the content of…

Ridge Regression for Interactive Models.

ERIC Educational Resources Information Center

Tate, Richard L.

1988-01-01

An exploratory study of the value of ridge regression for interactive models is reported. Assuming that the linear terms in a simple interactive model are centered to eliminate non-essential multicollinearity, a variety of common models, representing both ordinal and disordinal interactions, are shown to have "orientations" that are…

Ensemble urban flood simulation in comparison with laboratory-scale experiments: Impact of interaction models for manhole, sewer pipe, and surface flow

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Lee, Seungsoo; An, Hyunuk; Kawaike, Kenji; Nakagawa, Hajime

2016-11-01

An urban flood is an integrated phenomenon that is affected by various uncertainty sources such as input forcing, model parameters, complex geometry, and exchanges of flow among different domains in surfaces and subsurfaces. Despite considerable advances in urban flood modeling techniques, limited knowledge is currently available with regard to the impact of dynamic interaction among different flow domains on urban floods. In this paper, an ensemble method for urban flood modeling is presented to consider the parameter uncertainty of interaction models among a manhole, a sewer pipe, and surface flow. Laboratory-scale experiments on urban flood and inundation are performed under various flow conditions to investigate the parameter uncertainty of interaction models. The results show that ensemble simulation using interaction models based on weir and orifice formulas reproduces experimental data with high accuracy and detects the identifiability of model parameters. Among interaction-related parameters, the parameters of the sewer-manhole interaction show lower uncertainty than those of the sewer-surface interaction. Experimental data obtained under unsteady-state conditions are more informative than those obtained under steady-state conditions to assess the parameter uncertainty of interaction models. Although the optimal parameters vary according to the flow conditions, the difference is marginal. Simulation results also confirm the capability of the interaction models and the potential of the ensemble-based approaches to facilitate urban flood simulation.

Hadron-nucleus interactions at high energies

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

Chiu, C.B.; He, Z.; Tow, D.M.

1982-06-01

A simple space-time description of high-energy hadron-nucleus interactions is presented. The model is based on the DTU (dual topologial unitarization)-parton-model description of soft multiparticle production in hadron-hadron interactions. The essentially parameter-free model agrees well with the general features of high-energy data for hadron-nucleus interactions; in particular, this DTU-parton model has a natural explanation for an approximate nu-bar universality. The expansion to high-energy nucleus-nucleus interactions is presented. We also compare and contrast this model with several previously proposed models.

Hadron-nucleus interactions at high energies

NASA Astrophysics Data System (ADS)

Chiu, Charles B.; He, Zuoxiu; Tow, Don M.

1982-06-01

A simple space-time description of high-energy hadron-nucleus interactions is presented. The model is based on the DTU (dual topological unitarization) -parton-model description of soft multiparticle production in hadron-hadron interactions. The essentially parameter-free model agrees well with the general features of high-energy data for hadron-nucleus interactions; in particular, this DTU-parton model has a natural explanation for an approximate ν¯ universality. The extension to high-energy nucleus-nucleus interactions is presented. We also compare and contrast this model with several previously proposed models.

Interaction in Balanced Cross Nested Designs

NASA Astrophysics Data System (ADS)

Ramos, Paulo; Mexia, João T.; Carvalho, Francisco; Covas, Ricardo

2011-09-01

Commutative Jordan Algebras, CJA, are used in the study of mixed models obtained, through crossing and nesting, from simpler ones. In the study of cross nested models the interaction between nested factors have been systematically discarded. However this can constitutes an artificial simplification of the models. We point out that, when two crossed factors interact, such interaction is symmetric, both factors playing in it equivalent roles, while when two nested factors interact, the interaction is determined by the nesting factor. These interactions will be called interactions with nesting. In this work we present a coherent formulation of the algebraic structure of models enabling the choice of families of interactions between cross and nested factors using binary operations on CJA.

Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation

PubMed Central

Rathouz, Paul J.; Van Hulle, Carol A.; Lee Rodgers, Joseph; Waldman, Irwin D.; Lahey, Benjamin B.

2009-01-01

Purcell (2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell’s model extends the Cholesky model to include gene-environment interaction. We examine a number of closely-related alternative models that do not involve gene-environment interaction but which may fit the data as well Purcell’s model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell’s model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model. PMID:18293078

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

ISS Plasma Interaction: Measurements and Modeling

NASA Technical Reports Server (NTRS)

Barsamian, H.; Mikatarian, R.; Alred, J.; Minow, J.; Koontz, S.

2004-01-01

Ionospheric plasma interaction effects on the International Space Station are discussed in the following paper. The large structure and high voltage arrays of the ISS represent a complex system interacting with LEO plasma. Discharge current measurements made by the Plasma Contactor Units and potential measurements made by the Floating Potential Probe delineate charging and magnetic induction effects on the ISS. Based on theoretical and physical understanding of the interaction phenomena, a model of ISS plasma interaction has been developed. The model includes magnetic induction effects, interaction of the high voltage solar arrays with ionospheric plasma, and accounts for other conductive areas on the ISS. Based on these phenomena, the Plasma Interaction Model has been developed. Limited verification of the model has been performed by comparison of Floating Potential Probe measurement data to simulations. The ISS plasma interaction model will be further tested and verified as measurements from the Floating Potential Measurement Unit become available, and construction of the ISS continues.

Synchronization of multi-agent systems with metric-topological interactions.

PubMed

Wang, Lin; Chen, Guanrong

2016-09-01

A hybrid multi-agent systems model integrating the advantages of both metric interaction and topological interaction rules, called the metric-topological model, is developed. This model describes planar motions of mobile agents, where each agent can interact with all the agents within a circle of a constant radius, and can furthermore interact with some distant agents to reach a pre-assigned number of neighbors, if needed. Some sufficient conditions imposed only on system parameters and agent initial states are presented, which ensure achieving synchronization of the whole group of agents. It reveals the intrinsic relationships among the interaction range, the speed, the initial heading, and the density of the group. Moreover, robustness against variations of interaction range, density, and speed are investigated by comparing the motion patterns and performances of the hybrid metric-topological interaction model with the conventional metric-only and topological-only interaction models. Practically in all cases, the hybrid metric-topological interaction model has the best performance in the sense of achieving highest frequency of synchronization, fastest convergent rate, and smallest heading difference.

Can the vector space model be used to identify biological entity activities?

PubMed Central

2011-01-01

Background Biological systems are commonly described as networks of entity interactions. Some interactions are already known and integrate the current knowledge in life sciences. Others remain unknown for long periods of time and are frequently discovered by chance. In this work we present a model to predict these unknown interactions from a textual collection using the vector space model (VSM), a well known and established information retrieval model. We have extended the VSM ability to retrieve information using a transitive closure approach. Our objective is to use the VSM to identify the known interactions from the literature and construct a network. Based on interactions established in the network our model applies the transitive closure in order to predict and rank new interactions. Results We have tested and validated our model using a collection of patent claims issued from 1976 to 2005. From 266,528 possible interactions in our network, the model identified 1,027 known interactions and predicted 3,195 new interactions. Iterating the model according to patent issue dates, interactions found in a given past year were often confirmed by patent claims not in the collection and issued in more recent years. Most confirmation patent claims were found at the top 100 new interactions obtained from each subnetwork. We have also found papers on the Web which confirm new inferred interactions. For instance, the best new interaction inferred by our model relates the interaction between the adrenaline neurotransmitter and the androgen receptor gene. We have found a paper that reports the partial dependence of the antiapoptotic effect of adrenaline on androgen receptor. Conclusions The VSM extended with a transitive closure approach provides a good way to identify biological interactions from textual collections. Specifically for the context of literature-based discovery, the extended VSM contributes to identify and rank relevant new interactions even if these interactions occcur in only a few documents in the collection. Consequently, we have developed an efficient method for extracting and restricting the best potential results to consider as new advances in life sciences, even when indications of these results are not easily observed from a mass of documents. PMID:22369514

SABRINA: an interactive solid geometry modeling program for Monte Carlo

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

West, J.T.

SABRINA is a fully interactive three-dimensional geometry modeling program for MCNP. In SABRINA, a user interactively constructs either body geometry, or surface geometry models, and interactively debugs spatial descriptions for the resulting objects. This enhanced capability significantly reduces the effort in constructing and debugging complicated three-dimensional geometry models for Monte Carlo Analysis.

Modeled interactive effects of precipitation, temperature, and [CO2] on ecosystem carbon and water dynamics in different climatic zones

Treesearch

Yiqi Luo; Dieter Gerten; Guerric Le Maire; William J. Parton; Ensheng Weng; Xuhui Zhou; Cindy Keough; Claus Beier; Philippe Ciais; Wolfgang Cramer; Jeffrey S. Dukes; Bridget Emmett; Paul J. Hanson; Alan Knapp; Sune Linder; Dan Nepstad; Lindsey. Rustad

2008-01-01

Interactive effects of multiple global change factors on ecosystem processes are complex. It is relatively expensive to explore those interactions in manipulative experiments. We conducted a modeling analysis to identify potentially important interactions and to stimulate hypothesis formulation for experimental research. Four models were used to quantify interactive...

Supervisor's Interactive Model of Organizational Relationships

ERIC Educational Resources Information Center

O'Reilly, Frances L.; Matt, John; McCaw, William P.

2014-01-01

The Supervisor's Interactive Model of Organizational Relationships (SIMOR) integrates two models addressed in the leadership literature and then highlights the importance of relationships. The Supervisor's Interactive Model of Organizational Relationships combines the modified Hersey and Blanchard model of situational leadership, the…

Capturing nonlocal interaction effects in the Hubbard model: Optimal mappings and limits of applicability

NASA Astrophysics Data System (ADS)

van Loon, E. G. C. P.; Schüler, M.; Katsnelson, M. I.; Wehling, T. O.

2016-10-01

We investigate the Peierls-Feynman-Bogoliubov variational principle to map Hubbard models with nonlocal interactions to effective models with only local interactions. We study the renormalization of the local interaction induced by nearest-neighbor interaction and assess the quality of the effective Hubbard models in reproducing observables of the corresponding extended Hubbard models. We compare the renormalization of the local interactions as obtained from numerically exact determinant quantum Monte Carlo to approximate but more generally applicable calculations using dual boson, dynamical mean field theory, and the random phase approximation. These more approximate approaches are crucial for any application with real materials in mind. Furthermore, we use the dual boson method to calculate observables of the extended Hubbard models directly and benchmark these against determinant quantum Monte Carlo simulations of the effective Hubbard model.

Further Investigations of Gravity Modeling on Surface-Interacting Vehicle Simulations

NASA Technical Reports Server (NTRS)

Madden, Michael M.

2009-01-01

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations perform ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of the gravitation and world model. A surface-interacting simulation cannot treat the gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a subsonic civil transport in level flight under various starting conditions.

Gravity Modeling Effects on Surface-Interacting Vehicles in Supersonic Flight

NASA Technical Reports Server (NTRS)

Madden, Michael M.

2010-01-01

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations per-form ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of these two models. A surface-interacting simulation cannot treat gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a supersonic aircraft in level flight under various start-ing conditions.

Ginzburg criterion for ionic fluids: the effect of Coulomb interactions.

PubMed

Patsahan, O

2013-08-01

The effect of the Coulomb interactions on the crossover between mean-field and Ising critical behavior in ionic fluids is studied using the Ginzburg criterion. We consider the charge-asymmetric primitive model supplemented by short-range attractive interactions in the vicinity of the gas-liquid critical point. The model without Coulomb interactions exhibiting typical Ising critical behavior is used to calibrate the Ginzburg temperature of the systems comprising electrostatic interactions. Using the collective variables method, we derive a microscopic-based effective Hamiltonian for the full model. We obtain explicit expressions for all the relevant Hamiltonian coefficients within the framework of the same approximation, i.e., the one-loop approximation. Then we consistently calculate the reduced Ginzburg temperature t(G) for both the purely Coulombic model (a restricted primitive model) and the purely nonionic model (a hard-sphere square-well model) as well as for the model parameters ranging between these two limiting cases. Contrary to the previous theoretical estimates, we obtain the reduced Ginzburg temperature for the purely Coulombic model to be about 20 times smaller than for the nonionic model. For the full model including both short-range and long-range interactions, we show that t(G) approaches the value found for the purely Coulombic model when the strength of the Coulomb interactions becomes sufficiently large. Our results suggest a key role of Coulomb interactions in the crossover behavior observed experimentally in ionic fluids as well as confirm the Ising-like criticality in the Coulomb-dominated ionic systems.

A Partial Least Square Approach for Modeling Gene-gene and Gene-environment Interactions When Multiple Markers Are Genotyped

PubMed Central

Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.

2008-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621

A partial least-square approach for modeling gene-gene and gene-environment interactions when multiple markers are genotyped.

PubMed

Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C

2009-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.

Toward a more complete understanding of noncovalent interactions involving aromatic rings.

PubMed

Wheeler, Steven E; Bloom, Jacob W G

2014-08-14

Noncovalent interactions involving aromatic rings, which include π-stacking interactions, anion-π interactions, and XH-π interactions, among others, are ubiquitous in chemical and biochemical systems. Despite dramatic advances in our understanding of these interactions over the past decade, many aspects of these noncovalent interactions have only recently been uncovered, with many questions remaining. We summarize our computational studies aimed at understanding the impact of substituents and heteroatoms on these noncovalent interactions. In particular, we discuss our local, direct interaction model of substituent effects in π-stacking interactions. In this model, substituent effects are dominated by electrostatic interactions of the local dipoles associated with the substituents and the electric field of the other ring. The implications of the local nature of substituent effects on π-stacking interactions in larger systems are discussed, with examples given for complexes with carbon nanotubes and a small graphene model, as well as model stacked discotic systems. We also discuss related issues involving the interpretation of electrostatic potential (ESP) maps. Although ESP maps are widely used in discussions of noncovalent interactions, they are often misinterpreted. Next, we provide an alternative explanation for the origin of anion-π interactions involving substituted benzenes and N-heterocycles, and show that these interactions are well-described by simple models based solely on charge-dipole interactions. Finally, we summarize our recent work on the physical nature of substituent effects in XH-π interactions. Together, these results paint a more complete picture of noncovalent interactions involving aromatic rings and provide a firm conceptual foundation for the rational exploitation of these interactions in a myriad of chemical contexts.

Cyberpsychology: a human-interaction perspective based on cognitive modeling.

PubMed

Emond, Bruno; West, Robert L

2003-10-01

This paper argues for the relevance of cognitive modeling and cognitive architectures to cyberpsychology. From a human-computer interaction point of view, cognitive modeling can have benefits both for theory and model building, and for the design and evaluation of sociotechnical systems usability. Cognitive modeling research applied to human-computer interaction has two complimentary objectives: (1) to develop theories and computational models of human interactive behavior with information and collaborative technologies, and (2) to use the computational models as building blocks for the design, implementation, and evaluation of interactive technologies. From the perspective of building theories and models, cognitive modeling offers the possibility to anchor cyberpsychology theories and models into cognitive architectures. From the perspective of the design and evaluation of socio-technical systems, cognitive models can provide the basis for simulated users, which can play an important role in usability testing. As an example of application of cognitive modeling to technology design, the paper presents a simulation of interactive behavior with five different adaptive menu algorithms: random, fixed, stacked, frequency based, and activation based. Results of the simulation indicate that fixed menu positions seem to offer the best support for classification like tasks such as filing e-mails. This research is part of the Human-Computer Interaction, and the Broadband Visual Communication research programs at the National Research Council of Canada, in collaboration with the Carleton Cognitive Modeling Lab at Carleton University.

Full-Potential Modeling of Blade-Vortex Interactions. Degree awarded by George Washington Univ., Feb. 1987

NASA Technical Reports Server (NTRS)

Jones, Henry E.

1997-01-01

A study of the full-potential modeling of a blade-vortex interaction was made. A primary goal of this study was to investigate the effectiveness of the various methods of modeling the vortex. The model problem restricts the interaction to that of an infinite wing with an infinite line vortex moving parallel to its leading edge. This problem provides a convenient testing ground for the various methods of modeling the vortex while retaining the essential physics of the full three-dimensional interaction. A full-potential algorithm specifically tailored to solve the blade-vortex interaction (BVI) was developed to solve this problem. The basic algorithm was modified to include the effect of a vortex passing near the airfoil. Four different methods of modeling the vortex were used: (1) the angle-of-attack method, (2) the lifting-surface method, (3) the branch-cut method, and (4) the split-potential method. A side-by-side comparison of the four models was conducted. These comparisons included comparing generated velocity fields, a subcritical interaction, and a critical interaction. The subcritical and critical interactions are compared with experimentally generated results. The split-potential model was used to make a survey of some of the more critical parameters which affect the BVI.

Biophysical interactions with model lipid membranes: applications in drug discovery and drug delivery

PubMed Central

Peetla, Chiranjeevi; Stine, Andrew; Labhasetwar, Vinod

2009-01-01

The transport of drugs or drug delivery systems across the cell membrane is a complex biological process, often difficult to understand because of its dynamic nature. In this regard, model lipid membranes, which mimic many aspects of cell-membrane lipids, have been very useful in helping investigators to discern the roles of lipids in cellular interactions. One can use drug-lipid interactions to predict pharmacokinetic properties of drugs, such as their transport, biodistribution, accumulation, and hence efficacy. These interactions can also be used to study the mechanisms of transport, based on the structure and hydrophilicity/hydrophobicity of drug molecules. In recent years, model lipid membranes have also been explored to understand their mechanisms of interactions with peptides, polymers, and nanocarriers. These interaction studies can be used to design and develop efficient drug delivery systems. Changes in the lipid composition of cells and tissue in certain disease conditions may alter biophysical interactions, which could be explored to develop target-specific drugs and drug delivery systems. In this review, we discuss different model membranes, drug-lipid interactions and their significance, studies of model membrane interactions with nanocarriers, and how biophysical interaction studies with lipid model membranes could play an important role in drug discovery and drug delivery. PMID:19432455

Interacting holographic dark energy models: a general approach

NASA Astrophysics Data System (ADS)

Som, S.; Sil, A.

2014-08-01

Dark energy models inspired by the cosmological holographic principle are studied in homogeneous isotropic spacetime with a general choice for the dark energy density . Special choices of the parameters enable us to obtain three different holographic models, including the holographic Ricci dark energy (RDE) model. Effect of interaction between dark matter and dark energy on the dynamics of those models are investigated for different popular forms of interaction. It is found that crossing of phantom divide can be avoided in RDE models for β>0.5 irrespective of the presence of interaction. A choice of α=1 and β=2/3 leads to a varying Λ-like model introducing an IR cutoff length Λ -1/2. It is concluded that among the popular choices an interaction of the form Q∝ Hρ m suits the best in avoiding the coincidence problem in this model.

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

PubMed Central

Liu, Hua; Wu, Wen

2017-01-01

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF). PMID:28608843

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Liu, Hua; Wu, Wen

2017-06-13

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

Astronomical bounds on a cosmological model allowing a general interaction in the dark sector

NASA Astrophysics Data System (ADS)

Pan, Supriya; Mukherjee, Ankan; Banerjee, Narayan

2018-06-01

Non-gravitational interaction between two barotropic dark fluids, namely the pressureless dust and the dark energy in a spatially flat Friedmann-Lemaître-Robertson-Walker model, has been discussed. It is shown that for the interactions that are linear in terms the energy densities of the dark components and their first order derivatives, the net energy density is governed by a second-order differential equation with constant coefficients. Taking a generalized interaction, which includes a number of already known interactions as special cases, the dynamics of the universe is described for three types of the dark energy equation of state, namely that of interacting quintessence, interacting vacuum energy density, and interacting phantom. The models have been constrained using the standard cosmological probes, Supernovae Type Ia data from joint light curve analysis and the observational Hubble parameter data. Two geometric tests, the cosmographic studies, and the Om diagnostic have been invoked so as to ascertain the behaviour of the present model vis-a-vis the Λ-cold dark matter model. We further discussed the interacting scenarios taking into account the thermodynamic considerations.

An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Zhu, Wei; Wang, Wei; Yuan, Gannan

2016-06-01

In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).

Search for the standard model Higgs boson in $$l\

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

Li, Dikai

2013-01-01

Humans have always attempted to understand the mystery of Nature, and more recently physicists have established theories to describe the observed phenomena. The most recent theory is a gauge quantum field theory framework, called Standard Model (SM), which proposes a model comprised of elementary matter particles and interaction particles which are fundamental force carriers in the most unified way. The Standard Model contains the internal symmetries of the unitary product group SU(3) c ⓍSU(2) L Ⓧ U(1) Y , describes the electromagnetic, weak and strong interactions; the model also describes how quarks interact with each other through all of thesemore » three interactions, how leptons interact with each other through electromagnetic and weak forces, and how force carriers mediate the fundamental interactions.« less

Land-atmosphere interaction patterns in southeastern South America using satellite products and climate models

NASA Astrophysics Data System (ADS)

Spennemann, P. C.; Salvia, M.; Ruscica, R. C.; Sörensson, A. A.; Grings, F.; Karszenbaum, H.

2018-02-01

In regions of strong Land-Atmosphere (L-A) interaction, soil moisture (SM) conditions can impact the atmosphere through modulating the land surface fluxes. The importance of the identification of L-A interaction regions lies in the potential improvement of the weather/seasonal forecast and the better understanding of the physical mechanisms involved. This study aims to compare the terrestrial segment of the L-A interaction from satellite products and climate models, motivated by previous modeling studies pointing out southeastern South America (SESA) as a L-A hotspot during austral summer. In addition, the L-A interaction under dry or wet anomalous conditions over SESA is analyzed. To identify L-A hotspots the AMSRE-LPRM SM and MODIS land surface temperature products; coupled climate models and uncoupled land surface models were used. SESA highlights as a strong L-A interaction hotspot when employing different metrics, temporal scales and independent datasets, showing consistency between models and satellite estimations. Both AMSRE-LPRM bands (X and C) are consistent showing a strong L-A interaction hotspot over the Pampas ecoregion. Intensification and a larger spatial extent of the L-A interaction for dry summers was observed in both satellite products and models compared to wet summers. These results, which were derived from measured physical variables, are encouraging and promising for future studies analyzing L-A interactions. L-A interaction analysis is proposed here as a meeting point between remote sensing and climate modelling communities of Argentina, within a region with the highest agricultural and livestock production of the continent, but with an important lack of in-situ SM observations.

Investigation on the individual contributions of N-H...O=C and C-H...O=C interactions to the binding energies of beta-sheet models.

PubMed

Wang, Chang-Sheng; Sun, Chang-Liang

2010-04-15

In this article, the binding energies of 16 antiparallel and parallel beta-sheet models are estimated using the analytic potential energy function we proposed recently and the results are compared with those obtained from MP2, AMBER99, OPLSAA/L, and CHARMM27 calculations. The comparisons indicate that the analytic potential energy function can produce reasonable binding energies for beta-sheet models. Further comparisons suggest that the binding energy of the beta-sheet models might come mainly from dipole-dipole attractive and repulsive interactions and VDW interactions between the two strands. The dipole-dipole attractive and repulsive interactions are further obtained in this article. The total of N-H...H-N and C=O...O=C dipole-dipole repulsive interaction (the secondary electrostatic repulsive interaction) in the small ring of the antiparallel beta-sheet models is estimated to be about 6.0 kcal/mol. The individual N-H...O=C dipole-dipole attractive interaction is predicted to be -6.2 +/- 0.2 kcal/mol in the antiparallel beta-sheet models and -5.2 +/- 0.6 kcal/mol in the parallel beta-sheet models. The individual C(alpha)-H...O=C attractive interaction is -1.2 +/- 0.2 kcal/mol in the antiparallel beta-sheet models and -1.5 +/- 0.2 kcal/mol in the parallel beta-sheet models. These values are important in understanding the interactions at protein-protein interfaces and developing a more accurate force field for peptides and proteins. 2009 Wiley Periodicals, Inc.

Stand By for Fun: Experience and Interaction.

ERIC Educational Resources Information Center

Crockford, Douglas

1986-01-01

This paper explores interactivity, and considers what should be done to create a mass market for interactive media. It is suggested that one way to do so is to examine the video game phenomenon, and a model of interactivity is proposed. The model, a "home interactive theater," would involve interaction in the telling of a story, with the…

The Drosophila melanogaster host model

PubMed Central

Igboin, Christina O.; Griffen, Ann L.; Leys, Eugene J.

2012-01-01

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen–host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial–host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis–host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed. PMID:22368770

The Drosophila melanogaster host model.

PubMed

Igboin, Christina O; Griffen, Ann L; Leys, Eugene J

2012-01-01

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen-host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial-host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis-host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed.

A Study of Fan Stage/Casing Interaction Models

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Carney, Kelly; Gallardo, Vicente

2003-01-01

The purpose of the present study is to investigate the performance of several existing and new, blade-case interactions modeling capabilities that are compatible with the large system simulations used to capture structural response during blade-out events. Three contact models are examined for simulating the interactions between a rotor bladed disk and a case: a radial and linear gap element and a new element based on a hydrodynamic formulation. The first two models are currently available in commercial finite element codes such as NASTRAN and have been showed to perform adequately for simulating rotor-case interactions. The hydrodynamic model, although not readily available in commercial codes, may prove to be better able to characterize rotor-case interactions.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Interacting 3-form dark energy models: Distinguishing interactions and avoiding the Little Sibling of the Big Rip

NASA Astrophysics Data System (ADS)

Morais, João; Bouhmadi-López, Mariam; Kumar, K. Sravan; Marto, João; Tavakoli, Yaser

2017-03-01

In this paper we consider 3-form dark energy (DE) models with interactions in the dark sector. We aim to distinguish the phenomenological interactions that are defined through the dark matter (DM) and the DE energy densities. We do our analysis mainly in two stages. In the first stage, we identify the non-interacting 3-form DE model which generically leads to an abrupt late-time cosmological event which is known as the little sibling of the Big Rip (LSBR). We classify the interactions which can possibly avoid this late-time abrupt event. We also study the parameter space of the model that is consistent with the interaction between DM and DE energy densities at present as indicated by recent studies based on BAO and SDSS data. In the later stage, we observationally distinguish those interactions using the statefinder hierarchy parameters S3(1), S4(1), S3(1), S5(1). We also compute the growth factor parameter ɛ(z) for the various interactions we consider herein and use the composite null diagnostic (CND) S3(1), ɛ(z) } as a tool to characterise those interactions by measuring their departures from the concordance model. In addition, we make a preliminary analysis of our model in light of the recently released data by SDSS III on the measurement of the linear growth rate of structure.

ILP-2 modeling and virtual screening of an FDA-approved library:a possible anticancer therapy.

PubMed

Khalili, Saeed; Mohammadpour, Hemn; Shokrollahi Barough, Mahideh; Kokhaei, Parviz

2016-06-23

The members of the inhibitors of apoptosis protein (IAP) family inhibit diverse components of the caspase signaling pathway, notably caspase 3, 7, and 9. ILP-2 (BIRC-8) is the most recently identified member of the IAPs, mainly interacting with caspase 9. This interaction would eventually lead to death resistance in the case of cancerous cells. Therefore, structural modeling of ILP-2 and finding applicable inhibitors of its interaction with caspase 9 are a compelling challenge. Three main protein modeling approaches along with various model refinement measures were harnessed to achieve a reliable 3D model, using state-of-the-art software. Thereafter, the selected model was employed to perform virtual screening of an FDA approved library. A model built by a combinatorial approach (homology and ab initio approaches) was chosen as the best model. Model refinement processes successfully bolstered the model quality. Virtual screening of the compound library introduced several high affinity inhibitor candidates that interact with functional residues of ILP2. Given the 3D structure of the ILP2 molecule, we found promising inhibitory molecules. In addition to high affinity towards the ILP2 molecule, these molecules interact with residues that play pivotal rules in ILP2-caspase interaction. These molecules would inhibit ILP2-caspase interaction and consequently would lead to reactivated cell apoptosis through the caspases pathway.

Linking market interaction intensity of 3D Ising type financial model with market volatility

NASA Astrophysics Data System (ADS)

Fang, Wen; Ke, Jinchuan; Wang, Jun; Feng, Ling

2016-11-01

Microscopic interaction models in physics have been used to investigate the complex phenomena of economic systems. The simple interactions involved can lead to complex behaviors and help the understanding of mechanisms in the financial market at a systemic level. This article aims to develop a financial time series model through 3D (three-dimensional) Ising dynamic system which is widely used as an interacting spins model to explain the ferromagnetism in physics. Through Monte Carlo simulations of the financial model and numerical analysis for both the simulation return time series and historical return data of Hushen 300 (HS300) index in Chinese stock market, we show that despite its simplicity, this model displays stylized facts similar to that seen in real financial market. We demonstrate a possible underlying link between volatility fluctuations of real stock market and the change in interaction strengths of market participants in the financial model. In particular, our stochastic interaction strength in our model demonstrates that the real market may be consistently operating near the critical point of the system.

Interactive graphic editing tools in bioluminescent imaging simulation

NASA Astrophysics Data System (ADS)

Li, Hui; Tian, Jie; Luo, Jie; Wang, Ge; Cong, Wenxiang

2005-04-01

It is a challenging task to accurately describe complicated biological tissues and bioluminescent sources in bioluminescent imaging simulation. Several graphic editing tools have been developed to efficiently model each part of the bioluminescent simulation environment and to interactively correct or improve the initial models of anatomical structures or bioluminescent sources. There are two major types of graphic editing tools: non-interactive tools and interactive tools. Geometric building blocks (i.e. regular geometric graphics and superquadrics) are applied as non-interactive tools. To a certain extent, complicated anatomical structures and bioluminescent sources can be approximately modeled by combining a sufficient large number of geometric building blocks with Boolean operators. However, those models are too simple to describe the local features and fine changes in 2D/3D irregular contours. Therefore, interactive graphic editing tools have been developed to facilitate the local modifications of any initial surface model. With initial models composed of geometric building blocks, interactive spline mode is applied to conveniently perform dragging and compressing operations on 2D/3D local surface of biological tissues and bioluminescent sources inside the region/volume of interest. Several applications of the interactive graphic editing tools will be presented in this article.

Interactive activation and mutual constraint satisfaction in perception and cognition.

PubMed

McClelland, James L; Mirman, Daniel; Bolger, Donald J; Khaitan, Pranav

2014-08-01

In a seminal 1977 article, Rumelhart argued that perception required the simultaneous use of multiple sources of information, allowing perceivers to optimally interpret sensory information at many levels of representation in real time as information arrives. Building on Rumelhart's arguments, we present the Interactive Activation hypothesis-the idea that the mechanism used in perception and comprehension to achieve these feats exploits an interactive activation process implemented through the bidirectional propagation of activation among simple processing units. We then examine the interactive activation model of letter and word perception and the TRACE model of speech perception, as early attempts to explore this hypothesis, and review the experimental evidence relevant to their assumptions and predictions. We consider how well these models address the computational challenge posed by the problem of perception, and we consider how consistent they are with evidence from behavioral experiments. We examine empirical and theoretical controversies surrounding the idea of interactive processing, including a controversy that swirls around the relationship between interactive computation and optimal Bayesian inference. Some of the implementation details of early versions of interactive activation models caused deviation from optimality and from aspects of human performance data. More recent versions of these models, however, overcome these deficiencies. Among these is a model called the multinomial interactive activation model, which explicitly links interactive activation and Bayesian computations. We also review evidence from neurophysiological and neuroimaging studies supporting the view that interactive processing is a characteristic of the perceptual processing machinery in the brain. In sum, we argue that a computational analysis, as well as behavioral and neuroscience evidence, all support the Interactive Activation hypothesis. The evidence suggests that contemporary versions of models based on the idea of interactive activation continue to provide a basis for efforts to achieve a fuller understanding of the process of perception. Copyright © 2014 Cognitive Science Society, Inc.

A New Poisson-Nernst-Planck Model with Ion-Water Interactions for Charge Transport in Ion Channels.

PubMed

Chen, Duan

2016-08-01

In this work, we propose a new Poisson-Nernst-Planck (PNP) model with ion-water interactions for biological charge transport in ion channels. Due to narrow geometries of these membrane proteins, ion-water interaction is critical for both dielectric property of water molecules in channel pore and transport dynamics of mobile ions. We model the ion-water interaction energy based on realistic experimental observations in an efficient mean-field approach. Variation of a total energy functional of the biological system yields a new PNP-type continuum model. Numerical simulations show that the proposed model with ion-water interaction energy has the new features that quantitatively describe dielectric properties of water molecules in narrow pores and are possible to model the selectivity of some ion channels.

Modeling Child-Nature Interaction in a Nature Preschool: A Proof of Concept.

PubMed

Kahn, Peter H; Weiss, Thea; Harrington, Kit

2018-01-01

This article provides a proof of concept for an approach to modeling child-nature interaction based on the idea of interaction patterns : characterizations of essential features of interaction between humans and nature, specified abstractly enough such that countless different instantiations of each one can occur - in more domestic or wild forms - given different types of nature, people, and purposes. The model draws from constructivist psychology, ecological psychology, and evolutionary psychology, and is grounded in observational data collected through a time-sampling methodology at a nature preschool. Through using a nature language that emphasizes ontogenetic and phylogenetic significance, seven keystone interaction patterns are described for this nature preschool: using one's body vigorously in nature, striking wood on wood, constructing shelter, being in solitude in nature, lying on earth, cohabiting with a wild animal , and being outside in weather . These 7 interactions patterns are then brought together with 13 other patterns published elsewhere to provide a total of 20 keystone interaction patterns that begin to fill out the model, and to show its promise. Discussion focuses on what the model aims to be in terms of both product and process, on what work the model can currently do, and how to further develop the model.

Experiment and simulation for CSI: What are the missing links?

NASA Technical Reports Server (NTRS)

Belvin, W. Keith; Park, K. C.

1989-01-01

Viewgraphs on experiment and simulation for control structure interaction (CSI) are presented. Topics covered include: control structure interaction; typical control/structure interaction system; CSI problem classification; actuator/sensor models; modeling uncertainty; noise models; real-time computations; and discrete versus continuous.

Assessing reliability of protein-protein interactions by integrative analysis of data in model organisms.

PubMed

Lin, Xiaotong; Liu, Mei; Chen, Xue-wen

2009-04-29

Protein-protein interactions play vital roles in nearly all cellular processes and are involved in the construction of biological pathways such as metabolic and signal transduction pathways. Although large-scale experiments have enabled the discovery of thousands of previously unknown linkages among proteins in many organisms, the high-throughput interaction data is often associated with high error rates. Since protein interaction networks have been utilized in numerous biological inferences, the inclusive experimental errors inevitably affect the quality of such prediction. Thus, it is essential to assess the quality of the protein interaction data. In this paper, a novel Bayesian network-based integrative framework is proposed to assess the reliability of protein-protein interactions. We develop a cross-species in silico model that assigns likelihood scores to individual protein pairs based on the information entirely extracted from model organisms. Our proposed approach integrates multiple microarray datasets and novel features derived from gene ontology. Furthermore, the confidence scores for cross-species protein mappings are explicitly incorporated into our model. Applying our model to predict protein interactions in the human genome, we are able to achieve 80% in sensitivity and 70% in specificity. Finally, we assess the overall quality of the experimentally determined yeast protein-protein interaction dataset. We observe that the more high-throughput experiments confirming an interaction, the higher the likelihood score, which confirms the effectiveness of our approach. This study demonstrates that model organisms certainly provide important information for protein-protein interaction inference and assessment. The proposed method is able to assess not only the overall quality of an interaction dataset, but also the quality of individual protein-protein interactions. We expect the method to continually improve as more high quality interaction data from more model organisms becomes available and is readily scalable to a genome-wide application.

Introducing a novel interaction model structure for the combined effect of temperature and pH on the microbial growth rate.

PubMed

Akkermans, Simen; Noriega Fernandez, Estefanía; Logist, Filip; Van Impe, Jan F

2017-01-02

Efficient modelling of the microbial growth rate can be performed by combining the effects of individual conditions in a multiplicative way, known as the gamma concept. However, several studies have illustrated that interactions between different effects should be taken into account at stressing environmental conditions to achieve a more accurate description of the growth rate. In this research, a novel approach for modeling the interactions between the effects of environmental conditions on the microbial growth rate is introduced. As a case study, the effect of temperature and pH on the growth rate of Escherichia coli K12 is modeled, based on a set of computer controlled bioreactor experiments performed under static environmental conditions. The models compared in this case study are the gamma model, the model of Augustin and Carlier (2000), the model of Le Marc et al. (2002) and the novel multiplicative interaction model, developed in this paper. This novel model enables the separate identification of interactions between the effects of two (or more) environmental conditions. The comparison of these models focuses on the accuracy, interpretability and compatibility with efficient modeling approaches. Moreover, for the separate effects of temperature and pH, new cardinal parameter model structures are proposed. The novel interaction model contributes to a generic modeling approach, resulting in predictive models that are (i) accurate, (ii) easily identifiable with a limited work load, (iii) modular, and (iv) biologically interpretable. Copyright © 2016. Published by Elsevier B.V.

Quantum Bose-Hubbard model with an evolving graph as a toy model for emergent spacetime

NASA Astrophysics Data System (ADS)

Hamma, Alioscia; Markopoulou, Fotini; Lloyd, Seth; Caravelli, Francesco; Severini, Simone; Markström, Klas

2010-05-01

We present a toy model for interacting matter and geometry that explores quantum dynamics in a spin system as a precursor to a quantum theory of gravity. The model has no a priori geometric properties; instead, locality is inferred from the more fundamental notion of interaction between the matter degrees of freedom. The interaction terms are themselves quantum degrees of freedom so that the structure of interactions and hence the resulting local and causal structures are dynamical. The system is a Hubbard model where the graph of the interactions is a set of quantum evolving variables. We show entanglement between spatial and matter degrees of freedom. We study numerically the quantum system and analyze its entanglement dynamics. We analyze the asymptotic behavior of the classical model. Finally, we discuss analogues of trapped surfaces and gravitational attraction in this simple model.

Pairwise Force SPH Model for Real-Time Multi-Interaction Applications.

PubMed

Yang, Tao; Martin, Ralph R; Lin, Ming C; Chang, Jian; Hu, Shi-Min

2017-10-01

In this paper, we present a novel pairwise-force smoothed particle hydrodynamics (PF-SPH) model to enable simulation of various interactions at interfaces in real time. Realistic capture of interactions at interfaces is a challenging problem for SPH-based simulations, especially for scenarios involving multiple interactions at different interfaces. Our PF-SPH model can readily handle multiple types of interactions simultaneously in a single simulation; its basis is to use a larger support radius than that used in standard SPH. We adopt a novel anisotropic filtering term to further improve the performance of interaction forces. The proposed model is stable; furthermore, it avoids the particle clustering problem which commonly occurs at the free surface. We show how our model can be used to capture various interactions. We also consider the close connection between droplets and bubbles, and show how to animate bubbles rising in liquid as well as bubbles in air. Our method is versatile, physically plausible and easy-to-implement. Examples are provided to demonstrate the capabilities and effectiveness of our approach.

Detecting signals of drug-drug interactions in a spontaneous reports database.

PubMed

Thakrar, Bharat T; Grundschober, Sabine Borel; Doessegger, Lucette

2007-10-01

The spontaneous reports database is widely used for detecting signals of ADRs. We have extended the methodology to include the detection of signals of ADRs that are associated with drug-drug interactions (DDI). In particular, we have investigated two different statistical assumptions for detecting signals of DDI. Using the FDA's spontaneous reports database, we investigated two models, a multiplicative and an additive model, to detect signals of DDI. We applied the models to four known DDIs (methotrexate-diclofenac and bone marrow depression, simvastatin-ciclosporin and myopathy, ketoconazole-terfenadine and torsades de pointes, and cisapride-erythromycin and torsades de pointes) and to four drug-event combinations where there is currently no evidence of a DDI (fexofenadine-ketoconazole and torsades de pointes, methotrexade-rofecoxib and bone marrow depression, fluvastatin-ciclosporin and myopathy, and cisapride-azithromycine and torsade de pointes) and estimated the measure of interaction on the two scales. The additive model correctly identified all four known DDIs by giving a statistically significant (P < 0.05) positive measure of interaction. The multiplicative model identified the first two of the known DDIs as having a statistically significant or borderline significant (P < 0.1) positive measure of interaction term, gave a nonsignificant positive trend for the third interaction (P = 0.27), and a negative trend for the last interaction. Both models correctly identified the four known non interactions by estimating a negative measure of interaction. The spontaneous reports database is a valuable resource for detecting signals of DDIs. In particular, the additive model is more sensitive in detecting such signals. The multiplicative model may further help qualify the strength of the signal detected by the additive model.

Detecting signals of drug–drug interactions in a spontaneous reports database

PubMed Central

Thakrar, Bharat T; Grundschober, Sabine Borel; Doessegger, Lucette

2007-01-01

Aims The spontaneous reports database is widely used for detecting signals of ADRs. We have extended the methodology to include the detection of signals of ADRs that are associated with drug–drug interactions (DDI). In particular, we have investigated two different statistical assumptions for detecting signals of DDI. Methods Using the FDA's spontaneous reports database, we investigated two models, a multiplicative and an additive model, to detect signals of DDI. We applied the models to four known DDIs (methotrexate-diclofenac and bone marrow depression, simvastatin-ciclosporin and myopathy, ketoconazole-terfenadine and torsades de pointes, and cisapride-erythromycin and torsades de pointes) and to four drug-event combinations where there is currently no evidence of a DDI (fexofenadine-ketoconazole and torsades de pointes, methotrexade-rofecoxib and bone marrow depression, fluvastatin-ciclosporin and myopathy, and cisapride-azithromycine and torsade de pointes) and estimated the measure of interaction on the two scales. Results The additive model correctly identified all four known DDIs by giving a statistically significant (P< 0.05) positive measure of interaction. The multiplicative model identified the first two of the known DDIs as having a statistically significant or borderline significant (P< 0.1) positive measure of interaction term, gave a nonsignificant positive trend for the third interaction (P= 0.27), and a negative trend for the last interaction. Both models correctly identified the four known non interactions by estimating a negative measure of interaction. Conclusions The spontaneous reports database is a valuable resource for detecting signals of DDIs. In particular, the additive model is more sensitive in detecting such signals. The multiplicative model may further help qualify the strength of the signal detected by the additive model. PMID:17506784

Method and apparatus for modeling interactions

DOEpatents

Xavier, Patrick G.

2002-01-01

The present invention provides a method and apparatus for modeling interactions that overcomes drawbacks. The method of the present invention comprises representing two bodies undergoing translations by two swept volume representations. Interactions such as nearest approach and collision can be modeled based on the swept body representations. The present invention is more robust and allows faster modeling than previous methods.

The influence of instructional interactions on students’ mental models about the quantization of physical observables: a modern physics course case

NASA Astrophysics Data System (ADS)

Didiş Körhasan, Nilüfer; Eryılmaz, Ali; Erkoç, Şakir

2016-01-01

Mental models are coherently organized knowledge structures used to explain phenomena. They interact with social environments and evolve with the interaction. Lacking daily experience with phenomena, the social interaction gains much more importance. In this part of our multiphase study, we investigate how instructional interactions influenced students’ mental models about the quantization of physical observables. Class observations and interviews were analysed by studying students’ mental models constructed in a modern physics course during an academic semester. The research revealed that students’ mental models were influenced by (1) the manner of teaching, including instructional methodologies and content specific techniques used by the instructor, (2) order of the topics and familiarity with concepts, and (3) peers.

Dyadic brain modelling, mirror systems and the ontogenetic ritualization of ape gesture

PubMed Central

Arbib, Michael; Ganesh, Varsha; Gasser, Brad

2014-01-01

The paper introduces dyadic brain modelling, offering both a framework for modelling the brains of interacting agents and a general framework for simulating and visualizing the interactions generated when the brains (and the two bodies) are each coded up in computational detail. It models selected neural mechanisms in ape brains supportive of social interactions, including putative mirror neuron systems inspired by macaque neurophysiology but augmented by increased access to proprioceptive state. Simulation results for a reduced version of the model show ritualized gesture emerging from interactions between a simulated child and mother ape. PMID:24778382

Dyadic brain modelling, mirror systems and the ontogenetic ritualization of ape gesture.

PubMed

Arbib, Michael; Ganesh, Varsha; Gasser, Brad

2014-01-01

The paper introduces dyadic brain modelling, offering both a framework for modelling the brains of interacting agents and a general framework for simulating and visualizing the interactions generated when the brains (and the two bodies) are each coded up in computational detail. It models selected neural mechanisms in ape brains supportive of social interactions, including putative mirror neuron systems inspired by macaque neurophysiology but augmented by increased access to proprioceptive state. Simulation results for a reduced version of the model show ritualized gesture emerging from interactions between a simulated child and mother ape.

Gene-Culture Coevolutionary Games

ERIC Educational Resources Information Center

Blute, Marion

2006-01-01

Gene-culture interactions have largely been modelled employing population genetic-type models. Moreover, in the most notable application to date, the "interactive" modes have been one way rather than bidirectional. This paper suggests using game theoretic, fully interactive models. Employing the logic utilized in population ecology for coevolution…

Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

PubMed Central

Momeni, Babak; Xie, Li; Shou, Wenying

2017-01-01

Pairwise models are commonly used to describe many-species communities. In these models, an individual receives additive fitness effects from pairwise interactions with each species in the community ('additivity assumption'). All pairwise interactions are typically represented by a single equation where parameters reflect signs and strengths of fitness effects ('universality assumption'). Here, we show that a single equation fails to qualitatively capture diverse pairwise microbial interactions. We build mechanistic reference models for two microbial species engaging in commonly-found chemical-mediated interactions, and attempt to derive pairwise models. Different equations are appropriate depending on whether a mediator is consumable or reusable, whether an interaction is mediated by one or more mediators, and sometimes even on quantitative details of the community (e.g. relative fitness of the two species, initial conditions). Our results, combined with potential violation of the additivity assumption in many-species communities, suggest that pairwise modeling will often fail to predict microbial dynamics. DOI: http://dx.doi.org/10.7554/eLife.25051.001 PMID:28350295

Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems

PubMed Central

Perez-Garcia, Octavio; Lear, Gavin; Singhal, Naresh

2016-01-01

We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN) models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms, and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA), experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e., (i) lumped networks, (ii) compartment per guild networks, (iii) bi-level optimization simulations, and (iv) dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach) are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial interactions can be used to analyze complex “omics” data and to infer and optimize metabolic processes. Thereby, SMN models are suitable to capitalize on advances in high-throughput molecular and metabolic data generation. SMN models are starting to be applied to describe microbial interactions during wastewater treatment, in-situ bioremediation, microalgae blooms methanogenic fermentation, and bioplastic production. Despite their current challenges, we envisage that SMN models have future potential for the design and development of novel growth media, biochemical pathways and synthetic microbial associations. PMID:27242701

Ferromagnetic interaction model of activity level in workplace communication

NASA Astrophysics Data System (ADS)

Akitomi, Tomoaki; Ara, Koji; Watanabe, Jun-ichiro; Yano, Kazuo

2013-03-01

The nature of human-human interaction, specifically, how people synchronize with each other in multiple-participant conversations, is described by a ferromagnetic interaction model of people’s activity levels. We found two microscopic human interaction characteristics from a real-environment face-to-face conversation. The first characteristic is that people quite regularly synchronize their activity level with that of the other participants in a conversation. The second characteristic is that the degree of synchronization increases as the number of participants increases. Based on these microscopic ferromagnetic characteristics, a “conversation activity level” was modeled according to the Ising model. The results of a simulation of activity level based on this model well reproduce macroscopic experimental measurements of activity level. This model will give a new insight into how people interact with each other in a conversation.

A polarizable dipole-dipole interaction model for evaluation of the interaction energies for N-H···O=C and C-H···O=C hydrogen-bonded complexes.

PubMed

Li, Shu-Shi; Huang, Cui-Ying; Hao, Jiao-Jiao; Wang, Chang-Sheng

2014-03-05

In this article, a polarizable dipole-dipole interaction model is established to estimate the equilibrium hydrogen bond distances and the interaction energies for hydrogen-bonded complexes containing peptide amides and nucleic acid bases. We regard the chemical bonds N-H, C=O, and C-H as bond dipoles. The magnitude of the bond dipole moment varies according to its environment. We apply this polarizable dipole-dipole interaction model to a series of hydrogen-bonded complexes containing the N-H···O=C and C-H···O=C hydrogen bonds, such as simple amide-amide dimers, base-base dimers, peptide-base dimers, and β-sheet models. We find that a simple two-term function, only containing the permanent dipole-dipole interactions and the van der Waals interactions, can produce the equilibrium hydrogen bond distances compared favorably with those produced by the MP2/6-31G(d) method, whereas the high-quality counterpoise-corrected (CP-corrected) MP2/aug-cc-pVTZ interaction energies for the hydrogen-bonded complexes can be well-reproduced by a four-term function which involves the permanent dipole-dipole interactions, the van der Waals interactions, the polarization contributions, and a corrected term. Based on the calculation results obtained from this polarizable dipole-dipole interaction model, the natures of the hydrogen bonding interactions in these hydrogen-bonded complexes are further discussed. Copyright © 2013 Wiley Periodicals, Inc.

Simplifying the interaction between cognitive models and task environments with the JSON Network Interface.

PubMed

Hope, Ryan M; Schoelles, Michael J; Gray, Wayne D

2014-12-01

Process models of cognition, written in architectures such as ACT-R and EPIC, should be able to interact with the same software with which human subjects interact. By eliminating the need to simulate the experiment, this approach would simplify the modeler's effort, while ensuring that all steps required of the human are also required by the model. In practice, the difficulties of allowing one software system to interact with another present a significant barrier to any modeler who is not also skilled at this type of programming. The barrier increases if the programming language used by the modeling software differs from that used by the experimental software. The JSON Network Interface simplifies this problem for ACT-R modelers, and potentially, modelers using other systems.

Quantitative systems pharmacology analysis of drug combination and scaling to humans: the interaction between noradrenaline and vasopressin on vasoconstriction.

PubMed

Yin, Anyue; Yamada, Akihiro; Stam, Wiro B; van Hasselt, Johan G C; van der Graaf, Piet H

2018-06-02

Development of combination therapies has received significant interest in recent years. Previously a two-receptor one-transducer (2R-1T) model was proposed to characterize drug interactions with two receptors that lead to the same phenotypic response through a common transducer pathway. We applied, for the first time, the 2R-1T model to characterize the interaction of noradrenaline and arginine-vasopressin on vasoconstriction, and performed inter-species scaling to humans using this mechanism-based model. Contractile data was obtained from in vitro rat small mesenteric arteries after exposure to single or combined challenges of noradrenaline and arginine-vasopressin with or without pre-treatment with the irreversible α-adrenoceptor antagonist, phenoxybenzamine. Data was analysed using the 2R-1T model to characterize the observed exposure-response relationships and drug-drug interaction. The model was then scaled to humans by accounting for differences in receptor density. With receptor affinities set to literature values, the 2R-1T model satisfactorily characterized the interaction between noradrenaline and arginine-vasopressin in rat small mesenteric arteries (relative standard error ≤ 20%), as well as the effect of phenoxybenzamine. Furthermore, after scaling the model to human vascular tissue, the model also adequately predicted the interaction between both agents on human renal arteries. The 2R-1T model can be of relevance to quantitatively characterize the interaction between two drugs that interact via different receptors and a common transducer pathway. Its mechanistic properties are valuable for scaling the model across species. This approach is therefore of significant value to rationally optimize novel combination treatments. This article is protected by copyright. All rights reserved.

An Interactive Model of Career Decision Making.

ERIC Educational Resources Information Center

Amundson, Norman E.

1995-01-01

The decision-making model described highlights the interaction between contextual factors, decision triggers, establishing a frame of the problem, reframing, and action planning. The interactive perspective is based on process and change. Career counseling with an interactive decision-making approach requires an acknowledgment of external…

Development of 3D browsing and interactive web system

NASA Astrophysics Data System (ADS)

Shi, Xiaonan; Fu, Jian; Jin, Chaolin

2017-09-01

In the current market, users need to download specific software or plug-ins to browse the 3D model, and browsing the system may be unstable, and it cannot be 3D model interaction issues In order to solve this problem, this paper presents a solution to the interactive browsing of the model in the server-side parsing model, and when the system is applied, the user only needs to input the system URL and upload the 3D model file to operate the browsing The server real-time parsing 3D model, the interactive response speed, these completely follows the user to walk the minimalist idea, and solves the current market block 3D content development question.

Entanglement and teleportation through a two-qubit Heisenberg XXZ model with the Dzyaloshinskii-Moriya interaction

NASA Astrophysics Data System (ADS)

Guo, J. L.; Song, H. S.

2010-01-01

We study the thermal entanglement in the two-qubit Heisenberg XXZ model with the Dzyaloshinskii-Moriya (DM) interaction, and teleport an unknown state using the model in thermal equilibrium state as a quantum channel. The effects of DM interaction, including Dx and Dz interaction, the anisotropy and temperature on the entanglement and fully entangled fraction are considered. What deserves mentioning here is that for the antiferromagnetic case, the Dx interaction can be more helpful for increasing the entanglement and critical temperature than Dz, but this cannot for teleportation.

A definitional framework for the human/biometric sensor interaction model

NASA Astrophysics Data System (ADS)

Elliott, Stephen J.; Kukula, Eric P.

2010-04-01

Existing definitions for biometric testing and evaluation do not fully explain errors in a biometric system. This paper provides a definitional framework for the Human Biometric-Sensor Interaction (HBSI) model. This paper proposes six new definitions based around two classifications of presentations, erroneous and correct. The new terms are: defective interaction (DI), concealed interaction (CI), false interaction (FI), failure to detect (FTD), failure to extract (FTX), and successfully acquired samples (SAS). As with all definitions, the new terms require a modification to the general biometric model developed by Mansfield and Wayman [1].

Constructing Interpretative Views of Learners' Interaction Behavior in an Open Learner Model

ERIC Educational Resources Information Center

Papanikolaou, Kyparisia A.

2015-01-01

In this paper, we discuss how externalizing learners' interaction behavior may support learners' explorations in an adaptive educational hypermedia environment that provides activity-oriented content. In particular, we propose a model for producing interpretative views of learners' interaction behavior and we further apply this model to…

Modeling Child–Nature Interaction in a Nature Preschool: A Proof of Concept

PubMed Central

Kahn, Peter H.; Weiss, Thea; Harrington, Kit

2018-01-01

This article provides a proof of concept for an approach to modeling child–nature interaction based on the idea of interaction patterns: characterizations of essential features of interaction between humans and nature, specified abstractly enough such that countless different instantiations of each one can occur – in more domestic or wild forms – given different types of nature, people, and purposes. The model draws from constructivist psychology, ecological psychology, and evolutionary psychology, and is grounded in observational data collected through a time-sampling methodology at a nature preschool. Through using a nature language that emphasizes ontogenetic and phylogenetic significance, seven keystone interaction patterns are described for this nature preschool: using one’s body vigorously in nature, striking wood on wood, constructing shelter, being in solitude in nature, lying on earth, cohabiting with a wild animal, and being outside in weather. These 7 interactions patterns are then brought together with 13 other patterns published elsewhere to provide a total of 20 keystone interaction patterns that begin to fill out the model, and to show its promise. Discussion focuses on what the model aims to be in terms of both product and process, on what work the model can currently do, and how to further develop the model. PMID:29896143

The Monash University Interactive Simple Climate Model

NASA Astrophysics Data System (ADS)

Dommenget, D.

2013-12-01

The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

User Interaction Modeling and Profile Extraction in Interactive Systems: A Groupware Application Case Study †

PubMed Central

Tîrnăucă, Cristina; Duque, Rafael; Montaña, José L.

2017-01-01

A relevant goal in human–computer interaction is to produce applications that are easy to use and well-adjusted to their users’ needs. To address this problem it is important to know how users interact with the system. This work constitutes a methodological contribution capable of identifying the context of use in which users perform interactions with a groupware application (synchronous or asynchronous) and provides, using machine learning techniques, generative models of how users behave. Additionally, these models are transformed into a text that describes in natural language the main characteristics of the interaction of the users with the system. PMID:28726762

Testing charged current quasi-elastic and multinucleon interaction models in the NEUT neutrino interaction generator with published datasets from the MiniBooNE and MINERνA experiments

NASA Astrophysics Data System (ADS)

Wilkinson, C.; Terri, R.; Andreopoulos, C.; Bercellie, A.; Bronner, C.; Cartwright, S.; de Perio, P.; Dobson, J.; Duffy, K.; Furmanski, A. P.; Haegel, L.; Hayato, Y.; Kaboth, A.; Mahn, K.; McFarland, K. S.; Nowak, J.; Redij, A.; Rodrigues, P.; Sánchez, F.; Schwehr, J. D.; Sinclair, P.; Sobczyk, J. T.; Stamoulis, P.; Stowell, P.; Tacik, R.; Thompson, L.; Tobayama, S.; Wascko, M. O.; Żmuda, J.

2016-04-01

There has been a great deal of theoretical work on sophisticated charged current quasi-elastic (CCQE) neutrino interaction models in recent years, prompted by a number of experimental results that measured unexpectedly large CCQE cross sections on nuclear targets. As the dominant interaction mode at T2K energies, and the signal process in oscillation analyses, it is important for the T2K experiment to include realistic CCQE cross section uncertainties in T2K analyses. To this end, T2K's Neutrino Interaction Working Group has implemented a number of recent models in NEUT, T2K's primary neutrino interaction event generator. In this paper, we give an overview of the models implemented and present fits to published νμ and ν¯ μ CCQE cross section measurements from the MiniBooNE and MINER ν A experiments. The results of the fits are used to select a default cross section model for future T2K analyses and to constrain the cross section uncertainties of the model. We find strong tension between datasets for all models investigated. Among the evaluated models, the combination of a modified relativistic Fermi gas with multinucleon CCQE-like interactions gives the most consistent description of the available data.

DSMC Simulation and Experimental Validation of Shock Interaction in Hypersonic Low Density Flow

PubMed Central

2014-01-01

Direct simulation Monte Carlo (DSMC) of shock interaction in hypersonic low density flow is developed. Three collision molecular models, including hard sphere (HS), variable hard sphere (VHS), and variable soft sphere (VSS), are employed in the DSMC study. The simulations of double-cone and Edney's type IV hypersonic shock interactions in low density flow are performed. Comparisons between DSMC and experimental data are conducted. Investigation of the double-cone hypersonic flow shows that three collision molecular models can predict the trend of pressure coefficient and the Stanton number. HS model shows the best agreement between DSMC simulation and experiment among three collision molecular models. Also, it shows that the agreement between DSMC and experiment is generally good for HS and VHS models in Edney's type IV shock interaction. However, it fails in the VSS model. Both double-cone and Edney's type IV shock interaction simulations show that the DSMC errors depend on the Knudsen number and the models employed for intermolecular interaction. With the increase in the Knudsen number, the DSMC error is decreased. The error is the smallest in HS compared with those in the VHS and VSS models. When the Knudsen number is in the level of 10−4, the DSMC errors, for pressure coefficient, the Stanton number, and the scale of interaction region, are controlled within 10%. PMID:24672360

Modeling of Tool-Tissue Interactions for Computer-Based Surgical Simulation: A Literature Review

PubMed Central

Misra, Sarthak; Ramesh, K. T.; Okamura, Allison M.

2009-01-01

Surgical simulators present a safe and potentially effective method for surgical training, and can also be used in robot-assisted surgery for pre- and intra-operative planning. Accurate modeling of the interaction between surgical instruments and organs has been recognized as a key requirement in the development of high-fidelity surgical simulators. Researchers have attempted to model tool-tissue interactions in a wide variety of ways, which can be broadly classified as (1) linear elasticity-based, (2) nonlinear (hyperelastic) elasticity-based finite element (FE) methods, and (3) other techniques that not based on FE methods or continuum mechanics. Realistic modeling of organ deformation requires populating the model with real tissue data (which are difficult to acquire in vivo) and simulating organ response in real time (which is computationally expensive). Further, it is challenging to account for connective tissue supporting the organ, friction, and topological changes resulting from tool-tissue interactions during invasive surgical procedures. Overcoming such obstacles will not only help us to model tool-tissue interactions in real time, but also enable realistic force feedback to the user during surgical simulation. This review paper classifies the existing research on tool-tissue interactions for surgical simulators specifically based on the modeling techniques employed and the kind of surgical operation being simulated, in order to inform and motivate future research on improved tool-tissue interaction models. PMID:20119508

Introductory lecture: interpreting and predicting Hofmeister salt ion and solute effects on biopolymer and model processes using the solute partitioning model.

PubMed

Record, M Thomas; Guinn, Emily; Pegram, Laurel; Capp, Michael

2013-01-01

Understanding how Hofmeister salt ions and other solutes interact with proteins, nucleic acids, other biopolymers and water and thereby affect protein and nucleic acid processes as well as model processes (e.g. solubility of model compounds) in aqueous solution is a longstanding goal of biophysical research. Empirical Hofmeister salt and solute "m-values" (derivatives of the observed standard free energy change for a model or biopolymer process with respect to solute or salt concentration m3) are equal to differences in chemical potential derivatives: m-value = delta(dmu2/dm3) = delta mu23, which quantify the preferential interactions of the solute or salt with the surface of the biopolymer or model system (component 2) exposed or buried in the process. Using the solute partitioning model (SPM), we dissect mu23 values for interactions of a solute or Hofmeister salt with a set of model compounds displaying the key functional groups of biopolymers to obtain interaction potentials (called alpha-values) that quantify the interaction of the solute or salt per unit area of each functional group or type of surface. Interpreted using the SPM, these alpha-values provide quantitative information about both the hydration of functional groups and the competitive interaction of water and the solute or salt with functional groups. The analysis corroborates and quantifies previous proposals that the Hofmeister anion and cation series for biopolymer processes are determined by ion-specific, mostly unfavorable interactions with hydrocarbon surfaces; the balance between these unfavorable nonpolar interactions and often-favorable interactions of ions with polar functional groups determine the series null points. The placement of urea and glycine betaine (GB) at opposite ends of the corresponding series of nonelectrolytes results from the favorable interactions of urea, and unfavorable interactions of GB, with many (but not all) biopolymer functional groups. Interaction potentials and local-bulk partition coefficients quantifying the distribution of solutes (e.g. urea, glycine betaine) and Hofmeister salt ions in the vicinity of each functional group make good chemical sense when interpreted in terms of competitive noncovalent interactions. These interaction potentials allow solute and Hofmeister (noncoulombic) salt effects on protein and nucleic acid processes to be interpreted or predicted, and allow the use of solutes and salts as probes of

The MV model of the color glass condensate for a finite number of sources including Coulomb interactions

DOE PAGES

McLerran, Larry; Skokov, Vladimir V.

2016-09-19

We modify the McLerran–Venugopalan model to include only a finite number of sources of color charge. In the effective action for such a system of a finite number of sources, there is a point-like interaction and a Coulombic interaction. The point interaction generates the standard fluctuation term in the McLerran–Venugopalan model. The Coulomb interaction generates the charge screening originating from well known evolution in x. Such a model may be useful for computing angular harmonics of flow measured in high energy hadron collisions for small systems. In this study we provide a basic formulation of the problem on a lattice.

Multi-gas interaction modeling on decorated semiconductor interfaces: A novel Fermi distribution-based response isotherm and the inverse hard/soft acid/base concept

NASA Astrophysics Data System (ADS)

Laminack, William; Gole, James

2015-12-01

A unique MEMS/NEMS approach is presented for the modeling of a detection platform for mixed gas interactions. Mixed gas analytes interact with nanostructured decorating metal oxide island sites supported on a microporous silicon substrate. The Inverse Hard/Soft acid/base (IHSAB) concept is used to assess a diversity of conductometric responses for mixed gas interactions as a function of these nanostructured metal oxides. The analyte conductometric responses are well represented using a combination diffusion/absorption-based model for multi-gas interactions where a newly developed response absorption isotherm, based on the Fermi distribution function is applied. A further coupling of this model with the IHSAB concept describes the considerations in modeling of multi-gas mixed analyte-interface, and analyte-analyte interactions. Taking into account the molecular electronic interaction of both the analytes with each other and an extrinsic semiconductor interface we demonstrate how the presence of one gas can enhance or diminish the reversible interaction of a second gas with the extrinsic semiconductor interface. These concepts demonstrate important considerations in the array-based formats for multi-gas sensing and its applications.

Membrane Interaction of Antimicrobial Peptides Using E. coli Lipid Extract as Model Bacterial Cell Membranes and SFG Spectroscopy

PubMed Central

Soblosky, Lauren; Ramamoorthy, Ayyalusamy; Chen, Zhan

2015-01-01

Supported lipid bilayers are used as a convenient model cell membrane system to study biologically important molecule-lipid interactions in situ. However, the lipid bilayer models are often simple and the acquired results with these models may not provide all pertinent information related to a real cell membrane. In this work, we use sum frequency generation (SFG) vibrational spectroscopy to study molecular-level interactions between the antimicrobial peptides (AMPs) MSI-594, ovispirin-1 G18, magainin 2 and a simple 1,2-dipalmitoyl-d62-sn-glycero-3-phosphoglycerol (dDPPG)-1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG) bilayer. We compared such interactions to those between the AMPs and a more complex dDPPG/E. coli polar lipid extract bilayer. We show that to fully understand more complex aspects of peptide-bilayer interaction, such as interaction kinetics, a heterogeneous lipid composition is required, such as the E. coli polar lipid extract. The discrepancy in peptide-bilayer interaction is likely due in part to the difference in bilayer charge between the two systems since highly negative charged lipids can promote more favorable electrostatic interactions between the peptide and lipid bilayer. Results presented in this paper indicate that more complex model bilayers are needed to accurately analyze peptide-cell membrane interactions and demonstrates the importance of using an appropriate lipid composition to study AMP interaction properties. PMID:25707312

Proteome-wide Prediction of Self-interacting Proteins Based on Multiple Properties*

PubMed Central

Liu, Zhongyang; Guo, Feifei; Zhang, Jiyang; Wang, Jian; Lu, Liang; Li, Dong; He, Fuchu

2013-01-01

Self-interacting proteins, whose two or more copies can interact with each other, play important roles in cellular functions and the evolution of protein interaction networks (PINs). Knowing whether a protein can self-interact can contribute to and sometimes is crucial for the elucidation of its functions. Previous related research has mainly focused on the structures and functions of specific self-interacting proteins, whereas knowledge on their overall properties is limited. Meanwhile, the two current most common high throughput protein interaction assays have limited ability to detect self-interactions because of biological artifacts and design limitations, whereas the bioinformatic prediction method of self-interacting proteins is lacking. This study aims to systematically study and predict self-interacting proteins from an overall perspective. We find that compared with other proteins the self-interacting proteins in the structural aspect contain more domains; in the evolutionary aspect they tend to be conserved and ancient; in the functional aspect they are significantly enriched with enzyme genes, housekeeping genes, and drug targets, and in the topological aspect tend to occupy important positions in PINs. Furthermore, based on these features, after feature selection, we use logistic regression to integrate six representative features, including Gene Ontology term, domain, paralogous interactor, enzyme, model organism self-interacting protein, and betweenness centrality in the PIN, to develop a proteome-wide prediction model of self-interacting proteins. Using 5-fold cross-validation and an independent test, this model shows good performance. Finally, the prediction model is developed into a user-friendly web service SLIPPER (SeLf-Interacting Protein PrEdictoR). Users may submit a list of proteins, and then SLIPPER will return the probability_scores measuring their possibility to be self-interacting proteins and various related annotation information. This work helps us understand the role self-interacting proteins play in cellular functions from an overall perspective, and the constructed prediction model may contribute to the high throughput finding of self-interacting proteins and provide clues for elucidating their functions. PMID:23422585

How Levels of Interactivity in Tutorials Affect Students' Learning of Modeling Transportation Problems in a Spreadsheet

ERIC Educational Resources Information Center

Seal, Kala Chand; Przasnyski, Zbigniew H.; Leon, Linda A.

2010-01-01

Do students learn to model OR/MS problems better by using computer-based interactive tutorials and, if so, does increased interactivity in the tutorials lead to better learning? In order to determine the effect of different levels of interactivity on student learning, we used screen capture technology to design interactive support materials for…

Continued use of an interactive computer game-based visual perception learning system in children with developmental delay.

PubMed

Lin, Hsien-Cheng; Chiu, Yu-Hsien; Chen, Yenming J; Wuang, Yee-Pay; Chen, Chiu-Ping; Wang, Chih-Chung; Huang, Chien-Ling; Wu, Tang-Meng; Ho, Wen-Hsien

2017-11-01

This study developed an interactive computer game-based visual perception learning system for special education children with developmental delay. To investigate whether perceived interactivity affects continued use of the system, this study developed a theoretical model of the process in which learners decide whether to continue using an interactive computer game-based visual perception learning system. The technology acceptance model, which considers perceived ease of use, perceived usefulness, and perceived playfulness, was extended by integrating perceived interaction (i.e., learner-instructor interaction and learner-system interaction) and then analyzing the effects of these perceptions on satisfaction and continued use. Data were collected from 150 participants (rehabilitation therapists, medical paraprofessionals, and parents of children with developmental delay) recruited from a single medical center in Taiwan. Structural equation modeling and partial-least-squares techniques were used to evaluate relationships within the model. The modeling results indicated that both perceived ease of use and perceived usefulness were positively associated with both learner-instructor interaction and learner-system interaction. However, perceived playfulness only had a positive association with learner-system interaction and not with learner-instructor interaction. Moreover, satisfaction was positively affected by perceived ease of use, perceived usefulness, and perceived playfulness. Thus, satisfaction positively affects continued use of the system. The data obtained by this study can be applied by researchers, designers of computer game-based learning systems, special education workers, and medical professionals. Copyright © 2017 Elsevier B.V. All rights reserved.

The Target Model of Strategic Interaction of Kazan Federal University and the Region in the Field of Education

ERIC Educational Resources Information Center

Gabdulchakov, Valerian F.

2016-01-01

The subject of the study in the article is conceptual basis of construction of the target model of interaction between University and region. Hence the topic of the article "the Target model of strategic interaction between the University and the region in the field of education." The objective was to design a target model of this…

Probing interaction and spatial curvature in the holographic dark energy model

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

Li, Miao; Li, Xiao-Dong; Wang, Shuang

2009-12-01

In this paper we place observational constraints on the interaction and spatial curvature in the holographic dark energy model. We consider three kinds of phenomenological interactions between holographic dark energy and matter, i.e., the interaction term Q is proportional to the energy densities of dark energy (ρ{sub Λ}), matter (ρ{sub m}), and matter plus dark energy (ρ{sub m}+ρ{sub Λ}). For probing the interaction and spatial curvature in the holographic dark energy model, we use the latest observational data including the type Ia supernovae (SNIa) Constitution data, the shift parameter of the cosmic microwave background (CMB) given by the five-year Wilkinsonmore » Microwave Anisotropy Probe (WMAP5) observations, and the baryon acoustic oscillation (BAO) measurement from the Sloan Digital Sky Survey (SDSS). Our results show that the interaction and spatial curvature in the holographic dark energy model are both rather small. Besides, it is interesting to find that there exists significant degeneracy between the phenomenological interaction and the spatial curvature in the holographic dark energy model.« less

Pedagogical Interaction in High School, the Structural and Functional Model of Pedagogical Interaction

ERIC Educational Resources Information Center

Semenova, Larissa A.; Kazantseva, Anastassiya I.; Sergeyeva, Valeriya V.; Raklova, Yekaterina M.; Baiseitova, Zhanar B.

2016-01-01

The study covers the problems of pedagogical technologies and their experimental implementation in the learning process. The theoretical aspects of the "student-teacher" interaction are investigated. A structural and functional model of pedagogical interaction is offered, which determines the conditions for improving pedagogical…

Statistical models for detecting differential chromatin interactions mediated by a protein.

PubMed

Niu, Liang; Li, Guoliang; Lin, Shili

2014-01-01

Chromatin interactions mediated by a protein of interest are of great scientific interest. Recent studies show that protein-mediated chromatin interactions can have different intensities in different types of cells or in different developmental stages of a cell. Such differences can be associated with a disease or with the development of a cell. Thus, it is of great importance to detect protein-mediated chromatin interactions with different intensities in different cells. A recent molecular technique, Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET), which uses formaldehyde cross-linking and paired-end sequencing, is able to detect genome-wide chromatin interactions mediated by a protein of interest. Here we proposed two models (One-Step Model and Two-Step Model) for two sample ChIA-PET count data (one biological replicate in each sample) to identify differential chromatin interactions mediated by a protein of interest. Both models incorporate the data dependency and the extent to which a fragment pair is related to a pair of DNA loci of interest to make accurate identifications. The One-Step Model makes use of the data more efficiently but is more computationally intensive. An extensive simulation study showed that the models can detect those differentially interacted chromatins and there is a good agreement between each classification result and the truth. Application of the method to a two-sample ChIA-PET data set illustrates its utility. The two models are implemented as an R package MDM (available at http://www.stat.osu.edu/~statgen/SOFTWARE/MDM).

Statistical Models for Detecting Differential Chromatin Interactions Mediated by a Protein

PubMed Central

Niu, Liang; Li, Guoliang; Lin, Shili

2014-01-01

Chromatin interactions mediated by a protein of interest are of great scientific interest. Recent studies show that protein-mediated chromatin interactions can have different intensities in different types of cells or in different developmental stages of a cell. Such differences can be associated with a disease or with the development of a cell. Thus, it is of great importance to detect protein-mediated chromatin interactions with different intensities in different cells. A recent molecular technique, Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET), which uses formaldehyde cross-linking and paired-end sequencing, is able to detect genome-wide chromatin interactions mediated by a protein of interest. Here we proposed two models (One-Step Model and Two-Step Model) for two sample ChIA-PET count data (one biological replicate in each sample) to identify differential chromatin interactions mediated by a protein of interest. Both models incorporate the data dependency and the extent to which a fragment pair is related to a pair of DNA loci of interest to make accurate identifications. The One-Step Model makes use of the data more efficiently but is more computationally intensive. An extensive simulation study showed that the models can detect those differentially interacted chromatins and there is a good agreement between each classification result and the truth. Application of the method to a two-sample ChIA-PET data set illustrates its utility. The two models are implemented as an R package MDM (available at http://www.stat.osu.edu/~statgen/SOFTWARE/MDM). PMID:24835279

Complex molecular assemblies at hand via interactive simulations.

PubMed

Delalande, Olivier; Férey, Nicolas; Grasseau, Gilles; Baaden, Marc

2009-11-30

Studying complex molecular assemblies interactively is becoming an increasingly appealing approach to molecular modeling. Here we focus on interactive molecular dynamics (IMD) as a textbook example for interactive simulation methods. Such simulations can be useful in exploring and generating hypotheses about the structural and mechanical aspects of biomolecular interactions. For the first time, we carry out low-resolution coarse-grain IMD simulations. Such simplified modeling methods currently appear to be more suitable for interactive experiments and represent a well-balanced compromise between an important gain in computational speed versus a moderate loss in modeling accuracy compared to higher resolution all-atom simulations. This is particularly useful for initial exploration and hypothesis development for rare molecular interaction events. We evaluate which applications are currently feasible using molecular assemblies from 1900 to over 300,000 particles. Three biochemical systems are discussed: the guanylate kinase (GK) enzyme, the outer membrane protease T and the soluble N-ethylmaleimide-sensitive factor attachment protein receptors complex involved in membrane fusion. We induce large conformational changes, carry out interactive docking experiments, probe lipid-protein interactions and are able to sense the mechanical properties of a molecular model. Furthermore, such interactive simulations facilitate exploration of modeling parameters for method improvement. For the purpose of these simulations, we have developed a freely available software library called MDDriver. It uses the IMD protocol from NAMD and facilitates the implementation and application of interactive simulations. With MDDriver it becomes very easy to render any particle-based molecular simulation engine interactive. Here we use its implementation in the Gromacs software as an example. Copyright 2009 Wiley Periodicals, Inc.

Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model.

PubMed

Fernandes, Jose A; Cheung, William W L; Jennings, Simon; Butenschön, Momme; de Mora, Lee; Frölicher, Thomas L; Barange, Manuel; Grant, Alastair

2013-08-01

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment. © 2013 John Wiley & Sons Ltd.

Observational constraint on the interacting dark energy models including the Sandage-Loeb test

NASA Astrophysics Data System (ADS)

Zhang, Ming-Jian; Liu, Wen-Biao

2014-05-01

Two types of interacting dark energy models are investigated using the type Ia supernova (SNIa), observational data (OHD), cosmic microwave background shift parameter, and the secular Sandage-Loeb (SL) test. In the investigation, we have used two sets of parameter priors including WMAP-9 and Planck 2013. They have shown some interesting differences. We find that the inclusion of SL test can obviously provide a more stringent constraint on the parameters in both models. For the constant coupling model, the interaction term has been improved to be only a half of the original scale on corresponding errors. Comparing with only SNIa and OHD, we find that the inclusion of the SL test almost reduces the best-fit interaction to zero, which indicates that the higher-redshift observation including the SL test is necessary to track the evolution of the interaction. For the varying coupling model, data with the inclusion of the SL test show that the parameter at C.L. in Planck priors is , where the constant is characteristic for the severity of the coincidence problem. This indicates that the coincidence problem will be less severe. We then reconstruct the interaction , and we find that the best-fit interaction is also negative, similar to the constant coupling model. However, for a high redshift, the interaction generally vanishes at infinity. We also find that the phantom-like dark energy with is favored over the CDM model.

Extrapolating a Dyadic Model to Small Group Methodology: Validation of the Spitzberg and Cupach Model of Communication Competence.

ERIC Educational Resources Information Center

Keyton, Joann

A study assessed the validity of applying the Spitzberg and Cupach dyadic model of communication competence to small group interaction. Twenty-four students, in five task-oriented work groups, completed questionnaires concerning self-competence, alter competence, interaction effectiveness, and other group members' interaction appropriateness. They…

Understanding Parental Monitoring through Analysis of Monitoring Episodes in Context

ERIC Educational Resources Information Center

Hayes, Louise; Hudson, Alan; Matthews, Jan

2007-01-01

A model of monitoring interactions was proposed that is based on behavioural principles and places episodic parent-adolescent interactions at the centre of analysis for monitoring. The process-monitoring model contends that monitoring is an interactive process between parents and their adolescents, nested within a social setting. In the model it…

Ideology and Interaction: Debating Determinisms in Literacy Studies

ERIC Educational Resources Information Center

Collin, Ross; Street, Brian V.

2014-01-01

In this exchange, Street and Collin debate the merits of the interaction model of literacy that Collin outlined in a recent issue of Reading Research Quarterly. Built as a complement and a counter to Street's ideological model of literacy, Collin's interaction model defines literacies as technologies that coevolve with sociocultural…

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

PubMed Central

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-01-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km2 to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere. PMID:22686347

Method and apparatus for modeling interactions

DOEpatents

Xavier, Patrick G.

2000-08-08

A method and apparatus for modeling interactions between bodies. The method comprises representing two bodies undergoing translations and rotations by two hierarchical swept volume representations. Interactions such as nearest approach and collision can be modeled based on the swept body representations. The present invention can serve as a practical tool in motion planning, CAD systems, simulation systems, safety analysis, and applications that require modeling time-based interactions. A body can be represented in the present invention by a union of convex polygons and convex polyhedra. As used generally herein, polyhedron includes polygon, and polyhedra includes polygons. The body undergoing translation can be represented by a swept body representation, where the swept body representation comprises a hierarchical bounding volume representation whose leaves each contain a representation of the region swept by a section of the body during the translation, and where the union of the regions is a superset of the region swept by the surface of the body during translation. Interactions between two bodies thus represented can be modeled by modeling interactions between the convex hulls of the finite sets of discrete points in the swept body representations.

System theoretic models for high density VLSI structures

NASA Astrophysics Data System (ADS)

Dickinson, Bradley W.; Hopkins, William E., Jr.

This research project involved the development of mathematical models for analysis, synthesis, and simulation of large systems of interacting devices. The work was motivated by problems that may become important in high density VLSI chips with characteristic feature sizes less than 1 micron: it is anticipated that interactions of neighboring devices will play an important role in the determination of circuit properties. It is hoped that the combination of high device densities and such local interactions can somehow be exploited to increase circuit speed and to reduce power consumption. To address these issues from the point of view of system theory, research was pursued in the areas of nonlinear and stochastic systems and into neural network models. Statistical models were developed to characterize various features of the dynamic behavior of interacting systems. Random process models for studying the resulting asynchronous modes of operation were investigated. The local interactions themselves may be modeled as stochastic effects. The resulting behavior was investigated through the use of various scaling limits, and by a combination of other analytical and simulation techniques. Techniques arising in a variety of disciplines where models of interaction were formulated and explored were considered and adapted for use.

Monte Carlo modeling of atomic oxygen attack of polymers with protective coatings on LDEF

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Degroh, Kim K.; Auer, Bruce M.; Gebauer, Linda; Edwards, Jonathan L.

1993-01-01

Characterization of the behavior of atomic oxygen interaction with materials on the Long Duration Exposure Facility (LDEF) assists in understanding of the mechanisms involved. Thus the reliability of predicting in-space durability of materials based on ground laboratory testing should be improved. A computational model which simulates atomic oxygen interaction with protected polymers was developed using Monte Carlo techniques. Through the use of an assumed mechanistic behavior of atomic oxygen interaction based on in-space atomic oxygen erosion of unprotected polymers and ground laboratory atomic oxygen interaction with protected polymers, prediction of atomic oxygen interaction with protected polymers on LDEF was accomplished. However, the results of these predictions are not consistent with the observed LDEF results at defect sites in protected polymers. Improved agreement between observed LDEF results and predicted Monte Carlo modeling can be achieved by modifying of the atomic oxygen interactive assumptions used in the model. LDEF atomic oxygen undercutting results, modeling assumptions, and implications are presented.

"Bohr's Atomic Model."

ERIC Educational Resources Information Center

Willden, Jeff

2001-01-01

"Bohr's Atomic Model" is a small interactive multimedia program that introduces the viewer to a simplified model of the atom. This interactive simulation lets students build an atom using an atomic construction set. The underlying design methodology for "Bohr's Atomic Model" is model-centered instruction, which means the central model of the…

Simulating an emergency department: the importance of modeling the interactions between physicians and delegates in a discrete event simulation.

PubMed

Lim, Morgan E; Worster, Andrew; Goeree, Ron; Tarride, Jean-Éric

2013-05-22

Computer simulation studies of the emergency department (ED) are often patient driven and consider the physician as a human resource whose primary activity is interacting directly with the patient. In many EDs, physicians supervise delegates such as residents, physician assistants and nurse practitioners each with different skill sets and levels of independence. The purpose of this study is to present an alternative approach where physicians and their delegates in the ED are modeled as interacting pseudo-agents in a discrete event simulation (DES) and to compare it with the traditional approach ignoring such interactions. The new approach models a hierarchy of heterogeneous interacting pseudo-agents in a DES, where pseudo-agents are entities with embedded decision logic. The pseudo-agents represent a physician and delegate, where the physician plays a senior role to the delegate (i.e. treats high acuity patients and acts as a consult for the delegate). A simple model without the complexity of the ED is first created in order to validate the building blocks (programming) used to create the pseudo-agents and their interaction (i.e. consultation). Following validation, the new approach is implemented in an ED model using data from an Ontario hospital. Outputs from this model are compared with outputs from the ED model without the interacting pseudo-agents. They are compared based on physician and delegate utilization, patient waiting time for treatment, and average length of stay. Additionally, we conduct sensitivity analyses on key parameters in the model. In the hospital ED model, comparisons between the approach with interaction and without showed physician utilization increase from 23% to 41% and delegate utilization increase from 56% to 71%. Results show statistically significant mean time differences for low acuity patients between models. Interaction time between physician and delegate results in increased ED length of stay and longer waits for beds. This example shows the importance of accurately modeling physician relationships and the roles in which they treat patients. Neglecting these relationships could lead to inefficient resource allocation due to inaccurate estimates of physician and delegate time spent on patient related activities and length of stay.

Object Oriented Modeling and Design

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali

2007-01-01

The Object Oriented Modeling and Design seminar is intended for software professionals and students, it covers the concepts and a language-independent graphical notation that can be used to analyze problem requirements, and design a solution to the problem. The seminar discusses the three kinds of object-oriented models class, state, and interaction. The class model represents the static structure of a system, the state model describes the aspects of a system that change over time as well as control behavior and the interaction model describes how objects collaborate to achieve overall results. Existing knowledge of object oriented programming may benefit the learning of modeling and good design. Specific expectations are: Create a class model, Read, recognize, and describe a class model, Describe association and link, Show abstract classes used with multiple inheritance, Explain metadata, reification and constraints, Group classes into a package, Read, recognize, and describe a state model, Explain states and transitions, Read, recognize, and describe interaction model, Explain Use cases and use case relationships, Show concurrency in activity diagram, Object interactions in sequence diagram.

Figure-ground organization and object recognition processes: an interactive account.

PubMed

Vecera, S P; O'Reilly, R C

1998-04-01

Traditional bottom-up models of visual processing assume that figure-ground organization precedes object recognition. This assumption seems logically necessary: How can object recognition occur before a region is labeled as figure? However, some behavioral studies find that familiar regions are more likely to be labeled figure than less familiar regions, a problematic finding for bottom-up models. An interactive account is proposed in which figure-ground processes receive top-down input from object representations in a hierarchical system. A graded, interactive computational model is presented that accounts for behavioral results in which familiarity effects are found. The interactive model offers an alternative conception of visual processing to bottom-up models.

Symmetry breaking in (gravitating) scalar field models describing interacting boson stars and Q-balls

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

Brihaye, Yves; Caebergs, Thierry; Hartmann, Betti

2009-09-15

We investigate the properties of interacting Q-balls and boson stars that sit on top of each other in great detail. The model that describes these solutions is essentially a (gravitating) two-scalar field model where both scalar fields are complex. We construct interacting Q-balls or boson stars with arbitrarily small charges but finite mass. We observe that in the interacting case--where the interaction can be either due to the potential or due to gravity--two types of solutions exist for equal frequencies: one for which the two-scalar fields are equal, but also one for which the two-scalar fields differ. This constitutes amore » symmetry breaking in the model. While for Q-balls asymmetric solutions have always corresponding symmetric solutions and are thus likely unstable to decay to symmetric solutions with lower energy, there exists a parameter regime for interacting boson stars, where only asymmetric solutions exist. We present the domain of existence for two interacting nonrotating solutions as well as for solutions describing the interaction between rotating and nonrotating Q-balls and boson stars, respectively.« less

Interacting dark energy: Dynamical system analysis

NASA Astrophysics Data System (ADS)

Golchin, Hanif; Jamali, Sara; Ebrahimi, Esmaeil

We investigate the impacts of interaction between dark matter (DM) and dark energy (DE) in the context of two DE models, holographic (HDE) and ghost dark energy (GDE). In fact, using the dynamical system analysis, we obtain the cosmological consequence of several interactions, considering all relevant component of universe, i.e. matter (dark and luminous), radiation and DE. Studying the phase space for all interactions in detail, we show the existence of unstable matter-dominated and stable DE-dominated phases. We also show that linear interactions suffer from the absence of standard radiation-dominated epoch. Interestingly, this failure resolved by adding the nonlinear interactions to the models. We find an upper bound for the value of the coupling constant of the interaction between DM and DE as b < 0.57in the case of holographic model, and b < 0.61 in the case of GDE model, to result in a cosmological viable matter-dominated epoch. More specifically, this bound is vital to satisfy instability and deceleration of matter-dominated epoch.

Inferring genetic interactions via a nonlinear model and an optimization algorithm.

PubMed

Chen, Chung-Ming; Lee, Chih; Chuang, Cheng-Long; Wang, Chia-Chang; Shieh, Grace S

2010-02-26

Biochemical pathways are gradually becoming recognized as central to complex human diseases and recently genetic/transcriptional interactions have been shown to be able to predict partial pathways. With the abundant information made available by microarray gene expression data (MGED), nonlinear modeling of these interactions is now feasible. Two of the latest advances in nonlinear modeling used sigmoid models to depict transcriptional interaction of a transcription factor (TF) for a target gene, but do not model cooperative or competitive interactions of several TFs for a target. An S-shape model and an optimization algorithm (GASA) were developed to infer genetic interactions/transcriptional regulation of several genes simultaneously using MGED. GASA consists of a genetic algorithm (GA) and a simulated annealing (SA) algorithm, which is enhanced by a steepest gradient descent algorithm to avoid being trapped in local minimum. Using simulated data with various degrees of noise, we studied how GASA with two model selection criteria and two search spaces performed. Furthermore, GASA was shown to outperform network component analysis, the time series network inference algorithm (TSNI), GA with regular GA (GAGA) and GA with regular SA. Two applications are demonstrated. First, GASA is applied to infer a subnetwork of human T-cell apoptosis. Several of the predicted interactions are supported by the literature. Second, GASA was applied to infer the transcriptional factors of 34 cell cycle regulated targets in S. cerevisiae, and GASA performed better than one of the latest advances in nonlinear modeling, GAGA and TSNI. Moreover, GASA is able to predict multiple transcription factors for certain targets, and these results coincide with experiments confirmed data in YEASTRACT. GASA is shown to infer both genetic interactions and transcriptional regulatory interactions well. In particular, GASA seems able to characterize the nonlinear mechanism of transcriptional regulatory interactions (TIs) in yeast, and may be applied to infer TIs in other organisms. The predicted genetic interactions of a subnetwork of human T-cell apoptosis coincide with existing partial pathways, suggesting the potential of GASA on inferring biochemical pathways.

How social factors and behavioural strategies affect feeding and social interaction patterns in pigs.

PubMed

Boumans, Iris J M M; de Boer, Imke J M; Hofstede, Gert Jan; Bokkers, Eddie A M

2018-04-26

Animals living in groups compete for food resources and face food conflicts. These conflicts are affected by social factors (e.g. competition level) and behavioural strategies (e.g. avoidance). This study aimed to deepen our understanding of the complex interactions between social factors and behavioural strategies affecting feeding and social interaction patterns in animals. We focused on group-housed growing pigs, Sus scrofa, which typically face conflicts around the feeder, and of which patterns in various competitive environments (i.e. pig:feeder ratio) have been documented soundly. An agent-based model was developed to explore how interactions among social factors and behavioural strategies can affect various feeding and social interaction patterns differently under competitive situations. Model results show that pig and diet characteristics interact with group size and affect daily feeding patterns (e.g. feed intake and feeding time) and conflicts around the feeder. The level of competition can cause a turning point in feeding and social interaction patterns. Beyond a certain point of competition, meal-based (e.g. meal frequency) and social interaction patterns (e.g. displacements) are determined mainly by behavioural strategies. The average daily feeding time can be used to predict the group size at which this turning point occurs. Under the model's assumptions, social facilitation was relatively unimportant in the causation of behavioural patterns in pigs. To validate our model, simulated patterns were compared with empirical patterns in conventionally housed pigs. Similarities between empirical and model patterns support the model results. Our model can be used as a tool in further research for studying the effects of social factors and group dynamics on individual variation in feeding and social interaction patterns in pigs, as well as in other animal species. Copyright © 2018 Elsevier Inc. All rights reserved.

Sequential Exposure of Bortezomib and Vorinostat is Synergistic in Multiple Myeloma Cells

PubMed Central

Nanavati, Charvi; Mager, Donald E.

2018-01-01

Purpose To examine the combination of bortezomib and vorinostat in multiple myeloma cells (U266) and xenografts, and to assess the nature of their potential interactions with semi-mechanistic pharmacodynamic models and biomarkers. Methods U266 proliferation was examined for a range of bortezomib and vorinostat exposure times and concentrations (alone and in combination). A non-competitive interaction model was used with interaction parameters that reflect the nature of drug interactions after simultaneous and sequential exposures. p21 and cleaved PARP were measured using immunoblotting to assess critical biomarker dynamics. For xenografts, data were extracted from literature and modeled with a PK/PD model with an interaction parameter. Results Estimated model parameters for simultaneous in vitro and xenograft treatments suggested additive drug effects. The sequence of bortezomib preincubation for 24 hours, followed by vorinostat for 24 hours, resulted in an estimated interaction term significantly less than 1, suggesting synergistic effects. p21 and cleaved PARP were also up-regulated the most in this sequence. Conclusions Semi-mechanistic pharmacodynamic modeling suggests synergistic pharmacodynamic interactions for the sequential administration of bortezomib followed by vorinostat. Increased p21 and cleaved PARP expression can potentially explain mechanisms of their enhanced effects, which require further PK/PD systems analysis to suggest an optimal dosing regimen. PMID:28101809

Membrane interaction of antimicrobial peptides using E. coli lipid extract as model bacterial cell membranes and SFG spectroscopy.

PubMed

Soblosky, Lauren; Ramamoorthy, Ayyalusamy; Chen, Zhan

2015-04-01

Supported lipid bilayers are used as a convenient model cell membrane system to study biologically important molecule-lipid interactions in situ. However, the lipid bilayer models are often simple and the acquired results with these models may not provide all pertinent information related to a real cell membrane. In this work, we use sum frequency generation (SFG) vibrational spectroscopy to study molecular-level interactions between the antimicrobial peptides (AMPs) MSI-594, ovispirin-1 G18, magainin 2 and a simple 1,2-dipalmitoyl-d62-sn-glycero-3-phosphoglycerol (dDPPG)/1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG) bilayer. We compared such interactions to those between the AMPs and a more complex dDPPG/Escherichia coli (E. coli) polar lipid extract bilayer. We show that to fully understand more complex aspects of peptide-bilayer interaction, such as interaction kinetics, a heterogeneous lipid composition is required, such as the E. coli polar lipid extract. The discrepancy in peptide-bilayer interaction is likely due in part to the difference in bilayer charge between the two systems since highly negative charged lipids can promote more favorable electrostatic interactions between the peptide and lipid bilayer. Results presented in this paper indicate that more complex model bilayers are needed to accurately analyze peptide-cell membrane interactions and demonstrates the importance of using an appropriate lipid composition to study AMP interaction properties. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Theoretical and Numerical Studies of a Vortex - Interaction Problem

NASA Astrophysics Data System (ADS)

Hsu, To-Ming

The problem of vortex-airfoil interaction has received considerable interest in the helicopter industry. This phenomenon has been shown to be a major source of noise, vibration, and structural fatigue in helicopter flight. Since unsteady flow is always associated with vortex shedding and movement of free vortices, the problem of vortex-airfoil interaction also serves as a basic building block in unsteady aerodynamics. A careful study of the vortex-airfoil interaction reveals the major effects of the vortices on the generation of unsteady aerodynamic forces, especially the lift. The present work establishes three different flow models to study the vortex-airfoil interaction problem: a theoretical model, an inviscid flow model, and a viscous flow model. In the first two models, a newly developed aerodynamic force theorem has been successfully applied to identify the contributions to unsteady forces from various vortical systems in the flow field. Through viscous flow analysis, different features of laminar interaction, turbulent attached interaction, and turbulent separated interaction are examined. Along with the study of the vortex-airfoil interaction problem, several new schemes are developed for inviscid and viscous flow solutions. New formulas are derived to determine the trailing edge flow conditions, such as flow velocity and direction, in unsteady inviscid flow. A new iteration scheme that is faster for higher Reynolds number is developed for solving the viscous flow problem.

Interactions of Metacognition with Motivation and Affect in Self-Regulated Learning: The MASRL Model

ERIC Educational Resources Information Center

Efklides, Anastasia

2011-01-01

Metacognition, motivation, and affect are components of self-regulated learning (SRL) that interact. The "metacognitive and affective model of self-regulated learning" (the MASRL model) distinguishes two levels of functioning in SRL, namely, the Person level and the Task x Person level. At the Person level interactions between trait-like…

A Cognitive Model of How Interactive Multimedia Authoring Facilitates Conceptual Understanding of Object-Oriented Programming in Novices

ERIC Educational Resources Information Center

Yuen, Timothy; Liu, Min

2011-01-01

This paper presents a cognitive model of how interactive multimedia authoring (IMA) affect novices' cognition in object-oriented programming. This model was generated through an empirical study of first year computer science students at the university level being engaged in interactive multimedia authoring of a role-playing game. Clinical…

Understanding Language Learning: Review of the Application of the Interaction Model in Foreign Language Contexts

ERIC Educational Resources Information Center

Dixon, L. Quentin; Wu, Shuang

2014-01-01

Purpose: This paper examined the application of the input-interaction-output model in English-as-Foreign-Language (EFL) learning environments with four specific questions: (1) How do the three components function in the model? (2) Does interaction in the foreign language classroom seem to be effective for foreign language acquisition? (3) What…

Cyberdemocracy and Online Politics: A New Model of Interactivity

ERIC Educational Resources Information Center

Ferber, Paul; Foltz, Franz; Pugliese, Rudy

2007-01-01

Building on McMillan's two-way model of interactivity, this study presents a three-way model of interactive communication, which is used to assess political Web sites' progress toward the ideals of cyberdemocracy and the fostering of public deliberation. Results of a 3-year study of state legislature Web sites, an analysis of the community…

Learning with Interactive Whiteboards: Determining the Factors on Promoting Interactive Whiteboards to Students by Technology Acceptance Model

ERIC Educational Resources Information Center

Kilic, Eylem; Güler, Çetin; Çelik, H. Eray; Tatli, Cemal

2015-01-01

Purpose: The purpose of this study is to investigate the factors which might affect the intention to use interactive whiteboards (IWBs) by university students, using Technology Acceptance Model by the structural equation modeling approach. The following hypothesis guided the current study: H1. There is a positive relationship between IWB…

A Nonlinear Model for Gene-Based Gene-Environment Interaction.

PubMed

Sa, Jian; Liu, Xu; He, Tao; Liu, Guifen; Cui, Yuehua

2016-06-04

A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

Interactions within the MHC contribute to the genetic architecture of celiac disease.

PubMed

Goudey, Benjamin; Abraham, Gad; Kikianty, Eder; Wang, Qiao; Rawlinson, Dave; Shi, Fan; Haviv, Izhak; Stern, Linda; Kowalczyk, Adam; Inouye, Michael

2017-01-01

Interaction analysis of GWAS can detect signal that would be ignored by single variant analysis, yet few robust interactions in humans have been detected. Recent work has highlighted interactions in the MHC region between known HLA risk haplotypes for various autoimmune diseases. To better understand the genetic interactions underlying celiac disease (CD), we have conducted exhaustive genome-wide scans for pairwise interactions in five independent CD case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 14 independent interaction signals within the MHC region that achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD interaction signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkin's lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for statistical interaction outside the MHC was not observed. Both within and between European populations, we observed striking consistency of two-locus models and model distribution. Within the UK population, models of CD based on both interactions and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. The interactions signal detected across the five cohorts indicates the presence of novel associations in the MHC region that cannot be detected using additive models. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.

Model-free inference of direct network interactions from nonlinear collective dynamics.

PubMed

Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

2017-12-19

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

The Bilingual Language Interaction Network for Comprehension of Speech*

PubMed Central

Marian, Viorica

2013-01-01

During speech comprehension, bilinguals co-activate both of their languages, resulting in cross-linguistic interaction at various levels of processing. This interaction has important consequences for both the structure of the language system and the mechanisms by which the system processes spoken language. Using computational modeling, we can examine how cross-linguistic interaction affects language processing in a controlled, simulated environment. Here we present a connectionist model of bilingual language processing, the Bilingual Language Interaction Network for Comprehension of Speech (BLINCS), wherein interconnected levels of processing are created using dynamic, self-organizing maps. BLINCS can account for a variety of psycholinguistic phenomena, including cross-linguistic interaction at and across multiple levels of processing, cognate facilitation effects, and audio-visual integration during speech comprehension. The model also provides a way to separate two languages without requiring a global language-identification system. We conclude that BLINCS serves as a promising new model of bilingual spoken language comprehension. PMID:24363602

Exploring the roles of interaction and flow in explaining nurses' e-learning acceptance.

PubMed

Cheng, Yung-Ming

2013-01-01

To provide safe and competent patient care, it is very important that medical institutions should provide nurses with continuing education by using appropriate learning methods. As compared to traditional learning, electronic learning (e-learning) is a more flexible method for nurses' in-service learning. Hence, e-learning is expected to play a pivotal role in providing continuing education for nurses. This study's purpose was to explore the role and relevance of interaction factors, intrinsic motivator (i.e., flow), and extrinsic motivators (i.e., perceived usefulness (PU) and perceived ease of use (PEOU)) in explaining nurses' intention to use the e-learning system. Based on the technology acceptance model (TAM) with the flow theory, this study's research model presents three types of interaction factors, learner-system interaction, instructor-learner interaction, and learner-learner interaction to construct an extended TAM to explore nurses' intention to use the e-learning system. Sample data were gathered from nurses at two regional hospitals in Taiwan. A total of 320 questionnaires were distributed, 254 (79.375%) questionnaires were returned. Consequently, 218 usable questionnaires were analyzed in this study, with a usable response rate of 68.125%. First, confirmatory factor analysis was used to develop the measurement model. Second, to explore the causal relationships among all constructs, the structural model for the research model was tested by using structural equation modeling. First, learner-system interaction, instructor-learner interaction, and learner-learner interaction respectively had significant effects on PU, PEOU, and flow. Next, flow had significant effects on PU and PEOU, and PEOU had a significant effect on PU. Finally, the effects of flow, PU, and PEOU on intention to use were significant. Synthetically speaking, learner-system interaction, instructor-learner interaction, and learner-learner interaction can indirectly make significant impacts on nurses' usage intention of the e-learning system via their extrinsic motivators (i.e., PU and PEOU) and intrinsic motivator (i.e., flow). Copyright © 2012 Elsevier Ltd. All rights reserved.

Relativistic quantum optics: The relativistic invariance of the light-matter interaction models

NASA Astrophysics Data System (ADS)

Martín-Martínez, Eduardo; Rodriguez-Lopez, Pablo

2018-05-01

In this article we discuss the invariance under general changes of reference frame of all the physical predictions of particle detector models in quantum field theory in general and, in particular, of those used in quantum optics to model atoms interacting with light. We find explicitly how the light-matter interaction Hamiltonians change under general coordinate transformations, and analyze the subtleties of the Hamiltonians commonly used to describe the light-matter interaction when relativistic motion is taken into account.

Interpretation of neutrino-matter interactions at low energies as contraction of gauge group of Electroweak Model

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

Gromov, N. A., E-mail: gromov@dm.komisc.ru

The very weak neutrino-matter interactions are explained with the help of the gauge group contraction of the standard Electroweak Model. The mathematical contraction procedure is connected with the energy dependence of the interaction cross section for neutrinos and corresponds to the limiting case of the Electroweak Model at low energies. Contraction parameter is connected with the universal Fermi constant of weak interactions and neutrino energy as j{sup 2}(s) = {radical}(G{sub F} s)

Drivers' communicative interactions: on-road observations and modelling for integration in future automation systems.

PubMed

Portouli, Evangelia; Nathanael, Dimitris; Marmaras, Nicolas

2014-01-01

Social interactions with other road users are an essential component of the driving activity and may prove critical in view of future automation systems; still up to now they have received only limited attention in the scientific literature. In this paper, it is argued that drivers base their anticipations about the traffic scene to a large extent on observations of social behaviour of other 'animate human-vehicles'. It is further argued that in cases of uncertainty, drivers seek to establish a mutual situational awareness through deliberate communicative interactions. A linguistic model is proposed for modelling these communicative interactions. Empirical evidence from on-road observations and analysis of concurrent running commentary by 25 experienced drivers support the proposed model. It is suggested that the integration of a social interactions layer based on illocutionary acts in future driving support and automation systems will improve their performance towards matching human driver's expectations. Practitioner Summary: Interactions between drivers on the road may play a significant role in traffic coordination. On-road observations and running commentaries are presented as empirical evidence to support a model of such interactions; incorporation of drivers' interactions in future driving support and automation systems may improve their performance towards matching driver's expectations.

Statistical interactions and Bayes estimation of log odds in case-control studies.

PubMed

Satagopan, Jaya M; Olson, Sara H; Elston, Robert C

2017-04-01

This paper is concerned with the estimation of the logarithm of disease odds (log odds) when evaluating two risk factors, whether or not interactions are present. Statisticians define interaction as a departure from an additive model on a certain scale of measurement of the outcome. Certain interactions, known as removable interactions, may be eliminated by fitting an additive model under an invertible transformation of the outcome. This can potentially provide more precise estimates of log odds than fitting a model with interaction terms. In practice, we may also encounter nonremovable interactions. The model must then include interaction terms, regardless of the choice of the scale of the outcome. However, in practical settings, we do not know at the outset whether an interaction exists, and if so whether it is removable or nonremovable. Rather than trying to decide on significance levels to test for the existence of removable and nonremovable interactions, we develop a Bayes estimator based on a squared error loss function. We demonstrate the favorable bias-variance trade-offs of our approach using simulations, and provide empirical illustrations using data from three published endometrial cancer case-control studies. The methods are implemented in an R program, and available freely at http://www.mskcc.org/biostatistics/~satagopj .

Time and dose-dependent risk of pneumococcal pneumonia following influenza: a model for within-host interaction between influenza and Streptococcus pneumoniae

PubMed Central

Shrestha, Sourya; Foxman, Betsy; Dawid, Suzanne; Aiello, Allison E.; Davis, Brian M.; Berus, Joshua; Rohani, Pejman

2013-01-01

A significant fraction of seasonal and in particular pandemic influenza deaths are attributed to secondary bacterial infections. In animal models, influenza virus predisposes hosts to severe infection with both Streptococcus pneumoniae and Staphylococcus aureus. Despite its importance, the mechanistic nature of the interaction between influenza and pneumococci, its dependence on the timing and sequence of infections as well as the clinical and epidemiological consequences remain unclear. We explore an immune-mediated model of the viral–bacterial interaction that quantifies the timing and the intensity of the interaction. Taking advantage of the wealth of knowledge gained from animal models, and the quantitative understanding of the kinetics of pathogen-specific immunological dynamics, we formulate a mathematical model for immune-mediated interaction between influenza virus and S. pneumoniae in the lungs. We use the model to examine the pathogenic effect of inoculum size and timing of pneumococcal invasion relative to influenza infection, as well as the efficacy of antivirals in preventing severe pneumococcal disease. We find that our model is able to capture the key features of the interaction observed in animal experiments. The model predicts that introduction of pneumococcal bacteria during a 4–6 day window following influenza infection results in invasive pneumonia at significantly lower inoculum size than in hosts not infected with influenza. Furthermore, we find that antiviral treatment administered later than 4 days after influenza infection was not able to prevent invasive pneumococcal disease. This work provides a quantitative framework to study interactions between influenza and pneumococci and has the potential to accurately quantify the interactions. Such quantitative understanding can form a basis for effective clinical care, public health policies and pandemic preparedness. PMID:23825111

Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques

PubMed Central

Hwang, Minki; Garbey, Marc; Berceli, Scott A.; Tran-Son-Tay, Roger

2011-01-01

Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented. PMID:21369345

Modeling and simulating networks of interdependent protein interactions.

PubMed

Stöcker, Bianca K; Köster, Johannes; Zamir, Eli; Rahmann, Sven

2018-05-21

Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of these systems emerge not only from the protein interactions themselves but also from the dependencies between these interactions, as generated by allosteric effects or mutual exclusion due to steric hindrance. Therefore, formal models for integrating and utilizing information about interaction dependencies are of high interest. Here, we describe an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining constrained protein interaction networks ("constrained networks"). The construction of these networks is based on public interaction databases as well as text-mined information about interaction dependencies. We present an efficient data structure and algorithm to simulate protein complex formation in constrained networks. The efficiency of the model allows fast simulation and facilitates the analysis of many proteins in large networks. In addition, this approach enables the simulation of perturbation effects, such as knockout of single or multiple proteins and changes of protein concentrations. We illustrate how our model can be used to analyze a constrained human adhesome protein network, which is responsible for the formation of diverse and dynamic cell-matrix adhesion sites. By comparing protein complex formation under known interaction dependencies versus without dependencies, we investigate how these dependencies shape the resulting repertoire of protein complexes. Furthermore, our model enables investigating how the interplay of network topology with interaction dependencies influences the propagation of perturbation effects across a large biochemical system. Our simulation software CPINSim (for Constrained Protein Interaction Network Simulator) is available under the MIT license at http://github.com/BiancaStoecker/cpinsim and as a Bioconda package (https://bioconda.github.io).

Charge-dependent many-body exchange and dispersion interactions in combined QM/MM simulations

NASA Astrophysics Data System (ADS)

Kuechler, Erich R.; Giese, Timothy J.; York, Darrin M.

2015-12-01

Accurate modeling of the molecular environment is critical in condensed phase simulations of chemical reactions. Conventional quantum mechanical/molecular mechanical (QM/MM) simulations traditionally model non-electrostatic non-bonded interactions through an empirical Lennard-Jones (LJ) potential which, in violation of intuitive chemical principles, is bereft of any explicit coupling to an atom's local electronic structure. This oversight results in a model whereby short-ranged exchange-repulsion and long-ranged dispersion interactions are invariant to changes in the local atomic charge, leading to accuracy limitations for chemical reactions where significant atomic charge transfer can occur along the reaction coordinate. The present work presents a variational, charge-dependent exchange-repulsion and dispersion model, referred to as the charge-dependent exchange and dispersion (QXD) model, for hybrid QM/MM simulations. Analytic expressions for the energy and gradients are provided, as well as a description of the integration of the model into existing QM/MM frameworks, allowing QXD to replace traditional LJ interactions in simulations of reactive condensed phase systems. After initial validation against QM data, the method is demonstrated by capturing the solvation free energies of a series of small, chlorine-containing compounds that have varying charge on the chlorine atom. The model is further tested on the SN2 attack of a chloride anion on methylchloride. Results suggest that the QXD model, unlike the traditional LJ model, is able to simultaneously obtain accurate solvation free energies for a range of compounds while at the same time closely reproducing the experimental reaction free energy barrier. The QXD interaction model allows explicit coupling of atomic charge with many-body exchange and dispersion interactions that are related to atomic size and provides a more accurate and robust representation of non-electrostatic non-bonded QM/MM interactions.

In vitro cell and tissue models for studying host-microbe interactions: a review.

PubMed

Bermudez-Brito, Miriam; Plaza-Díaz, Julio; Fontana, Luis; Muñoz-Quezada, Sergio; Gil, Angel

2013-01-01

Ideally, cell models should resemble the in vivo conditions; however, in most in vitro experimental models, epithelial cells are cultivated as monolayers, in which the establishment of functional epithelial features is not achieved. To overcome this problem, co-culture experiments with probiotics, dendritic cells and intestinal epithelial cells and three-dimensional models attempt to reconcile the complex and dynamic interactions that exist in vivo between the intestinal epithelium and bacteria on the luminal side and between the epithelium and the underlying immune system on the basolateral side. Additional models include tissue explants, bioreactors and organoids. The present review details the in vitro models used to study host-microbe interactions and explores the new tools that may help in understanding the molecular mechanisms of these interactions.

Development of Coarse Grained Models for Long Chain Alkanes

NASA Astrophysics Data System (ADS)

Gyawali, Gaurav; Sternfield, Samuel; Hwang, In Chul; Rick, Steven; Kumar, Revati; Rick Group Team; Kumar Group Team

Modeling aggregation in aqueous solution is a challenge for molecular simulations as it involves long time scales, a range of length scales, and the correct balance of hydrophobic and hydrophilic interactions. We have developed a coarse-grained model fast enough for the rapid testing of molecular structures for their aggregation properties. This model, using the Stillinger-Weber potential, achieves efficiency through a reduction in the number of interaction sites and the use of short-ranged interactions. The model can be two to three orders of magnitude more efficient than conventional all atom simulations, yet through a careful parameterization process and the use of many-body interactions can be remarkably accurate. We have developed models for long chain alkanes in water that reproduce the thermodynamics and structure of water-alkane and liquid alkane systems.

Information of Complex Systems and Applications in Agent Based Modeling.

PubMed

Bao, Lei; Fritchman, Joseph C

2018-04-18

Information about a system's internal interactions is important to modeling the system's dynamics. This study examines the finer categories of the information definition and explores the features of a type of local information that describes the internal interactions of a system. Based on the results, a dual-space agent and information modeling framework (AIM) is developed by explicitly distinguishing an information space from the material space. The two spaces can evolve both independently and interactively. The dual-space framework can provide new analytic methods for agent based models (ABMs). Three examples are presented including money distribution, individual's economic evolution, and artificial stock market. The results are analyzed in the dual-space, which more clearly shows the interactions and evolutions within and between the information and material spaces. The outcomes demonstrate the wide-ranging applicability of using the dual-space AIMs to model and analyze a broad range of interactive and intelligent systems.

Quantum-memory-assisted entropic uncertainty in spin models with Dzyaloshinskii-Moriya interaction

NASA Astrophysics Data System (ADS)

Huang, Zhiming

2018-02-01

In this article, we investigate the dynamics and correlations of quantum-memory-assisted entropic uncertainty, the tightness of the uncertainty, entanglement, quantum correlation and mixedness for various spin chain models with Dzyaloshinskii-Moriya (DM) interaction, including the XXZ model with DM interaction, the XY model with DM interaction and the Ising model with DM interaction. We find that the uncertainty grows to a stable value with growing temperature but reduces as the coupling coefficient, anisotropy parameter and DM values increase. It is found that the entropic uncertainty is closely correlated with the mixedness of the system. The increasing quantum correlation can result in a decrease in the uncertainty, and the robustness of quantum correlation is better than entanglement since entanglement means sudden birth and death. The tightness of the uncertainty drops to zero, apart from slight volatility as various parameters increase. Furthermore, we propose an effective approach to steering the uncertainty by weak measurement reversal.

Testing the Two-Layer Model for Correcting Clear Sky Reflectance near Clouds

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Evans, Frank; Varnai, Tamas; Levy, Rob

2015-01-01

A two-layer model (2LM) was developed in our earlier studies to estimate the clear sky reflectance enhancement due to cloud-molecular radiative interaction at MODIS at 0.47 micrometers. Recently, we extended the model to include cloud-surface and cloud-aerosol radiative interactions. We use the LES/SHDOM simulated 3D true radiation fields to test the 2LM for reflectance enhancement at 0.47 micrometers. We find: The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; the cloud-molecular interaction alone accounts for 70 percent of the enhancement; the cloud-surface interaction accounts for 16 percent of the enhancement; the cloud-aerosol interaction accounts for an additional 13 percent of the enhancement. We conclude that the 2LM is simple to apply and unbiased.

Topological phases in the Haldane model with spin–spin on-site interactions

NASA Astrophysics Data System (ADS)

Rubio-García, A.; García-Ripoll, J. J.

2018-04-01

Ultracold atom experiments allow the study of topological insulators, such as the non-interacting Haldane model. In this work we study a generalization of the Haldane model with spin–spin on-site interactions that can be implemented on such experiments. We focus on measuring the winding number, a topological invariant, of the ground state, which we compute using a mean-field calculation that effectively captures long-range correlations and a matrix product state computation in a lattice with 64 sites. Our main result is that we show how the topological phases present in the non-interacting model survive until the interactions are comparable to the kinetic energy. We also demonstrate the accuracy of our mean-field approach in efficiently capturing long-range correlations. Based on state-of-the-art ultracold atom experiments, we propose an implementation of our model that can give information about the topological phases.

Agent-based modeling: a new approach for theory building in social psychology.

PubMed

Smith, Eliot R; Conrey, Frederica R

2007-02-01

Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach.

Formulation of human-structure interaction system models for vertical vibration

NASA Astrophysics Data System (ADS)

Caprani, Colin C.; Ahmadi, Ehsan

2016-09-01

In this paper, human-structure interaction system models for vibration in the vertical direction are considered. This work assembles various moving load models from the literature and proposes extension of the single pedestrian to a crowd of pedestrians for the FE formulation for crowd-structure interaction systems. The walking pedestrian vertical force is represented as a general time-dependent force, and the pedestrian is in turn modelled as moving force, moving mass, and moving spring-mass-damper. The arbitrary beam structure is modelled using either a formulation in modal coordinates or finite elements. In each case, the human-structure interaction (HSI) system is first formulated for a single walking pedestrian and then extended to consider a crowd of pedestrians. Finally, example applications for single pedestrian and crowd loading scenarios are examined. It is shown how the models can be used to quantify the interaction between the crowd and bridge structure. This work should find use for the evaluation of existing and new footbridges.

A unifying framework for quantifying the nature of animal interactions.

PubMed

Potts, Jonathan R; Mokross, Karl; Lewis, Mark A

2014-07-06

Collective phenomena, whereby agent-agent interactions determine spatial patterns, are ubiquitous in the animal kingdom. On the other hand, movement and space use are also greatly influenced by the interactions between animals and their environment. Despite both types of interaction fundamentally influencing animal behaviour, there has hitherto been no unifying framework for the models proposed in both areas. Here, we construct a general method for inferring population-level spatial patterns from underlying individual movement and interaction processes, a key ingredient in building a statistical mechanics for ecological systems. We show that resource selection functions, as well as several examples of collective motion models, arise as special cases of our framework, thus bringing together resource selection analysis and collective animal behaviour into a single theory. In particular, we focus on combining the various mechanistic models of territorial interactions in the literature with step selection functions, by incorporating interactions into the step selection framework and demonstrating how to derive territorial patterns from the resulting models. We demonstrate the efficacy of our model by application to a population of insectivore birds in the Amazon rainforest. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Inhibitory control in mind and brain 2.0: Blocked-input models of saccadic countermanding

PubMed Central

Logan, Gordon D.; Yamaguchi, Motonori; Schall, Jeffrey D.; Palmeri, Thomas J.

2015-01-01

The interactive race model of saccadic countermanding assumes that response inhibition results from an interaction between a go unit, identified with gaze-shifting neurons, and a stop unit, identified with gaze-holding neurons, in which activation of the stop unit inhibits the growth of activation in the go unit to prevent it from reaching threshold. The interactive race model accounts for behavioral data and predicts physiological data in monkeys performing the stop-signal task. We propose an alternative model that assumes that response inhibition results from blocking the input to the go unit. We show that the blocked-input model accounts for behavioral data as accurately as the original interactive race model and predicts aspects of the physiological data more accurately. We extend the models to address the steady-state fixation period before the go stimulus is presented and find that the blocked-input model fits better than the interactive race model. We consider a model in which fixation activity is boosted when a stop signal occurs and find that it fits as well as the blocked input model but predicts very high steady-state fixation activity after the response is inhibited. We discuss the alternative linking propositions that connect computational models to neural mechanisms, the lessons to be learned from model mimicry, and generalization from countermanding saccades to countermanding other kinds of responses. PMID:25706403

Effects of Ignoring Item Interaction on Item Parameter Estimation and Detection of Interacting Items

ERIC Educational Resources Information Center

Chen, Cheng-Te; Wang, Wen-Chung

2007-01-01

This study explores the effects of ignoring item interaction on item parameter estimation and the efficiency of using the local dependence index Q[subscript 3] and the SAS NLMIXED procedure to detect item interaction under the three-parameter logistic model and the generalized partial credit model. Through simulations, it was found that ignoring…

A Model for Enhancing Social Communication and Interaction in Everyday Activities for Primary School Children with ASD

ERIC Educational Resources Information Center

Peters, Brenda

2016-01-01

Children with a diagnosis of Autism Spectrum Disorder may find the social aspects of learning particularly challenging because of the traits of diffculty with social communication and interaction. This paper evaluates the impact of an interactive model designed to support social communication and interaction for twelve students with ASD, who…

Simple potential model for interaction of dark particles with massive bodies

NASA Astrophysics Data System (ADS)

Takibayev, Nurgali

2018-01-01

A simple model for interaction of dark particles with matter based on resonance behavior in a three-body system is proposed. The model describes resonant amplification of effective interaction between two massive bodies at large distances between them. The phenomenon is explained by catalytic action of dark particles rescattering at a system of two heavy bodies which are understood here as the big stellar objects. Resonant amplification of the effective interaction between the two heavy bodies imitates the increase in their mass while their true gravitational mass remains unchanged. Such increased interaction leads to more pronounced gravitational lensing of bypassing light. It is shown that effective interaction between the heavy bodies is changed at larger distances and can transform into repulsive action.

First-order metal-insulator transitions in the extended Hubbard model due to self-consistent screening of the effective interaction

NASA Astrophysics Data System (ADS)

Schüler, M.; van Loon, E. G. C. P.; Katsnelson, M. I.; Wehling, T. O.

2018-04-01

While the Hubbard model is the standard model to study Mott metal-insulator transitions, it is still unclear to what extent it can describe metal-insulator transitions in real solids, where nonlocal Coulomb interactions are always present. By using a variational principle, we clarify this issue for short- and long-range nonlocal Coulomb interactions for half-filled systems on bipartite lattices. We find that repulsive nonlocal interactions generally stabilize the Fermi-liquid regime. The metal-insulator phase boundary is shifted to larger interaction strengths to leading order linearly with nonlocal interactions. Importantly, nonlocal interactions can raise the order of the metal-insulator transition. We present a detailed analysis of how the dimension and geometry of the lattice as well as the temperature determine the critical nonlocal interaction leading to a first-order transition: for systems in more than two dimensions with nonzero density of states at the Fermi energy the critical nonlocal interaction is arbitrarily small; otherwise, it is finite.

Polaron mobility obtained by a variational approach for lattice Fröhlich models

NASA Astrophysics Data System (ADS)

Kornjača, Milan; Vukmirović, Nenad

2018-04-01

Charge carrier mobility for a class of lattice models with long-range electron-phonon interaction was investigated. The approach for mobility calculation is based on a suitably chosen unitary transformation of the model Hamiltonian which transforms it into the form where the remaining interaction part can be treated as a perturbation. Relevant spectral functions were then obtained using Matsubara Green's functions technique and charge carrier mobility was evaluated using Kubo's linear response formula. Numerical results were presented for a wide range of electron-phonon interaction strengths and temperatures in the case of one-dimensional version of the model. The results indicate that the mobility decreases with increasing temperature for all electron-phonon interaction strengths in the investigated range, while longer interaction range leads to more mobile carriers.

Interaction of methotrexate with trypsin analyzed by spectroscopic and molecular modeling methods

NASA Astrophysics Data System (ADS)

Wang, Yanqing; Zhang, Hongmei; Cao, Jian; Zhou, Qiuhua

2013-11-01

Trypsin is one of important digestive enzymes that have intimate correlation with human health and illness. In this work, the interaction of trypsin with methotrexate was investigated by spectroscopic and molecular modeling methods. The results revealed that methotrexate could interact with trypsin with about one binding site. Methotrexate molecule could enter into the primary substrate-binding pocket, resulting in inhibition of trypsin activity. Furthermore, the thermodynamic analysis implied that electrostatic force, hydrogen bonding, van der Waals and hydrophobic interactions were the main interactions for stabilizing the trypsin-methotrexate system, which agreed well with the results from the molecular modeling study.

Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models.

PubMed

Sae-Lim, Panya; Komen, Hans; Kause, Antti; Mulder, Han A

2014-02-26

Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. Day*Degree and photoperiod were identified as environmental variables responsible for the strong GxE interaction for body weight at harvest in rainbow trout across four environments. Both the reaction norm and the factor analytic models can help identify the environmental variables responsible for GxE interaction. A factor analytic model is preferred over a reaction norm model when limited information on differences in environmental variables between farms is available.

Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models

PubMed Central

2014-01-01

Background Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. Methods Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. Results The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. Conclusions Day*Degree and photoperiod were identified as environmental variables responsible for the strong GxE interaction for body weight at harvest in rainbow trout across four environments. Both the reaction norm and the factor analytic models can help identify the environmental variables responsible for GxE interaction. A factor analytic model is preferred over a reaction norm model when limited information on differences in environmental variables between farms is available. PMID:24571451

A model-based approach to monitor complex road-vehicle interactions through first principles

NASA Astrophysics Data System (ADS)

Chakravarty, T.; Srinivasarengan, K.; Roy, S.; Bilal, S.; Balamuralidhar, P.

2013-02-01

The increasing availability of portable computing devices and their interaction with physical systems ask for designing compact models and simulations to understand and characterize such interactions. For instance, monitoring a road's grade using accelerometer stationed inside a moving ground vehicle is an emerging trend in city administration. Typically the focus has largely been to develop algorithms to articulate meaning from that. But, the experimentation cannot provide with an exhaustive analysis of all scenarios and the characteristics of them. We propose an approach of modeling these interactions of physical systems with gadgets through first principles, in a compact manner to focus on limited number of interactions. We derive an approach to model the vehicle interaction with a pothole on a road, a specific case, but allowing for selectable car parameters like natural damped frequency, tire size etc, thus generalizing it. Different road profiles are also created to represent rough road with sharp irregularities. These act as excitation to the moving vehicle and the interaction is computed to determine the vertical/ lateral vibration of the system i.e vehicle with sensors using joint time-frequency signal analysis methods. The simulation is compared with experimental data for validation. We show some directions as to how simulation of such models can reveal different characteristics of the interaction through analysis of their frequency spectrum. It is envisioned that the proposed models will get enriched further as and when large data set of real life data is captured and appropriate sensitivity analysis is done.

Interactions of elevation, aspect, and slope in models of forest species composition and productivity

Treesearch

Albert R. Stage; Christian Salas

2007-01-01

We present a linear model for the interacting effects of elevation, aspect, and slope for use in predicting forest productivity or species composition. The model formulation we propose integrates interactions of these three factors in a mathematical expression representing their combined effect in terms of a cosine function of aspect with a phase shift and amplitude...

Taking Venus models to new dimensions.

NASA Astrophysics Data System (ADS)

Murawski, K.

1997-11-01

Space plasma physicists in Poland and Japan have gained new insights into the interaction between the solar wind and Venus. Computer simulations of this 3D global interaction between the solar wind and nonmagnetized bodies have enabled greater understanding of the large-scale processes involved in such phenomena. A model that offers improved understanding of the solar wind interaction with Venus (as well as other nonmagnetized bodies impacted by the solar wind) has been developed. In this model, the interaction of the solar wind with the ionosphere of Venus is studied by calculating numerical solutions of the 3D MHD equations for two-component, chemically reactive plasma. The author describes the innovative model.

Agent based models for wealth distribution with preference in interaction

NASA Astrophysics Data System (ADS)

Goswami, Sanchari; Sen, Parongama

2014-12-01

We propose a set of conservative models in which agents exchange wealth with a preference in the choice of interacting agents in different ways. The common feature in all the models is that the temporary values of financial status of agents is a deciding factor for interaction. Other factors which may play important role are past interactions and wealth possessed by individuals. Wealth distribution, network properties and activity are the main quantities which have been studied. Evidence of phase transitions and other interesting features are presented. The results show that certain observations of the real economic system can be reproduced by the models.

The Volume Field Model about Strong Interaction and Weak Interaction

NASA Astrophysics Data System (ADS)

Liu, Rongwu

2016-03-01

For a long time researchers have believed that strong interaction and weak interaction are realized by exchanging intermediate particles. This article proposes a new mechanism as follows: Volume field is a form of material existence in plane space, it takes volume-changing motion in the form of non-continuous motion, volume fields have strong interaction or weak interaction between them by overlapping their volume fields. Based on these concepts, this article further proposes a ``bag model'' of volume field for atomic nucleus, which includes three sub-models of the complex structure of fundamental body (such as quark), the atom-like structure of hadron, and the molecule-like structure of atomic nucleus. This article also proposes a plane space model and formulates a physics model of volume field in the plane space, as well as a model of space-time conversion. The model of space-time conversion suggests that: Point space-time and plane space-time convert each other by means of merging and rupture respectively, the essence of space-time conversion is the mutual transformations of matter and energy respectively; the process of collision of high energy hadrons, the formation of black hole, and the Big Bang of universe are three kinds of space-time conversions.

Influence of World and Gravity Model Selection on Surface Interacting Vehicle Simulations

NASA Technical Reports Server (NTRS)

Madden, Michael M.

2007-01-01

A vehicle simulation is surface-interacting if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations perform ascent, entry, descent, landing, surface travel, or atmospheric flight. Modeling of gravity is an influential environmental factor for surface-interacting simulations. Gravity is the free-fall acceleration observed from a world-fixed frame that rotates with the world. Thus, gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. In surface-interacting simulations, the fidelity of gravity at heights above the surface is more significant than gravity fidelity at locations in inertial space. A surface-interacting simulation cannot treat the gravity model separately from the world model, which simulates the motion and shape of the world. The world model's simulation of the world's rotation, or lack thereof, produces the centrifugal acceleration component of gravity. The world model s reproduction of the world's shape will produce different positions relative to the world center for a given height above the surface. These differences produce variations in the gravitation component of gravity. This paper examines the actual performance of world and gravity/gravitation pairs in a simulation using the Earth.

A physical-based gas-surface interaction model for rarefied gas flow simulation

NASA Astrophysics Data System (ADS)

Liang, Tengfei; Li, Qi; Ye, Wenjing

2018-01-01

Empirical gas-surface interaction models, such as the Maxwell model and the Cercignani-Lampis model, are widely used as the boundary condition in rarefied gas flow simulations. The accuracy of these models in the prediction of macroscopic behavior of rarefied gas flows is less satisfactory in some cases especially the highly non-equilibrium ones. Molecular dynamics simulation can accurately resolve the gas-surface interaction process at atomic scale, and hence can predict accurate macroscopic behavior. They are however too computationally expensive to be applied in real problems. In this work, a statistical physical-based gas-surface interaction model, which complies with the basic relations of boundary condition, is developed based on the framework of the washboard model. In virtue of its physical basis, this new model is capable of capturing some important relations/trends for which the classic empirical models fail to model correctly. As such, the new model is much more accurate than the classic models, and in the meantime is more efficient than MD simulations. Therefore, it can serve as a more accurate and efficient boundary condition for rarefied gas flow simulations.

Investigation of Fully Three-Dimensional Helical RF Field Effects on TWT Beam/Circuit Interaction

NASA Technical Reports Server (NTRS)

Kory, Carol L.

2000-01-01

A fully three-dimensional (3D), time-dependent, helical traveling wave-tube (TWT) interaction model has been developed using the electromagnetic particle-in-cell (PIC) code MAFIA. The model includes a short section of helical slow-wave circuit with excitation fed by RF input/output couplers, and electron beam contained by periodic permanent magnet (PPM) focusing. All components of the model are simulated in three dimensions allowing the effects of the fully 3D helical fields on RF circuit/beam interaction to be investigated for the first time. The development of the interaction model is presented, and predicted TWT performance using 2.5D and 3D models is compared to investigate the effect of conventional approximations used in TWT analyses.

SABRINA - an interactive geometry modeler for MCNP

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

West, J.T.; Murphy, J.

One of the most difficult tasks when analyzing a complex three-dimensional system with Monte Carlo is geometry model development. SABRINA attempts to make the modeling process more user-friendly and less of an obstacle. It accepts both combinatorial solid bodies and MCNP surfaces and produces MCNP cells. The model development process in SABRINA is highly interactive and gives the user immediate feedback on errors. Users can view their geometry from arbitrary perspectives while the model is under development and interactively find and correct modeling errors. An example of a SABRINA display is shown. It represents a complex three-dimensional shape.

Comparison of Control Approaches in Genetic Regulatory Networks by Using Stochastic Master Equation Models, Probabilistic Boolean Network Models and Differential Equation Models and Estimated Error Analyzes

NASA Astrophysics Data System (ADS)

Caglar, Mehmet Umut; Pal, Ranadip

2011-03-01

Central dogma of molecular biology states that ``information cannot be transferred back from protein to either protein or nucleic acid''. However, this assumption is not exactly correct in most of the cases. There are a lot of feedback loops and interactions between different levels of systems. These types of interactions are hard to analyze due to the lack of cell level data and probabilistic - nonlinear nature of interactions. Several models widely used to analyze and simulate these types of nonlinear interactions. Stochastic Master Equation (SME) models give probabilistic nature of the interactions in a detailed manner, with a high calculation cost. On the other hand Probabilistic Boolean Network (PBN) models give a coarse scale picture of the stochastic processes, with a less calculation cost. Differential Equation (DE) models give the time evolution of mean values of processes in a highly cost effective way. The understanding of the relations between the predictions of these models is important to understand the reliability of the simulations of genetic regulatory networks. In this work the success of the mapping between SME, PBN and DE models is analyzed and the accuracy and affectivity of the control policies generated by using PBN and DE models is compared.

SELF-BLM: Prediction of drug-target interactions via self-training SVM.

PubMed

Keum, Jongsoo; Nam, Hojung

2017-01-01

Predicting drug-target interactions is important for the development of novel drugs and the repositioning of drugs. To predict such interactions, there are a number of methods based on drug and target protein similarity. Although these methods, such as the bipartite local model (BLM), show promise, they often categorize unknown interactions as negative interaction. Therefore, these methods are not ideal for finding potential drug-target interactions that have not yet been validated as positive interactions. Thus, here we propose a method that integrates machine learning techniques, such as self-training support vector machine (SVM) and BLM, to develop a self-training bipartite local model (SELF-BLM) that facilitates the identification of potential interactions. The method first categorizes unlabeled interactions and negative interactions among unknown interactions using a clustering method. Then, using the BLM method and self-training SVM, the unlabeled interactions are self-trained and final local classification models are constructed. When applied to four classes of proteins that include enzymes, G-protein coupled receptors (GPCRs), ion channels, and nuclear receptors, SELF-BLM showed the best performance for predicting not only known interactions but also potential interactions in three protein classes compare to other related studies. The implemented software and supporting data are available at https://github.com/GIST-CSBL/SELF-BLM.

A study on the application of voice interaction in automotive human machine interface experience design

NASA Astrophysics Data System (ADS)

Huang, Zhaohui; Huang, Xiemin

2018-04-01

This paper, firstly, introduces the application trend of the integration of multi-channel interactions in automotive HMI ((Human Machine Interface) from complex information models faced by existing automotive HMI and describes various interaction modes. By comparing voice interaction and touch screen, gestures and other interaction modes, the potential and feasibility of voice interaction in automotive HMI experience design are concluded. Then, the related theories of voice interaction, identification technologies, human beings' cognitive models of voices and voice design methods are further explored. And the research priority of this paper is proposed, i.e. how to design voice interaction to create more humane task-oriented dialogue scenarios to enhance interactive experiences of automotive HMI. The specific scenarios in driving behaviors suitable for the use of voice interaction are studied and classified, and the usability principles and key elements for automotive HMI voice design are proposed according to the scenario features. Then, through the user participatory usability testing experiment, the dialogue processes of voice interaction in automotive HMI are defined. The logics and grammars in voice interaction are classified according to the experimental results, and the mental models in the interaction processes are analyzed. At last, the voice interaction design method to create the humane task-oriented dialogue scenarios in the driving environment is proposed.

van der Waals three-body force shell model (VTSM) for the lattice dynamical studies of thallous bromide

NASA Astrophysics Data System (ADS)

Tiwari, Sarvesh K.; Pandey, L. K.; Shukla, Lal Ji; Upadhyaya, K. S.

2009-12-01

The van der Waals three-body force shell model (VTSM) has been developed by modifying the three-body force shell model (TSM) for the lattice dynamics of ionic crystals with cesium chloride (CsCl) structure. This new model incorporates van der Waals interactions along with long-range Coulomb interactions, three-body interactions and short-range second neighbour interactions in the framework of a rigid shell model (RSM). In the present paper, VTSM has been used to study the lattice dynamics of thallous bromide (TlBr), from which adequacy of VTSM has been established. A comparative study of the dynamical behaviour of TlBr has also been done between the present model and TSM, the model over which modification has been made to obtain the present model VTSM. Good agreement has been observed between the theoretical and experimental results, which give confidence that it is an appropriate model for the complete description of ionic crystals with CsCl structure.

Modelling the interaction between flooding events and economic growth

NASA Astrophysics Data System (ADS)

Grames, J.; Prskawetz, A.; Grass, D.; Blöschl, G.

2015-06-01

Socio-hydrology describes the interaction between the socio-economy and water. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre et al., 2013; Viglione et al., 2014). These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. In order to build this first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events, we transform an existing descriptive stochastic model into an optimal deterministic model. The intermediate step is to formulate and simulate a descriptive deterministic model. We develop a periodic water function to approximate the former discrete stochastic time series of rainfall events. Due to the non-autonomous exogenous periodic rainfall function the long-term path of consumption and investment will be periodic.

The display of molecular models with the Ames Interactive Modeling System (AIMS)

NASA Technical Reports Server (NTRS)

Egan, J. T.; Hart, J.; Burt, S. K.; Macelroy, R. D.

1982-01-01

A visualization of molecular models can lead to a clearer understanding of the models. Sophisticated graphics devices supported by minicomputers make it possible for the chemist to interact with the display of a very large model, altering its structure. In addition to user interaction, the need arises also for other ways of displaying information. These include the production of viewgraphs, film presentation, as well as publication quality prints of various models. To satisfy these needs, the display capability of the Ames Interactive Modeling System (AIMS) has been enhanced to provide a wide range of graphics and plotting capabilities. Attention is given to an overview of the AIMS system, graphics hardware used by the AIMS display subsystem, a comparison of graphics hardware, the representation of molecular models, graphics software used by the AIMS display subsystem, the display of a model obtained from data stored in molecule data base, a graphics feature for obtaining single frame permanent copy displays, and a feature for producing multiple frame displays.

Implementation of aerosol-cloud interactions in the regional atmosphere-aerosol model COSMO-MUSCAT(5.0) and evaluation using satellite data

NASA Astrophysics Data System (ADS)

Dipu, Sudhakar; Quaas, Johannes; Wolke, Ralf; Stoll, Jens; Mühlbauer, Andreas; Sourdeval, Odran; Salzmann, Marc; Heinold, Bernd; Tegen, Ina

2017-06-01

The regional atmospheric model Consortium for Small-scale Modeling (COSMO) coupled to the Multi-Scale Chemistry Aerosol Transport model (MUSCAT) is extended in this work to represent aerosol-cloud interactions. Previously, only one-way interactions (scavenging of aerosol and in-cloud chemistry) and aerosol-radiation interactions were included in this model. The new version allows for a microphysical aerosol effect on clouds. For this, we use the optional two-moment cloud microphysical scheme in COSMO and the online-computed aerosol information for cloud condensation nuclei concentrations (Cccn), replacing the constant Cccn profile. In the radiation scheme, we have implemented a droplet-size-dependent cloud optical depth, allowing now for aerosol-cloud-radiation interactions. To evaluate the models with satellite data, the Cloud Feedback Model Intercomparison Project Observation Simulator Package (COSP) has been implemented. A case study has been carried out to understand the effects of the modifications, where the modified modeling system is applied over the European domain with a horizontal resolution of 0.25° × 0.25°. To reduce the complexity in aerosol-cloud interactions, only warm-phase clouds are considered. We found that the online-coupled aerosol introduces significant changes for some cloud microphysical properties. The cloud effective radius shows an increase of 9.5 %, and the cloud droplet number concentration is reduced by 21.5 %.

Numerical models as interactive art

NASA Astrophysics Data System (ADS)

Donchyts, G.; Baart, F.; van de Pas, B.; Joling, A.

2017-12-01

We capture our understanding of the environment in advanced computer models. We use these numerical models to simulate the growth of deltas, meandering rivers, dune erosion, river floodings, effects of interventions. If presented with care, models can help understand the complexity of our environment and show the beautiful patterns of nature. While the topics are relevant and appealing to the general public the use of numerical models has been limited to technical users. Not many people have appreciations for the pluriform of options, esoteric user interfaces, manual editing of configuration files and extensive jargon. The models are static, you can start them, but then you have to wait, usually hours or more, for the results to become available, not something that you could imagine resulting in an immersive, interactive experience for the general public. How can we go beyond just using results? How can we adapt existing numerical models so they can be used in an interactive environment? How can we touch them and feel them? Here we show how we adapted existing models (Delft3D, Lisflood, XBeach) and reused them in as the basis for interactive exhibitions in museums with an educative goal. We present our structured approach which consists of combining a story, inspiration, a canvas, colors, shapes and interactive elements. We show how the progression from simple presentation forms to interactive art installations.

FE Modelling of the Fluid-Structure-Acoustic Interaction for the Vocal Folds Self-Oscillation

NASA Astrophysics Data System (ADS)

Švancara, Pavel; Horáček, J.; Hrůza, V.

The flow induced self-oscillation of the human vocal folds in interaction with acoustic processes in the simplified vocal tract model was explored by three-dimensional (3D) finite element (FE) model. Developed FE model includes vocal folds pretension before phonation, large deformations of the vocal fold tissue, vocal folds contact, fluid-structure interaction, morphing the fluid mesh according the vocal folds motion (Arbitrary Lagrangian-Eulerian approach), unsteady viscous compressible airflow described by the Navier-Stokes equations and airflow separation during the glottis closure. Iterative partitioned approach is used for modelling the fluid-structure interaction. Computed results prove that the developed model can be used for simulation of the vocal folds self-oscillation and resulting acoustic waves. The developed model enables to numerically simulate an influence of some pathological changes in the vocal fold tissue on the voice production.

A model-based executive for commanding robot teams

NASA Technical Reports Server (NTRS)

Barrett, Anthony

2005-01-01

The paper presents a way to robustly command a system of systems as a single entity. Instead of modeling each component system in isolation and then manually crafting interaction protocols, this approach starts with a model of the collective population as a single system. By compiling the model into separate elements for each component system and utilizing a teamwork model for coordination, it circumvents the complexities of manually crafting robust interaction protocols. The resulting systems are both globally responsive by virtue of a team oriented interaction model and locally responsive by virtue of a distributed approach to model-based fault detection, isolation, and recovery.

Model-Mapped RPA for Determining the Effective Coulomb Interaction

NASA Astrophysics Data System (ADS)

Sakakibara, Hirofumi; Jang, Seung Woo; Kino, Hiori; Han, Myung Joon; Kuroki, Kazuhiko; Kotani, Takao

2017-04-01

We present a new method to obtain a model Hamiltonian from first-principles calculations. The effective interaction contained in the model is determined on the basis of random phase approximation (RPA). In contrast to previous methods such as projected RPA and constrained RPA (cRPA), the new method named "model-mapped RPA" takes into account the long-range part of the polarization effect to determine the effective interaction in the model. After discussing the problems of cRPA, we present the formulation of the model-mapped RPA, together with a numerical test for the single-band Hubbard model of HgBa2CuO4.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

PubMed

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-02-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere. © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society.

Detection of epistatic effects with logic regression and a classical linear regression model.

PubMed

Malina, Magdalena; Ickstadt, Katja; Schwender, Holger; Posch, Martin; Bogdan, Małgorzata

2014-02-01

To locate multiple interacting quantitative trait loci (QTL) influencing a trait of interest within experimental populations, usually methods as the Cockerham's model are applied. Within this framework, interactions are understood as the part of the joined effect of several genes which cannot be explained as the sum of their additive effects. However, if a change in the phenotype (as disease) is caused by Boolean combinations of genotypes of several QTLs, this Cockerham's approach is often not capable to identify them properly. To detect such interactions more efficiently, we propose a logic regression framework. Even though with the logic regression approach a larger number of models has to be considered (requiring more stringent multiple testing correction) the efficient representation of higher order logic interactions in logic regression models leads to a significant increase of power to detect such interactions as compared to a Cockerham's approach. The increase in power is demonstrated analytically for a simple two-way interaction model and illustrated in more complex settings with simulation study and real data analysis.

Estimation and Model Selection for Finite Mixtures of Latent Interaction Models

ERIC Educational Resources Information Center

Hsu, Jui-Chen

2011-01-01

Latent interaction models and mixture models have received considerable attention in social science research recently, but little is known about how to handle if unobserved population heterogeneity exists in the endogenous latent variables of the nonlinear structural equation models. The current study estimates a mixture of latent interaction…

Adaptive iterative design (AID): a novel approach for evaluating the interactive effects of multiple stressors on aquatic organisms.

PubMed

Glaholt, Stephen P; Chen, Celia Y; Demidenko, Eugene; Bugge, Deenie M; Folt, Carol L; Shaw, Joseph R

2012-08-15

The study of stressor interactions by eco-toxicologists using nonlinear response variables is limited by required amounts of a priori knowledge, complexity of experimental designs, the use of linear models, and the lack of use of optimal designs of nonlinear models to characterize complex interactions. Therefore, we developed AID, an adaptive-iterative design for eco-toxicologist to more accurately and efficiently examine complex multiple stressor interactions. AID incorporates the power of the general linear model and A-optimal criteria with an iterative process that: 1) minimizes the required amount of a priori knowledge, 2) simplifies the experimental design, and 3) quantifies both individual and interactive effects. Once a stable model is determined, the best fit model is identified and the direction and magnitude of stressors, individually and all combinations (including complex interactions) are quantified. To validate AID, we selected five commonly co-occurring components of polluted aquatic systems, three metal stressors (Cd, Zn, As) and two water chemistry parameters (pH, hardness) to be tested using standard acute toxicity tests in which Daphnia mortality is the (nonlinear) response variable. We found after the initial data input of experimental data, although literature values (e.g. EC-values) may also be used, and after only two iterations of AID, our dose response model was stable. The model ln(Cd)*ln(Zn) was determined the best predictor of Daphnia mortality response to the combined effects of Cd, Zn, As, pH, and hardness. This model was then used to accurately identify and quantify the strength of both greater- (e.g. As*Cd) and less-than additive interactions (e.g. Cd*Zn). Interestingly, our study found only binary interactions significant, not higher order interactions. We conclude that AID is more efficient and effective at assessing multiple stressor interactions than current methods. Other applications, including life-history endpoints commonly used by regulators, could benefit from AID's efficiency in assessing water quality criteria. Copyright © 2012 Elsevier B.V. All rights reserved.

Sculpting proteins interactively: continual energy minimization embedded in a graphical modeling system.

PubMed

Surles, M C; Richardson, J S; Richardson, D C; Brooks, F P

1994-02-01

We describe a new paradigm for modeling proteins in interactive computer graphics systems--continual maintenance of a physically valid representation, combined with direct user control and visualization. This is achieved by a fast algorithm for energy minimization, capable of real-time performance on all atoms of a small protein, plus graphically specified user tugs. The modeling system, called Sculpt, rigidly constrains bond lengths, bond angles, and planar groups (similar to existing interactive modeling programs), while it applies elastic restraints to minimize the potential energy due to torsions, hydrogen bonds, and van der Waals and electrostatic interactions (similar to existing batch minimization programs), and user-specified springs. The graphical interface can show bad and/or favorable contacts, and individual energy terms can be turned on or off to determine their effects and interactions. Sculpt finds a local minimum of the total energy that satisfies all the constraints using an augmented Lagrange-multiplier method; calculation time increases only linearly with the number of atoms because the matrix of constraint gradients is sparse and banded. On a 100-MHz MIPS R4000 processor (Silicon Graphics Indigo), Sculpt achieves 11 updates per second on a 20-residue fragment and 2 updates per second on an 80-residue protein, using all atoms except non-H-bonding hydrogens, and without electrostatic interactions. Applications of Sculpt are described: to reverse the direction of bundle packing in a designed 4-helix bundle protein, to fold up a 2-stranded beta-ribbon into an approximate beta-barrel, and to design the sequence and conformation of a 30-residue peptide that mimics one partner of a protein subunit interaction. Computer models that are both interactive and physically realistic (within the limitations of a given force field) have 2 significant advantages: (1) they make feasible the modeling of very large changes (such as needed for de novo design), and (2) they help the user understand how different energy terms interact to stabilize a given conformation. The Sculpt paradigm combines many of the best features of interactive graphical modeling, energy minimization, and actual physical models, and we propose it as an especially productive way to use current and future increases in computer speed.

Are Anion/π Interactions Actually a Case of Simple Charge–Dipole Interactions?†

PubMed Central

Wheeler, Steven E.; Houk, K. N.

2011-01-01

Substituent effects in Cl− ••• C6H6−nXn complexes, models for anion/π interactions, have been examined using density functional theory and robust ab initio methods paired with large basis sets. Predicted interaction energies for 83 model Cl− ••• C6H6−nXn complexes span almost 40 kcal mol−1 and show an excellent correlation (r = 0.99) with computed electrostatic potentials. In contrast to prevailing models of anion/π interactions, which rely on substituent-induced changes in the aryl π-system, it is shown that substituent effects in these systems are due mostly to direct interactions between the anion and the substituents. Specifically, interaction energies for Cl− ••• C6H6−nXn complexes are recovered using a model system in which the substituents are isolated from the aromatic ring and π-resonance effects are impossible. Additionally, accurate potential energy curves for Cl− interacting with prototypical anion-binding arenes can be qualitatively reproduced by adding a classical charge–dipole interaction to the Cl− ••• C6H6 interaction potential. In substituted benzenes, binding of anions arises primarily from interactions of the anion with the local dipoles induced by the substituents, not changes in the interaction with the aromatic ring itself. When designing anion-binding motifs, phenyl rings should be viewed as a scaffold upon which appropriate substituents can be placed, because there are no attractive interactions between anions and the aryl π-system of substituted benzenes. PMID:20433187

Family Interaction Patterns Associated with Self-Esteem in Preadolescent Girls and Boys.

ERIC Educational Resources Information Center

Loeb, Roger C.; And Others

1980-01-01

Examines four traditional explanatory models for the influence of parents on children's self-esteem. These models are directiveness, modeling, reward and punishment, and positive family interaction. (Author/DB)

MIMO model of an interacting series process for Robust MPC via System Identification.

PubMed

Wibowo, Tri Chandra S; Saad, Nordin

2010-07-01

This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

A Nonlinear Interactions Approximation Model for Large-Eddy Simulation

NASA Astrophysics Data System (ADS)

Haliloglu, Mehmet U.; Akhavan, Rayhaneh

2003-11-01

A new approach to LES modelling is proposed based on direct approximation of the nonlinear terms \\overlineu_iuj in the filtered Navier-Stokes equations, instead of the subgrid-scale stress, τ_ij. The proposed model, which we call the Nonlinear Interactions Approximation (NIA) model, uses graded filters and deconvolution to parameterize the local interactions across the LES cutoff, and a Smagorinsky eddy viscosity term to parameterize the distant interactions. A dynamic procedure is used to determine the unknown eddy viscosity coefficient, rendering the model free of adjustable parameters. The proposed NIA model has been applied to LES of turbulent channel flows at Re_τ ≈ 210 and Re_τ ≈ 570. The results show good agreement with DNS not only for the mean and resolved second-order turbulence statistics but also for the full (resolved plus subgrid) Reynolds stress and turbulence intensities.

Modeling plant interspecific interactions from experiments with perennial crop mixtures to predict optimal combinations.

PubMed

Halty, Virginia; Valdés, Matías; Tejera, Mauricio; Picasso, Valentín; Fort, Hugo

2017-12-01

The contribution of plant species richness to productivity and ecosystem functioning is a longstanding issue in ecology, with relevant implications for both conservation and agriculture. Both experiments and quantitative modeling are fundamental to the design of sustainable agroecosystems and the optimization of crop production. We modeled communities of perennial crop mixtures by using a generalized Lotka-Volterra model, i.e., a model such that the interspecific interactions are more general than purely competitive. We estimated model parameters -carrying capacities and interaction coefficients- from, respectively, the observed biomass of monocultures and bicultures measured in a large diversity experiment of seven perennial forage species in Iowa, United States. The sign and absolute value of the interaction coefficients showed that the biological interactions between species pairs included amensalism, competition, and parasitism (asymmetric positive-negative interaction), with various degrees of intensity. We tested the model fit by simulating the combinations of more than two species and comparing them with the polycultures experimental data. Overall, theoretical predictions are in good agreement with the experiments. Using this model, we also simulated species combinations that were not sown. From all possible mixtures (sown and not sown) we identified which are the most productive species combinations. Our results demonstrate that a combination of experiments and modeling can contribute to the design of sustainable agricultural systems in general and to the optimization of crop production in particular. © 2017 by the Ecological Society of America.

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

PubMed Central

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

2017-01-01

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

A Bayesian mixture model for chromatin interaction data.

PubMed

Niu, Liang; Lin, Shili

2015-02-01

Chromatin interactions mediated by a particular protein are of interest for studying gene regulation, especially the regulation of genes that are associated with, or known to be causative of, a disease. A recent molecular technique, Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET), that uses chromatin immunoprecipitation (ChIP) and high throughput paired-end sequencing, is able to detect such chromatin interactions genomewide. However, ChIA-PET may generate noise (i.e., pairings of DNA fragments by random chance) in addition to true signal (i.e., pairings of DNA fragments by interactions). In this paper, we propose MC_DIST based on a mixture modeling framework to identify true chromatin interactions from ChIA-PET count data (counts of DNA fragment pairs). The model is cast into a Bayesian framework to take into account the dependency among the data and the available information on protein binding sites and gene promoters to reduce false positives. A simulation study showed that MC_DIST outperforms the previously proposed hypergeometric model in terms of both power and type I error rate. A real data study showed that MC_DIST may identify potential chromatin interactions between protein binding sites and gene promoters that may be missed by the hypergeometric model. An R package implementing the MC_DIST model is available at http://www.stat.osu.edu/~statgen/SOFTWARE/MDM.

InterPred: A pipeline to identify and model protein-protein interactions.

PubMed

Mirabello, Claudio; Wallner, Björn

2017-06-01

Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The BioGRID interaction database: 2017 update

PubMed Central

Chatr-aryamontri, Andrew; Oughtred, Rose; Boucher, Lorrie; Rust, Jennifer; Chang, Christie; Kolas, Nadine K.; O'Donnell, Lara; Oster, Sara; Theesfeld, Chandra; Sellam, Adnane; Stark, Chris; Breitkreutz, Bobby-Joe; Dolinski, Kara; Tyers, Mike

2017-01-01

The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the annotation and archival of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2016 (build 3.4.140), the BioGRID contains 1 072 173 genetic and protein interactions, and 38 559 post-translational modifications, as manually annotated from 48 114 publications. This dataset represents interaction records for 66 model organisms and represents a 30% increase compared to the previous 2015 BioGRID update. BioGRID curates the biomedical literature for major model organism species, including humans, with a recent emphasis on central biological processes and specific human diseases. To facilitate network-based approaches to drug discovery, BioGRID now incorporates 27 501 chemical–protein interactions for human drug targets, as drawn from the DrugBank database. A new dynamic interaction network viewer allows the easy navigation and filtering of all genetic and protein interaction data, as well as for bioactive compounds and their established targets. BioGRID data are directly downloadable without restriction in a variety of standardized formats and are freely distributed through partner model organism databases and meta-databases. PMID:27980099

Short cell-penetrating peptides: a model of interactions with gene promoter sites.

PubMed

Khavinson, V Kh; Tarnovskaya, S I; Linkova, N S; Pronyaeva, V E; Shataeva, L K; Yakutseni, P P

2013-01-01

Analysis of the main parameters of molecular mechanics (number of hydrogen bonds, hydrophobic and electrostatic interactions, DNA-peptide complex minimization energy) provided the data to validate the previously proposed qualitative models of peptide-DNA interactions and to evaluate their quantitative characteristics. Based on these estimations, a three-dimensional model of Lys-Glu and Ala-Glu-Asp-Gly peptide interactions with DNA sites (GCAG and ATTTC) located in the promoter zones of genes encoding CD5, IL-2, MMP2, and Tram1 signal molecules.

MODELING THE INTERACTION OF AGROCHEMICALS WITH ENVIRONMENTAL SURFACES: PESTICIDES ON RUTILE AND ORGANO-RUTILE SURFACES

EPA Science Inventory

Non-bonded interactions between model pesticides and organo-mineral surfaces have been studied using molecular mechanical conformational calculations and molecular dynamics simulations. The minimum energy conformations and relative binding energies for the interaction of atrazine...

Course 1: Physics of Protein-DNA Interaction

NASA Astrophysics Data System (ADS)

Bruinsma, R. F.

1 Introduction 1.1 The central dogma and bacterial gene expression 1.2 Molecular structure 2 Thermodynamics and kinetics of repressor-DNA interaction 2.1 Thermodynamics and the lac repressor 2.2 Kinetics of repressor-DNA interaction 3 DNA deformability and protein-DNA interaction 3.1 Introduction 3.2 The worm-like chain 3.3 The RST model 4 Electrostatics in water and protein-DNA interaction 4.1 Macro-ions and aqueous electrostatics 4.2 The primitive model 4.3 Manning condensation 4.4 Counter-ion release and non-specific protein-DNA interaction

Emotional valence and context of social influences on drug abuse-related behavior in animal models of social stress and prosocial interaction.

PubMed

Neisewander, J L; Peartree, N A; Pentkowski, N S

2012-11-01

Social factors are important determinants of drug dependence and relapse. We reviewed pre-clinical literature examining the role of social experiences from early life through the development of drug dependence and relapse, emphasizing two aspects of these experiences: (1) whether the social interaction is appetitive or aversive and (2) whether the social interaction occurs within or outside of the drug-taking context. The models reviewed include neonatal care, isolation, social defeat, chronic subordination, and prosocial interactions. We review results from these models in regard to effects on self-administration and conditioned place preference established with alcohol, psychostimulants, and opiates. We suggest that in general, when the interactions occur outside of the drug-taking context, prosocial interactions are protective against drug abuse-related behaviors, whereas social stressors facilitate these behaviors. By contrast, positive or negative social interactions occurring within the drug-taking context may interact with other risk factors to enhance or inhibit these behaviors. Despite differences in the nature and complexity of human social behavior compared to other species, the evolving animal literature provides useful models for understanding social influences on drug abuse-related behavior that will allow for research on the behavioral and biological mechanisms involved. The models have contributed to understanding social influences on initiation and maintenance of drug use, but more research is needed to understand social influences on drug relapse.

Sensitivity Analysis to Turbulent Combustion Models for Combustor-Turbine Interactions

NASA Astrophysics Data System (ADS)

Miki, Kenji; Moder, Jeff; Liou, Meng-Sing

2017-11-01

The recently-updated Open National CombustionCode (Open NCC) equipped with alarge-eddy simulation (LES) is applied to model the flow field inside the Energy Efficient Engine (EEE) in conjunction with sensitivity analysis to turbulent combustion models. In this study, we consider three different turbulence-combustion interaction models, the Eddy-Breakup model (EBU), the Linear-Eddy Model (LEM) and the Probability Density Function (PDF)model as well as the laminar chemistry model. Acomprehensive comparison of the flow field and the flame structure will be provided. One of our main interests isto understand how a different model predicts thermal variation on the surface of the first stage vane. Considering that these models are often used in combustor/turbine communities, this study should provide some guidelines on numerical modeling of combustor-turbine interactions.

Modeling Creep-Fatigue-Environment Interactions in Steam Turbine Rotor Materials for Advanced Ultra-supercritical Coal Power Plants

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

Shen, Chen

2014-04-01

The goal of this project is to model creep-fatigue-environment interactions in steam turbine rotor materials for advanced ultra-supercritical (A-USC) coal power Alloy 282 plants, to develop and demonstrate computational algorithms for alloy property predictions, and to determine and model key mechanisms that contribute to the damages caused by creep-fatigue-environment interactions.

High Frequency Acoustic Reflection and Transmission in Ocean Sediments

DTIC Science & Technology

2006-09-30

06-1-0766 http://www.arlut.utexas.edu LONG-TERM GOALS Development of a physical model of high-frequency acoustic interaction with the...shallow water. OBJECTIVES 1) A comparative study of acoustic sediment interaction models including visco-elastic, Biot, BICSQS, and grain...experimental measurements of the bistatic return, for the purpose of defining the best physical model of high-frequency acoustic interaction with the ocean

A hybrid spectral representation of phytoplankton growth and zooplankton response: The ''control rod'' model of plankton interaction

NASA Astrophysics Data System (ADS)

Armstrong, Robert A.

2003-11-01

Phytoplankton species interact through competition for light and nutrients; they also interact through grazers they hold in common. Both interactions are expected to be size-dependent: smaller phytoplankton species will be at an advantage when nutrients are scarce due to surface/volume considerations, while species that are similar in size are more likely to be consumed by grazers held in common than are species that differ greatly in size. While phytoplankton competition for nutrients and light has been extensively characterized, size-based interaction through shared grazers has not been represented systematically. The latter situation is particularly unfortunate because small changes in community structure can give rise to large changes in ecosystem dynamics and, in inverse modeling, to large changes in estimated parameter values. A simple, systematic way to represent phytoplankton interaction through shared grazers, one resistant to unintended idiosyncrasy of model construction yet capable of representing scientifically justifiable idiosyncrasy, would aid greatly in the modeling process. Here I develop a model structure that allows systematic representation of plankton interaction. In this model, the zooplankton community is represented as a continuous size spectrum, while phytoplankton species can be represented individually. The mechanistic basis of the model is a shift in the zooplankton community from carnivory to omnivory to herbivory as phytoplankton density increases. I discuss two limiting approximations in some detail, and fit both to data from the IronEx II experiment. The first limiting case represents a community with no grazer-based interaction among phytoplankton species; this approximation illuminates the general structure of the model. In particular, the zooplankton spectrum can be viewed as the analog of a control rod in a nuclear reactor, which prevents (or fails to prevent) an exponential bloom of phytoplankton. A second, more complex limiting case allows more general interaction of phytoplankton species along a size axis. This latter case would be suitable for describing competition among species with distinct biogeochemical roles, or between species that cause harmful algal blooms and those that do not. The model structure as a whole is therefore simple enough to guide thinking, yet detailed enough to allow quantitative prediction.

Localization in a random XY model with long-range interactions: Intermediate case between single-particle and many-body problems

NASA Astrophysics Data System (ADS)

Burin, Alexander L.

2015-09-01

Many-body localization in an XY model with a long-range interaction is investigated. We show that in the regime of a high strength of disordering compared to the interaction an off-resonant flip-flop spin-spin interaction (hopping) generates the effective Ising interactions of spins in the third order of perturbation theory in a hopping. The combination of hopping and induced Ising interactions for the power-law distance dependent hopping V (R ) ∝R-α always leads to the localization breakdown in a thermodynamic limit of an infinite system at α <3 d /2 where d is a system dimension. The delocalization takes place due to the induced Ising interactions U (R ) ∝R-2 α of "extended" resonant pairs. This prediction is consistent with the numerical finite size scaling in one-dimensional systems. Many-body localization in an XY model is more stable with respect to the long-range interaction compared to a many-body problem with similar Ising and Heisenberg interactions requiring α ≥2 d which makes the practical implementations of this model more attractive for quantum information applications. The full summary of dimension constraints and localization threshold size dependencies for many-body localization in the case of combined Ising and hopping interactions is obtained using this and previous work and it is the subject for the future experimental verification using cold atomic systems.

AA9int: SNP Interaction Pattern Search Using Non-Hierarchical Additive Model Set.

PubMed

Lin, Hui-Yi; Huang, Po-Yu; Chen, Dung-Tsa; Tung, Heng-Yuan; Sellers, Thomas A; Pow-Sang, Julio; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Hamdy, Freddie; Neal, David E; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen N; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lu, Yong-Jie; Park, Jong Y

2018-06-07

The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. hlin1@lsuhsc.edu. Supplementary data are available at Bioinformatics online.

Three-body interactions in sociophysics and their role in coalition forming

NASA Astrophysics Data System (ADS)

Naumis, Gerardo G.; Samaniego-Steta, F.; del Castillo-Mussot, M.; Vázquez, G. J.

2007-06-01

An study of the effects of three-body interactions in the process of coalition formation is presented. In particular, we modify a spin glass model of bimodal propensities and also a Potts model in order to include a particular three-body Hamiltonian that reproduces the main features of the required interactions. The model can be used to study conflicts, political struggles, political parties, social networks, wars and organizational structures. As an application, we analyze a simplified model of the Iraq war.

Measuring directional urban spatial interaction in China: A migration perspective

PubMed Central

Li, Fangzhou; Feng, Zhiming; Li, Peng; You, Zhen

2017-01-01

The study of urban spatial interaction is closely linked to that of economic geography, urban planning, regional development, and so on. Currently, this topic is generating a great deal of interest among researchers who are striving to find accurate ways to measure urban spatial interaction. Classical spatial interaction models lack theoretical guidance and require complicated parameter-adjusting processes. The radiation model, however, as proposed by Simini et al. with rigorous formula derivation, can simulate directional urban spatial interaction. We applied the radiation model in China to simulate the directional migration number among 337 nationwide research units, comprising 4 municipalities and 333 prefecture-level cities. We then analyzed the overall situation in Chinese cities, the interaction intensity hierarchy, and the prime urban agglomerations from the perspective of migration. This was done to ascertain China’s urban spatial interaction and regional development from 2000 to 2010 to reveal ground realities. PMID:28141853

Measuring directional urban spatial interaction in China: A migration perspective.

PubMed

Li, Fangzhou; Feng, Zhiming; Li, Peng; You, Zhen

2017-01-01

The study of urban spatial interaction is closely linked to that of economic geography, urban planning, regional development, and so on. Currently, this topic is generating a great deal of interest among researchers who are striving to find accurate ways to measure urban spatial interaction. Classical spatial interaction models lack theoretical guidance and require complicated parameter-adjusting processes. The radiation model, however, as proposed by Simini et al. with rigorous formula derivation, can simulate directional urban spatial interaction. We applied the radiation model in China to simulate the directional migration number among 337 nationwide research units, comprising 4 municipalities and 333 prefecture-level cities. We then analyzed the overall situation in Chinese cities, the interaction intensity hierarchy, and the prime urban agglomerations from the perspective of migration. This was done to ascertain China's urban spatial interaction and regional development from 2000 to 2010 to reveal ground realities.

An integrated approach to characterize genetic interaction networks in yeast metabolism

PubMed Central

Szappanos, Balázs; Kovács, Károly; Szamecz, Béla; Honti, Frantisek; Costanzo, Michael; Baryshnikova, Anastasia; Gelius-Dietrich, Gabriel; Lercher, Martin J.; Jelasity, Márk; Myers, Chad L.; Andrews, Brenda J.; Boone, Charles; Oliver, Stephen G.; Pál, Csaba; Papp, Balázs

2011-01-01

Intense experimental and theoretical efforts have been made to globally map genetic interactions, yet we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we: i) quantitatively measure genetic interactions between ~185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii) superpose the data on a detailed systems biology model of metabolism, and iii) introduce a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigate the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy, and gene dispensability. Last, we demonstrate the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments. PMID:21623372

Topological Sachdev-Ye-Kitaev model

NASA Astrophysics Data System (ADS)

Zhang, Pengfei; Zhai, Hui

2018-05-01

In this Rapid Communication, we construct a large-N exactly solvable model to study the interplay between interaction and topology, by connecting the Sachdev-Ye-Kitaev (SYK) model with constant hopping. The hopping forms a band structure that can exhibit both topologically trivial and nontrivial phases. Starting from a topologically trivial insulator with zero Hall conductance, we show that the interaction can drive a phase transition to a topologically nontrivial insulator with quantized nonzero Hall conductance, and a single gapless Dirac fermion emerges when the interaction is fine tuned to the critical point. The finite temperature effect is also considered, and we show that the topological phase with a stronger interaction is less stable against temperature. Our model provides a concrete example to illustrate the interacting topological phases and phase transitions, and can shed light on similar problems in physical systems.

Weighting of topologically different interactions in a model of two-dimensional polymer collapse.

PubMed

Bedini, Andrea; Owczarek, Aleksander L; Prellberg, Thomas

2013-01-01

We study by computer simulation a recently introduced generalized model of self-interacting self-avoiding trails on the square lattice that distinguishes two topologically different types of self-interaction: namely, crossings where the trail passes across itself and collisions where the lattice path visits the same site without crossing. This model generalizes the canonical interacting self-avoiding trail model of polymer collapse, which has a strongly divergent specific heat at its transition point. We confirm the recent prediction that the asymmetry does not affect the universality class for a range of asymmetry. Certainly, where the weighting of collisions outweighs that of crossings this is well supported numerically. When crossings are weighted heavily relative to collisions, the collapse transition reverts to the canonical θ-point-like behavior found in interacting self-avoiding walks.

Threshold models for genome-enabled prediction of ordinal categorical traits in plant breeding.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo; Eskridge, Kent; Crossa, José

2014-12-23

Categorical scores for disease susceptibility or resistance often are recorded in plant breeding. The aim of this study was to introduce genomic models for analyzing ordinal characters and to assess the predictive ability of genomic predictions for ordered categorical phenotypes using a threshold model counterpart of the Genomic Best Linear Unbiased Predictor (i.e., TGBLUP). The threshold model was used to relate a hypothetical underlying scale to the outward categorical response. We present an empirical application where a total of nine models, five without interaction and four with genomic × environment interaction (G×E) and genomic additive × additive × environment interaction (G×G×E), were used. We assessed the proposed models using data consisting of 278 maize lines genotyped with 46,347 single-nucleotide polymorphisms and evaluated for disease resistance [with ordinal scores from 1 (no disease) to 5 (complete infection)] in three environments (Colombia, Zimbabwe, and Mexico). Models with G×E captured a sizeable proportion of the total variability, which indicates the importance of introducing interaction to improve prediction accuracy. Relative to models based on main effects only, the models that included G×E achieved 9-14% gains in prediction accuracy; adding additive × additive interactions did not increase prediction accuracy consistently across locations. Copyright © 2015 Montesinos-López et al.

Control of Stochastic Master Equation Models of Genetic Regulatory Networks by Approximating Their Average Behavior

NASA Astrophysics Data System (ADS)

Umut Caglar, Mehmet; Pal, Ranadip

2010-10-01

The central dogma of molecular biology states that ``information cannot be transferred back from protein to either protein or nucleic acid.'' However, this assumption is not exactly correct in most of the cases. There are a lot of feedback loops and interactions between different levels of systems. These types of interactions are hard to analyze due to the lack of data in the cellular level and probabilistic nature of interactions. Probabilistic models like Stochastic Master Equation (SME) or deterministic models like differential equations (DE) can be used to analyze these types of interactions. SME models based on chemical master equation (CME) can provide detailed representation of genetic regulatory system, but their use is restricted by the large data requirements and computational costs of calculations. The differential equations models on the other hand, have low calculation costs and much more adequate to generate control procedures on the system; but they are not adequate to investigate the probabilistic nature of interactions. In this work the success of the mapping between SME and DE is analyzed, and the success of a control policy generated by DE model with respect to SME model is examined. Index Terms--- Stochastic Master Equation models, Differential Equation Models, Control Policy Design, Systems biology

Incorporating time-delays in S-System model for reverse engineering genetic networks.

PubMed

Chowdhury, Ahsan Raja; Chetty, Madhu; Vinh, Nguyen Xuan

2013-06-18

In any gene regulatory network (GRN), the complex interactions occurring amongst transcription factors and target genes can be either instantaneous or time-delayed. However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. As a result, all these approaches cannot detect important interactions of the other type. S-System model, a differential equation based approach which has been increasingly applied for modeling GRNs, also suffers from this limitation. In fact, all S-System based existing modeling approaches have been designed to capture only instantaneous interactions, and are unable to infer time-delayed interactions. In this paper, we propose a novel Time-Delayed S-System (TDSS) model which uses a set of delay differential equations to represent the system dynamics. The ability to incorporate time-delay parameters in the proposed S-System model enables simultaneous modeling of both instantaneous and time-delayed interactions. Furthermore, the delay parameters are not limited to just positive integer values (corresponding to time stamps in the data), but can also take fractional values. Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time significantly but also improves model accuracy. The evaluation criterion systematically adapts the max-min in-degrees and also systematically balances the effect of network accuracy and complexity during optimization. The four well-known performance measures applied to the experimental studies on synthetic networks with various time-delayed regulations clearly demonstrate that the proposed method can capture both instantaneous and delayed interactions correctly with high precision. The experiments carried out on two well-known real-life networks, namely IRMA and SOS DNA repair network in Escherichia coli show a significant improvement compared with other state-of-the-art approaches for GRN modeling.

Interaction model between capsule robot and intestine based on nonlinear viscoelasticity.

PubMed

Zhang, Cheng; Liu, Hao; Tan, Renjia; Li, Hongyi

2014-03-01

Active capsule endoscope could also be called capsule robot, has been developed from laboratory research to clinical application. However, the system still has defects, such as poor controllability and failing to realize automatic checks. The imperfection of the interaction model between capsule robot and intestine is one of the dominating reasons causing the above problems. A model is hoped to be established for the control method of the capsule robot in this article. It is established based on nonlinear viscoelasticity. The interaction force of the model consists of environmental resistance, viscous resistance and Coulomb friction. The parameters of the model are identified by experimental investigation. Different methods are used in the experiment to obtain different values of the same parameter at different velocities. The model is proved to be valid by experimental verification. The achievement in this article is the attempted perfection of an interaction model. It is hoped that the model can optimize the control method of the capsule robot in the future.

Analytical solutions of hypersonic type IV shock - shock interactions

NASA Astrophysics Data System (ADS)

Frame, Michael John

An analytical model has been developed to predict the effects of a type IV shock interaction at high Mach numbers. This interaction occurs when an impinging oblique shock wave intersects the most normal portion of a detached bow shock. The flowfield which develops is complicated and contains an embedded jet of supersonic flow, which may be unsteady. The jet impinges on the blunt body surface causing very high pressure and heating loads. Understanding this type of interaction is vital to the designers of cowl lips and leading edges on air- breathing hypersonic vehicles. This analytical model represents the first known attempt at predicting the geometry of the interaction explicitly, without knowing beforehand the jet dimensions, including the length of the transmitted shock where the jet originates. The model uses a hyperbolic equation for the bow shock and by matching mass continuity, flow directions and pressure throughout the flowfield, a prediction of the interaction geometry can be derived. The model has been shown to agree well with the flowfield patterns and properties of experiments and CFD, but the prediction for where the peak pressure is located, and its value, can be significantly in error due to a lack of sophistication in the model of the jet fluid stagnation region. Therefore it is recommended that this region of the flowfield be modeled in more detail and more accurate experimental and CFD measurements be used for validation. However, the analytical model has been shown to be a fast and economic prediction tool, suitable for preliminary design, or for understanding the interactions effects, including the basic physics of the interaction, such as the jet unsteadiness. The model has been used to examine a wide parametric space of possible interactions, including different Mach number, impinging shock strength and location, and cylinder radius. It has also been used to examine the interaction on power-law shaped blunt bodies, a possible candidate for hypersonic leading edges. The formation of vortices at the termination shock of the supersonic jet has been modeled using the analytical method. The vortices lead to deflections in the jet terminating flow, and the presence of the cylinder surface seems to causes the vortices to break off the jet resulting in an oscillation in the jet flow.

Kobayashi-Kondo-Maskawa-'t Hooft interaction in pentaquarks

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

Dmitrasinovic, V.

2005-05-01

We review critically the predictions of pentaquarks in the quark model, in particular, those based on the flavor-spin-dependent (Glozman-Riska) hyperfine interaction and the color-spin (one-gluon-exchange Fermi-Breit) one. We include the antiquark interactions and find that: (1) the exotic SU(3) multiplets are not substantially affected in the flavor-spin model, whereas some of the nonexotic multiplets are; and (2) the variational upper bound on the {xi}{sup --}-{theta}{sup +} mass difference in the color-spin hyperfine interaction model is substantially reduced. This leads us to the U{sub A}(1) symmetry breaking Kobayashi-Kondo-Maskawa-'tHooft interaction. We discuss some of its phenomenological consequences for pentaquarks.

Propulsion and airframe aerodynamic interactions of supersonic V/STOL configurations, phase 1

NASA Technical Reports Server (NTRS)

Mraz, M. R.; Hiley, P. E.

1985-01-01

A wind tunnel model of a supersonic V/STOL fighter configuration has been tested to measure the aerodynamic interaction effects which can result from geometrically close-coupled propulsion system/airframe components. The approach was to configure the model to present two different test techniques. One was a coventional test technique composed of two test modes. In the Flow-Through mode, absolute configuration aerodynamics are measured, including inlet/airframe interactions. In the Jet-Effects mode, incremental nozzle/airframe interactions are measured. The other test technique is a propulsion simulator approach, where a subscale, externally powered engine is mounted in the model. This allows proper measurement of inlet/airframe and nozzle/airframe interactions simultaneously.

Modeling Negotiation by a Paticipatory Approach

NASA Astrophysics Data System (ADS)

Torii, Daisuke; Ishida, Toru; Bousquet, François

In a participatory approach by social scientists, role playing games (RPG) are effectively used to understand real thinking and behavior of stakeholders, but RPG is not sufficient to handle a dynamic process like negotiation. In this study, a participatory simulation where user-controlled avatars and autonomous agents coexist is introduced to the participatory approach for modeling negotiation. To establish a modeling methodology of negotiation, we have tackled the following two issues. First, for enabling domain experts to concentrate interaction design for participatory simulation, we have adopted the architecture in which an interaction layer controls agents and have defined three types of interaction descriptions (interaction protocol, interaction scenario and avatar control scenario) to be described. Second, for enabling domain experts and stakeholders to capitalize on participatory simulation, we have established a four-step process for acquiring negotiation model: 1) surveys and interviews to stakeholders, 2) RPG, 3) interaction design, and 4) participatory simulation. Finally, we discussed our methodology through a case study of agricultural economics in the northeast Thailand.

GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data.

PubMed

Mifsud, Borbala; Martincorena, Inigo; Darbo, Elodie; Sugar, Robert; Schoenfelder, Stefan; Fraser, Peter; Luscombe, Nicholas M

2017-01-01

Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html).

A smoothed particle hydrodynamics framework for modelling multiphase interactions at meso-scale

NASA Astrophysics Data System (ADS)

Li, Ling; Shen, Luming; Nguyen, Giang D.; El-Zein, Abbas; Maggi, Federico

2018-01-01

A smoothed particle hydrodynamics (SPH) framework is developed for modelling multiphase interactions at meso-scale, including the liquid-solid interaction induced deformation of the solid phase. With an inter-particle force formulation that mimics the inter-atomic force in molecular dynamics, the proposed framework includes the long-range attractions between particles, and more importantly, the short-range repulsive forces to avoid particle clustering and instability problems. Three-dimensional numerical studies have been conducted to demonstrate the capabilities of the proposed framework to quantitatively replicate the surface tension of water, to model the interactions between immiscible liquids and solid, and more importantly, to simultaneously model the deformation of solid and liquid induced by the multiphase interaction. By varying inter-particle potential magnitude, the proposed SPH framework has successfully simulated various wetting properties ranging from hydrophobic to hydrophilic surfaces. The simulation results demonstrate the potential of the proposed framework to genuinely study complex multiphase interactions in wet granular media.

Pathway redundancy and protein essentiality revealed in the Saccharomyces cerevisiae interaction networks

PubMed Central

Ulitsky, Igor; Shamir, Ron

2007-01-01

The biological interpretation of genetic interactions is a major challenge. Recently, Kelley and Ideker proposed a method to analyze together genetic and physical networks, which explains many of the known genetic interactions as linking different pathways in the physical network. Here, we extend this method and devise novel analytic tools for interpreting genetic interactions in a physical context. Applying these tools on a large-scale Saccharomyces cerevisiae data set, our analysis reveals 140 between-pathway models that explain 3765 genetic interactions, roughly doubling those that were previously explained. Model genes tend to have short mRNA half-lives and many phosphorylation sites, suggesting that their stringent regulation is linked to pathway redundancy. We also identify ‘pivot' proteins that have many physical interactions with both pathways in our models, and show that pivots tend to be essential and highly conserved. Our analysis of models and pivots sheds light on the organization of the cellular machinery as well as on the roles of individual proteins. PMID:17437029

Simple model for deriving sdg interacting boson model Hamiltonians: 150Nd example

NASA Astrophysics Data System (ADS)

Devi, Y. D.; Kota, V. K. B.

1993-07-01

A simple and yet useful model for deriving sdg interacting boson model (IBM) Hamiltonians is to assume that single-boson energies derive from identical particle (pp and nn) interactions and proton, neutron single-particle energies, and that the two-body matrix elements for bosons derive from pn interaction, with an IBM-2 to IBM-1 projection of the resulting p-n sdg IBM Hamiltonian. The applicability of this model in generating sdg IBM Hamiltonians is demonstrated, using a single-j-shell Otsuka-Arima-Iachello mapping of the quadrupole and hexadecupole operators in proton and neutron spaces separately and constructing a quadrupole-quadrupole plus hexadecupole-hexadecupole Hamiltonian in the analysis of the spectra, B(E2)'s, and E4 strength distribution in the example of 150Nd.

Interacting with an artificial partner: modeling the role of emotional aspects.

PubMed

Cattinelli, Isabella; Goldwurm, Massimiliano; Borghese, N Alberto

2008-12-01

In this paper we introduce a simple model based on probabilistic finite state automata to describe an emotional interaction between a robot and a human user, or between simulated agents. Based on the agent's personality, attitude, and nature, and on the emotional inputs it receives, the model will determine the next emotional state displayed by the agent itself. The probabilistic and time-varying nature of the model yields rich and dynamic interactions, and an autonomous adaptation to the interlocutor. In addition, a reinforcement learning technique is applied to have one agent drive its partner's behavior toward desired states. The model may also be used as a tool for behavior analysis, by extracting high probability patterns of interaction and by resorting to the ergodic properties of Markov chains.

Systematic Uncertainties in High-Energy Hadronic Interaction Models

NASA Astrophysics Data System (ADS)

Zha, M.; Knapp, J.; Ostapchenko, S.

2003-07-01

Hadronic interaction models for cosmic ray energies are uncertain since our knowledge of hadronic interactions is extrap olated from accelerator experiments at much lower energies. At present most high-energy models are based on Grib ov-Regge theory of multi-Pomeron exchange, which provides a theoretical framework to evaluate cross-sections and particle production. While experimental data constrain some of the model parameters, others are not well determined and are therefore a source of systematic uncertainties. In this paper we evaluate the variation of results obtained with the QGSJET model, when modifying parameters relating to three ma jor sources of uncertainty: the form of the parton structure function, the role of diffractive interactions, and the string hadronisation. Results on inelastic cross sections, on secondary particle production and on the air shower development are discussed.

Numerical implementation of a cold-ion, Boltzmann-electron model for nonplanar plasma-surface interactions

NASA Astrophysics Data System (ADS)

Holgate, J. T.; Coppins, M.

2018-04-01

Plasma-surface interactions are ubiquitous in the field of plasma science and technology. Much of the physics of these interactions can be captured with a simple model comprising a cold ion fluid and electrons which satisfy the Boltzmann relation. However, this model permits analytical solutions in a very limited number of cases. This paper presents a versatile and robust numerical implementation of the model for arbitrary surface geometries in cartesian and axisymmetric cylindrical coordinates. Specific examples of surfaces with sinusoidal corrugations, trenches, and hemi-ellipsoidal protrusions verify this numerical implementation. The application of the code to problems involving plasma-liquid interactions, plasma etching, and electron emission from the surface is discussed.

Biofilm models of polymicrobial infection.

PubMed

Gabrilska, Rebecca A; Rumbaugh, Kendra P

2015-01-01

Interactions between microbes are complex and play an important role in the pathogenesis of infections. These interactions can range from fierce competition for nutrients and niches to highly evolved cooperative mechanisms between different species that support their mutual growth. An increasing appreciation for these interactions, and desire to uncover the mechanisms that govern them, has resulted in a shift from monomicrobial to polymicrobial biofilm studies in different disease models. Here we provide an overview of biofilm models used to study select polymicrobial infections and highlight the impact that the interactions between microbes within these biofilms have on disease progression. Notable recent advances in the development of polymicrobial biofilm-associated infection models and challenges facing the study of polymicrobial biofilms are addressed.

Faraday Discussion 160 Introductory Lecture: Interpreting and Predicting Hofmeister Salt Ion and Solute Effects on Biopolymer and Model Processes Using the Solute Partitioning Model

PubMed Central

Record, M. Thomas; Guinn, Emily; Pegram, Laurel; Capp, Michael

2013-01-01

Understanding how Hofmeister salt ions and other solutes interact with proteins, nucleic acids, other biopolymers and water and thereby affect protein and nucleic acid processes as well as model processes (e.g solubility of model compounds) in aqueous solution is a longstanding goal of biophysical research. Empirical Hofmeister salt and solute “m-values” (derivatives of the observed standard free energy change for a model or biopolymer process with respect to solute or salt concentration m3) are equal to differences in chemical potential derivatives: m-value = Δ(dμ2/dm3) = Δμ23 which quantify the preferential interactions of the solute or salt with the surface of the biopolymer or model system (component 2) exposed or buried in the process. Using the SPM, we dissect μ23 values for interactions of a solute or Hofmeister salt with a set of model compounds displaying the key functional groups of biopolymers to obtain interaction potentials (called α-values) that quantify the interaction of the solute or salt per unit area of each functional group or type of surface. Interpreted using the SPM, these α-values provide quantitative information about both the hydration of functional groups and the competitive interaction of water and the solute or salt with functional groups. The analysis corroborates and quantifies previous proposals that the Hofmeister anion and cation series for biopolymer processes are determined by ion-specific, mostly unfavorable interactions with hydrocarbon surfaces; the balance between these unfavorable nonpolar interactions and often-favorable interactions of ions with polar functional groups determine the series null points. The placement of urea and glycine betaine (GB) at opposite ends of the corresponding series of nonelectrolytes results from the favorable interactions of urea, and unfavorable interactions of GB, with many (but not all) biopolymer functional groups. Interaction potentials and local-bulk partition coefficients quantifying the distribution of solutes (e.g. urea, glycine betaine) and Hofmeister salt ions in the vicinity of each functional group make good chemical sense when interpreted in terms of competitive noncovalent interactions. These interaction potentials allow solute and Hofmeister (noncoulombic) salt effects on protein and nucleic acid processes to be interpreted or predicted, and allow the use of solutes and salts as probes of interface formation and large-scale conformational changes in the steps of a biopolymer mechanism. PMID:23795491

Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees.

PubMed

Fokkema, M; Smits, N; Zeileis, A; Hothorn, T; Kelderman, H

2017-10-25

Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.

The network organization of protein interactions in the spliceosome is reproduced by the simple rules of food-web models

PubMed Central

Pires, Mathias M.; Cantor, Maurício; Guimarães, Paulo R.; de Aguiar, Marcus A. M.; dos Reis, Sérgio F.; Coltri, Patricia P.

2015-01-01

The network structure of biological systems provides information on the underlying processes shaping their organization and dynamics. Here we examined the structure of the network depicting protein interactions within the spliceosome, the macromolecular complex responsible for splicing in eukaryotic cells. We show the interactions of less connected spliceosome proteins are nested subsets of the connections of the highly connected proteins. At the same time, the network has a modular structure with groups of proteins sharing similar interaction patterns. We then investigated the role of affinity and specificity in shaping the spliceosome network by adapting a probabilistic model originally designed to reproduce food webs. This food-web model was as successful in reproducing the structure of protein interactions as it is in reproducing interactions among species. The good performance of the model suggests affinity and specificity, partially determined by protein size and the timing of association to the complex, may be determining network structure. Moreover, because network models allow building ensembles of realistic networks while encompassing uncertainty they can be useful to examine the dynamics and vulnerability of intracelullar processes. Unraveling the mechanisms organizing the spliceosome interactions is important to characterize the role of individual proteins on splicing catalysis and regulation. PMID:26443080

Contagion Shocks in One Dimension

NASA Astrophysics Data System (ADS)

Bertozzi, Andrea L.; Rosado, Jesus; Short, Martin B.; Wang, Li

2015-02-01

We consider an agent-based model of emotional contagion coupled with motion in one dimension that has recently been studied in the computer science community. The model involves movement with a speed proportional to a "fear" variable that undergoes a temporal consensus averaging based on distance to other agents. We study the effect of Riemann initial data for this problem, leading to shock dynamics that are studied both within the agent-based model as well as in a continuum limit. We examine the behavior of the model under distinguished limits as the characteristic contagion interaction distance and the interaction timescale both approach zero. The limiting behavior is related to a classical model for pressureless gas dynamics with "sticky" particles. In comparison, we observe a threshold for the interaction distance vs. interaction timescale that produce qualitatively different behavior for the system - in one case particle paths do not cross and there is a natural Eulerian limit involving nonlocal interactions and in the other case particle paths can cross and one may consider only a kinetic model in the continuum limit.

The introduction of hydrogen bond and hydrophobicity effects into the rotational isomeric states model for conformational analysis of unfolded peptides.

PubMed

Engin, Ozge; Sayar, Mehmet; Erman, Burak

2009-01-13

Relative contributions of local and non-local interactions to the unfolded conformations of peptides are examined by using the rotational isomeric states model which is a Markov model based on pairwise interactions of torsion angles. The isomeric states of a residue are well described by the Ramachandran map of backbone torsion angles. The statistical weight matrices for the states are determined by molecular dynamics simulations applied to monopeptides and dipeptides. Conformational properties of tripeptides formed from combinations of alanine, valine, tyrosine and tryptophan are investigated based on the Markov model. Comparison with molecular dynamics simulation results on these tripeptides identifies the sequence-distant long-range interactions that are missing in the Markov model. These are essentially the hydrogen bond and hydrophobic interactions that are obtained between the first and the third residue of a tripeptide. A systematic correction is proposed for incorporating these long-range interactions into the rotational isomeric states model. Preliminary results suggest that the Markov assumption can be improved significantly by renormalizing the statistical weight matrices to include the effects of the long-range correlations.

Global Quantitative Modeling of Chromatin Factor Interactions

PubMed Central

Zhou, Jian; Troyanskaya, Olga G.

2014-01-01

Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

Toddlers' imitative learning in interactive and observational contexts: the role of age and familiarity of the model.

PubMed

Shimpi, Priya M; Akhtar, Nameera; Moore, Chris

2013-10-01

Three experiments examined the effects of age and familiarity of a model on toddlers' imitative learning in observational contexts (Experiments 1, 2, and 3) and interactive contexts (Experiments 2 and 3). Experiment 1 (N=112 18-month-old toddlers) varied the age (child vs. adult) and long-term familiarity (kin vs. stranger) of the person who modeled the novel actions. Experiment 2 (N=48 18-month-olds and 48 24-month-olds) and Experiment 3 (N=48 24-month-olds) varied short-term familiarity with the model (some or none) and learning context (interactive or observational). The most striking findings were that toddlers were able to learn a new action from observing completely unfamiliar strangers who did not address them and were far less likely to imitate an unfamiliar model who directly interacted with them. These studies highlight the robustness of toddlers' observational learning and reveal limitations of learning from unfamiliar models in interactive contexts. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

The introduction of hydrogen bond and hydrophobicity effects into the rotational isomeric states model for conformational analysis of unfolded peptides

NASA Astrophysics Data System (ADS)

Engin, Ozge; Sayar, Mehmet; Erman, Burak

2009-03-01

Relative contributions of local and non-local interactions to the unfolded conformations of peptides are examined by using the rotational isomeric states model which is a Markov model based on pairwise interactions of torsion angles. The isomeric states of a residue are well described by the Ramachandran map of backbone torsion angles. The statistical weight matrices for the states are determined by molecular dynamics simulations applied to monopeptides and dipeptides. Conformational properties of tripeptides formed from combinations of alanine, valine, tyrosine and tryptophan are investigated based on the Markov model. Comparison with molecular dynamics simulation results on these tripeptides identifies the sequence-distant long-range interactions that are missing in the Markov model. These are essentially the hydrogen bond and hydrophobic interactions that are obtained between the first and the third residue of a tripeptide. A systematic correction is proposed for incorporating these long-range interactions into the rotational isomeric states model. Preliminary results suggest that the Markov assumption can be improved significantly by renormalizing the statistical weight matrices to include the effects of the long-range correlations.

Test of interaction models up to 40 PeV by studying hadronic cores of EAS

NASA Astrophysics Data System (ADS)

KASCADE Collaboration; Apel, W. D.; Badea, A. F.; Bekk, K.; Blümer, J.; Bozdog, H.; Brancus, I. M.; Daumiller, K.; Doll, P.; Engel, R.; Engler, J.; Gils, H. J.; Glasstetter, R.; Haungs, A.; Heck, D.; Hörandel, J. R.; Kampert, K.-H.; Klages, H. O.; Mathes, H. J.; Mayer, H. J.; Milke, J.; Oehlschläger, J.; Ostapchenko, S.; Petcu, M.; Pierog, T.; Rebel, H.; Risse, A.; Risse, M.; Roth, M.; Schatz, G.; Schieler, H.; Ulrich, H.; van Buren, J.; Weindl, A.; Wochele, J.; Zabierowski, J.

2007-12-01

The interpretation of extensive air shower measurements often requires a comparison with shower simulations in the atmosphere. These calculations rely on hadronic interaction models which have to extrapolate into kinematical and energy regions not explored by present-day collider experiments. The KASCADE experiment with its large hadron calorimeter and the detector array for the electromagnetic and muonic components provides experimental data to check such interaction models. For the simulations the program CORSIKA is used, which has several hadronic event generators embedded. For high-energy interactions (E_{\\rm{lab}}\\gtrsim100 \\ {\\rm{GeV}}) the models DPMJET, \\{\\sc NEX{\\sc US}} , QGSJET and SIBYLL have been used. Low-energy interactions have been treated by GHEISHA and FLUKA. Different hadronic observables are investigated as well as their correlations with the electromagnetic and muonic shower components up to primary energies of about 40 PeV. Although the predictions of the more recent models are to a large extent compatible with the measured data within the range given by proton and iron primary particles, there are still significant differences between the individual models.

Traffic Games: Modeling Freeway Traffic with Game Theory

PubMed Central

Cortés-Berrueco, Luis E.; Gershenson, Carlos; Stephens, Christopher R.

2016-01-01

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers’ interactions. PMID:27855176

Traffic Games: Modeling Freeway Traffic with Game Theory.

PubMed

Cortés-Berrueco, Luis E; Gershenson, Carlos; Stephens, Christopher R

2016-01-01

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers' interactions.

An Empirical Validation of a Dynamic Systems Model of Interaction: Do Children of Different Sociometric Statuses Differ in Their Dyadic Play?

ERIC Educational Resources Information Center

Steenbeek, Henderien; van Geert, Paul

2008-01-01

Studying short-term dynamic processes and change mechanisms in interaction yields important knowledge that contributes to understanding long-term social development of children. In order to get a grip on this short-term dynamics of interaction processes, the authors made a dynamic systems model of dyadic interaction of children during one play…

Theoretical study on the photoabsorption in the Herzberg I band system of the O 2 molecule

NASA Astrophysics Data System (ADS)

Takegami, Ryuta; Yabushita, Satoshi

2005-01-01

The Herzberg I band system of the oxygen molecule is electric-dipole forbidden and its absorption strength has been explained by intensity borrowing models which include the spin-orbit (SO) and L-uncoupling (RO) interactions as perturbations. We employed three different levels of theoretical models to evaluate these two interactions, and obtained the rotational and vibronic absorption strengths using the ab initio method. The first model calculates the transition moments induced by the SO interaction variationally with the SO configuration interaction method (SOCI), and uses the first-order perturbation theory for the RO interaction, and is called SOCI. The second is based on the first-order perturbation theory for both the SO and RO interactions, and is called Pert(Full). The last is a limited version of Pert(Full), in that the first-order perturbation wavefunction for the initial and final state is represented by only one dominant basis, namely the 1 3Π g and B3Σu- state, respectively, as originally used by England et al. [Can. J. Phys. 74 (1996) 185], and is called Pert(England). The vibronic oscillator strengths calculated by these three models were in good agreement with the experimental values. As for the integrated rotational linestrengths, the SOCI and Pert(Full) models reproduced the experimental results very well, however the Pert(England) model did not give satisfactory results. Since the Pert(England) model takes only the 1 3Π g and B3Σu- states into consideration, it cannot contain the complicated configuration interactions with highly excited states induced by the SO and RO interaction, which plays an important role for calculating the delicate integrated rotational linestrength. This result suggests that the configuration interaction with highly excited states due to some perturbations cannot be neglected in the case of very weak absorption band systems.

A conceptual network model of the air transportation system. the basic level 1 model.

DOT National Transportation Integrated Search

1971-04-01

A basic conceptual model of the entire Air Transportation System is being developed to serve as an analytical tool for studying the interactions among the system elements. The model is being designed to function in an interactive computer graphics en...

A new 3D immersed boundary method for non-Newtonian fluid-structure-interaction with application

NASA Astrophysics Data System (ADS)

Zhu, Luoding

2017-11-01

Motivated by fluid-structure-interaction (FSI) phenomena in life sciences (e.g., motions of sperm and cytoskeleton in complex fluids), we introduce a new immersed boundary method for FSI problems involving non-Newtonian fluids in three dimensions. The non-Newtonian fluids are modelled by the FENE-P model (including the Oldroyd-B model as an especial case) and numerically solved by a lattice Boltzmann scheme (the D3Q7 model). The fluid flow is modelled by the lattice Boltzmann equations and numerically solved by the D3Q19 model. The deformable structure and the fluid-structure-interaction are handled by the immersed boundary method. As an application, we study a FSI toy problem - interaction of an elastic plate (flapped at its leading edge and restricted nowhere else) with a non-Newtonian fluid in a 3D flow. Thanks to the support of NSF-DMS support under research Grant 1522554.

In silico modeling of the yeast protein and protein family interaction network

NASA Astrophysics Data System (ADS)

Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

Biochemistry students' ideas about how an enzyme interacts with a substrate.

PubMed

Linenberger, Kimberly J; Bretz, Stacey Lowery

2015-01-01

Enzyme-substrate interactions are a fundamental concept of biochemistry that is built upon throughout multiple biochemistry courses. Central to understanding enzyme-substrate interactions is specific knowledge of exactly how an enzyme and substrate interact. Within this narrower topic, students must understand the various binding sites on an enzyme and be able to reason from simplistic lock and key or induced fit models to the more complex energetics model of transition state theory. Learning to understand these many facets of enzyme-substrate interactions and reasoning from multiple models present challenges where students incorrectly make connections between concepts or make no connection at all. This study investigated biochemistry students' understanding of enzyme-substrate interactions through the use of clinical interviews and a national administration (N = 707) of the Enzyme-Substrate Interactions Concept Inventory. Findings include misconceptions regarding the nature of enzyme-substrate interactions, naïve ideas about the active site, a lack of energetically driven interactions, and an incomplete understanding of the specificity pocket. © 2015 by the International Union of Biochemistry and Molecular Biology.

Asymmetric biotic interactions and abiotic niche differences revealed by a dynamic joint species distribution model.

PubMed

Lany, Nina K; Zarnetske, Phoebe L; Schliep, Erin M; Schaeffer, Robert N; Orians, Colin M; Orwig, David A; Preisser, Evan L

2018-05-01

A species' distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co-occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species' abundance on other species in the community. Accounting for dependence among co-occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions. © 2018 by the Ecological Society of America.

Cerebral-Body Perfusion Model

DTIC Science & Technology

1990-07-01

to simulate flow and pressure interaction between the cerebral and the body systems. its objective is to study the dynamic interaction between the...single model. The objective is to enable the study of the dynamic interaction between these two systems. In this model, relevant parts of the brain and of...34blackout, can also be investigated. For example, the effect can be studied of different inhale/exhale and/or different relative positioning betwoen head-body

Interactions between human osteoblasts and prostate cancer cells in a novel 3D in vitro model

PubMed Central

Sieh, Shirly; Lubik, Amy A; Clements, Judith A; Nelson, Colleen C

2010-01-01

Cell-cell and cell-matrix interactions play a major role in tumor morphogenesis and cancer metastasis. Therefore, it is crucial to create a model with a biomimetic microenvironment that allows such interactions to fully represent the pathophysiology of a disease for an in vitro study. This is achievable by using three-dimensional (3D) models instead of conventional two-dimensional (2D) cultures with the aid of tissue engineering technology. We are now able to better address the complex intercellular interactions underlying prostate cancer (CaP) bone metastasis through such models. In this study, we assessed the interaction of CaP cells and human osteoblasts (hOBs) within a tissue engineered bone (TEB) construct. Consistent with other in vivo studies, our findings show that intercellular and CaP cell-bone matrix interactions lead to elevated levels of matrix metalloproteinases, steroidogenic enzymes and the CaP biomarker, prostate specific antigen (PSA); all associated with CaP metastasis. Hence, it highlights the physiological relevance of this model. We believe that this model will provide new insights for understanding of the previously poorly understood molecular mechanisms of bone metastasis, which will foster further translational studies, and ultimately offer a potential tool for drug screening. PMID:21197221

Plant microRNA-Target Interaction Identification Model Based on the Integration of Prediction Tools and Support Vector Machine

PubMed Central

Meng, Jun; Shi, Lin; Luan, Yushi

2014-01-01

Background Confident identification of microRNA-target interactions is significant for studying the function of microRNA (miRNA). Although some computational miRNA target prediction methods have been proposed for plants, results of various methods tend to be inconsistent and usually lead to more false positive. To address these issues, we developed an integrated model for identifying plant miRNA–target interactions. Results Three online miRNA target prediction toolkits and machine learning algorithms were integrated to identify and analyze Arabidopsis thaliana miRNA-target interactions. Principle component analysis (PCA) feature extraction and self-training technology were introduced to improve the performance. Results showed that the proposed model outperformed the previously existing methods. The results were validated by using degradome sequencing supported Arabidopsis thaliana miRNA-target interactions. The proposed model constructed on Arabidopsis thaliana was run over Oryza sativa and Vitis vinifera to demonstrate that our model is effective for other plant species. Conclusions The integrated model of online predictors and local PCA-SVM classifier gained credible and high quality miRNA-target interactions. The supervised learning algorithm of PCA-SVM classifier was employed in plant miRNA target identification for the first time. Its performance can be substantially improved if more experimentally proved training samples are provided. PMID:25051153

Mathematical models for plant-herbivore interactions

USGS Publications Warehouse

Feng, Zhilan; DeAngelis, Donald L.

2017-01-01

Mathematical Models of Plant-Herbivore Interactions addresses mathematical models in the study of practical questions in ecology, particularly factors that affect herbivory, including plant defense, herbivore natural enemies, and adaptive herbivory, as well as the effects of these on plant community dynamics. The result of extensive research on the use of mathematical modeling to investigate the effects of plant defenses on plant-herbivore dynamics, this book describes a toxin-determined functional response model (TDFRM) that helps explains field observations of these interactions. This book is intended for graduate students and researchers interested in mathematical biology and ecology.

Hole superconductivity in a generalized two-band model

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

Hong, X.Q.; Hirsch, J.E.

1992-06-01

We study superconductivity in a two-band model that generalizes the model introduced by Suhl, Matthias, and Walker: All possible interaction terms coupling both bands are included. The pairing interaction is assumed to originate in the momentum dependence of the intraband interactions that arises in the model of hole superconductivity. The model generically displays a single critical temperature and two gaps, with the larger gap associated with the band with strongest holelike character to the carriers. The dependence of the critical temperature and of the magnitudes of the gaps on the various parameters in the Hamiltonian is studied.

A System for Modelling Cell–Cell Interactions during Plant Morphogenesis

PubMed Central

Dupuy, Lionel; Mackenzie, Jonathan; Rudge, Tim; Haseloff, Jim

2008-01-01

Background and aims During the development of multicellular organisms, cells are capable of interacting with each other through a range of biological and physical mechanisms. A description of these networks of cell–cell interactions is essential for an understanding of how cellular activity is co-ordinated in regionalized functional entities such as tissues or organs. The difficulty of experimenting on living tissues has been a major limitation to describing such systems, and computer modelling appears particularly helpful to characterize the behaviour of multicellular systems. The experimental difficulties inherent to the multitude of parallel interactions that underlie cellular morphogenesis have led to the need for computer models. Methods A new generic model of plant cellular morphogenesis is described that expresses interactions amongst cellular entities explicitly: the plant is described as a multi-scale structure, and interactions between distinct entities is established through a topological neighbourhood. Tissues are represented as 2D biphasic systems where the cell wall responds to turgor pressure through a viscous yielding of the cell wall. Key Results This principle was used in the development of the CellModeller software, a generic tool dedicated to the analysis and modelling of plant morphogenesis. The system was applied to three contrasting study cases illustrating genetic, hormonal and mechanical factors involved in plant morphogenesis. Conclusions Plant morphogenesis is fundamentally a cellular process and the CellModeller software, through its underlying generic model, provides an advanced research tool to analyse coupled physical and biological morphogenetic mechanisms. PMID:17921524

Learning epistatic interactions from sequence-activity data to predict enantioselectivity

NASA Astrophysics Data System (ADS)

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K.; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from 50 {× } 5 -fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of r=0.90 and r=0.93 . As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from r=0.51 to r=0.87 respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity

NASA Astrophysics Data System (ADS)

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K.; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger ( AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients ( r) from 50 {× } 5-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of r=0.90 and r=0.93. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from r=0.51 to r=0.87 respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Multidisciplinary model-based-engineering for laser weapon systems: recent progress

NASA Astrophysics Data System (ADS)

Coy, Steve; Panthaki, Malcolm

2013-09-01

We are working to develop a comprehensive, integrated software framework and toolset to support model-based engineering (MBE) of laser weapons systems. MBE has been identified by the Office of the Director, Defense Science and Engineering as one of four potentially "game-changing" technologies that could bring about revolutionary advances across the entire DoD research and development and procurement cycle. To be effective, however, MBE requires robust underlying modeling and simulation technologies capable of modeling all the pertinent systems, subsystems, components, effects, and interactions at any level of fidelity that may be required in order to support crucial design decisions at any point in the system development lifecycle. Very often the greatest technical challenges are posed by systems involving interactions that cut across two or more distinct scientific or engineering domains; even in cases where there are excellent tools available for modeling each individual domain, generally none of these domain-specific tools can be used to model the cross-domain interactions. In the case of laser weapons systems R&D these tools need to be able to support modeling of systems involving combined interactions among structures, thermal, and optical effects, including both ray optics and wave optics, controls, atmospheric effects, target interaction, computational fluid dynamics, and spatiotemporal interactions between lasing light and the laser gain medium. To address this problem we are working to extend Comet™, to add the addition modeling and simulation capabilities required for this particular application area. In this paper we will describe our progress to date.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity.

PubMed

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from [Formula: see text]-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of [Formula: see text] and [Formula: see text]. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from [Formula: see text] to [Formula: see text] respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

The cognitive impact of interactive design features for learning complex materials in medical education.

PubMed

Song, Hyuksoon S; Pusic, Martin; Nick, Michael W; Sarpel, Umut; Plass, Jan L; Kalet, Adina L

2014-02-01

To identify the most effective way for medical students to interact with a browser-based learning module on the symptoms and neurological underpinnings of stroke syndromes, this study manipulated the way in which subjects interacted with a graphical model of the brain and examined the impact of functional changes on learning outcomes. It was hypothesized that behavioral interactions that were behaviorally more engaging and which required deeper consideration of the model would result in heightened cognitive interaction and better learning than those whose manipulation required less deliberate behavioral and cognitive processing. One hundred forty four students were randomly assigned to four conditions whose model controls incorporated features that required different levels of behavioral and cognitive interaction: Movie (low behavioral/low cognitive, n = 40), Slider (high behavioral/low cognitive, n = 36), Click (low behavioral/high cognitive, n = 30), and Drag (high behavioral/high cognitive, n = 38). Analysis of Covariates (ANCOVA) showed that students who received the treatments associated with lower cognitive interactivity (Movie and Slider) performed better on a transfer task than those receiving the module associated with high cognitive interactivity (Click and Drag, partial eta squared = .03). In addition, the students in the high cognitive interactivity conditions spent significantly more time on the stroke locator activity than other conditions (partial eta squared = .36). The results suggest that interaction with controls that were tightly coupled with the model and whose manipulation required deliberate consideration of the model's features may have overtaxed subjects' cognitive resources. Cognitive effort that facilitated manipulation of content, though directed at the model, may have resulted in extraneous cognitive load, impeding subjects in recognizing the deeper, global relationships in the materials. Instructional designers must, therefore, keep in mind that the way in which functional affordances are integrated with the content can shape both behavioral and cognitive processing, and has significant cognitive load implications.

Charge-dependent many-body exchange and dispersion interactions in combined QM/MM simulations

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

Kuechler, Erich R.; Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455-0431; Giese, Timothy J.

2015-12-21

Accurate modeling of the molecular environment is critical in condensed phase simulations of chemical reactions. Conventional quantum mechanical/molecular mechanical (QM/MM) simulations traditionally model non-electrostatic non-bonded interactions through an empirical Lennard-Jones (LJ) potential which, in violation of intuitive chemical principles, is bereft of any explicit coupling to an atom’s local electronic structure. This oversight results in a model whereby short-ranged exchange-repulsion and long-ranged dispersion interactions are invariant to changes in the local atomic charge, leading to accuracy limitations for chemical reactions where significant atomic charge transfer can occur along the reaction coordinate. The present work presents a variational, charge-dependent exchange-repulsion andmore » dispersion model, referred to as the charge-dependent exchange and dispersion (QXD) model, for hybrid QM/MM simulations. Analytic expressions for the energy and gradients are provided, as well as a description of the integration of the model into existing QM/MM frameworks, allowing QXD to replace traditional LJ interactions in simulations of reactive condensed phase systems. After initial validation against QM data, the method is demonstrated by capturing the solvation free energies of a series of small, chlorine-containing compounds that have varying charge on the chlorine atom. The model is further tested on the S{sub N}2 attack of a chloride anion on methylchloride. Results suggest that the QXD model, unlike the traditional LJ model, is able to simultaneously obtain accurate solvation free energies for a range of compounds while at the same time closely reproducing the experimental reaction free energy barrier. The QXD interaction model allows explicit coupling of atomic charge with many-body exchange and dispersion interactions that are related to atomic size and provides a more accurate and robust representation of non-electrostatic non-bonded QM/MM interactions.« less

A Generic Model of Dyadic Social Relationships

PubMed Central

Favre, Maroussia; Sornette, Didier

2015-01-01

We introduce a model of dyadic social interactions and establish its correspondence with relational models theory (RMT), a theory of human social relationships. RMT posits four elementary models of relationships governing human interactions, singly or in combination: Communal Sharing, Authority Ranking, Equality Matching, and Market Pricing. To these are added the limiting cases of asocial and null interactions, whereby people do not coordinate with reference to any shared principle. Our model is rooted in the observation that each individual in a dyadic interaction can do either the same thing as the other individual, a different thing or nothing at all. To represent these three possibilities, we consider two individuals that can each act in one out of three ways toward the other: perform a social action X or Y, or alternatively do nothing. We demonstrate that the relationships generated by this model aggregate into six exhaustive and disjoint categories. We propose that four of these categories match the four relational models, while the remaining two correspond to the asocial and null interactions defined in RMT. We generalize our results to the presence of N social actions. We infer that the four relational models form an exhaustive set of all possible dyadic relationships based on social coordination. Hence, we contribute to RMT by offering an answer to the question of why there could exist just four relational models. In addition, we discuss how to use our representation to analyze data sets of dyadic social interactions, and how social actions may be valued and matched by the agents. PMID:25826403

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

PubMed Central

Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

2013-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

Culturicon model: A new model for cultural-based emoticon

NASA Astrophysics Data System (ADS)

Zukhi, Mohd Zhafri Bin Mohd; Hussain, Azham

2017-10-01

Emoticons are popular among distributed collective interaction user in expressing their emotion, gestures and actions. Emoticons have been proved to be able to avoid misunderstanding of the message, attention saving and improved the communications among different native speakers. However, beside the benefits that emoticons can provide, the study regarding emoticons in cultural perspective is still lacking. As emoticons are crucial in global communication, culture should be one of the extensively research aspect in distributed collective interaction. Therefore, this study attempt to explore and develop model for cultural-based emoticon. Three cultural models that have been used in Human-Computer Interaction were studied which are the Hall Culture Model, Trompenaars and Hampden Culture Model and Hofstede Culture Model. The dimensions from these three models will be used in developing the proposed cultural-based emoticon model.

Increased prediction accuracy in wheat breeding trials using a marker x environment interaction genomic selection model

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates for selection. Originally these models were developed without considering genotype ' environment interaction (GE). Several authors have proposed extensions of the cannonical GS model that accomm...

Density perturbation in the models reconstructed from jerk parameter

NASA Astrophysics Data System (ADS)

Sinha, Srijita; Banerjee, Narayan

2018-06-01

The present work deals with the late time evolution of the linear density contrast in the dark energy models reconstructed from the jerk parameter. It is found that the non-interacting models are favoured compared to the models where an interaction is allowed in the dark sector.

Prediction of the structure of fuel sprays in gas turbine combustors

NASA Technical Reports Server (NTRS)

Shuen, J. S.

1985-01-01

The structure of fuel sprays in a combustion chamber is theoretically investigated using computer models of current interest. Three representative spray models are considered: (1) a locally homogeneous flow (LHF) model, which assumes infinitely fast interphase transport rates; (2) a deterministic separated flow (DSF) model, which considers finite rates of interphase transport but ignores effects of droplet/turbulence interactions; and (3) a stochastic separated flow (SSF) model, which considers droplet/turbulence interactions using random sampling for turbulence properties in conjunction with random-walk computations for droplet motion and transport. Two flow conditions are studied to investigate the influence of swirl on droplet life histories and the effects of droplet/turbulence interactions on flow properties. Comparison of computed results with the experimental data show that general features of the flow structure can be predicted with reasonable accuracy using the two separated flow models. In contrast, the LHF model overpredicts the rate of development of the flow. While the SSF model provides better agreement with measurements than the DSF model, definitive evaluation of the significance of droplet/turbulence interaction is not achieved due to uncertainties in the spray initial conditions.

Interactive, process-oriented climate modeling with CLIMLAB

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2016-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The Jupyter Notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields.

A model for adatom structures

NASA Astrophysics Data System (ADS)

Kappus, W.

1981-06-01

A model concerning adatom structures is proposed. Attractive nearest neighbour interactions, which may be of electronic nature lead to 2-dimensional condensation. Every pair bond causes and elastic dipole. The elastic dipoles interact via substrate strains with an anisotropic s -3 power law. Different types of adatoms or sites are permitted and many-body effects result, from the assumptions. Electric dipole interactions of adatoms are included for comparison. The model is applied to the W(110) surface and compared with superstructures experimentally found in the W(110)-0 system. It is found that there is still lack for an additional next-nearest neighbour interaction.

On a two-particle bound system on the half-line

NASA Astrophysics Data System (ADS)

Kerner, Joachim; Mühlenbruch, Tobias

2017-10-01

In this paper we provide an extension of the model discussed in [10] describing two singularly interacting particles on the half-line ℝ+. In this model, the particles are interacting only whenever at least one particle is situated at the origin. Stimulated by [11] we then provide a generalisation of this model in order to include additional interactions between the particles leading to a molecular-like state. We give a precise mathematical formulation of the Hamiltonian of the system and perform spectral analysis. In particular, we are interested in the effect of the singular two-particle interactions onto the molecule.

Single pion production in neutrino-nucleon interactions

NASA Astrophysics Data System (ADS)

Kabirnezhad, M.

2018-01-01

This work represents an extension of the single pion production model proposed by Rein [Z. Phys. C 35, 43 (1987)., 10.1007/BF01561054]. The model consists of resonant pion production and nonresonant background contributions coming from three Born diagrams in the helicity basis. The new work includes lepton mass effects, and nonresonance interaction is described by five diagrams based on a nonlinear σ model. This work provides a full kinematic description of single pion production in the neutrino-nucleon interactions, including resonant and nonresonant interactions in the helicity basis, in order to study the interference effect.

Phase transitions in the antiferromagnetic Ising model on a body-centered cubic lattice with interactions between next-to-nearest neighbors

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

Murtazaev, A. K.; Ramazanov, M. K., E-mail: sheikh77@mail.ru; Kassan-Ogly, F. A.

2015-01-15

Phase transitions in the antiferromagnetic Ising model on a body-centered cubic lattice are studied on the basis of the replica algorithm by the Monte Carlo method and histogram analysis taking into account the interaction of next-to-nearest neighbors. The phase diagram of the dependence of the critical temperature on the intensity of interaction of the next-to-nearest neighbors is constructed. It is found that a second-order phase transition is realized in this model in the investigated interval of the intensities of interaction of next-to-nearest neighbors.

Scrambling in the quantum Lifshitz model

NASA Astrophysics Data System (ADS)

Plamadeala, Eugeniu; Fradkin, Eduardo

2018-06-01

We study signatures of chaos in the quantum Lifshitz model through out-of-time ordered correlators (OTOC) of current operators. This model is a free scalar field theory with dynamical critical exponent z  =  2. It describes the quantum phase transition in 2D systems, such as quantum dimer models, between a phase with a uniform ground state to another one with spontaneously broken translation invariance. At the lowest temperatures the chaotic dynamics are dominated by a marginally irrelevant operator which induces a temperature dependent stiffness term. The numerical computations of OTOC exhibit a non-zero Lyapunov exponent (LE) in a wide range of temperatures and interaction strengths. The LE (in units of temperature) is a weakly temperature-dependent function; it vanishes at weak interaction and saturates for strong interaction. The Butterfly velocity increases monotonically with interaction strength in the studied region while remaining smaller than the interaction-induced velocity/stiffness.

Reading Aloud: Discrete Stage(s) Redux

PubMed Central

Robidoux, Serje; Besner, Derek

2017-01-01

Interactive activation accounts of processing have had a broad and deep influence on cognitive psychology, particularly so in the context of computational accounts of reading aloud at the single word level. Here we address the issue of whether such a framework can simulate the joint effects of stimulus quality and word frequency (which have been shown to produce both additive and interactive effects depending on the context). We extend previous work on this question by considering an alternative implementation of a stimulus quality manipulation, and the role of interactive activation. Simulations with a version of the Dual Route Cascaded model (a model with interactive activation dynamics along the lexical route) demonstrate that the model is unable to simulate the entire pattern seen in human performance. We discuss how a hybrid interactive activation model that includes some context dependent staged processing could accommodate these data. PMID:28289395

A test of an interactive model of binge eating among undergraduate men.

PubMed

Minnich, Allison M; Gordon, Kathryn H; Holm-Denoma, Jill M; Troop-Gordon, Wendy

2014-12-01

Past research has shown that a combination of high perfectionism, high body dissatisfaction, and low self-esteem is predictive of binge eating in college women (Bardone-Cone et al., 2006). In the current study, we examined whether this triple interaction model is applicable to men. Male undergraduate college students from a large Midwestern university (n=302) completed self-report measures online at two different time points, a minimum of eight weeks apart. Analyses revealed a significant interaction between the three risk factors, such that high perfectionism, high body dissatisfaction, and low self-esteem at Time 1 were associated with higher levels of Time 2 binge eating symptoms. The triple interaction model did not predict Time 2 anxiety or depressive symptoms, which suggests model specificity. These findings offer a greater understanding of the interactive nature of risk factors in predicting binge eating symptoms among men. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling Human Dynamics of Face-to-Face Interaction Networks

NASA Astrophysics Data System (ADS)

Starnini, Michele; Baronchelli, Andrea; Pastor-Satorras, Romualdo

2013-04-01

Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of interconversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here we present a simple model that reproduces quantitatively most of the relevant features of empirical face-to-face interaction networks. The model describes agents that perform a random walk in a two-dimensional space and are characterized by an attractiveness whose effect is to slow down the motion of people around them. The proposed framework sheds light on the dynamics of human interactions and can improve the modeling of dynamical processes taking place on the ensuing dynamical social networks.

Amphiphilic naproxen prodrugs: differential scanning calorimetry study on their interaction with phospholipid bilayers.

PubMed

Giuffrida, Maria Chiara; Pignatello, Rosario; Castelli, Francesco; Sarpietro, Maria Grazia

2017-09-01

Naproxen, a nonsteroid anti-inflammatory drug studied for Alzheimer's disease, was conjugated with lipoamino acids (LAA) directly or through a diethylamine (EDA) spacer to improve the drug lipophilicity and the interaction with phospholipid bilayers. The interaction of naproxen and its prodrugs with biomembrane models consisting of dimyristoylphosphatidylcholine multilamellar vesicles was studied by differential scanning calorimetry. The transfer of prodrugs from a lipophilic carrier to a biomembrane model was also studied. Naproxen conjugation to lipoamino acids improves its interaction with biomembrane models and affects the transfer from a lipophilic carrier to biomembrane model. LAA portion may localize between the phospholipid chains; the entity of the interaction depends not only on the presence of the spacer but also on the LAA chain length. Variation of LAA portion can modulate the naproxen prodrugs affinity towards the biological membrane as well as towards the lipophilic carrier. © 2017 Royal Pharmaceutical Society.

Modeling interactions between political parties and electors

NASA Astrophysics Data System (ADS)

Bagarello, F.; Gargano, F.

2017-09-01

In this paper we extend some recent results on an operatorial approach to the description of alliances between political parties interacting among themselves and with a basin of electors. In particular, we propose and compare three different models, deducing the dynamics of their related decision functions, i.e. the attitude of each party to form or not an alliance. In the first model the interactions between each party and their electors are considered. We show that these interactions drive the decision functions toward certain asymptotic values depending on the electors only: this is the perfect party, which behaves following the electors' suggestions. The second model is an extension of the first one in which we include a rule which modifies the status of the electors, and of the decision functions as a consequence, at some specific time step. In the third model we neglect the interactions with the electors while we consider cubic and quartic interactions between the parties and we show that we get (slightly oscillating) asymptotic values for the decision functions, close to their initial values. This is the real party, which does not listen to the electors. Several explicit situations are considered in details and numerical results are also shown.

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.

PubMed

Staniczenko, Phillip P A; Sivasubramaniam, Prabu; Suttle, K Blake; Pearson, Richard G

2017-06-01

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

Integrable generalizations of non-linear multiple three-wave interaction models

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

1989-07-01

Integrable generalizations of multiple three-wave interaction models in terms of r-matrix formulation are investigated. The Lax representations, complete sets of first integrals in involution are constructed, the quantization leading to Gaudin's models is discussed.

A Grammar-based Approach for Modeling User Interactions and Generating Suggestions During the Data Exploration Process.

PubMed

Dabek, Filip; Caban, Jesus J

2017-01-01

Despite the recent popularity of visual analytics focusing on big data, little is known about how to support users that use visualization techniques to explore multi-dimensional datasets and accomplish specific tasks. Our lack of models that can assist end-users during the data exploration process has made it challenging to learn from the user's interactive and analytical process. The ability to model how a user interacts with a specific visualization technique and what difficulties they face are paramount in supporting individuals with discovering new patterns within their complex datasets. This paper introduces the notion of visualization systems understanding and modeling user interactions with the intent of guiding a user through a task thereby enhancing visual data exploration. The challenges faced and the necessary future steps to take are discussed; and to provide a working example, a grammar-based model is presented that can learn from user interactions, determine the common patterns among a number of subjects using a K-Reversible algorithm, build a set of rules, and apply those rules in the form of suggestions to new users with the goal of guiding them along their visual analytic process. A formal evaluation study with 300 subjects was performed showing that our grammar-based model is effective at capturing the interactive process followed by users and that further research in this area has the potential to positively impact how users interact with a visualization system.

How Model Can Help Inquiry--A Qualitative Study of Model Based Inquiry Learning (Mobile) in Engineering Education

ERIC Educational Resources Information Center

Gong, Yu

2017-01-01

This study investigates how students can use "interactive example models" in inquiry activities to develop their conceptual knowledge about an engineering phenomenon like electromagnetic fields and waves. An interactive model, for example a computational model, could be used to develop and teach principles of dynamic complex systems, and…

Key Results of Interaction Models with Centering

ERIC Educational Resources Information Center

Afshartous, David; Preston, Richard A.

2011-01-01

We consider the effect on estimation of simultaneous variable centering and interaction effects in linear regression. We technically define, review, and amplify many of the statistical issues for interaction models with centering in order to create a useful and compact reference for teachers, students, and applied researchers. In addition, we…

Strong interactions in air showers

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

Dietrich, Dennis D.; Institut für Theoretische Physik, Goethe-Universität, Max-von-Laue-Straße, Frankfurt am Main

2015-03-02

We study the role new gauge interactions in extensions of the standard model play in air showers initiated by ultrahigh-energy cosmic rays. Hadron-hadron events remain dominated by quantum chromodynamics, while projectiles and/or targets from beyond the standard model permit us to see qualitative differences arising due to the new interactions.

Towards a Model of Human Resource Solutions for Achieving Intergenerational Interaction in Organisations

ERIC Educational Resources Information Center

McGuire, David; By, Rune Todnem; Hutchings, Kate

2007-01-01

Purpose: Achieving intergenerational interaction and avoiding conflict is becoming increasingly difficult in a workplace populated by three generations--Baby Boomers, Generation X-ers and Generation Y-ers. This paper presents a model and proposes HR solutions towards achieving co-operative generational interaction. Design/methodology/approach:…

The Behavior of Preschool Handicapped Children and Their Interactions with Model Children: An Update.

ERIC Educational Resources Information Center

Montemurro, Theodore J.

The behavior patterns of 6 handicapped children and 14 nonhandicapped children were recorded during participation in a model developmental-interactive based curriculum for preschool children. Interactions were recorded using the Coping Analysis Schedule for Educational Settings. Among findings were the following: the consistently high occurrence…

Problem Solving: Physics Modeling-Based Interactive Engagement

ERIC Educational Resources Information Center

Ornek, Funda

2009-01-01

The purpose of this study was to investigate how modeling-based instruction combined with an interactive-engagement teaching approach promotes students' problem solving abilities. I focused on students in a calculus-based introductory physics course, based on the matter and interactions curriculum of Chabay & Sherwood (2002) at a large state…

Speech Perception as a Cognitive Process: The Interactive Activation Model.

ERIC Educational Resources Information Center

Elman, Jeffrey L.; McClelland, James L.

Research efforts to model speech perception in terms of a processing system in which knowledge and processing are distributed over large numbers of highly interactive--but computationally primative--elements are described in this report. After discussing the properties of speech that demand a parallel interactive processing system, the report…

Five Papers on Human-Machine Interaction.

ERIC Educational Resources Information Center

Norman, Donald A.

Different aspects of human-machine interaction are discussed in the five brief papers that comprise this report. The first paper, "Some Observations on Mental Models," discusses the role of a person's mental model in the interaction with systems. The second paper, "A Psychologist Views Human Processing: Human Errors and Other…

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit.

PubMed

Pendergrass, Sarah A; Verma, Shefali S; Holzinger, Emily R; Moore, Carrie B; Wallace, John; Dudek, Scott M; Huggins, Wayne; Kitchner, Terrie; Waudby, Carol; Berg, Richard; McCarty, Catherine A; Ritchie, Marylyn D

2013-01-01

Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, 2580 cataract cases and 1367 controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) Biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 529,431 single nucleotide polymorphisms (SNPs) with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using the Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 5 statistically significant models with an interaction term with p-value < 0.05, as well as an overall model with p-value < 0.05 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use; these environmental factors have been previously associated with the formation of cataracts. We found a total of 288 models that exhibit an interaction term with a p-value ≤ 1×10(-4) associated with cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.

Polarizable molecular interactions in condensed phase and their equivalent nonpolarizable models.

PubMed

Leontyev, Igor V; Stuchebrukhov, Alexei A

2014-07-07

Earlier, using phenomenological approach, we showed that in some cases polarizable models of condensed phase systems can be reduced to nonpolarizable equivalent models with scaled charges. Examples of such systems include ionic liquids, TIPnP-type models of water, protein force fields, and others, where interactions and dynamics of inherently polarizable species can be accurately described by nonpolarizable models. To describe electrostatic interactions, the effective charges of simple ionic liquids are obtained by scaling the actual charges of ions by a factor of 1/√(ε(el)), which is due to electronic polarization screening effect; the scaling factor of neutral species is more complicated. Here, using several theoretical models, we examine how exactly the scaling factors appear in theory, and how, and under what conditions, polarizable Hamiltonians are reduced to nonpolarizable ones. These models allow one to trace the origin of the scaling factors, determine their values, and obtain important insights on the nature of polarizable interactions in condensed matter systems.

Test of Hadronic Interaction Models with the KASCADE Hadron Calorimeter

NASA Astrophysics Data System (ADS)

Milke, J.; KASCADE Collaboration

The interpretation of extensive air shower (EAS) measurements often requires the comparison with EAS simulations based on high-energy hadronic interaction models. These interaction models have to extrapolate into kinematical regions and energy ranges beyond the limit of present accelerators. Therefore, it is necessary to test whether these models are able to describe the EAS development in a consistent way. By measuring simultaneously the hadronic, electromagnetic, and muonic part of an EAS the experiment KASCADE offers best facilities for checking the models. For the EAS simulations the program CORSIKA with several hadronic event generators implemented is used. Different hadronic observables, e.g. hadron number, energy spectrum, lateral distribution, are investigated, as well as their correlations with the electromagnetic and muonic shower size. By comparing measurements and simulations the consistency of the description of the EAS development is checked. First results with the new interaction model NEXUS and the version II.5 of the model DPMJET, recently included in CORSIKA, are presented and compared with QGSJET simulations.

Interaction of actin filaments with the plasma membrane in Amoeba proteus: studies using a cell model and isolated plasma membrane.

PubMed

Kawakatsu, T; Kikuchi, A; Shimmen, T; Sonobe, S

2000-08-01

We prepared a cell model of Amoeba proteus by mechanical bursting to study the interaction between actin filaments (AFs) and plasma membrane (PM). The cell model prepared in the absence of Ca2+ showed remarkable contraction upon addition of ATP. When the model was prepared in the presence of Ca2+, the cytoplasmic granules formed an aggregate in the central region, having moved away from PM. Although this model showed contraction upon addition of ATP in the presence of Ca2+, less contraction was noted. Staining with rhodamine-phalloidin revealed association of AFs with PM in the former model, and a lesser amount of association in the latter model. The interaction between AFs and PM was also studied using the isolated PM. AFs were associated with PM isolated in the absence of Ca2+, but were not when Ca2+ was present. These results suggest that the interaction between AFs and PM is regulated by Ca2+.

Investigate wave-mean flow interaction and transport in the extratropical winter stratosphere

NASA Technical Reports Server (NTRS)

Smith, Anne K.

1993-01-01

The grant supported studies using several models along with observations in order to investigate some questions of wave-mean flow interaction and transport in the extratropical winter stratosphere. A quasi-geostrophic wave model was used to investigate the possibility that resonant growth of planetary wave 2 may have played a role in the sudden stratospheric warming of February 1979. The results of the time-dependent integration support the interpretation of resonance during February, 1979. Because of the possibility that the model treatment of critical line interactions exerted a controlling influence on the atmospheric dynamics, a more accurate model was needed for wave-mean flow interaction studies. A new model was adapted from the 3-dimensional primitive equation model developed by K. Rose and G. Brasseur. In its present form the model is global, rather than hemispheric; it contains an infrared cooling algorithm and a parameterized solar heating; it has parameterized gravity wave drag; and the chemistry has been entirely revised.

A coarse grain model for protein-surface interactions

NASA Astrophysics Data System (ADS)

Wei, Shuai; Knotts, Thomas A.

2013-09-01

The interaction of proteins with surfaces is important in numerous applications in many fields—such as biotechnology, proteomics, sensors, and medicine—but fundamental understanding of how protein stability and structure are affected by surfaces remains incomplete. Over the last several years, molecular simulation using coarse grain models has yielded significant insights, but the formalisms used to represent the surface interactions have been rudimentary. We present a new model for protein surface interactions that incorporates the chemical specificity of both the surface and the residues comprising the protein in the context of a one-bead-per-residue, coarse grain approach that maintains computational efficiency. The model is parameterized against experimental adsorption energies for multiple model peptides on different types of surfaces. The validity of the model is established by its ability to quantitatively and qualitatively predict the free energy of adsorption and structural changes for multiple biologically-relevant proteins on different surfaces. The validation, done with proteins not used in parameterization, shows that the model produces remarkable agreement between simulation and experiment.

Handling Massive Models: Representation, Real-Time Display and Interaction

DTIC Science & Technology

2008-09-16

Published, K. Ward, N. Galoppo, and M. Lin, "Interactive Virtual Hair Salon ", Presence, p. , vol. , (2007). Published, K. Ward, F. Bertails, T.-Y...Detection for Deformable Models using Representative-Triangles", Symposium on Interactive 3D Graphics and Games , p. , vol. , (2008). Published...Interactive 3D Graphics and Games (I3D), p. , vol. , (2008). Published, Brandon Lloyd, Naga K. Govindaraju, Cory Quammen, Steven E. Molnar, Dinesh

Emotional valence and context of social influences on drug abuse-related behavior in animal models of social stress and prosocial interaction

PubMed Central

Neisewander, J.L.; Peartree, N.A.; Pentkowski, N.S.

2014-01-01

Rationale Social factors are important determinants of drug dependence and relapse. Objectives We reviewed preclinical literature examining the role of social experiences from early life through the development of drug dependence and relapse, emphasizing two aspects of these experiences: 1) whether the social interaction is appetitive or aversive and 2) whether the social interaction occurs within or outside of the drug-taking context. Methods The models reviewed include neonatal care, isolation, social defeat, chronic subordination, and prosocial interactions. We review results from these models in regard to effects on self-administration and conditioned place preference established with alcohol, psychostimulants, and opiates. Results We suggest that in general, when the interactions occur outside of the drug-taking context, prosocial interactions are protective against drug abuse-related behaviors whereas social stressors facilitate these behaviors. By contrast, positive or negative social interactions occurring within the drug-taking context may interact with other risk factors to enhance or inhibit these behaviors. Conclusions Despite differences in the nature and complexity of human social behavior compared to other species, the evolving animal literature provides useful models for understanding social influences on drug abuse-related behavior that will allow for research on the behavioral and biological mechanisms involved. The models have contributed to understanding social influences on initiation and maintenance of drug use, but more research is needed to understand social influences on drug relapse. PMID:22955569

Open issues in hadronic interactions for air showers

NASA Astrophysics Data System (ADS)

Pierog, Tanguy

2017-06-01

In detailed air shower simulations, the uncertainty in the prediction of shower observables for different primary particles and energies is currently dominated by differences between hadronic interaction models. With the results of the first run of the LHC, the difference between post-LHC model predictions has been reduced to the same level as experimental uncertainties of cosmic ray experiments. At the same time new types of air shower observables, like the muon production depth, have been measured, adding new constraints on hadronic models. Currently no model is able to consistently reproduce all mass composition measurements possible within the Pierre Auger Observatory for instance. Comparing the different models, and with LHC and cosmic ray data, we will show that the remaining open issues in hadronic interactions in air shower development are now in the pion-air interactions and in nuclear effects.

Use of Molecular Modeling to Determine the Interaction and Competition of Gases within Coal for Carbon Dioxide Sequestration

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

Jeffrey D. Evanseck; Jeffry D. Madura

A 3-dimensional coal structural model for the Argonne Premium Coal Pocahontas No. 3 has been generated. The model was constructed based on the wealth of structural information available in the literature with the enhancement that the structural diversity within the structure was represented implicitly (for the first time) based on image analysis of HRTEM in combination with LDMS data. The complex and large structural model (>10,000 carbon atoms) will serve as a basis for examining the interaction of gases within this low volatile bituminous coal. Simulations are of interest to permit reasonable simulations of the host-guest interactions with regard tomore » carbon dioxide sequestration within coal and methane displacement from coal. The molecular structure will also prove useful in examining other coal related behavior such as solvent swelling, liquefaction and other properties. Molecular models of CO{sub 2} have been evaluated with water to analyze which classical molecular force-field parameters are the most reasonable to predict the interactions of CO{sub 2} with water. The comparison of the molecular force field models was for a single CO{sub 2}-H{sub 2}O complex and was compared against first principles quantum mechanical calculations. The interaction energies and the electrostatic interaction distances were used as criteria in the comparison. The ab initio calculations included Hartree-Fock, B3LYP, and Moeller-Plesset 2nd, 3rd, and 4th order perturbation theories with basis sets up to the aug-cc-pvtz basis set. The Steele model was the best literature model, when compared to the ab initio data, however, our new CO{sub 2} model reproduces the QM data significantly better than the Steele force-field model.« less

Effects of field interactions upon particle creation in Robertson-Walker universes

NASA Technical Reports Server (NTRS)

Birrell, N. D.; Davies, P. C. W.; Ford, L. H.

1980-01-01

Particle creation due to field interactions in an expanding Robertson-Walker universe is investigated. A model in which pseudoscalar mesons and photons are created as a result of their mutual interaction is considered, and the energy density of created particles is calculated in model universes which undergo a bounce at some maximum curvature. The free-field creation of non-conformally coupled scalar particles and of gravitons is calculated in the same space-times. It is found that if the bounce occurs at a sufficiently early time the interacting particle creation will dominate. This result may be traced to the fact that the model interaction chosen introduces a length scale which is much larger than the Planck length.

Propulsion and airframe aerodynamic interactions of supersonic V/STOL configurations. Volume 4: Summary

NASA Technical Reports Server (NTRS)

Zilz, D. E.; Wallace, H. W.; Hiley, P. E.

1985-01-01

A wind tunnel model of a supersonic V/STOL fighter configuration has been tested to measure the aerodynamic interaction effects which can result from geometrically close-coupled propulsion system/airframe components. The approach was to configure the model to represent two different test techniques. One was a conventional test technique composed of two test modes. In the Flow-Through mode, absolute configuration aerodynamics are measured, including inlet/airframe interactions. In the Jet-Effects mode, incremental nozzle/airframe interactions are measured. The other test technique is a propulsion simulator approach, where a sub-scale, externally powered engine is mounted in the model. This allows proper measurement of inlet/airframe and nozzle/airframe interactions simultaneously. This is Volume 4 of 4: Final Report- Summary.

Compulsory citizenship behavior and organizational citizenship behavior: the role of organizational identification and perceived interactional justice.

PubMed

Zhao, Hongdan; Peng, Zhenglong; Chen, Hsiu-Kuei

2014-01-01

This article examines the psychological mechanism underlying the relationship between compulsory citizenship behavior (CCB) and organizational citizenship behavior (OCB) by developing a moderated mediation model. The model focuses on the mediating role of organizational identification and the moderating role of interactional justice in influencing the mediation. Using a time-lagged research design, the authors collected two waves of data from 388 supervisor-subordinate dyads in 67 teams to test the moderated mediation model. Results revealed that CCB negatively influenced OCB via impairing organizational identification. Moreover, interactional justice moderated the strength of the indirect effect of CCB on OCB (through organizational identification), such that the mediated relationship was stronger under low interactional justice than under high interactional justice.

SABRINA - An interactive geometry modeler for MCNP (Monte Carlo Neutron Photon)

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

West, J.T.; Murphy, J.

SABRINA is an interactive three-dimensional geometry modeler developed to produce complicated models for the Los Alamos Monte Carlo Neutron Photon program MCNP. SABRINA produces line drawings and color-shaded drawings for a wide variety of interactive graphics terminals. It is used as a geometry preprocessor in model development and as a Monte Carlo particle-track postprocessor in the visualization of complicated particle transport problem. SABRINA is written in Fortran 77 and is based on the Los Alamos Common Graphics System, CGS. 5 refs., 2 figs.

Interacting steps with finite-range interactions: Analytical approximation and numerical results

NASA Astrophysics Data System (ADS)

Jaramillo, Diego Felipe; Téllez, Gabriel; González, Diego Luis; Einstein, T. L.

2013-05-01

We calculate an analytical expression for the terrace-width distribution P(s) for an interacting step system with nearest- and next-nearest-neighbor interactions. Our model is derived by mapping the step system onto a statistically equivalent one-dimensional system of classical particles. The validity of the model is tested with several numerical simulations and experimental results. We explore the effect of the range of interactions q on the functional form of the terrace-width distribution and pair correlation functions. For physically plausible interactions, we find modest changes when next-nearest neighbor interactions are included and generally negligible changes when more distant interactions are allowed. We discuss methods for extracting from simulated experimental data the characteristic scale-setting terms in assumed potential forms.

From synthetic modeling of social interaction to dynamic theories of brain-body-environment-body-brain systems.

PubMed

Froese, Tom; Iizuka, Hiroyuki; Ikegami, Takashi

2013-08-01

Synthetic approaches to social interaction support the development of a second-person neuroscience. Agent-based models and psychological experiments can be related in a mutually informing manner. Models have the advantage of making the nonlinear brain-body-environment-body-brain system as a whole accessible to analysis by dynamical systems theory. We highlight some general principles of how social interaction can partially constitute an individual's behavior.

Observational constraints on holographic tachyonic dark energy in interaction with dark matter

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

Micheletti, Sandro M. R., E-mail: smrm@fma.if.usp.br

2010-05-01

We discuss an interacting tachyonic dark energy model in the context of the holographic principle. The potential of the holographic tachyon field in interaction with dark matter is constructed. The model results are compared with CMB shift parameter, baryonic acoustic oscilations, lookback time and the Constitution supernovae sample. The coupling constant of the model is compatible with zero, but dark energy is not given by a cosmological constant.

Triangular arbitrage as an interaction among foreign exchange rates

NASA Astrophysics Data System (ADS)

Aiba, Yukihiro; Hatano, Naomichi; Takayasu, Hideki; Marumo, Kouhei; Shimizu, Tokiko

2002-07-01

We first show that there are in fact triangular arbitrage opportunities in the spot foreign exchange markets, analyzing the time dependence of the yen-dollar rate, the dollar-euro rate and the yen-euro rate. Next, we propose a model of foreign exchange rates with an interaction. The model includes effects of triangular arbitrage transactions as an interaction among three rates. The model explains the actual data of the multiple foreign exchange rates well.

Biofilm models of polymicrobial infection

PubMed Central

Gabrilska, Rebecca A; Rumbaugh, Kendra P

2015-01-01

Interactions between microbes are complex and play an important role in the pathogenesis of infections. These interactions can range from fierce competition for nutrients and niches to highly evolved cooperative mechanisms between different species that support their mutual growth. An increasing appreciation for these interactions, and desire to uncover the mechanisms that govern them, has resulted in a shift from monomicrobial to polymicrobial biofilm studies in different disease models. Here we provide an overview of biofilm models used to study select polymicrobial infections and highlight the impact that the interactions between microbes within these biofilms have on disease progression. Notable recent advances in the development of polymicrobial biofilm-associated infection models and challenges facing the study of polymicrobial biofilms are addressed. PMID:26592098

Positive affect predicts avoidance goals in social interaction anxiety: testing a hierarchical model of social goals.

PubMed

Trew, Jennifer L; Alden, Lynn E

2012-01-01

Models of self-regulation suggest that social goals may contribute to interpersonal and affective difficulties, yet little research has addressed this issue in the context of social anxiety. The present studies evaluated a hierarchical model of approach and avoidance in the context of social interaction anxiety, with affect as a mediating factor in the relationship between motivational tendencies and social goals. This model was refined in one undergraduate sample (N = 186) and cross-validated in a second sample (N = 195). The findings support hierarchical relationships between motivational tendencies, social interaction anxiety, affect, and social goals, with higher positive affect predicting fewer avoidance goals in both samples. Implications for the treatment of social interaction anxiety are discussed.

Laser interferometer skin-friction measurements of crossing-shock-wave/turbulent-boundary-layer interactions

NASA Technical Reports Server (NTRS)

Garrison, T. J.; Settles, G. S.; Narayanswami, N.; Knight, D. D.

1994-01-01

Wall shear stress measurements beneath crossing-shock-wave/turbulent boundary-layer interactions have been made for three interactions of different strengths. The interactions are generated by two sharp fins at symetric angles of attack mounted on a flat plate. The shear stress measurements were made for fin angles of 7 and 11 deg at Mach 3 and 15 deg at Mach 3.85. The measurements were made using a laser interferometer skin-friction meter, a device that determines the wall shear by optically measuring the time rate of thinning of an oil film placed on the test model surface. Results of the measurements reveal high skin-friction coefficients in the vicinity of the fin/plate junction and the presence of quasi-two-dimensional flow separation on the interaction center line. Additionally, two Navier-Stokes computations, one using a Baldwin-Lomax turbulence model and one using a k-epsilon model, are compared with the experimental results for the Mach 3.85, 15-deg interaction case. Although the k-epsilon model did a reasonable job of predicting the overall trend in portions of the skin-friction distribution, neither computation fully captured the physics of the near-surface flow in this complex interaction.

Laser Interferometer Skin-Friction measurements of crossing-shock wave/turbulent boundary-layer interactions

NASA Technical Reports Server (NTRS)

Garrison, T. J.; Settles, G. S.

1993-01-01

Wall shear stress measurements beneath crossingshock wave/turbulent boundary-layer interactions have been made for three interactions of different strengths. The interactions are generated by two sharp fins at symmetric angles of attack mounted on a flat plate. The shear stress measurements were made for fin angles of 7 and 11 degrees at Mach 3 and 15 degrees at Mach 4. The measurements were made using a Laser Interferometer Skin Friction (LISF) meter; a device which determines the wail shear by optically measuring the time rate of thinning of an oil film placed on the test model surface. Results of the measurements reveal high skin friction coefficients in the vicinity of the fin/plate junction and the presence of quasi-two-dimensional flow separation on the interaction centerline. Additionally, two Navier-Stokes computations, one using a Baldwin-Lomax turbulence model and one using a k- model, are compared to the experimental results for the Mach 4, 15 degree interaction case. While the k- model did a reasonable job of predicting the overall trend in portions of the skin friction distribution, neither computation fully captured the physics of the near surface flow in this complex interaction.

Quantum Treatment of Two Coupled Oscillators in Interaction with a Two-Level Atom:

NASA Astrophysics Data System (ADS)

Khalil, E. M.; Abdalla, M. Sebawe; Obada, A. S.-F.

In this communication we handle a modified model representing the interaction between a two-level atom and two modes of the electromagnetic field in a cavity. The interaction between the modes is assumed to be of a parametric amplifier type. The model consists of two different systems, one represents the Jaynes-Cummings model (atom-field interaction) and the other represents the two mode parametric amplifier model (field-field interaction). After some canonical transformations the constants of the motion have been obtained and used to derive the time evolution operator. The wave function in the Schrödinger picture is constructed and employed to discuss some statistical properties related to the system. Further discussion related to the statistical properties of some physical quantities is given where we have taken into account an initial correlated pair-coherent state for the modes. We concentrate in our examination on the system behavior that occurred as a result of the variation of the parametric amplifier coupling parameter as well as the detuning parameter. It has been shown that the interaction of the parametric amplifier term increases the revival period and consequently longer period of strong interaction between the atom and the fields.

Agent-based spin model for financial markets on complex networks: Emergence of two-phase phenomena

NASA Astrophysics Data System (ADS)

Kim, Yup; Kim, Hong-Joo; Yook, Soon-Hyung

2008-09-01

We study a microscopic model for financial markets on complex networks, motivated by the dynamics of agents and their structure of interaction. The model consists of interacting agents (spins) with local ferromagnetic coupling and global antiferromagnetic coupling. In order to incorporate more realistic situations, we also introduce an external field which changes in time. From numerical simulations, we find that the model shows two-phase phenomena. When the local ferromagnetic interaction is balanced with the global antiferromagnetic interaction, the resulting return distribution satisfies a power law having a single peak at zero values of return, which corresponds to the market equilibrium phase. On the other hand, if local ferromagnetic interaction is dominant, then the return distribution becomes double peaked at nonzero values of return, which characterizes the out-of-equilibrium phase. On random networks, the crossover between two phases comes from the competition between two different interactions. However, on scale-free networks, not only the competition between the different interactions but also the heterogeneity of underlying topology causes the two-phase phenomena. Possible relationships between the critical phenomena of spin system and the two-phase phenomena are discussed.

Learning Gene Expression Through Modelling and Argumentation. A Case Study Exploring the Connections Between the Worlds of Knowledge

NASA Astrophysics Data System (ADS)

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-12-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is framed in Tiberghien's (2000) two worlds of knowledge, the world of "theories & models" and the world of "objects & events", adding a third component, the world of representations. We seek to examine how modelling and argumentation interact and connect the three worlds of knowledge while modelling gene expression. It is a case study of 10th graders learning about diseases with a genetic component. The research questions are as follows: (1) What argumentative and modelling operations do students enact in the process of modelling gene expression? Specifically, which operations allow connecting the three worlds of knowledge? (2) What are the interactions between modelling and argumentation in modelling gene expression? To what extent do these interactions help students connect the three worlds of knowledge and modelling gene expression? The argumentative operation of using evidence helps students to relate the three worlds of knowledge, enacted in all the connections. It seems to be a relationship among the number of interactions between modelling and argumentation, the connections between world of knowledge and students' capacity to develop a more sophisticated representation. Despite this is a case study, this approach of analysis reveals potentialities for a deeper understanding of learning genetics though scientific practices.

Epistemological Models of the Teacher-Students Interaction in Academic Learning

ERIC Educational Resources Information Center

Yavoruk, Oleg

2017-01-01

This study deals with the most popular forms of the classroom communication related to the scientific cognitive models. The teachers tend to use simple intuitive models to describe the teaching issues: "Bucket theory"; "Knowledge floodlight"; "Interaction"; "Rationalism"; "Criticism";…

The 3-D CFD modeling of gas turbine combustor-integral bleed flow interaction

NASA Technical Reports Server (NTRS)

Chen, D. Y.; Reynolds, R. S.

1993-01-01

An advanced 3-D Computational Fluid Dynamics (CFD) model was developed to analyze the flow interaction between a gas turbine combustor and an integral bleed plenum. In this model, the elliptic governing equations of continuity, momentum and the k-e turbulence model were solved on a boundary-fitted, curvilinear, orthogonal grid system. The model was first validated against test data from public literature and then applied to a gas turbine combustor with integral bleed. The model predictions agreed well with data from combustor rig testing. The model predictions also indicated strong flow interaction between the combustor and the integral bleed. Integral bleed flow distribution was found to have a great effect on the pressure distribution around the gas turbine combustor.

Analysis of the Mechanism of Prolonged Persistence of Drug Interaction between Terbinafine and Amitriptyline or Nortriptyline.

PubMed

Mikami, Akiko; Hori, Satoko; Ohtani, Hisakazu; Sawada, Yasufumi

2017-01-01

The purpose of the study was to quantitatively estimate and predict drug interactions between terbinafine and tricyclic antidepressants (TCAs), amitriptyline or nortriptyline, based on in vitro studies. Inhibition of TCA-metabolizing activity by terbinafine was investigated using human liver microsomes. Based on the unbound K i values obtained in vitro and reported pharmacokinetic parameters, a pharmacokinetic model of drug interaction was fitted to the reported plasma concentration profiles of TCAs administered concomitantly with terbinafine to obtain the drug-drug interaction parameters. Then, the model was used to predict nortriptyline plasma concentration with concomitant administration of terbinafine and changes of area under the curve (AUC) of nortriptyline after cessation of terbinafine. The CYP2D6 inhibitory potency of terbinafine was unaffected by preincubation, so the inhibition seems to be reversible. Terbinafine competitively inhibited amitriptyline or nortriptyline E-10-hydroxylation, with unbound K i values of 13.7 and 12.4 nM, respectively. Observed plasma concentrations of TCAs administered concomitantly with terbinafine were successfully simulated with the drug interaction model using the in vitro parameters. Model-predicted nortriptyline plasma concentration after concomitant nortriptylene/terbinafine administration for two weeks exceeded the toxic level, and drug interaction was predicted to be prolonged; the AUC of nortriptyline was predicted to be increased by 2.5- or 2.0- and 1.5-fold at 0, 3 and 6 months after cessation of terbinafine, respectively. The developed model enables us to quantitatively predict the prolonged drug interaction between terbinafine and TCAs. The model should be helpful for clinical management of terbinafine-CYP2D6 substrate drug interactions, which are difficult to predict due to their time-dependency.

Interaction of ACE genotype and salt intake on hypertension among Chinese Kazakhs: results from a population-based cross-sectional study.

PubMed

Wang, Yuyan; Zhang, Biao; Hou, Lei; Han, Wei; Xue, Fang; Wang, Yanhong; Tang, Yong; Liang, Shaohua; Wang, Weizhi; Asaiti, Kuliqian; Wang, Zixing; Hu, Yaoda; Wang, Lei; Qiu, Changchun; Zhang, Mingtao; Jiang, Jingmei

2017-05-17

To explore the effect of interaction between ACE genotype and salt intake on hypertension among Chinese Kazakhs, and to compare applications of interactions between logistic model and generalised partially linear tree-based regression (GPLTR) model. Population-based cross-sectional study. Hong Dun, North Xinjiang, China. Non-consanguineous Chinese Kazakh participants (n=916, 342 men and 574 women) aged ≥30 years. Association between ACE genotype and hypertension, association between salt intake and hypertension, and interaction of ACE genotype and salt intake on hypertension in two models. Associations between salt intake and hypertension were different in ACE genotype of II and ID+DD. Under the logistic models, main and interaction effects were not observed for men, but effects were present in opposite directions for women (main effect of ACE: OR=0.20, p=0.003; interaction effect: OR=1.07, p=0.027). Under the GPLTR model, Bayesian information criterion trees included both salt intake and ACE genotype as split variables. Individuals with a salt intake ≥19.5 g/day and ID+DD genotypes had a 3.99-fold (p=0.004) higher risk of hypertension compared with the II genotype for men, whereas salt intake <20.1 g/day and ID+DD genotypes had an OR=0.55 (p=0.014) compared with the II genotype for women. An interaction of ACE genotype and salt intake on hypertension was observed among Chinese Kazakhs but in different ways according to sex. The GPLTR model appears to be more suitable for an exploration of interactions in complex diseases. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Interaction Mindsets, Interactional Behaviors, and L2 Development: An Affective-Social-Cognitive Model

ERIC Educational Resources Information Center

Sato, Masatoshi

2017-01-01

This classroom-based study explored links among second language (L2) learners' interaction mindsets, interactional behaviors, and L2 development in the context of peer interaction. While peer interaction research has revealed that certain interactional behaviors (e.g., receiving corrective feedback and engaging in collaborative interaction) assist…

Wing-wake interaction destabilizes hover equilibrium of a flapping insect-scale wing.

PubMed

Bluman, James; Kang, Chang-Kwon

2017-06-15

Wing-wake interaction is a characteristic nonlinear flow feature that can enhance unsteady lift in flapping flight. However, the effects of wing-wake interaction on the flight dynamics of hover are inadequately understood. We use a well-validated 2D Navier-Stokes equation solver and a quasi-steady model to investigate the role of wing-wake interaction on the hover stability of a fruit fly scale flapping flyer. The Navier-Stokes equations capture wing-wake interaction, whereas the quasi-steady models do not. Both aerodynamic models are tightly coupled to a flight dynamic model, which includes the effects of wing mass. The flapping amplitude, stroke plane angle, and flapping offset angle are adjusted in free flight for various wing rotations to achieve hover equilibrium. We present stability results for 152 simulations which consider different kinematics involving the pitch amplitude and pitch axis as well as the duration and timing of pitch rotation. The stability of all studied motions was qualitatively similar, with an unstable oscillatory mode present in each case. Wing-wake interaction has a destabilizing effect on the longitudinal stability, which cannot be predicted by a quasi-steady model. Wing-wake interaction increases the tendency of the flapping flyer to pitch up in the presence of a horizontal velocity perturbation, which further destabilizes the unstable oscillatory mode of hovering flight dynamics.

Disentangling and modeling interactions in fish with burst-and-coast swimming reveal distinct alignment and attraction behaviors

PubMed Central

Calovi, Daniel S.; Litchinko, Alexandra; Lopez, Ugo; Chaté, Hugues; Sire, Clément

2018-01-01

The development of tracking methods for automatically quantifying individual behavior and social interactions in animal groups has open up new perspectives for building quantitative and predictive models of collective behavior. In this work, we combine extensive data analyses with a modeling approach to measure, disentangle, and reconstruct the actual functional form of interactions involved in the coordination of swimming in Rummy-nose tetra (Hemigrammus rhodostomus). This species of fish performs burst-and-coast swimming behavior that consists of sudden heading changes combined with brief accelerations followed by quasi-passive, straight decelerations. We quantify the spontaneous stochastic behavior of a fish and the interactions that govern wall avoidance and the reaction to a neighboring fish, the latter by exploiting general symmetry constraints for the interactions. In contrast with previous experimental works, we find that both attraction and alignment behaviors control the reaction of fish to a neighbor. We then exploit these results to build a model of spontaneous burst-and-coast swimming and interactions of fish, with all parameters being estimated or directly measured from experiments. This model quantitatively reproduces the key features of the motion and spatial distributions observed in experiments with a single fish and with two fish. This demonstrates the power of our method that exploits large amounts of data for disentangling and fully characterizing the interactions that govern collective behaviors in animals groups. PMID:29324853

Modeling and Detecting Feature Interactions among Integrated Services of Home Network Systems

NASA Astrophysics Data System (ADS)

Igaki, Hiroshi; Nakamura, Masahide

This paper presents a framework for formalizing and detecting feature interactions (FIs) in the emerging smart home domain. We first establish a model of home network system (HNS), where every networked appliance (or the HNS environment) is characterized as an object consisting of properties and methods. Then, every HNS service is defined as a sequence of method invocations of the appliances. Within the model, we next formalize two kinds of FIs: (a) appliance interactions and (b) environment interactions. An appliance interaction occurs when two method invocations conflict on the same appliance, whereas an environment interaction arises when two method invocations conflict indirectly via the environment. Finally, we propose offline and online methods that detect FIs before service deployment and during execution, respectively. Through a case study with seven practical services, it is shown that the proposed framework is generic enough to capture feature interactions in HNS integrated services. We also discuss several FI resolution schemes within the proposed framework.

The Analysis of Three-Way Contingency Tables by Three-Mode Association Models.

ERIC Educational Resources Information Center

Anderson, Carolyn J.

1996-01-01

Generalizations of L. A. Goodman's RC(M) association model (1991 and earlier) are presented for three-way tables. These three-mode association models use L. R. Tucker's three-mode components model (1964, 1966) to represent the three-factor interaction or the combined effects of two- and three-factor interactions. (SLD)

Hierarchical Modeling of Sequential Behavioral Data: Examining Complex Association Patterns in Mediation Models

ERIC Educational Resources Information Center

Dagne, Getachew A.; Brown, C. Hendricks; Howe, George W.

2007-01-01

This article presents new methods for modeling the strength of association between multiple behaviors in a behavioral sequence, particularly those involving substantively important interaction patterns. Modeling and identifying such interaction patterns becomes more complex when behaviors are assigned to more than two categories, as is the case…

On quantum integrable models related to nonlinear quantum optics. An algebraic Bethe ansatz approach

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

1989-08-01

A unified approach based on Bethe ansatz in a large variety of integrable models in quantum optics is given. Second harmonics generation, three-boson interaction, the Dicke model, and some cases of four-boson interaction as special cases of su(2)⊕su(1,1)-Gaudin models are included.

Phenomenology of soft hadron interactions and the relevant EAS data

NASA Technical Reports Server (NTRS)

Kalmykov, N. N.; Khristiansen, G. B.; Motova, M. V.

1984-01-01

The interpretation of the experimental data in superhigh energy cosmic rays requires the calculations using various models of elementary hadron interaction. One should prefer the models justified by accelerator data and giving definite predictions for superhigh energies. The model of quark-gluon pomeron strings (the QGPS models) satisfies this requirement.

An Interactive Teaching System for Bond Graph Modeling and Simulation in Bioengineering

ERIC Educational Resources Information Center

Roman, Monica; Popescu, Dorin; Selisteanu, Dan

2013-01-01

The objective of the present work was to implement a teaching system useful in modeling and simulation of biotechnological processes. The interactive system is based on applications developed using 20-sim modeling and simulation software environment. A procedure for the simulation of bioprocesses modeled by bond graphs is proposed and simulators…

An Interactive, Instructor-Supported Reading Approach vs. Traditional Reading Instruction in Spanish

ERIC Educational Resources Information Center

Gladwin, Ransom F., IV; Stepp-Greany, Jonita

2008-01-01

This study analyzes the effects of the Interactive Reading with Instructor Support (IRIS) model on reading comprehension, as compared to a traditional (direct-teaching/lecture format) instructional model. The IRIS model combines reading strategies and social mediation together in the Spanish as a second language environment. In the IRIS model,…

Distance Education for the Gifted and Talented: An Interactive Design Model.

ERIC Educational Resources Information Center

McKinnon, David H.; Nolan, C. J. Patrick

1999-01-01

Discusses development of an Australian distance-education cosmology course that employs an interactive design model and an extensive communication system. The way the model is used to organized, sequence, and deliver the course is explained. Discussion addresses how the model might be used to design other courses. (Author/CR)

The Negative Effects of Positive Reinforcement in Teaching Children with Developmental Delay.

ERIC Educational Resources Information Center

Biederman, Gerald B.; And Others

1994-01-01

This study compared the performance of 12 children (ages 4 to 10) with developmental delay, each trained in 2 tasks, one through interactive modeling (with or without verbal reinforcement) and the other through passive modeling. Results showed that passive modeling produced better rated performance than interactive modeling and that verbal…

Separating direct and indirect effects of global change: a population dynamic modeling approach using readily available field data.

PubMed

Farrer, Emily C; Ashton, Isabel W; Knape, Jonas; Suding, Katharine N

2014-04-01

Two sources of complexity make predicting plant community response to global change particularly challenging. First, realistic global change scenarios involve multiple drivers of environmental change that can interact with one another to produce non-additive effects. Second, in addition to these direct effects, global change drivers can indirectly affect plants by modifying species interactions. In order to tackle both of these challenges, we propose a novel population modeling approach, requiring only measurements of abundance and climate over time. To demonstrate the applicability of this approach, we model population dynamics of eight abundant plant species in a multifactorial global change experiment in alpine tundra where we manipulated nitrogen, precipitation, and temperature over 7 years. We test whether indirect and interactive effects are important to population dynamics and whether explicitly incorporating species interactions can change predictions when models are forecast under future climate change scenarios. For three of the eight species, population dynamics were best explained by direct effect models, for one species neither direct nor indirect effects were important, and for the other four species indirect effects mattered. Overall, global change had negative effects on species population growth, although species responded to different global change drivers, and single-factor effects were slightly more common than interactive direct effects. When the fitted population dynamic models were extrapolated under changing climatic conditions to the end of the century, forecasts of community dynamics and diversity loss were largely similar using direct effect models that do not explicitly incorporate species interactions or best-fit models; however, inclusion of species interactions was important in refining the predictions for two of the species. The modeling approach proposed here is a powerful way of analyzing readily available datasets which should be added to our toolbox to tease apart complex drivers of global change. © 2013 John Wiley & Sons Ltd.

Evaluation of Aerosol-cloud Interaction in the GISS Model E Using ARM Observations

NASA Technical Reports Server (NTRS)

DeBoer, G.; Bauer, S. E.; Toto, T.; Menon, Surabi; Vogelmann, A. M.

2013-01-01

Observations from the US Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to evaluate the ability of the NASA GISS ModelE global climate model in reproducing observed interactions between aerosols and clouds. Included in the evaluation are comparisons of basic meteorology and aerosol properties, droplet activation, effective radius parameterizations, and surface-based evaluations of aerosol-cloud interactions (ACI). Differences between the simulated and observed ACI are generally large, but these differences may result partially from vertical distribution of aerosol in the model, rather than the representation of physical processes governing the interactions between aerosols and clouds. Compared to the current observations, the ModelE often features elevated droplet concentrations for a given aerosol concentration, indicating that the activation parameterizations used may be too aggressive. Additionally, parameterizations for effective radius commonly used in models were tested using ARM observations, and there was no clear superior parameterization for the cases reviewed here. This lack of consensus is demonstrated to result in potentially large, statistically significant differences to surface radiative budgets, should one parameterization be chosen over another.

A model of mechanical interactions between heart and lungs.

PubMed

Fontecave Jallon, Julie; Abdulhay, Enas; Calabrese, Pascale; Baconnier, Pierre; Gumery, Pierre-Yves

2009-12-13

To study the mechanical interactions between heart, lungs and thorax, we propose a mathematical model combining a ventilatory neuromuscular model and a model of the cardiovascular system, as described by Smith et al. (Smith, Chase, Nokes, Shaw & Wake 2004 Med. Eng. Phys.26, 131-139. (doi:10.1016/j.medengphy.2003.10.001)). The respiratory model has been adapted from Thibault et al. (Thibault, Heyer, Benchetrit & Baconnier 2002 Acta Biotheor. 50, 269-279. (doi:10.1023/A:1022616701863)); using a Liénard oscillator, it allows the activity of the respiratory centres, the respiratory muscles and rib cage internal mechanics to be simulated. The minimal haemodynamic system model of Smith includes the heart, as well as the pulmonary and systemic circulation systems. These two modules interact mechanically by means of the pleural pressure, calculated in the mechanical respiratory system, and the intrathoracic blood volume, calculated in the cardiovascular model. The simulation by the proposed model provides results, first, close to experimental data, second, in agreement with the literature results and, finally, highlighting the presence of mechanical cardiorespiratory interactions.

Assessment of Spacecraft Systems Integration Using the Electric Propulsion Interactions Code (EPIC)

NASA Technical Reports Server (NTRS)

Mikellides, Ioannis G.; Kuharski, Robert A.; Mandell, Myron J.; Gardner, Barbara M.; Kauffman, William J. (Technical Monitor)

2002-01-01

SAIC is currently developing the Electric Propulsion Interactions Code 'EPIC', an interactive computer tool that allows the construction of a 3-D spacecraft model, and the assessment of interactions between its subsystems and the plume from an electric thruster. EPIC unites different computer tools to address the complexity associated with the interaction processes. This paper describes the overall architecture and capability of EPIC including the physics and algorithms that comprise its various components. Results from selected modeling efforts of different spacecraft-thruster systems are also presented.

Rotating hot-wire investigation of the vortex responsible for blade-vortex interaction noise

NASA Technical Reports Server (NTRS)

Fontana, Richard Remo

1988-01-01

This distribution of the circumferential velocity of the vortex responsible for blade-vortex interaction noise was measured using a rotating hot-wire rake synchronously meshed with a model helicopter rotor at the blade passage frequency. Simultaneous far-field acoustic data and blade differential pressure measurements were obtained. Results show that the shape of the measured far-field acoustic blade-vortex interaction signature depends on the blade-vortex interaction geometry. The experimental results are compared with the Widnall-Wolf model for blade-vortex interaction noise.

sdg interacting-boson model in the SU(3) scheme and its application to 168Er

NASA Astrophysics Data System (ADS)

Yoshinaga, N.; Akiyama, Y.; Arima, A.

1988-07-01

The sdg interacting-boson model is presented in the SU(3) tensor formalism. The interactions are decomposed according to their SU(3) tensor character. The existence of the SU(3)-seniority preserving operator is found to be important. The model is applied to 168Er. Energy levels and electromagnetic transitions are calculated. This model is shown to solve the problem of anharmonicity regarding the excitation energy of the first Kπ=4+ band relative to that of the first Kπ=2+ one. E4 transitions are calculated to give different predictions from those by the quasiparticle-phonon nuclear model.

Shape: A 3D Modeling Tool for Astrophysics.

PubMed

Steffen, Wolfgang; Koning, Nicholas; Wenger, Stephan; Morisset, Christophe; Magnor, Marcus

2011-04-01

We present a flexible interactive 3D morpho-kinematical modeling application for astrophysics. Compared to other systems, our application reduces the restrictions on the physical assumptions, data type, and amount that is required for a reconstruction of an object's morphology. It is one of the first publicly available tools to apply interactive graphics to astrophysical modeling. The tool allows astrophysicists to provide a priori knowledge about the object by interactively defining 3D structural elements. By direct comparison of model prediction with observational data, model parameters can then be automatically optimized to fit the observation. The tool has already been successfully used in a number of astrophysical research projects.

The electronic-commerce-oriented virtual merchandise model

NASA Astrophysics Data System (ADS)

Fang, Xiaocui; Lu, Dongming

2004-03-01

Electronic commerce has been the trend of commerce activities. Providing with Virtual Reality interface, electronic commerce has better expressing capacity and interaction means. But most of the applications of virtual reality technology in EC, 3D model is only the appearance description of merchandises. There is almost no information concerned with commerce information and interaction information. This resulted in disjunction of virtual model and commerce information. So we present Electronic Commerce oriented Virtual Merchandise Model (ECVMM), which combined a model with commerce information, interaction information and figure information of virtual merchandise. ECVMM with abundant information provides better support to information obtainment and communication in electronic commerce.

Structure and dynamics of microbe-exuded polymers and their interactions with calcite surfaces.

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

Cygan, Randall Timothy; Mitchell, Ralph; Perry, Thomas D.

2005-12-01

Cation binding by polysaccharides is observed in many environments and is important for predictive environmental modeling, and numerous industrial and food technology applications. The complexities of these organo-cation interactions are well suited to predictive molecular modeling studies for investigating the roles of conformation and configuration of polysaccharides on cation binding. In this study, alginic acid was chosen as a model polymer and representative disaccharide and polysaccharide subunits were modeled. The ability of disaccharide subunits to bind calcium and to associate with the surface of calcite was investigated. The findings were extended to modeling polymer interactions with calcium ions.

Thermodynamic perturbation theory for fused sphere hard chain fluids using nonadditive interactions

NASA Astrophysics Data System (ADS)

Abu-Sharkh, Basel F.; Sunaidi, Abdallah; Hamad, Esam Z.

2004-03-01

A model is developed for the equation of state of fused chains based on Wertheim thermodynamic perturbation theory and nonadditive size interactions. The model also assumes that the structure (represented by the radial distribution function) of the fused chain fluid is the same as that of the touching hard sphere chain fluid. The model is completely based on spherical additive and nonadditive size interactions. The model has the advantage of offering good agreement with simulation data while at the same time being independent of fitted parameters. The model is most accurate for short chains, small values of Δ (slightly fused spheres) and at intermediate (liquidlike) densities.

Hierarchical, parallel computing strategies using component object model for process modelling responses of forest plantations to interacting multiple stresses

Treesearch

J. G. Isebrands; G. E. Host; K. Lenz; G. Wu; H. W. Stech

2000-01-01

Process models are powerful research tools for assessing the effects of multiple environmental stresses on forest plantations. These models are driven by interacting environmental variables and often include genetic factors necessary for assessing forest plantation growth over a range of different site, climate, and silvicultural conditions. However, process models are...

A crystal plasticity model for slip in hexagonal close packed metals based on discrete dislocation simulations

NASA Astrophysics Data System (ADS)

Messner, Mark C.; Rhee, Moono; Arsenlis, Athanasios; Barton, Nathan R.

2017-06-01

This work develops a method for calibrating a crystal plasticity model to the results of discrete dislocation (DD) simulations. The crystal model explicitly represents junction formation and annihilation mechanisms and applies these mechanisms to describe hardening in hexagonal close packed metals. The model treats these dislocation mechanisms separately from elastic interactions among populations of dislocations, which the model represents through a conventional strength-interaction matrix. This split between elastic interactions and junction formation mechanisms more accurately reproduces the DD data and results in a multi-scale model that better represents the lower scale physics. The fitting procedure employs concepts of machine learning—feature selection by regularized regression and cross-validation—to develop a robust, physically accurate crystal model. The work also presents a method for ensuring the final, calibrated crystal model respects the physical symmetries of the crystal system. Calibrating the crystal model requires fitting two linear operators: one describing elastic dislocation interactions and another describing junction formation and annihilation dislocation reactions. The structure of these operators in the final, calibrated model reflect the crystal symmetry and slip system geometry of the DD simulations.

A multi-fidelity framework for physics based rotor blade simulation and optimization

NASA Astrophysics Data System (ADS)

Collins, Kyle Brian

New helicopter rotor designs are desired that offer increased efficiency, reduced vibration, and reduced noise. Rotor Designers in industry need methods that allow them to use the most accurate simulation tools available to search for these optimal designs. Computer based rotor analysis and optimization have been advanced by the development of industry standard codes known as "comprehensive" rotorcraft analysis tools. These tools typically use table look-up aerodynamics, simplified inflow models and perform aeroelastic analysis using Computational Structural Dynamics (CSD). Due to the simplified aerodynamics, most design studies are performed varying structural related design variables like sectional mass and stiffness. The optimization of shape related variables in forward flight using these tools is complicated and results are viewed with skepticism because rotor blade loads are not accurately predicted. The most accurate methods of rotor simulation utilize Computational Fluid Dynamics (CFD) but have historically been considered too computationally intensive to be used in computer based optimization, where numerous simulations are required. An approach is needed where high fidelity CFD rotor analysis can be utilized in a shape variable optimization problem with multiple objectives. Any approach should be capable of working in forward flight in addition to hover. An alternative is proposed and founded on the idea that efficient hybrid CFD methods of rotor analysis are ready to be used in preliminary design. In addition, the proposed approach recognizes the usefulness of lower fidelity physics based analysis and surrogate modeling. Together, they are used with high fidelity analysis in an intelligent process of surrogate model building of parameters in the high fidelity domain. Closing the loop between high and low fidelity analysis is a key aspect of the proposed approach. This is done by using information from higher fidelity analysis to improve predictions made with lower fidelity models. This thesis documents the development of automated low and high fidelity physics based rotor simulation frameworks. The low fidelity framework uses a comprehensive code with simplified aerodynamics. The high fidelity model uses a parallel processor capable CFD/CSD methodology. Both low and high fidelity frameworks include an aeroacoustic simulation for prediction of noise. A synergistic process is developed that uses both the low and high fidelity frameworks together to build approximate models of important high fidelity metrics as functions of certain design variables. To test the process, a 4-bladed hingeless rotor model is used as a baseline. The design variables investigated include tip geometry and spanwise twist distribution. Approximation models are built for metrics related to rotor efficiency and vibration using the results from 60+ high fidelity (CFD/CSD) experiments and 400+ low fidelity experiments. Optimization using the approximation models found the Pareto Frontier anchor points, or the design having maximum rotor efficiency and the design having minimum vibration. Various Pareto generation methods are used to find designs on the frontier between these two anchor designs. When tested in the high fidelity framework, the Pareto anchor designs are shown to be very good designs when compared with other designs from the high fidelity database. This provides evidence that the process proposed has merit. Ultimately, this process can be utilized by industry rotor designers with their existing tools to bring high fidelity analysis into the preliminary design stage of rotors. In conclusion, the methods developed and documented in this thesis have made several novel contributions. First, an automated high fidelity CFD based forward flight simulation framework has been built for use in preliminary design optimization. The framework was built around an integrated, parallel processor capable CFD/CSD/AA process. Second, a novel method of building approximate models of high fidelity parameters has been developed. The method uses a combination of low and high fidelity results and combines Design of Experiments, statistical effects analysis, and aspects of approximation model management. And third, the determination of rotor blade shape variables through optimization using CFD based analysis in forward flight has been performed. This was done using the high fidelity CFD/CSD/AA framework and method mentioned above. While the low and high fidelity predictions methods used in the work still have inaccuracies that can affect the absolute levels of the results, a framework has been successfully developed and demonstrated that allows for an efficient process to improve rotor blade designs in terms of a selected choice of objective function(s). Using engineering judgment, this methodology could be applied today to investigate opportunities to improve existing designs. With improvements in the low and high fidelity prediction components that will certainly occur, this framework could become a powerful tool for future rotorcraft design work. (Abstract shortened by UMI.)

Exchange interactions in transition metal oxides: the role of oxygen spin polarization.

PubMed

Logemann, R; Rudenko, A N; Katsnelson, M I; Kirilyuk, A

2017-08-23

Magnetism of transition metal (TM) oxides is usually described in terms of the Heisenberg model, with orientation-independent interactions between the spins. However, the applicability of such a model is not fully justified for TM oxides because spin polarization of oxygen is usually ignored. In the conventional model based on the Anderson principle, oxygen effects are considered as a property of the TM ion and only TM interactions are relevant. Here, we perform a systematic comparison between two approaches for spin polarization on oxygen in typical TM oxides. To this end, we calculate the exchange interactions in NiO, MnO and hematite (Fe 2 O 3 ) for different magnetic configurations using the magnetic force theorem. We consider the full spin Hamiltonian including oxygen sites, and also derive an effective model where the spin polarization on oxygen renormalizes the exchange interactions between TM sites. Surprisingly, the exchange interactions in NiO depend on the magnetic state if spin polarization on oxygen is neglected, resulting in non-Heisenberg behavior. In contrast, the inclusion of spin polarization in NiO makes the Heisenberg model more applicable. Just the opposite, MnO behaves as a Heisenberg magnet when oxygen spin polarization is neglected, but shows strong non-Heisenberg effects when spin polarization on oxygen is included. In hematite, both models result in non-Heisenberg behavior. The general applicability of the magnetic force theorem as well as the Heisenberg model to TM oxides is discussed.

Intermolecular orbital interaction in π systems

NASA Astrophysics Data System (ADS)

Zhao, Rundong; Zhang, Rui-Qin

2018-04-01

Intermolecular interactions, in regard to which people tend to emphasise the noncovalent van der Waals (vdW) forces when conducting investigations throughout chemistry, can influence the structure, stability and function of molecules and materials. Despite the ubiquitous nature of vdW interactions, a simplified electrostatic model has been popularly adopted to explain common intermolecular interactions, especially those existing in π-involved systems. However, this classical model has come under fire in revealing specific issues such as substituent effects, due to its roughness; and it has been followed in past decades by sundry explanations which sometimes bring in nebulous descriptions. In this account, we try to summarise and present a unified model for describing and analysing the binding mechanism of such systems from the viewpoint of energy decomposition. We also emphasise a commonly ignored factor - orbital interaction, pointing out that the noncovalent intermolecular orbital interactions actually exhibit similar bonding and antibonding phenomena as those in covalent bonds.

Unintended consequences of information technologies in health care--an interactive sociotechnical analysis.

PubMed

Harrison, Michael I; Koppel, Ross; Bar-Lev, Shirly

2007-01-01

Many unintended and undesired consequences of Healthcare Information Technologies (HIT) flow from interactions between the HIT and the healthcare organization's sociotechnical system-its workflows, culture, social interactions, and technologies. This paper develops and illustrates a conceptual model of these processes that we call Interactive Sociotechnical Analysis (ISTA). ISTA captures common types of interaction with special emphasis on recursive processes, i.e., feedback loops that alter the newly introduced HIT and promote second-level changes in the social system. ISTA draws on prior studies of unintended consequences, along with research in sociotechnical systems, ergonomics, social informatics, technology-in-practice, and social construction of technology. We present five types of sociotechnical interaction and illustrate each with cases from published research. The ISTA model should further research on emergent and recursive processes in HIT implementation and their unintended consequences. Familiarity with the model can also foster practitioners' awareness of unanticipated consequences that only become evident during HIT implementation.

Staging scientific controversies: a gallery test on science museums' interactivity.

PubMed

Yaneva, Albena; Rabesandratana, Tania Mara; Greiner, Birgit

2009-01-01

The "transfer" model in science communication has been addressed critically from different perspectives, while the advantages of the interactive model have been continuously praised. Yet, little is done to account for the specific role of the interactive model in communicating "unfinished science." The traditional interactive methods in museums are not sufficient to keep pace with rapid scientific developments. Interactive exchanges between laypeople and experts are thought mainly through the lens of a dialogue that is facilitated and framed by the traditional "conference room" architecture. Drawing on the results of a small-scale experiment in a gallery space, we argue for the need for a new "architecture of interaction" in museum settings based on art installation and simulation techniques, which will enhance the communication potentials of science museums and will provide conditions for a fruitful even-handed exchange of expert and lay knowledge.

The role of perceived interactivity in virtual communities: building trust and increasing stickiness

NASA Astrophysics Data System (ADS)

Wang, Hongwei; Meng, Yuan; Wang, Wei

2013-03-01

Although previous research has explored factors affecting trust building in websites, little research has been analysed from the perceived interactivity perspective in virtual communities (VCs). A research model for verifying interactivity antecedents to trust and its impact on member stickiness behaviour is presented. Two social interactivity components and two system interactivity components are, respectively, theorised as process-based antecedents and institution-based antecedents to trust in the model. Data were collected from 310 members of VCs to test the model. The results show that connectedness and reciprocity are important antecedents to trust in members, while responsiveness and active control are important antecedents to trust in systems. The results also indicate that trust has significant influence on the members' duration and retention, which are two dimensions of member stickiness measured in this research. These findings have theoretical implications for online interaction-related literature and critical business implications for practitioners of VCs.

Long-range Acoustic Interactions in Insect Swarms - An Adaptive Gravity Model

NASA Astrophysics Data System (ADS)

Gorbonos, Dan; Ianconescu, Reuven; Puckett, James G.; Ni, Rui; Ouellette, Nicholas T.; Gov, Nir S.

The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. We consider mating swarms of midges, which are thought to interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our ``adaptive gravity'' model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. Additionally, the adaptive interactions open a new class of equations of motion, which may appear in other biological contexts.

Multiple tipping points and optimal repairing in interacting networks

PubMed Central

Majdandzic, Antonio; Braunstein, Lidia A.; Curme, Chester; Vodenska, Irena; Levy-Carciente, Sary; Eugene Stanley, H.; Havlin, Shlomo

2016-01-01

Systems composed of many interacting dynamical networks—such as the human body with its biological networks or the global economic network consisting of regional clusters—often exhibit complicated collective dynamics. Three fundamental processes that are typically present are failure, damage spread and recovery. Here we develop a model for such systems and find a very rich phase diagram that becomes increasingly more complex as the number of interacting networks increases. In the simplest example of two interacting networks we find two critical points, four triple points, ten allowed transitions and two ‘forbidden' transitions, as well as complex hysteresis loops. Remarkably, we find that triple points play the dominant role in constructing the optimal repairing strategy in damaged interacting systems. To test our model, we analyse an example of real interacting financial networks and find evidence of rapid dynamical transitions between well-defined states, in agreement with the predictions of our model. PMID:26926803

An interactive graphics system to facilitate finite element structural analysis

NASA Technical Reports Server (NTRS)

Burk, R. C.; Held, F. H.

1973-01-01

The characteristics of an interactive graphics systems to facilitate the finite element method of structural analysis are described. The finite element model analysis consists of three phases: (1) preprocessing (model generation), (2) problem solution, and (3) postprocessing (interpretation of results). The advantages of interactive graphics to finite element structural analysis are defined.

Levels of Interaction Provided by Online Distance Education Models

ERIC Educational Resources Information Center

Alhih, Mohammed; Ossiannilsson, Ebba; Berigel, Muhammet

2017-01-01

Interaction plays a significant role to foster usability and quality in online education. It is one of the quality standard to reveal the evidence of practice in online distance education models. This research study aims to evaluate levels of interaction in the practices of distance education centres. It is aimed to provide online distance…

Modeling Rich Interactions for Web Search Intent Inference, Ranking and Evaluation

ERIC Educational Resources Information Center

Guo, Qi

2012-01-01

Billions of people interact with Web search engines daily and their interactions provide valuable clues about their interests and preferences. While modeling search behavior, such as queries and clicks on results, has been found to be effective for various Web search applications, the effectiveness of the existing approaches are limited by…

The Impact of Social Interaction on Student Learning

ERIC Educational Resources Information Center

Hurst, Beth; Wallace, Randall; Nixon, Sarah B.

2013-01-01

Due to the lack of student engagement in the common lecture-centered model, we explored a model of instructional delivery where our undergraduate and graduate classes were structured so that students had opportunities for daily interaction with each other. Specifically, we examined how students perceived the value of social interaction on their…

Bilingual Lexical Interactions in an Unsupervised Neural Network Model

ERIC Educational Resources Information Center

Zhao, Xiaowei; Li, Ping

2010-01-01

In this paper we present an unsupervised neural network model of bilingual lexical development and interaction. We focus on how the representational structures of the bilingual lexicons can emerge, develop, and interact with each other as a function of the learning history. The results show that: (1) distinct representations for the two lexicons…

Analysis of Feedback Processes in Online Group Interaction: A Methodological Model

ERIC Educational Resources Information Center

Espasa, Anna; Guasch, Teresa; Alvarez, Ibis M.

2013-01-01

The aim of this article is to present a methodological model to analyze students' group interaction to improve their essays in online learning environments, based on asynchronous and written communication. In these environments teacher and student scaffolds for discussion are essential to promote interaction. One of these scaffolds can be the…

Investigation of head group behaviour of lamellar liquid crystals

NASA Astrophysics Data System (ADS)

Delikatny, E. J.; Burnell, E. E.

A mean field equilibrium statistical mechanical model, based on the Samulski inertial frame model, was developed to simulate experimental dipolar and quadrupolar nmr couplings of isotopically substituted potassium palmitates. An isolated four spin system was synthesized (2,2,3,3,-H4-palmitic acid-d27) and in conjunction with data presented in a previous paper on perdeuterated and carbon 13 labelled soaps, the head group behaviour of the molecule was investigated. Two interactions were considered in the modelling procedure: a mean field steric interaction characterized by a constraining cylinder, and a head group interaction characterized by a mass on the end of a rod of variable length. The rod lies along the first C-C bond direction and accounts for the interaction between polar head group and water via its effect on the moment of inertia of the molecule. In potassium palmitate mean field steric repulsive forces remain constant over the entire temperature range studied. In contrast, electrostatic interactions between polar head group and water, approximately constant at higher temperatures, increase dramatically as the phase transition is approached. This evidence supports a previously proposed model of lipidwater interaction.

Equilibrium, metastability, and hysteresis in a model spin-crossover material with nearest-neighbor antiferromagnetic-like and long-range ferromagnetic-like interactions

NASA Astrophysics Data System (ADS)

Rikvold, Per Arne; Brown, Gregory; Miyashita, Seiji; Omand, Conor; Nishino, Masamichi

2016-02-01

Phase diagrams and hysteresis loops were obtained by Monte Carlo simulations and a mean-field method for a simplified model of a spin-crossover material with a two-step transition between the high-spin and low-spin states. This model is a mapping onto a square-lattice S =1 /2 Ising model with antiferromagnetic nearest-neighbor and ferromagnetic Husimi-Temperley (equivalent-neighbor) long-range interactions. Phase diagrams obtained by the two methods for weak and strong long-range interactions are found to be similar. However, for intermediate-strength long-range interactions, the Monte Carlo simulations show that tricritical points decompose into pairs of critical end points and mean-field critical points surrounded by horn-shaped regions of metastability. Hysteresis loops along paths traversing the horn regions are strongly reminiscent of thermal two-step transition loops with hysteresis, recently observed experimentally in several spin-crossover materials. We believe analogous phenomena should be observable in experiments and simulations for many systems that exhibit competition between local antiferromagnetic-like interactions and long-range ferromagnetic-like interactions caused by elastic distortions.

Heat transfer modelling of pulsed laser-tissue interaction

NASA Astrophysics Data System (ADS)

Urzova, J.; Jelinek, M.

2018-03-01

Due to their attributes, the application of medical lasers is on the rise in numerous medical fields. From a biomedical point of view, the most interesting applications are the thermal interactions and the photoablative interactions, which effectively remove tissue without excessive heat damage to the remaining tissue. The objective of this work is to create a theoretical model for heat transfer in the tissue following its interaction with the laser beam to predict heat transfer during medical laser surgery procedures. The dimensions of the ablated crater (shape and ablation depth) were determined by computed tomography imaging. COMSOL Multiphysics software was used for temperature modelling. The parameters of tissue and blood, such as density, specific heat capacity, thermal conductivity and diffusivity, were calculated from the chemical ratio. The parameters of laser-tissue interaction, such as absorption and reflection coefficients, were experimentally determined. The parameters of the laser beam were power density, repetition frequency, pulse length and spot dimensions. Heat spreading after laser interaction with tissue was captured using a Fluke thermal camera. The model was verified for adipose tissue, skeletal muscle tissue and heart muscle tissue.

Rational redesign of inhibitors of furin/kexin processing proteases by electrostatic mutations.

PubMed

Cai, Xiao-hui; Zhang, Qing; Ding, Da-fu

2004-12-01

To model the three-dimensional structure and investigate the interaction mechanism of the proprotein convertase furin/kexin and their inhibitors (eglin c mutants). The three-dimensional complex structures of furin/kexin with its inhibitors, eglin c mutants, were generated by modeller program using the newly published X-ray crystallographical structures of mouse furin and yeast kexin as templates. The electrostatic interaction energy of each complex was calculated and the results were compared with the experimentally determined inhibition constants to find the correlation between them. High quality models of furin/kexin-eglin c mutants were obtained and used for calculation of the electrostatic interaction energies between the proteases and their inhibitors. The calculated electrostatic energies of interaction showed a linear correlation to the experimental inhibition constants. The modeled structures give good explanations of the specificity of eglin c mutants to furin/kexin. The electrostatic interactions play important roles in inhibitory activity of eglin c mutants to furin/kexin. The results presented here provided quantitative structural and functional information concerning the role of the charge-charge interactions in the binding of furin/kexin and their inhibitors.

Effect of P T symmetry on nonlinear waves for three-wave interaction models in the quadratic nonlinear media

NASA Astrophysics Data System (ADS)

Shen, Yujia; Wen, Zichao; Yan, Zhenya; Hang, Chao

2018-04-01

We study the three-wave interaction that couples an electromagnetic pump wave to two frequency down-converted daughter waves in a quadratic optical crystal and P T -symmetric potentials. P T symmetric potentials are shown to modulate stably nonlinear modes in two kinds of three-wave interaction models. The first one is a spatially extended three-wave interaction system with odd gain-and-loss distribution in the channel. Modulated by the P T -symmetric single-well or multi-well Scarf-II potentials, the system is numerically shown to possess stable soliton solutions. Via adiabatical change of system parameters, numerical simulations for the excitation and evolution of nonlinear modes are also performed. The second one is a combination of P T -symmetric models which are coupled via three-wave interactions. Families of nonlinear modes are found with some particular choices of parameters. Stable and unstable nonlinear modes are shown in distinct families by means of numerical simulations. These results will be useful to further investigate nonlinear modes in three-wave interaction models.

Influence of nonelectrostatic ion-ion interactions on double-layer capacitance

NASA Astrophysics Data System (ADS)

Zhao, Hui

2012-11-01

Recently a Poisson-Helmholtz-Boltzmann (PHB) model [Bohinc , Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.85.031130 85, 031130 (2012)] was developed by accounting for solvent-mediated nonelectrostatic ion-ion interactions. Nonelectrostatic interactions are described by a Yukawa-like pair potential. In the present work, we modify the PHB model by adding steric effects (finite ion size) into the free energy to derive governing equations. The modified PHB model is capable of capturing both ion specificity and ion crowding. This modified model is then employed to study the capacitance of the double layer. More specifically, we focus on the influence of nonelectrostatic ion-ion interactions on charging a double layer near a flat surface in the presence of steric effects. We numerically compute the differential capacitance as a function of the voltage under various conditions. At small voltages and low salt concentrations (dilute solution), we find out that the predictions from the modified PHB model are the same as those from the classical Poisson-Boltzmann theory, indicating that nonelectrostatic ion-ion interactions and steric effects are negligible. At moderate voltages, nonelectrostatic ion-ion interactions play an important role in determining the differential capacitance. Generally speaking, nonelectrostatic interactions decrease the capacitance because of additional nonelectrostatic repulsion among excess counterions inside the double layer. However, increasing the voltage gradually favors steric effects, which induce a condensed layer with crowding of counterions near the electrode. Accordingly, the predictions from the modified PHB model collapse onto those computed by the modified Poisson-Boltzmann theory considering steric effects alone. Finally, theoretical predictions are compared and favorably agree with experimental data, in particular, in concentrated solutions, leading one to conclude that the modified PHB model adequately predicts the diffuse-charge dynamics of the double layer with ion specificity and steric effects.

Linear time-varying models can reveal non-linear interactions of biomolecular regulatory networks using multiple time-series data.

PubMed

Kim, Jongrae; Bates, Declan G; Postlethwaite, Ian; Heslop-Harrison, Pat; Cho, Kwang-Hyun

2008-05-15

Inherent non-linearities in biomolecular interactions make the identification of network interactions difficult. One of the principal problems is that all methods based on the use of linear time-invariant models will have fundamental limitations in their capability to infer certain non-linear network interactions. Another difficulty is the multiplicity of possible solutions, since, for a given dataset, there may be many different possible networks which generate the same time-series expression profiles. A novel algorithm for the inference of biomolecular interaction networks from temporal expression data is presented. Linear time-varying models, which can represent a much wider class of time-series data than linear time-invariant models, are employed in the algorithm. From time-series expression profiles, the model parameters are identified by solving a non-linear optimization problem. In order to systematically reduce the set of possible solutions for the optimization problem, a filtering process is performed using a phase-portrait analysis with random numerical perturbations. The proposed approach has the advantages of not requiring the system to be in a stable steady state, of using time-series profiles which have been generated by a single experiment, and of allowing non-linear network interactions to be identified. The ability of the proposed algorithm to correctly infer network interactions is illustrated by its application to three examples: a non-linear model for cAMP oscillations in Dictyostelium discoideum, the cell-cycle data for Saccharomyces cerevisiae and a large-scale non-linear model of a group of synchronized Dictyostelium cells. The software used in this article is available from http://sbie.kaist.ac.kr/software

Electrostatic interaction map reveals a new binding position for tropomyosin on F-actin.

PubMed

Rynkiewicz, Michael J; Schott, Veronika; Orzechowski, Marek; Lehman, William; Fischer, Stefan

2015-12-01

Azimuthal movement of tropomyosin around the F-actin thin filament is responsible for muscle activation and relaxation. Recently a model of αα-tropomyosin, derived from molecular-mechanics and electron microscopy of different contractile states, showed that tropomyosin is rather stiff and pre-bent to present one specific face to F-actin during azimuthal transitions. However, a new model based on cryo-EM of troponin- and myosin-free filaments proposes that the interacting-face of tropomyosin can differ significantly from that in the original model. Because resolution was insufficient to assign tropomyosin side-chains, the interacting-face could not be unambiguously determined. Here, we use structural analysis and energy landscapes to further examine the proposed models. The observed bend in seven crystal structures of tropomyosin is much closer in direction and extent to the original model than to the new model. Additionally, we computed the interaction map for repositioning tropomyosin over the F-actin surface, but now extended over a much larger surface than previously (using the original interacting-face). This map shows two energy minima-one corresponding to the "blocked-state" as in the original model, and the other related by a simple 24 Å translation of tropomyosin parallel to the F-actin axis. The tropomyosin-actin complex defined by the second minimum fits perfectly into the recent cryo-EM density, without requiring any change in the interacting-face. Together, these data suggest that movement of tropomyosin between regulatory states does not require interacting-face rotation. Further, they imply that thin filament assembly may involve an interplay between initially seeded tropomyosin molecules growing from distinct binding-site regions on actin.

University Physics Students' Use of Models in Explanations of Phenomena Involving Interaction between Metals and Electromagnetic Radiation.

ERIC Educational Resources Information Center

Redfors, Andreas; Ryder, Jim

2001-01-01

Examines third year university physics students' use of models when explaining familiar phenomena involving interaction between metals and electromagnetic radiation. Concludes that few students use a single model consistently. (Contains 27 references.) (DDR)

An examination of a voluntary policy model to effect ...

EPA Pesticide Factsheets

An examination of a voluntary policy model to effect behavioral change and influence interactions and decision-making in the freight sector An examination of a voluntary policy model to effect behavioral change and influence interactions and decision-making in the freight sector

HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy.

PubMed

Hu, Huan; Zhang, Li; Ai, Haixin; Zhang, Hui; Fan, Yetian; Zhao, Qi; Liu, Hongsheng

2018-03-27

LncRNA plays an important role in many biological and disease progression by binding to related proteins. However, the experimental methods for studying lncRNA-protein interactions are time-consuming and expensive. Although there are a few models designed to predict the interactions of ncRNA-protein, they all have some common drawbacks that limit their predictive performance. In this study, we present a model called HLPI-Ensemble designed specifically for human lncRNA-protein interactions. HLPI-Ensemble adopts the ensemble strategy based on three mainstream machine learning algorithms of Support Vector Machines (SVM), Random Forests (RF) and Extreme Gradient Boosting (XGB) to generate HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble, respectively. The results of 10-fold cross-validation show that HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble achieved AUCs of 0.95, 0.96 and 0.96, respectively, in the test dataset. Furthermore, we compared the performance of the HLPI-Ensemble models with the previous models through external validation dataset. The results show that the false positives (FPs) of HLPI-Ensemble models are much lower than that of the previous models, and other evaluation indicators of HLPI-Ensemble models are also higher than those of the previous models. It is further showed that HLPI-Ensemble models are superior in predicting human lncRNA-protein interaction compared with previous models. The HLPI-Ensemble is publicly available at: http://ccsipb.lnu.edu.cn/hlpiensemble/ .

Phenomenology of ultrahigh energy neutrino interactions and fluxes

NASA Astrophysics Data System (ADS)

Hussain, Shahid

There are several models that predict the existence of high and ultrahigh energy (UHE) neutrinos; neutrinos that have amazingly high energies---energies above 10 15 eV. No man-made machines, existing or planned, can produce any particles of this high energies. It is the energies of these neutrinos that make them very interesting for the particle physics and astrophysics community; these neutrinos can be a unique tool to study the unknown regimes of energy, space, and time. Consequently, there is intense experimental activity focused on the detection of these neutrinos; no UHE neutrinos have been detected by these experiments so far. However, most of the UHE neutrino flux models predict that the fluxes of these neutrinos might be too small to be detected by the current detectors. Therefore, more powerful detectors are being built and we are at the beginning of a new and exciting era in neutrino astronomy. The interactions and fluxes of UHE neutrinos both are unknown experimentally. Our focus here is to explore, by numerically calculating observable signals from these neutrinos, different scenarios that can arise by the inter play of UHE neutrino interaction and flux models. Given several AGN and cosmogenic neutrino flux models, we look at two possibilities for neutrino interactions: (i) Neutrinos have standard model weak interactions at ultrahigh energies. (ii) neutrino interactions are enhanced around a TeV mass-scale, as implied by low scale gravity models with extra dimensions. The standard model weak and low scale gravity enhanced neutrino-nucleon interactions of UHE neutrinos both produce observable signals. In standard model, the charged current neutrino-nucleon interactions give muons, taus, and particle showers, and the neutral current interactions give particle showers. In low scale gravity, the micro black hole formation (and its subsequent decay) and the graviton exchange both give particle showers. Muons, taus, and the showers can be detected by the optical Cherenkov radiation they produce; showers can also be detected by the coherent radio Cherenkov signal they produce which is much powerful than their optical Cherenkov signal. We give the formalism for calculating muon, tau, and shower rates for the optical (ICECUBE- like) and the shower rates for the radio (RICE-like) Cherenkov detectors. Our focus is on simulation of the radio signal from neutrino-initiated showers and calculation of the expected neutrino-initiated shower rates for RICE. Finally, given the calculated rates for muons, taus, and showers, we discuss what we can say about the models for UHE neutrino fluxes and interactions.

Hadronic Interaction Models and the Air Shower Simulation Program CORSIKA

NASA Astrophysics Data System (ADS)

Heck, D.; KASCADE Collaboration

The Monte Carlo program CORSIKA simulates the 4-dimensional evolution of extensive air showers in the atmosphere initiated by photons, hadrons or nuclei. It contains links to the hadronic interaction models DPMJET, HDPM, NEXUS, QGSJET, SIBYLL, and VENUS. These codes are employed to treat the hadronic interactions at energies above 80 GeV. Since their first implementation in 1996 the models DPMJET and SIBYLL have been revised to versions II.5 and 2.1, respectively. Also the treatment of diffractive interactions by QGSJET has been slightly modified. The models DPMJET, QGSJET and SIBYLL are able to simulate collisions even at the highest energies reaching up to 1020 eV, which are at the focus of present research. The recently added NEXUS 2 program uses a unified approach combining Gribov-Regge theory and perturbative QCD. This model is based on the universality hypothesis of the behavior of highenergy interactions and presently works up to 1017 eV. A comparison of simulations performed with different models gives an indication on the systematic uncertainties of simulated air shower properties, which arise from the extrapolations to energies, kinematic ranges, or projectile-target combinations not covered by man-made colliders. Results obtained with the most actual programs are presented.

Stochastic analog neutron transport with TRIPOLI-4 and FREYA: Bayesian uncertainty quantification for neutron multiplicity counting

DOE PAGES

Verbeke, J. M.; Petit, O.

2016-06-01

From nuclear safeguards to homeland security applications, the need for the better modeling of nuclear interactions has grown over the past decades. Current Monte Carlo radiation transport codes compute average quantities with great accuracy and performance; however, performance and averaging come at the price of limited interaction-by-interaction modeling. These codes often lack the capability of modeling interactions exactly: for a given collision, energy is not conserved, energies of emitted particles are uncorrelated, and multiplicities of prompt fission neutrons and photons are uncorrelated. Many modern applications require more exclusive quantities than averages, such as the fluctuations in certain observables (e.g., themore » neutron multiplicity) and correlations between neutrons and photons. In an effort to meet this need, the radiation transport Monte Carlo code TRIPOLI-4® was modified to provide a specific mode that models nuclear interactions in a full analog way, replicating as much as possible the underlying physical process. Furthermore, the computational model FREYA (Fission Reaction Event Yield Algorithm) was coupled with TRIPOLI-4 to model complete fission events. As a result, FREYA automatically includes fluctuations as well as correlations resulting from conservation of energy and momentum.« less

Including gauge-group parameters into the theory of interactions: an alternative mass-generating mechanism for gauge fields

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

Aldaya, V.; Lopez-Ruiz, F. F.; Sanchez-Sastre, E.

2006-11-03

We reformulate the gauge theory of interactions by introducing the gauge group parameters into the model. The dynamics of the new 'Goldstone-like' bosons is accomplished through a non-linear {sigma}-model Lagrangian. They are minimally coupled according to a proper prescription which provides mass terms to the intermediate vector bosons without spoiling gauge invariance. The present formalism is explicitly applied to the Standard Model of electroweak interactions.

A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

PubMed Central

Zhang, Feng; Xu, Yuetong; Chou, Jarong

2016-01-01

The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples. PMID:27681730

Anomalous finite-size effect due to quasidegenerate phases in triangular antiferromagnets with long-range interactions and mapping to the generalized six-state clock model

NASA Astrophysics Data System (ADS)

Nishino, Masamichi; Miyashita, Seiji

2016-11-01

The effect of long-range (LR) interactions on frustrated-spin models is an interesting problem, which provides rich ordering processes. We study the effect of LR interactions on triangular Ising antiferromagnets with the next-nearest-neighbor ferromagnetic interaction (TIAFF). In the thermodynamic limit, the LRTIAFF model should reproduce the corresponding mean-field results, in which successive phase transitions occur among various phases, i.e., the disordered paramagnetic phase, so-called partially disordered phase, three-sublattice ferrimagnetic phase, and two-sublattice ferrimagnetic phase. In the present paper we focus on the magnetic susceptibility at the transition point between the two-sublattice ferrimagnetic and the disordered paramagnetic phases at relatively large ferromagnetic interactions. In the mean-field analysis, the magnetic susceptibility shows no divergence at the transition point. In contrast, a divergencelike enhancement of the susceptibility is observed in Monte Carlo simulations in finite-size systems. We investigate the origin of this difference and find that it is attributed to a virtual degeneracy of the free energies of the partially disordered and 2-FR phases. We also exploit a generalized six-state clock model with an LR interaction, which is a more general system with Z6 symmetry. We discuss the phase diagram of this model and find that it exhibits richer transition patterns and contains the physics of the LRTIAFF model.

Modelling surface water-groundwater interaction with a conceptual approach: model development and application in New Zealand

NASA Astrophysics Data System (ADS)

Yang, J.; Zammit, C.; McMillan, H. K.

2016-12-01

As in most countries worldwide, water management in lowland areas is a big concern for New Zealand due to its economic importance for water related human activities. As a result, the estimation of available water resources in these areas (e.g., for irrigation and water supply purpose) is crucial and often requires an understanding of complex hydrological processes, which are often characterized by strong interactions between surface water and groundwater (usually expressed as losing and gaining rivers). These processes are often represented and simulated using integrated physically based hydrological models. However models with physically based groundwater modules typically require large amount of non-readily available geologic and aquifer information and are computationally intensive. Instead, this paper presents a conceptual groundwater model that is fully integrated into New Zealand's national hydrological model TopNet based on TopModel concepts (Beven, 1992). Within this conceptual framework, the integrated model can simulate not only surface processes, but also groundwater processes and surface water-groundwater interaction processes (including groundwater flow, river-groundwater interaction, and groundwater interaction with external watersheds). The developed model was applied to two New Zealand catchments with different hydro-geological and climate characteristics (Pareora catchment in the Canterbury Plains and Grey catchment on the West Coast). Previous studies have documented strong interactions between the river and groundwater, based on the analysis of a large number of concurrent flow measurements and associated information along the river main stem. Application of the integrated hydrological model indicates flow simulation (compared to the original hydrological model conceptualisation) during low flow conditions are significantly improved and further insights on local river dynamics are gained. Due to its conceptual characteristics and low level of data requirement, the integrated model could be used at local and national scales to improve the simulation of hydrological processes in non-topographically driven areas (where groundwater processes are important), and to assess impact of climate change on the integrated hydrological cycle in these areas.

Does glimepiride alter the pharmacokinetics of sildenafil citrate in diabetic nephropathy animals: investigating mechanism of interaction by molecular modeling studies.

PubMed

Tripathi, Alok Shiomurti; Timiri, Ajay Kumar; Mazumder, Papiya Mitra; Chandewar, Anil

2015-10-01

The present study evaluates possible drug interactions between glimepiride (GLIM) and sildenafil citrate (SIL) in streptozotocin (STZ)-induced diabetic nephropathic (DN) animals and also postulates the possible mechanism of interaction based on molecular modeling studies. Diabetic nephropathy was induced by single dose of STZ (60 mg kg(-1), i.p.) and was confirmed by assessing blood and urine biochemical parameters 28 days after induction. Selected DN animals were used to explore the drug interaction between GLIM (0.5 mg kg(-1), p.o.) and SIL (2.5 mg kg(-1), p.o.) on the 29th and 70th day of the protocol. Possible drug interaction was assessed by evaluating the plasma drug concentration using HPLC-UV and changes in biochemical parameters in blood and urine were also determined. The mechanism of the interaction was postulated from the results of a molecular modeling study using the Maestro module of Schrodinger software. DN was confirmed as there was significant alteration in blood and urine biochemical parameters in STZ-treated groups. The concentration of SIL increased significantly (P < 0.001) in rat plasma when co-administered with GLIM on the 70th day of the protocol. Molecular modeling revealed important interactions with rat serum albumin and CYP2C9. GLIM has a strong hydrophobic interaction with binding site residues of rat serum albumin compared to SIL, whereas for CYP2C9, GLIM forms a stronger hydrogen bond than SIL with polar contacts and hydrophobic interactions. The present study concludes that bioavailability of SIL increases when co-administered chronically with GLIM in the management of DN animals, and the mechanism is supported by molecular modeling studies.

Models of science-policy interaction: exploring approaches to Bisphenol A management in the EU.

PubMed

Udovyk, O

2014-07-01

This study investigated science-policy interaction models and their limitations under conditions of uncertainty. In detail, it looked at the management of the suspected endocrine-disrupting chemical Bisphenol A (BPA). Despite growing evidence that BPA is hazardous to human and environmental health, the level of scientific uncertainty is still high and, as a result, there is significant disagreement on the actual extent and type of risk. Analysis of decision-making processes at different regulatory levels (EU, Sweden, and the Swedish municipality of Gothenburg) exposed chemicals risk management and associated science-policy interaction under uncertainty. The results of the study show that chemicals management and associated science-policy interaction follow the modern model of science-policy interaction, where science is assumed to 'speak truth to policy' and highlights existing limitations of this model under conditions of uncertainty. The study not only explores alternative models (precautionary, consensus, science-policy demarcation. and extended participation) but also shows their limitations. The study concludes that all models come with their particular underlying assumptions, strengths, and limitations. At the same time, by exposing serious limitations of the modern model, the study calls for a rethinking of the relationship between science, policy, and management. Copyright © 2014 Elsevier B.V. All rights reserved.

Structural and elastic properties of InX (X = P, As, Sb) at pressure and room temperature

NASA Astrophysics Data System (ADS)

Pawar, Pooja; Singh, Sadhna

2018-06-01

We have investigated the pressure-induced phase transition of InX (X = P, As, Sb) from Zinc-Blende (ZB) to NaCl structure by using realistic interaction potential model involving the effect of temperature. This model consists of Coulomb interaction, three-body interaction and short-range overlap repulsive interaction upto the second nearest neighbor involving temperature. Phase-transition pressure is associated with a sudden collapse in volume, showing the incidence of first-order phase transition. The phase-transition pressure is associated with volume collapses, and the elastic constants obtained from the present model indicate good agreement with the available experimental and theoretical data.

Variable sound speed in interacting dark energy models

NASA Astrophysics Data System (ADS)

Linton, Mark S.; Pourtsidou, Alkistis; Crittenden, Robert; Maartens, Roy

2018-04-01

We consider a self-consistent and physical approach to interacting dark energy models described by a Lagrangian, and identify a new class of models with variable dark energy sound speed. We show that if the interaction between dark energy in the form of quintessence and cold dark matter is purely momentum exchange this generally leads to a dark energy sound speed that deviates from unity. Choosing a specific sub-case, we study its phenomenology by investigating the effects of the interaction on the cosmic microwave background and linear matter power spectrum. We also perform a global fitting of cosmological parameters using CMB data, and compare our findings to ΛCDM.

Research on odor interaction between aldehyde compounds via a partial differential equation (PDE) model.

PubMed

Yan, Luchun; Liu, Jiemin; Qu, Chen; Gu, Xingye; Zhao, Xia

2015-01-28

In order to explore the odor interaction of binary odor mixtures, a series of odor intensity evaluation tests were performed using both individual components and binary mixtures of aldehydes. Based on the linear relation between the logarithm of odor activity value and odor intensity of individual substances, the relationship between concentrations of individual constituents and their joint odor intensity was investigated by employing a partial differential equation (PDE) model. The obtained results showed that the binary odor interaction was mainly influenced by the mixing ratio of two constituents, but not the concentration level of an odor sample. Besides, an extended PDE model was also proposed on the basis of the above experiments. Through a series of odor intensity matching tests for several different binary odor mixtures, the extended PDE model was proved effective at odor intensity prediction. Furthermore, odorants of the same chemical group and similar odor type exhibited similar characteristics in the binary odor interaction. The overall results suggested that the PDE model is a more interpretable way of demonstrating the odor interactions of binary odor mixtures.

A Penalized Robust Method for Identifying Gene-Environment Interactions

PubMed Central

Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

2015-01-01

In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model mis-specification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications. PMID:24616063

Constraining Roche-Lobe Overflow Models Using the Hot-Subdwarf Wide Binary Population

NASA Astrophysics Data System (ADS)

Vos, Joris; Vučković, Maja

2017-12-01

One of the important issues regarding the final evolution of stars is the impact of binarity. A rich zoo of peculiar, evolved objects are born from the interaction between the loosely bound envelope of a giant, and the gravitational pull of a companion. However, binary interactions are not understood from first principles, and the theoretical models are subject to many assumptions. It is currently agreed upon that hot subdwarf stars can only be formed through binary interaction, either through common envelope ejection or stable Roche-lobe overflow (RLOF) near the tip of the red giant branch (RGB). These systems are therefore an ideal testing ground for binary interaction models. With our long term study of wide hot subdwarf (sdB) binaries we aim to improve our current understanding of stable RLOF on the RGB by comparing the results of binary population synthesis studies with the observed population. In this article we describe the current model and possible improvements, and which observables can be used to test different parts of the interaction model.

Simple analytical model reveals the functional role of embodied sensorimotor interaction in hexapod gaits

PubMed Central

Aoi, Shinya; Nachstedt, Timo; Manoonpong, Poramate; Wörgötter, Florentin; Matsuno, Fumitoshi

2018-01-01

Insects have various gaits with specific characteristics and can change their gaits smoothly in accordance with their speed. These gaits emerge from the embodied sensorimotor interactions that occur between the insect’s neural control and body dynamic systems through sensory feedback. Sensory feedback plays a critical role in coordinated movements such as locomotion, particularly in stick insects. While many previously developed insect models can generate different insect gaits, the functional role of embodied sensorimotor interactions in the interlimb coordination of insects remains unclear because of their complexity. In this study, we propose a simple physical model that is amenable to mathematical analysis to explain the functional role of these interactions clearly. We focus on a foot contact sensory feedback called phase resetting, which regulates leg retraction timing based on touchdown information. First, we used a hexapod robot to determine whether the distributed decoupled oscillators used for legs with the sensory feedback generate insect-like gaits through embodied sensorimotor interactions. The robot generated two different gaits and one had similar characteristics to insect gaits. Next, we proposed the simple model as a minimal model that allowed us to analyze and explain the gait mechanism through the embodied sensorimotor interactions. The simple model consists of a rigid body with massless springs acting as legs, where the legs are controlled using oscillator phases with phase resetting, and the governed equations are reduced such that they can be explained using only the oscillator phases with some approximations. This simplicity leads to analytical solutions for the hexapod gaits via perturbation analysis, despite the complexity of the embodied sensorimotor interactions. This is the first study to provide an analytical model for insect gaits under these interaction conditions. Our results clarified how this specific foot contact sensory feedback contributes to generation of insect-like ipsilateral interlimb coordination during hexapod locomotion. PMID:29489831

System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).

PubMed

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN.

System-Level Insights into the Cellular Interactome of a Non-Model Organism: Inferring, Modelling and Analysing Functional Gene Network of Soybean (Glycine max)

PubMed Central

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN. PMID:25423109

Investigating the thermal dissociation of viral capsid by lattice model

NASA Astrophysics Data System (ADS)

Chen, Jingzhi; Chevreuil, Maelenn; Combet, Sophie; Lansac, Yves; Tresset, Guillaume

2017-11-01

The dissociation of icosahedral viral capsids was investigated by a homogeneous and a heterogeneous lattice model. In thermal dissociation experiments with cowpea chlorotic mottle virus and probed by small-angle neutron scattering, we observed a slight shrinkage of viral capsids, which can be related to the strengthening of the hydrophobic interaction between subunits at increasing temperature. By considering the temperature dependence of hydrophobic interaction in the homogeneous lattice model, we were able to give a better estimate of the effective charge. In the heterogeneous lattice model, two sets of lattice sites represented different capsid subunits with asymmetric interaction strengths. In that case, the dissociation of capsids was found to shift from a sharp one-step transition to a gradual two-step transition by weakening the hydrophobic interaction between AB and CC subunits. We anticipate that such lattice models will shed further light on the statistical mechanics underlying virus assembly and disassembly.

Log-Linear Models for Gene Association

PubMed Central

Hu, Jianhua; Joshi, Adarsh; Johnson, Valen E.

2009-01-01

We describe a class of log-linear models for the detection of interactions in high-dimensional genomic data. This class of models leads to a Bayesian model selection algorithm that can be applied to data that have been reduced to contingency tables using ranks of observations within subjects, and discretization of these ranks within gene/network components. Many normalization issues associated with the analysis of genomic data are thereby avoided. A prior density based on Ewens’ sampling distribution is used to restrict the number of interacting components assigned high posterior probability, and the calculation of posterior model probabilities is expedited by approximations based on the likelihood ratio statistic. Simulation studies are used to evaluate the efficiency of the resulting algorithm for known interaction structures. Finally, the algorithm is validated in a microarray study for which it was possible to obtain biological confirmation of detected interactions. PMID:19655032

Primary care access improvement: an empowerment-interaction model.

PubMed

Ledlow, G R; Bradshaw, D M; Shockley, C

2000-05-01

Improving community primary care access is a difficult and dynamic undertaking. Realizing a need to improve appointment availability, a systematic approach based on measurement, empowerment, and interaction was developed. The model fostered exchange of information and problem solving between interdependent staff sections within a managed care system. Measuring appointments demanded but not available proved to be a credible customer-focused approach to benchmark against set goals. Changing the organizational culture to become more sensitive to changing beneficiary needs was a paramount consideration. Dependent-group t tests were performed to compare the pretreatment and posttreatment effect. The empowerment-interaction model significantly improved the availability of routine and wellness-type appointments. The availability of urgent appointments improved but not significantly; a better prospective model needs to be developed. In aggregate, appointments demanded but not available (empowerment-interaction model) were more than 10% before the treatment and less than 3% with the treatment.

Energy economy in the actomyosin interaction: lessons from simple models.

PubMed

Lehman, Steven L

2010-01-01

The energy economy of the actomyosin interaction in skeletal muscle is both scientifically fascinating and practically important. This chapter demonstrates how simple cross-bridge models have guided research regarding the energy economy of skeletal muscle. Parameter variation on a very simple two-state strain-dependent model shows that early events in the actomyosin interaction strongly influence energy efficiency, and late events determine maximum shortening velocity. Addition of a weakly-bound state preceding force production allows weak coupling of cross-bridge mechanics and ATP turnover, so that a simple three-state model can simulate the velocity-dependence of ATP turnover. Consideration of the limitations of this model leads to a review of recent evidence regarding the relationship between ligand binding states, conformational states, and macromolecular structures of myosin cross-bridges. Investigation of the fine structure of the actomyosin interaction during the working stroke continues to inform fundamental research regarding the energy economy of striated muscle.

Recent Advances in the Theory and Simulation of Model Colloidal Microphase Formers.

PubMed

Zhuang, Yuan; Charbonneau, Patrick

2016-08-18

This mini-review synthesizes our understanding of the equilibrium behavior of particle-based models with short-range attractive and long-range repulsive (SALR) interactions. These models, which can form stable periodic microphases, aim to reproduce the essence of colloidal suspensions with competing interparticle interactions. Ordered structures, however, have yet to be obtained in experiments. In order to better understand the hurdles to periodic microphase assembly, marked theoretical and simulation advances have been made over the past few years. Here, we present recent progress in the study of microphases in models with SALR interactions using liquid-state theory and density-functional theory as well as numerical simulations. Combining these various approaches provides a description of periodic microphases, and gives insights into the rich phenomenology of the surrounding disordered regime. Ongoing research directions in the thermodynamics of models with SALR interactions are also presented.

Modeling Local Interactions during the Motion of Cyanobacteria

PubMed Central

Galante, Amanda; Wisen, Susanne; Bhaya, Devaki; Levy, Doron

2012-01-01

Synechocystis sp., a common unicellular freshwater cyanobacterium, has been used as a model organism to study phototaxis, an ability to move in the direction of a light source. This microorganism displays a number of additional characteristics such as delayed motion, surface dependence, and a quasi-random motion, where cells move in a seemingly disordered fashion instead of in the direction of the light source, a global force on the system. These unexplained motions are thought to be modulated by local interactions between cells such as intercellular communication. In this paper, we consider only local interactions of these phototactic cells in order to mathematically model this quasi-random motion. We analyze an experimental data set to illustrate the presence of quasi-random motion and then derive a stochastic dynamic particle system modeling interacting phototactic cells. The simulations of our model are consistent with experimentally observed phototactic motion. PMID:22713858

Multisite Interactions in Lattice-Gas Models

NASA Astrophysics Data System (ADS)

Einstein, T. L.; Sathiyanarayanan, R.

For detailed applications of lattice-gas models to surface systems, multisite interactions often play at least as significant a role as interactions between pairs of adatoms that are separated by a few lattice spacings. We recall that trio (3-adatom, non-pairwise) interactions do not inevitably create phase boundary asymmetries about half coverage. We discuss a sophisticated application to an experimental system and describe refinements in extracting lattice-gas energies from calculations of total energies of several different ordered overlayers. We describe how lateral relaxations complicate matters when there is direct interaction between the adatoms, an issue that is important when examining the angular dependence of step line tensions. We discuss the connector model as an alternative viewpoint and close with a brief account of recent work on organic molecule overlayers.

Propulsion and airframe aerodynamic interactions of supersonic V/STOL configurations. Volume 1: Wind tunnel test pressure data report

NASA Technical Reports Server (NTRS)

Zilz, D. E.; Devereaux, P. A.

1985-01-01

A wind tunnel model of a supersonic V/STOL fighter configuration has been tested to measure the aerodynamic interaction effects which can result from geometrically close-coupled propulsion system/airframe components. The approach was to configure the model to represent two different test techniques. One was a conventional test technique composed of two test modes. In the Flow-Through mode, absolute configuration aerodynamics are measured, including inlet/airframe interactions. In the Jet-Effects mode, incremental nozzle/airframe interactions are measured. The other test technique is a propulsion simulator approach, where a sub-scale, externally powered engine is mounted in the model. This allows proper measurement of inlet/airframe and nozzle/airframe interactions simultaneously. This is Volume 1 of 2: Wind Tunnel Test Pressure Data Report.

Performance implications of leader briefings and team-interaction training for team adaptation to novel environments.

PubMed

Marks, M A; Zaccaro, S J; Mathieu, J E

2000-12-01

The authors examined how leader briefings and team-interaction training influence team members' knowledge structures concerning processes related to effective performance in both routine and novel environments. Two-hundred thirty-seven undergraduates from a large mid-Atlantic university formed 79 three-member tank platoon teams and participated in a low-fidelity tank simulation. Team-interaction training, leader briefings, and novelty of performance environment were manipulated. Findings indicated that both leader briefings and team-interaction training affected the development of mental models, which in turn positively influenced team communication processes and team performance. Mental models and communication processes predicted performance more strongly in novel than in routine environments. Implications for the role of team-interaction training, leader briefings, and mental models as mechanisms for team adaptation are discussed.

An Integrative-Interactive Conceptual Model for Curriculum Development.

ERIC Educational Resources Information Center

Al-Ibrahim, Abdul Rahman H.

1982-01-01

The Integrative-Interactive Conceptual Model for Curriculum Development calls for curriculum reform and innovation to be cybernetic so that all aspects of curriculum planning get adequate attention. (CJ)

Editors pp iii Effects of long-range magnetic interactions on DLA aggregation [rapid communication

NASA Astrophysics Data System (ADS)

Xu, Xiao-Jun; Cai, Ping-Gen; Ye, Quan-Lin; Xia, A.-Gen; Ye, Gao-Xiang

2005-04-01

An extra degree of freedom is introduced in the well-known diffusion-limited aggregation model, i.e., the growth entities are “spin” taking. The model with long-range magnetic interactions that decay as βC/rα on two-dimensional square lattices is studied for different values of α. This model leads to a wide variety of kinetic processes and morphology distribution with both the coupling energy βC and the range of the interactions, i.e., the exponent α. The simulated result of the model shows that the “quenching” of the degree of freedom on the cluster by the long-range magnetic interactions leads to branching or compactness, but, moreover, to combined geometric and physical “transitions” of the aggregations with the growth parameters.

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

PubMed Central

Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John

2016-01-01

The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia. PMID:27725886

All-particle energy spectrum of KASCADE-Grande based on shower size and different hadronic interaction models

NASA Astrophysics Data System (ADS)

Kang, D.; Apel, W. D.; Arteaga-Velazquez, J. C.; Bekk, K.; Bertaina, M.; Blümer, J.; Bozdog, H.; Brancus, I. M.; Cantoni, E.; Chiavassa, A.; Cossavella, F.; Daumiller, K.; de Souza, V.; Di Pierro, F.; Doll, P.; Engel, R.; Engler, J.; Finger, M.; Fuchs, B.; Fuhrmann, D.; Gils, H. J.; Glasstetter, R.; Grupen, C.; Haungs, A.; Heck, D.; Hörandel, J. R.; Huber, D.; Huege, T.; Kampert, K.-H.; Klages, H. O.; Link, K.; Łuczak, P.; Ludwig, M.; Mathes, H. J.; Mayer, H. J.; Melissas, M.; Milke, J.; Morello, C.; Oehlschläger, J.; Ostapchenko, S.; Palmieri, N.; Petcu, M.; Pierog, T.; Rebel, H.; Roth, M.; Schieler, H.; Schoo, S.; Schroder, F.; Sima, O.; Toma, G.; Trinchero, G. C.; Ulrich, H.; Weindl, A.; Wochele, J.; Wommer, M.; Zabierowski, J.

2013-02-01

KASCADE-Grande is a large detector array for observations of the energy spectrum as well as the chemical composition of cosmic ray air showers up to primary energies of 1 EeV. The multi-detector arrangement allows to measure the electromagnetic and muonic components for individual air showers. In this analysis, the reconstruction of the all-particle energy spectrum is based on the size spectra of the charged particle component. The energy is calibrated by using Monte Carlo simulations performed with CORSIKA and high-energy interaction models QGSJet, EPOS and SIBYLL. In all cases FLUKA has been used as low-energy interaction model. In this contribution the resulting spectra by means of different hadronic interaction models will be compared and discussed.

Evaluating Differential Effects Using Regression Interactions and Regression Mixture Models

ERIC Educational Resources Information Center

Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

2015-01-01

Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their…

The Spiral-Interactive Program Evaluation Model.

ERIC Educational Resources Information Center

Khaleel, Ibrahim Adamu

1988-01-01

Describes the spiral interactive program evaluation model, which is designed to evaluate vocational-technical education programs in secondary schools in Nigeria. Program evaluation is defined; utility oriented and process oriented models for evaluation are described; and internal and external evaluative factors and variables that define each…

Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models

PubMed Central

2016-01-01

Studies of audiovisual perception of distance are rare. Here, visual and auditory cue interactions in distance are tested against several multisensory models, including a modified causal inference model. In this causal inference model predictions of estimate distributions are included. In our study, the audiovisual perception of distance was overall better explained by Bayesian causal inference than by other traditional models, such as sensory dominance and mandatory integration, and no interaction. Causal inference resolved with probability matching yielded the best fit to the data. Finally, we propose that sensory weights can also be estimated from causal inference. The analysis of the sensory weights allows us to obtain windows within which there is an interaction between the audiovisual stimuli. We find that the visual stimulus always contributes by more than 80% to the perception of visual distance. The visual stimulus also contributes by more than 50% to the perception of auditory distance, but only within a mobile window of interaction, which ranges from 1 to 4 m. PMID:27959919

Ontogenetic ritualization of primate gesture as a case study in dyadic brain modeling.

PubMed

Gasser, Brad; Cartmill, Erica A; Arbib, Michael A

2014-01-01

This paper introduces dyadic brain modeling - the simultaneous, computational modeling of the brains of two interacting agents - to explore ways in which our understanding of macaque brain circuitry can ground new models of brain mechanisms involved in ape interaction. Specifically, we assess a range of data on gestural communication of great apes as the basis for developing an account of the interactions of two primates engaged in ontogenetic ritualization, a proposed learning mechanism through which a functional action may become a communicative gesture over repeated interactions between two individuals (the 'dyad'). The integration of behavioral, neural, and computational data in dyadic (or, more generally, social) brain modeling has broad application to comparative and evolutionary questions, particularly for the evolutionary origins of cognition and language in the human lineage. We relate this work to the neuroinformatics challenges of integrating and sharing data to support collaboration between primatologists, neuroscientists and modelers that will help speed the emergence of what may be called comparative neuro-primatology.

Assessing the applicability of template-based protein docking in the twilight zone.

PubMed

Negroni, Jacopo; Mosca, Roberto; Aloy, Patrick

2014-09-02

The structural modeling of protein interactions in the absence of close homologous templates is a challenging task. Recently, template-based docking methods have emerged to exploit local structural similarities to help ab-initio protocols provide reliable 3D models for protein interactions. In this work, we critically assess the performance of template-based docking in the twilight zone. Our results show that, while it is possible to find templates for nearly all known interactions, the quality of the obtained models is rather limited. We can increase the precision of the models at expenses of coverage, but it drastically reduces the potential applicability of the method, as illustrated by the whole-interactome modeling of nine organisms. Template-based docking is likely to play an important role in the structural characterization of the interaction space, but we still need to improve the repertoire of structural templates onto which we can reliably model protein complexes. Copyright © 2014 Elsevier Ltd. All rights reserved.

New generation of exploration tools: interactive modeling software and microcomputers

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

Krajewski, S.A.

1986-08-01

Software packages offering interactive modeling techniques are now available for use on microcomputer hardware systems. These packages are reasonably priced for both company and independent explorationists; they do not require users to have high levels of computer literacy; they are capable of rapidly completing complex ranges of sophisticated geologic and geophysical modeling tasks; and they can produce presentation-quality output for comparison with real-world data. For example, interactive packages are available for mapping, log analysis, seismic modeling, reservoir studies, and financial projects as well as for applying a variety of statistical and geostatistical techniques to analysis of exploration data. More importantly,more » these packages enable explorationists to directly apply their geologic expertise when developing and fine-tuning models for identifying new prospects and for extending producing fields. As a result of these features, microcomputers and interactive modeling software are becoming common tools in many exploration offices. Gravity and magnetics software programs illustrate some of the capabilities of such exploration tools.« less

Simulation of Hydraulic and Natural Fracture Interaction Using a Coupled DFN-DEM Model

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

Zhou, J.; Huang, H.; Deo, M.

2016-03-01

The presence of natural fractures will usually result in a complex fracture network due to the interactions between hydraulic and natural fracture. The reactivation of natural fractures can generally provide additional flow paths from formation to wellbore which play a crucial role in improving the hydrocarbon recovery in these ultra-low permeability reservoir. Thus, accurate description of the geometry of discrete fractures and bedding is highly desired for accurate flow and production predictions. Compared to conventional continuum models that implicitly represent the discrete feature, Discrete Fracture Network (DFN) models could realistically model the connectivity of discontinuities at both reservoir scale andmore » well scale. In this work, a new hybrid numerical model that couples Discrete Fracture Network (DFN) and Dual-Lattice Discrete Element Method (DL-DEM) is proposed to investigate the interaction between hydraulic fracture and natural fractures. Based on the proposed model, the effects of natural fracture orientation, density and injection properties on hydraulic-natural fractures interaction are investigated.« less

Identifying and modeling the structural discontinuities of human interactions

NASA Astrophysics Data System (ADS)

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

Identifying and modeling the structural discontinuities of human interactions

PubMed Central

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-01-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales. PMID:28443647

Diffusion-controlled reactions: hydrodynamic interaction between charged, uniformly reactive spherical reactants.

PubMed

Allison, Stuart

2006-12-28

In this work, different models of hydrodynamic interaction (HI) are examined in the diffusion-controlled reaction between uniformly reactive charged spherical particles. In addition to Oseen "stick" and "slip" models of HI, one is considered that accounts for the disturbance of fluid flow by the ions around one reactive partner as they interact with a neighboring reactive species. This interaction is closely related to the "electrophoretic effect" in electrokinetics and can be described by a fairly simple electrophoretic, or E-tensor. These models are applied to the electron-transfer quenching reaction of Ru(bpy)3(2+) and methyl viologen (MV2+) over a wide range of NaCl concentrations (Chiorboli, C. et al., J. Phys. Chem. 1988, 92, 156). The back reaction is also considered. From a comparison of the salt dependence of the model and experimental rates, it is concluded that the "E-tensor" model works best and ignoring HI altogether works worst. The Oseen "stick" and "slip" models fall between these.

Identifying and modeling the structural discontinuities of human interactions.

PubMed

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-26

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

Simulation of Hydraulic and Natural Fracture Interaction Using a Coupled DFN-DEM Model

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

J. Zhou; H. Huang; M. Deo

The presence of natural fractures will usually result in a complex fracture network due to the interactions between hydraulic and natural fracture. The reactivation of natural fractures can generally provide additional flow paths from formation to wellbore which play a crucial role in improving the hydrocarbon recovery in these ultra-low permeability reservoir. Thus, accurate description of the geometry of discrete fractures and bedding is highly desired for accurate flow and production predictions. Compared to conventional continuum models that implicitly represent the discrete feature, Discrete Fracture Network (DFN) models could realistically model the connectivity of discontinuities at both reservoir scale andmore » well scale. In this work, a new hybrid numerical model that couples Discrete Fracture Network (DFN) and Dual-Lattice Discrete Element Method (DL-DEM) is proposed to investigate the interaction between hydraulic fracture and natural fractures. Based on the proposed model, the effects of natural fracture orientation, density and injection properties on hydraulic-natural fractures interaction are investigated.« less

Microbial Interactions within a Cheese Microbial Community▿ †

PubMed Central

Mounier, Jérôme; Monnet, Christophe; Vallaeys, Tatiana; Arditi, Roger; Sarthou, Anne-Sophie; Hélias, Arnaud; Irlinger, Françoise

2008-01-01

The interactions that occur during the ripening of smear cheeses are not well understood. Yeast-yeast interactions and yeast-bacterium interactions were investigated within a microbial community composed of three yeasts and six bacteria found in cheese. The growth dynamics of this community was precisely described during the ripening of a model cheese, and the Lotka-Volterra model was used to evaluate species interactions. Subsequently, the effects on ecosystem functioning of yeast omissions in the microbial community were evaluated. It was found both in the Lotka-Volterra model and in the omission study that negative interactions occurred between yeasts. Yarrowia lipolytica inhibited mycelial expansion of Geotrichum candidum, whereas Y. lipolytica and G. candidum inhibited Debaryomyces hansenii cell viability during the stationary phase. However, the mechanisms involved in these interactions remain unclear. It was also shown that yeast-bacterium interactions played a significant role in the establishment of this multispecies ecosystem on the cheese surface. Yeasts were key species in bacterial development, but their influences on the bacteria differed. It appeared that the growth of Arthrobacter arilaitensis or Hafnia alvei relied less on a specific yeast function because these species dominated the bacterial flora, regardless of which yeasts were present in the ecosystem. For other bacteria, such as Leucobacter sp. or Brevibacterium aurantiacum, growth relied on a specific yeast, i.e., G. candidum. Furthermore, B. aurantiacum, Corynebacterium casei, and Staphylococcus xylosus showed reduced colonization capacities in comparison with the other bacteria in this model cheese. Bacterium-bacterium interactions could not be clearly identified. PMID:17981942

Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model.

PubMed

Gürsoy, Gamze; Xu, Yun; Liang, Jie

2017-07-01

Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.

SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803.

PubMed

Kim, Woo-Yeon; Kang, Sungsoo; Kim, Byoung-Chul; Oh, Jeehyun; Cho, Seongwoong; Bhak, Jong; Choi, Jong-Soon

2008-01-01

Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactions as well as their protein-level interactions using the model cyanobacterium, Synechocystis sp. PCC 6803. It predicts the protein-protein interactions using public interaction databases that contain mutually complementary and redundant data. Furthermore, SynechoNET provides information on transmembrane topology, signal peptide, and domain structure in order to support the analysis of regulatory membrane proteins. Such biological information can be queried and visualized in user-friendly web interfaces that include the interactive network viewer and search pages by keyword and functional category. SynechoNET is an integrated protein-protein interaction database designed to analyze regulatory membrane proteins in cyanobacteria. It provides a platform for biologists to extend the genomic data of cyanobacteria by predicting interaction partners, membrane association, and membrane topology of Synechocystis proteins. SynechoNET is freely available at http://synechocystis.org/ or directly at http://bioportal.kobic.kr/SynechoNET/.

Screen and clean: a tool for identifying interactions in genome-wide association studies.

PubMed

Wu, Jing; Devlin, Bernie; Ringquist, Steven; Trucco, Massimo; Roeder, Kathryn

2010-04-01

Epistasis could be an important source of risk for disease. How interacting loci might be discovered is an open question for genome-wide association studies (GWAS). Most researchers limit their statistical analyses to testing individual pairwise interactions (i.e., marginal tests for association). A more effective means of identifying important predictors is to fit models that include many predictors simultaneously (i.e., higher-dimensional models). We explore a procedure called screen and clean (SC) for identifying liability loci, including interactions, by using the lasso procedure, which is a model selection tool for high-dimensional regression. We approach the problem by using a varying dictionary consisting of terms to include in the model. In the first step the lasso dictionary includes only main effects. The most promising single-nucleotide polymorphisms (SNPs) are identified using a screening procedure. Next the lasso dictionary is adjusted to include these main effects and the corresponding interaction terms. Again, promising terms are identified using lasso screening. Then significant terms are identified through the cleaning process. Implementation of SC for GWAS requires algorithms to explore the complex model space induced by the many SNPs genotyped and their interactions. We propose and explore a set of algorithms and find that SC successfully controls Type I error while yielding good power to identify risk loci and their interactions. When the method is applied to data obtained from the Wellcome Trust Case Control Consortium study of Type 1 Diabetes it uncovers evidence supporting interaction within the HLA class II region as well as within Chromosome 12q24.

Reconstruction of interaction rate in holographic dark energy

NASA Astrophysics Data System (ADS)

Mukherjee, Ankan

2016-11-01

The present work is based on the holographic dark energy model with Hubble horizon as the infrared cut-off. The interaction rate between dark energy and dark matter has been reconstructed for three different parameterizations of the deceleration parameter. Observational constraints on the model parameters have been obtained by maximum likelihood analysis using the observational Hubble parameter data (OHD), type Ia supernovab data (SNe), baryon acoustic oscillation data (BAO) and the distance prior of cosmic microwave background (CMB) namely the CMB shift parameter data (CMBShift). The interaction rate obtained in the present work remains always positive and increases with expansion. It is very similar to the result obtained by Sen and Pavon [1] where the interaction rate has been reconstructed for a parametrization of the dark energy equation of state. Tighter constraints on the interaction rate have been obtained in the present work as it is based on larger data sets. The nature of the dark energy equation of state parameter has also been studied for the present models. Though the reconstruction is done from different parametrizations, the overall nature of the interaction rate is very similar in all the cases. Different information criteria and the Bayesian evidence, which have been invoked in the context of model selection, show that the these models are at close proximity of each other.

A phase field approach for multicellular aggregate fusion in biofabrication.

PubMed

Yang, Xiaofeng; Sun, Yi; Wang, Qi

2013-07-01

We present a modeling and computational approach to study fusion of multicellular aggregates during tissue and organ fabrication, which forms the foundation for the scaffold-less biofabrication of tissues and organs known as bioprinting. It is known as the phase field method, where multicellular aggregates are modeled as mixtures of multiphase complex fluids whose phase mixing or separation is governed by interphase force interactions, mimicking the cell-cell interaction in the multicellular aggregates, and intermediate range interaction mediated by the surrounding hydrogel. The material transport in the mixture is dictated by hydrodynamics as well as forces due to the interphase interactions. In a multicellular aggregate system with fixed number of cells and fixed amount of the hydrogel medium, the effect of cell differentiation, proliferation, and death are neglected in the current model, which can be readily included in the model, and the interaction between different components is dictated by the interaction energy between cell and cell as well as between cell and medium particles, respectively. The modeling approach is applicable to transient simulations of fusion of cellular aggregate systems at the time and length scale appropriate to biofabrication. Numerical experiments are presented to demonstrate fusion and cell sorting during tissue and organ maturation processes in biofabrication.

Phase transitions and thermodynamic properties of antiferromagnetic Ising model with next-nearest-neighbor interactions on the Kagomé lattice

NASA Astrophysics Data System (ADS)

Ramazanov, M. K.; Murtazaev, A. K.; Magomedov, M. A.; Badiev, M. K.

2018-06-01

We study phase transitions and thermodynamic properties in the two-dimensional antiferromagnetic Ising model with next-nearest-neighbor interaction on a Kagomé lattice by Monte Carlo simulations. A histogram data analysis shows that a second-order transition occurs in the model. From the analysis of obtained data, we can assume that next-nearest-neighbor ferromagnetic interactions in two-dimensional antiferromagnetic Ising model on a Kagomé lattice excite the occurrence of a second-order transition and unusual behavior of thermodynamic properties on the temperature dependence.

Chiral helimagnetic state in a Kondo lattice model with the Dzyaloshinskii-Moriya interaction

NASA Astrophysics Data System (ADS)

Okumura, Shun; Kato, Yasuyuki; Motome, Yukitoshi

2018-05-01

Monoaxial chiral magnets can form a noncollinear twisted spin structure called the chiral helimagnetic state. We study magnetic properties of such a chiral helimagnetic state, with emphasis on the effect of itinerant electrons. Modeling a monoaxial chiral helimagnet by a one-dimensional Kondo lattice model with the Dzyaloshinskii-Moriya interaction, we perform a variational calculation to elucidate the stable spin configuration in the ground state. We obtain a chiral helimagnetic state as a candidate for the ground state, whose helical pitch is modulated by the model parameters: the Kondo coupling, the Dzyaloshinski-Moriya interaction, and electron filling.

Solution to the sign problem in a frustrated quantum impurity model

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

Hann, Connor T., E-mail: connor.hann@yale.edu; Huffman, Emilie; Chandrasekharan, Shailesh

2017-01-15

In this work we solve the sign problem of a frustrated quantum impurity model consisting of three quantum spin-half chains interacting through an anti-ferromagnetic Heisenberg interaction at one end. We first map the model into a repulsive Hubbard model of spin-half fermions hopping on three independent one dimensional chains that interact through a triangular hopping at one end. We then convert the fermion model into an inhomogeneous one dimensional model and express the partition function as a weighted sum over fermion worldline configurations. By imposing a pairing of fermion worldlines in half the space we show that all negative weightmore » configurations can be eliminated. This pairing naturally leads to the original frustrated quantum spin model at half filling and thus solves its sign problem.« less

Effects of air-sea interaction on extended-range prediction of geopotential height at 500 hPa over the northern extratropical region

NASA Astrophysics Data System (ADS)

Wang, Xujia; Zheng, Zhihai; Feng, Guolin

2018-04-01

The contribution of air-sea interaction on the extended-range prediction of geopotential height at 500 hPa in the northern extratropical region has been analyzed with a coupled model form Beijing Climate Center and its atmospheric components. Under the assumption of the perfect model, the extended-range prediction skill was evaluated by anomaly correlation coefficient (ACC), root mean square error (RMSE), and signal-to-noise ratio (SNR). The coupled model has a better prediction skill than its atmospheric model, especially, the air-sea interaction in July made a greater contribution for the improvement of prediction skill than other months. The prediction skill of the extratropical region in the coupled model reaches 16-18 days in all months, while the atmospheric model reaches 10-11 days in January, April, and July and only 7-8 days in October, indicating that the air-sea interaction can extend the prediction skill of the atmospheric model by about 1 week. The errors of both the coupled model and the atmospheric model reach saturation in about 20 days, suggesting that the predictable range is less than 3 weeks.

Creating and Using Interactive, 3D-Printed Models to Improve Student Comprehension of the Bohr Model of the Atom, Bond Polarity, and Hybridization

ERIC Educational Resources Information Center

Smiar, Karen; Mendez, J. D.

2016-01-01

Molecular model kits have been used in chemistry classrooms for decades but have seen very little recent innovation. Using 3D printing, three sets of physical models were created for a first semester, introductory chemistry course. Students manipulated these interactive models during class activities as a supplement to existing teaching tools for…

Seldon v.3.0

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

Berry, Nina; Ko, Teresa; Shneider, Max

Seldon is an agent-based social simulation framework that uniquely integrates concepts from a variety of different research areas including psychology, social science, and agent-based modeling. Development has been taking place for a number of years, previously focusing on gang and terrorist recruitment. The toolkit consists of simple agents (individuals) and abstract agents (groups of individuals representing social/institutional concepts) that interact according to exchangeable rule sets (i.e. linear attraction, linear reinforcement). Each agent has a set of customizable attributes that get modified during the interactions. Interactions create relationships between agents, and each agent has a maximum amount of relationship energy thatmore » it can expend. As relationships evolve, they form multiple levels of social networks (i.e. acquaintances, friends, cliques) that in turn drive future interactions. Agents can also interact randomly if they are not connected through a network, mimicking the chance interactions that real people have in everyday life. We are currently integrating Seldon with the cognitive framework (also developed at Sandia). Each individual agent has a lightweight cognitive model that is created automatically from textual sources. Cognitive information is exchanged during interactions, and can also be injected into a running simulation. The entire framework has been parallelized to allow for larger simulations in an HPC environment. We have also added more detail to the agents themselves (a"Big Five" personality model) and their interactions (an enhanced relationship model) for a more realistic representation.« less

77 FR 70941 - Special Conditions: Embraer S.A., Model EMB-550 Airplane; Interaction of Systems and Structures

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-28

... primary structure is metal with composite empennage and control surfaces. The Model EMB-550 airplane is...., Model EMB-550 Airplane; Interaction of Systems and Structures AGENCY: Federal Aviation Administration... conditions for the Embraer S.A. Model EMB-550 airplane. This airplane will have a novel or unusual design...

Spatial Interactions in Multiple-Use Forestry and Substitution and Wealth Effects for the Single Stand

Treesearch

Stephen K. Swallow; David N. Wear

1993-01-01

Forestry models often ignore spatial relationships between forest stands. This paper isolates the effects of stand interactions in muitiple-use forestry through a straightforward extension of the single-stand model. Effects of stand interactions decompose into wealth and substitution effects and may cause time-varying patterns of resource use for a forest...

Testing for Two-Way Interactions in the Multigroup Common Factor Model

ERIC Educational Resources Information Center

van Smeden, Maarten; Hessen, David J.

2013-01-01

In this article, a 2-way multigroup common factor model (MG-CFM) is presented. The MG-CFM can be used to estimate interaction effects between 2 grouping variables on 1 or more hypothesized latent variables. For testing the significance of such interactions, a likelihood ratio test is presented. In a simulation study, the robustness of the…

Using the Graded Response Model to Control Spurious Interactions in Moderated Multiple Regression

ERIC Educational Resources Information Center

Morse, Brendan J.; Johanson, George A.; Griffeth, Rodger W.

2012-01-01

Recent simulation research has demonstrated that using simple raw score to operationalize a latent construct can result in inflated Type I error rates for the interaction term of a moderated statistical model when the interaction (or lack thereof) is proposed at the latent variable level. Rescaling the scores using an appropriate item response…

Description of alpha-nucleus interaction cross sections for cosmic ray shielding studies

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Townsend, Lawrence W.; Wilson, John W.

1993-01-01

Nuclear interactions of high-energy alpha particles with target nuclei important for cosmic ray studies are discussed. Models for elastic, quasi-elastic, and breakup reactions are presented and compared with experimental data. Energy-dependent interaction cross sections and secondary spectra are presented based on theoretical models and the limited experimental data base.

Catching fire? Social interactions, beliefs, and wildfire risk mitigation behaviors

Treesearch

Katherine Dickinson; Hannah Brenkert-Smith; Patricia Champ; Nicholas Flores

2015-01-01

Social interactions are widely recognized as a potential influence on risk-related behaviors. We present a mediation model in which social interactions (classified as formal/informal and generic-fire-specific) are associated with beliefs about wildfire risk and mitigation options, which in turn shape wildfire mitigation behaviors. We test this model using survey data...

On-Line Course Curricula and Interactional Strategies: The Foundations and Extensions to Adult e-Learning Communities

ERIC Educational Resources Information Center

Chaves, Christopher A.

2009-01-01

The purpose of this article is to provide researchers and, in particular, practitioner-scholars of e-learning curricular designs and instructors with one conceptual model that supports more involvement and interaction within on-line courses. The "On-line Curriculum Interaction Model" posited by the author is informed by the foundational…

Three Cultural Models of Teacher Interaction Valued by Mexican Students at a US High School

ERIC Educational Resources Information Center

Andrews, Micah

2016-01-01

Using students' interviews as data source, this study explores the interactional experiences of several Mexican students at a US high school in the Midwest with their teachers and discusses how three cultural models of teacher interaction valued by the students impact their affiliation, motivation, and engagement with school. Emphasis is given to…

Self-consistent Models of Strong Interaction with Chiral Symmetry

DOE R&D Accomplishments Database

Nambu, Y.; Pascual, P.

1963-04-01

Some simple models of (renormalizable) meson-nucleon interaction are examined in which the nucleon mass is entirely due to interaction and the chiral ( gamma {sub 5}) symmetry is "broken'' to become a hidden symmetry. It is found that such a scheme is possible provided that a vector meson is introduced as an elementary field. (auth)

Lieb-Thirring inequality for a model of particles with point interactions

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

Frank, Rupert L.; Seiringer, Robert

2012-09-15

We consider a model of quantum-mechanical particles interacting via point interactions of infinite scattering length. In the case of fermions we prove a Lieb-Thirring inequality for the energy, i.e., we show that the energy is bounded from below by a constant times the integral of the particle density to the power (5/3).

Event reweighting with the NuWro neutrino interaction generator

NASA Astrophysics Data System (ADS)

Pickering, Luke; Stowell, Patrick; Sobczyk, Jan

2017-09-01

Event reweighting has been implemented in the NuWro neutrino event generator for a number of free theory parameters in the interaction model. Event reweighting is a key analysis technique, used to efficiently study the effect of neutrino interaction model uncertainties. This opens up the possibility for NuWro to be used as a primary event generator by experimental analysis groups. A preliminary model tuning to ANL and BNL data of quasi-elastic and single pion production events was performed to validate the reweighting engine.

Evaluation of HardSys/HardDraw, An Expert System for Electromagnetic Interactions Modelling

DTIC Science & Technology

1993-05-01

interactions ir complex systems. This report gives a description of HardSys/HardDraw and reviews the main concepts used in its design. Various aspects of its ...HardDraw, an expert system for the modelling of electromagnetic interactions in complex systems. It consists of two main components: HardSys and HardDraw...HardSys is the advisor part of the expert system. It is knowledge-based, that is it contains a database of models and properties for various types of

CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2015-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

Fluctuating hyperfine interactions: an updated computational implementation

NASA Astrophysics Data System (ADS)

Zacate, M. O.; Evenson, W. E.

2015-04-01

The stochastic hyperfine interactions modeling library (SHIML) is a set of routines written in the C programming language designed to assist in the analysis of stochastic models of hyperfine interactions. The routines read a text-file description of the model, set up the Blume matrix, upon which the evolution operator of the quantum mechanical system depends, and calculate the eigenvalues and eigenvectors of the Blume matrix, from which theoretical spectra of experimental techniques can be calculated. The original version of SHIML constructs Blume matrices applicable for methods that measure hyperfine interactions with only a single nuclear spin state. In this paper, we report an extension of the library to provide support for methods such as Mössbauer spectroscopy and nuclear resonant scattering of synchrotron radiation, which are sensitive to interactions with two nuclear spin states. Examples will be presented that illustrate the use of this extension of SHIML to generate Mössbauer spectra for polycrystalline samples under a number of fluctuating hyperfine field models.

Functional mapping of reaction norms to multiple environmental signals through nonparametric covariance estimation

PubMed Central

2011-01-01

Background The identification of genes or quantitative trait loci that are expressed in response to different environmental factors such as temperature and light, through functional mapping, critically relies on precise modeling of the covariance structure. Previous work used separable parametric covariance structures, such as a Kronecker product of autoregressive one [AR(1)] matrices, that do not account for interaction effects of different environmental factors. Results We implement a more robust nonparametric covariance estimator to model these interactions within the framework of functional mapping of reaction norms to two signals. Our results from Monte Carlo simulations show that this estimator can be useful in modeling interactions that exist between two environmental signals. The interactions are simulated using nonseparable covariance models with spatio-temporal structural forms that mimic interaction effects. Conclusions The nonparametric covariance estimator has an advantage over separable parametric covariance estimators in the detection of QTL location, thus extending the breadth of use of functional mapping in practical settings. PMID:21269481

Kinetic Framework for the Magnetosphere-Ionosphere-Plasmasphere-Polar Wind System: Modeling Ion Outflow

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Barakat, A. R.; Eccles, V.; Karimabadi, H.; Omelchenko, Y.; Khazanov, G. V.; Glocer, A.; Kistler, L. M.

2014-12-01

A Kinetic Framework for the Magnetosphere-Ionosphere-Plasmasphere-Polar Wind System is being developed in order to provide a rigorous approach to modeling the interaction of hot and cold particle interactions. The framework will include ion and electron kinetic species in the ionosphere, plasmasphere and polar wind, and kinetic ion, super-thermal electron and fluid electron species in the magnetosphere. The framework is ideally suited to modeling ion outflow from the ionosphere and plasmasphere, where a wide range for fluid and kinetic processes are important. These include escaping ion interactions with (1) photoelectrons, (2) cusp/auroral waves, double layers, and field-aligned currents, (3) double layers in the polar cap due to the interaction of cold ionospheric and hot magnetospheric electrons, (4) counter-streaming ions, and (5) electromagnetic wave turbulence. The kinetic ion interactions are particularly strong during geomagnetic storms and substorms. The presentation will provide a brief description of the models involved and discuss the effect that kinetic processes have on the ion outflow.

Maximally informative pairwise interactions in networks

PubMed Central

Fitzgerald, Jeffrey D.; Sharpee, Tatyana O.

2010-01-01

Several types of biological networks have recently been shown to be accurately described by a maximum entropy model with pairwise interactions, also known as the Ising model. Here we present an approach for finding the optimal mappings between input signals and network states that allow the network to convey the maximal information about input signals drawn from a given distribution. This mapping also produces a set of linear equations for calculating the optimal Ising-model coupling constants, as well as geometric properties that indicate the applicability of the pairwise Ising model. We show that the optimal pairwise interactions are on average zero for Gaussian and uniformly distributed inputs, whereas they are nonzero for inputs approximating those in natural environments. These nonzero network interactions are predicted to increase in strength as the noise in the response functions of each network node increases. This approach also suggests ways for how interactions with unmeasured parts of the network can be inferred from the parameters of response functions for the measured network nodes. PMID:19905153

Biophysical interactions between plant and soil: theory and practice

NASA Astrophysics Data System (ADS)

van der Ploeg, Martine

2016-04-01

Vegetation plays an essential role in the hydrological cycle, as it regulates the water flux to the atmosphere through evapotranspiration, while it is dependent on adequate water supply. Vegetation shapes the land surface by changing infiltration characteristics as a result of root growth, and controls soil moisture storage, which in turn affect runoff characteristics and groundwater recharge. Vegetation and the underlying geology are in constant interaction, wherein water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. Models are a useful tool to explore interaction and feedbacks between vegetation, soil and landscape. Plants respond biochemically to their environment, while the models used for hydrology are often based on physical interactions. Gene-expression and genotype adaptation may complicate our modelling efforts in for example climate change impacts. Combination of new techniques to assess soil and plant properties facilitates assessment of biophysical interactions. This poster will review these techniques and compare the obtained insights of soil-plant relationships with the current modeling approaches.

Experimental Models to Study the Role of Microbes in Host-Parasite Interactions.

PubMed

Hahn, Megan A; Dheilly, Nolwenn M

2016-01-01

Until recently, parasitic infections have been primarily studied as interactions between the parasite and the host, leaving out crucial players: microbes. The recent realization that microbes play key roles in the biology of all living organisms is not only challenging our understanding of host-parasite evolution, but it also provides new clues to develop new therapies and remediation strategies. In this paper we provide a review of promising and advanced experimental organismal systems to examine the dynamic of host-parasite-microbe interactions. We address the benefits of developing new experimental models appropriate to this new research area and identify systems that offer the best promises considering the nature of the interactions among hosts, parasites, and microbes. Based on these systems, we identify key criteria for selecting experimental models to elucidate the fundamental principles of these complex webs of interactions. It appears that no model is ideal and that complementary studies should be performed on different systems in order to understand the driving roles of microbes in host and parasite evolution.

A novel Arg H52/Tyr H33 conservative motif in antibodies: A correlation between sequence of antibodies and antigen binding.

PubMed

Petrov, Artem; Arzhanik, Vladimir; Makarov, Gennady; Koliasnikov, Oleg

2016-08-01

Antibodies are the family of proteins, which are responsible for antigen recognition. The computational modeling of interaction between an antigen and an antibody is very important when crystallographic structure is unavailable. In this research, we have discovered the correlation between the amino acid sequence of antibody and its specific binding characteristics on the example of the novel conservative binding motif, which consists of four residues: Arg H52, Tyr H33, Thr H59, and Glu H61. These residues are specifically oriented in the binding site and interact with each other in a specific manner. The residues of the binding motif are involved in interaction strictly with negatively charged groups of antigens, and form a binding complex. Mechanism of interaction and characteristics of the complex were also discovered. The results of this research can be used to increase the accuracy of computational antibody-antigen interaction modeling and for post-modeling quality control of the modeled structures.