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…

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.

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.

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...

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…

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.

Consequences of stage-structured predators: cannibalism, behavioral effects, and trophic cascades.

PubMed

Rudolf, Volker H W

2007-12-01

Cannibalistic and asymmetrical behavioral interactions between stages are common within stage-structured predator populations. Such direct interactions between predator stages can result in density- and trait-mediated indirect interactions between a predator and its prey. A set of structured predator-prey models is used to explore how such indirect interactions affect the dynamics and structure of communities. Analyses of the separate and combined effects of stage-structured cannibalism and behavior-mediated avoidance of cannibals under different ecological scenarios show that both cannibalism and behavioral avoidance of cannibalism can result in short- and long-term positive indirect connections between predator stages and the prey, including "apparent mutualism." These positive interactions alter the strength of trophic cascades such that the system's dynamics are determined by the interaction between bottom-up and top-down effects. Contrary to the expectation of simpler models, enrichment increases both predator and prey abundance in systems with cannibalism or behavioral avoidance of cannibalism. The effect of behavioral avoidance of cannibalism, however, depends on how strongly it affects the maturation rate of the predator. Behavioral interactions between predator stages reduce the short-term positive effect of cannibalism on the prey density, but can enhance its positive long-term effects. Both interaction types reduce the destabilizing effect of enrichment. These results suggest that inconsistencies between data and simple models can be resolved by accounting for stage-structured interactions within and among species.

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…

Statistical modeling of compressible turbulence - Shock-wave/turbulence interactions and buoyancy effects

NASA Astrophysics Data System (ADS)

Yoshizawa, Akira

1991-12-01

A mass-weighted mean compressible turbulence model is presented with the aid of the results from a two-scale DIA. This model aims at dealing with two typical aspects in compressible flows: the interaction of a shock wave with turbulence in high-speed flows and strong buoyancy effects in thermally-driven flows as in stellar convection and conflagration. The former is taken into account through the effect of turbulent dilatation that is related to the density fluctuation and leads to the enhanced kinetic-energy dissipation. The latter is incorporated through the interaction between the gravitational and density-fluctuation effects.

Evaluating differential effects using regression interactions and regression mixture models

PubMed Central

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 paper focuses on understanding regression mixture models, a 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 formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The paper aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design. PMID:26556903

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.

Interactions among resource partitioning, sampling effect, and facilitation on the biodiversity effect: a modeling approach.

PubMed

Flombaum, Pedro; Sala, Osvaldo E; Rastetter, Edward B

2014-02-01

Resource partitioning, facilitation, and sampling effect are the three mechanisms behind the biodiversity effect, which is depicted usually as the effect of plant-species richness on aboveground net primary production. These mechanisms operate simultaneously but their relative importance and interactions are difficult to unravel experimentally. Thus, niche differentiation and facilitation have been lumped together and separated from the sampling effect. Here, we propose three hypotheses about interactions among the three mechanisms and test them using a simulation model. The model simulated water movement through soil and vegetation, and net primary production mimicking the Patagonian steppe. Using the model, we created grass and shrub monocultures and mixtures, controlled root overlap and grass water-use efficiency (WUE) to simulate gradients of biodiversity, resource partitioning and facilitation. The presence of shrubs facilitated grass growth by increasing its WUE and in turn increased the sampling effect, whereas root overlap (resource partitioning) had, on average, no effect on sampling effect. Interestingly, resource partitioning and facilitation interacted so the effect of facilitation on sampling effect decreased as resource partitioning increased. Sampling effect was enhanced by the difference between the two functional groups in their efficiency in using resources. Morphological and physiological differences make one group outperform the other; once these differences were established further differences did not enhance the sampling effect. In addition, grass WUE and root overlap positively influence the biodiversity effect but showed no interactions.

Predicting interactions among fishing, ocean warming, and ocean acidification in a marine system with whole-ecosystem models.

PubMed

Griffith, Gary P; Fulton, Elizabeth A; Gorton, Rebecca; Richardson, Anthony J

2012-12-01

An important challenge for conservation is a quantitative understanding of how multiple human stressors will interact to mitigate or exacerbate global environmental change at a community or ecosystem level. We explored the interaction effects of fishing, ocean warming, and ocean acidification over time on 60 functional groups of species in the southeastern Australian marine ecosystem. We tracked changes in relative biomass within a coupled dynamic whole-ecosystem modeling framework that included the biophysical system, human effects, socioeconomics, and management evaluation. We estimated the individual, additive, and interactive effects on the ecosystem and for five community groups (top predators, fishes, benthic invertebrates, plankton, and primary producers). We calculated the size and direction of interaction effects with an additive null model and interpreted results as synergistic (amplified stress), additive (no additional stress), or antagonistic (reduced stress). Individually, only ocean acidification had a negative effect on total biomass. Fishing and ocean warming and ocean warming with ocean acidification had an additive effect on biomass. Adding fishing to ocean warming and ocean acidification significantly changed the direction and magnitude of the interaction effect to a synergistic response on biomass. The interaction effect depended on the response level examined (ecosystem vs. community). For communities, the size, direction, and type of interaction effect varied depending on the combination of stressors. Top predator and fish biomass had a synergistic response to the interaction of all three stressors, whereas biomass of benthic invertebrates responded antagonistically. With our approach, we were able to identify the regional effects of fishing on the size and direction of the interacting effects of ocean warming and ocean acidification. ©2012 Society for Conservation Biology.

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.

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

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.

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.

A Bayesian Model for the Estimation of Latent Interaction and Quadratic Effects When Latent Variables Are Non-Normally Distributed

ERIC Educational Resources Information Center

Kelava, Augustin; Nagengast, Benjamin

2012-01-01

Structural equation models with interaction and quadratic effects have become a standard tool for testing nonlinear hypotheses in the social sciences. Most of the current approaches assume normally distributed latent predictor variables. In this article, we present a Bayesian model for the estimation of latent nonlinear effects when the latent…

Interactive Sound Propagation using Precomputation and Statistical Approximations

NASA Astrophysics Data System (ADS)

Antani, Lakulish

Acoustic phenomena such as early reflections, diffraction, and reverberation have been shown to improve the user experience in interactive virtual environments and video games. These effects arise due to repeated interactions between sound waves and objects in the environment. In interactive applications, these effects must be simulated within a prescribed time budget. We present two complementary approaches for computing such acoustic effects in real time, with plausible variation in the sound field throughout the scene. The first approach, Precomputed Acoustic Radiance Transfer, precomputes a matrix that accounts for multiple acoustic interactions between all scene objects. The matrix is used at run time to provide sound propagation effects that vary smoothly as sources and listeners move. The second approach couples two techniques---Ambient Reverberance, and Aural Proxies---to provide approximate sound propagation effects in real time, based on only the portion of the environment immediately visible to the listener. These approaches lie at different ends of a space of interactive sound propagation techniques for modeling sound propagation effects in interactive applications. The first approach emphasizes accuracy by modeling acoustic interactions between all parts of the scene; the second approach emphasizes efficiency by only taking the local environment of the listener into account. These methods have been used to efficiently generate acoustic walkthroughs of architectural models. They have also been integrated into a modern game engine, and can enable realistic, interactive sound propagation on commodity desktop PCs.

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

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.

Mean-field velocity difference model considering the average effect of multi-vehicle interaction

NASA Astrophysics Data System (ADS)

Guo, Yan; Xue, Yu; Shi, Yin; Wei, Fang-ping; Lü, Liang-zhong; He, Hong-di

2018-06-01

In this paper, a mean-field velocity difference model(MFVD) is proposed to describe the average effect of multi-vehicle interactions on the whole road. By stability analysis, the stability condition of traffic system is obtained. Comparison with stability of full velocity-difference (FVD) model and the completeness of MFVD model are discussed. The mKdV equation is derived from MFVD model through nonlinear analysis to reveal the traffic jams in the form of the kink-antikink density wave. Then the numerical simulation is performed and the results illustrate that the average effect of multi-vehicle interactions plays an important role in effectively suppressing traffic jam. The increase strength of the mean-field velocity difference in MFVD model can rapidly reduce traffic jam and enhance the stability of traffic system.

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.

Does raising type 1 error rate improve power to detect interactions in linear regression models? A simulation study.

PubMed

Durand, Casey P

2013-01-01

Statistical interactions are a common component of data analysis across a broad range of scientific disciplines. However, the statistical power to detect interactions is often undesirably low. One solution is to elevate the Type 1 error rate so that important interactions are not missed in a low power situation. To date, no study has quantified the effects of this practice on power in a linear regression model. A Monte Carlo simulation study was performed. A continuous dependent variable was specified, along with three types of interactions: continuous variable by continuous variable; continuous by dichotomous; and dichotomous by dichotomous. For each of the three scenarios, the interaction effect sizes, sample sizes, and Type 1 error rate were varied, resulting in a total of 240 unique simulations. In general, power to detect the interaction effect was either so low or so high at α = 0.05 that raising the Type 1 error rate only served to increase the probability of including a spurious interaction in the model. A small number of scenarios were identified in which an elevated Type 1 error rate may be justified. Routinely elevating Type 1 error rate when testing interaction effects is not an advisable practice. Researchers are best served by positing interaction effects a priori and accounting for them when conducting sample size calculations.

Results of test MA22 in the NASA/LaRC 31-inch CFHT on an 0.010-scale model (32-0) of the space shuttle configuration 3 to determine RCS jet flow field interaction, volume 1. [wind tunnel tests for interactions of aerodynamic heating on jet flow

NASA Technical Reports Server (NTRS)

Kanipe, D. B.

1976-01-01

A wind tunnel test was conducted in the Langley Research Center 31-inch Continuous Flow Hypersonic Wind Tunnel from May 6, 1975 through June 3, 1975. The primary objectives of this test were the following: (1) to study the ability of the wind tunnel to repeat, on a run-to-run basis, data taken for identical configurations to determine if errors in repeatability could have a significant effect on jet interaction data, (2) to determine the effect of aerodynamic heating of the scale model on jet interaction, (3) to investigate the effects of elevon and body flap deflections on jet interaction, (4) to determine if the effects from jets fired separately along different axes can be added to equal the effects of the jets fired simultaneously (super position effects), (5) to study multiple jet effects, and (6) to investigate area ratio effects, i.e., the effect on jet interaction measurements of using wind tunnel nozzles with different area ratios in the same location. The model used in the test was a .010-scale model of the Space Shuttle Orbiter Configuration 3. The test was conducted at Mach 10.3 and a dynamic pressure of 150 psf. RCS chamber pressure was varied to simulate free flight dynamic pressures of 5, 7.5, 10, and 20 psf.

Deriving the nuclear shell model from first principles

NASA Astrophysics Data System (ADS)

Barrett, Bruce R.; Dikmen, Erdal; Vary, James P.; Maris, Pieter; Shirokov, Andrey M.; Lisetskiy, Alexander F.

2014-09-01

The results of an 18-nucleon No Core Shell Model calculation, performed in a large basis space using a bare, soft NN interaction, can be projected into the 0 ℏω space, i.e., the sd -shell. Because the 16 nucleons in the 16O core are frozen in the 0 ℏω space, all the correlations of the 18-nucleon system are captured by the two valence, sd -shell nucleons. By the projection, we obtain microscopically the sd -shell 2-body effective interactions, the core energy and the sd -shell s.p. energies. Thus, the input for standard shell-model calculations can be determined microscopically by this approach. If the same procedure is then applied to 19-nucleon systems, the sd -shell 3-body effective interactions can also be obtained, indicating the importance of these 3-body effective interactions relative to the 2-body effective interactions. Applications to A = 19 and heavier nuclei with different intrinsic NN interactions will be presented and discussed. The results of an 18-nucleon No Core Shell Model calculation, performed in a large basis space using a bare, soft NN interaction, can be projected into the 0 ℏω space, i.e., the sd -shell. Because the 16 nucleons in the 16O core are frozen in the 0 ℏω space, all the correlations of the 18-nucleon system are captured by the two valence, sd -shell nucleons. By the projection, we obtain microscopically the sd -shell 2-body effective interactions, the core energy and the sd -shell s.p. energies. Thus, the input for standard shell-model calculations can be determined microscopically by this approach. If the same procedure is then applied to 19-nucleon systems, the sd -shell 3-body effective interactions can also be obtained, indicating the importance of these 3-body effective interactions relative to the 2-body effective interactions. Applications to A = 19 and heavier nuclei with different intrinsic NN interactions will be presented and discussed. Supported by the US NSF under Grant No. 0854912, the US DOE under Grants Nos. DESC0008485 and DE-FG02-87ER40371, the Higher Education Council of Turkey(YOK), and the Ministry of Education and Science of Russian Fed. under contracts P521 and 14.v37.21.1297.

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.

[Analytic methods for seed models with genotype x environment interactions].

PubMed

Zhu, J

1996-01-01

Genetic models with genotype effect (G) and genotype x environment interaction effect (GE) are proposed for analyzing generation means of seed quantitative traits in crops. The total genetic effect (G) is partitioned into seed direct genetic effect (G0), cytoplasm genetic of effect (C), and maternal plant genetic effect (Gm). Seed direct genetic effect (G0) can be further partitioned into direct additive (A) and direct dominance (D) genetic components. Maternal genetic effect (Gm) can also be partitioned into maternal additive (Am) and maternal dominance (Dm) genetic components. The total genotype x environment interaction effect (GE) can also be partitioned into direct genetic by environment interaction effect (G0E), cytoplasm genetic by environment interaction effect (CE), and maternal genetic by environment interaction effect (GmE). G0E can be partitioned into direct additive by environment interaction (AE) and direct dominance by environment interaction (DE) genetic components. GmE can also be partitioned into maternal additive by environment interaction (AmE) and maternal dominance by environment interaction (DmE) genetic components. Partitions of genetic components are listed for parent, F1, F2 and backcrosses. A set of parents, their reciprocal F1 and F2 seeds is applicable for efficient analysis of seed quantitative traits. MINQUE(0/1) method can be used for estimating variance and covariance components. Unbiased estimation for covariance components between two traits can also be obtained by the MINQUE(0/1) method. Random genetic effects in seed models are predictable by the Adjusted Unbiased Prediction (AUP) approach with MINQUE(0/1) method. The jackknife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects, which can be further used in a t-test for parameter. Unbiasedness and efficiency for estimating variance components and predicting genetic effects are tested by Monte Carlo simulations.

More Precise Estimation of Lower-Level Interaction Effects in Multilevel Models.

PubMed

Loeys, Tom; Josephy, Haeike; Dewitte, Marieke

2018-01-01

In hierarchical data, the effect of a lower-level predictor on a lower-level outcome may often be confounded by an (un)measured upper-level factor. When such confounding is left unaddressed, the effect of the lower-level predictor is estimated with bias. Separating this effect into a within- and between-component removes such bias in a linear random intercept model under a specific set of assumptions for the confounder. When the effect of the lower-level predictor is additionally moderated by another lower-level predictor, an interaction between both lower-level predictors is included into the model. To address unmeasured upper-level confounding, this interaction term ought to be decomposed into a within- and between-component as well. This can be achieved by first multiplying both predictors and centering that product term next, or vice versa. We show that while both approaches, on average, yield the same estimates of the interaction effect in linear models, the former decomposition is much more precise and robust against misspecification of the effects of cross-level and upper-level terms, compared to the latter.

Effects of macromolecular crowding on biochemical reaction equilibria: a molecular thermodynamic perspective.

PubMed

Hu, Zhongqiao; Jiang, Jianwen; Rajagopalan, Raj

2007-09-01

A molecular thermodynamic model is developed to investigate the effects of macromolecular crowding on biochemical reactions. Three types of reactions, representing protein folding/conformational isomerization, coagulation/coalescence, and polymerization/association, are considered. The reactants, products, and crowders are modeled as coarse-grained spherical particles or as polymer chains, interacting through hard-sphere interactions with or without nonbonded square-well interactions, and the effects of crowder size and chain length as well as product size are examined. The results predicted by this model are consistent with experimentally observed crowding effects based on preferential binding or preferential exclusion of the crowders. Although simple hard-core excluded-volume arguments do in general predict the qualitative aspects of the crowding effects, the results show that other intermolecular interactions can substantially alter the extent of enhancement or reduction of the equilibrium and can even change the direction of the shift. An advantage of the approach presented here is that competing reactions can be incorporated within the model.

A genome-wide survey of transgenerational genetic effects in autism.

PubMed

Tsang, Kathryn M; Croen, Lisa A; Torres, Anthony R; Kharrazi, Martin; Delorenze, Gerald N; Windham, Gayle C; Yoshida, Cathleen K; Zerbo, Ousseny; Weiss, Lauren A

2013-01-01

Effects of parental genotype or parent-offspring genetic interaction are well established in model organisms for a variety of traits. However, these transgenerational genetic models are rarely studied in humans. We have utilized an autism case-control study with 735 mother-child pairs to perform genome-wide screening for maternal genetic effects and maternal-offspring genetic interaction. We used simple models of single locus parent-child interaction and identified suggestive results (P<10(-4)) that cannot be explained by main effects, but no genome-wide significant signals. Some of these maternal and maternal-child associations were in or adjacent to autism candidate genes including: PCDH9, FOXP1, GABRB3, NRXN1, RELN, MACROD2, FHIT, RORA, CNTN4, CNTNAP2, FAM135B, LAMA1, NFIA, NLGN4X, RAPGEF4, and SDK1. We attempted validation of potential autism association under maternal-specific models using maternal-paternal comparison in family-based GWAS datasets. Our results suggest that further study of parental genetic effects and parent-child interaction in autism is warranted.

Order Effects of Learning with Modeling and Simulation Software on Field-Dependent and Field-Independent Children's Cognitive Performance: An Interaction Effect

ERIC Educational Resources Information Center

Angeli, Charoula; Valanides, Nicos; Polemitou, Eirini; Fraggoulidou, Elena

2014-01-01

The study examined the interaction between field dependence-independence (FD/I) and learning with modeling software and simulations, and their effect on children's performance. Participants were randomly assigned into two groups. Group A first learned with a modeling tool and then with simulations. Group B learned first with simulations and then…

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.

Identifying key sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2013-09-01

This study investigates sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment, through the use of local and global sensitivity analysis tools, and contributes to an in-depth understanding of wastewater treatment modelling by revealing critical parameters and parameter interactions. One-factor-at-a-time sensitivity analysis is used to screen model parameters and identify those with significant individual effects on three performance indicators: total greenhouse gas emissions, effluent quality and operational cost. Sobol's method enables identification of parameters with significant higher order effects and of particular parameter pairs to which model outputs are sensitive. Use of a variance-based global sensitivity analysis tool to investigate parameter interactions enables identification of important parameters not revealed in one-factor-at-a-time sensitivity analysis. These interaction effects have not been considered in previous studies and thus provide a better understanding wastewater treatment plant model characterisation. It was found that uncertainty in modelled nitrous oxide emissions is the primary contributor to uncertainty in total greenhouse gas emissions, due largely to the interaction effects of three nitrogen conversion modelling parameters. The higher order effects of these parameters are also shown to be a key source of uncertainty in effluent quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

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 %.

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.

Three-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data.

PubMed

Frank, Till D; Kiyatkin, Anatoly; Cheong, Alex; Kholodenko, Boris N

2017-06-01

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Meson exchange current (MEC) models in neutrino interaction generators

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

Katori, Teppei

2015-05-15

Understanding of the so-called 2 particle-2 hole (2p-2h) effect is an urgent program in neutrino interaction physics for current and future oscillation experiments. Such processes are believed to be responsible for the event excesses observed by recent neutrino experiments. The 2p-2h effect is dominated by the meson exchange current (MEC), and is accompanied by a 2-nucleon emission from the primary vertex, instead of a single nucleon emission from the charged-current quasi-elastic (CCQE) interaction. Current and future high resolution experiments can potentially nail down this effect. For this reason, there are world wide efforts to model and implement this process inmore » neutrino interaction simulations. In these proceedings, I would like to describe how this channel is modeled in neutrino interaction generators.« less

Two-dimensional Yukawa interactions from nonlocal Proca quantum electrodynamics

NASA Astrophysics Data System (ADS)

Alves, Van Sérgio; Macrı, Tommaso; Magalhães, Gabriel C.; Marino, E. C.; Nascimento, Leandro O.

2018-05-01

We derive two versions of an effective model to describe dynamical effects of the Yukawa interaction among Dirac electrons in the plane. Such short-range interaction is obtained by introducing a mass term for the intermediate particle, which may be either scalar or an abelian gauge field, both of them in (3 +1 ) dimensions. Thereafter, we consider that the fermionic matter field propagates only in (2 +1 ) dimensions, whereas the bosonic field is free to propagate out of the plane. Within these assumptions, we apply a mechanism for dimensional reduction, which yields an effective model in (2 +1 ) dimensions. In particular, for the gauge-field case, we use the Stueckelberg mechanism in order to preserve gauge invariance. We refer to this version as nonlocal-Proca quantum electrodynamics (NPQED). For both scalar and gauge cases, the effective models reproduce the usual Yukawa interaction in the static limit. By means of perturbation theory at one loop, we calculate the mass renormalization of the Dirac field. Our model is a generalization of Pseudo quantum electrodynamics (PQED), which is a gauge-field model that provides a Coulomb interaction for two-dimensional electrons. Possibilities of application to Fermi-Bose mixtures in mixed dimensions, using cold atoms, are briefly discussed.

A fashion model with social interaction

NASA Astrophysics Data System (ADS)

Nakayama, Shoichiro; Nakamura, Yasuyuki

2004-06-01

In general, it is difficult to investigate social phenomena mathematically or quantitatively due to non-linear interactions. Statistical physics can provide powerful methods for studying social phenomena with interactions, and could be very useful for them. In this study, we take a focus on fashion as a social phenomenon with interaction. The social interaction considered here are “bandwagon effect” and “snob effect.” In the bandwagon effect, the correlation between one's behavior and others is positive. People feel fashion weary or boring when it is overly popular. This is the snob effect. It is assumed that the fashion phenomenon is formed by the aggregation of individual's binary choice, that is, the fashion is adopted or not. We formulate the fashion phenomenon as the logit model, which is based on the random utility theory in social science, especially economics. The model derived here basically has the similarity with the pioneering model by Weidlich (Phys. Rep. 204 (1991) 1), which was derived from the master equation, the Langevin equation, or the Fokker-Planck equation. This study seems to give the behavioral or behaviormetrical foundation to his model. As a result of dynamical analysis, it is found that in the case that both the bandwagon effect and the snob effect work, periodic or chaotic behavior of fashion occurs under certain conditions.

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.

Effects of functional interactivity on patients' knowledge, empowerment, and health outcomes: an experimental model-driven evaluation of a web-based intervention.

PubMed

Camerini, Luca; Schulz, Peter Johannes

2012-07-18

The effectiveness of eHealth interventions in terms of reach and outcomes is now well documented. However, there is a need to understand not only whether eHealth interventions work, but also what kind of functions and mechanisms enhance their effectiveness. The present investigation contributes to tackling these challenges by investigating the role played by functional interactivity on patients' knowledge, empowerment, and health outcomes. To test whether health knowledge and empowerment mediate a possible relationship between the availability of interactive features on an eHealth application and individuals' health outcomes. We present an empirical, model-driven evaluation of the effects of functional interactivity implemented in an eHealth application, based on a brief theoretical review of the constructs of interactivity, health knowledge, empowerment, and health outcomes. We merged these constructs into a theoretical model of interactivity effects that we tested on an eHealth application for patients with fibromyalgia syndrome (FMS). This study used a pretest-posttest experimental design. We recruited 165 patients and randomly assigned them to three study groups, corresponding to different levels of functional interactivity. Eligibility to participate in the study required that patients (1) be fluent in Italian, (2) have access to the Internet, (3) report confidence in how to use a computer, and (4) have received a diagnosis of FMS from a doctor. We used structural equation modeling techniques to analyze changes between the pretest and the posttest results. The main finding was that functional interactivity had no impact on empowerment dimensions, nor direct observable effects on knowledge. However, knowledge positively affected health outcomes (b = -.12, P = .02), as did the empowerment dimensions of meaning (b = -.49, P < .001) and impact (b = -.25, P < .001). The theoretical model was partially confirmed, but only as far as the effects of knowledge and empowerment were concerned. The differential effect of interactive functions was by far weaker than expected. The strong impact of knowledge and empowerment on health outcomes suggests that these constructs should be targeted and enhanced by eHealth applications.

Flow regime, temperature, and biotic interactions drive differential declines of trout species under climate change [includes Supporting Information

Treesearch

Seth J. Wenger; Daniel J. Isaak; Charlie Luce; Helen M. Neville; Kurt D. Fausch; Jason B. Dunham; Daniel C. Dauwalter; Michael K. Young; Marketa M. Elsner; Bruce E. Rieman; Alan F. Hamlet; Jack E. Williams

2011-01-01

Broad-scale studies of climate change effects on freshwater species have focused mainly on temperature, ignoring critical drivers such as flow regime and biotic interactions. We use downscaled outputs from general circulation models coupled with a hydrologic model to forecast the effects of altered flows and increased temperatures on four interacting species of trout...

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).

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…

Characteristics of aperiodic sequence of slip events caused by interaction between seismic patches and that caused be self-organized stress heterogeneity

NASA Astrophysics Data System (ADS)

Kato, N.

2017-12-01

Numerical simulations of earthquake cycles are conducted to investigate the origin of complexity of earthquake recurrence. There are two main causes of the complexity. One is self-organized stress heterogeneity due to dynamical effect. The other is the effect of interaction between some fault patches. In the model, friction on the fault is assumed to obey a rate- and state-dependent friction law. Circular patches of velocity-weakening frictional property are assumed on the fault. On the remaining areas of the fault, velocity-strengthening friction is assumed. We consider three models: Single patch model, two-patch model, and three-patch model. In the first model, the dynamical effect is mainly examined. The latter two models take into consideration the effect of interaction as well as the dynamical effect. Complex multiperiodic or aperiodic sequences of slip events occur when slip behavior changes from the seismic to aseismic, and when the degree of interaction between seismic patches is intermediate. The former is observed in all the models, and the latter is observed in the two-patch model and the three-patch model. Evolution of spatial distribution of shear stress on the fault suggests that aperiodicity at the transition from seismic to aseismic slip is caused by self-organized stress heterogeneity. The iteration maps of recurrence intervals of slip events in aperiodic sequences are examined, and they are approximately expressed by simple curves for aperiodicity at the transition from seismic to aseismic slip. In contrast, the iteration maps for aperiodic sequences caused by interaction between seismic patches are scattered and they are not expressed by simple curves. This result suggests that complex sequences caused by different mechanisms may be distinguished.

Epistasis interaction of QTL effects as a genetic parameter influencing estimation of the genetic additive effect.

PubMed

Bocianowski, Jan

2013-03-01

Epistasis, an additive-by-additive interaction between quantitative trait loci, has been defined as a deviation from the sum of independent effects of individual genes. Epistasis between QTLs assayed in populations segregating for an entire genome has been found at a frequency close to that expected by chance alone. Recently, epistatic effects have been considered by many researchers as important for complex traits. In order to understand the genetic control of complex traits, it is necessary to clarify additive-by-additive interactions among genes. Herein we compare estimates of a parameter connected with the additive gene action calculated on the basis of two models: a model excluding epistasis and a model with additive-by-additive interaction effects. In this paper two data sets were analysed: 1) 150 barley doubled haploid lines derived from the Steptoe × Morex cross, and 2) 145 DH lines of barley obtained from the Harrington × TR306 cross. The results showed that in cases when the effect of epistasis was different from zero, the coefficient of determination was larger for the model with epistasis than for the one excluding epistasis. These results indicate that epistatic interaction plays an important role in controlling the expression of complex traits.

Effect of Coulomb interaction on chemical potential of metal film

NASA Astrophysics Data System (ADS)

Kostrobij, P. P.; Markovych, B. M.

2018-07-01

The chemical potential of a metal film within the jellium model taking into account the Coulomb interaction between electrons is calculated. The surface potential is modelled as the infinite rectangular potential well. The behaviour of the chemical potential as a function of the film thickness is studied, the quantum size effect for this quantity is analysed. It is shown that taking into account the Coulomb interaction leads to a significant decrease of the chemical potential and to an enhancement of the quantum size effect.

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…

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

Effects of economic interactions on credit risk

NASA Astrophysics Data System (ADS)

Hatchett, J. P. L.; Kühn, R.

2006-03-01

We study a credit-risk model which captures effects of economic interactions on a firm's default probability. Economic interactions are represented as a functionally defined graph, and the existence of both cooperative and competitive business relations is taken into account. We provide an analytic solution of the model in a limit where the number of business relations of each company is large, but the overall fraction of the economy with which a given company interacts may be small. While the effects of economic interactions are relatively weak in typical (most probable) scenarios, they are pronounced in situations of economic stress, and thus lead to a substantial fattening of the tails of loss distributions in large loan portfolios. This manifests itself in a pronounced enhancement of the value at risk computed for interacting economies in comparison with their non-interacting counterparts.

Viscous-inviscid interaction method including wake effects for three-dimensional wing-body configurations

NASA Technical Reports Server (NTRS)

Streett, C. L.

1981-01-01

A viscous-inviscid interaction method has been developed by using a three-dimensional integral boundary-layer method which produces results in good agreement with a finite-difference method in a fraction of the computer time. The integral method is stable and robust and incorporates a model for computation in a small region of streamwise separation. A locally two-dimensional wake model, accounting for thickness and curvature effects, is also included in the interaction procedure. Computation time spent in converging an interacted result is, many times, only slightly greater than that required to converge an inviscid calculation. Results are shown from the interaction method, run at experimental angle of attack, Reynolds number, and Mach number, on a wing-body test case for which viscous effects are large. Agreement with experiment is good; in particular, the present wake model improves prediction of the spanwise lift distribution and lower surface cove pressure.

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.

Gender-specific interactions between education and income in relation to obesity: a cross-sectional analysis of the Fifth Korea National Health and Nutrition Examination Survey (KNHANES V)

PubMed Central

Chung, Woojin; Lim, Seung-ji; Lee, Sunmi; Kim, Roeul; Kim, Jaeyeun

2017-01-01

Objectives To identify gender-specific associations between education and income in relation to obesity in developed countries by considering both the interaction-effect terms of the independent variables and their main-effect terms. Design A cross-sectional study. Education and income levels were chosen as socioeconomic status indicators. Sociodemographics, lifestyles and medical conditions were used as covariates in multivariable logistic regression models. Adjusted ORs and predicted probabilities of being obese were computed and adjusted for a complex survey design. Setting Data were obtained from the Fifth Korea National Health and Nutrition Examination Survey (2010–2012). Participants The sample included 7337 male and 9908 female participants aged ≥19 years. Outcome measure Obesity was defined as body mass index of ≥25, according to a guideline for Asians. Results In models with no interaction-effect terms of independent variables, education was significantly associated with obesity in both men and women, but income was significant only in women. However, in models with the interaction-effect terms, education was significant only in women, but income was significant only in men. The interaction effect between income and education was significant in men but not in women. Participants having the highest predicted probability of being obese over educational and income levels differed between the two types of models, and between men and women. A prediction using the models with the interaction-effect terms demonstrated that for all men, the highest level of formal education was associated with an increase in their probability of being obese by as much as 26%. Conclusions The well-known, negative association between socioeconomic status and obesity in developed countries may not be valid when interaction effects are included. Ignoring these effects and their gender differences may result in the targeting of wrong populations for reducing obesity prevalence and its resultant socioeconomic gradients. PMID:29288171

Temporal scale dependent interactions between multiple environmental disturbances in microcosm ecosystems.

PubMed

Garnier, Aurélie; Pennekamp, Frank; Lemoine, Mélissa; Petchey, Owen L

2017-12-01

Global environmental change has negative impacts on ecological systems, impacting the stable provision of functions, goods, and services. Whereas effects of individual environmental changes (e.g. temperature change or change in resource availability) are reasonably well understood, we lack information about if and how multiple changes interact. We examined interactions among four types of environmental disturbance (temperature, nutrient ratio, carbon enrichment, and light) in a fully factorial design using a microbial aquatic ecosystem and observed responses of dissolved oxygen saturation at three temporal scales (resistance, resilience, and return time). We tested whether multiple disturbances combine in a dominant, additive, or interactive fashion, and compared the predictability of dissolved oxygen across scales. Carbon enrichment and shading reduced oxygen concentration in the short term (i.e. resistance); although no other effects or interactions were statistically significant, resistance decreased as the number of disturbances increased. In the medium term, only enrichment accelerated recovery, but none of the other effects (including interactions) were significant. In the long term, enrichment and shading lengthened return times, and we found significant two-way synergistic interactions between disturbances. The best performing model (dominant, additive, or interactive) depended on the temporal scale of response. In the short term (i.e. for resistance), the dominance model predicted resistance of dissolved oxygen best, due to a large effect of carbon enrichment, whereas none of the models could predict the medium term (i.e. resilience). The long-term response was best predicted by models including interactions among disturbances. Our results indicate the importance of accounting for the temporal scale of responses when researching the effects of environmental disturbances on ecosystems. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

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

[An ADAA model and its analysis method for agronomic traits based on the double-cross mating design].

PubMed

Xu, Z C; Zhu, J

2000-01-01

According to the double-cross mating design and using principles of Cockerham's general genetic model, a genetic model with additive, dominance and epistatic effects (ADAA model) was proposed for the analysis of agronomic traits. Components of genetic effects were derived for different generations. Monte Carlo simulation was conducted for analyzing the ADAA model and its reduced AD model by using different generations. It was indicated that genetic variance components could be estimated without bias by MINQUE(1) method and genetic effects could be predicted effectively by AUP method; at least three generations (including parent, F1 of single cross and F1 of double-cross) were necessary for analyzing the ADAA model and only two generations (including parent and F1 of double-cross) were enough for the reduced AD model. When epistatic effects were taken into account, a new approach for predicting the heterosis of agronomic traits of double-crosses was given on the basis of unbiased prediction of genotypic merits of parents and their crosses. In addition, genotype x environment interaction effects and interaction heterosis due to G x E interaction were discussed briefly.

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…

Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm.

PubMed

Yu, Isseki; Mori, Takaharu; Ando, Tadashi; Harada, Ryuhei; Jung, Jaewoon; Sugita, Yuji; Feig, Michael

2016-11-01

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology.

Interaction between Faraday rotation and Cotton-Mouton effects in polarimetry modeling for NSTX

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

Zhang, J.; Crocker, N. A.; Carter, T. A.

The evolution of electromagnetic wave polarization is modeled for propagation in the major radial direction in the National Spherical Torus Experiment with retroreflection from the center stack of the vacuum vessel. This modeling illustrates that the Cotton-Mouton effect-elliptization due to the magnetic field perpendicular to the propagation direction-is shown to be strongly weighted to the high-field region of the plasma. An interaction between the Faraday rotation and Cotton-Mouton effects is also clearly identified. Elliptization occurs when the wave polarization direction is neither parallel nor perpendicular to the local transverse magnetic field. Since Faraday rotation modifies the polarization direction during propagation,more » it must also affect the resultant elliptization. The Cotton-Mouton effect also intrinsically results in rotation of the polarization direction, but this effect is less significant in the plasma conditions modeled. The interaction increases at longer wavelength and complicates interpretation of polarimetry measurements.« less

Climate change amplifies the interactions between wind and bark beetle disturbances in forest landscapes.

PubMed

Seidl, Rupert; Rammer, Werner

2017-07-01

Growing evidence suggests that climate change could substantially alter forest disturbances. Interactions between individual disturbance agents are a major component of disturbance regimes, yet how interactions contribute to their climate sensitivity remains largely unknown. Here, our aim was to assess the climate sensitivity of disturbance interactions, focusing on wind and bark beetle disturbances. We developed a process-based model of bark beetle disturbance, integrated into the dynamic forest landscape model iLand (already including a detailed model of wind disturbance). We evaluated the integrated model against observations from three wind events and a subsequent bark beetle outbreak, affecting 530.2 ha (3.8 %) of a mountain forest landscape in Austria between 2007 and 2014. Subsequently, we conducted a factorial experiment determining the effect of changes in climate variables on the area disturbed by wind and bark beetles separately and in combination. iLand was well able to reproduce observations with regard to area, temporal sequence, and spatial pattern of disturbance. The observed disturbance dynamics was strongly driven by interactions, with 64.3 % of the area disturbed attributed to interaction effects. A +4 °C warming increased the disturbed area by +264.7 % and the area-weighted mean patch size by +1794.3 %. Interactions were found to have a ten times higher sensitivity to temperature changes than main effects, considerably amplifying the climate sensitivity of the disturbance regime. Disturbance interactions are a key component of the forest disturbance regime. Neglecting interaction effects can lead to a substantial underestimation of the climate change sensitivity of disturbance regimes.

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.

The effective colloid interaction in the Asakura-Oosawa model. Assessment of non-pairwise terms from the virial expansion.

PubMed

Santos, Andrés; López de Haro, Mariano; Fiumara, Giacomo; Saija, Franz

2015-06-14

The relevance of neglecting three- and four-body interactions in the coarse-grained version of the Asakura-Oosawa model is examined. A mapping between the first few virial coefficients of the binary nonadditive hard-sphere mixture representative of this model and those arising from the coarse-grained (pairwise) depletion potential approximation allows for a quantitative evaluation of the effect of such interactions. This turns out to be especially important for large size ratios and large reservoir polymer packing fractions.

Evaluating nuclear physics inputs in core-collapse supernova models

NASA Astrophysics Data System (ADS)

Lentz, E.; Hix, W. R.; Baird, M. L.; Messer, O. E. B.; Mezzacappa, A.

Core-collapse supernova models depend on the details of the nuclear and weak interaction physics inputs just as they depend on the details of the macroscopic physics (transport, hydrodynamics, etc.), numerical methods, and progenitors. We present preliminary results from our ongoing comparison studies of nuclear and weak interaction physics inputs to core collapse supernova models using the spherically-symmetric, general relativistic, neutrino radiation hydrodynamics code Agile-Boltztran. We focus on comparisons of the effects of the nuclear EoS and the effects of improving the opacities, particularly neutrino--nucleon interactions.

No direct by maternal effects interaction detected for pre-weaning growth in Romane sheep using a reaction norm model.

PubMed

David, Ingrid; Bouvier, Frédéric; Ricard, Edmond; Ruesche, Julien; Weisbecker, Jean-Louis

2013-09-30

The pre-weaning growth of lambs, an important component of meat production, depends on maternal and direct effects. These effects cannot be observed directly and models used to study pre-weaning growth assume that they are additive. However, it is reasonable to suggest that the influence of direct effects on growth may differ depending on the value of maternal effects i.e. an interaction may exist between the two components. To test this hypothesis, an experiment was carried out in Romane sheep in order to obtain observations of maternal phenotypic effects (milk yield and milk quality) and pre-weaning growth of the lambs. The experiment consisted of mating ewes that had markedly different maternal genetic effects with rams that contributed very different genetic effects in four replicates of a 3 × 2 factorial plan. Milk yield was measured using the lamb suckling weight differential technique and milk composition (fat and protein contents) was determined by infrared spectroscopy at 15, 21 and 35 days after lambing. Lambs were weighed at birth and then at 15, 21 and 35 days. An interaction between genotype (of the lamb) and environment (milk yield and quality) for average daily gain was tested using a restricted likelihood ratio test, comparing a linear reaction norm model (interaction model) to a classical additive model (no interaction model). A total of 1284 weights of 442 lambs born from 166 different ewes were analysed. On average, the ewes produced 2.3 ± 0.8 L milk per day. The average protein and fat contents were 50 ± 4 g/L and 60 ± 18 g/L, respectively. The mean 0-35 day average daily gain was 207 ± 46 g/d. Results of the restricted likelihood ratio tests did not highlight any significant interactions between the genotype of the lambs and milk production of the ewe. Our results support the hypothesis of additivity of maternal and direct effects on growth that is currently applied in genetic evaluation models.

Ion specific effects: decoupling ion-ion and ion-water interactions

PubMed Central

Song, Jinsuk; Kang, Tae Hui; Kim, Mahn Won; Han, Songi

2015-01-01

Ion-specific effects in aqueous solution, known as the Hofmeister effect is prevalent in diverse systems ranging from pure ionic to complex protein solutions. The objective of this paper is to explicitly demonstrate how complex ion-ion and ion-water interactions manifest themselves in the Hofmeister effects, based on a series of recent experimental observation. These effects are not considered in the classical description of ion effects, such as the Deryaguin-Landau-Verwey-Overbeek (DLVO) theory that, likely for that reason, fail to describe the origin of the phenomenological Hofmeister effect. However, given that models considering the basic forces of electrostatic and van der Waals interactions can offer rationalization for the core experimental observations, a universal interaction model stands a chance to be developed. In this perspective, we separately derive the contribution from ion-ion electrostatic interaction and ion-water interaction from second harmonic generation (SHG) data at the air-ion solution interface, which yields an estimate of ion-water interactions in solution. Hofmeister ion effects observed on biological solutes in solution should be similarly influenced by contributions from ion-ion and ion-water interactions, where the same ion-water interaction parameters derived from SHG data at the air-ion solution interface could be applicable. A key experimental data set available from solution systems to probe ion-water interaction is the modulation of water diffusion dynamics near ions in bulk ion solution, as well as near biological liposome surfaces. It is obtained from Overhauser dynamic nuclear polarization (ODNP), a nuclear magnetic resonance (NMR) relaxometry technique. The surface water diffusivity is influenced by the contribution from ion-water interactions, both from localized surface charges and adsorbed ions, although the relative contribution of the former is larger on liposome surfaces. In this perspective, ion-water interaction energy values derived from experimental data for various ions are compared with theoretical values in the literature. Ultimately, quantifying ion-induced changes in surface energy for the purpose of developing valid theoretical models for ion-water interaction, will be critical to rationalizing the Hofmeister effect. PMID:25761273

Uncoupling the Effects of Seed Predation and Seed Dispersal by Granivorous Ants on Plant Population Dynamics

PubMed Central

Arnan, Xavier; Molowny-Horas, Roberto; Rodrigo, Anselm; Retana, Javier

2012-01-01

Secondary seed dispersal is an important plant-animal interaction, which is central to understanding plant population and community dynamics. Very little information is still available on the effects of dispersal on plant demography and, particularly, for ant-seed dispersal interactions. As many other interactions, seed dispersal by animals involves costs (seed predation) and benefits (seed dispersal), the balance of which determines the outcome of the interaction. Separate quantification of each of them is essential in order to understand the effects of this interaction. To address this issue, we have successfully separated and analyzed the costs and benefits of seed dispersal by seed-harvesting ants on the plant population dynamics of three shrub species with different traits. To that aim a stochastic, spatially-explicit individually-based simulation model has been implemented based on actual data sets. The results from our simulation model agree with theoretical models of plant response dependent on seed dispersal, for one plant species, and ant-mediated seed predation, for another one. In these cases, model predictions were close to the observed values at field. Nonetheless, these ecological processes did not affect in anyway a third species, for which the model predictions were far from the observed values. This indicates that the balance between costs and benefits associated to secondary seed dispersal is clearly related to specific traits. This study is one of the first works that analyze tradeoffs of secondary seed dispersal on plant population dynamics, by disentangling the effects of related costs and benefits. We suggest analyzing the effects of interactions on population dynamics as opposed to merely analyzing the partners and their interaction strength. PMID:22880125

Systems pharmacology - Towards the modeling of network interactions.

PubMed

Danhof, Meindert

2016-10-30

Mechanism-based pharmacokinetic and pharmacodynamics (PKPD) and disease system (DS) models have been introduced in drug discovery and development research, to predict in a quantitative manner the effect of drug treatment in vivo in health and disease. This requires consideration of several fundamental properties of biological systems behavior including: hysteresis, non-linearity, variability, interdependency, convergence, resilience, and multi-stationarity. Classical physiology-based PKPD models consider linear transduction pathways, connecting processes on the causal path between drug administration and effect, as the basis of drug action. Depending on the drug and its biological target, such models may contain expressions to characterize i) the disposition and the target site distribution kinetics of the drug under investigation, ii) the kinetics of target binding and activation and iii) the kinetics of transduction. When connected to physiology-based DS models, PKPD models can characterize the effect on disease progression in a mechanistic manner. These models have been found useful to characterize hysteresis and non-linearity, yet they fail to explain the effects of the other fundamental properties of biological systems behavior. Recently systems pharmacology has been introduced as novel approach to predict in vivo drug effects, in which biological networks rather than single transduction pathways are considered as the basis of drug action and disease progression. These models contain expressions to characterize the functional interactions within a biological network. Such interactions are relevant when drugs act at multiple targets in the network or when homeostatic feedback mechanisms are operative. As a result systems pharmacology models are particularly useful to describe complex patterns of drug action (i.e. synergy, oscillatory behavior) and disease progression (i.e. episodic disorders). In this contribution it is shown how physiology-based PKPD and disease models can be extended to account for internal systems interactions. It is demonstrated how SP models can be used to predict the effects of multi-target interactions and of homeostatic feedback on the pharmacological response. In addition it is shown how DS models may be used to distinguish symptomatic from disease modifying effects and to predict the long term effects on disease progression, from short term biomarker responses. It is concluded that incorporation of expressions to describe the interactions in biological network analysis opens new avenues to the understanding of the effects of drug treatment on the fundamental aspects of biological systems behavior. Copyright © 2016 The Author. Published by Elsevier B.V. All rights reserved.

Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations.

PubMed

Hayes, Andrew F; Matthes, Jörg

2009-08-01

Researchers often hypothesize moderated effects, in which the effect of an independent variable on an outcome variable depends on the value of a moderator variable. Such an effect reveals itself statistically as an interaction between the independent and moderator variables in a model of the outcome variable. When an interaction is found, it is important to probe the interaction, for theories and hypotheses often predict not just interaction but a specific pattern of effects of the focal independent variable as a function of the moderator. This article describes the familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models and introduces macros for SPSS and SAS to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression. A script version of the SPSS macro is also available for users who prefer a point-and-click user interface rather than command syntax.

Estimating Interaction Effects With Incomplete Predictor Variables

PubMed Central

Enders, Craig K.; Baraldi, Amanda N.; Cham, Heining

2014-01-01

The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (e.g., a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline centering and transformation strategies that researchers can implement in popular software packages, and we use a series of real data analyses to illustrate these methods. Finally, we use computer simulations to evaluate the performance of the proposed techniques. PMID:24707955

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.

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

Effect of the band structure in a rigorous two-body model with long-range interactions in 1D optical lattices

NASA Astrophysics Data System (ADS)

Kristensen, Tom; Simoni, Andrea; Launay, Jean-Michel

2016-05-01

We compute scattering and bound state properties for two ultracold molecules in a pure 1D optical lattice. We introduce reference functions with complex quasi-momentum that naturally account for the effect of excited energy bands. Our exact results for a short-range interaction are first compared with the simplest version of the standard Bose-Hubbard (BH) model. Such comparison allows us to highlight the effect of the excited bands, of the non-on-site interaction and of tunneling with distant neighbor, that are not taken into account in the BH model. The effective interaction can depend strongly on the particle quasi-momenta and can present a resonant behavior even in a deep lattice. As a second step, we study scattering of two polar particles in the optical lattice. Peculiar Wigner threshold laws stem from the interplay of the long range dipolar interaction and the presence of the energy bands. We finally assess the validity of an extended Bose-Hubbard model for dipolar gases based on our exact two-body calculations. This work was supported by the Agence Nationale de la Recherche (Contract No. ANR-12-BS04-0020-01).

Incorporating Context Dependency of Species Interactions in Species Distribution Models.

PubMed

Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A

2017-07-01

Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same pattern to a lesser degree, although this pattern was not significant. This work bridges the disciplines of biogeography and community ecology to develop tools to better understand the direct and indirect effects of abiotic conditions on ecological communities. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Oxytocin attenuates deficits in social interaction but not recognition memory in a prenatal valproic acid-induced mouse model of autism.

PubMed

Hara, Yuta; Ago, Yukio; Higuchi, Momoko; Hasebe, Shigeru; Nakazawa, Takanobu; Hashimoto, Hitoshi; Matsuda, Toshio; Takuma, Kazuhiro

2017-11-01

Recent studies have reported that oxytocin ameliorates behavioral abnormalities in both animal models and individuals with autism spectrum disorders (ASD). However, the mechanisms underlying the ameliorating effects of oxytocin remain unclear. In this study, we examined the effects of intranasal oxytocin on impairments in social interaction and recognition memory in an ASD mouse model in which animals are prenatally exposed to valproic acid (VPA). We found that a single intranasal administration of oxytocin restored social interaction deficits for up to 2h in mice prenatally exposed to VPA, but there was no effect on recognition memory impairments. Additionally, administration of oxytocin across 2weeks improved prenatal VPA-induced social interaction deficits for at least 24h. In contrast, there were no effects on the time spent sniffing in control mice. Immunohistochemical analysis revealed that intranasal administration of oxytocin increased c-Fos expression in the paraventricular nuclei (PVN), prefrontal cortex, and somatosensory cortex, but not the hippocampal CA1 and CA3 regions of VPA-exposed mice, suggesting the former regions may underlie the effects of oxytocin. These findings suggest that oxytocin attenuates social interaction deficits through the activation of higher cortical areas and the PVN in an ASD mouse model. Copyright © 2017 Elsevier Inc. All rights reserved.

Use of AMMI and linear regression models to analyze genotype-environment interaction in durum wheat.

PubMed

Nachit, M M; Nachit, G; Ketata, H; Gauch, H G; Zobel, R W

1992-03-01

The joint durum wheat (Triticum turgidum L var 'durum') breeding program of the International Maize and Wheat Improvement Center (CIMMYT) and the International Center for Agricultural Research in the Dry Areas (ICARDA) for the Mediterranean region employs extensive multilocation testing. Multilocation testing produces significant genotype-environment (GE) interaction that reduces the accuracy for estimating yield and selecting appropriate germ plasm. The sum of squares (SS) of GE interaction was partitioned by linear regression techniques into joint, genotypic, and environmental regressions, and by Additive Main effects and the Multiplicative Interactions (AMMI) model into five significant Interaction Principal Component Axes (IPCA). The AMMI model was more effective in partitioning the interaction SS than the linear regression technique. The SS contained in the AMMI model was 6 times higher than the SS for all three regressions. Postdictive assessment recommended the use of the first five IPCA axes, while predictive assessment AMMI1 (main effects plus IPCA1). After elimination of random variation, AMMI1 estimates for genotypic yields within sites were more precise than unadjusted means. This increased precision was equivalent to increasing the number of replications by a factor of 3.7.

Modelling algae-duckweed interaction under chemical pressure within a laboratory microcosm.

PubMed

Lamonica, Dominique; Clément, Bernard; Charles, Sandrine; Lopes, Christelle

2016-06-01

Contaminant effects on species are generally assessed with single-species bioassays. As a consequence, interactions between species that occur in ecosystems are not taken into account. To investigate the effects of contaminants on interacting species dynamics, our study describes the functioning of a 2-L laboratory microcosm with two species, the duckweed Lemna minor and the microalgae Pseudokirchneriella subcapitata, exposed to cadmium contamination. We modelled the dynamics of both species and their interactions using a mechanistic model based on coupled ordinary differential equations. The main processes occurring in this two-species microcosm were thus formalised, including growth and settling of algae, growth of duckweeds, interspecific competition between the two species and cadmium effects. We estimated model parameters by Bayesian inference, using simultaneously all the data issued from multiple laboratory experiments specifically conducted for this study. Cadmium concentrations ranged between 0 and 50 μg·L(-1). For all parameters of our model, we obtained biologically realistic values and reasonable uncertainties. Only duckweed dynamics was affected by interspecific competition, while algal dynamics was not impaired. Growth rate of both species decreased with cadmium concentration, as well as competition intensity showing that the interspecific competition pressure on duckweed decreased with cadmium concentration. This innovative combination of mechanistic modelling and model-guided experiments was successful to understand the algae-duckweed microcosm functioning without and with contaminant. This approach appears promising to include interactions between species when studying contaminant effects on ecosystem functioning. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

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.

The effect of thematic learning model, learning style, and reading ability on the students’ learning outcomes

NASA Astrophysics Data System (ADS)

Nurlaela, L.; Samani, M.; Asto, I. G. P.; Wibawa, S. C.

2018-01-01

This study aims at gaining empirical findings of the effectiveness of thematic instructional model as compared to conventional instruction; and the potential capacity of thematic instructional model in accommodating different learning styles and reading abilities. This is an experimental research design with 140 elementary students as research subject. The data were collected by using achievement test, learning style questionnaire, and reading comprehension test, and analyzed by using Anava. The results indicate: there is a significant difference in achievement between students who use thematic instructional model and those using conventional model; a significant difference in achievement between students with visual learning style and those having auditorial learning style; a significant difference between students with high reading ability and those with low reading ability. Student’s achievement is influenced by the interaction between instructional model and student’s learning style. Student’s achievement is not influenced by the interaction between instructional model and student’s reading ability, the interaction between student’s learning style and student’s reading ability, and the interaction among instructional model, learning style and student’s reading ability. The conclusion is thematic instructional model was more effective than conventional instruction and thematic instructional model had a capacity in accommodating different learning styles and reading abilities.

Tunable fictitious substituent effects on the π-π interactions of substituted sandwich benzene dimers.

PubMed

Garcia, Amee M; Determan, John J; Janesko, Benjamin G

2014-05-08

Substituent effects on the π-π interactions of aromatic rings are a topic of much recent debate. Real substituents give a complicated combination of inductive, resonant, dispersion, and other effects. To help partition these effects, we present calculations on fictitious "pure" σ donor/acceptor substituents, hydrogen atoms with nuclear charges other than 1. "Pure" σ donors with nuclear charge <1 weaken π-π stacking in the sandwich benzene dimer. This result is consistent with the electrostatic model of Hunter and Sanders, and different from real substituents. Calculated inductive effects are largely additive and transferable, consistent with a local direct interaction model. A second series of fictitious substituents, neutral hydrogen atoms with an artificially broadened nuclear charge distribution, give similar trends though with reduced additivity. These results provide an alternative perspective on substituent effects in noncovalent interactions.

Indirect genetic effect model using feeding behaviour traits to define the degree of interaction between mates: an implementation in pigs growth rate.

PubMed

Ragab, M; Piles, M; Quintanilla, R; Sánchez, J P

2018-06-06

An alternative implementation of the animal model including indirect genetic effect (IGE) is presented considering pair-mate-specific interaction degrees to improve the performance of the model. Data consisted of average daily gain (ADG) records from 663 pigs kept in groups of 10 to 14 mates during the fattening period. Three types of models were used to fit ADG data: (i) animal model (AM); (ii) AM with classical IGE (AM-IGE); and (iii) AM fitting IGE with a specific degree of interaction between each pair of mates (AM-IGEi). Several feeding behavior phenotypes were used to define the pair-mate-specific degree of interaction in AM-IGEi: feeding rate (g/min), feeding frequency (min/day), the time between consecutive visits to the feeder (min/day), occupation time (min/day) and an index considering all these variables. All models included systematic effects batch, initial age (covariate), final age (covariate), number of pigs per pen (covariate), plus the random effect of the pen. Estimated posterior mean (posterior SD) of heritability was 0.47 (0.15) using AM. Including social genetic effects in the model, total heritable variance expressed as a proportion of total phenotypic variance (T 2) was 0.54 (0.29) using AM-IGE, whereas it ranged from 0.51 to 0.55 (0.12 to 0.14) with AM-IGEi, depending on the behavior trait used to define social interactions. These results confirm the contribution of IGEs to the total heritable variation of ADG. Moreover, important differences between models were observed in EBV rankings. The percentage of coincidence of top 10% animals between AM and AM-IGEi ranged from 0.44 to 0.89 and from 0.41to 0.68 between AM-IGE and AM-IGEi. Based on the goodness of fit and predictive ability, social models are preferred for the genetic evaluation of ADG. Among models including IGEs, when the pair-specific degree of interaction was defined using feeding behavior phenotypes we obtained an increase in the accuracy of genetic parameters estimates, the better goodness of fit and higher predictive ability. We conclude that feeding behavior variables can be used to measure the interaction between pen mates and to improve the performance of models including IGEs.

The Two Faces of Social Interaction Reward in Animal Models of Drug Dependence.

PubMed

El Rawas, Rana; Saria, Alois

2016-03-01

Drug dependence is a serious health and social problem. Social factors can modify vulnerability to developing drug dependence, acting as risk factors or protective factors. Whereas stress and peer environment that encourage substance use may increase drug taking, strong attachments between family members and peer environment that do not experience drug use may protect against drug taking and, ultimately, drug dependence. The rewarding effects of drug abuse and social interaction can be evaluated using animal models. In this review we focus on evaluating social interaction reward in the conditioned place preference paradigm. We give an overview of how social interaction, if made available within the drug context, may facilitate, promote and interact with the drug's effects. However, social interaction, if offered alternatively outside the drug context, may have pronounced protective effects against drug abuse and relapse. We also address the importance of the weight difference parameter between the social partners in determining the positive or "agonistic" versus the hostile or "antagonistic" social interaction. We conclude that understanding social interaction reward and its subsequent effects on drug reward is sorely needed for therapeutic interventions against drug dependence.

Effects of cavity-cavity interaction on the entanglement dynamics of a generalized double Jaynes-Cummings model

NASA Astrophysics Data System (ADS)

Pandit, Mahasweta; Das, Sreetama; Singha Roy, Sudipto; Shekhar Dhar, Himadri; Sen, Ujjwal

2018-02-01

We consider a generalized double Jaynes-Cummings model consisting of two isolated two-level atoms, each contained in a lossless cavity that interact with each other through a controlled photon-hopping mechanism. We analytically show that at low values of such a mediated cavity-cavity interaction, the temporal evolution of entanglement between the atoms, under the effects of cavity perturbation, exhibits the well-known phenomenon of entanglement sudden death (ESD). Interestingly, for moderately large interaction values, a complete preclusion of ESD is achieved, irrespective of its value in the initial atomic state. Our results provide a model to sustain entanglement between two atomic qubits, under the adverse effect of cavity induced perturbation, by introducing a non-intrusive inter-cavity photon exchange that can be physically realized through cavity-QED setups in contemporary experiments.

Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages.

PubMed

Radinger, Johannes; Hölker, Franz; Horký, Pavel; Slavík, Ondřej; Dendoncker, Nicolas; Wolter, Christian

2016-04-01

River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts. © 2015 John Wiley & Sons Ltd.

Comparison of methods for the analysis of relatively simple mediation models.

PubMed

Rijnhart, Judith J M; Twisk, Jos W R; Chinapaw, Mai J M; de Boer, Michiel R; Heymans, Martijn W

2017-09-01

Statistical mediation analysis is an often used method in trials, to unravel the pathways underlying the effect of an intervention on a particular outcome variable. Throughout the years, several methods have been proposed, such as ordinary least square (OLS) regression, structural equation modeling (SEM), and the potential outcomes framework. Most applied researchers do not know that these methods are mathematically equivalent when applied to mediation models with a continuous mediator and outcome variable. Therefore, the aim of this paper was to demonstrate the similarities between OLS regression, SEM, and the potential outcomes framework in three mediation models: 1) a crude model, 2) a confounder-adjusted model, and 3) a model with an interaction term for exposure-mediator interaction. Secondary data analysis of a randomized controlled trial that included 546 schoolchildren. In our data example, the mediator and outcome variable were both continuous. We compared the estimates of the total, direct and indirect effects, proportion mediated, and 95% confidence intervals (CIs) for the indirect effect across OLS regression, SEM, and the potential outcomes framework. OLS regression, SEM, and the potential outcomes framework yielded the same effect estimates in the crude mediation model, the confounder-adjusted mediation model, and the mediation model with an interaction term for exposure-mediator interaction. Since OLS regression, SEM, and the potential outcomes framework yield the same results in three mediation models with a continuous mediator and outcome variable, researchers can continue using the method that is most convenient to them.

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.

Including Finite Surface Span Effects in Empirical Jet-Surface Interaction Noise Models

NASA Technical Reports Server (NTRS)

Brown, Clifford A.

2016-01-01

The effect of finite span on the jet-surface interaction noise source and the jet mixing noise shielding and reflection effects is considered using recently acquired experimental data. First, the experimental setup and resulting data are presented with particular attention to the role of surface span on far-field noise. These effects are then included in existing empirical models that have previously assumed that all surfaces are semi-infinite. This extended abstract briefly describes the experimental setup and data leaving the empirical modeling aspects for the final paper.

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.

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.

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.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

Genetic and environmental (physical fitness and sedentary activity) interaction effects on cardiometabolic risk factors in Mexican American children and adolescents.

PubMed

Arya, Rector; Farook, Vidya S; Fowler, Sharon P; Puppala, Sobha; Chittoor, Geetha; Resendez, Roy G; Mummidi, Srinivas; Vanamala, Jairam; Almasy, Laura; Curran, Joanne E; Comuzzie, Anthony G; Lehman, Donna M; Jenkinson, Christopher P; Lynch, Jane L; DeFronzo, Ralph A; Blangero, John; Hale, Daniel E; Duggirala, Ravindranath; Diego, Vincent P

2018-06-01

Knowledge on genetic and environmental (G × E) interaction effects on cardiometabolic risk factors (CMRFs) in children is limited.  The purpose of this study was to examine the impact of G × E interaction effects on CMRFs in Mexican American (MA) children (n = 617, ages 6-17 years). The environments examined were sedentary activity (SA), assessed by recalls from "yesterday" (SAy) and "usually" (SAu) and physical fitness (PF) assessed by Harvard PF scores (HPFS). CMRF data included body mass index (BMI), waist circumference (WC), fat mass (FM), fasting insulin (FI), homeostasis model of assessment-insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), systolic (SBP) and diastolic (DBP) blood pressure, and number of metabolic syndrome components (MSC). We examined potential G × E interaction in the phenotypic expression of CMRFs using variance component models and likelihood-based statistical inference. Significant G × SA interactions were identified for six CMRFs: BMI, WC, FI, HOMA-IR, MSC, and HDL, and significant G × HPFS interactions were observed for four CMRFs: BMI, WC, FM, and HOMA-IR. However, after correcting for multiple hypothesis testing, only WC × SAy, FM × SAy, and FI × SAu interactions became marginally significant. After correcting for multiple testing, most of CMRFs exhibited significant G × E interactions (Reduced G × E model vs. Constrained model). These findings provide evidence that genetic factors interact with SA and PF to influence variation in CMRFs, and underscore the need for better understanding of these relationships to develop strategies and interventions to effectively reduce or prevent cardiometabolic risk in children. © 2018 WILEY PERIODICALS, INC.

Developing a model for effects of climate change on human health and health-environment interactions: Heat stress in Austin, Texas

EPA Science Inventory

Background/Question/Methods In December, 2010, a consortium of EPA, Centers for Disease Control, and state and local health officials convened in Austin, Texas for a “participatory modeling workshop” on climate change effects on human health and health-environment interactions. ...

Work-life balance culture, work-home interaction, and emotional exhaustion: a structural equation modeling approach.

PubMed

Nitzsche, Anika; Pfaff, Holger; Jung, Julia; Driller, Elke

2013-01-01

To examine the relationships among employees' emotional exhaustion, positive and negative work-home interaction, and perceived work-life balance culture in companies. Data for this study were collected through online surveys of employees from companies in the micro- and nanotechnology sectors (N = 509). A structural equation modeling analysis was performed. A company culture perceived by employees as supportive of their work-life balance was found to have both a direct negative effect on emotional exhaustion and an indirect negative effect meditated by negative work-home interaction. In addition, whereas negative work-home interaction associated positively with emotional exhaustion, positive work-home interaction had no significant effect. The direct and indirect relationship between work-life balance culture and emotional exhaustion has practical implications for health promotion in companies.

Anxiolytic effects of aniracetam in three different mouse models of anxiety and the underlying mechanism.

PubMed

Nakamura, K; Kurasawa, M

2001-05-18

The anxiolytic effects of aniracetam have not been proven in animals despite its clinical usefulness for post-stroke anxiety. This study, therefore, aimed to characterize the anxiolytic effects of aniracetam in different anxiety models using mice and to examine the mode of action. In a social interaction test in which all classes (serotonergic, cholinergic and dopaminergic) of compounds were effective, aniracetam (10-100 mg/kg) increased total social interaction scores (time and frequency), and the increase in the total social interaction time mainly reflected an increase in trunk sniffing and following. The anxiolytic effects were completely blocked by haloperidol and nearly completely by mecamylamine or ketanserin, suggesting an involvement of nicotinic acetylcholine, 5-HT2A and dopamine D2 receptors in the anxiolytic mechanism. Aniracetam also showed anti-anxiety effects in two other anxiety models (elevated plus-maze and conditioned fear stress tests), whereas diazepam as a positive control was anxiolytic only in the elevated plus-maze and social interaction tests. The anxiolytic effects of aniracetam in each model were mimicked by different metabolites (i.e., p-anisic acid in the elevated plus-maze test) or specific combinations of metabolites. These results indicate that aniracetam possesses a wide range of anxiolytic properties, which may be mediated by an interaction between cholinergic, dopaminergic and serotonergic systems. Thus, our findings suggest the potential usefulness of aniracetam against various types of anxiety-related disorders and social failure/impairments.

Weak Interaction Models with New Quarks and Right-handed Currents

DOE R&D Accomplishments Database

Wilczek, F. A.; Zee, A.; Kingsley, R. L.; Treiman, S. B.

1975-06-01

We discuss various weak interaction issues for a general class of models within the SU(2) x U(1) gauge theory framework, with special emphasis on the effects of right-handed, charged currents and of quarks bearing new quantum numbers. In particular we consider the restrictions on model building which are imposed by the small KL - KS mass difference and by the .I = = rule; and we classify various possibilities for neutral current interactions and, in the case of heavy mesons with new quantum numbers, various possibilities for mixing effects analogous to KL - KS mixing.

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.

Effects of molecular model, ionic strength, divalent ions, and hydrophobic interaction on human neurofilament conformation

NASA Astrophysics Data System (ADS)

Lee, Joonseong; Kim, Seonghoon; Chang, Rakwoo; Jayanthi, Lakshmi; Gebremichael, Yeshitila

2013-01-01

The present study examines the effects of the model dependence, ionic strength, divalent ions, and hydrophobic interaction on the structural organization of the human neurofilament (NF) brush, using canonical ensemble Monte Carlo (MC) simulations of a coarse-grained model with the amino-acid resolution. The model simplifies the interactions between the NF core and the sidearm or between the sidearms by the sum of excluded volume, electrostatic, and hydrophobic interactions, where both monovalent salt ions and solvents are implicitly incorporated into the electrostatic interaction potential. Several important observations are made from the MC simulations of the coarse-grained model NF systems. First, the mean-field type description of monovalent salt ions works reasonably well in the NF system. Second, the manner by which the NF sidearms are arranged on the surface of the NF backbone core has little influence on the lateral extension of NF sidearms. Third, the lateral extension of the NF sidearms is highly affected by the ionic strength of the system: at low ionic strength, NF-M is most extended but at high ionic strength, NF-H is more stretched out because of the effective screening of the electrostatic interaction. Fourth, the presence of Ca2 + ions induces the attraction between negatively charged residues, which leads to the contraction of the overall NF extension. Finally, the introduction of hydrophobic interaction does not change the general structural organization of the NF sidearms except that the overall extension is contracted.

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.

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.

Influence of evolution on the stability of ecological communities.

PubMed

Loeuille, Nicolas

2010-12-01

In randomly assembled communities, diversity is known to have a destabilizing effect. Evolution may affect this result, but our theoretical knowledge of its role is mostly limited to models of small food webs. In the present article, I introduce evolution in a two-species Lotka-Volterra model in which I vary the interaction type and the cost constraining evolution. Regardless of the cost type, evolution tends to stabilize the dynamics more often in trophic interactions than for mutualism or competition. I then use simulations to study the effect of evolution in larger communities that contain all interaction types. Results suggest that evolution usually stabilizes the dynamics. This stabilizing effect is stronger when evolution affects trophic interactions, but happens for all interaction types. Stabilization decreases with diversity and evolution becomes destabilizing in very diverse communities. This suggests that evolution may not counteract the destabilizing effect of diversity observed in random communities. © 2010 Blackwell Publishing Ltd/CNRS.

Magneto-elastic modeling of composites containing chain-structured magnetostrictive particles

NASA Astrophysics Data System (ADS)

Yin, H. M.; Sun, L. Z.; Chen, J. S.

2006-05-01

Magneto-elastic behavior is investigated for two-phase composites containing chain-structured magnetostrictive particles under both magnetic and mechanical loading. To derive the local magnetic and elastic fields, three modified Green's functions are derived and explicitly integrated for the infinite domain containing a spherical inclusion with a prescribed magnetization, body force, and eigenstrain. A representative volume element containing a chain of infinite particles is introduced to solve averaged magnetic and elastic fields in the particles and the matrix. Effective magnetostriction of composites is derived by considering the particle's magnetostriction and the magnetic interaction force. It is shown that there exists an optimal choice of the Young's modulus of the matrix and the volume fraction of the particles to achieve the maximum effective magnetostriction. A transversely isotropic effective elasticity is derived at the infinitesimal deformation. Disregarding the interaction term, this model provides the same effective elasticity as Mori-Tanaka's model. Comparisons of model results with the experimental data and other models show the efficacy of the model and suggest that the particle interactions have a considerable effect on the effective magneto-elastic properties of composites even for a low particle volume fraction.

Effects of septum and pericardium on heart-lung interactions in a cardiopulmonary simulation model.

PubMed

Karamolegkos, Nikolaos; Albanese, Antonio; Chbat, Nicolas W

2017-07-01

Mechanical heart-lung interactions are often overlooked in clinical settings. However, their impact on cardiac function can be quite significant. Mechanistic physiology-based models can provide invaluable insights into such cardiorespiratory interactions, which occur not only under external mechanical ventilatory support but in normal physiology as well. In this work, we focus on the cardiac component of a previously developed mathematical model of the human cardiopulmonary system, aiming to improve the model's response to the intrathoracic pressure variations that are associated with the respiratory cycle. Interventricular septum and pericardial membrane are integrated into the existing model. Their effect on the overall cardiac response is explained by means of comparison against simulation results from the original model as well as experimental data from literature.

Bayesian GGE biplot models applied to maize multi-environments trials.

PubMed

de Oliveira, L A; da Silva, C P; Nuvunga, J J; da Silva, A Q; Balestre, M

2016-06-17

The additive main effects and multiplicative interaction (AMMI) and the genotype main effects and genotype x environment interaction (GGE) models stand out among the linear-bilinear models used in genotype x environment interaction studies. Despite the advantages of their use to describe genotype x environment (AMMI) or genotype and genotype x environment (GGE) interactions, these methods have known limitations that are inherent to fixed effects models, including difficulty in treating variance heterogeneity and missing data. Traditional biplots include no measure of uncertainty regarding the principal components. The present study aimed to apply the Bayesian approach to GGE biplot models and assess the implications for selecting stable and adapted genotypes. Our results demonstrated that the Bayesian approach applied to GGE models with non-informative priors was consistent with the traditional GGE biplot analysis, although the credible region incorporated into the biplot enabled distinguishing, based on probability, the performance of genotypes, and their relationships with the environments in the biplot. Those regions also enabled the identification of groups of genotypes and environments with similar effects in terms of adaptability and stability. The relative position of genotypes and environments in biplots is highly affected by the experimental accuracy. Thus, incorporation of uncertainty in biplots is a key tool for breeders to make decisions regarding stability selection and adaptability and the definition of mega-environments.

Quantitative model for the blood pressure-lowering interaction of valsartan and amlodipine.

PubMed

Heo, Young-A; Holford, Nick; Kim, Yukyung; Son, Mijeong; Park, Kyungsoo

2016-12-01

The objective of this study was to develop a population pharmacokinetic (PK) and pharmacodynamic (PD) model to quantitatively describe the antihypertensive effect of combined therapy with amlodipine and valsartan. PK modelling was used with data collected from 48 healthy volunteers receiving a single dose of combined formulation of 10 mg amlodipine and 160 mg valsartan. Systolic (SBP) and diastolic blood pressure (DBP) were recorded during combined administration. SBP and DBP data for each drug alone were gathered from the literature. PKPD models of each drug and for combined administration were built with NONMEM 7.3. A two-compartment model with zero order absorption best described the PK data of both drugs. Amlodipine and valsartan monotherapy effects on SBP and DBP were best described by an I max model with an effect compartment delay. Combined therapy was described using a proportional interaction term as follows: (D 1  + D 2 ) +ALPHA×(D 1 × D 2 ). D 1 and D 2 are the predicted drug effects of amlodipine and valsartan monotherapy respectively. ALPHA is the interaction term for combined therapy. Quantitative estimates of ALPHA were -0.171 (95% CI: -0.218, -0.143) for SBP and -0.0312 (95% CI: -0.07739, -0.00283) for DBP. These infra-additive interaction terms for both SBP and DBP were consistent with literature results for combined administration of drugs in these classes. PKPD models for SBP and DBP successfully described the time course of the antihypertensive effects of amlodipine and valsartan. An infra-additive interaction between amlodipine and valsartan when used in combined administration was confirmed and quantified. © 2016 The British Pharmacological Society.

Quantitative model for the blood pressure‐lowering interaction of valsartan and amlodipine

PubMed Central

Heo, Young‐A; Holford, Nick; Kim, Yukyung; Son, Mijeong

2016-01-01

Aims The objective of this study was to develop a population pharmacokinetic (PK) and pharmacodynamic (PD) model to quantitatively describe the antihypertensive effect of combined therapy with amlodipine and valsartan. Methods PK modelling was used with data collected from 48 healthy volunteers receiving a single dose of combined formulation of 10 mg amlodipine and 160 mg valsartan. Systolic (SBP) and diastolic blood pressure (DBP) were recorded during combined administration. SBP and DBP data for each drug alone were gathered from the literature. PKPD models of each drug and for combined administration were built with NONMEM 7.3. Results A two‐compartment model with zero order absorption best described the PK data of both drugs. Amlodipine and valsartan monotherapy effects on SBP and DBP were best described by an I max model with an effect compartment delay. Combined therapy was described using a proportional interaction term as follows: (D1 + D2) +ALPHA×(D1 × D2). D1 and D2 are the predicted drug effects of amlodipine and valsartan monotherapy respectively. ALPHA is the interaction term for combined therapy. Quantitative estimates of ALPHA were −0.171 (95% CI: −0.218, −0.143) for SBP and −0.0312 (95% CI: −0.07739, −0.00283) for DBP. These infra‐additive interaction terms for both SBP and DBP were consistent with literature results for combined administration of drugs in these classes. Conclusion PKPD models for SBP and DBP successfully described the time course of the antihypertensive effects of amlodipine and valsartan. An infra‐additive interaction between amlodipine and valsartan when used in combined administration was confirmed and quantified. PMID:27504853

Non-equilibrium effects of diatomic and polyatomic gases on the shock-vortex interaction based on the second-order constitutive model of the Boltzmann-Curtiss equation

NASA Astrophysics Data System (ADS)

Singh, S.; Karchani, A.; Myong, R. S.

2018-01-01

The rotational mode of molecules plays a critical role in the behavior of diatomic and polyatomic gases away from equilibrium. In order to investigate the essence of the non-equilibrium effects, the shock-vortex interaction problem was investigated by employing an explicit modal discontinuous Galerkin method. In particular, the first- and second-order constitutive models for diatomic and polyatomic gases derived rigorously from the Boltzmann-Curtiss kinetic equation were solved in conjunction with the physical conservation laws. As compared with a monatomic gas, the non-equilibrium effects result in a substantial change in flow fields in both macroscale and microscale shock-vortex interactions. Specifically, the computational results showed three major effects of diatomic and polyatomic gases on the shock-vortex interaction: (i) the generation of the third sound waves and additional reflected shock waves with strong and enlarged expansion, (ii) the dominance of viscous vorticity generation, and (iii) an increase in enstrophy with increasing bulk viscosity, related to the rotational mode of gas molecules. Moreover, it was shown that there is a significant discrepancy in flow fields between the microscale and macroscale shock-vortex interactions in diatomic and polyatomic gases. The quadrupolar acoustic wave source structures, which are typically observed in macroscale shock-vortex interactions, were not found in any microscale shock-vortex interactions. The physics of the shock-vortex interaction was also investigated in detail to examine vortex deformation and evolution dynamics over an incident shock wave. A comparative study of first- and second-order constitutive models was also conducted for the enstrophy and dissipation rate. Finally, the study was extended to the shock-vortex pair interaction case to examine the effects of pair interaction on vortex deformation and evolution dynamics.

A numerical study of neutral-plasma interaction in magnetically confined plasmas

NASA Astrophysics Data System (ADS)

Taheri, S.; Shumlak, U.; King, J. R.

2017-10-01

Interactions between plasma and neutral species can have a large effect on the dynamic behavior of magnetically confined plasma devices, such as the edge region of tokamaks and the plasma formation of Z-pinches. The presence of neutrals can affect the stability of the pinch and change the dynamics of the pinch collapse, and they can lead to deposition of high energy particles on the first wall. However, plasma-neutral interactions can also have beneficial effects such as quenching the disruptions in tokamaks. In this research a reacting plasma-neutral model, which combines a magnetohydrodynamic (MHD) plasma model with a gas dynamic neutral fluid model, is used to study the interaction between plasma and neutral gas. Incorporating this model into NIMROD allows the study of electron-impact ionization, radiative recombination, and resonant charge-exchange in plasma-neutral systems. An accelerated plasma moving through a neutral gas background is modeled in both a parallel plate and a coaxial electrode configuration to explore the effect of neutral gas in pinch-like devices. This work is supported by a Grant from US DOE.

Propulsion and airframe aerodynamic interactions of supersonic V/STOL configurations. Volume 2: Wind tunnel test force and moment data report

NASA Technical Reports Server (NTRS)

Zilz, D. 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 2 of 2: Wind Tunnel Test Force and Moment Data Report.

Aerodynamic Interaction Effects of a Helicopter Rotor and Fuselage

NASA Technical Reports Server (NTRS)

Boyd, David D., Jr.

1999-01-01

A three year Cooperative Research Agreements made in each of the three years between the Subsonic Aerodynamics Branch of the NASA Langley Research Center and the Virginia Polytechnic Institute and State University (Va. Tech) has been completed. This document presents results from this three year endeavor. The goal of creating an efficient method to compute unsteady interactional effects between a helicopter rotor and fuselage has been accomplished. This paper also includes appendices to support these findings. The topics are: 1) Rotor-Fuselage Interactions Aerodynamics: An Unsteady Rotor Model; and 2) Rotor/Fuselage Unsteady Interactional Aerodynamics: A New Computational Model.

Modulation of additive and interactive effects in lexical decision by trial history.

PubMed

Masson, Michael E J; Kliegl, Reinhold

2013-05-01

Additive and interactive effects of word frequency, stimulus quality, and semantic priming have been used to test theoretical claims about the cognitive architecture of word-reading processes. Additive effects among these factors have been taken as evidence for discrete-stage models of word reading. We present evidence from linear mixed-model analyses applied to 2 lexical decision experiments indicating that apparent additive effects can be the product of aggregating over- and underadditive interaction effects that are modulated by recent trial history, particularly the lexical status and stimulus quality of the previous trial's target. Even a simple practice effect expressed as improved response speed across trials was powerfully modulated by the nature of the previous target item. These results suggest that additivity and interaction between factors may reflect trial-to-trial variation in stimulus representations and decision processes rather than fundamental differences in processing architecture.

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.

Mirror energy difference and the structure of loosely bound proton-rich nuclei around A =20

NASA Astrophysics Data System (ADS)

Yuan, Cenxi; Qi, Chong; Xu, Furong; Suzuki, Toshio; Otsuka, Takaharu

2014-04-01

The properties of loosely bound proton-rich nuclei around A =20 are investigated within the framework of the nuclear shell model. In these nuclei, the strength of the effective interactions involving the loosely bound proton s1/2 orbit is significantly reduced in comparison with that of those in their mirror nuclei. We evaluate the reduction of the effective interaction by calculating the monopole-based-universal interaction (VMU) in the Woods-Saxon basis. The shell-model Hamiltonian in the sd shell, such as USD, can thus be modified to reproduce the binding energies and energy levels of the weakly bound proton-rich nuclei around A =20. The effect of the reduction of the effective interaction on the structure and decay properties of these nuclei is also discussed.

Electric Propulsion Interactions Code (EPIC): Recent Enhancements and Goals for Future Capabilities

NASA Technical Reports Server (NTRS)

Gardner, Barbara M.; Kuharski, Robert A.; Davis, Victoria A.; Ferguson, Dale C.

2007-01-01

The Electric Propulsion Interactions Code (EPIC) is the leading interactive computer tool for assessing the effects of electric thruster plumes on spacecraft subsystems. EPIC, developed by SAIC under the sponsorship of the Space Environments and Effects (SEE) Program at the NASA Marshall Space Flight Center, has three primary modules. One is PlumeTool, which calculates plumes of electrostatic thrusters and Hall-effect thrusters by modeling the primary ion beam as well as elastic scattering and charge-exchange of beam ions with thruster-generated neutrals. ObjectToolkit is a 3-D object definition and spacecraft surface modeling tool developed for use with several SEE Program codes. The main EPIC interface integrates the thruster plume into the 3-D geometry of the spacecraft and calculates interactions and effects of the plume with the spacecraft. Effects modeled include erosion of surfaces due to sputtering, re-deposition of sputtered materials, surface heating, torque on the spacecraft, and changes in surface properties due to erosion and deposition. In support of Prometheus I (JIMO), a number of new capabilities and enhancements were made to existing EPIC models. Enhancements to EPIC include adding the ability to scale and view individual plume components, to import a neutral plume associated with a thruster (to model a grid erosion plume, for example), and to calculate the plume from new initial beam conditions. Unfortunately, changes in program direction have left a number of desired enhancements undone. Variable gridding over a surface and resputtering of deposited materials, including multiple bounces and sticking coefficients, would significantly enhance the erosion/deposition model. Other modifications such as improving the heating model and the PlumeTool neutral plume model, enabling time dependent surface interactions, and including EM1 and optical effects would enable EPIC to better serve the aerospace engineer and electric propulsion systems integrator. We review EPIC S overall capabilities and recent modifications, and discuss directions for future enhancements.

Interaction of rate- and size-effect using a dislocation density based strain gradient viscoplasticity model

NASA Astrophysics Data System (ADS)

Nguyen, Trung N.; Siegmund, Thomas; Tomar, Vikas; Kruzic, Jamie J.

2017-12-01

Size effects occur in non-uniform plastically deformed metals confined in a volume on the scale of micrometer or sub-micrometer. Such problems have been well studied using strain gradient rate-independent plasticity theories. Yet, plasticity theories describing the time-dependent behavior of metals in the presence of size effects are presently limited, and there is no consensus about how the size effects vary with strain rates or whether there is an interaction between them. This paper introduces a constitutive model which enables the analysis of complex load scenarios, including loading rate sensitivity, creep, relaxation and interactions thereof under the consideration of plastic strain gradient effects. A strain gradient viscoplasticity constitutive model based on the Kocks-Mecking theory of dislocation evolution, namely the strain gradient Kocks-Mecking (SG-KM) model, is established and allows one to capture both rate and size effects, and their interaction. A formulation of the model in the finite element analysis framework is derived. Numerical examples are presented. In a special virtual creep test with the presence of plastic strain gradients, creep rates are found to diminish with the specimen size, and are also found to depend on the loading rate in an initial ramp loading step. Stress relaxation in a solid medium containing cylindrical microvoids is predicted to increase with decreasing void radius and strain rate in a prior ramp loading step.

A numerical study on the effects of wave-current-surge interactions on the height and propagation of sea surface waves in Charleston Harbor during Hurricane Hugo 1989

NASA Astrophysics Data System (ADS)

Liu, Huiqing; Xie, Lian

2009-06-01

The effects of wave-current interactions on ocean surface waves induced by Hurricane Hugo in and around the Charleston Harbor and its adjacent coastal waters are examined by using a three-dimensional (3D) wave-current coupled modeling system. The 3D storm surge modeling component of the coupled system is based on the Princeton Ocean Model (POM), the wave modeling component is based on the third generation wave model, Simulating WAves Nearshore (SWAN), and the inundation model is adopted from [Xie, L., Pietrafesa, L. J., Peng, M., 2004. Incorporation of a mass-conserving inundation scheme into a three-dimensional storm surge model. J. Coastal Res., 20, 1209-1223]. The results indicate that the change of water level associated with the storm surge is the primary cause for wave height changes due to wave-surge interaction. Meanwhile, waves propagating on top of surge cause a feedback effect on the surge height by modulating the surface wind stress and bottom stress. This effect is significant in shallow coastal waters, but relatively small in offshore deep waters. The influence of wave-current interaction on wave propagation is relatively insignificant, since waves generally propagate in the direction of the surface currents driven by winds. Wave-current interactions also affect the surface waves as a result of inundation and drying induced by the storm. Waves break as waters retreat in regions of drying, whereas waves are generated in flooded regions where no waves would have occurred without the flood water.

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

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.

Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm

PubMed Central

Yu, Isseki; Mori, Takaharu; Ando, Tadashi; Harada, Ryuhei; Jung, Jaewoon; Sugita, Yuji; Feig, Michael

2016-01-01

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology. DOI: http://dx.doi.org/10.7554/eLife.19274.001 PMID:27801646

A coarse-grained model of the effective interaction for charged amino acid residues and its application to formation of GCN4-pLI tetramer

NASA Astrophysics Data System (ADS)

Kawaguchi, Kazutomo; Nakagawa, Satoshi; Kurniawan, Isman; Kodama, Koichi; Arwansyah, Muhammad Saleh; Nagao, Hidemi

2018-03-01

We present a simple coarse-grained model of the effective interaction for charged amino acid residues, such as Glu and Lys, in a water solvent. The free-energy profile as a function of the distance between two charged amino acid side-chain analogues in an explicit water solvent is calculated with all-atom molecular dynamics simulation and thermodynamic integration method. The calculated free-energy profile is applied to the coarse-grained potential of the effective interaction between two amino acid residues. The Langevin dynamics simulations with our coarse-grained potential are performed for association of a small protein complex, GCN4-pLI tetramer. The tetramer conformation reproduced by our coarse-grained model is similar to the X-ray crystallographic structure. We show that the effective interaction between charged amino acid residues stabilises association and orientation of protein complex. We also investigate the association pathways of GCN4-pLI tetramer.

Interaction of the sonic boom with atmospheric turbulence

NASA Technical Reports Server (NTRS)

Rusak, Zvi; Cole, Julian D.

1994-01-01

Theoretical research was carried out to study the effect of free-stream turbulence on sonic boom pressure fields. A new transonic small-disturbance model to analyze the interactions of random disturbances with a weak shock was developed. The model equation has an extended form of the classic small-disturbance equation for unsteady transonic aerodynamics. An alternative approach shows that the pressure field may be described by an equation that has an extended form of the classic nonlinear acoustics equation that describes the propagation of sound beams with narrow angular spectrum. The model shows that diffraction effects, nonlinear steepening effects, focusing and caustic effects and random induced vorticity fluctuations interact simultaneously to determine the development of the shock wave in space and time and the pressure field behind it. A finite-difference algorithm to solve the mixed type elliptic-hyperbolic flows around the shock wave was also developed. Numerical calculations of shock wave interactions with various deterministic and random fluctuations will be presented in a future report.

Estimating Latent Variable Interactions With Non-Normal Observed Data: A Comparison of Four Approaches

PubMed Central

Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S.

2012-01-01

A Monte Carlo simulation was conducted to investigate the robustness of four latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of non-normality of the observed exogenous variables. Results showed that the CPI and LMS approaches yielded biased estimates of the interaction effect when the exogenous variables were highly non-normal. When the violation of non-normality was not severe (normal; symmetric with excess kurtosis < 1), the LMS approach yielded the most efficient estimates of the latent interaction effect with the highest statistical power. In highly non-normal conditions, the GAPI and UPI approaches with ML estimation yielded unbiased latent interaction effect estimates, with acceptable actual Type-I error rates for both the Wald and likelihood ratio tests of interaction effect at N ≥ 500. An empirical example illustrated the use of the four approaches in testing a latent variable interaction between academic self-efficacy and positive family role models in the prediction of academic performance. PMID:23457417

Turbulent reacting flow computations including turbulence-chemistry interactions

NASA Technical Reports Server (NTRS)

Narayan, J. R.; Girimaji, S. S.

1992-01-01

A two-equation (k-epsilon) turbulence model has been extended to be applicable for compressible reacting flows. A compressibility correction model based on modeling the dilatational terms in the Reynolds stress equations has been used. A turbulence-chemistry interaction model is outlined. In this model, the effects of temperature and species mass concentrations fluctuations on the species mass production rates are decoupled. The effect of temperature fluctuations is modeled via a moment model, and the effect of concentration fluctuations is included using an assumed beta-pdf model. Preliminary results obtained using this model are presented. A two-dimensional reacting mixing layer has been used as a test case. Computations are carried out using the Navier-Stokes solver SPARK using a finite rate chemistry model for hydrogen-air combustion.

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)

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,…

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…

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.

Mesoscopic Effects in an Agent-Based Bargaining Model in Regular Lattices

PubMed Central

Poza, David J.; Santos, José I.; Galán, José M.; López-Paredes, Adolfo

2011-01-01

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders. PMID:21408019

Mesoscopic effects in an agent-based bargaining model in regular lattices.

PubMed

Poza, David J; Santos, José I; Galán, José M; López-Paredes, Adolfo

2011-03-09

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders.

A latent modeling approach to genotype-phenotype relationships: maternal problem behavior clusters, prenatal smoking, and MAOA genotype.

PubMed

McGrath, L M; Mustanski, B; Metzger, A; Pine, D S; Kistner-Griffin, E; Cook, E; Wakschlag, L S

2012-08-01

This study illustrates the application of a latent modeling approach to genotype-phenotype relationships and gene × environment interactions, using a novel, multidimensional model of adult female problem behavior, including maternal prenatal smoking. The gene of interest is the monoamine oxidase A (MAOA) gene which has been well studied in relation to antisocial behavior. Participants were adult women (N = 192) who were sampled from a prospective pregnancy cohort of non-Hispanic, white individuals recruited from a neighborhood health clinic. Structural equation modeling was used to model a female problem behavior phenotype, which included conduct problems, substance use, impulsive-sensation seeking, interpersonal aggression, and prenatal smoking. All of the female problem behavior dimensions clustered together strongly, with the exception of prenatal smoking. A main effect of MAOA genotype and a MAOA × physical maltreatment interaction were detected with the Conduct Problems factor. Our phenotypic model showed that prenatal smoking is not simply a marker of other maternal problem behaviors. The risk variant in the MAOA main effect and interaction analyses was the high activity MAOA genotype, which is discrepant from consensus findings in male samples. This result contributes to an emerging literature on sex-specific interaction effects for MAOA.

Using Agent Based Modeling (ABM) to Develop Cultural Interaction Simulations

NASA Technical Reports Server (NTRS)

Drucker, Nick; Jones, Phillip N.

2012-01-01

Today, most cultural training is based on or built around "cultural engagements" or discrete interactions between the individual learner and one or more cultural "others". Often, success in the engagement is the end or the objective. In reality, these interactions usually involve secondary and tertiary effects with potentially wide ranging consequences. The concern is that learning culture within a strict engagement context might lead to "checklist" cultural thinking that will not empower learners to understand the full consequence of their actions. We propose the use of agent based modeling (ABM) to collect, store, and, simulating the effects of social networks, promulgate engagement effects over time, distance, and consequence. The ABM development allows for rapid modification to re-create any number of population types, extending the applicability of the model to any requirement for social modeling.

Additive and Interactive Effects of Stimulus Degradation: No Challenge for CDP+

ERIC Educational Resources Information Center

Ziegler, Johannes C.; Perry, Conrad; Zorzi, Marco

2009-01-01

S. O'Malley and D. Besner (2008) showed that additive effects of stimulus degradation and word frequency in reading aloud occur in the presence of nonwords but not in pure word lists. They argued that this dissociation presents a major challenge to interactive computational models of reading aloud and claimed that no currently implemented model is…

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

The effect of anisotropy on the thermodynamics of the interacting holographic dark energy model

NASA Astrophysics Data System (ADS)

Hossienkhani, H.; Jafari, A.; Fayaz, V.; Ramezani, A. H.

2018-02-01

By considering a holographic model for the dark energy in an anisotropic universe, the thermodynamics of a scheme of dark matter and dark energy interaction has been investigated. The results suggest that when holographic dark energy and dark matter evolve separately, each of them remains in thermodynamic equilibrium, therefore the interaction between them may be viewed as a stable thermal fluctuation that brings a logarithmic correction to the equilibrium entropy. Also the relation between the interaction term of the dark components and this thermal fluctuation has been obtained. Additionally, for a cosmological interaction as a free function, the anisotropy effects on the generalized second law of thermodynamics have been studied. By using the latest observational data on the holographic dark energy models as the unification of dark matter and dark energy, the observational constraints have been probed. To do this, we focus on observational determinations of the Hubble expansion rate H( z). Finally, we evaluate the anisotropy effects (although low) on various topics, such as the evolution of the statefinder diagnostic, the distance modulus and the spherical collapse from the holographic dark energy model and compare them with the results of the holographic dark energy of the Friedmann-Robertson-Walker and Λ CDM models.

Genetic background effects in quantitative genetics: gene-by-system interactions.

PubMed

Sardi, Maria; Gasch, Audrey P

2018-04-11

Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype-phenotype relationships across individuals.

The effects of teacher anxiety and modeling on the acquisition of a science teaching skill and concomitant student performance

NASA Astrophysics Data System (ADS)

Koran, John J., Jr.; Koran, Mary Lou

In a study designed to explore the effects of teacher anxiety and modeling on acquisition of a science teaching skill and concomitant student performance, 69 preservice secondary teachers and 295 eighth grade students were randomly assigned to microteaching sessions. Prior to microteaching, teachers were given an anxiety test, then randomly assigned to one of three treatments; a transcript model, a protocol model, or a control condition. Subsequently both teacher and student performance was assessed using written and behavioral measures. Analysis of variance indicated that subjects in the two modeling treatments significantly exceeded performance of control group subjects on all measures of the dependent variable, with the protocol model being generally superior to the transcript model. The differential effects of the modeling treatments were further reflected in student performance. Regression analysis of aptitude-treatment interactions indicated that teacher anxiety scores interacted significantly with instructional treatments, with high anxiety teachers performing best in the protocol modeling treatment. Again, this interaction was reflected in student performance, where students taught by highly anxious teachers performed significantly better when their teachers had received the protocol model. These results were discussed in terms of teacher concerns and a memory model of the effects of anxiety on performance.

Towards a First-Principles Determination of Effective Coulomb Interactions in Correlated Electron Materials: Role of Intershell Interactions

NASA Astrophysics Data System (ADS)

Seth, Priyanka; Hansmann, Philipp; van Roekeghem, Ambroise; Vaugier, Loig; Biermann, Silke

2017-08-01

The determination of the effective Coulomb interactions to be used in low-energy Hamiltonians for materials with strong electronic correlations remains one of the bottlenecks for parameter-free electronic structure calculations. We propose and benchmark a scheme for determining the effective local Coulomb interactions for charge-transfer oxides and related compounds. Intershell interactions between electrons in the correlated shell and ligand orbitals are taken into account in an effective manner, leading to a reduction of the effective local interactions on the correlated shell. Our scheme resolves inconsistencies in the determination of effective interactions as obtained by standard methods for a wide range of materials, and allows for a conceptual understanding of the relation of cluster model and dynamical mean field-based electronic structure calculations.

Towards a First-Principles Determination of Effective Coulomb Interactions in Correlated Electron Materials: Role of Intershell Interactions.

PubMed

Seth, Priyanka; Hansmann, Philipp; van Roekeghem, Ambroise; Vaugier, Loig; Biermann, Silke

2017-08-04

The determination of the effective Coulomb interactions to be used in low-energy Hamiltonians for materials with strong electronic correlations remains one of the bottlenecks for parameter-free electronic structure calculations. We propose and benchmark a scheme for determining the effective local Coulomb interactions for charge-transfer oxides and related compounds. Intershell interactions between electrons in the correlated shell and ligand orbitals are taken into account in an effective manner, leading to a reduction of the effective local interactions on the correlated shell. Our scheme resolves inconsistencies in the determination of effective interactions as obtained by standard methods for a wide range of materials, and allows for a conceptual understanding of the relation of cluster model and dynamical mean field-based electronic structure calculations.

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

Modelling nuclear effects in neutrino scattering

NASA Astrophysics Data System (ADS)

Leitner, T.; Alvarez-Ruso, L.; Mosel, U.

2006-07-01

We have developed a model to describe the interactions of neutrinos with nucleons and nuclei via charged and neutral currents, focusing on the region of the quasielastic and Δ(1232) peaks. For νN collisions a fully relativistic formalism is used. The extension to finite nuclei has been done in the framework of a coupled-channel BUU transport model where we have studied exclusive channels taking into account in-medium effects and final state interactions.

Modelling non-linear effects of dark energy

NASA Astrophysics Data System (ADS)

Bose, Benjamin; Baldi, Marco; Pourtsidou, Alkistis

2018-04-01

We investigate the capabilities of perturbation theory in capturing non-linear effects of dark energy. We test constant and evolving w models, as well as models involving momentum exchange between dark energy and dark matter. Specifically, we compare perturbative predictions at 1-loop level against N-body results for four non-standard equations of state as well as varying degrees of momentum exchange between dark energy and dark matter. The interaction is modelled phenomenologically using a time dependent drag term in the Euler equation. We make comparisons at the level of the matter power spectrum and the redshift space monopole and quadrupole. The multipoles are modelled using the Taruya, Nishimichi and Saito (TNS) redshift space spectrum. We find perturbation theory does very well in capturing non-linear effects coming from dark sector interaction. We isolate and quantify the 1-loop contribution coming from the interaction and from the non-standard equation of state. We find the interaction parameter ξ amplifies scale dependent signatures in the range of scales considered. Non-standard equations of state also give scale dependent signatures within this same regime. In redshift space the match with N-body is improved at smaller scales by the addition of the TNS free parameter σv. To quantify the importance of modelling the interaction, we create mock data sets for varying values of ξ using perturbation theory. This data is given errors typical of Stage IV surveys. We then perform a likelihood analysis using the first two multipoles on these sets and a ξ=0 modelling, ignoring the interaction. We find the fiducial growth parameter f is generally recovered even for very large values of ξ both at z=0.5 and z=1. The ξ=0 modelling is most biased in its estimation of f for the phantom w=‑1.1 case.

Multiple Stressors and the Functioning of Coral Reefs.

PubMed

Harborne, Alastair R; Rogers, Alice; Bozec, Yves-Marie; Mumby, Peter J

2017-01-03

Coral reefs provide critical services to coastal communities, and these services rely on ecosystem functions threatened by stressors. By summarizing the threats to the functioning of reefs from fishing, climate change, and decreasing water quality, we highlight that these stressors have multiple, conflicting effects on functionally similar groups of species and their interactions, and that the overall effects are often uncertain because of a lack of data or variability among taxa. The direct effects of stressors on links among functional groups, such as predator-prey interactions, are particularly uncertain. Using qualitative modeling, we demonstrate that this uncertainty of stressor impacts on functional groups (whether they are positive, negative, or neutral) can have significant effects on models of ecosystem stability, and reducing uncertainty is vital for understanding changes to reef functioning. This review also provides guidance for future models of reef functioning, which should include interactions among functional groups and the cumulative effect of stressors.

Multiple Stressors and the Functioning of Coral Reefs

NASA Astrophysics Data System (ADS)

Harborne, Alastair R.; Rogers, Alice; Bozec, Yves-Marie; Mumby, Peter J.

2017-01-01

Coral reefs provide critical services to coastal communities, and these services rely on ecosystem functions threatened by stressors. By summarizing the threats to the functioning of reefs from fishing, climate change, and decreasing water quality, we highlight that these stressors have multiple, conflicting effects on functionally similar groups of species and their interactions, and that the overall effects are often uncertain because of a lack of data or variability among taxa. The direct effects of stressors on links among functional groups, such as predator-prey interactions, are particularly uncertain. Using qualitative modeling, we demonstrate that this uncertainty of stressor impacts on functional groups (whether they are positive, negative, or neutral) can have significant effects on models of ecosystem stability, and reducing uncertainty is vital for understanding changes to reef functioning. This review also provides guidance for future models of reef functioning, which should include interactions among functional groups and the cumulative effect of stressors.

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.

Singlet model interference effects with high scale UV physics

DOE PAGES

Dawson, S.; Lewis, I. M.

2017-01-06

One of the simplest extensions of the Standard Model (SM) is the addition of a scalar gauge singlet, S . If S is not forbidden by a symmetry from mixing with the Standard Model Higgs boson, the mixing will generate non-SM rates for Higgs production and decays. Generally, there could also be unknown high energy physics that generates additional effective low energy interactions. We show that interference effects between the scalar resonance of the singlet model and the effective field theory (EFT) operators can have significant effects in the Higgs sector. Here, we examine a non- Z 2 symmetricmore » scalar singlet model and demonstrate that a fit to the 125 GeV Higgs boson couplings and to limits on high mass resonances, S , exhibit an interesting structure and possible large cancellations of effects between the resonance contribution and the new EFT interactions, that invalidate conclusions based on the renormalizable singlet model alone.« less

The Two Faces of Social Interaction Reward in Animal Models of Drug Dependence

PubMed Central

Rawas, Rana El

2016-01-01

Drug dependence is a serious health and social problem. Social factors can modify vulnerability to developing drug dependence, acting as risk factors or protective factors. Whereas stress and peer environment that encourage substance use may increase drug taking, strong attachments between family members and peer environment that do not experience drug use may protect against drug taking and, ultimately, drug dependence. The rewarding effects of drug abuse and social interaction can be evaluated using animal models. In this review we focus on evaluating social interaction reward in the conditioned place preference paradigm. We give an overview of how social interaction, if made available within the drug context, may facilitate, promote and interact with the drug’s effects. However, social interaction, if offered alternatively outside the drug context, may have pronounced protective effects against drug abuse and relapse. We also address the importance of the weight difference parameter between the social partners in determining the positive or “agonistic” versus the hostile or “antagonistic” social interaction. We conclude that understanding social interaction reward and its subsequent effects on drug reward is sorely needed for therapeutic interventions against drug dependence. PMID:26088685

[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.

Effective Potentials for Folding Proteins

NASA Astrophysics Data System (ADS)

Chen, Nan-Yow; Su, Zheng-Yao; Mou, Chung-Yu

2006-02-01

A coarse-grained off-lattice model that is not biased in any way to the native state is proposed to fold proteins. To predict the native structure in a reasonable time, the model has included the essential effects of water in an effective potential. Two new ingredients, the dipole-dipole interaction and the local hydrophobic interaction, are introduced and are shown to be as crucial as the hydrogen bonding. The model allows successful folding of the wild-type sequence of protein G and may have provided important hints to the study of protein folding.

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...

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.

A Comparison of Approaches for the Analysis of Interaction Effects between Latent Variables Using Partial Least Squares Path Modeling

ERIC Educational Resources Information Center

Henseler, Jorg; Chin, Wynne W.

2010-01-01

In social and business sciences, the importance of the analysis of interaction effects between manifest as well as latent variables steadily increases. Researchers using partial least squares (PLS) to analyze interaction effects between latent variables need an overview of the available approaches as well as their suitability. This article…

Pairwise Interaction Extended Point-Particle (PIEP) model for multiphase jets and sedimenting particles

NASA Astrophysics Data System (ADS)

Liu, Kai; Balachandar, S.

2017-11-01

We perform a series of Euler-Lagrange direct numerical simulations (DNS) for multiphase jets and sedimenting particles. The forces the flow exerts on the particles in these two-way coupled simulations are computed using the Basset-Bousinesq-Oseen (BBO) equations. These forces do not explicitly account for particle-particle interactions, even though such pairwise interactions induced by the perturbations from neighboring particles may be important especially when the particle volume fraction is high. Such effects have been largely unaddressed in the literature. Here, we implement the Pairwise Interaction Extended Point-Particle (PIEP) model to simulate the effect of neighboring particle pairs. A simple collision model is also applied to avoid unphysical overlapping of solid spherical particles. The simulation results indicate that the PIEP model provides a more elaborative and complicated movement of the dispersed phase (droplets and particles). Office of Naval Research (ONR) Multidisciplinary University Research Initiative (MURI) project N00014-16-1-2617.

Role of clouds, aerosols, and aerosol-cloud interaction in 20th century simulations with GISS ModelE2

NASA Astrophysics Data System (ADS)

Nazarenko, L.; Rind, D. H.; Bauer, S.; Del Genio, A. D.

2015-12-01

Simulations of aerosols, clouds and their interaction contribute to the major source of uncertainty in predicting the changing Earth's energy and in estimating future climate. Anthropogenic contribution of aerosols affects the properties of clouds through aerosol indirect effects. Three different versions of NASA GISS global climate model are presented for simulation of the twentieth century climate change. All versions have fully interactive tracers of aerosols and chemistry in both the troposphere and stratosphere. All chemical species are simulated prognostically consistent with atmospheric physics in the model and the emissions of short-lived precursors [Shindell et al., 2006]. One version does not include the aerosol indirect effect on clouds. The other two versions include a parameterization of the interactive first indirect aerosol effect on clouds following Menon et al. [2010]. One of these two models has the Multiconfiguration Aerosol Tracker of Mixing state (MATRIX) that permits detailed treatment of aerosol mixing state, size, and aerosol-cloud activation. The main purpose of this study is evaluation of aerosol-clouds interactions and feedbacks, as well as cloud and aerosol radiative forcings, for the twentieth century climate under different assumptions and parameterizations for aerosol, clouds and their interactions in the climate models. The change of global surface air temperature based on linear trend ranges from +0.8°C to +1.2°C between 1850 and 2012. Water cloud optical thickness increases with increasing temperature in all versions with the largest increase in models with interactive indirect effect of aerosols on clouds, which leads to the total (shortwave and longwave) cloud radiative cooling trend at the top of the atmosphere. Menon, S., D. Koch, G. Beig, S. Sahu, J. Fasullo, and D. Orlikowski (2010), Black carbon aerosols and the third polar ice cap, Atmos. Chem. Phys., 10,4559-4571, doi:10.5194/acp-10-4559-2010. Shindell, D., G. Faluvegi, N. Unger, E. Aguilar, G.A. Schmidt, D.M. Koch, S.E. Bauer, and J.R. Miller (2006), Simulations of preindustrial, present-day, and 2100 conditions in the NASA GISS composition and climate model G-PUCCINI, Atmos. Chem. Phys., 6, 4427-4459.

Cosmological constraints on interacting light particles

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

Brust, Christopher; Cui, Yanou; Sigurdson, Kris, E-mail: cbrust@perimeterinstitute.ca, E-mail: yanou.cui@ucr.edu, E-mail: krs@phas.ubc.ca

2017-08-01

Cosmological observations are becoming increasingly sensitive to the effects of light particles in the form of dark radiation (DR) at the time of recombination. The conventional observable of effective neutrino number, N {sub eff}, is insufficient for probing generic, interacting models of DR. In this work, we perform likelihood analyses which allow both free-streaming effective neutrinos (parametrized by N {sub eff}) and interacting effective neutrinos (parametrized by N {sub fld}). We motivate an alternative parametrization of DR in terms of N {sub tot} (total effective number of neutrinos) and f {sub fs} (the fraction of effective neutrinos which are free-streaming),more » which is less degenerate than using N {sub eff} and N {sub fld}. Using the Planck 2015 likelihoods in conjunction with measurements of baryon acoustic oscillations (BAO), we find constraints on the total amount of beyond the Standard Model effective neutrinos (both free-streaming and interacting) of Δ N {sub tot} < 0.39 at 2σ. In addition, we consider the possibility that this scenario alleviates the tensions between early-time and late-time cosmological observations, in particular the measurements of σ{sub 8} (the amplitude of matter power fluctuations at 8 h {sup −1} Mpc), finding a mild preference for interactions among light species. We further forecast the sensitivities of a variety of future experiments, including Advanced ACTPol (a representative CMB Stage-III experiment), CMB Stage-IV, and the Euclid satellite. This study is relevant for probing non-standard neutrino physics as well as a wide variety of new particle physics models beyond the Standard Model that involve dark radiation.« less

A Single-Boundary Accumulator Model of Response Times in an Addition Verification Task

PubMed Central

Faulkenberry, Thomas J.

2017-01-01

Current theories of mathematical cognition offer competing accounts of the interplay between encoding and calculation in mental arithmetic. Additive models propose that manipulations of problem format do not interact with the cognitive processes used in calculation. Alternatively, interactive models suppose that format manipulations have a direct effect on calculation processes. In the present study, we tested these competing models by fitting participants' RT distributions in an arithmetic verification task with a single-boundary accumulator model (the shifted Wald distribution). We found that in addition to providing a more complete description of RT distributions, the accumulator model afforded a potentially more sensitive test of format effects. Specifically, we found that format affected drift rate, which implies that problem format has a direct impact on calculation processes. These data give further support for an interactive model of mental arithmetic. PMID:28769853

A Computer Model of the Cardiovascular System for Effective Learning.

ERIC Educational Resources Information Center

Rothe, Carl F.

1980-01-01

Presents a model of the cardiovascular system which solves a set of interacting, possibly nonlinear, differential equations. Figures present a schematic diagram of the model and printouts that simulate normal conditions, exercise, hemorrhage, reduced contractility. The nine interacting equations used to describe the system are described in the…

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

Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data.

PubMed

Sariyar, Murat; Hoffmann, Isabell; Binder, Harald

2014-02-26

Molecular data, e.g. arising from microarray technology, is often used for predicting survival probabilities of patients. For multivariate risk prediction models on such high-dimensional data, there are established techniques that combine parameter estimation and variable selection. One big challenge is to incorporate interactions into such prediction models. In this feasibility study, we present building blocks for evaluating and incorporating interactions terms in high-dimensional time-to-event settings, especially for settings in which it is computationally too expensive to check all possible interactions. We use a boosting technique for estimation of effects and the following building blocks for pre-selecting interactions: (1) resampling, (2) random forests and (3) orthogonalization as a data pre-processing step. In a simulation study, the strategy that uses all building blocks is able to detect true main effects and interactions with high sensitivity in different kinds of scenarios. The main challenge are interactions composed of variables that do not represent main effects, but our findings are also promising in this regard. Results on real world data illustrate that effect sizes of interactions frequently may not be large enough to improve prediction performance, even though the interactions are potentially of biological relevance. Screening interactions through random forests is feasible and useful, when one is interested in finding relevant two-way interactions. The other building blocks also contribute considerably to an enhanced pre-selection of interactions. We determined the limits of interaction detection in terms of necessary effect sizes. Our study emphasizes the importance of making full use of existing methods in addition to establishing new ones.

Optimal free descriptions of many-body theories

NASA Astrophysics Data System (ADS)

Turner, Christopher J.; Meichanetzidis, Konstantinos; Papić, Zlatko; Pachos, Jiannis K.

2017-04-01

Interacting bosons or fermions give rise to some of the most fascinating phases of matter, including high-temperature superconductivity, the fractional quantum Hall effect, quantum spin liquids and Mott insulators. Although these systems are promising for technological applications, they also present conceptual challenges, as they require approaches beyond mean-field and perturbation theory. Here we develop a general framework for identifying the free theory that is closest to a given interacting model in terms of their ground-state correlations. Moreover, we quantify the distance between them using the entanglement spectrum. When this interaction distance is small, the optimal free theory provides an effective description of the low-energy physics of the interacting model. Our construction of the optimal free model is non-perturbative in nature; thus, it offers a theoretical framework for investigating strongly correlated systems.

Suspensions of polymer-grafted nanoparticles with added polymers-Structure and effective pair-interactions.

PubMed

Chandran, Sivasurender; Saw, Shibu; Kandar, A K; Dasgupta, C; Sprung, M; Basu, J K

2015-08-28

We present the results of combined experimental and theoretical (molecular dynamics simulations and integral equation theory) studies of the structure and effective interactions of suspensions of polymer grafted nanoparticles (PGNPs) in the presence of linear polymers. Due to the absence of systematic experimental and theoretical studies of PGNPs, it is widely believed that the structure and effective interactions in such binary mixtures would be very similar to those of an analogous soft colloidal material-star polymers. In our study, polystyrene-grafted gold nanoparticles with functionality f = 70 were mixed with linear polystyrene (PS) of two different molecular weights for obtaining two PGNP:PS size ratios, ξ = 0.14 and 2.76 (where, ξ = Mg/Mm, Mg and Mm being the molecular weights of grafting and matrix polymers, respectively). The experimental structure factor of PGNPs could be modeled with an effective potential (Model-X), which has been found to be widely applicable for star polymers. Similarly, the structure factor of the blends with ξ = 0.14 could be modeled reasonably well, while the structure of blends with ξ = 2.76 could not be captured, especially for high density of added polymers. A model (Model-Y) for effective interactions between PGNPs in a melt of matrix polymers also failed to provide good agreement with the experimental data for samples with ξ = 2.76 and high density of added polymers. We tentatively attribute this anomaly in modeling the structure factor of blends with ξ = 2.76 to the questionable assumption of Model-X in describing the added polymers as star polymers with functionality 2, which gets manifested in both polymer-polymer and polymer-PGNP interactions especially at higher fractions of added polymers. The failure of Model-Y may be due to the neglect of possible many-body interactions among PGNPs mediated by matrix polymers when the fraction of added polymers is high. These observations point to the need for a new framework to understand not only the structural behavior of PGNPs but also possibly their dynamics and thermo-mechanical properties as well.

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…

A multi-scale conceptual model of fire and disease interactions in North American forests

NASA Astrophysics Data System (ADS)

Varner, J. M.; Kreye, J. K.; Sherriff, R.; Metz, M.

2013-12-01

One aspect of global change with increasing attention is the interactions between irruptive pests and diseases and wildland fire behavior and effects. These pests and diseases affect fire behavior and effects in spatially and temporally complex ways. Models of fire and pathogen interactions have been constructed for individual pests or diseases, but to date, no synthesis of this complexity has been attempted. Here we synthesize North American fire-pathogen interactions into syndromes with similarities in spatial extent and temporal duration. We base our models on fire interactions with three examples: sudden oak death (caused by the pathogen Phytopthora ramorum) and the native tree tanoak (Notholithocarpus densiflorus); mountain pine beetle (Dendroctonus ponderosae) and western Pinus spp.; and hemlock woolly adelgid (Adelges tsugae) on Tsuga spp. We evaluate each across spatial (severity of attack from branch to landscape scale) and temporal scales (from attack to decades after) and link each change to its coincident effects on fuels and potential fire behavior. These syndromes differ in their spatial and temporal severity, differentially affecting windows of increased or decreased community flammability. We evaluate these models with two examples: the recently emergent ambrosia beetle-vectored laurel wilt (caused by the pathogen Raffaelea lauricola) in native members of the Lauraceae and the early 20th century chestnut blight (caused by the pathogen Cryphonectria parasitica) that led to the decline of American chestnut (Castanea dentata). Some changes (e.g., reduced foliar moisture content) have short-term consequences for potential fire behavior while others (functional extirpation) have more complex indirect effects on community flammability. As non-native emergent diseases and pests continue, synthetic models that aid in prediction of fire behavior and effects will enable the research and management community to prioritize mitigation efforts to realized effects.

Advanced Nonlinear Latent Variable Modeling: Distribution Analytic LMS and QML Estimators of Interaction and Quadratic Effects

ERIC Educational Resources Information Center

Kelava, Augustin; Werner, Christina S.; Schermelleh-Engel, Karin; Moosbrugger, Helfried; Zapf, Dieter; Ma, Yue; Cham, Heining; Aiken, Leona S.; West, Stephen G.

2011-01-01

Interaction and quadratic effects in latent variable models have to date only rarely been tested in practice. Traditional product indicator approaches need to create product indicators (e.g., x[superscript 2] [subscript 1], x[subscript 1]x[subscript 4]) to serve as indicators of each nonlinear latent construct. These approaches require the use of…

Evaluation of Two Methods for Modeling Measurement Errors When Testing Interaction Effects with Observed Composite Scores

ERIC Educational Resources Information Center

Hsiao, Yu-Yu; Kwok, Oi-Man; Lai, Mark H. C.

2018-01-01

Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…

Constraints on non-Standard Model Higgs boson interactions in an effective Lagrangian using differential cross sections measured in the H→γγ decay channel at \\(\\sqrt{s} = 8\\) TeV with the ATLAS detector

DOE PAGES

Aad, G.

2015-12-02

The strength and tensor structure of the Higgs boson's interactions are investigated using an effective Lagrangian, which introduces additional CP-even and CP-odd interactions that lead to changes in the kinematic properties of the Higgs boson and associated jet spectra with respect to the Standard Model. We found that the parameters of the effective Lagrangian are probed using a fit to five differential cross sections previously measured by the ATLAS experiment in the H→γγ decay channel with an integrated luminosity of 20.3 fb -1 at \\(\\sqrt{s} = 8\\) TeV. In order to perform a simultaneous fit to the five distributions, themore » statistical correlations between them are determined by re-analysing the H→γγ candidate events in the proton–proton collision data. No significant deviations from the Standard Model predictions are observed and limits on the effective Lagrangian parameters are derived. These statistical correlations are made publicly available to allow for future analysis of theories with non-Standard Model interactions.« less

Constraints on non-Standard Model Higgs boson interactions in an effective Lagrangian using differential cross sections measured in the H→γγ decay channel at \\(\\sqrt{s} = 8\\) TeV with the ATLAS detector

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

Aad, G.

The strength and tensor structure of the Higgs boson's interactions are investigated using an effective Lagrangian, which introduces additional CP-even and CP-odd interactions that lead to changes in the kinematic properties of the Higgs boson and associated jet spectra with respect to the Standard Model. We found that the parameters of the effective Lagrangian are probed using a fit to five differential cross sections previously measured by the ATLAS experiment in the H→γγ decay channel with an integrated luminosity of 20.3 fb -1 at \\(\\sqrt{s} = 8\\) TeV. In order to perform a simultaneous fit to the five distributions, themore » statistical correlations between them are determined by re-analysing the H→γγ candidate events in the proton–proton collision data. No significant deviations from the Standard Model predictions are observed and limits on the effective Lagrangian parameters are derived. These statistical correlations are made publicly available to allow for future analysis of theories with non-Standard Model interactions.« less

Effects of hydrophobic and dipole-dipole interactions on the conformational transitions of a model polypeptide

NASA Astrophysics Data System (ADS)

Mu, Yan; Gao, Yi Qin

2007-09-01

We studied the effects of hydrophobicity and dipole-dipole interactions between the nearest-neighbor amide planes on the secondary structures of a model polypeptide by calculating the free energy differences between different peptide structures. The free energy calculations were performed with low computational costs using the accelerated Monte Carlo simulation (umbrella sampling) method, with a bias-potential method used earlier in our accelerated molecular dynamics simulations. It was found that the hydrophobic interaction enhances the stability of α helices at both low and high temperatures but stabilizes β structures only at high temperatures at which α helices are not stable. The nearest-neighbor dipole-dipole interaction stabilizes β structures under all conditions, especially in the low temperature region where α helices are the stable structures. Our results indicate clearly that the dipole-dipole interaction between the nearest neighboring amide planes plays an important role in determining the peptide structures. Current research provides a more unified and quantitative picture for understanding the effects of different forms of interactions on polypeptide structures. In addition, the present model can be extended to describe DNA/RNA, polymer, copolymer, and other chain systems.

Community trait overdispersion due to trophic interactions: concerns for assembly process inference

PubMed Central

Petchey, Owen L.

2016-01-01

The expected link between competitive exclusion and community trait overdispersion has been used to infer competition in local communities, and trait clustering has been interpreted as habitat filtering. Such community assembly process inference has received criticism for ignoring trophic interactions, as competition and trophic interactions might create similar trait patterns. While other theoretical studies have generally demonstrated the importance of predation for coexistence, ours provides the first quantitative demonstration of such effects on assembly process inference, using a trait-based ecological model to simulate the assembly of a competitive primary consumer community with and without the influence of trophic interactions. We quantified and contrasted trait dispersion/clustering of the competitive communities with the absence and presence of secondary consumers. Trophic interactions most often decreased trait clustering (i.e. increased dispersion) in the competitive communities due to evenly distributed invasions of secondary consumers and subsequent competitor extinctions over trait space. Furthermore, effects of trophic interactions were somewhat dependent on model parameters and clustering metric. These effects create considerable problems for process inference from trait distributions; one potential solution is to use more process-based and inclusive models in inference. PMID:27733548

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.

Human Birth Weight and Reproductive Immunology: Testing for Interactions between Maternal and Offspring KIR and HLA-C Genes.

PubMed

Clark, Michelle M; Chazara, Olympe; Sobel, Eric M; Gjessing, Håkon K; Magnus, Per; Moffett, Ashley; Sinsheimer, Janet S

2016-01-01

Maternal and offspring cell contact at the site of placentation presents a plausible setting for maternal-fetal genotype (MFG) interactions affecting fetal growth. We test hypotheses regarding killer cell immunoglobulin-like receptor (KIR) and HLA-C MFG effects on human birth weight by extending the quantitative MFG (QMFG) test. Until recently, association testing for MFG interactions had limited applications. To improve the ability to test for these interactions, we developed the extended QMFG test, a linear mixed-effect model that can use multi-locus genotype data from families. We demonstrate the extended QMFG test's statistical properties. We also show that if an offspring-only model is fit when MFG effects exist, associations can be missed or misattributed. Furthermore, imprecisely modeling the effects of both KIR and HLA-C could result in a failure to replicate if these loci's allele frequencies differ among populations. To further illustrate the extended QMFG test's advantages, we apply the extended QMFG test to a UK cohort study and the Norwegian Mother and Child Cohort (MoBa) study. We find a significant KIR-HLA-C interaction effect on birth weight. More generally, the QMFG test can detect genetic associations that may be missed by standard genome-wide association studies for quantitative traits. © 2017 S. Karger AG, Basel.

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.

Study of interactions between metal ions and protein model compounds by energy decomposition analyses and the AMOEBA force field

NASA Astrophysics Data System (ADS)

Jing, Zhifeng; Qi, Rui; Liu, Chengwen; Ren, Pengyu

2017-10-01

The interactions between metal ions and proteins are ubiquitous in biology. The selective binding of metal ions has a variety of regulatory functions. Therefore, there is a need to understand the mechanism of protein-ion binding. The interactions involving metal ions are complicated in nature, where short-range charge-penetration, charge transfer, polarization, and many-body effects all contribute significantly, and a quantitative description of all these interactions is lacking. In addition, it is unclear how well current polarizable force fields can capture these energy terms and whether these polarization models are good enough to describe the many-body effects. In this work, two energy decomposition methods, absolutely localized molecular orbitals and symmetry-adapted perturbation theory, were utilized to study the interactions between Mg2+/Ca2+ and model compounds for amino acids. Comparison of individual interaction components revealed that while there are significant charge-penetration and charge-transfer effects in Ca complexes, these effects can be captured by the van der Waals (vdW) term in the AMOEBA force field. The electrostatic interaction in Mg complexes is well described by AMOEBA since the charge penetration is small, but the distance-dependent polarization energy is problematic. Many-body effects were shown to be important for protein-ion binding. In the absence of many-body effects, highly charged binding pockets will be over-stabilized, and the pockets will always favor Mg and thus lose selectivity. Therefore, many-body effects must be incorporated in the force field in order to predict the structure and energetics of metalloproteins. Also, the many-body effects of charge transfer in Ca complexes were found to be non-negligible. The absorption of charge-transfer energy into the additive vdW term was a main source of error for the AMOEBA many-body interaction energies.

Computational Identification of Diverse Mechanisms Underlying Transcription Factor-DNA Occupancy

PubMed Central

Cheng, Qiong; Kazemian, Majid; Pham, Hannah; Blatti, Charles; Celniker, Susan E.; Wolfe, Scot A.; Brodsky, Michael H.; Sinha, Saurabh

2013-01-01

ChIP-based genome-wide assays of transcription factor (TF) occupancy have emerged as a powerful, high-throughput method to understand transcriptional regulation, especially on a global scale. This has led to great interest in the underlying biochemical mechanisms that direct TF-DNA binding, with the ultimate goal of computationally predicting a TF's occupancy profile in any cellular condition. In this study, we examined the influence of various potential determinants of TF-DNA binding on a much larger scale than previously undertaken. We used a thermodynamics-based model of TF-DNA binding, called “STAP,” to analyze 45 TF-ChIP data sets from Drosophila embryonic development. We built a cross-validation framework that compares a baseline model, based on the ChIP'ed (“primary”) TF's motif, to more complex models where binding by secondary TFs is hypothesized to influence the primary TF's occupancy. Candidates interacting TFs were chosen based on RNA-SEQ expression data from the time point of the ChIP experiment. We found widespread evidence of both cooperative and antagonistic effects by secondary TFs, and explicitly quantified these effects. We were able to identify multiple classes of interactions, including (1) long-range interactions between primary and secondary motifs (separated by ≤150 bp), suggestive of indirect effects such as chromatin remodeling, (2) short-range interactions with specific inter-site spacing biases, suggestive of direct physical interactions, and (3) overlapping binding sites suggesting competitive binding. Furthermore, by factoring out the previously reported strong correlation between TF occupancy and DNA accessibility, we were able to categorize the effects into those that are likely to be mediated by the secondary TF's effect on local accessibility and those that utilize accessibility-independent mechanisms. Finally, we conducted in vitro pull-down assays to test model-based predictions of short-range cooperative interactions, and found that seven of the eight TF pairs tested physically interact and that some of these interactions mediate cooperative binding to DNA. PMID:23935523

Simulation of the Boltzmann Process: An Energy Space Model.

ERIC Educational Resources Information Center

Eger, Martin; Kress, Michael

1982-01-01

A model is introduced for the simulation of Boltzmann-like binary interactions which may be extended to exhibit the effect of angular dependence in the scattering cross section and other dynamical aspects of two-body interactions. (Author/SK)

Effective model with strong Kitaev interactions for α -RuCl3

NASA Astrophysics Data System (ADS)

Suzuki, Takafumi; Suga, Sei-ichiro

2018-04-01

We use an exact numerical diagonalization method to calculate the dynamical spin structure factors of three ab initio models and one ab initio guided model for a honeycomb-lattice magnet α -RuCl3 . We also use thermal pure quantum states to calculate the temperature dependence of the heat capacity, the nearest-neighbor spin-spin correlation function, and the static spin structure factor. From the results obtained from these four effective models, we find that, even when the magnetic order is stabilized at low temperature, the intensity at the Γ point in the dynamical spin structure factors increases with increasing nearest-neighbor spin correlation. In addition, we find that the four models fail to explain heat-capacity measurements whereas two of the four models succeed in explaining inelastic-neutron-scattering experiments. In the four models, when temperature decreases, the heat capacity shows a prominent peak at a high temperature where the nearest-neighbor spin-spin correlation function increases. However, the peak temperature in heat capacity is too low in comparison with that observed experimentally. To address these discrepancies, we propose an effective model that includes strong ferromagnetic Kitaev coupling, and we show that this model quantitatively reproduces both inelastic-neutron-scattering experiments and heat-capacity measurements. To further examine the adequacy of the proposed model, we calculate the field dependence of the polarized terahertz spectra, which reproduces the experimental results: the spin-gapped excitation survives up to an onset field where the magnetic order disappears and the response in the high-field region is almost linear. Based on these numerical results, we argue that the low-energy magnetic excitation in α -RuCl3 is mainly characterized by interactions such as off-diagonal interactions and weak Heisenberg interactions between nearest-neighbor pairs, rather than by the strong Kitaev interactions.

Visual search for conjunctions of physical and numerical size shows that they are processed independently.

PubMed

Sobel, Kenith V; Puri, Amrita M; Faulkenberry, Thomas J; Dague, Taylor D

2017-03-01

The size congruity effect refers to the interaction between numerical magnitude and physical digit size in a symbolic comparison task. Though this effect is well established in the typical 2-item scenario, the mechanisms at the root of the interference remain unclear. Two competing explanations have emerged in the literature: an early interaction model and a late interaction model. In the present study, we used visual conjunction search to test competing predictions from these 2 models. Participants searched for targets that were defined by a conjunction of physical and numerical size. Some distractors shared the target's physical size, and the remaining distractors shared the target's numerical size. We held the total number of search items fixed and manipulated the ratio of the 2 distractor set sizes. The results from 3 experiments converge on the conclusion that numerical magnitude is not a guiding feature for visual search, and that physical and numerical magnitude are processed independently, which supports a late interaction model of the size congruity effect. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Collider effects of unparticle interactions in multiphoton signals

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

Aliev, T. M.; Frank, Mariana; Turan, Ismail

2009-12-01

A new model of physics, with a hidden conformal sector which manifests itself as an unparticle coupling to standard model particles effectively through higher dimensional operators, predicts strong collider signals due to unparticle self-interactions. We perform a complete analysis of the most spectacular of these signals at the hadron collider, pp(p){yields}{gamma}{gamma}{gamma}{gamma} and {gamma}{gamma}gg. These processes can go through the three-point unparticle self-interactions as well as through some s and t channel diagrams with one and/or two unparticle exchanges. We study the contributions of individual diagrams classified with respect to the number of unparticle exchanges and discuss their effect on themore » cross sections at the Tevatron and the LHC. We also restrict the Tevatron bound on the unknown coefficient of the three-point unparticle correlator. With the availability of data from the Tevatron, and the advent of the data emerging from the LHC, these interactions can provide a clear and strong indication of unparticle physics and distinguish this model from other beyond the standard model scenarios.« less

Interactive electromagnetic launcher simulation

NASA Astrophysics Data System (ADS)

Young, F. J.; Howland, H. R.; Hughes, W. F.; Fikse, D. A.

1982-01-01

The mathematical model, usage, and documentation of an interactive computer simulation for an electromagnetic launcher is presented. The launcher is modeled as an electrical circuit. Three slight variations of the program permit studies of a launcher with (1) rail skin effects, (2) rail skin effects and approximated storage coil skin effects, or (3) neither of these effects. Usage of the program as currently implemented on the Westinghouse R&D Univac 1106 is described, with a sample session shown. The implementation of the program permits rapid scoping of the effects of parameter changes.

Latent interaction effects in the theory of planned behaviour applied to quitting smoking.

PubMed

Hukkelberg, Silje Sommer; Hagtvet, Knut A; Kovac, Velibor Bobo

2014-02-01

This study applies three latent interaction models in the theory of planned behaviour (TPB; Ajzen, 1988, Attitudes, personality, and behavior. Homewood, IL: Dorsey Press; Ajzen, 1991, Organ. Behav. Hum. Decis. Process., 50, 179) to quitting smoking: (1) attitude × perceived behavioural control on intention; (2) subjective norms (SN) × attitude on intention; and (3) perceived behavioural control × intention on quitting behaviour. The data derive from a longitudinal Internet survey of 939 smokers aged 15-74 over a period of 4 months. Latent interaction effects were estimated using the double-mean-centred unconstrained approach (Lin et al., 2010, Struct. Equ. Modeling, 17, 374) in LISREL. Attitude × SN and attitude × perceived behavioural control both showed a significant interaction effect on intention. No significant interaction effect was found for perceived behavioural control × intention on quitting. The latent interaction approach is a useful method for investigating specific conditions between TPB components in the context of quitting behaviour. Theoretical and practical implications of the results are discussed. © 2013 The British Psychological Society.

Effect of interactions with the chaperonin cavity on protein folding and misfolding†

PubMed Central

Sirur, Anshul; Knott, Michael; Best, Robert B.

2015-01-01

Recent experimental and computational results have suggested that attractive interactions between a chaperonin and an enclosed substrate can have an important effect on the protein folding rate: it appears that folding may even be slower inside the cavity than under unconfined conditions, in contrast to what we would expect from excluded volume effects on the unfolded state. Here we examine systematically the dependence of the protein stability and folding rate on the strength of such attractive interactions between the chaperonin and substrate, by using molecular simulations of model protein systems in an idealised attractive cavity. Interestingly, we find a maximum in stability, and a rate which indeed slows down at high attraction strengths. We have developed a simple phenomenological model which can explain the variations in folding rate and stability due to differing effects on the free energies of the unfolded state, folded state, and transition state; changes in the diffusion coefficient along the folding coordinate are relatively small, at least for our simplified model. In order to investigate a possible role for these attractive interactions in folding, we have studied a recently developed model for misfolding in multidomain proteins. We find that, while encapsulation in repulsive cavities greatly increases the fraction of misfolded protein, sufficiently strong attractive protein-cavity interactions can strongly reduce the fraction of proteins reaching misfolded traps. PMID:24077053

Using Nucleon Multiplicities to Analyze Anti-Neutrino Interactions with Nuclei

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

Elkins, Miranda J.

The most commonly used, simple interaction models have not accurately described the nuclear effects on either neutrino-nucleus or anti-neutrino-nucleus interactions. Comparison of data collected by the MINERvA experiment and these models shows a discrepancy in the reconstructed hadronic energy distribution at momentum transfers below 0.8 GeV. Two nuclear model effects that were previously not modeled are possible culprits of this discrepancy. The first is known as random-phase-approximation and the second is the addition of a meson exchange current process, also known as two-particle two-hole due to its result in two particles leaving the nucleus with two holes left in theirmore » place. For the first time a neutron counting software algorithm has been created and used to compare the multiplicity and spatial distributions of neutrons between the simulation and data. There is localized sensitivity to the RPA and 2p2h effects and both help the simulation better describe the data. Ad ditional systematic or model effects are present which cause the simulation to overproduce neutrons, and potential causes are discussed.« less

Evaluating wave-current interaction in an urban estuary and flooding implications for coastal communities

NASA Astrophysics Data System (ADS)

Cifuentes-Lorenzen, A.; O'Donnell, J.; Howard-Strobel, M. M.; Fake, T.; McCardell, G.

2016-12-01

Accurate hydrodynamic-wave coupled coastal circulation models aid the prediction of storm impacts, particularly in areas where data is absent, and can inform mitigation options. They are essential everywhere to account for the effects of climate change. Here, the Finite Volume Community Ocean Model (FVCOM) was used to estimate the residual circulation inside a small urban estuary, Long Island Sound, during three severe weather events of different magnitude (i.e. 1/5, 1/25 and 1/50 year events). The effect of including wave coupling using a log-layer bottom boundary and the bottom wave-current coupling, following the approach of Madsen (1994) on the simulated residual circulation was assessed. Significant differences in the solutions were constrained to the near surface (s>-0.3) region. No significant difference in the depth-averaged residual circulation was detected. When the Madsen (1994) bottom boundary layer model for wave-current interaction was employed, differences in residual circulation resulted. The bottom wave-current interaction also plays an important role in the wave dynamics. Significant wave heights along the northern Connecticut shoreline were enhanced by up to 15% when the bottom wave-current interaction was included in the simulations. The wave-induced bottom drag enhancement has a substantial effect on tides in the Sound, possibly because it is nearly resonant at semidiurnal frequencies. This wave-current interaction current leads to severe tidal dampening ( 40% amplitude reduction) at the Western end of the estuary in the modeled sea surface displacement. The potential magnitude of these effects means that wave current interaction should be included and carefully evaluated in models of estuaries that are useful.

Effects of Couple Interactions and Relationship Quality on Plasma Oxytocin and Cardiovascular Reactivity: Empirical Findings and Methodological Considerations

PubMed Central

Smith, Timothy W.; Uchino, Bert N.; MacKenzie, Justin; Hicks, Angela; Campo, Rebecca A.; Reblin, Maija; Grewen, Karen; Amico, Janet A.; Light, Kathleen C.

2016-01-01

Cardiovascular reactivity is a potential mechanism underlying associations of close relationship quality with cardiovascular disease. Two models describe oxytocin as another mechanism. The “calm and connect” model posits an association between positive relationship experiences and oxytocin levels and responses, whereas the “tend and befriend” model emphasizes the effects of negative relationship experiences in evoking oxytocin release. In this study of 180 younger couples, relationship quality had a small, marginally significant inverse association with plasma oxytocin levels, and neither positive nor negative couple interactions evoked change in plasma oxytocin. Negative couple interactions evoked significant cardiovascular reactivity, especially among women. Hence, in the largest study of these issues to date, there was little support for key tenets of the “calm and connect” model, and only very modest support for the ”tend and befriend” model. However, findings were consistent with the view that CVR contributes to the effects of relationship difficulties on health. PMID:22543270

Models of atmosphere-ecosystem-hydrology interactions: Approaches and testing

NASA Technical Reports Server (NTRS)

Schimel, David S.

1992-01-01

Interactions among the atmosphere, terrestrial ecosystems, and the hydrological cycle have been the subject of investigation for many years, although most of the research has had a regional focus. The topic is broad, including the effects of climate and hydrology on vegetation, the effects of vegetation on hydrology, the effects of the hydrological cycle on the atmosphere, and interactions of the cycles via material flux such as solutes and trace gases. The intent of this paper is to identify areas of critical uncertainty, discuss modeling approaches to resolving those problems, and then propose techniques for testing. I consider several interactions specifically to illustrate the range of problems. These areas are as follows: (1) cloud parameterizations and the land surface, (2) soil moisture, and (3) the terrestrial carbon cycle.

Sonic boom interaction with turbulence

NASA Technical Reports Server (NTRS)

Rusak, Zvi; Giddings, Thomas E.

1994-01-01

A recently developed transonic small-disturbance model is used to analyze the interactions of random disturbances with a weak shock. The model equation has an extended form of the classic small-disturbance equation for unsteady transonic aerodynamics. It shows that diffraction effects, nonlinear steepening effects, focusing and caustic effects and random induced vorticity fluctuations interact simultaneously to determine the development of the shock wave in space and time and the pressure field behind it. A finite-difference algorithm to solve the mixed-type elliptic hyperbolic flows around the shock wave is presented. Numerical calculations of shock wave interactions with various deterministic vorticity and temperature disturbances result in complicate shock wave structures and describe peaked as well as rounded pressure signatures behind the shock front, as were recorded in experiments of sonic booms running through atmospheric turbulence.

Development of a recursion RNG-based turbulence model

NASA Technical Reports Server (NTRS)

Zhou, YE; Vahala, George; Thangam, S.

1993-01-01

Reynolds stress closure models based on the recursion renormalization group theory are developed for the prediction of turbulent separated flows. The proposed model uses a finite wavenumber truncation scheme to account for the spectral distribution of energy. In particular, the model incorporates effects of both local and nonlocal interactions. The nonlocal interactions are shown to yield a contribution identical to that from the epsilon-renormalization group (RNG), while the local interactions introduce higher order dispersive effects. A formal analysis of the model is presented and its ability to accurately predict separated flows is analyzed from a combined theoretical and computational stand point. Turbulent flow past a backward facing step is chosen as a test case and the results obtained based on detailed computations demonstrate that the proposed recursion -RNG model with finite cut-off wavenumber can yield very good predictions for the backstep problem.

Ultracold Nonreactive Molecules in an Optical Lattice: Connecting Chemistry to Many-Body Physics.

PubMed

Doçaj, Andris; Wall, Michael L; Mukherjee, Rick; Hazzard, Kaden R A

2016-04-01

We derive effective lattice models for ultracold bosonic or fermionic nonreactive molecules (NRMs) in an optical lattice, analogous to the Hubbard model that describes ultracold atoms in a lattice. In stark contrast to the Hubbard model, which is commonly assumed to accurately describe NRMs, we find that the single on-site interaction parameter U is replaced by a multichannel interaction, whose properties we elucidate. Because this arises from complex short-range collisional physics, it requires no dipolar interactions and thus occurs even in the absence of an electric field or for homonuclear molecules. We find a crossover between coherent few-channel models and fully incoherent single-channel models as the lattice depth is increased. We show that the effective model parameters can be determined in lattice modulation experiments, which, consequently, measure molecular collision dynamics with a vastly sharper energy resolution than experiments in a free-space ultracold gas.

Comparative analysis of methods for detecting interacting loci

PubMed Central

2011-01-01

Background Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. Results We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. Conclusion This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list. PMID:21729295

Comparative analysis of methods for detecting interacting loci.

PubMed

Chen, Li; Yu, Guoqiang; Langefeld, Carl D; Miller, David J; Guy, Richard T; Raghuram, Jayaram; Yuan, Xiguo; Herrington, David M; Wang, Yue

2011-07-05

Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.

A latent modeling approach to genotype–phenotype relationships: maternal problem behavior clusters, prenatal smoking, and MAOA genotype

PubMed Central

Mustanski, B.; Metzger, A.; Pine, D. S.; Kistner-Griffin, E.; Cook, E.; Wakschlag, L. S.

2013-01-01

This study illustrates the application of a latent modeling approach to genotype–phenotype relationships and gene×environment interactions, using a novel, multidimensional model of adult female problem behavior, including maternal prenatal smoking. The gene of interest is the mono-amine oxidase A (MAOA) gene which has been well studied in relation to antisocial behavior. Participants were adult women (N=192) who were sampled from a prospective pregnancy cohort of non-Hispanic, white individuals recruited from a neighborhood health clinic. Structural equation modeling was used to model a female problem behavior phenotype, which included conduct problems, substance use, impulsive-sensation seeking, interpersonal aggression, and prenatal smoking. All of the female problem behavior dimensions clustered together strongly, with the exception of prenatal smoking. A main effect of MAOA genotype and a MAOA× physical maltreatment interaction were detected with the Conduct Problems factor. Our phenotypic model showed that prenatal smoking is not simply a marker of other maternal problem behaviors. The risk variant in the MAOA main effect and interaction analyses was the high activity MAOA genotype, which is discrepant from consensus findings in male samples. This result contributes to an emerging literature on sex-specific interaction effects for MAOA. PMID:22610759

Effects of large vessel on temperature distribution based on photothermal coupling interaction model

NASA Astrophysics Data System (ADS)

Li, Zhifang; Zhang, Xiyang; Li, Zuoran; Li, Hui

2016-10-01

This paper is based on the finite element analysis method for studying effects of large blood vessel on temperature based on photothermal coupling interaction model, and it couples the physical field of optical transmission with the physical field of heat transfer in biological tissue by using COMSOL Multiphysics 4.4 software. The results demonstrate the cooling effect of large blood vessel, which can be potential application for the treatment of liver tumors.

Analysis of weak interactions and Eotvos experiments

NASA Technical Reports Server (NTRS)

Hsu, J. P.

1978-01-01

The intermediate-vector-boson model is preferred over the current-current model as a basis for calculating effects due to weak self-energy. Attention is given to a possible violation of the equivalence principle by weak-interaction effects, and it is noted that effects due to weak self-energy are at least an order of magnitude greater than those due to the weak binding energy for typical nuclei. It is assumed that the weak and electromagnetic energies are independent.

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.

Gene-Environment Interactions in Cardiovascular Disease

PubMed Central

Flowers, Elena; Froelicher, Erika Sivarajan; Aouizerat, Bradley E.

2011-01-01

Background Historically, models to describe disease were exclusively nature-based or nurture-based. Current theoretical models for complex conditions such as cardiovascular disease acknowledge the importance of both biologic and non-biologic contributors to disease. A critical feature is the occurrence of interactions between numerous risk factors for disease. The interaction between genetic (i.e. biologic, nature) and environmental (i.e. non-biologic, nurture) causes of disease is an important mechanism for understanding both the etiology and public health impact of cardiovascular disease. Objectives The purpose of this paper is to describe theoretical underpinnings of gene-environment interactions, models of interaction, methods for studying gene-environment interactions, and the related concept of interactions between epigenetic mechanisms and the environment. Discussion Advances in methods for measurement of genetic predictors of disease have enabled an increasingly comprehensive understanding of the causes of disease. In order to fully describe the effects of genetic predictors of disease, it is necessary to place genetic predictors within the context of known environmental risk factors. The additive or multiplicative effect of the interaction between genetic and environmental risk factors is often greater than the contribution of either risk factor alone. PMID:21684212

Viscous-inviscid calculations of jet entrainment effects on the subsonic flow over nozzle afterbodies

NASA Technical Reports Server (NTRS)

Wilmoth, R. G.

1980-01-01

A viscous-inviscid interaction model was developed to account for jet entrainment effects in the prediction of the subsonic flow over nozzle afterbodies. The model is based on the concept of a weakly interacting shear layer in which the local streamline deflections due to entrainment are accounted for by a displacement-thickness type of correction to the inviscid plume boundary. The entire flow field is solved in an iterative manner to account for the effects on the inviscid external flow of the turbulent boundary layer, turbulent mixing and chemical reactions in the shear layer, and the inviscid jet exhaust flow. The components of the computational model are described, and numerical results are presented to illustrate the interactive effects of entrainment on the overall flow structure. The validity of the model is assessed by comparisons with data obtained form flow-field measurements on cold-air jet exhausts. Numerical results and experimental data are also given to show the entrainment effects on nozzle boattail drag under various jet exhaust and free-stream flow conditions.

Self-assembly kinetics of microscale components: A parametric evaluation

NASA Astrophysics Data System (ADS)

Carballo, Jose M.

The goal of the present work is to develop, and evaluate a parametric model of a basic microscale Self-Assembly (SA) interaction that provides scaling predictions of process rates as a function of key process variables. At the microscale, assembly by "grasp and release" is generally challenging. Recent research efforts have proposed adapting nanoscale self-assembly (SA) processes to the microscale. SA offers the potential for reduced equipment cost and increased throughput by harnessing attractive forces (most commonly, capillary) to spontaneously assemble components. However, there are challenges for implementing microscale SA as a commercial process. The existing lack of design tools prevents simple process optimization. Previous efforts have characterized a specific aspect of the SA process. However, the existing microscale SA models do not characterize the inter-component interactions. All existing models have simplified the outcome of SA interactions as an experimentally-derived value specific to a particular configuration, instead of evaluating it outcome as a function of component level parameters (such as speed, geometry, bonding energy and direction). The present study parameterizes the outcome of interactions, and evaluates the effect of key parameters. The present work closes the gap between existing microscale SA models to add a key piece towards a complete design tool for general microscale SA process modeling. First, this work proposes a simple model for defining the probability of assembly of basic SA interactions. A basic SA interaction is defined as the event where a single part arrives on an assembly site. The model describes the probability of assembly as a function of kinetic energy, binding energy, orientation and incidence angle for the component and the assembly site. Secondly, an experimental SA system was designed, and implemented to create individual SA interactions while controlling process parameters independently. SA experiments measured the outcome of SA interactions, while studying the independent effects of each parameter. As a first step towards a complete scaling model, experiments were performed to evaluate the effects of part geometry and part travel direction under low kinetic energy conditions. Experimental results show minimal dependence of assembly yield on the incidence angle of the parts, and significant effects induced by changes in part geometry. The results from this work indicate that SA could be modeled as an energy-based process due to the small path dependence effects. Assembly probability is linearly related to the orientation probability. The proportionality constant is based on the area fraction of the sites with an amplification factor. This amplification factor accounts for the ability of capillary forces to align parts with only very small areas of contact when they have a low kinetic energy. Results provide unprecedented insight about SA interactions. The present study is a key step towards completing a basic model of a general SA process. Moreover, the outcome from this work can complement existing SA process models, in order to create a complete design tool for microscale SA systems. In addition to SA experiments, Monte Carlo simulations of experimental part-site interactions were conducted. This study confirmed that a major contributor to experimental variation is the stochastic nature of experimental SA interactions and the limited sample size of the experiments. Furthermore, the simulations serve as a tool for defining an optimum sampling strategy to minimize the uncertainty in future SA experiments.

Real beards and real networks: a spin-glass model for interacting individuals

NASA Astrophysics Data System (ADS)

O'Neale, Dion

''I want to be different, just like all the other different people'' sang the band King Missile. Whether they are the Beatniks of the 1950s, the punks of the 1970s, or the hipsters of today, non-conformists often tend to look the same, seemingly at odds with their goal of non-conformity. The spin-glass model, originally developed to describe the interaction of magnetic spins, and since applied to situations as diverse as the electrical activity of networks of neurons, to trades on a financial market, has recently been used in social science to study populations of interacting individuals comprised of a mix of both conformists and anti-conformists - or hipsters. Including delay effects for the interactions between individuals has been shown to give a system with non-trivial dynamics with a phase transition from stable behaviour to periodic switching between two states (let's call them bushy bearded and clean shaven). Analytic solutions to such a model are possible, but only for particular assumptions about the interaction and delay matrices. In this work we will show what happens when the interactions in the model are based on real-world networks with ''small-world'' effects and clustering.

Effective temperature in an interacting vertex system: theory and experiment on artificial spin ice.

PubMed

Nisoli, Cristiano; Li, Jie; Ke, Xianglin; Garand, D; Schiffer, Peter; Crespi, Vincent H

2010-07-23

Frustrated arrays of interacting single-domain nanomagnets provide important model systems for statistical mechanics, as they map closely onto well-studied vertex models and are amenable to direct imaging and custom engineering. Although these systems are manifestly athermal, we demonstrate that an effective temperature, controlled by an external magnetic drive, describes their microstates and therefore their full statistical properties.

Wall Layers

DTIC Science & Technology

1992-01-14

modes. Nonlinearity 4, 697-726. Campbell, S. A . 1991. The Effects of Symmetry on Low Dimensional Modal Interactions. Ph. D. Thesis. (Theoretical and...et aL; they have a ready for submission entitled " Bifurcation from symmetric heteroclinic cycles with three interacting modes". The purpose of this...simple model for the effects of riblets on the growth and form of eigenstructures is under investigation. This model is a straight-forward extension of

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting

PubMed Central

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-01-01

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes. PMID:29453930

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting.

PubMed

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-02-17

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes.

Does Negative Interaction in the Church Increase Psychological Distress? Longitudinal Findings from the Presbyterian Panel Survey*

PubMed Central

Ellison, Christopher G.; Zhang, Wei; Krause, Neal; Marcum, John P.

2009-01-01

This study examines the effects of negative interaction in church on psychological distress. After outlining a series of theoretical arguments linking negative interaction with health and well-being, relevant hypotheses are tested using longitudinal data from two surveys of the 1997–1999 Presbyterian Panel, a nationwide panel of members and elders (lay leaders) in congregations of the Presbyterian Church (USA). Findings confirm that negative interaction appears to foster or exacerbate distress over the study period. In addition, specific dimensions of social negativity have distinctive effects; the impact of criticisms on distress surface only in cross-sectional models, while the effects of excessive demands emerge only in the longitudinal models. No subgroup variations in these effects are detected. Implications of these findings are discussed with regard to (a) research on religion and health and (b) congregational life, and a number of promising directions for future research are elaborated. PMID:20694051

Effective operators in a single-j orbital

NASA Astrophysics Data System (ADS)

Derbali, E.; Van Isacker, P.; Tellili, B.; Souga, C.

2018-03-01

We present an analysis of effective operators in the shell model with up to three-body interactions in the Hamiltonian and two-body terms in electromagnetic transition operators when the nucleons are either neutrons or protons occupying a single-j orbital. We first show that evidence for an effective three-body interaction exists in the N = 50 isotones and in the lead isotopes but that the separate components of such interaction are difficult to obtain empirically. We then determine higher-order terms on more microscopic grounds. The starting point is a realistic two-body interaction in a large shell-model space together with a standard one-body transition operator, which, after restriction to the dominant orbital and with use of stationary perturbation theory, are transformed into effective versions with higher-order terms. An application is presented for the lead isotopes with neutrons in the 1{g}9/2 orbital.

Chemotactic and hydrodynamic effects on collective dynamics of self-diffusiophoretic Janus motors

NASA Astrophysics Data System (ADS)

Huang, Mu-Jie; Schofield, Jeremy; Kapral, Raymond

2017-12-01

Collective motion in nonequilibrium steady state suspensions of self-propelled Janus motors driven by chemical reactions can arise due to interactions coming from direct intermolecular forces, hydrodynamic flow effects, or chemotactic effects mediated by chemical gradients. The relative importance of these interactions depends on the reactive characteristics of the motors, the way in which the system is maintained in a steady state, and properties of the suspension, such as the volume fraction. From simulations of a microscopic hard collision model for the interaction of fluid particles with the Janus motor we show that dynamic cluster states exist and determine the interaction mechanisms that are responsible for their formation. The relative importance of chemotactic and hydrodynamic effects is identified by considering a microscopic model in which chemotactic effects are turned off while the full hydrodynamic interactions are retained. The system is maintained in a steady state by means of a bulk reaction in which product particles are reconverted into fuel particles. The influence of the bulk reaction rate on the collective dynamics is also studied.

The interacting effects of temperature and food chain length on trophic abundance and ecosystem function.

PubMed

Beveridge, Oliver S; Humphries, Stuart; Petchey, Owen L

2010-05-01

1. While much is known about the independent effects of trophic structure and temperature on density and ecosystem processes, less is known about the interaction(s) between the two. 2. We manipulated the temperature of laboratory-based bacteria-protist communities that contained communities with one, two, or three trophic levels, and recorded species' densities and bacterial decomposition. 3. Temperature, food chain length and their interaction produced significant responses in microbial density and bacterial decomposition. Prey and resource density expressed different patterns of temperature dependency during different phases of population dynamics. The addition of a predator altered the temperature-density relationship of prey, from a unimodal trend to a negative one. Bacterial decomposition was greatest in the presence of consumers at higher temperatures. 4. These results are qualitatively consistent with a recent model of direct and indirect temperature effects on resource-consumer population dynamics. Results highlight and reinforce the importance of indirect effects of temperature mediated through trophic interactions. Understanding and predicting the consequences of environmental change will require that indirect effects, trophic structure, and individual species' tolerances be incorporated into theory and models.

Modelling multi-species interactions in the Barents Sea ecosystem with special emphasis on minke whales and their interactions with cod, herring and capelin

NASA Astrophysics Data System (ADS)

Lindstrøm, Ulf; Smout, Sophie; Howell, Daniel; Bogstad, Bjarte

2009-10-01

The Barents Sea ecosystem, one of the most productive and commercially important ecosystems in the world, has experienced major fluctuations in species abundance the past five decades. Likely causes are natural variability, climate change, overfishing and predator-prey interactions. In this study, we use an age-length structured multi-species model (Gadget, Globally applicable Area-Disaggregated General Ecosystem Toolbox) to analyse the historic population dynamics of major fish and marine mammal species in the Barents Sea. The model was used to examine possible effects of a number of plausible biological and fisheries scenarios. The results suggest that changes in cod mortality from fishing or cod cannibalism levels have the largest effect on the ecosystem, while changes to the capelin fishery have had only minor effects. Alternate whale migration scenarios had only a moderate impact on the modelled ecosystem. Indirect effects are seen to be important, with cod fishing pressure, cod cannibalism and whale predation on cod having an indirect impact on capelin, emphasising the importance of multi-species modelling in understanding and managing ecosystems. Models such as the one presented here provide one step towards an ecosystem-based approach to fisheries management.

The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study.

PubMed

Lekman, Magnus; Hössjer, Ola; Andrews, Peter; Källberg, Henrik; Uvehag, Daniel; Charney, Dennis; Manji, Husseini; Rush, John A; McMahon, Francis J; Moore, Jason H; Kockum, Ingrid

2014-01-01

Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e.g. additive dominant model Puncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with Puncorrected = 6.95E-5 with odds ratio (OR estimated from β3) value = 4.99) the area under the curve (AUC) estimates were low (< 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (< 0.15). We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied.

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

Ordered phases in the Holstein-Hubbard model: Interplay of strong Coulomb interaction and electron-phonon coupling

NASA Astrophysics Data System (ADS)

Murakami, Yuta; Werner, Philipp; Tsuji, Naoto; Aoki, Hideo

2013-09-01

We study the Holstein-Hubbard model at half filling to explore ordered phases including superconductivity (SC), antiferromagnetism (AF), and charge order (CO) in situations where the electron-electron and electron-phonon interactions are strong (comparable to the electronic bandwidth). The model is solved in the dynamical mean-field approximation with a continuous-time quantum Monte Carlo impurity solver. We determine the superconducting transition temperature Tc and the SC order parameter and show that the phonon-induced retardation or the strong Coulomb interaction leads to a significant reduction and shift of the Tc dome against the effective electron-electron interaction Ueff given by the Hubbard U reduced by the phonon-mediated attraction in the static limit. This behavior is analyzed by comparison to an effective static model in the polaron representation with a renormalized bandwidth. In addition, we discuss the superconducting gap Δ and 2Δ/Tc to reveal the effect of the retardation and the Coulomb interaction. We also determine the finite-temperature phase diagram including AF and CO. In the moderate-coupling regime, there is a hysteretic region of AF and CO around Ueff=0, while the two phases are separated by a paramagnetic metal in the weak-coupling regime and a paramagnetic insulator in the strong-coupling regime.

Analyzing average and conditional effects with multigroup multilevel structural equation models

PubMed Central

Mayer, Axel; Nagengast, Benjamin; Fletcher, John; Steyer, Rolf

2014-01-01

Conventionally, multilevel analysis of covariance (ML-ANCOVA) has been the recommended approach for analyzing treatment effects in quasi-experimental multilevel designs with treatment application at the cluster-level. In this paper, we introduce the generalized ML-ANCOVA with linear effect functions that identifies average and conditional treatment effects in the presence of treatment-covariate interactions. We show how the generalized ML-ANCOVA model can be estimated with multigroup multilevel structural equation models that offer considerable advantages compared to traditional ML-ANCOVA. The proposed model takes into account measurement error in the covariates, sampling error in contextual covariates, treatment-covariate interactions, and stochastic predictors. We illustrate the implementation of ML-ANCOVA with an example from educational effectiveness research where we estimate average and conditional effects of early transition to secondary schooling on reading comprehension. PMID:24795668

Does the growth response of woody plants to elevated CO2 increase with temperature? A model-oriented meta-analysis.

PubMed

Baig, Sofia; Medlyn, Belinda E; Mercado, Lina M; Zaehle, Sönke

2015-12-01

The temperature dependence of the reaction kinetics of the Rubisco enzyme implies that, at the level of a chloroplast, the response of photosynthesis to rising atmospheric CO2 concentration (Ca ) will increase with increasing air temperature. Vegetation models incorporating this interaction predict that the response of net primary productivity (NPP) to elevated CO2 (eCa ) will increase with rising temperature and will be substantially larger in warm tropical forests than in cold boreal forests. We tested these model predictions against evidence from eCa experiments by carrying out two meta-analyses. Firstly, we tested for an interaction effect on growth responses in factorial eCa  × temperature experiments. This analysis showed a positive, but nonsignificant interaction effect (95% CI for above-ground biomass response = -0.8, 18.0%) between eCa and temperature. Secondly, we tested field-based eCa experiments on woody plants across the globe for a relationship between the eCa effect on plant biomass and mean annual temperature (MAT). This second analysis showed a positive but nonsignificant correlation between the eCa response and MAT. The magnitude of the interactions between CO2 and temperature found in both meta-analyses were consistent with model predictions, even though both analyses gave nonsignificant results. Thus, we conclude that it is not possible to distinguish between the competing hypotheses of no interaction vs. an interaction based on Rubisco kinetics from the available experimental database. Experiments in a wider range of temperature zones are required. Until such experimental data are available, model predictions should aim to incorporate uncertainty about this interaction. © 2015 John Wiley & Sons Ltd.

The influence of interspecific interactions on species range expansion rates

USGS Publications Warehouse

Svenning, Jens-Christian; Gravel, Dominique; Holt, Robert D.; Schurr, Frank M.; Thuiller, Wilfried; Münkemüller, Tamara; Schiffers, Katja H.; Dullinger, Stefan; Edwards, Thomas C.; Hickler, Thomas; Higgins, Steven I.; Nabel, Julia E.M.S.; Pagel, Jörn; Normand, Signe

2014-01-01

Ongoing and predicted global change makes understanding and predicting species’ range shifts an urgent scientific priority. Here, we provide a synthetic perspective on the so far poorly understood effects of interspecific interactions on range expansion rates. We present theoretical foundations for how interspecific interactions may modulate range expansion rates, consider examples from empirical studies of biological invasions and natural range expansions as well as process-based simulations, and discuss how interspecific interactions can be more broadly represented in process-based, spatiotemporally explicit range forecasts. Theory tells us that interspecific interactions affect expansion rates via alteration of local population growth rates and spatial displacement rates, but also via effects on other demographic parameters. The best empirical evidence for interspecific effects on expansion rates comes from studies of biological invasions. Notably, invasion studies indicate that competitive dominance and release from specialized enemies can enhance expansion rates. Studies of natural range expansions especially point to the potential for competition from resident species to reduce expansion rates. Overall, it is clear that interspecific interactions may have important consequences for range dynamics, but also that their effects have received too little attention to robustly generalize on their importance. We then discuss how interspecific interactions effects can be more widely incorporated in dynamic modeling of range expansions. Importantly, models must describe spatiotemporal variation in both local population dynamics and dispersal. Finally, we derive the following guidelines for when it is particularly important to explicitly represent interspecific interactions in dynamic range expansion forecasts: if most interacting species show correlated spatial or temporal trends in their effects on the target species, if the number of interacting species is low, and if the abundance of one or more strongly interacting species is not closely linked to the abundance of the target species.

The influence of interspecific interactions on species range expansion rates.

PubMed

Svenning, Jens-Christian; Gravel, Dominique; Holt, Robert D; Schurr, Frank M; Thuiller, Wilfried; Münkemüller, Tamara; Schiffers, Katja H; Dullinger, Stefan; Edwards, Thomas C; Hickler, Thomas; Higgins, Steven I; Nabel, Julia E M S; Pagel, Jörn; Normand, Signe

2014-12-01

Ongoing and predicted global change makes understanding and predicting species' range shifts an urgent scientific priority. Here, we provide a synthetic perspective on the so far poorly understood effects of interspecific interactions on range expansion rates. We present theoretical foundations for how interspecific interactions may modulate range expansion rates, consider examples from empirical studies of biological invasions and natural range expansions as well as process-based simulations, and discuss how interspecific interactions can be more broadly represented in process-based, spatiotemporally explicit range forecasts. Theory tells us that interspecific interactions affect expansion rates via alteration of local population growth rates and spatial displacement rates, but also via effects on other demographic parameters. The best empirical evidence for interspecific effects on expansion rates comes from studies of biological invasions. Notably, invasion studies indicate that competitive dominance and release from specialized enemies can enhance expansion rates. Studies of natural range expansions especially point to the potential for competition from resident species to reduce expansion rates. Overall, it is clear that interspecific interactions may have important consequences for range dynamics, but also that their effects have received too little attention to robustly generalize on their importance. We then discuss how interspecific interactions effects can be more widely incorporated in dynamic modeling of range expansions. Importantly, models must describe spatiotemporal variation in both local population dynamics and dispersal. Finally, we derive the following guidelines for when it is particularly important to explicitly represent interspecific interactions in dynamic range expansion forecasts: if most interacting species show correlated spatial or temporal trends in their effects on the target species, if the number of interacting species is low, and if the abundance of one or more strongly interacting species is not closely linked to the abundance of the target species.

The influence of interspecific interactions on species range expansion rates

PubMed Central

Svenning, Jens-Christian; Gravel, Dominique; Holt, Robert D.; Schurr, Frank M.; Thuiller, Wilfried; Münkemüller, Tamara; Schiffers, Katja H.; Dullinger, Stefan; Edwards, Thomas C.; Hickler, Thomas; Higgins, Steven I.; Nabel, Julia E. M. S.; Pagel, Jörn; Normand, Signe

2014-01-01

Ongoing and predicted global change makes understanding and predicting species’ range shifts an urgent scientific priority. Here, we provide a synthetic perspective on the so far poorly understood effects of interspecific interactions on range expansion rates. We present theoretical foundations for how interspecific interactions may modulate range expansion rates, consider examples from empirical studies of biological invasions and natural range expansions as well as process-based simulations, and discuss how interspecific interactions can be more broadly represented in process-based, spatiotemporally explicit range forecasts. Theory tells us that interspecific interactions affect expansion rates via alteration of local population growth rates and spatial displacement rates, but also via effects on other demographic parameters. The best empirical evidence for interspecific effects on expansion rates comes from studies of biological invasions. Notably, invasion studies indicate that competitive dominance and release from specialized enemies can enhance expansion rates. Studies of natural range expansions especially point to the potential for competition from resident species to reduce expansion rates. Overall, it is clear that interspecific interactions may have important consequences for range dynamics, but also that their effects have received too little attention to robustly generalize on their importance. We then discuss how interspecific interactions effects can be more widely incorporated in dynamic modeling of range expansions. Importantly, models must describe spatiotemporal variation in both local population dynamics and dispersal. Finally, we derive the following guidelines for when it is particularly important to explicitly represent interspecific interactions in dynamic range expansion forecasts: if most interacting species show correlated spatial or temporal trends in their effects on the target species, if the number of interacting species is low, and if the abundance of one or more strongly interacting species is not closely linked to the abundance of the target species. PMID:25722537

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.

One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information.

PubMed

Hua, Hairui; Burke, Danielle L; Crowther, Michael J; Ensor, Joie; Tudur Smith, Catrin; Riley, Richard D

2017-02-28

Stratified medicine utilizes individual-level covariates that are associated with a differential treatment effect, also known as treatment-covariate interactions. When multiple trials are available, meta-analysis is used to help detect true treatment-covariate interactions by combining their data. Meta-regression of trial-level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta-analyses are preferable to examine interactions utilizing individual-level information. However, one-stage IPD models are often wrongly specified, such that interactions are based on amalgamating within- and across-trial information. We compare, through simulations and an applied example, fixed-effect and random-effects models for a one-stage IPD meta-analysis of time-to-event data where the goal is to estimate a treatment-covariate interaction. We show that it is crucial to centre patient-level covariates by their mean value in each trial, in order to separate out within-trial and across-trial information. Otherwise, bias and coverage of interaction estimates may be adversely affected, leading to potentially erroneous conclusions driven by ecological bias. We revisit an IPD meta-analysis of five epilepsy trials and examine age as a treatment effect modifier. The interaction is -0.011 (95% CI: -0.019 to -0.003; p = 0.004), and thus highly significant, when amalgamating within-trial and across-trial information. However, when separating within-trial from across-trial information, the interaction is -0.007 (95% CI: -0.019 to 0.005; p = 0.22), and thus its magnitude and statistical significance are greatly reduced. We recommend that meta-analysts should only use within-trial information to examine individual predictors of treatment effect and that one-stage IPD models should separate within-trial from across-trial information to avoid ecological bias. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

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.

Elastic interaction among transition metals in one-dimensional spin-crossover solids

NASA Astrophysics Data System (ADS)

Boukheddaden, K.; Miyashita, S.; Nishino, M.

2007-03-01

We present an exact examination of a one-dimensional (1D) spin-phonon model describing the thermodynamical properties of spin-crossover (SC) solids. This model has the advantage of giving a physical mechanism for the interaction between the SC units. The origin of the interaction comes from the fact that the elastic constant of the spring linking two atoms depends on their electronic states. This leads to local variation of the elastic constant. Up to now, all the statistical studies of this model have been performed in the frame of the mean-field (MF) approach, which is not adequate to describe 1D systems with short-range interactions. An alternative method, based on the variational approach and taking into account the short-range correlations between neighboring molecules, was also suggested, but it consists in an extension of the previous MF approximation. Here, we solve exactly this Hamiltonian in the frame of classical statistical mechanics using the transfer-matrix technique. The temperature dependence of the high spin fraction and that of the total energy are obtained analytically. Our results clearly show that there is a clear tendency to a sharp transition when we tune the elastic constants adequately, which indicates that first-order phase transition takes place at higher dimensions. In addition, we demonstrate the existence of an interesting isomorphism between the present model and Ising model under effective interaction and effective ligand field energy, in which both depend linearly on temperature and both come from the phonon contribution. We have also studied the effect of the pressure (the tension) on the thermodynamical properties of the high spin (HS) fraction and have found a nontrivial pressure effect that while for weak tension values, the low spin state is stabilized for the pressure above a threshold value, it enhances the interaction between the HS states. Finally, we have also introduced elastic interactions between the chains. Treating exactly (in mean field) the intrachain (interchain) contributions, we found that our model leads us to obtain first-order spin transitions when both short- and long-range interactions are ferroelastic. We show also that competing (antiferroelastic short-range and ferroelastic long-range) interactions between spin-state ions reproduce qualitatively the two-step-like spin-crossover transitions.

Velocity statistics for interacting edge dislocations in one dimension from Dyson's Coulomb gas model.

PubMed

Jafarpour, Farshid; Angheluta, Luiza; Goldenfeld, Nigel

2013-10-01

The dynamics of edge dislocations with parallel Burgers vectors, moving in the same slip plane, is mapped onto Dyson's model of a two-dimensional Coulomb gas confined in one dimension. We show that the tail distribution of the velocity of dislocations is power law in form, as a consequence of the pair interaction of nearest neighbors in one dimension. In two dimensions, we show the presence of a pairing phase transition in a system of interacting dislocations with parallel Burgers vectors. The scaling exponent of the velocity distribution at effective temperatures well below this pairing transition temperature can be derived from the nearest-neighbor interaction, while near the transition temperature, the distribution deviates from the form predicted by the nearest-neighbor interaction, suggesting the presence of collective effects.

Final state interactions at the threshold of Higgs boson pair production

NASA Astrophysics Data System (ADS)

Zhang, Zhentao

2015-11-01

We study the effect of final state interactions at the threshold of Higgs boson pair production in the Glashow-Weinberg-Salam model. We consider three major processes of the pair production in the model: lepton pair annihilation, ZZ fusion, and WW fusion. We find that the corrections caused by the effect for these processes are markedly different. According to our results, the effect can cause non-negligible corrections to the cross sections for lepton pair annihilation and small corrections for ZZ fusion, and this effect is negligible for WW fusion.

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

Dawson, S.; Lewis, I. M.

One of the simplest extensions of the Standard Model (SM) is the addition of a scalar gauge singlet, S . If S is not forbidden by a symmetry from mixing with the Standard Model Higgs boson, the mixing will generate non-SM rates for Higgs production and decays. Generally, there could also be unknown high energy physics that generates additional effective low energy interactions. We show that interference effects between the scalar resonance of the singlet model and the effective field theory (EFT) operators can have significant effects in the Higgs sector. Here, we examine a non- Z 2 symmetricmore » scalar singlet model and demonstrate that a fit to the 125 GeV Higgs boson couplings and to limits on high mass resonances, S , exhibit an interesting structure and possible large cancellations of effects between the resonance contribution and the new EFT interactions, that invalidate conclusions based on the renormalizable singlet model alone.« less

Statin-Induced Cardioprotection Against Ischemia-Reperfusion Injury: Potential Drug-Drug Interactions. Lesson to be Learnt by Translating Results from Animal Models to the Clinical Settings.

PubMed

Birnbaum, Gilad D; Birnbaum, Itamar; Ye, Yumei; Birnbaum, Yochai

2015-01-01

Numerous interventions have been shown to limit myocardial infarct size in animal models; however, most of these interventions have failed to have a significant effect in clinical trials. One potential explanation for the lack of efficacy in the clinical setting is that in bench models, a single intervention is studied without the background of other interventions or modalities. This is in contrast to the clinical setting in which new medications are added to the "standard of care" treatment that by now includes a growing number of medications. Drug-drug interaction may lead to alteration, dampening, augmenting or masking the effects of the intended intervention. We use the well described model of statin-induced myocardial protection to demonstrate potential interactions with agents which are commonly concomitantly used in patients with stable coronary artery disease and/or acute coronary syndromes. These interactions could potentially explain the reduced efficacy of statins in the clinical trials compared to the animal models. In particular, caffeine and aspirin could attenuate the infarct size limiting effects of statins; morphine could delay the onset of protection or mask the protective effect in patients with ST elevation myocardial infarction, whereas other anti-platelet agents (dipyridamole, cilostazol and ticagrelor) may augment (or mask) the effect due to their favorable effects on adenosine cell reuptake and intracellular cAMP levels. We recommend that after characterizing the effects of new modalities in single intervention bench research, studies should be repeated in the background of standard-of-care medications to assure that the magnitude of the effect is not altered before proceeding with clinical trials.

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.

Hysteretic Models Considering Axial-Shear-Flexure Interaction

NASA Astrophysics Data System (ADS)

Ceresa, Paola; Negrisoli, Giorgio

2017-10-01

Most of the existing numerical models implemented in finite element (FE) software, at the current state of the art, are not capable to describe, with enough reliability, the interaction between axial, shear and flexural actions under cyclic loading (e.g. seismic actions), neglecting crucial effects for predicting the nature of the collapse of reinforced concrete (RC) structural elements. Just a few existing 3D volume models or fibre beam models can lead to a quite accurate response, but they are still computationally inefficient for typical applications in earthquake engineering and also characterized by very complex formulation. Thus, discrete models with lumped plasticity hinges may be the preferred choice for modelling the hysteretic behaviour due to cyclic loading conditions, in particular with reference to its implementation in a commercial software package. These considerations lead to this research work focused on the development of a model for RC beam-column elements able to consider degradation effects and interaction between the actions under cyclic loading conditions. In order to develop a model for a general 3D discrete hinge element able to take into account the axial-shear-flexural interaction, it is necessary to provide an implementation which involves a corrector-predictor iterative scheme. Furthermore, a reliable constitutive model based on damage plasticity theory is formulated and implemented for its numerical validation. Aim of this research work is to provide the formulation of a numerical model, which will allow implementation within a FE software package for nonlinear cyclic analysis of RC structural members. The developed model accounts for stiffness degradation effect and stiffness recovery for loading reversal.

Using a Three-Dimensional Interactive Model To Teach Environmental Concepts to Visually Impaired Children.

ERIC Educational Resources Information Center

Budd, Julia M.; LaGrow, Steven J.

2000-01-01

A study investigated the efficacy of using the Buddy Road Kit, an interactive, wooden model, to teach environmental concepts to 4 children with visual impairments ages 7 to 11 years old. Results indicate the model was effective in teaching environmental concepts and traffic safety to the children involved. (Contains references.) (CR)

Relevance of the hadronic interaction model in the interpretation of multiple muon data as detected with the MACRO experiment

NASA Astrophysics Data System (ADS)

Ambrosio, M.; Antolini, R.; Aramo, C.; Auriemma, G.; Baldini, A.; Barbarino, G. C.; Barish, B. C.; Battistoni, G.; Bellotti, R.; Bemporad, C.; Bernardini, P.; Bilokon, H.; Bisi, V.; Bloise, C.; Bower, C.; Bussino, S.; Cafagna, F.; Calicchio, M.; Campana, D.; Carboni, M.; Castellano, M.; Cecchini, S.; Cei, F.; Chiarella, V.; Coutu, S.; de Benedictis, L.; de Cataldo, G.; Dekhissi, H.; de Marzo, C.; de Mitri, I.; de Vincenzi, M.; di Credico, A.; Erriquez, O.; Favuzzi, C.; Forti, C.; Fusco, P.; Giacomelli, G.; Giannini, G.; Giglietto, N.; Grassi, M.; Gray, L.; Grillo, A.; Guarino, F.; Guarnaccia, P.; Gustavino, C.; Habig, A.; Hanson, K.; Hawthorne, A.; Heinz, R.; Iarocci, E.; Katsavounidis, E.; Kearns, E.; Kyriazopoulou, S.; Lamanna, E.; Lane, C.; Levin, D. S.; Lipari, P.; Longley, N. P.; Longo, M. J.; Maaroufi, F.; Mancarella, G.; Mandrioli, G.; Manzoor, S.; Margiotta Neri, A.; Marini, A.; Martello, D.; Marzari-Chiesa, A.; Mazziotta, M. N.; Mazzotta, C.; Michael, D. G.; Mikheyev, S.; Miller, L.; Monacelli, P.; Montaruli, T.; Monteno, M.; Mufson, S.; Musser, J.; Nicoló, D.; Nolty, R.; Okada, C.; Orth, C.; Osteria, G.; Palamara, O.; Patera, V.; Patrizii, L.; Pazzi, R.; Peck, C. W.; Petrera, S.; Pistilli, P.; Popa, V.; Rainó, A.; Rastelli, A.; Reynoldson, J.; Ronga, F.; Rubizzo, U.; Sanzgiri, A.; Satriano, C.; Satta, L.; Scapparone, E.; Scholberg, K.; Sciubba, A.; Serra-Lugaresi, P.; Severi, M.; Sioli, M.; Sitta, M.; Spinelli, P.; Spinetti, M.; Spurio, M.; Steinberg, R.; Stone, J. L.; Sulak, L. R.; Surdo, A.; Tarlé, G.; Togo, V.; Walter, C. W.; Webb, R.

1999-03-01

With the aim of discussing the effect of the possible sources of systematic uncertainties in simulation models, the analysis of multiple muon events from the MACRO experiment at Gran Sasso is reviewed. In particular, the predictions from different currently available hadronic interaction models are compared.

A continuum-based structural modeling approach for cellulose nanocrystals (CNCs)

Treesearch

Mehdi Shishehbor; Fernando L. Dri; Robert J. Moon; Pablo D. Zavattieri

2018-01-01

We present a continuum-based structural model to study the mechanical behavior of cel- lulose nanocrystals (CNCs), and analyze the effect of bonded and non-bonded interactions on the mechanical properties under various loading conditions. In particular, this model assumes the uncoupling between the bonded and non-bonded interactions and their be- havior is obtained...

Competition and cooperation among similar representations: toward a unified account of facilitative and inhibitory effects of lexical neighbors.

PubMed

Chen, Qi; Mirman, Daniel

2012-04-01

One of the core principles of how the mind works is the graded, parallel activation of multiple related or similar representations. Parallel activation of multiple representations has been particularly important in the development of theories and models of language processing, where coactivated representations (neighbors) have been shown to exhibit both facilitative and inhibitory effects on word recognition and production. Researchers generally ascribe these effects to interactive activation and competition, but there is no unified explanation for why the effects are facilitative in some cases and inhibitory in others. We present a series of simulations of a simple domain-general interactive activation and competition model that is broadly consistent with more specialized domain-specific models of lexical processing. The results showed that interactive activation and competition can indeed account for the complex pattern of reversals. Critically, the simulations revealed a core computational principle that determines whether neighbor effects are facilitative or inhibitory: strongly active neighbors exert a net inhibitory effect, and weakly active neighbors exert a net facilitative effect.

Mathematical modelling of CRISPR-Cas system effects on biofilm formation.

PubMed

Ali, Qasim; Wahl, Lindi M

2017-08-01

Clustered regularly interspaced short palindromic repeats (CRISPR), linked with CRISPR associated (Cas) genes, can confer adaptive immunity to bacteria, against bacteriophage infections. Thus from a therapeutic standpoint, CRISPR immunity increases biofilm resistance to phage therapy. Recently, however, CRISPR-Cas genes have been implicated in reducing biofilm formation in lysogenized cells. Thus CRISPR immunity can have complex effects on phage-host-lysogen interactions, particularly in a biofilm. In this contribution, we develop and analyse a series of dynamical systems to elucidate and disentangle these interactions. Two competition models are used to study the effects of lysogens (first model) and CRISPR-immune bacteria (second model) in the biofilm. In the third model, the effect of delivering lysogens to a CRISPR-immune biofilm is investigated. Using standard analyses of equilibria, stability and bifurcations, our models predict that lysogens may be able to displace CRISPR-immune bacteria in a biofilm, and thus suggest strategies to eliminate phage-resistant biofilms.

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

PubMed Central

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

2016-01-01

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

PubMed

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

2017-01-05

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

Additive Interaction between Heterogeneous Environmental Quality Domains (Air, Water, Land, Sociodemographic, and Built Environment) on Preterm Birth.

PubMed

Grabich, Shannon C; Rappazzo, Kristen M; Gray, Christine L; Jagai, Jyotsna S; Jian, Yun; Messer, Lynne C; Lobdell, Danelle T

2016-01-01

Environmental exposures often occur in tandem; however, epidemiological research often focuses on singular exposures. Statistical interactions among broad, well-characterized environmental domains have not yet been evaluated in association with health. We address this gap by conducting a county-level cross-sectional analysis of interactions between Environmental Quality Index (EQI) domain indices on preterm birth in the Unites States from 2000 to 2005. The EQI, a county-level index constructed for the 2000-2005 time period, was constructed from five domain-specific indices (air, water, land, built, and sociodemographic) using principal component analyses. County-level preterm birth rates ( n  = 3141) were estimated using live births from the National Center for Health Statistics. Linear regression was used to estimate prevalence differences (PDs) and 95% confidence intervals (CIs) comparing worse environmental quality to the better quality for each model for (a) each individual domain main effect, (b) the interaction contrast, and (c) the two main effects plus interaction effect (i.e., the "net effect") to show departure from additivity for the all U.S. counties. Analyses were also performed for subgroupings by four urban/rural strata. We found the suggestion of antagonistic interactions but no synergism, along with several purely additive (i.e., no interaction) associations. In the non-stratified model, we observed antagonistic interactions, between the sociodemographic/air domains [net effect (i.e., the association, including main effects and interaction effects) PD: -0.004 (95% CI: -0.007, 0.000), interaction contrast: -0.013 (95% CI: -0.020, -0.007)] and built/air domains [net effect PD: 0.008 (95% CI 0.004, 0.011), interaction contrast: -0.008 (95% CI: -0.015, -0.002)]. Most interactions were between the air domain and other respective domains. Interactions differed by urbanicity, with more interactions observed in non-metropolitan regions. Observed antagonistic associations may indicate that those living in areas with multiple detrimental domains may have other interfering factors reducing the burden of environmental exposure. This study is the first to explore interactions across different environmental domains and demonstrates the utility of the EQI to examine the relationship between environmental domain interactions and human health. While we did observe some departures from additivity, many observed effects were additive. This study demonstrated that interactions between environmental domains should be considered in future analyses.

A predictive pharmacokinetic-pharmacodynamic model of tumor growth kinetics in xenograft mice after administration of anticancer agents given in combination.

PubMed

Terranova, Nadia; Germani, Massimiliano; Del Bene, Francesca; Magni, Paolo

2013-08-01

In clinical oncology, combination treatments are widely used and increasingly preferred over single drug administrations. A better characterization of the interaction between drug effects and the selection of synergistic combinations represent an open challenge in drug development process. To this aim, preclinical studies are routinely performed, even if they are only qualitatively analyzed due to the lack of generally applicable mathematical models. This paper presents a new pharmacokinetic-pharmacodynamic model that, starting from the well-known single agent Simeoni TGI model, is able to describe tumor growth in xenograft mice after the co-administration of two anticancer agents. Due to the drug action, tumor cells are divided in two groups: damaged and not damaged ones. The damaging rate has two terms proportional to drug concentrations (as in the single drug administration model) and one interaction term proportional to their product. Six of the eight pharmacodynamic parameters assume the same value as in the corresponding single drug models. Only one parameter summarizes the interaction, and it can be used to compute two important indexes that are a clear way to score the synergistic/antagonistic interaction among drug effects. The model was successfully applied to four new compounds co-administered with four drugs already available on the market for the treatment of three different tumor cell lines. It also provided reliable predictions of different combination regimens in which the same drugs were administered at different doses/schedules. A good and quantitative measurement of the intensity and nature of interaction between drug effects, as well as the capability to correctly predict new combination arms, suggest the use of this generally applicable model for supporting the experiment optimal design and the prioritization of different therapies.

Analysis of Learning Achievement and Teacher-Student Interactions in Flipped and Conventional Classrooms

ERIC Educational Resources Information Center

Sun, Jerry Chih-Yuan; Wu, Yu-Ting

2016-01-01

This study aimed to investigate the effectiveness of two different teaching methods on learning effectiveness. OpenCourseWare was integrated into the flipped classroom model (experimental group) and distance learning (control group). Learning effectiveness encompassed learning achievement, teacher-student interactions, and learning satisfaction.…

Interactive Nature of Climate Change and Aerosol Forcing

NASA Technical Reports Server (NTRS)

Nazarenko, L.; Rind, D.; Tsigaridis, K.; Del Genio, A. D.; Kelley, M.; Tausnev, N.

2017-01-01

The effect of changing cloud cover on climate, based on cloud-aerosol interactions, is one of the major unknowns for climate forcing and climate sensitivity. It has two components: (1) the impact of aerosols on clouds and climate due to in-situ interactions (i.e., rapid response); and (2) the effect of aerosols on the cloud feedback that arises as climate changes - climate feedback response. We examine both effects utilizing the NASA GISS ModelE2 to assess the indirect effect, with both mass-based and microphysical aerosol schemes, in transient twentieth-century simulations. We separate the rapid response and climate feedback effects by making simulations with a coupled version of the model as well as one with no sea surface temperature or sea ice response (atmosphere-only simulations). We show that the indirect effect of aerosols on temperature is altered by the climate feedbacks following the ocean response, and this change differs depending upon which aerosol model is employed. Overall the effective radiative forcing (ERF) for the direct effect of aerosol-radiation interaction (ERFari) ranges between -0.2 and -0.6 W/sq m for atmosphere-only experiments while the total effective radiative forcing, including the indirect effect (ERFari+aci) varies between about -0.4 and -1.1 W/sq m for atmosphere-only simulations; both ranges are in agreement with those given in IPCC (2013). Including the full feedback of the climate system lowers these ranges to -0.2 to -0.5 W/sq m for ERFari, and -0.3 to -0.74 W/sq m for ERFari+aci. With both aerosol schemes, the climate change feedbacks have reduced the global average indirect radiative effect of atmospheric aerosols relative to what the emission changes would have produced, at least partially due to its effect on tropical upper tropospheric clouds.

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.

Effects of aerodynamic interaction between main and tail rotors on helicopter hover performance and noise

NASA Technical Reports Server (NTRS)

Menger, R. P.; Wood, T. L.; Brieger, J. T.

1983-01-01

A model test was conducted to determine the effects of aerodynamic interaction between main rotor, tail rotor, and vertical fin on helicopter performance and noise in hover out of ground effect. The experimental data were obtained from hover tests performed with a .151 scale Model 222 main rotor, tail rotor and vertical fin. Of primary interest was the effect of location of the tail rotor with respect to the main rotor. Penalties on main rotor power due to interaction with the tail rotor ranged up to 3% depending upon tail rotor location and orientation. Penalties on tail rotor power due to fin blockage alone ranged up to 10% for pusher tail rotors and up to 50% for tractor tail rotors. The main rotor wake had only a second order effect on these tail rotor/fin interactions. Design charts are presented showing the penalties on main rotor power as a function of the relative location of the tail rotor.

A simple model for electrical charge in globular macromolecules and linear polyelectrolytes in solution

NASA Astrophysics Data System (ADS)

Krishnan, M.

2017-05-01

We present a model for calculating the net and effective electrical charge of globular macromolecules and linear polyelectrolytes such as proteins and DNA, given the concentration of monovalent salt and pH in solution. The calculation is based on a numerical solution of the non-linear Poisson-Boltzmann equation using a finite element discretized continuum approach. The model simultaneously addresses the phenomena of charge regulation and renormalization, both of which underpin the electrostatics of biomolecules in solution. We show that while charge regulation addresses the true electrical charge of a molecule arising from the acid-base equilibria of its ionizable groups, charge renormalization finds relevance in the context of a molecule's interaction with another charged entity. Writing this electrostatic interaction free energy in terms of a local electrical potential, we obtain an "interaction charge" for the molecule which we demonstrate agrees closely with the "effective charge" discussed in charge renormalization and counterion-condensation theories. The predictions of this model agree well with direct high-precision measurements of effective electrical charge of polyelectrolytes such as nucleic acids and disordered proteins in solution, without tunable parameters. Including the effective interior dielectric constant for compactly folded molecules as a tunable parameter, the model captures measurements of effective charge as well as published trends of pKa shifts in globular proteins. Our results suggest a straightforward general framework to model electrostatics in biomolecules in solution. In offering a platform that directly links theory and experiment, these calculations could foster a systematic understanding of the interrelationship between molecular 3D structure and conformation, electrical charge and electrostatic interactions in solution. The model could find particular relevance in situations where molecular crystal structures are not available or rapid, reliable predictions are desired.

Examining the Effects of Field Dependence-Independence on Learners' Problem-Solving Performance and Interaction with a Computer Modeling Tool: Implications for the Design of Joint Cognitive Systems

ERIC Educational Resources Information Center

Angeli, Charoula

2013-01-01

An investigation was carried out to examine the effects of cognitive style on learners' performance and interaction during complex problem solving with a computer modeling tool. One hundred and nineteen undergraduates volunteered to participate in the study. Participants were first administered a test, and based on their test scores they were…

Analysis and modeling of subgrid scalar mixing using numerical data

NASA Technical Reports Server (NTRS)

Girimaji, Sharath S.; Zhou, YE

1995-01-01

Direct numerical simulations (DNS) of passive scalar mixing in isotropic turbulence is used to study, analyze and, subsequently, model the role of small (subgrid) scales in the mixing process. In particular, we attempt to model the dissipation of the large scale (supergrid) scalar fluctuations caused by the subgrid scales by decomposing it into two parts: (1) the effect due to the interaction among the subgrid scales; and (2) the effect due to interaction between the supergrid and the subgrid scales. Model comparisons with DNS data show good agreement. This model is expected to be useful in the large eddy simulations of scalar mixing and reaction.

Theoretical study on interaction of cytochrome f and plastocyanin complex by a simple coarse-grained model with molecular crowding effect

NASA Astrophysics Data System (ADS)

Nakagawa, Satoshi; Kurniawan, Isman; Kodama, Koichi; Arwansyah, Muhammad Saleh; Kawaguchi, Kazutomo; Nagao, Hidemi

2018-03-01

We present a simple coarse-grained model with the molecular crowding effect in solvent to investigate the structure and dynamics of protein complexes including association and/or dissociation processes and investigate some physical properties such as the structure and the reaction rate from the viewpoint of the hydrophobic intermolecular interactions of protein complex. In the present coarse-grained model, a function depending upon the density of hydrophobic amino acid residues in a binding area of the complex is introduced, and the function involves the molecular crowding effect for the intermolecular interactions of hydrophobic amino acid residues between proteins. We propose a hydrophobic intermolecular potential energy between proteins by using the density-dependent function. The present coarse-grained model is applied to the complex of cytochrome f and plastocyanin by using the Langevin dynamics simulation to investigate some physical properties such as the complex structure, the electron transfer reaction rate constant from plastocyanin to cytochrome f and so on. We find that for proceeding the electron transfer reaction, the distance between metals in their active sites is necessary within about 18 Å. We discuss some typical complex structures formed in the present simulation in relation to the molecular crowding effect on hydrophobic interactions.

Assessing the Moral Coherence and Moral Robustness of Social Systems: Proof of Concept for a Graphical Models Approach.

PubMed

Hoss, Frauke; London, Alex John

2016-12-01

This paper presents a proof of concept for a graphical models approach to assessing the moral coherence and moral robustness of systems of social interactions. "Moral coherence" refers to the degree to which the rights and duties of agents within a system are effectively respected when agents in the system comply with the rights and duties that are recognized as in force for the relevant context of interaction. "Moral robustness" refers to the degree to which a system of social interaction is configured to ensure that the interests of agents are effectively respected even in the face of noncompliance. Using the case of conscientious objection of pharmacists to filling prescriptions for emergency contraception as an example, we illustrate how a graphical models approach can help stakeholders identify structural weaknesses in systems of social interaction and evaluate the relative merits of alternate organizational structures. By illustrating the merits of a graphical models approach we hope to spur further developments in this area.

Space shuttle orbiter rear mounted reaction control system jet interaction study. [hypersonic wind tunnel tests

NASA Technical Reports Server (NTRS)

Rausch, J. R.

1977-01-01

The effect of interaction between the reaction control system (RCS) jets and the flow over the space shuttle orbiter in the atmosphere was investigated in the NASA Langley 31-inch continuous flow hypersonic tunnel at a nominal Mach number of 10.3 and in the AEDC continuous flow hypersonic tunnel B at a nominal Mach number of 6, using 0.01 and .0125 scale force models with aft RCS nozzles mounted both on the model and on the sting of the force model balance. The data show that RCS nozzle exit momentum ratio is the primary correlating parameter for effects where the plume impinges on an adjacent surface and mass flow ratio is the parameter when the plume interaction is primarily with the external stream. An analytic model of aft mounted RCS units was developed in which the total reaction control moments are the sum of thrust, impingement, interaction, and cross-coupling terms.

Long-term evolution of a planetesimal swarm in the vicinity of a protoplanet

NASA Technical Reports Server (NTRS)

Kary, David M.; Lissauer, Jack J.

1991-01-01

Many models of planet formation involve scenarios in which one or a few large protoplanets interact with a swarm of much smaller planetesimals. In such scenarios, three-body perturbations by the protoplanet as well as mutual collisions and gravitational interactions between the swarm bodies are important in determining the velocity distribution of the swarm. We are developing a model to examine the effects of these processes on the evolution of a planetesimal swarm. The model consists of a combination of numerical integrations of the gravitational influence of one (or a few) massive protoplanets on swarm bodies together with a statistical treatment of the interactions between the planetesimals. Integrating the planetesimal orbits allows us to take into account effects that are difficult to model analytically or statistically, such as three-body collision cross-sections and resonant perturbations by the protoplanet, while using a statistical treatment for the particle-particle interactions allows us to use a large enough sample to obtain meaningful results.

Response of different regional online coupled models to aerosol-radiation interactions

NASA Astrophysics Data System (ADS)

Forkel, Renate; Balzarini, Alessandra; Brunner, Dominik; Baró, Rocio; Curci, Gabriele; Hirtl, Marcus; Honzak, Luka; Jiménez-Guerrero, Pedro; Jorba, Oriol; Pérez, Juan L.; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Tuccella, Paolo; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela

2016-04-01

The importance of aerosol-meteorology interactions and their representation in online coupled regional atmospheric chemistry-meteorology models was investigated in COST Action ES1004 (EuMetChem, http://eumetchem.info/). Case study results from different models (COSMO-Muscat, COSMO-ART, and different configurations of WRF-Chem), which were applied for Europe as a coordinated exercise for the year 2010, are analyzed with respect to inter-model variability and the response of the different models to direct and indirect aerosol-radiation interactions. The main focus was on two episodes - the Russian heat wave and wildfires episode in July/August 2010 and a period in October 2010 with enhanced cloud cover and rain and including an of Saharan dust transport to Europe. Looking at physical plausibility the decrease in downward solar radiation and daytime temperature due to the direct aerosol effect is robust for all model configurations. The same holds for the pronounced decrease in cloud water content and increase in solar radiation for cloudy conditions and very low aerosol concentrations that was found for WRF-Chem when aerosol cloud interactions were considered. However, when the differences were tested for statistical significance no significant differences in mean solar radiation and mean temperature between the baseline case and the simulations including the direct and indirect effect from simulated aerosol concentrations were found over Europe for the October episode. Also for the fire episode differences between mean temperature and radiation from the simulations with and without the direct aerosol effect were not significant for the major part of the modelling domain. Only for the region with high fire emissions in Russia, the differences in mean solar radiation and temperature due to the direct effect were found to be significant during the second half of the fire episode - however only for a significance level of 0.1. The few observational data indicate that the inclusion of aerosol radiative effects improves simulated temperatures in this area. In summary, the direct aerosol effect leads to lower temperatures and PBL heights for all seasons whereas the impact of the aerosol indirect effect on temperature and pollutant concentrations over Northern Europe was found to depend strongly on the season. It cannot be generalized whether the inclusion of aerosol radiative effects and aerosol cloud interactions based on simulated aerosol concentrations does improve the simulation results. Furthermore, assumptions how aerosol optical properties are calculated, i.e. on the aerosol's mixing state have a strong effect on simulated aerosol optical depth and the aerosol effect on incoming solar radiation and temperature. The inter-model variation of the response of different online coupled models suggests that further work comparing the methodologies and parameterizations used to represent the direct and indirect aerosol effect in these models is still necessary.

Built Expansion and Global Climate Change Drive Projected Urban Heat: Relative Magnitudes, Interactions, and Mitigation

NASA Astrophysics Data System (ADS)

Krayenhoff, E. S.; Georgescu, M.; Moustaoui, M.

2016-12-01

Surface climates are projected to warm due to global climate change over the course of the 21st century, and demographic projections suggest urban areas in the United States will continue to expand and develop, with associated local climate outcomes. Interactions between these two drivers of urban heat have not been robustly quantified to date. Here, simulations with the Weather Research and Forecasting model (coupled to a Single-Layer Urban Canopy Model) are performed at 20 km resolution over the continental U.S. for two 10-year periods: contemporary (2000-2009) and end-of-century (2090-2099). Present and end of century urban land use are derived from the Environmental Protection Agency's Integrated Climate and Land-Use Scenarios. Modelled effects on urban climates are evaluated regionally. Sensitivity to climate projection (Community Climate System Model 4.0, RCP 4.5 vs. RCP 8.5) and associated urban development scenarios are assessed. Effects on near-surface urban air temperature of RCP8.5 climate change are greater than those attributable to the corresponding urban development in many regions. Interaction effects vary by region, and while of lesser magnitude, are not negligible. Moreover, urban development and its interactions with RCP8.5 climate change modify the distribution of convective precipitation over the eastern US. Interaction effects result from the different meteorological effects of urban areas under current and future climate. Finally, the potential for design implementations such as green roofs and high albedo roofs to offset the projected warming is considered. Impacts of these implementations on precipitation are also assessed.

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

HiTEC: a connectionist model of the interaction between perception and action planning.

PubMed

Haazebroek, Pascal; Raffone, Antonino; Hommel, Bernhard

2017-11-01

Increasing evidence suggests that perception and action planning do not represent separable stages of a unidirectional processing sequence, but rather emerging properties of highly interactive processes. To capture these characteristics of the human cognitive system, we have developed a connectionist model of the interaction between perception and action planning: HiTEC, based on the Theory of Event Coding (Hommel et al. in Behav Brain Sci 24:849-937, 2001). The model is characterized by representations at multiple levels and by shared representations and processes. It complements available models of stimulus-response translation by providing a rationale for (1) how situation-specific meanings of motor actions emerge, (2) how and why some aspects of stimulus-response translation occur automatically and (3) how task demands modulate sensorimotor processing. The model is demonstrated to provide a unitary account and simulation of a number of key findings with multiple experimental paradigms on the interaction between perception and action such as the Simon effect, its inversion (Hommel in Psychol Res 55:270-279, 1993), and action-effect learning.

The influence of surface roughness on the contact stiffness and the contact filter effect in nonlinear wheel-track interaction

NASA Astrophysics Data System (ADS)

Lundberg, Oskar E.; Nordborg, Anders; Lopez Arteaga, Ines

2016-03-01

A state-dependent contact model including nonlinear contact stiffness and nonlinear contact filtering is used to calculate contact forces and rail vibrations with a time-domain wheel-track interaction model. In the proposed method, the full three-dimensional contact geometry is reduced to a point contact in order to lower the computational cost and to reduce the amount of required input roughness-data. Green's functions including the linear dynamics of the wheel and the track are coupled with a point contact model, leading to a numerically efficient model for the wheel-track interaction. Nonlinear effects due to the shape and roughness of the wheel and the rail surfaces are included in the point contact model by pre-calculation of functions for the contact stiffness and contact filters. Numerical results are compared to field measurements of rail vibrations for passenger trains running at 200 kph on a ballast track. Moreover, the influence of vehicle pre-load and different degrees of roughness excitation on the resulting wheel-track interaction is studied by means of numerical predictions.

[Understory effects on overstory trees: A review.

PubMed

Du, Zhong; Cai, Xiao Hu; Bao, Wei Kai; Chen, Huai; Pan, Hong Li

2016-03-01

Plant-plant interactions play a key role in regulating the composition and structure of communities and ecosystems. Studies of plant-plant interactions in forest ecosystems have traditionally concentrated on either tree-tree interactions or overstory species' impacts on understory plants. The possible effects of understory species on overstory trees have received less attention. We summarized the effects of understory species on soil physiological properties, soil fauna activities, leaf litter decomposition, and ecophysiology and growth of the overstory species. Then the effects of distur-bance on understory-overstory interactions were discussed. Finally, an ecophysiology-based concept model of understory effects on overstory trees was proposed. Understory removal experiments showed that the study area, overstory species age, soil fertility and understory species could significantly affect the understory-overstory interactions.

What is the impact of natural variability and aerosol-cloud interaction on the effective radiative forcing of anthropogenic aerosol?

NASA Astrophysics Data System (ADS)

Fiedler, S.; Stevens, B.; Mauritsen, T.

2017-12-01

State-of-the-art climate models have persistently shown a spread in estimates of the effective radiative forcing (ERF) associated with anthropogenic aerosol. Different reasons for the spread are known, but their relative importance is poorly understood. In this presentation we investigate the role of natural atmospheric variability, global patterns of aerosol radiative effects, and magnitudes of aerosol-cloud interaction in controlling the ERF of anthropogenic aerosol (Fiedler et al., 2017). We use the Earth system model MPI-ESM1.2 for conducting ensembles of atmosphere-only simulations and calculate the shortwave ERF of anthropogenic aerosol at the top of the atmosphere. The radiative effects are induced with the new parameterisation MACv2-SP (Stevens et al., 2017) that prescribes observationally constrained anthropogenic aerosol optical properties and an associated Twomey effect. Firstly, we compare the ERF of global patterns of anthropogenic aerosol from the mid-1970s and today. Our results suggest that such a substantial pattern difference has a negligible impact on the global mean ERF, when the natural variability of the atmosphere is considered. The clouds herein efficiently mask the clear-sky contributions to the forcing and reduce the detectability of significant anthropogenic aerosol radiative effects in all-sky conditions. Secondly, we strengthen the forcing magnitude through increasing the effect of aerosol-cloud interaction by prescribing an enhanced Twomey effect. In that case, the different spatial pattern of aerosol radiative effects from the mid-1970s and today causes a moderate change (15%) in the ERF of anthropogenic aerosol in our model. This finding lets us speculate that models with strong aerosol-cloud interactions would show a stronger ERF change with anthropogenic aerosol patterns. Testing whether the anthropogenic aerosol radiative forcing is model-dependent under prescribed aerosol conditions is currently ongoing work using MACv2-SP in comprehensive aerosol-climate models in the framework of the EU-funded project BACCHUS. In the future, MACv2-SP will be used in models participating in the Radiative Forcing Model Intercomparison Project (Pincus et al., 2016).

Anomalous waterlike behavior in spherically-symmetric water models optimized with the relative entropy.

PubMed

Chaimovich, Aviel; Shell, M Scott

2009-03-28

Recent efforts have attempted to understand many of liquid water's anomalous properties in terms of effective spherically-symmetric pairwise molecular interactions entailing two characteristic length scales (so-called "core-softened" potentials). In this work, we examine the extent to which such simple descriptions of water are representative of the true underlying interactions by extracting coarse-grained potential functions that are optimized to reproduce the behavior of an all-atom model. To perform this optimization, we use a novel procedure based upon minimizing the relative entropy, a quantity that measures the extent to which a coarse-grained configurational ensemble overlaps with a reference all-atom one. We show that the optimized spherically-symmetric water models exhibit notable variations with the state conditions at which they were optimized, reflecting in particular the shifting accessibility of networked hydrogen bonding interactions. Moreover, we find that water's density and diffusivity anomalies are only reproduced when the effective coarse-grained potentials are allowed to vary with state. Our results therefore suggest that no state-independent spherically-symmetric potential can fully capture the interactions responsible for water's unique behavior; rather, the particular way in which the effective interactions vary with temperature and density contributes significantly to anomalous properties.

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.

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.

Effects of neonatal excitotoxic lesions in ventral thalamus on social interaction in the rat.

PubMed

Wolf, Rainer; Dobrowolny, Henrik; Nullmeier, Sven; Bogerts, Bernhard; Schwegler, Herbert

2017-03-30

The role of the thalamus in schizophrenia has increasingly been studied in recent years. Deficits in the ventral thalamus have been described in only few postmortem and neuroimaging studies. We utilised our previously introduced neurodevelopmental animal model, the neonatal excitotoxic lesion of the ventral thalamus of Sprague-Dawley rats (Wolf et al., Pharmacopsychiatry 43:99-109, 22). At postnatal day (PD7), male pubs received bilateral thalamic infusions with ibotenic acid (IBA) or artificial cerebrospinal fluid (control). In adulthood, social interaction of two animals not familiar to each other was studied by a computerised video tracking system. This study displays clear lesion effects on social interaction of adult male rats. The significant reduction of total contact time and the significant increase in distance between the animals in the IBA group compared to controls can be interpreted as social withdrawal modelling a negative symptom of schizophrenia. The significant increase of total distance travelled in the IBA group can be hypothesised as agitation modelling a positive symptom of schizophrenia. Using a triple concept of social interaction, the percentage of no social interaction (Non-SI%) was significantly larger, and inversely, the percentage of passive social interaction (SI-passive%) was significantly smaller in the IBA group when compared to controls. In conclusion, on the background of findings in schizophrenic patients, the effects of neonatal ventral thalamic IBA lesions in adult male rats support the hypothesis of face and construct validity as animal model of schizophrenia.

A feature-based approach to modeling protein-protein interaction hot spots.

PubMed

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-05-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

Probing the cross-effect of strains in non-linear elasticity of nearly regular polymer networks by pure shear deformation.

PubMed

Katashima, Takuya; Urayama, Kenji; Chung, Ung-il; Sakai, Takamasa

2015-05-07

The pure shear deformation of the Tetra-polyethylene glycol gels reveals the presence of an explicit cross-effect of strains in the strain energy density function even for the polymer networks with nearly regular structure including no appreciable amount of structural defect such as trapped entanglement. This result is in contrast to the expectation of the classical Gaussian network model (Neo Hookean model), i.e., the vanishing of the cross effect in regular networks with no trapped entanglement. The results show that (1) the cross effect of strains is not dependent on the network-strand length; (2) the cross effect is not affected by the presence of non-network strands; (3) the cross effect is proportional to the network polymer concentration including both elastically effective and ineffective strands; (4) no cross effect is expected exclusively in zero limit of network concentration in real polymer networks. These features indicate that the real polymer networks with regular network structures have an explicit cross-effect of strains, which originates from some interaction between network strands (other than entanglement effect) such as nematic interaction, topological interaction, and excluded volume interaction.

Modeling the effects of ozone on soybean growth and yield.

PubMed

Kobayashi, K; Miller, J E; Flagler, R B; Heck, W W

1990-01-01

A simple mechanistic model was developed based on an existing growth model in order to address the mechanisms of the effects of ozone on growth and yield of soybean [Glycine max. (L.) Merr. 'Davis'] and interacting effects of other environmental stresses. The model simulates daily growth of soybean plants using environmental data including shortwave radiation, temperature, precipitation, irrigation and ozone concentration. Leaf growth, dry matter accumulation, water budget, nitrogen input and seed growth linked to senescence and abscission of leaves are described in the model. The effects of ozone are modeled as reduced photosynthate production and accelerated senescence. The model was applied to the open-top chamber experiments in which soybean plants were exposed to ozone under two levels of soil moisture regimes. After calibrating the model to the growth data and seed yield, goodness-of-fit of the model was tested. The model fitted well for top dry weight in the vegetative growth phase and also at maturity. The effect of ozone on seen yield was also described satisfactorily by the model. The simulation showed apparent interaction between the effect of ozone and soil moisture stress on the seed yield. The model revealed that further work is needed concerning the effect of ozone on the senescence process and the consequences of alteration of canopy microclimate by the open-top chambers.

Spatial interactions in a modified Daisyworld model: Heat diffusivity and greenhouse effects

NASA Astrophysics Data System (ADS)

Alberti, T.; Primavera, L.; Vecchio, A.; Lepreti, F.; Carbone, V.

2015-11-01

In this work we investigate a modified version of the Daisyworld model, originally introduced by Lovelock and Watson to describe in a simple way the interactions between an Earth-like planet, its biosphere, and the incoming solar radiation. Here a spatial dependency on latitude is included, and both a variable heat diffusivity along latitudes and a simple greenhouse effect description are introduced in the model. We show that the spatial interactions between the variables of the system can locally stabilize the coexistence of the two vegetation types. The feedback on albedo is able to generate equilibrium solutions which can efficiently self-regulate the planet climate, even for values of the solar luminosity relatively far from the current Earth conditions.

Unraveling torsional bath interactions with the CO stretching state in methanol

NASA Astrophysics Data System (ADS)

Pearson, John C.; Daly, Adam M.; Lees, Ronald M.

2015-12-01

Quantum mechanical models describing the effects of a C3 internal rotor have been successful in modeling all the torsional manifolds of isolated vibrational states. However, modeling the coupling between nearly degenerate small amplitude vibrations in the C3 internal rotation case remains far from satisfactory and a variety of practical and fundamental questions persist on basis sets, the relative importance of effects and how the problem should be approached. The ν8 C-O stretching state of methanol has been well studied with infrared techniques and has the potential to serve as an experimental reference data set for the development of models for the coupled large and small amplitude motion case. A combined infrared-microwave study of the lowest K A-states of vt = 3, vt = 4 and ν8 has been performed to understand the nature of the interactions between ν8 the excited torsional states. The interaction between vt = 4 and ν8 at K = 0+ has been confirmed to be Fermi type with magnitude of 2.5 cm-1. Additionally, the fundamental a-symmetry and b-symmetry Coriolis interactions between vt = 3 and ν8 have been estimated to be 8900 MHz and -360 MHz, respectively. The magnitude of these interactions suggests that modeling the ν8 state, the vt = 3 state, and the vt = 4 states will have to carefully account for these interactions.

An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on forest ecosystem services

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on multiple ecosystem services

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

Final state interactions and inclusive nuclear collisions

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Dubey, Rajendra R.

1993-01-01

A scattering formalism is developed in a multiple scattering model to describe inclusive momentum distributions for high-energy projectiles. The effects of final state interactions on response functions and momentum distributions are investigated. Calculations for high-energy protons that include shell model response functions are compared with experiments.

Urbanism and life satisfaction among the aged.

PubMed

Liang, J; Warfel, B L

1983-01-01

This study examines the impact of urbanism on the causal mechanisms by which life satisfaction is determined. Although the links between the type of community and life satisfaction have been the foci of many studies, the findings are by no means conclusive. Some have found that the rural elderly express greater satisfaction, others have not. Such a discrepancy may be due to (a) the neglect of other variables, (b) a lack of explicit causal specifications, and (c) the failure to distinguish main effects from interaction effects. In this study a causal model that incorporates urbanism as a polytomous variable and its interaction effects has been proposed. The model was evaluated by using four data sets with sample sizes ranging from 961 to 3,996. Urbanism was found to have indirect main effects as well as interaction effects on life satisfaction.

Wind-US Code Contributions to the First AIAA Shock Boundary Layer Interaction Prediction Workshop

NASA Technical Reports Server (NTRS)

Georgiadis, Nicholas J.; Vyas, Manan A.; Yoder, Dennis A.

2013-01-01

This report discusses the computations of a set of shock wave/turbulent boundary layer interaction (SWTBLI) test cases using the Wind-US code, as part of the 2010 American Institute of Aeronautics and Astronautics (AIAA) shock/boundary layer interaction workshop. The experiments involve supersonic flows in wind tunnels with a shock generator that directs an oblique shock wave toward the boundary layer along one of the walls of the wind tunnel. The Wind-US calculations utilized structured grid computations performed in Reynolds-averaged Navier-Stokes mode. Four turbulence models were investigated: the Spalart-Allmaras one-equation model, the Menter Baseline and Shear Stress Transport k-omega two-equation models, and an explicit algebraic stress k-omega formulation. Effects of grid resolution and upwinding scheme were also considered. The results from the CFD calculations are compared to particle image velocimetry (PIV) data from the experiments. As expected, turbulence model effects dominated the accuracy of the solutions with upwinding scheme selection indicating minimal effects.

Correlation Imaging Reveals Specific Crowding Dynamics of Kinesin Motor Proteins

NASA Astrophysics Data System (ADS)

Miedema, Daniël M.; Kushwaha, Vandana S.; Denisov, Dmitry V.; Acar, Seyda; Nienhuis, Bernard; Peterman, Erwin J. G.; Schall, Peter

2017-10-01

Molecular motor proteins fulfill the critical function of transporting organelles and other building blocks along the biopolymer network of the cell's cytoskeleton, but crowding effects are believed to crucially affect this motor-driven transport due to motor interactions. Physical transport models, like the paradigmatic, totally asymmetric simple exclusion process (TASEP), have been used to predict these crowding effects based on simple exclusion interactions, but verifying them in experiments remains challenging. Here, we introduce a correlation imaging technique to precisely measure the motor density, velocity, and run length along filaments under crowding conditions, enabling us to elucidate the physical nature of crowding and test TASEP model predictions. Using the kinesin motor proteins kinesin-1 and OSM-3, we identify crowding effects in qualitative agreement with TASEP predictions, and we achieve excellent quantitative agreement by extending the model with motor-specific interaction ranges and crowding-dependent detachment probabilities. These results confirm the applicability of basic nonequilibrium models to the intracellular transport and highlight motor-specific strategies to deal with crowding.

A nonparametric method for assessment of interactions in a median regression model for analyzing right censored data.

PubMed

Lee, MinJae; Rahbar, Mohammad H; Talebi, Hooshang

2018-01-01

We propose a nonparametric test for interactions when we are concerned with investigation of the simultaneous effects of two or more factors in a median regression model with right censored survival data. Our approach is developed to detect interaction in special situations, when the covariates have a finite number of levels with a limited number of observations in each level, and it allows varying levels of variance and censorship at different levels of the covariates. Through simulation studies, we compare the power of detecting an interaction between the study group variable and a covariate using our proposed procedure with that of the Cox Proportional Hazard (PH) model and censored quantile regression model. We also assess the impact of censoring rate and type on the standard error of the estimators of parameters. Finally, we illustrate application of our proposed method to real life data from Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study to test an interaction effect between type of injury and study sites using median time for a trauma patient to receive three units of red blood cells. The results from simulation studies indicate that our procedure performs better than both Cox PH model and censored quantile regression model based on statistical power for detecting the interaction, especially when the number of observations is small. It is also relatively less sensitive to censoring rates or even the presence of conditionally independent censoring that is conditional on the levels of covariates.

A Model of Auditory-Cognitive Processing and Relevance to Clinical Applicability.

PubMed

Edwards, Brent

2016-01-01

Hearing loss and cognitive function interact in both a bottom-up and top-down relationship. Listening effort is tied to these interactions, and models have been developed to explain their relationship. The Ease of Language Understanding model in particular has gained considerable attention in its explanation of the effect of signal distortion on speech understanding. Signal distortion can also affect auditory scene analysis ability, however, resulting in a distorted auditory scene that can affect cognitive function, listening effort, and the allocation of cognitive resources. These effects are explained through an addition to the Ease of Language Understanding model. This model can be generalized to apply to all sounds, not only speech, representing the increased effort required for auditory environmental awareness and other nonspeech auditory tasks. While the authors have measures of speech understanding and cognitive load to quantify these interactions, they are lacking measures of the effect of hearing aid technology on auditory scene analysis ability and how effort and attention varies with the quality of an auditory scene. Additionally, the clinical relevance of hearing aid technology on cognitive function and the application of cognitive measures in hearing aid fittings will be limited until effectiveness is demonstrated in real-world situations.

Evaluation of Drug-Drug Interaction Potential Between Sacubitril/Valsartan (LCZ696) and Statins Using a Physiologically Based Pharmacokinetic Model.

PubMed

Lin, Wen; Ji, Tao; Einolf, Heidi; Ayalasomayajula, Surya; Lin, Tsu-Han; Hanna, Imad; Heimbach, Tycho; Breen, Christopher; Jarugula, Venkateswar; He, Handan

2017-05-01

Sacubitril/valsartan (LCZ696) has been approved for the treatment of heart failure. Sacubitril is an in vitro inhibitor of organic anion-transporting polypeptides (OATPs). In clinical studies, LCZ696 increased atorvastatin C max by 1.7-fold and area under the plasma concentration-time curve by 1.3-fold, but had little or no effect on simvastatin or simvastatin acid exposure. A physiologically based pharmacokinetics modeling approach was applied to explore the underlying mechanisms behind the statin-specific LCZ696 drug interaction observations. The model incorporated OATP-mediated clearance (CL int,T ) for simvastatin and simvastatin acid to successfully describe the pharmacokinetic profiles of either analyte in the absence or presence of LCZ696. Moreover, the model successfully described the clinically observed drug effect with atorvastatin. The simulations clarified the critical parameters responsible for the observation of a low, yet clinically relevant, drug-drug interaction DDI between sacubitril and atorvastatin and the lack of effect with simvastatin acid. Atorvastatin is administered in its active form and rapidly achieves C max that coincide with the low C max of sacubitril. In contrast, simvastatin requires a hydrolysis step to the acid form and therefore is not present at the site of interactions at sacubitril concentrations that are inhibitory. Similar models were used to evaluate the drug-drug interaction risk for additional OATP-transported statins which predicted to maximally result in a 1.5-fold exposure increase. Copyright © 2017. Published by Elsevier Inc.

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.

Control Surface Interaction Effects of the Active Aeroelastic Wing Wind Tunnel Model

NASA Technical Reports Server (NTRS)

Heeg, Jennifer

2006-01-01

This paper presents results from testing the Active Aeroelastic Wing wind tunnel model in NASA Langley s Transonic Dynamics Tunnel. The wind tunnel test provided an opportunity to study aeroelastic system behavior under combined control surface deflections, testing for control surface interaction effects. Control surface interactions were observed in both static control surface actuation testing and dynamic control surface oscillation testing. The primary method of evaluating interactions was examination of the goodness of the linear superposition assumptions. Responses produced by independently actuating single control surfaces were combined and compared with those produced by simultaneously actuating and oscillating multiple control surfaces. Adjustments to the data were required to isolate the control surface influences. Using dynamic data, the task increases, as both the amplitude and phase have to be considered in the data corrections. The goodness of static linear superposition was examined and analysis of variance was used to evaluate significant factors influencing that goodness. The dynamic data showed interaction effects in both the aerodynamic measurements and the structural measurements.

Modeling the Effect of Fluid-Structure Interaction on the Impact Dynamics of Pressurized Tank Cars

DOT National Transportation Integrated Search

2009-11-13

This paper presents a computational framework that : analyzes the effect of fluid-structure interaction (FSI) on the : impact dynamics of pressurized commodity tank cars using the : nonlinear dynamic finite element code ABAQUS/Explicit. : There exist...

Electron interactions in graphene through an effective Coulomb potential

NASA Astrophysics Data System (ADS)

Rodrigues, Joao N. B.; Adam, Shaffique

A recent numerical work [H.-K. Tang et al, PRL 115, 186602 (2015)] considering graphene's π-electrons interacting through an effective Coulomb potential that is finite at short-distances, stressed the importance of the sp2 -electrons in determining the semimetal to Mott insulator phase transition in graphene. Some years ago, I. F. Herbut [PRL 97, 146401 (2006)] studied such a transition by mapping graphene's π-electrons into a Gross-Neveu model. From a different perspective, D. T. Son [PRB 75, 235423 (2007)] put the emphasis on the long-range interactions by modelling graphene as Dirac fermions interacting through a bare Coulomb potential. Here we build on these works and explore the phase diagram of Dirac fermions interacting through an effective Coulomb-like potential screened at short-distances. The interaction potential used allows for analytic results that controllably switch between the two perspectives above. This work was supported by the Singapore National Research Foundation (NRF-NRFF2012-01 and CA2DM medium-sized centre program) and by the Singapore Ministry of Education and Yale-NUS College (R-607-265-01312).

Response trajectories capture the continuous dynamics of the size congruity effect.

PubMed

Faulkenberry, Thomas J; Cruise, Alexander; Lavro, Dmitri; Shaki, Samuel

2016-01-01

In a comparison task involving numbers, the size congruity effect refers to the general finding that responses are usually faster when there is a match between numerical size and physical size (e.g., 2-8) than when there is a mismatch (e.g., 2-8). In the present study, we used computer mouse tracking to test two competing models of the size congruity effect: an early interaction model, where interference occurs at an early representational stage, and a late interaction model, where interference occurs as dynamic competition between response options. In three experiments, we found that the curvature of responses for incongruent trials was greater than for congruent trials. In Experiment 2 we showed that this curvature effect was reliably modulated by the numerical distance between the two stimulus numbers, with large distance pairs exhibiting a larger curvature effect than small distance pairs. In Experiment 3 we demonstrated that the congruity effects persist into response execution. These findings indicate that incongruities between numerical and physical sizes are carried throughout the response process and result from competition between parallel and partially active response options, lending further support to a late interaction model of the size congruity effect. Copyright © 2015 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.

Substituent Effects in the Benzene Dimer are Due to Direct Interactions of the Substituents with the Unsubstituted Benzene

PubMed Central

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

2009-01-01

The prevailing views of substituent effects in the sandwich configuration of the benzene dimer are flawed. For example, in the polar/π model of Cozzi and co-workers (J. Am. Chem. Soc. 1992, 114, 5729), electron-withdrawing substituents enhance binding in the benzene dimer by withdrawing electron density from the π-cloud of the substituted ring, reducing the repulsive electrostatic interaction with the non-substituted benzene. Conversely, electron-donating substituents donate excess electrons into the π-system and diminish the π-stacking interaction. We present computed interaction energies for the sandwich configuration of the benzene dimer and 24 substituted dimers, as well as sandwich complexes of substituted benzenes with perfluorobenzene. While the computed interaction energies correlate well with σm values for the substituents, interaction energies for related model systems demonstrate that this trend is independent of the substituted ring. Instead, the observed trends are consistent with direct electrostatic and dispersive interactions of the substituents with the unsubstituted ring. PMID:18652453

Interplay Between Hydrophobic Effect and Dipole Interactions in Peptide Aggregation

NASA Astrophysics Data System (ADS)

Ganesan, Sai; Matysiak, Silvina

In the past decade, the development of various coarse-grained models for proteins have provided key insights into the driving forces in folding and aggregation.We recently developed a low resolution Water Explicit Polarizable PROtein coarse-grained Model by adding oppositely charged dummy particles inside protein backbone beads.With this model,we were able to achieve significant α/ β secondary structure content,without any added bias.We now extend the model to study peptide aggregation at hydrophobic-hydrophilic interface using elastin-like octapeptides (GV)4 as a model system.A condensation-ordering mechanism of aggregation is observed in water.Our results suggest that backbone interpeptide dipolar interactions,not hydrophobicity,plays a more significant role in fibril-like peptide aggregation.We observe a cooperative effect in hydrogen bonding or dipolar interactions, with increase in aggregate size in water and interface.Based on this cooperative effect, we provide a potential explanation for the observed nucleus size in peptide aggregation pathways.Without dipolar particles,peptide aggregation is not observed at the hydrophilic-hydrophobic interface.Thus,the presence of dipoles,not hydrophobicity plays a key role in aggregation observed at hydrophobic interfaces.

Diffusion of multiple species with excluded-volume effects.

PubMed

Bruna, Maria; Chapman, S Jonathan

2012-11-28

Stochastic models of diffusion with excluded-volume effects are used to model many biological and physical systems at a discrete level. The average properties of the population may be described by a continuum model based on partial differential equations. In this paper we consider multiple interacting subpopulations/species and study how the inter-species competition emerges at the population level. Each individual is described as a finite-size hard core interacting particle undergoing brownian motion. The link between the discrete stochastic equations of motion and the continuum model is considered systematically using the method of matched asymptotic expansions. The system for two species leads to a nonlinear cross-diffusion system for each subpopulation, which captures the enhancement of the effective diffusion rate due to excluded-volume interactions between particles of the same species, and the diminishment due to particles of the other species. This model can explain two alternative notions of the diffusion coefficient that are often confounded, namely collective diffusion and self-diffusion. Simulations of the discrete system show good agreement with the analytic results.

The hadronic interaction model EPOS

NASA Astrophysics Data System (ADS)

Werner, Klaus

2008-01-01

EPOS is a sophisticated multiple scattering approach based on partons and Pomerons (parton ladders), with special emphasis on high parton densities. The latter aspect, particularly important in proton-nucleus or nucleus-nucleus collisions, is taken care of via an effective treatment of Pomeron-Pomeron interactions, referred to as parton ladder splitting. In addition, collective effects are introduced after separating the high density central core from the peripheral corona. EPOS is the successor of the NEXUS model.

Dual process interaction model of HIV-risk behaviors among drug offenders.

PubMed

Ames, Susan L; Grenard, Jerry L; Stacy, Alan W

2013-03-01

This study evaluated dual process interaction models of HIV-risk behavior among drug offenders. A dual process approach suggests that decisions to engage in appetitive behaviors result from a dynamic interplay between a relatively automatic associative system and an executive control system. One synergistic type of interplay suggests that executive functions may dampen or block effects of spontaneously activated associations. Consistent with this model, latent variable interaction analyses revealed that drug offenders scoring higher in affective decision making were relatively protected from predictive effects of spontaneous sex associations promoting risky sex. Among drug offenders with lower levels of affective decision making ability, spontaneous sexually-related associations more strongly predicted risky sex (lack of condom use and greater number of sex partners). These findings help elucidate associative and control process effects on appetitive behaviors and are important for explaining why some individuals engage in risky sex, while others are relatively protected.

Dual Process Interaction Model of HIV-Risk Behaviors Among Drug Offenders

PubMed Central

Grenard, Jerry L.; Stacy, Alan W.

2012-01-01

This study evaluated dual process interaction models of HIV-risk behavior among drug offenders. A dual process approach suggests that decisions to engage in appetitive behaviors result from a dynamic interplay between a relatively automatic associative system and an executive control system. One synergistic type of interplay suggests that executive functions may dampen or block effects of spontaneously activated associations. Consistent with this model, latent variable interaction analyses revealed that drug offenders scoring higher in affective decision making were relatively protected from predictive effects of spontaneous sex associations promoting risky sex. Among drug offenders with lower levels of affective decision making ability, spontaneous sexually-related associations more strongly predicted risky sex (lack of condom use and greater number of sex partners). These findings help elucidate associative and control process effects on appetitive behaviors and are important for explaining why some individuals engage in risky sex, while others are relatively protected. PMID:22331391

Synergism between rocuronium and cisatracurium: comparison of the Minto and Greco interaction models.

PubMed

Jeon, Soeun; Kwon, Jae Young; Kim, Hae-Kyu; Kim, Tae Kyun

2016-08-01

This study was conducted to investigate the pharmacodynamic interaction between rocuronium and cisatracurium using the response surface model, which is not subject to the limitations of traditional isobolographic analysis. One hundred and twenty patients were randomly allocated to receive one of the fifteen predefined combinations of rocuronium and cisatracurium. To study single drugs, cisatracurium 0.2, 0.15, or 0.1 mg/kg or rocuronium 0.8, 0.6 or 0.4 mg/kg doses were administered alone. To study the pharmacodynamic interaction, drugs were applied in three types of combination ratio, i.e., half dose of each drug alone, 75% of each single dose of rocuronium and 25% of each single dose of cisatracurium, and vice versa. Train-of-four (TOF) ratio and T1% (first twitch of the TOF presented as percentage compared to the initial T1) were used as pharmacodynamic endpoints, and the Greco and Minto models were used as surface interaction models. The interaction term α of the Greco model for TOF ratio and T1% measurements showed synergism with values of 0.977 and 1.12, respectively. Application of the Minto model resulted in U50 (θ) values (normalized unit of concentration that produces 50% of the maximal effect in the 0 < θ < 1 region) less than 1 for both TOF ratio and T1% measurements, indicating that rocuronium and cisatracurium exhibit synergism. Response surface modeling of the interaction between rocuronium and cisatracurium, based on considerations of their effects on muscle relaxation as measured by TOF ratio and T1%, indicated that the two drugs show considerable synergism.

A modulating effect of Tropical Instability Wave (TIW)-induced surface wind feedback in a hybrid coupled model of the tropical Pacific

NASA Astrophysics Data System (ADS)

Zhang, Rong-Hua

2016-10-01

Tropical Instability Waves (TIWs) and the El Niño-Southern Oscillation (ENSO) are two air-sea coupling phenomena that are prominent in the tropical Pacific, occurring at vastly different space-time scales. It has been challenging to adequately represent both of these processes within a large-scale coupled climate model, which has led to a poor understanding of the interactions between TIW-induced feedback and ENSO. In this study, a novel modeling system was developed that allows representation of TIW-scale air-sea coupling and its interaction with ENSO. Satellite data were first used to derive an empirical model for TIW-induced sea surface wind stress perturbations (τTIW). The model was then embedded in a basin-wide hybrid-coupled model (HCM) of the tropical Pacific. Because τTIW were internally determined from TIW-scale sea surface temperatures (SSTTIW) simulated in the ocean model, the wind-SST coupling at TIW scales was interactively represented within the large-scale coupled model. Because the τTIW-SSTTIW coupling part of the model can be turned on or off in the HCM simulations, the related TIW wind feedback effects can be isolated and examined in a straightforward way. Then, the TIW-scale wind feedback effects on the large-scale mean ocean state and interannual variability in the tropical Pacific were investigated based on this embedded system. The interactively represented TIW-scale wind forcing exerted an asymmetric influence on SSTs in the HCM, characterized by a mean-state cooling and by a positive feedback on interannual variability, acting to enhance ENSO amplitude. Roughly speaking, the feedback tends to increase interannual SST variability by approximately 9%. Additionally, there is a tendency for TIW wind to have an effect on the phase transition during ENSO evolution, with slightly shortened interannual oscillation periods. Additional sensitivity experiments were performed to elucidate the details of TIW wind effects on SST evolution during ENSO cycles.

Modulation of Additive and Interactive Effects in Lexical Decision by Trial History

ERIC Educational Resources Information Center

Masson, Michael E. J.; Kliegl, Reinhold

2013-01-01

Additive and interactive effects of word frequency, stimulus quality, and semantic priming have been used to test theoretical claims about the cognitive architecture of word-reading processes. Additive effects among these factors have been taken as evidence for discrete-stage models of word reading. We present evidence from linear mixed-model…

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.

Arsenic-gene interactions and beta-cell function in the Strong Heart Family Study.

PubMed

Balakrishnan, Poojitha; Navas-Acien, Ana; Haack, Karin; Vaidya, Dhananjay; Umans, Jason G; Best, Lyle G; Goessler, Walter; Francesconi, Kevin A; Franceschini, Nora; North, Kari E; Cole, Shelley A; Voruganti, V Saroja; Gribble, Matthew O

2018-06-01

We explored arsenic-gene interactions influencing pancreatic beta-cell activity in the Strong Heart Family Study (SHFS). We considered 42 variants selected for associations with either beta-cell function (31 variants) or arsenic metabolism (11 variants) in the SHFS. Beta-cell function was calculated as homeostatic model - beta corrected for insulin resistance (cHOMA-B) by regressing homeostatic model - insulin resistance (HOMA-IR) on HOMA-B and adding mean HOMA-B. Arsenic exposure was dichotomized at the median of the sum of creatinine-corrected inorganic and organic arsenic species measured by high performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICPMS). Additive GxE models for cHOMA-B were adjusted for age and ancestry, and accounted for family relationships. Models were stratified by center (Arizona, Oklahoma, North Dakota and South Dakota) and meta-analyzed. The two interactions between higher vs. lower arsenic and SNPs for cHOMA-B that were nominally significant at P < 0.05 were with rs10738708 (SNP overall effect -3.91, P = 0.56; interaction effect with arsenic -31.14, P = 0.02) and rs4607517 (SNP overall effect +16.61, P = 0.03; interaction effect with arsenic +27.02, P = 0.03). The corresponding genes GCK and TUSC1 suggest oxidative stress and apoptosis as possible mechanisms for arsenic impacts on beta-cell function. No interactions were Bonferroni-significant (1.16 × 10 -3 ). Our findings are suggestive of oligogenic moderation of arsenic impacts on pancreatic β-cell endocrine function, but were not Bonferroni-significant. Copyright © 2018 Elsevier Inc. All rights reserved.

Modelling Southern Ocean ecosystems: krill, the food-web, and the impacts of harvesting.

PubMed

Hill, S L; Murphy, E J; Reid, K; Trathan, P N; Constable, A J

2006-11-01

The ecosystem approach to fisheries recognises the interdependence between harvested species and other ecosystem components. It aims to account for the propagation of the effects of harvesting through the food-web. The formulation and evaluation of ecosystem-based management strategies requires reliable models of ecosystem dynamics to predict these effects. The krill-based system in the Southern Ocean was the focus of some of the earliest models exploring such effects. It is also a suitable example for the development of models to support the ecosystem approach to fisheries because it has a relatively simple food-web structure and progress has been made in developing models of the key species and interactions, some of which has been motivated by the need to develop ecosystem-based management. Antarctic krill, Euphausia superba, is the main target species for the fishery and the main prey of many top predators. It is therefore critical to capture the processes affecting the dynamics and distribution of krill in ecosystem dynamics models. These processes include environmental influences on recruitment and the spatially variable influence of advection. Models must also capture the interactions between krill and its consumers, which are mediated by the spatial structure of the environment. Various models have explored predator-prey population dynamics with simplistic representations of these interactions, while others have focused on specific details of the interactions. There is now a pressing need to develop plausible and practical models of ecosystem dynamics that link processes occurring at these different scales. Many studies have highlighted uncertainties in our understanding of the system, which indicates future priorities in terms of both data collection and developing methods to evaluate the effects of these uncertainties on model predictions. We propose a modelling approach that focuses on harvested species and their monitored consumers and that evaluates model uncertainty by using alternative structures and functional forms in a Monte Carlo framework.

Light hadron spectra in the constituent quark model with the Kobayashi-Kondo-Maskawa-'t Hooft effective U {sub A} (1) symmetry breaking interaction

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

Dmitrasinovic, V.; Toki, H.; Research Center for Nuclear Physics, Osaka University, Ibaraki, Osaka 567-0047

2006-02-15

We make a critical comparison of several versions of instanton-induced interactions present in the literature, all based on ITEP group's extension to three colours and flavours of 't Hooft's effective lagrangian, with the predictions of the phenomenological Kobayashi-Kondo-Maskawa (KKM) chiral quark lagrangian. We analyze the effects of all versions of the effective U {sub A} (1) symmetry breaking interactions on light hadron spectra in the non-relativistic constituent quark model. We show that the KKMT force, when used as a residual hyperfine interaction reproduces the correct ordering of pseudoscalar and vector mesons even without explicitly taking chiral symmetry into account. Moreover,more » the nucleon spectra are also correctly reproduced, only the Roper resonance remains too high, albeit lower than usual, at 1660 MeV. The latter's lower than expected mass is not due to a small excitation energy, as in the Glozman-Riska (GR) model, but to a combination of colour, flavour, and spatial wave function properties that enhance the relevant matrix elements. The KKMT interaction explicitly depends on flavour and spin of the quarks, but unlike the GR flavour-spin one it has a firm footing in QCD. In the process we provide several technical advances, in particular we show the first explicit derivation of the three-body Fierz transformation and apply it to the KKM interaction. We also discuss the ambiguities associated with the colour degree of freedom.« less

Effect of ultraviolet irradiation on free radical scavenging activity of immunosuppressants used in lung transplantation and comparative electron paramagnetic resonance study of kinetics of their interactions with model free radicals.

PubMed

Stanjek-Cichoracka, A; Żegleń, S; Ramos, P; Pilawa, B; Wojarski, J

2018-06-01

The immunosuppressive drugs used in solid organ transplantation or autoimmunological processes were studied by electron paramagnetic resonance (EPR) spectroscopy to estimate their free radical scavenging activity. The interactions of immunosuppressants with free radicals were examined by an X-band (9.3 GHz) EPR spectroscopy and a model of DPPH free radicals. The EPR spectra of DPPH and DPPH interacting with individual drugs were compared. Kinetic studies were performed, and the effect of ultraviolet (UV) irradiation on the free radical scavenging activity of the tested drugs was determined. The free radical scavenging activity of non-irradiated drugs decreased in the order: rapamycin > mycophenolate mofetil > ciclosporin > tacrolimus. UV irradiation increased the free radical scavenging activity of all the tested immunosuppressive drugs, and the effect was highest for tacrolimus. For the non-irradiated samples, the speed of free radical interactions decreased in the order: ciclosporin > tacrolimus > mycophenolate mofetil > rapamycin. UV irradiation only slightly affected the speed of interactions of the immunosuppressive drugs with the model DPPH free radicals. Electron paramagnetic resonance spectroscopy is useful for obtaining information on interactions of immunosuppressive drugs with free radicals. We hypothesized that the long-term immunosuppressive effects of these drugs after transplantation or during autoimmune disorders may be mediated by anti-inflammatory action in addition to the known receptor/cell cycle inhibition. © 2018 John Wiley & Sons Ltd.

Degenerate limit thermodynamics beyond leading order for models of dense matter

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

Constantinou, Constantinos, E-mail: c.constantinou@fz-juelich.de; Muccioli, Brian, E-mail: bm956810@ohio.edu; Prakash, Madappa, E-mail: prakash@ohio.edu

2015-12-15

Analytical formulas for next-to-leading order temperature corrections to the thermal state variables of interacting nucleons in bulk matter are derived in the degenerate limit. The formalism developed is applicable to a wide class of non-relativistic and relativistic models of hot and dense matter currently used in nuclear physics and astrophysics (supernovae, proto-neutron stars and neutron star mergers) as well as in condensed matter physics. We consider the general case of arbitrary dimensionality of momentum space and an arbitrary degree of relativity (for relativistic models). For non-relativistic zero-range interactions, knowledge of the Landau effective mass suffices to compute next-to-leading order effects,more » but for finite-range interactions, momentum derivatives of the Landau effective mass function up to second order are required. Results from our analytical formulas are compared with the exact results for zero- and finite-range potential and relativistic mean-field theoretical models. In all cases, inclusion of next-to-leading order temperature effects substantially extends the ranges of partial degeneracy for which the analytical treatment remains valid. Effects of many-body correlations that deserve further investigation are highlighted.« less

First and Higher Order Effects on Zero Order Radiative Transfer Model

NASA Astrophysics Data System (ADS)

Neelam, M.; Mohanty, B.

2014-12-01

Microwave radiative transfer model are valuable tool in understanding the complex land surface interactions. Past literature has largely focused on local sensitivity analysis for factor priotization and ignoring the interactions between the variables and uncertainties around them. Since land surface interactions are largely nonlinear, there always exist uncertainties, heterogeneities and interactions thus it is important to quantify them to draw accurate conclusions. In this effort, we used global sensitivity analysis to address the issues of variable uncertainty, higher order interactions, factor priotization and factor fixing for zero-order radiative transfer (ZRT) model. With the to-be-launched Soil Moisture Active Passive (SMAP) mission of NASA, it is very important to have a complete understanding of ZRT for soil moisture retrieval to direct future research and cal/val field campaigns. This is a first attempt to use GSA technique to quantify first order and higher order effects on brightness temperature from ZRT model. Our analyses reflect conditions observed during the growing agricultural season for corn and soybeans in two different regions in - Iowa, U.S.A and Winnipeg, Canada. We found that for corn fields in Iowa, there exist significant second order interactions between soil moisture, surface roughness parameters (RMS height and correlation length) and vegetation parameters (vegetation water content, structure and scattering albedo), whereas in Winnipeg, second order interactions are mainly due to soil moisture and vegetation parameters. But for soybean fields in both Iowa and Winnipeg, we found significant interactions only to exist between soil moisture and surface roughness parameters.

Predictive power of food web models based on body size decreases with trophic complexity.

PubMed

Jonsson, Tomas; Kaartinen, Riikka; Jonsson, Mattias; Bommarco, Riccardo

2018-05-01

Food web models parameterised using body size show promise to predict trophic interaction strengths (IS) and abundance dynamics. However, this remains to be rigorously tested in food webs beyond simple trophic modules, where indirect and intraguild interactions could be important and driven by traits other than body size. We systematically varied predator body size, guild composition and richness in microcosm insect webs and compared experimental outcomes with predictions of IS from models with allometrically scaled parameters. Body size was a strong predictor of IS in simple modules (r 2  = 0.92), but with increasing complexity the predictive power decreased, with model IS being consistently overestimated. We quantify the strength of observed trophic interaction modifications, partition this into density-mediated vs. behaviour-mediated indirect effects and show that model shortcomings in predicting IS is related to the size of behaviour-mediated effects. Our findings encourage development of dynamical food web models explicitly including and exploring indirect mechanisms. © 2018 John Wiley & Sons Ltd/CNRS.

IR characteristic simulation of city scenes based on radiosity model

NASA Astrophysics Data System (ADS)

Xiong, Xixian; Zhou, Fugen; Bai, Xiangzhi; Yu, Xiyu

2013-09-01

Reliable modeling for thermal infrared (IR) signatures of real-world city scenes is required for signature management of civil and military platforms. Traditional modeling methods generally assume that scene objects are individual entities during the physical processes occurring in infrared range. However, in reality, the physical scene involves convective and conductive interactions between objects as well as the radiations interactions between objects. A method based on radiosity model describes these complex effects. It has been developed to enable an accurate simulation for the radiance distribution of the city scenes. Firstly, the physical processes affecting the IR characteristic of city scenes were described. Secondly, heat balance equations were formed on the basis of combining the atmospheric conditions, shadow maps and the geometry of scene. Finally, finite difference method was used to calculate the kinetic temperature of object surface. A radiosity model was introduced to describe the scattering effect of radiation between surface elements in the scene. By the synthesis of objects radiance distribution in infrared range, we could obtain the IR characteristic of scene. Real infrared images and model predictions were shown and compared. The results demonstrate that this method can realistically simulate the IR characteristic of city scenes. It effectively displays the infrared shadow effects and the radiation interactions between objects in city scenes.

Inferring species interactions through joint mark–recapture analysis

USGS Publications Warehouse

Yackulic, Charles B.; Korman, Josh; Yard, Michael D.; Dzul, Maria C.

2018-01-01

Introduced species are frequently implicated in declines of native species. In many cases, however, evidence linking introduced species to native declines is weak. Failure to make strong inferences regarding the role of introduced species can hamper attempts to predict population viability and delay effective management responses. For many species, mark–recapture analysis is the more rigorous form of demographic analysis. However, to our knowledge, there are no mark–recapture models that allow for joint modeling of interacting species. Here, we introduce a two‐species mark–recapture population model in which the vital rates (and capture probabilities) of one species are allowed to vary in response to the abundance of the other species. We use a simulation study to explore bias and choose an approach to model selection. We then use the model to investigate species interactions between endangered humpback chub (Gila cypha) and introduced rainbow trout (Oncorhynchus mykiss) in the Colorado River between 2009 and 2016. In particular, we test hypotheses about how two environmental factors (turbidity and temperature), intraspecific density dependence, and rainbow trout abundance are related to survival, growth, and capture of juvenile humpback chub. We also project the long‐term effects of different rainbow trout abundances on adult humpback chub abundances. Our simulation study suggests this approach has minimal bias under potentially challenging circumstances (i.e., low capture probabilities) that characterized our application and that model selection using indicator variables could reliably identify the true generating model even when process error was high. When the model was applied to rainbow trout and humpback chub, we identified negative relationships between rainbow trout abundance and the survival, growth, and capture probability of juvenile humpback chub. Effects on interspecific interactions on survival and capture probability were strongly supported, whereas support for the growth effect was weaker. Environmental factors were also identified to be important and in many cases stronger than interspecific interactions, and there was still substantial unexplained variation in growth and survival rates. The general approach presented here for combining mark–recapture data for two species is applicable in many other systems and could be modified to model abundance of the invader via other modeling approaches.

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.

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.

Invited seminar, University of North Texas: An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

Invited OSU class lecture: An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on multiple ecosystem services

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on forest ecosystem services - ESRP mtg

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on multiple ecosystem services - 4/27/10

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

Stress in Marital Interaction and Change in Depression: A Longitudinal Analysis.

ERIC Educational Resources Information Center

Schafer, Robert B.; Wickrama, K. A. S.; Keith, Pat M.

1998-01-01

A model of the effects of two types of stress in everyday marital interaction on change in depressive symptoms is investigated. Mediating variables are unfavorable reflected appraisals, low competency, self-efficacy, and self-esteem. Participants (N=98 couples) were interviewed twice. The data supported the model. (Author/EMK)

Effects of structure on the interactions between five natural antimicrobial compounds and phospholipids of bacterial cell membrane on model monolayers

USDA-ARS?s Scientific Manuscript database

Monolayers composed of bacterial phospholipids were used as model membranes to study interactions of naturally occurring phenolic compounds 2,5-dihydroxybenzaldehyde, 2-hydroxy-5-methoxybenzaldehyde and the plant essential oil compounds carvacrol, cinnamaldehyde, and geraniol, previously found to be...

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.

Testing for gene-environment interaction under exposure misspecification.

PubMed

Sun, Ryan; Carroll, Raymond J; Christiani, David C; Lin, Xihong

2017-11-09

Complex interplay between genetic and environmental factors characterizes the etiology of many diseases. Modeling gene-environment (GxE) interactions is often challenged by the unknown functional form of the environment term in the true data-generating mechanism. We study the impact of misspecification of the environmental exposure effect on inference for the GxE interaction term in linear and logistic regression models. We first examine the asymptotic bias of the GxE interaction regression coefficient, allowing for confounders as well as arbitrary misspecification of the exposure and confounder effects. For linear regression, we show that under gene-environment independence and some confounder-dependent conditions, when the environment effect is misspecified, the regression coefficient of the GxE interaction can be unbiased. However, inference on the GxE interaction is still often incorrect. In logistic regression, we show that the regression coefficient is generally biased if the genetic factor is associated with the outcome directly or indirectly. Further, we show that the standard robust sandwich variance estimator for the GxE interaction does not perform well in practical GxE studies, and we provide an alternative testing procedure that has better finite sample properties. © 2017, The International Biometric Society.

Environmental Interactions and Epistasis Are Revealed in the Proteomic Responses to Complex Stimuli

PubMed Central

Samir, Parimal; Rahul; Slaughter, James C.; Link, Andrew J.

2015-01-01

Ultimately, the genotype of a cell and its interaction with the environment determine the cell’s biochemical state. While the cell’s response to a single stimulus has been studied extensively, a conceptual framework to model the effect of multiple environmental stimuli applied concurrently is not as well developed. In this study, we developed the concepts of environmental interactions and epistasis to explain the responses of the S. cerevisiae proteome to simultaneous environmental stimuli. We hypothesize that, as an abstraction, environmental stimuli can be treated as analogous to genetic elements. This would allow modeling of the effects of multiple stimuli using the concepts and tools developed for studying gene interactions. Mirroring gene interactions, our results show that environmental interactions play a critical role in determining the state of the proteome. We show that individual and complex environmental stimuli behave similarly to genetic elements in regulating the cellular responses to stimuli, including the phenomena of dominance and suppression. Interestingly, we observed that the effect of a stimulus on a protein is dominant over other stimuli if the response to the stimulus involves the protein. Using publicly available transcriptomic data, we find that environmental interactions and epistasis regulate transcriptomic responses as well. PMID:26247773

Mean-field behavior in coupled oscillators with attractive and repulsive interactions.

PubMed

Hong, Hyunsuk; Strogatz, Steven H

2012-05-01

We consider a variant of the Kuramoto model of coupled oscillators in which both attractive and repulsive pairwise interactions are allowed. The sign of the coupling is assumed to be a characteristic of a given oscillator. Specifically, some oscillators repel all the others, thus favoring an antiphase relationship with them. Other oscillators attract all the others, thus favoring an in-phase relationship. The Ott-Antonsen ansatz is used to derive the exact low-dimensional dynamics governing the system's long-term macroscopic behavior. The resulting analytical predictions agree with simulations of the full system. We explore the effects of changing various parameters, such as the width of the distribution of natural frequencies and the relative strengths and proportions of the positive and negative interactions. For the particular model studied here we find, unexpectedly, that the mixed interactions produce no new effects. The system exhibits conventional mean-field behavior and displays a second-order phase transition like that found in the original Kuramoto model. In contrast to our recent study of a different model with mixed interactions [Phys. Rev. Lett. 106, 054102 (2011)], the π state and traveling-wave state do not appear for the coupling type considered here.

Activity-induced clustering in model dumbbell swimmers: the role of hydrodynamic interactions.

PubMed

Furukawa, Akira; Marenduzzo, Davide; Cates, Michael E

2014-08-01

Using a fluid-particle dynamics approach, we numerically study the effects of hydrodynamic interactions on the collective dynamics of active suspensions within a simple model for bacterial motility: each microorganism is modeled as a stroke-averaged dumbbell swimmer with prescribed dipolar force pairs. Using both simulations and qualitative arguments, we show that, when the separation between swimmers is comparable to their size, the swimmers' motions are strongly affected by activity-induced hydrodynamic forces. To further understand these effects, we investigate semidilute suspensions of swimmers in the presence of thermal fluctuations. A direct comparison between simulations with and without hydrodynamic interactions shows these to enhance the dynamic clustering at a relatively small volume fraction; with our chosen model the key ingredient for this clustering behavior is hydrodynamic trapping of one swimmer by another, induced by the active forces. Furthermore, the density dependence of the motility (of both the translational and rotational motions) exhibits distinctly different behaviors with and without hydrodynamic interactions; we argue that this is linked to the clustering tendency. Our study illustrates the fact that hydrodynamic interactions not only affect kinetic pathways in active suspensions, but also cause major changes in their steady state properties.

Activity-induced clustering in model dumbbell swimmers: The role of hydrodynamic interactions

NASA Astrophysics Data System (ADS)

Furukawa, Akira; Marenduzzo, Davide; Cates, Michael E.

2014-08-01

Using a fluid-particle dynamics approach, we numerically study the effects of hydrodynamic interactions on the collective dynamics of active suspensions within a simple model for bacterial motility: each microorganism is modeled as a stroke-averaged dumbbell swimmer with prescribed dipolar force pairs. Using both simulations and qualitative arguments, we show that, when the separation between swimmers is comparable to their size, the swimmers' motions are strongly affected by activity-induced hydrodynamic forces. To further understand these effects, we investigate semidilute suspensions of swimmers in the presence of thermal fluctuations. A direct comparison between simulations with and without hydrodynamic interactions shows these to enhance the dynamic clustering at a relatively small volume fraction; with our chosen model the key ingredient for this clustering behavior is hydrodynamic trapping of one swimmer by another, induced by the active forces. Furthermore, the density dependence of the motility (of both the translational and rotational motions) exhibits distinctly different behaviors with and without hydrodynamic interactions; we argue that this is linked to the clustering tendency. Our study illustrates the fact that hydrodynamic interactions not only affect kinetic pathways in active suspensions, but also cause major changes in their steady state properties.

A crystal plasticity-based study of the relationship between microstructure and ultra-high-cycle fatigue life in nickel titanium alloys

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

Moore, John A.; Frankel, Dana; Prasannavenkatesan, Rajesh

Nickel Titanium (NiTi) alloys are often used in biomedical devices where failure due to mechanical fatigue is common. For other alloy systems, computational models have proven an effective means of determining the relationship between microstructural features and fatigue life. This work will extend the subset of those models which were based on crystal plasticity to examine the relationship between microstructure and fatigue life in NiTi alloys. It will explore the interaction between a spherical inclusion and the material’s free surface along with several NiTi microstructures reconstructed from 3D imaging. This work will determine the distance at which the free surfacemore » interacts with an inclusion and the effect of applied strain of surface-inclusion interaction. The effects of inclusion-inclusion interaction, matrix voiding, and matrix strengthening are explored and ranked with regards to their influence on fatigue life.« less

A crystal plasticity-based study of the relationship between microstructure and ultra-high-cycle fatigue life in nickel titanium alloys

DOE PAGES

Moore, John A.; Frankel, Dana; Prasannavenkatesan, Rajesh; ...

2016-06-06

Nickel Titanium (NiTi) alloys are often used in biomedical devices where failure due to mechanical fatigue is common. For other alloy systems, computational models have proven an effective means of determining the relationship between microstructural features and fatigue life. This work will extend the subset of those models which were based on crystal plasticity to examine the relationship between microstructure and fatigue life in NiTi alloys. It will explore the interaction between a spherical inclusion and the material’s free surface along with several NiTi microstructures reconstructed from 3D imaging. This work will determine the distance at which the free surfacemore » interacts with an inclusion and the effect of applied strain of surface-inclusion interaction. The effects of inclusion-inclusion interaction, matrix voiding, and matrix strengthening are explored and ranked with regards to their influence on fatigue life.« less

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.

Synergistic interactions between paracetamol and oxcarbazepine in somatic and visceral pain models in rodents.

PubMed

Tomić, Maja A; Vucković, Sonja M; Stepanović-Petrović, Radica M; Ugresić, Nenad D; Prostran, Milica S; Bosković, Bogdan

2010-04-01

Combination therapy is a valid approach in pain treatment, in which a reduction of doses could reduce side effects and still achieve optimal analgesia. We examined the effects of coadministered paracetamol, a widely used non-opioid analgesic, and oxcarbazepine, a relatively novel anticonvulsant with analgesic properties, in a rat model of paw inflammatory hyperalgesia and in a mice model of visceral pain and determined the type of interaction between components. The effects of paracetamol, oxcarbazepine, and their combinations were examined in carrageenan-induced (0.1 mL, 1%) paw inflammatory hyperalgesia in rats and in an acetic acid-induced (10 mg/kg, 0.75%) writhing test in mice. In both models, drugs were coadministered in fixed-dose fractions of the 50% effective dose (ED(50)), and type of interaction was determined by isobolographic analysis. Paracetamol (50-200 mg/kg peroral), oxcarbazepine (40-160 mg/kg peroral), and their combination (1/8, 1/4, 1/3, and 1/2 of a single drug ED(50)) produced a significant, dose-dependent antihyperalgesia in carrageenan-injected rats. In the writhing test in mice, paracetamol (60-180 mg/kg peroral), oxcarbazepine (20-80 mg/kg peroral), and their combination (1/16, 1/8, 1/4, and 1/2 of a single drug ED(50)) significantly and dose dependently reduced the number of writhes. In both models, isobolographic analysis revealed a significant synergistic interaction between paracetamol and oxcarbazepine, with a >4-fold reduction of doses of both drugs in combination, compared with single drugs ED(50). The synergistic interaction between paracetamol and oxcarbazepine provides new information about combination pain treatment and should be explored further in patients, especially with somatic and/or visceral pain.

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.

Consumer-mediated recycling and cascading trophic interactions.

PubMed

Leroux, Shawn J; Loreau, Michel

2010-07-01

Cascading trophic interactions mediated by consumers are complex phenomena, which encompass many direct and indirect effects. Nonetheless, most experiments and theory on the topic focus uniquely on the indirect, positive effects of predators on producers via regulation of herbivores. Empirical research in aquatic ecosystems, however, demonstrate that the indirect, positive effects of consumer-mediated recycling on primary producer stocks may be larger than the effects of herbivore regulation, particularly when predators have access to alternative prey. We derive an ecosystem model with both recipient- and donor-controlled trophic relationships to test the conditions of four hypotheses generated from recent empirical work on the role of consumer-mediated recycling in cascading trophic interactions. Our model predicts that predator regulation of herbivores will have larger, positive effects on producers than consumer-mediated recycling in most cases but that consumer-mediated recycling does generally have a positive effect on producer stocks. We demonstrate that herbivore recycling will have larger effects on producer biomass than predator recycling when turnover rates and recycling efficiencies are high and predators prefer local prey. In addition, predictions suggest that consumer-mediated recycling has the largest effects on primary producers when predators prefer allochthonous prey and predator attack rates are high. Finally, our model predicts that consumer-mediated recycling effects may not be largest when external nutrient loading is low. Our model predictions highlight predator and prey feeding relationships, turnover rates, and external nutrient loading rates as key determinants of the strength of cascading trophic interactions. We show that existing hypotheses from specific empirical systems do not occur under all conditions, which further exacerbates the need to consider a broad suite of mechanisms when investigating trophic cascades.

Probing the smearing effect by a pointlike graviton in the plane-wave matrix model

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

Lee, Bum-Hoon; Nam, Siyoung; Shin, Hyeonjoon

2010-08-15

We investigate the interaction between a flat membrane and pointlike graviton in the plane-wave matrix model. The one-loop effective potential in the large-distance limit is computed and is shown to be of r{sup -3} type where r is the distance between two objects. This type of interaction has been interpreted as the one incorporating the smearing effect due to the configuration of a flat membrane in a plane-wave background. Our results support this interpretation and provide more evidence about it.

The negative effects of prejudice on interpersonal relationships within adolescent peer groups.

PubMed

Poteat, V Paul; Mereish, Ethan H; Birkett, Michelle

2015-04-01

Social development theories highlight the centrality of peer groups during adolescence and their role in socializing attitudes and behaviors. In this longitudinal study, we tested the effects of group-level prejudice on ensuing positive and negative interpersonal interactions among peers over a 7-month period. We used social network analysis to identify peer groups based on sociometric nominations, followed by multilevel modeling of the effects of sexual prejudice at the group level on interpersonal interactions among individuals in these groups. As hypothesized, the interpersonal interactions in peer groups with stronger group-level sexual prejudice were distinct from and poorer than those in groups with weaker group-level sexual prejudice. Moreover, longitudinal models indicated that adolescents in groups with stronger initial sexual prejudice reported worse interpersonal interactions with their peers seven months later. These findings provide a contextual understanding of prejudice and its negative effects on how adolescents come to relate with one another over time. (c) 2015 APA, all rights reserved).

Effectiveness of Interactive Multimedia Environment on Language Acquisition Skills of 6th Grade Students in the United Arab Emirates

ERIC Educational Resources Information Center

Almekhlafi, Abdurrahman Ghaleb

2006-01-01

This study investigated the effect of interactive multimedia (IMM) program on students' acquisition of some English as a second language (ESL) skills. An interactive multimedia CD-ROM was used with ninety 6th grade ESL students in Al-Ain Model School 2, United Arab Emirates. Students were selected and divided into experimental and control groups…

Dynamic interactions between visual working memory and saccade target selection

PubMed Central

Schneegans, Sebastian; Spencer, John P.; Schöner, Gregor; Hwang, Seongmin; Hollingworth, Andrew

2014-01-01

Recent psychophysical experiments have shown that working memory for visual surface features interacts with saccadic motor planning, even in tasks where the saccade target is unambiguously specified by spatial cues. Specifically, a match between a memorized color and the color of either the designated target or a distractor stimulus influences saccade target selection, saccade amplitudes, and latencies in a systematic fashion. To elucidate these effects, we present a dynamic neural field model in combination with new experimental data. The model captures the neural processes underlying visual perception, working memory, and saccade planning relevant to the psychophysical experiment. It consists of a low-level visual sensory representation that interacts with two separate pathways: a spatial pathway implementing spatial attention and saccade generation, and a surface feature pathway implementing color working memory and feature attention. Due to bidirectional coupling between visual working memory and feature attention in the model, the working memory content can indirectly exert an effect on perceptual processing in the low-level sensory representation. This in turn biases saccadic movement planning in the spatial pathway, allowing the model to quantitatively reproduce the observed interaction effects. The continuous coupling between representations in the model also implies that modulation should be bidirectional, and model simulations provide specific predictions for complementary effects of saccade target selection on visual working memory. These predictions were empirically confirmed in a new experiment: Memory for a sample color was biased toward the color of a task-irrelevant saccade target object, demonstrating the bidirectional coupling between visual working memory and perceptual processing. PMID:25228628

Exploring social structure effect on language evolution based on a computational model

NASA Astrophysics Data System (ADS)

Gong, Tao; Minett, James; Wang, William

2008-06-01

A compositionality-regularity coevolution model is adopted to explore the effect of social structure on language emergence and maintenance. Based on this model, we explore language evolution in three experiments, and discuss the role of a popular agent in language evolution, the relationship between mutual understanding and social hierarchy, and the effect of inter-community communications and that of simple linguistic features on convergence of communal languages in two communities. This work embodies several important interactions during social learning, and introduces a new approach that manipulates individuals' probabilities to participate in social interactions to study the effect of social structure. We hope it will stimulate further theoretical and empirical explorations on language evolution in a social environment.

Flow structure generated by perpendicular blade-vortex interaction and implications for helicopter noise prediction. Volume 1: Measurements

NASA Technical Reports Server (NTRS)

Wittmer, Kenneth S.; Devenport, William J.

1996-01-01

The perpendicular interaction of a streamwise vortex with an infinite span helicopter blade was modeled experimentally in incompressible flow. Three-component velocity and turbulence measurements were made using a sub-miniature four sensor hot-wire probe. Vortex core parameters (radius, peak tangential velocity, circulation, and centerline axial velocity deficit) were determined as functions of blade-vortex separation, streamwise position, blade angle of attack, vortex strength, and vortex size. The downstream development of the flow shows that the interaction of the vortex with the blade wake is the primary cause of the changes in the core parameters. The blade sheds negative vorticity into its wake as a result of the induced angle of attack generated by the passing vortex. Instability in the vortex core due to its interaction with this negative vorticity region appears to be the catalyst for the magnification of the size and intensity of the turbulent flowfield downstream of the interaction. In general, the core radius increases while peak tangential velocity decreases with the effect being greater for smaller separations. These effects are largely independent of blade angle of attack; and if these parameters are normalized on their undisturbed values, then the effects of the vortex strength appear much weaker. Two theoretical models were developed to aid in extending the results to other flow conditions. An empirical model was developed for core parameter prediction which has some rudimentary physical basis, implying usefulness beyond a simple curve fit. An inviscid flow model was also created to estimate the vorticity shed by the interaction blade, and to predict the early stages of its incorporation into the interacting vortex.

Routine Discovery of Complex Genetic Models using Genetic Algorithms

PubMed Central

Moore, Jason H.; Hahn, Lance W.; Ritchie, Marylyn D.; Thornton, Tricia A.; White, Bill C.

2010-01-01

Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes. PMID:20948983

Reputation Effects in Social Networks Do Not Promote Cooperation: An Experimental Test of the Raub & Weesie Model.

PubMed

Corten, Rense; Rosenkranz, Stephanie; Buskens, Vincent; Cook, Karen S

2016-01-01

Despite the popularity of the notion that social cohesion in the form of dense social networks promotes cooperation in Prisoner's Dilemmas through reputation, very little experimental evidence for this claim exists. We address this issue by testing hypotheses from one of the few rigorous game-theoretic models on this topic, the Raub & Weesie model, in two incentivized lab experiments. In the experiments, 156 subjects played repeated two-person PDs in groups of six. In the "atomized interactions" condition, subjects were only informed about the outcomes of their own interactions, while in the "embedded" condition, subjects were informed about the outcomes of all interactions in their group, allowing for reputation effects. The design of the experiments followed the specification of the RW model as closely as possible. For those aspects of the model that had to be modified to allow practical implementation in an experiment, we present additional analyses that show that these modifications do not affect the predictions. Contrary to expectations, we do not find that cooperation is higher in the embedded condition than in the atomized interaction. Instead, our results are consistent with an interpretation of the RW model that includes random noise, or with learning models of cooperation in networks.

Food intake attenuates the drug interaction between new quinolones and aluminum.

PubMed

Imaoka, Ayuko; Abiru, Kosuke; Akiyoshi, Takeshi; Ohtani, Hisakazu

2018-01-01

Intestinal absorption of new quinolones is decreased by oral administration of polyvalent metal cations. Some clinical studies have demonstrated this drug - drug interaction is more prominent under fasted condition. However, the effect of food intake on the extent of drug - drug interaction between new quinolones and metal cations remains to be investigated quantitatively and systematically. The aim of this study was to develop an animal model that enables to evaluate the effect of food intake on the extent of drug - drug interaction in the gastrointestinal tract by chelation and to apply the model to evaluate quantitatively the effect of food intake on the drug - drug interaction between two new quinolones, ofloxacin or ciprofloxacin and sucralfate. The rats were orally administered new quinolones (5.3 mg/kg of ofloxacin or 10 mg/kg of ciprofloxacin) with or without 13.3 mg/kg of sucralfate under fasted or fed condition and plasma concentration profiles of new quinolones were monitored. To the fed group, standard breakfast used in human studies was pasted and administered at a dose of 8.8 g/kg. The area under the plasma concentration - time curves (AUC 0-6 ) of ofloxacin and ciprofloxacin under the fasted condition were significantly decreased to 28.8 and 17.1% by co-administration of sucralfate, respectively. On the contrary, sucralfate moderately decreased the AUC 0-6 of ofloxacin and ciprofloxacin to 54.9 and 33.2%, respectively, under fed condition. The effects of sucralfate and food intake on the kinetics of ofloxacin in this study were well consistent with the results of previous clinical trial. The developed animal model quantitatively reproduced the effect of food intake on the drug - drug interaction between ofloxacin and sucralfate. The similar influences were observed for the drug - drug interaction between ciprofloxacin and sucralfate, suggesting that the extent of drug - drug interaction caused by chelation is generally attenuated by food intake.

Implementation of a boundary element method to solve for the near field effects of an array of WECs

NASA Astrophysics Data System (ADS)

Oskamp, J. A.; Ozkan-Haller, H. T.

2010-12-01

When Wave Energy Converters (WECs) are installed, they affect the shoreline wave climate by removing some of the wave energy which would have reached the shore. Before large WEC projects are launched, it is important to understand the potential coastal impacts of these installations. The high cost associated with ocean scale testing invites the use of hydrodynamic models to play a major role in estimating these effects. In this study, a wave structure interaction program (WAMIT) is used to model an array of WECs. The program predicts the wave field throughout the array using a boundary element method to solve the potential flow fluid problem, taking into account the incident waves, the power dissipated, and the way each WEC moves and interacts with the others. This model is appropriate for a small domain near the WEC array in order to resolve the details in the interactions, but not extending to the coastline (where the far-field effects must be assessed). To propagate these effects to the coastline, the waves leaving this small domain will be used as boundary conditions for a larger model domain which will assess the shoreline effects caused by the array. The immediate work is concerned with setting up the WAMIT model for a small array of point absorbers. A 1:33 scale lab test is planned and will provide data to validate the WAMIT model on this small domain before it is nested with the larger domain to estimate shoreline effects.

Additive interaction between heterogeneous environmental ...

EPA Pesticide Factsheets

BACKGROUND Environmental exposures often occur in tandem; however, epidemiological research often focuses on singular exposures. Statistical interactions among broad, well-characterized environmental domains have not yet been evaluated in association with health. We address this gap by conducting a county-level cross-sectional analysis of interactions between Environmental Quality Index (EQI) domain indices on preterm birth in the Unites States from 2000-2005.METHODS: The EQI, a county-level index constructed for the 2000-2005 time period, was constructed from five domain-specific indices (air, water, land, built and sociodemographic) using principal component analyses. County-level preterm birth rates (n=3141) were estimated using live births from the National Center for Health Statistics. Linear regression was used to estimate prevalence differences (PD) and 95% confidence intervals (CI) comparing worse environmental quality to the better quality for each model for a) each individual domain main effect b) the interaction contrast and c) the two main effects plus interaction effect (i.e. the “net effect”) to show departure from additive interaction for the all U.S counties. Analyses were also performed for subgroupings by four urban/rural strata. RESULTS: We found the suggestion of antagonistic interactions but no synergism, along with several purely additive (i.e., no interaction) associations. In the non-stratified model, we observed antagonistic interac

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.

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.

The effect of front-to-rear propeller spacing on the interaction noise of a model counterrotation propeller at cruise conditions

NASA Technical Reports Server (NTRS)

Dittmar, James H.

1987-01-01

The effect of front-to-rear propeller spacing on the interaction noise of a counterrotation propeller model was measured at cruise conditions. The data taken at an axial Mach number of 0.80 behaved as expected: interaction noise was reduced with increased spacing. The data taken at M=0.76 and M=0.72 did not behave as expected. At some of the test conditions the noise was unchanged; others even showed noise increases with increased spacing. A possible explanation, involving the amount of downstream blade area impacted by the tip vortex, is presented.

Volcanism-Climate Interactions

NASA Technical Reports Server (NTRS)

Walter, Louis S. (Editor); Desilva, Shanaka (Editor)

1991-01-01

The range of disciplines in the study of volcanism-climate interactions includes paleoclimate, volcanology, petrology, tectonics, cloud physics and chemistry, and climate and radiation modeling. Questions encountered in understanding the interactions include: the source and evolution of sulfur and sulfur-gaseous species in magmas; their entrainment in volcanic plumes and injection into the stratosphere; their dissipation rates; and their radiative effects. Other issues include modeling and measuring regional and global effects of such large, dense clouds. A broad-range plan of research designed to answer these questions was defined. The plan includes observations of volcanoes, rocks, trees, and ice cores, as well as satellite and aircraft observations of erupting volcanoes and resulting lumes and clouds.

Model of interaction in Smart Grid on the basis of multi-agent system

NASA Astrophysics Data System (ADS)

Engel, E. A.; Kovalev, I. V.; Engel, N. E.

2016-11-01

This paper presents model of interaction in Smart Grid on the basis of multi-agent system. The use of travelling waves in the multi-agent system describes the behavior of the Smart Grid from the local point, which is being the complement of the conventional approach. The simulation results show that the absorption of the wave in the distributed multi-agent systems is effectively simulated the interaction in Smart Grid.

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

Effects of fluid structure interaction in a three dimensional model of the spinal subarachnoid space.

PubMed

Cheng, Shaokoon; Fletcher, David; Hemley, Sarah; Stoodley, Marcus; Bilston, Lynne

2014-08-22

It is unknown whether spinal cord motion has a significant effect on cerebrospinal fluid (CSF) pressure and therefore the importance of including fluid structure interaction (FSI) in computational fluid dynamics models (CFD) of the spinal subarachnoid space (SAS) is unclear. This study aims to determine the effects of FSI on CSF pressure and spinal cord motion in a normal and in a stenosis model of the SAS. A three-dimensional patient specific model of the SAS and spinal cord were constructed from MR anatomical images and CSF flow rate measurements obtained from a healthy human being. The area of SAS at spinal level T4 was constricted by 20% to represent the stenosis model. FSI simulations in both models were performed by running ANSYS CFX and ANSYS Mechanical in tandem. Results from this study show that the effect of FSI on CSF pressure is only about 1% in both the normal and stenosis models and therefore show that FSI has a negligible effect on CSF pressure. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Effect of salt entropy on protein solubility and Hofmeister series

NASA Astrophysics Data System (ADS)

Dahal, Yuba; Schmit, Jeremy

We present a theory of salt effects on protein solubility that accounts for salting-in, salting-out, and the Hofmeister series. We represent protein charge by the first order multipole expansion to include attractive and repulsive electrostatic interactions in the model. Our model also includes non-electrostatic protein-ion interactions, and ion-solvent interactions via an effective solvated ion radius. We find that the finite size of the ions has significant effects on the translational entropy of the salt, which accounts for the changes in the protein solubility. At low salt the dominant effect comes from the entropic cost of confining ions within the aggregate. At high concentrations the salt drives a depletion attraction that favors aggregation. Our theory explains the reversal in the Hofmeister series observed in lysozyme cloud point measurements and semi-quantitatively describes the solubility of lysozyme and chymosin crystals.

Predicting the sensitivity of populations from individual exposure to chemicals: the role of ecological interactions.

PubMed

Gabsi, Faten; Schäffer, Andreas; Preuss, Thomas G

2014-07-01

Population responses to chemical stress exposure are influenced by nonchemical, environmental processes such as species interactions. A realistic quantification of chemical toxicity to populations calls for the use of methodologies that integrate these multiple stress effects. The authors used an individual-based model for Daphnia magna as a virtual laboratory to determine the influence of ecological interactions on population sensitivity to chemicals with different modes of action on individuals. In the model, hypothetical chemical toxicity targeted different vital individual-level processes: reproduction, survival, feeding rate, or somatic growth rate. As for species interactions, predatory and competition effects on daphnid populations were implemented following a worst-case approach. The population abundance was simulated at different food levels and exposure scenarios, assuming exposure to chemical stress solely or in combination with either competition or predation. The chemical always targeted one vital endpoint. Equal toxicity-inhibition levels differently affected the population abundance with and without species interactions. In addition, population responses to chemicals were highly sensitive to the environmental stressor (predator or competitor) and to the food level. Results show that population resilience cannot be attributed to chemical stress only. Accounting for the relevant ecological interactions would reduce uncertainties when extrapolating effects of chemicals from individuals to the population level. Validated population models should be used for a more realistic risk assessment of chemicals. © 2014 SETAC.

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

Nesterov, V. A., E-mail: archerix@ukpost.ua

On the basis of the energy-density method, the effect of simultaneously taking into account the Pauli exclusion principle and the monopole and quadrupole polarizations of interacting nuclei on their interaction potential is considered for the example of the {sup 16}O + {sup 16}O system by using the wave function for the two-center shell model. The calculations performed in the adiabatic approximation reveal that the inclusion of the Pauli exclusion principle and the polarization of interacting nuclei, especially their quadrupole polarization, has a substantial effect on the potential of the nucleus-nucleus interaction.

EFFECTS OF LASER RADIATION ON MATTER. LASER PLASMA: Spatial-temporal distribution of a mechanical load resulting from interaction of laser radiation with a barrier (analytic model)

NASA Astrophysics Data System (ADS)

Fedyushin, B. T.

1992-01-01

The concepts developed earlier are used to propose a simple analytic model describing the spatial-temporal distribution of a mechanical load (pressure, impulse) resulting from interaction of laser radiation with a planar barrier surrounded by air. The correctness of the model is supported by a comparison with experimental results.

Multi-View Interaction Modelling of human collaboration processes: a business process study of head and neck cancer care in a Dutch academic hospital.

PubMed

Stuit, Marco; Wortmann, Hans; Szirbik, Nick; Roodenburg, Jan

2011-12-01

In the healthcare domain, human collaboration processes (HCPs), which consist of interactions between healthcare workers from different (para)medical disciplines and departments, are of growing importance as healthcare delivery becomes increasingly integrated. Existing workflow-based process modelling tools for healthcare process management, which are the most commonly applied, are not suited for healthcare HCPs mainly due to their focus on the definition of task sequences instead of the graphical description of human interactions. This paper uses a case study of a healthcare HCP at a Dutch academic hospital to evaluate a novel interaction-centric process modelling method. The HCP under study is the care pathway performed by the head and neck oncology team. The evaluation results show that the method brings innovative, effective, and useful features. First, it collects and formalizes the tacit domain knowledge of the interviewed healthcare workers in individual interaction diagrams. Second, the method automatically integrates these local diagrams into a single global interaction diagram that reflects the consolidated domain knowledge. Third, the case study illustrates how the method utilizes a graphical modelling language for effective tree-based description of interactions, their composition and routing relations, and their roles. A process analysis of the global interaction diagram is shown to identify HCP improvement opportunities. The proposed interaction-centric method has wider applicability since interactions are the core of most multidisciplinary patient-care processes. A discussion argues that, although (multidisciplinary) collaboration is in many cases not optimal in the healthcare domain, it is increasingly considered a necessity to improve integration, continuity, and quality of care. The proposed method is helpful to describe, analyze, and improve the functioning of healthcare collaboration. Copyright © 2011 Elsevier Inc. All rights reserved.

Cross-comparison of spacecraft-environment interaction model predictions applied to Solar Probe Plus near perihelion

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

Marchand, R.; Miyake, Y.; Usui, H.

2014-06-15

Five spacecraft-plasma models are used to simulate the interaction of a simplified geometry Solar Probe Plus (SPP) satellite with the space environment under representative solar wind conditions near perihelion. By considering similarities and differences between results obtained with different numerical approaches under well defined conditions, the consistency and validity of our models can be assessed. The impact on model predictions of physical effects of importance in the SPP mission is also considered by comparing results obtained with and without these effects. Simulation results are presented and compared with increasing levels of complexity in the physics of interaction between solar environmentmore » and the SPP spacecraft. The comparisons focus particularly on spacecraft floating potentials, contributions to the currents collected and emitted by the spacecraft, and on the potential and density spatial profiles near the satellite. The physical effects considered include spacecraft charging, photoelectron and secondary electron emission, and the presence of a background magnetic field. Model predictions obtained with our different computational approaches are found to be in agreement within 2% when the same physical processes are taken into account and treated similarly. The comparisons thus indicate that, with the correct description of important physical effects, our simulation models should have the required skill to predict details of satellite-plasma interaction physics under relevant conditions, with a good level of confidence. Our models concur in predicting a negative floating potential V{sub fl}∼−10V for SPP at perihelion. They also predict a “saturated emission regime” whereby most emitted photo- and secondary electron will be reflected by a potential barrier near the surface, back to the spacecraft where they will be recollected.« less

Physical processes in wheel-rail contact and its implications on vehicle-track interaction

NASA Astrophysics Data System (ADS)

Six, K.; Meierhofer, A.; Müller, G.; Dietmaier, P.

2015-05-01

Friction within the wheel-rail contact highly influences all aspects of vehicle-track interaction. Models describing this frictional behaviour are of high relevance, for example, for reliable predictions on drive train dynamics. It has been shown by experiments, that the friction at a certain position on rail is not describable by only one number for the coefficient of friction. Beside the contact conditions (existence of liquids, solid third bodies, etc.) the vehicle speed, normal loading and contact geometry are further influencing factors. State-of-the-art models are not able to account for this sufficiently. Thus, an Extended-Creep-Force-Model was developed taking into account effects from third body layers. This model is able to describe all considered effects. In this way, a significant improvement of the prediction quality with respect to all aspects of vehicle-track interaction is expected.

Effects of noise and confidence thresholds in nominal and metric Axelrod dynamics of social influence

NASA Astrophysics Data System (ADS)

de Sanctis, Luca; Galla, Tobias

2009-04-01

We study the effects of bounded confidence thresholds and of interaction and external noise on Axelrod’s model of social influence. Our study is based on a combination of numerical simulations and an integration of the mean-field master equation describing the system in the thermodynamic limit. We find that interaction thresholds affect the system only quantitatively, but that they do not alter the basic phase structure. The known crossover between an ordered and a disordered state in finite systems subject to external noise persists in models with general confidence threshold. Interaction noise here facilitates the dynamics and reduces relaxation times. We also study Axelrod systems with metric features and point out similarities and differences compared to models with nominal features.

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.

Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

Sakhanenko, Nikita A.

2010-01-01

Abstract Complex, non-additive genetic interactions are common and can be critical in determining phenotypes. Genome-wide association studies (GWAS) and similar statistical studies of linkage data, however, assume additive models of gene interactions in looking for genotype-phenotype associations. These statistical methods view the compound effects of multiple genes on a phenotype as a sum of influences of each gene and often miss a substantial part of the heritable effect. Such methods do not use any biological knowledge about underlying mechanisms. Modeling approaches from the artificial intelligence (AI) field that incorporate deterministic knowledge into models to perform statistical analysis can be applied to include prior knowledge in genetic analysis. We chose to use the most general such approach, Markov Logic Networks (MLNs), for combining deterministic knowledge with statistical analysis. Using simple, logistic regression-type MLNs we can replicate the results of traditional statistical methods, but we also show that we are able to go beyond finding independent markers linked to a phenotype by using joint inference without an independence assumption. The method is applied to genetic data on yeast sporulation, a complex phenotype with gene interactions. In addition to detecting all of the previously identified loci associated with sporulation, our method identifies four loci with smaller effects. Since their effect on sporulation is small, these four loci were not detected with methods that do not account for dependence between markers due to gene interactions. We show how gene interactions can be detected using more complex models, which can be used as a general framework for incorporating systems biology with genetics. PMID:20958249

Nature and Nurturing: Parenting in the Context of Child Temperament

ERIC Educational Resources Information Center

Kiff, Cara J.; Lengua, Liliana J.; Zalewski, Maureen

2011-01-01

Accounting for both bidirectional and interactive effects between parenting and child temperament can fine-tune theoretical models of the role of parenting and temperament in children's development of adjustment problems. Evidence for bidirectional and interactive effects between parenting and children's characteristics of frustration, fear,…

Proton-neutron sdg boson model and spherical-deformed phase transition

NASA Astrophysics Data System (ADS)

Otsuka, Takaharu; Sugita, Michiaki

1988-12-01

The spherical-deformed phase transition in nuclei is described in terms of the proton-neutron sdg interacting boson model. The sdg hamiltonian is introduced to model the pairing+quadrupole interaction. The phase transition is reproduced in this framework as a function of the boson number in the Sm isotopes, while all parameters in the hamiltonian are kept constant at values reasonable from the shell-model point of view. The sd IBM is derived from this model through the renormalization of g-boson effects.

Is there substituent cross-interaction effect in all the conjugated systems containing Cdbnd N polar bond? The substituent effects on the NMR chemical shifts of 2,5-disubstituted pyrimidines

NASA Astrophysics Data System (ADS)

Yuan, Hua; Zhang, Yan; Chen, Chun-Ni; Li, Meng-Yang

2018-03-01

The substituent cross-interaction effect in the substituted benzylidene anilines (p-Xsbnd C6H4sbnd CHdbnd Nsbnd C6H4sbnd Y-p) has been observed and widely investigated. In order to investigate whether the substituent cross-interaction effect exist in all the conjugated systems containing Cdbnd N polar bond, this paper employed 2-X-5-Y pyrimidines as the model compounds for study. The influences of substituents X and Y on the 1H NMR and 13C NMR chemical shifts of 2, 5-disubsitituted pyrimidines have been systematically investigated. Quantitative structure-chemical shifts relationship models have been built for δ(H4,6), δ(C2), δ(C4,6) and δ(C5) with four to six molecular descriptors. These models were confirmed of good stability and predictive performances by leave-one-out cross validation. This study indicates that the substituent effects of 2,5-disubstituted pyrimidines are much more complex than that of the substituted benzylidene anilines. More structural factors besides of Hammett parameter should be taken into consideration. Different from the substituted benzylidene anilines, the cross-interaction effect (Δσ2) of substituents X and Y has little contribution to δ(H4,6), δ(C2), δ(C5) and δ(C4,6) of 2,5-disubstituted pyrimidines.

A feature-based approach to modeling protein–protein interaction hot spots

PubMed Central

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-01-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to π–related interactions, especially π · · · π interactions. PMID:19273533

Towards end-to-end models for investigating the effects of climate and fishing in marine ecosystems

NASA Astrophysics Data System (ADS)

Travers, M.; Shin, Y.-J.; Jennings, S.; Cury, P.

2007-12-01

End-to-end models that represent ecosystem components from primary producers to top predators, linked through trophic interactions and affected by the abiotic environment, are expected to provide valuable tools for assessing the effects of climate change and fishing on ecosystem dynamics. Here, we review the main process-based approaches used for marine ecosystem modelling, focusing on the extent of the food web modelled, the forcing factors considered, the trophic processes represented, as well as the potential use and further development of the models. We consider models of a subset of the food web, models which represent the first attempts to couple low and high trophic levels, integrated models of the whole ecosystem, and size spectrum models. Comparisons within and among these groups of models highlight the preferential use of functional groups at low trophic levels and species at higher trophic levels and the different ways in which the models account for abiotic processes. The model comparisons also highlight the importance of choosing an appropriate spatial dimension for representing organism dynamics. Many of the reviewed models could be extended by adding components and by ensuring that the full life cycles of species components are represented, but end-to-end models should provide full coverage of ecosystem components, the integration of physical and biological processes at different scales and two-way interactions between ecosystem components. We suggest that this is best achieved by coupling models, but there are very few existing cases where the coupling supports true two-way interaction. The advantages of coupling models are that the extent of discretization and representation can be targeted to the part of the food web being considered, making their development time- and cost-effective. Processes such as predation can be coupled to allow the propagation of forcing factors effects up and down the food web. However, there needs to be a stronger focus on enabling two-way interaction, carefully selecting the key functional groups and species, reconciling different time and space scales and the methods of converting between energy, nutrients and mass.

Quantification of Interactions between Dynamic Cellular Network Functionalities by Cascaded Layering

PubMed Central

Prescott, Thomas P.; Lang, Moritz; Papachristodoulou, Antonis

2015-01-01

Large, naturally evolved biomolecular networks typically fulfil multiple functions. When modelling or redesigning such systems, functional subsystems are often analysed independently first, before subsequent integration into larger-scale computational models. In the design and analysis process, it is therefore important to quantitatively analyse and predict the dynamics of the interactions between integrated subsystems; in particular, how the incremental effect of integrating a subsystem into a network depends on the existing dynamics of that network. In this paper we present a framework for simulating the contribution of any given functional subsystem when integrated together with one or more other subsystems. This is achieved through a cascaded layering of a network into functional subsystems, where each layer is defined by an appropriate subset of the reactions. We exploit symmetries in our formulation to exhaustively quantify each subsystem’s incremental effects with minimal computational effort. When combining subsystems, their isolated behaviour may be amplified, attenuated, or be subject to more complicated effects. We propose the concept of mutual dynamics to quantify such nonlinear phenomena, thereby defining the incompatibility and cooperativity between all pairs of subsystems when integrated into any larger network. We exemplify our theoretical framework by analysing diverse behaviours in three dynamic models of signalling and metabolic pathways: the effect of crosstalk mechanisms on the dynamics of parallel signal transduction pathways; reciprocal side-effects between several integral feedback mechanisms and the subsystems they stabilise; and consequences of nonlinear interactions between elementary flux modes in glycolysis for metabolic engineering strategies. Our analysis shows that it is not sufficient to just specify subsystems and analyse their pairwise interactions; the environment in which the interaction takes place must also be explicitly defined. Our framework provides a natural representation of nonlinear interaction phenomena, and will therefore be an important tool for modelling large-scale evolved or synthetic biomolecular networks. PMID:25933116

Effective stochastic generator with site-dependent interactions

NASA Astrophysics Data System (ADS)

Khamehchi, Masoumeh; Jafarpour, Farhad H.

2017-11-01

It is known that the stochastic generators of effective processes associated with the unconditioned dynamics of rare events might consist of non-local interactions; however, it can be shown that there are special cases for which these generators can include local interactions. In this paper, we investigate this possibility by considering systems of classical particles moving on a one-dimensional lattice with open boundaries. The particles might have hard-core interactions similar to the particles in an exclusion process, or there can be many arbitrary particles at a single site in a zero-range process. Assuming that the interactions in the original process are local and site-independent, we will show that under certain constraints on the microscopic reaction rules, the stochastic generator of an unconditioned process can be local but site-dependent. As two examples, the asymmetric zero-temperature Glauber model and the A-model with diffusion are presented and studied under the above-mentioned constraints.

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.

Sensitivity of atmospheric muon flux calculation to low energy hadronic interaction models

NASA Astrophysics Data System (ADS)

Djemil, T.; Attallah, R.; Capdevielle, J. N.

2007-10-01

We investigate in this paper the impact of some up-to-date hadronic interaction models on the calculation of the atmospheric muon flux. Calculations are carried out with the air shower simulation code CORSIKA in combination with the hadronic interaction models FLUKA and UrQMD below 80 GeV/nucleon and NEXUS elsewhere. We also examine the atmospheric effects using two different parametrizations of the US standard atmosphere. The cosmic ray spectra of protons and α particles, the only primary particles considered here, are taken according to the force field model which describes properly solar modulation. Numerical results are compared with the BESS-2001 experimental data.

Influence of Dzyaloshinskii-Moriya interaction and ballistic spin transport in the two and three-dimensional Heisenberg model

NASA Astrophysics Data System (ADS)

Lima, L. S.

2018-06-01

We study the effect of Dzyaloshisnkii-Moriya interaction on spin transport in the two and three-dimensional Heisenberg antiferromagnetic models in the square lattice and cubic lattice respectively. For the three-dimensional model, we obtain a large peak for the spin conductivity and therefore a finite AC conductivity. For the two-dimensional model, we have gotten the AC spin conductivity tending to the infinity at ω → 0 limit and a suave decreasing in the spin conductivity with increase of ω. We obtain a small influence of the Dzyaloshinskii-Moriya interaction on the spin conductivity in all cases analyzed.

Representing climate, disturbance, and vegetation interactions in landscape models

Treesearch

Robert E. Keane; Donald McKenzie; Donald A. Falk; Erica A.H. Smithwick; Carol Miller; Lara-Karena B. Kellogg

2015-01-01

The prospect of rapidly changing climates over the next century calls for methods to predict their effects on myriad, interactive ecosystem processes. Spatially explicit models that simulate ecosystem dynamics at fine (plant, stand) to coarse (regional, global) scales are indispensable tools for meeting this challenge under a variety of possible futures. A special...

Interaction between Siblings in Primetime Television Families.

ERIC Educational Resources Information Center

Larson, Mary S.

1989-01-01

Analyzes three primetime family sitcoms in order to describe the nature of sibling interaction in television families. Research on television families is examined, and questions are raised concerning the value of television sibling images as role models for real people, and the effects of these models on family and peer relationships. (27…

Introducing Subgrid-scale convective cloud and aerosol interactions to the WRF-CMAQ integrated modeling system

EPA Science Inventory

Many regional and global climate models include aerosol indirect effects (AIE) on grid-scale/resolved clouds. However, the interaction between aerosols and convective clouds remains highly uncertain, as noted in the IPCC AR4 report. The objective of this work is to help fill in ...

The effect of wave current interactions on the storm surge and inundation in Charleston Harbor during Hurricane Hugo 1989

NASA Astrophysics Data System (ADS)

Xie, Lian; Liu, Huiqing; Peng, Machuan

The effects of wave-current interactions on the storm surge and inundation induced by Hurricane Hugo in and around the Charleston Harbor and its adjacent coastal regions are examined by using a three-dimensional (3-D) wave-current coupled modeling system. The 3-D storm surge and inundation modeling component of the coupled system is based on the Princeton ocean model (POM), whereas the wave modeling component is based on the third-generation wave model, simulating waves nearshore (SWAN). The results indicate that the effects of wave-induced surface, bottom, and radiation stresses can separately or in combination produce significant changes in storm surge and inundation. The effects of waves vary spatially. In some areas, the contribution of waves to peak storm surge during Hurricane Hugo reached as high as 0.76 m which led to substantial changes in the inundation and drying areas simulated by the storm surge model.

Space station crew safety: Human factors interaction model

NASA Technical Reports Server (NTRS)

Cohen, M. M.; Junge, M. K.

1985-01-01

A model of the various human factors issues and interactions that might affect crew safety is developed. The first step addressed systematically the central question: How is this space station different from all other spacecraft? A wide range of possible issue was identified and researched. Five major topics of human factors issues that interacted with crew safety resulted: Protocols, Critical Habitability, Work Related Issues, Crew Incapacitation and Personal Choice. Second, an interaction model was developed that would show some degree of cause and effect between objective environmental or operational conditions and the creation of potential safety hazards. The intermediary steps between these two extremes of causality were the effects on human performance and the results of degraded performance. The model contains three milestones: stressor, human performance (degraded) and safety hazard threshold. Between these milestones are two countermeasure intervention points. The first opportunity for intervention is the countermeasure against stress. If this countermeasure fails, performance degrades. The second opportunity for intervention is the countermeasure against error. If this second countermeasure fails, the threshold of a potential safety hazard may be crossed.

Powerful multilocus tests of genetic association in the presence of gene-gene and gene-environment interactions.

PubMed

Chatterjee, Nilanjan; Kalaylioglu, Zeynep; Moslehi, Roxana; Peters, Ulrike; Wacholder, Sholom

2006-12-01

In modern genetic epidemiology studies, the association between the disease and a genomic region, such as a candidate gene, is often investigated using multiple SNPs. We propose a multilocus test of genetic association that can account for genetic effects that might be modified by variants in other genes or by environmental factors. We consider use of the venerable and parsimonious Tukey's 1-degree-of-freedom model of interaction, which is natural when individual SNPs within a gene are associated with disease through a common biological mechanism; in contrast, many standard regression models are designed as if each SNP has unique functional significance. On the basis of Tukey's model, we propose a novel but computationally simple generalized test of association that can simultaneously capture both the main effects of the variants within a genomic region and their interactions with the variants in another region or with an environmental exposure. We compared performance of our method with that of two standard tests of association, one ignoring gene-gene/gene-environment interactions and the other based on a saturated model of interactions. We demonstrate major power advantages of our method both in analysis of data from a case-control study of the association between colorectal adenoma and DNA variants in the NAT2 genomic region, which are well known to be related to a common biological phenotype, and under different models of gene-gene interactions with use of simulated data.

Implementation of a plasma-neutral model in NIMROD

NASA Astrophysics Data System (ADS)

Taheri, S.; Shumlak, U.; King, J. R.

2016-10-01

Interaction between plasma fluid and neutral species is of great importance in the edge region of magnetically confined fusion plasmas. The presence of neutrals can have beneficial effects such as fueling burning plasmas and quenching the disruptions in tokamaks, as well as deleterious effects like depositing high energy particles on the vessel wall. The behavior of edge plasmas in magnetically confined systems has been investigated using computational approaches that utilize the fluid description for the plasma and Monte Carlo transport for neutrals. In this research a reacting plasma-neutral model is implemented in NIMROD to study the interaction between plasma and neutral fluids. This model, developed by E. T. Meier and U. Shumlak, combines a single-fluid magnetohydrodynamic (MHD) plasma model with a gas dynamic neutral fluid model which accounts for electron-impact ionization, radiative recombination, and resonant charge exchange. Incorporating this model into NIMROD allows the study of the interaction between neutrals and plasma in a variety of plasma science problems. An accelerated plasma moving through a neutral gas background in a coaxial electrode configuration is modeled, and the results are compared with previous calculations from the HiFi code.

Beyond the Young-Laplace model for cluster growth during dewetting of thin films: effective coarsening exponents and the role of long range dewetting interactions.

PubMed

Constantinescu, Adi; Golubović, Leonardo; Levandovsky, Artem

2013-09-01

Long range dewetting forces acting across thin films, such as the fundamental van der Waals interactions, may drive the formation of large clusters (tall multilayer islands) and pits, observed in thin films of diverse materials such as polymers, liquid crystals, and metals. In this study we further develop the methodology of the nonequilibrium statistical mechanics of thin films coarsening within continuum interface dynamics model incorporating long range dewetting interactions. The theoretical test bench model considered here is a generalization of the classical Mullins model for the dynamics of solid film surfaces. By analytic arguments and simulations of the model, we study the coarsening growth laws of clusters formed in thin films due to the dewetting interactions. The ultimate cluster growth scaling laws at long times are strongly universal: Short and long range dewetting interactions yield the same coarsening exponents. However, long range dewetting interactions, such as the van der Waals forces, introduce a distinct long lasting early time scaling behavior characterized by a slow growth of the cluster height/lateral size aspect ratio (i.e., a time-dependent Young angle) and by effective coarsening exponents that depend on cluster size. In this study, we develop a theory capable of analytically calculating these effective size-dependent coarsening exponents characterizing the cluster growth in the early time regime. Such a pronounced early time scaling behavior has been indeed seen in experiments; however, its physical origin has remained elusive to this date. Our theory attributes these observed phenomena to ubiquitous long range dewetting interactions acting across thin solid and liquid films. Our results are also applicable to cluster growth in initially very thin fluid films, formed by depositing a few monolayers or by a submonolayer deposition. Under this condition, the dominant coarsening mechanism is diffusive intercluster mass transport while the cluster coalescence plays a minor role, both in solid and in fluid films.

Brief report: learning via the electronic interactive whiteboard for two students with autism and a student with moderate intellectual disability.

PubMed

Yakubova, Gulnoza; Taber-Doughty, Teresa

2013-06-01

The effects of a multicomponent intervention (a self-operated video modeling and self-monitoring delivered via an electronic interactive whiteboard (IWB) and a system of least prompts) on skill acquisition and interaction behavior of two students with autism and one student with moderate intellectual disability were examined using a multi-probe across students design. Students were taught to operate and view video modeling clips, perform a chain of novel tasks and self-monitor task performance using a SMART Board IWB. Results support the effectiveness of a multicomponent intervention in improving students' skill acquisition. Results also highlight the use of this technology as a self-operated and interactive device rather than a traditional teacher-operated device to enhance students' active participation in learning.

Nuclear matter from effective quark-quark interaction.

PubMed

Baldo, M; Fukukawa, K

2014-12-12

We study neutron matter and symmetric nuclear matter with the quark-meson model for the two-nucleon interaction. The Bethe-Bruckner-Goldstone many-body theory is used to describe the correlations up to the three hole-line approximation with no extra parameters. At variance with other nonrelativistic realistic interactions, the three hole-line contribution turns out to be non-negligible and to have a substantial saturation effect. The saturation point of nuclear matter, the compressibility, the symmetry energy, and its slope are within the phenomenological constraints. Since the interaction also reproduces fairly well the properties of the three-nucleon system, these results indicate that the explicit introduction of the quark degrees of freedom within the considered constituent quark model is expected to reduce the role of three-body forces.

The home as a workplace: work-family interaction and psychological well-being in telework.

PubMed

Standen, P; Daniels, K; Lamond, D

1999-10-01

Home-based telework is a growing phenomenon with great potential to affect employees' psychological well-being. Although prior studies show both positive and negative effects on work-family interaction, conclusions are limited by the way telework, well-being, and work-family interaction have been modeled. The authors present a conceptual framework that describes telework as a multidimensional phenomenon and separates the effects of the home environment from those of distance from the organization. Propositions concerning work-family interaction are developed from P. Warr's (1987) model of the environmental antecedents of well-being, prior telework studies, and the work-family literature. Spillover between work and nonwork domains of well-being is discussed, and suggestions for future research on this complex issue are presented.

Rotor/Wing Interactions in Hover

NASA Technical Reports Server (NTRS)

Young, Larry A.; Derby, Michael R.

2002-01-01

Hover predictions of tiltrotor aircraft are hampered by the lack of accurate and computationally efficient models for rotor/wing interactional aerodynamics. This paper summarizes the development of an approximate, potential flow solution for the rotor-on-rotor and wing-on-rotor interactions. This analysis is based on actuator disk and vortex theory and the method of images. The analysis is applicable for out-of-ground-effect predictions. The analysis is particularly suited for aircraft preliminary design studies. Flow field predictions from this simple analytical model are validated against experimental data from previous studies. The paper concludes with an analytical assessment of the influence of rotor-on-rotor and wing-on-rotor interactions. This assessment examines the effect of rotor-to-wing offset distance, wing sweep, wing span, and flaperon incidence angle on tiltrotor inflow and performance.

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.

Evolution of spatially structured host-parasite interactions.

PubMed

Lion, S; Gandon, S

2015-01-01

Spatial structure has dramatic effects on the demography and the evolution of species. A large variety of theoretical models have attempted to understand how local dispersal may shape the coevolution of interacting species such as host-parasite interactions. The lack of a unifying framework is a serious impediment for anyone willing to understand current theory. Here, we review previous theoretical studies in the light of a single epidemiological model that allows us to explore the effects of both host and parasite migration rates on the evolution and coevolution of various life-history traits. We discuss the impact of local dispersal on parasite virulence, various host defence strategies and local adaptation. Our analysis shows that evolutionary and coevolutionary outcomes crucially depend on the details of the host-parasite life cycle and on which life-history trait is involved in the interaction. We also discuss experimental studies that support the effects of spatial structure on the evolution of host-parasite interactions. This review highlights major similarities between some theoretical results, but it also reveals an important gap between evolutionary and coevolutionary models. We discuss possible ways to bridge this gap within a more unified framework that would reconcile spatial epidemiology, evolution and coevolution. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Aircraft wake vortex transport model

DOT National Transportation Integrated Search

1974-03-31

A wake vortex transport model has been developed which includes the effects of wind and wind : shear, buoyancy, mutual and self-induction, ground plane interaction, viscous decay, finite core : and Crow instability effects. Photographic and ground-wi...

Assessment of combined antiandrogenic effects of binary parabens mixtures in a yeast-based reporter assay.

PubMed

Ma, Dehua; Chen, Lujun; Zhu, Xiaobiao; Li, Feifei; Liu, Cong; Liu, Rui

2014-05-01

To date, toxicological studies of endocrine disrupting chemicals (EDCs) have typically focused on single chemical exposures and associated effects. However, exposure to EDCs mixtures in the environment is common. Antiandrogens represent a group of EDCs, which draw increasing attention due to their resultant demasculinization and sexual disruption of aquatic organisms. Although there are a number of in vivo and in vitro studies investigating the combined effects of antiandrogen mixtures, these studies are mainly on selected model compounds such as flutamide, procymidone, and vinclozolin. The aim of the present study is to investigate the combined antiandrogenic effects of parabens, which are widely used antiandrogens in industrial and domestic commodities. A yeast-based human androgen receptor (hAR) assay (YAS) was applied to assess the antiandrogenic activities of n-propylparaben (nPrP), iso-propylparaben (iPrP), methylparaben (MeP), and 4-n-pentylphenol (PeP), as well as the binary mixtures of nPrP with each of the other three antiandrogens. All of the four compounds could exhibit antiandrogenic activity via the hAR. A linear interaction model was applied to quantitatively analyze the interaction between nPrP and each of the other three antiandrogens. The isoboles method was modified to show the variation of combined effects as the concentrations of mixed antiandrogens were changed. Graphs were constructed to show isoeffective curves of three binary mixtures based on the fitted linear interaction model and to evaluate the interaction of the mixed antiandrogens (synergism or antagonism). The combined effect of equimolar combinations of the three mixtures was also considered with the nonlinear isoboles method. The main effect parameters and interaction effect parameters in the linear interaction models of the three mixtures were different from zero. The results showed that any two antiandrogens in their binary mixtures tended to exert equal antiandrogenic activity in the linear concentration ranges. The antiandrogenicity of the binary mixture and the concentration of nPrP were fitted to a sigmoidal model if the concentrations of the other antiandrogens (iPrP, MeP, and PeP) in the mixture were lower than the AR saturation concentrations. Some concave isoboles above the additivity line appeared in all the three mixtures. There were some synergistic effects of the binary mixture of nPrP and MeP at low concentrations in the linear concentration ranges. Interesting, when the antiandrogens concentrations approached the saturation, the interaction between chemicals were antagonistic for all the three mixtures tested. When the toxicity of the three mixtures was assessed using nonlinear isoboles, only antagonism was observed for equimolar combinations of nPrP and iPrP as the concentrations were increased from the no-observed-effect-concentration (NOEC) to effective concentration of 80%. In addition, the interactions were changed from synergistic to antagonistic as effective concentrations were increased in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP. The combined effects of three binary antiandrogens mixtures in the linear ranges were successfully evaluated by curve fitting and isoboles. The combined effects of specific binary mixtures varied depending on the concentrations of the chemicals in the mixtures. At low concentrations in the linear concentration ranges, there was synergistic interaction existing in the binary mixture of nPrP and MeP. The interaction tended to be antagonistic as the antiandrogens approached saturation concentrations in mixtures of nPrP with each of the other three antiandrogens. The synergistic interaction was also found in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP, at low concentrations with another method of nonlinear isoboles. The mixture activities of binary antiandrogens had a tendency towards antagonism at high concentrations and synergism at low concentrations.

Analysis and application of opinion model with multiple topic interactions.

PubMed

Xiong, Fei; Liu, Yun; Wang, Liang; Wang, Ximeng

2017-08-01

To reveal heterogeneous behaviors of opinion evolution in different scenarios, we propose an opinion model with topic interactions. Individual opinions and topic features are represented by a multidimensional vector. We measure an agent's action towards a specific topic by the product of opinion and topic feature. When pairs of agents interact for a topic, their actions are introduced to opinion updates with bounded confidence. Simulation results show that a transition from a disordered state to a consensus state occurs at a critical point of the tolerance threshold, which depends on the opinion dimension. The critical point increases as the dimension of opinions increases. Multiple topics promote opinion interactions and lead to the formation of macroscopic opinion clusters. In addition, more topics accelerate the evolutionary process and weaken the effect of network topology. We use two sets of large-scale real data to evaluate the model, and the results prove its effectiveness in characterizing a real evolutionary process. Our model achieves high performance in individual action prediction and even outperforms state-of-the-art methods. Meanwhile, our model has much smaller computational complexity. This paper provides a demonstration for possible practical applications of theoretical opinion dynamics.

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

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.

Interplay between Magnetism, Superconductivity, and Orbital Order in 5-Pocket Model for Iron-Based Superconductors: Parquet Renormalization Group Study.

PubMed

Classen, Laura; Xing, Rui-Qi; Khodas, Maxim; Chubukov, Andrey V

2017-01-20

We report the results of the parquet renormalization group (RG) analysis of the phase diagram of the most general 5-pocket model for Fe-based superconductors. We use as an input the orbital structure of excitations near the five pockets made out of d_{xz}, d_{yz}, and d_{xy} orbitals and argue that there are 40 different interactions between low-energy fermions in the orbital basis. All interactions flow under the RG, as one progressively integrates out fermions with higher energies. We find that the low-energy behavior is amazingly simple, despite the large number of interactions. Namely, at low energies the full 5-pocket model effectively reduces either to a 3-pocket model made of one d_{xy} hole pocket and two electron pockets or a 4-pocket model made of two d_{xz}/d_{yz} hole pockets and two electron pockets. The leading instability in the effective 4-pocket model is a spontaneous orbital (nematic) order, followed by s^{+-} superconductivity. In the effective 3-pocket model, orbital fluctuations are weaker, and the system develops either s^{+-} superconductivity or a stripe spin-density wave. In the latter case, nematicity is induced by composite spin fluctuations.

Inferring protein domains associated with drug side effects based on drug-target interaction network.

PubMed

Iwata, Hiroaki; Mizutani, Sayaka; Tabei, Yasuo; Kotera, Masaaki; Goto, Susumu; Yamanishi, Yoshihiro

2013-01-01

Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains.

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

Chromatin loops as allosteric modulators of enhancer-promoter interactions.

PubMed

Doyle, Boryana; Fudenberg, Geoffrey; Imakaev, Maxim; Mirny, Leonid A

2014-10-01

The classic model of eukaryotic gene expression requires direct spatial contact between a distal enhancer and a proximal promoter. Recent Chromosome Conformation Capture (3C) studies show that enhancers and promoters are embedded in a complex network of looping interactions. Here we use a polymer model of chromatin fiber to investigate whether, and to what extent, looping interactions between elements in the vicinity of an enhancer-promoter pair can influence their contact frequency. Our equilibrium polymer simulations show that a chromatin loop, formed by elements flanking either an enhancer or a promoter, suppresses enhancer-promoter interactions, working as an insulator. A loop formed by elements located in the region between an enhancer and a promoter, on the contrary, facilitates their interactions. We find that different mechanisms underlie insulation and facilitation; insulation occurs due to steric exclusion by the loop, and is a global effect, while facilitation occurs due to an effective shortening of the enhancer-promoter genomic distance, and is a local effect. Consistently, we find that these effects manifest quite differently for in silico 3C and microscopy. Our results show that looping interactions that do not directly involve an enhancer-promoter pair can nevertheless significantly modulate their interactions. This phenomenon is analogous to allosteric regulation in proteins, where a conformational change triggered by binding of a regulatory molecule to one site affects the state of another site.

An approach to the ionic cholinergic interaction. Theoretical treatment of the interaction between tetramethylammonium and acetate ions

NASA Astrophysics Data System (ADS)

Zuccarello, Felice; Raudino, Antonio; Buemi, Giuseppe

1980-03-01

The interaction between the anionic site of cholinesterase and the cationic end of acetylcholine is estimated by considering a simplified model. The effect of the aqueous environment on the stability of the aggregate is considered.

Toxicodynamic analysis of the combined cholinesterase inhibition by paraoxon and methamidophos in human whole blood

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

Bosgra, Sieto; Eijkeren, Jan C.H. van; Schans, Marcel J. van der

2009-04-01

Theoretical work has shown that the isobole method is not generally valid as a method for testing the absence or presence of interaction (in the biochemical sense) between chemicals. The present study illustrates how interaction can be tested by fitting a toxicodynamic model to the results of a mixture experiment. The inhibition of cholinesterases (ChE) in human whole blood by various dose combinations of paraoxon and methamidophos was measured in vitro. A toxicodynamic model describing the processes related to both OPs in inhibiting AChE activity was developed, and fit to the observed activities. This model, not containing any interaction betweenmore » the two OPs, described the results from the mixture experiment well, and it was concluded that the OPs did not interact in the whole blood samples. While this approach of toxicodynamic modeling is the most appropriate method for predicting combined effects, it is not rapidly applicable. Therefore, we illustrate how toxicodynamic modeling can be used to explore under which conditions dose addition would give an acceptable approximation of the combined effects from various chemicals. In the specific case of paraoxon and methamidophos in whole blood samples, it was found that dose addition gave a reasonably accurate prediction of the combined effects, despite considerable difference in some of their rate constants, and mildly non-parallel dose-response curves. Other possibilities of validating dose-addition using toxicodynamic modeling are briefly discussed.« less

Local versus global interactions in nonequilibrium transitions: A model of social dynamics

NASA Astrophysics Data System (ADS)

González-Avella, J. C.; Eguíluz, V. M.; Cosenza, M. G.; Klemm, K.; Herrera, J. L.; San Miguel, M.

2006-04-01

A nonequilibrium system of locally interacting elements in a lattice with an absorbing order-disorder phase transition is studied under the effect of additional interacting fields. These fields are shown to produce interesting effects in the collective behavior of this system. Both for autonomous and external fields, disorder grows in the system when the probability of the elements to interact with the field is increased. There exists a threshold value of this probability beyond which the system is always disordered. The domain of parameters of the ordered regime is larger for nonuniform local fields than for spatially uniform fields. However, the zero field limit is discontinous. In the limit of vanishingly small probability of interaction with the field, autonomous or external fields are able to order a system that would fall in a disordered phase under local interactions of the elements alone. We consider different types of fields which are interpreted as forms of mass media acting on a social system in the context of Axelrod’s model for cultural dissemination.

Local versus global interactions in nonequilibrium transitions: A model of social dynamics.

PubMed

González-Avella, J C; Eguíluz, V M; Cosenza, M G; Klemm, K; Herrera, J L; San Miguel, M

2006-04-01

A nonequilibrium system of locally interacting elements in a lattice with an absorbing order-disorder phase transition is studied under the effect of additional interacting fields. These fields are shown to produce interesting effects in the collective behavior of this system. Both for autonomous and external fields, disorder grows in the system when the probability of the elements to interact with the field is increased. There exists a threshold value of this probability beyond which the system is always disordered. The domain of parameters of the ordered regime is larger for nonuniform local fields than for spatially uniform fields. However, the zero field limit is discontinous. In the limit of vanishingly small probability of interaction with the field, autonomous or external fields are able to order a system that would fall in a disordered phase under local interactions of the elements alone. We consider different types of fields which are interpreted as forms of mass media acting on a social system in the context of Axelrod's model for cultural dissemination.

Three-Nucleon Forces and Triplet Pairing in Neutron Matter

NASA Astrophysics Data System (ADS)

Papakonstantinou, P.; Clark, J. W.

2017-12-01

The existence of superfluidity of the neutron component in the core of a neutron star, associated specifically with triplet P-wave pairing, is currently an open question that is central to interpretation of the observed cooling curves and other neutron-star observables. Ab initio theoretical calculations aimed at resolving this issue face unique challenges in the relevant high-density domain, which reaches beyond the saturation density of symmetrical nuclear matter. These issues include uncertainties in the three-nucleon (3N) interaction and in the effects of strong short-range correlations—and more generally of in-medium modification of nucleonic self-energies and interactions. A survey of existing solutions of the gap equations in the triplet channel demonstrates that the net impact on the gap magnitude of 3N forces, coupled channels, and mass renormalization shows extreme variation dependent on specific theoretical inputs, in some cases even pointing to the absence of a triplet gap, thus motivating a detailed analysis of competing effects within a well-controlled model. In the present study, we track the effects of the 3N force and in-medium modifications in the representative case of the ^3P_2 channel, based on the Argonne v_{18} two-nucleon (2N) interaction supplemented by 3N interactions of the Urbana IX family. Sensitivity of the results to the input interaction is clearly demonstrated. We point out consistency issues with respect to the simultaneous treatment of 3N forces and in-medium effects, which warrant further investigation. We consider this pilot study as the first step toward a systematic and comprehensive exploration of coupled-channel ^3P F_2 pairing using a broad range of 2N and 3N interactions from the current generation of refined semi-phenomenological models and models derived from chiral effective field theory.

A network model of genomic hormone interactions underlying dementia and its translational validation through serendipitous off-target effect

PubMed Central

2013-01-01

Background While the majority of studies have focused on the association between sex hormones and dementia, emerging evidence supports the role of other hormone signals in increasing dementia risk. However, due to the lack of an integrated view on mechanistic interactions of hormone signaling pathways associated with dementia, molecular mechanisms through which hormones contribute to the increased risk of dementia has remained unclear and capacity of translating hormone signals to potential therapeutic and diagnostic applications in relation to dementia has been undervalued. Methods Using an integrative knowledge- and data-driven approach, a global hormone interaction network in the context of dementia was constructed, which was further filtered down to a model of convergent hormone signaling pathways. This model was evaluated for its biological and clinical relevance through pathway recovery test, evidence-based analysis, and biomarker-guided analysis. Translational validation of the model was performed using the proposed novel mechanism discovery approach based on ‘serendipitous off-target effects’. Results Our results reveal the existence of a well-connected hormone interaction network underlying dementia. Seven hormone signaling pathways converge at the core of the hormone interaction network, which are shown to be mechanistically linked to the risk of dementia. Amongst these pathways, estrogen signaling pathway takes the major part in the model and insulin signaling pathway is analyzed for its association to learning and memory functions. Validation of the model through serendipitous off-target effects suggests that hormone signaling pathways substantially contribute to the pathogenesis of dementia. Conclusions The integrated network model of hormone interactions underlying dementia may serve as an initial translational platform for identifying potential therapeutic targets and candidate biomarkers for dementia-spectrum disorders such as Alzheimer’s disease. PMID:23885764

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network.

PubMed

Katzman, Jared L; Shaham, Uri; Cloninger, Alexander; Bates, Jonathan; Jiang, Tingting; Kluger, Yuval

2018-02-26

Medical practitioners use survival models to explore and understand the relationships between patients' covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the linear Cox proportional hazards model require extensive feature engineering or prior medical knowledge to model treatment interaction at an individual level. While nonlinear survival methods, such as neural networks and survival forests, can inherently model these high-level interaction terms, they have yet to be shown as effective treatment recommender systems. We introduce DeepSurv, a Cox proportional hazards deep neural network and state-of-the-art survival method for modeling interactions between a patient's covariates and treatment effectiveness in order to provide personalized treatment recommendations. We perform a number of experiments training DeepSurv on simulated and real survival data. We demonstrate that DeepSurv performs as well as or better than other state-of-the-art survival models and validate that DeepSurv successfully models increasingly complex relationships between a patient's covariates and their risk of failure. We then show how DeepSurv models the relationship between a patient's features and effectiveness of different treatment options to show how DeepSurv can be used to provide individual treatment recommendations. Finally, we train DeepSurv on real clinical studies to demonstrate how it's personalized treatment recommendations would increase the survival time of a set of patients. The predictive and modeling capabilities of DeepSurv will enable medical researchers to use deep neural networks as a tool in their exploration, understanding, and prediction of the effects of a patient's characteristics on their risk of failure.

Selection of higher order regression models in the analysis of multi-factorial transcription data.

PubMed

Prazeres da Costa, Olivia; Hoffman, Arthur; Rey, Johannes W; Mansmann, Ulrich; Buch, Thorsten; Tresch, Achim

2014-01-01

Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.

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

A Meta-Analytic Investigation of Fiedler's Contingency Model of Leadership Effectiveness.

ERIC Educational Resources Information Center

Strube, Michael J.; Garcia, Joseph E.

According to Fiedler's Contingency Model of Leadership Effectiveness, group performance is a function of the leader-situation interaction. A review of past validations has found several problems associated with the model. Meta-analytic techniques were applied to the Contingency Model in order to assess the validation evidence quantitatively. The…

Modelling and simulation of particle-particle interaction in a magnetophoretic bio-separation chip

NASA Astrophysics Data System (ADS)

Alam, Manjurul; Golozar, Matin; Darabi, Jeff

2018-04-01

A Lagrangian particle trajectory model is developed to predict the interaction between cell-bead particle complexes and to track their trajectories in a magnetophoretic bio-separation chip. Magnetic flux gradients are simulated in the OpenFOAM CFD software and imported into MATLAB to obtain the trapping lengths and trajectories of the particles. A connector vector is introduced to calculate the interaction force between cell-bead complexes as they flow through a microfluidic device. The interaction force calculations are performed for cases where the connector vector is parallel, perpendicular, and at an angle of 45° with the applied magnetic field. The trajectories of the particles are simulated by solving a system of eight ordinary differential equations using a fourth order Runge-Kutta method. The model is then used to study the effects of geometric positions and angles of the connector vector between the particles as well as the cell size, number of beads per cell, and flow rate on the interaction force and trajectories of the particles. The results show that the interaction forces may be attractive or repulsive, depending on the orientation of the connector vector distance between the particle complexes and the applied magnetic field. When the interaction force is attractive, the particles are observed to merge and trap sooner than a single particle, whereas a repulsive interaction force has little or no effect on the trapping length.

A unification of mediation and interaction: a four-way decomposition

PubMed Central

VanderWeele, Tyler J.

2014-01-01

It is shown that the overall effect of an exposure on an outcome, in the presence of a mediator with which the exposure may interact, can be decomposed into four components: (i) the effect of the exposure in the absence of the mediator, (ii) the interactive effect when the mediator is left to what it would be in the absence of exposure, (iii) a mediated interaction, and (iv) a pure mediated effect. These four components, respectively, correspond to the portion of the effect that is due to neither mediation nor interaction, to just interaction (but not mediation), to both mediation and interaction, and to just mediation (but not interaction). This four-way decomposition unites methods that attribute effects to interactions and methods that assess mediation. Certain combinations of these four components correspond to measures for mediation, while other combinations correspond to measures of interaction previously proposed in the literature. Prior decompositions in the literature are in essence special cases of this four-way decomposition. The four-way decomposition can be carried out using standard statistical models, and software is provided to estimate each of the four components. The four-way decomposition provides maximum insight into how much of an effect is mediated, how much is due to interaction, how much is due to both mediation and interaction together, and how much is due to neither. PMID:25000145

A realistic host-vector transmission model for describing malaria prevalence pattern.

PubMed

Mandal, Sandip; Sinha, Somdatta; Sarkar, Ram Rup

2013-12-01

Malaria continues to be a major public health concern all over the world even after effective control policies have been employed, and considerable understanding of the disease biology have been attained, from both the experimental and modelling perspective. Interactions between different general and local processes, such as dependence on age and immunity of the human host, variations of temperature and rainfall in tropical and sub-tropical areas, and continued presence of asymptomatic infections, regulate the host-vector interactions, and are responsible for the continuing disease prevalence pattern.In this paper, a general mathematical model of malaria transmission is developed considering short and long-term age-dependent immunity of human host and its interaction with pathogen-infected mosquito vector. The model is studied analytically and numerically to understand the role of different parameters related to mosquitoes and humans. To validate the model with a disease prevalence pattern in a particular region, real epidemiological data from the north-eastern part of India was used, and the effect of seasonal variation in mosquito density was modelled based on local climactic data. The model developed based on general features of host-vector interactions, and modified simply incorporating local environmental factors with minimal changes, can successfully explain the disease transmission process in the region. This provides a general approach toward modelling malaria that can be adapted to control future outbreaks of malaria.

Effects of Solar UV Radiation and Climate Change on Biogeochemical Cycling: Interactions and Feedbacks

EPA Science Inventory

Solar UV radiation, climate and other drivers of global change are undergoing significant changes and models forecast that these changes will continue for the remainder of this century. Here we assess the effects of solar UV radiation on biogeochemical cycles and the interactions...

Generalized Structured Component Analysis with Latent Interactions

ERIC Educational Resources Information Center

Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan

2010-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…

Performance of the AMOEBA Water Model in the Vicinity of QM Solutes: A Diagnosis Using Energy Decomposition Analysis.

PubMed

Mao, Yuezhi; Shao, Yihan; Dziedzic, Jacek; Skylaris, Chris-Kriton; Head-Gordon, Teresa; Head-Gordon, Martin

2017-05-09

The importance of incorporating solvent polarization effects into the modeling of solvation processes has been well-recognized, and therefore a new generation of hybrid quantum mechanics/molecular mechanics (QM/MM) approaches that accounts for this effect is desirable. We present a fully self-consistent, mutually polarizable QM/MM scheme using the AMOEBA force field, in which the total energy of the system is variationally minimized with respect to both the QM electronic density and the MM induced dipoles. This QM/AMOEBA model is implemented through the Q-Chem/LibEFP code interface and then applied to the evaluation of solute-solvent interaction energies for various systems ranging from the water dimer to neutral and ionic solutes (NH 3 , NH 4 + , CN - ) surrounded by increasing numbers of water molecules (up to 100). In order to analyze the resulting interaction energies, we also utilize an energy decomposition analysis (EDA) scheme which identifies contributions from permanent electrostatics, polarization, and van der Waals (vdW) interaction for the interaction between the QM solute and the solvent molecules described by AMOEBA. This facilitates a component-wise comparison against full QM calculations where the corresponding energy components are obtained via a modified version of the absolutely localized molecular orbitals (ALMO)-EDA. The results show that the present QM/AMOEBA model can yield reasonable solute-solvent interaction energies for neutral and cationic species, while further scrutiny reveals that this accuracy highly relies on the delicate balance between insufficiently favorable permanent electrostatics and softened vdW interaction. For anionic solutes where the charge penetration effect becomes more pronounced, the QM/MM interface turns out to be unbalanced. These results are consistent with and further elucidate our findings in a previous study using a slightly different QM/AMOEBA model ( Dziedzic et al. J. Chem. Phys. 2016 , 145 , 124106 ). The implications of these results for further refinement of this model are also discussed.

Early prediction of student goals and affect in narrative-centered learning environments

NASA Astrophysics Data System (ADS)

Lee, Sunyoung

Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students' interactions in narrative-centered learning environments. Experimental results suggest that induced models can make accurate early predictions of student goals and affect states, and they are sufficiently efficient to meet the real-time performance requirements of interactive learning environments.

Interactions and Toxicity of Cu-Zn mixtures to Hordeum vulgare in Different Soils Can Be Rationalized with Bioavailability-Based Prediction Models.

PubMed

Qiu, Hao; Versieren, Liske; Rangel, Georgina Guzman; Smolders, Erik

2016-01-19

Soil contamination with copper (Cu) is often associated with zinc (Zn), and the biological response to such mixed contamination is complex. Here, we investigated Cu and Zn mixture toxicity to Hordeum vulgare in three different soils, the premise being that the observed interactions are mainly due to effects on bioavailability. The toxic effect of Cu and Zn mixtures on seedling root elongation was more than additive (i.e., synergism) in soils with high and medium cation-exchange capacity (CEC) but less than additive (antagonism) in a low-CEC soil. This was found when we expressed the dose as the conventional total soil concentration. In contrast, antagonism was found in all soils when we expressed the dose as free-ion activities in soil solution, indicating that there is metal-ion competition for binding to the plant roots. Neither a concentration addition nor an independent action model explained mixture effects, irrespective of the dose expressions. In contrast, a multimetal BLM model and a WHAM-Ftox model successfully explained the mixture effects across all soils and showed that bioavailability factors mainly explain the interactions in soils. The WHAM-Ftox model is a promising tool for the risk assessment of mixed-metal contamination in soils.

Interactivity and Trust as Antecedents of E-Training Use Intention in Nigeria: A Structural Equation Modelling Approach.

PubMed

Alkali, A U; Abu Mansor, Nur Naha

2017-07-18

The last few decades saw an intense development in information technology (IT) and it has affected the ways organisations achieve their goals. Training, in every organisation is an ongoing process that aims to update employees' knowledge and skills towards goals attainment. Through adequate deployment of IT, organisations can effectively meet their training needs. However, for successful IT integration in training, the employees who will use the system should be positively disposed towards it. This study predicts employees' intention to use the e-training system by extending the technology acceptance model (TAM) using interactivity and trust. Two hundred and fourteen employees participated in the study and structural equation modelling was used in the analysis. The findings of the structural equation modelling reveal that interactivity, trust, perceived usefulness and perceived ease of use have direct and positive effects on employees' intention to use e-training. It was also shown that perceived ease of use had no effects on perceived usefulness, while trust has the strongest indirect effects on employees' intention. In addition, the results of Importance-Performance Map Analysis (IPMA), which compares the contributions of each construct to the importance and performance of the model, indicate that to predict intention to use e-training, priorities should be accorded to trust and perceived usefulness.

Quantitative prediction of repaglinide-rifampicin complex drug interactions using dynamic and static mechanistic models: delineating differential CYP3A4 induction and OATP1B1 inhibition potential of rifampicin.

PubMed

Varma, Manthena V S; Lin, Jian; Bi, Yi-An; Rotter, Charles J; Fahmi, Odette A; Lam, Justine L; El-Kattan, Ayman F; Goosen, Theunis C; Lai, Yurong

2013-05-01

Repaglinide is mainly metabolized by cytochrome P450 enzymes CYP2C8 and CYP3A4, and it is also a substrate to a hepatic uptake transporter, organic anion transporting polypeptide (OATP)1B1. The purpose of this study is to predict the dosing time-dependent pharmacokinetic interactions of repaglinide with rifampicin, using mechanistic models. In vitro hepatic transport of repaglinide, characterized using sandwich-cultured human hepatocytes, and intrinsic metabolic parameters were used to build a dynamic whole-body physiologically-based pharmacokinetic (PBPK) model. The PBPK model adequately described repaglinide plasma concentration-time profiles and successfully predicted area under the plasma concentration-time curve ratios of repaglinide (within ± 25% error), dosed (staggered 0-24 hours) after rifampicin treatment when primarily considering induction of CYP3A4 and reversible inhibition of OATP1B1 by rifampicin. Further, a static mechanistic "extended net-effect" model incorporating transport and metabolic disposition parameters of repaglinide and interaction potency of rifampicin was devised. Predictions based on the static model are similar to those observed in the clinic (average error ∼19%) and to those based on the PBPK model. Both the models suggested that the combined effect of increased gut extraction and decreased hepatic uptake caused minimal repaglinide systemic exposure change when repaglinide is dosed simultaneously or 1 hour after the rifampicin dose. On the other hand, isolated induction effect as a result of temporal separation of the two drugs translated to an approximate 5-fold reduction in repaglinide systemic exposure. In conclusion, both dynamic and static mechanistic models are instrumental in delineating the quantitative contribution of transport and metabolism in the dosing time-dependent repaglinide-rifampicin interactions.

The Effect of Doctor-Consumer Interaction on Social Media on Consumers’ Health Behaviors: Cross-Sectional Study

PubMed Central

Wu, Tailai; Deng, Zhaohua; Gaskin, Darrell J; Zhang, Donglan; Wang, Ruoxi

2018-01-01

Background Both doctors and consumers have engaged in using social media for health purposes. Social media has changed traditional one-to-one communication between doctors and patients to many-to-many communication between doctors and consumers. However, little is known about the effect of doctor-consumer interaction on consumers’ health behaviors. Objective The aim of this study was to investigate how doctor-consumer interaction in social media affects consumers’ health behaviors. Methods On the basis of professional-client interaction theory and social cognitive theory, we propose that doctor-consumer interaction can be divided into instrumental interaction and affective interaction. These two types of interactions influence consumers’ health behaviors through declarative knowledge (DK), self-efficacy (SE), and outcome expectancy (OE). To validate our proposed research model, we employed the survey method and developed corresponding measurement instruments for constructs in our research model. A total of 352 valid answers were collected, and partial least square was performed to analyze the data. Results Instrumental doctor-consumer interaction was found to influence consumers’ DK (t294=5.763, P<.001), SE (t294=4.891, P<.001), and OE (t294=7.554, P<.001) significantly, whereas affective doctor-consumer interaction also impacted consumers’ DK (t294=4.025, P<.001), SE (t294=4.775, P<.001), and OE (t294=4.855, P<.001). Meanwhile, consumers’ DK (t294=3.838, P<.001), SE (t294=3.824, P<.001), and OE (t294=2.985, P<.01) all significantly affected consumers’ health behaviors. Our mediation analysis showed that consumers’ DK, SE, and OE partially mediated the effect of instrumental interaction on health behaviors, whereas the three mediators fully mediated the effect of affective interaction on health behaviors. Conclusions Compared with many intentional intervention programs, doctor-consumer interaction can be treated as a natural cost-effective intervention to promote consumers’ health behaviors. Meanwhile, both instrumental and affective interaction should be highlighted for the best interaction results. DK, SE, and OE are working mechanisms of doctor-consumer interaction. PMID:29490892

Celecoxib interferes to a limited extent with aspirin‐mediated inhibition of platelets aggregation

PubMed Central

Ruzov, Mark; Rimon, Gilad; Pikovsky, Oleg

2015-01-01

Aims The aim of the study was to analyze the interaction between celecoxib and low dose aspirin for COX‐1 binding and its consequences on the aspirin‐mediated antiplatelet effects. Methods We investigated ex vivo the interaction between celecoxib and aspirin for COX‐1 binding and measured the resulting antiplatelet effects. We applied mechanism‐based pharmacokinetic−pharmacodynamic (PKPD) modelling to analyze these data and to predict in vivo platelet aggregation for different doses and administration schedules of aspirin and celecoxib. Results The predictions of the PK‐PD model were consistent with results from previous studies that investigated interaction between aspirin and celecoxib. The modelling results indicate that celecoxib can attenuate to a limited extent the in vivo antiplatelet effects of low dose aspirin. The extent of this interaction can be substantial (up to 15% increase in platelet aggregation by 200 mg day−1 celecoxib when combined with low dose aspirin) during the first days of aspirin administration in patients who are already treated with celecoxib, and it cannot be prevented by separate administration of the interacting drugs. Conclusions At the recommended therapeutic doses, celecoxib can attenuate to a limited extent the in vivo antiplatelet effects of low dose aspirin. Patients receiving a combination of low dose aspirin and the recommended doses of celecoxib were not identified to have increased risk of cardiovascular and cerebrovascular events due to competition between these drugs for COX‐1 binding. Interaction between low dose aspirin and other COX‐2 inhibitors and its clinical consequences requires further investigation. PMID:26456703

Interactive Modelling of Salinity Intrusion in the Rhine-Meuse Delta

NASA Astrophysics Data System (ADS)

Baart, F.; Kranenburg, W.; Luijendijk, A.

2015-12-01

In many delta's of the world salinity intrusion imposes limits to fresh water availability. With increasing population and industry, the need for fresh water increases. But also salinity intrusion is expected to increase due to changes in river discharge, sea level and storm characteristics. In the Rhine-Meuse delta salt intrusion is impacted by human activities as well, like deepening of waterways and opening of delta-branches closed earlier. All these developments call for increasing the understanding of the system, but also for means for policy makers, coastal planners and engineers to assess effects of changes and to explore and design measures. In our presentation we present the developments in interactive modelling of salinity intrusion in the Rhine-Meuse delta. In traditional process-based numerical modelling, impacts are investigated by researchers and engineers by following the steps of pre-defining scenario's, running the model and post-processing the results. Interactive modelling lets users adjust simulations while running. Users can for instance change river discharges or bed levels, and can add measures like changes to geometry. The model will take the adjustments into account immediately, and will directly compute the effect. In this way, a tool becomes available with which coastal planners, policy makers and engineers together can develop and evaluate ideas and designs by interacting with the numerical model. When developing interactive numerical engines, one of the challenges is to optimize the exchange of variables as e.g. salt concentration. In our case we exchange variables on a 3D grid every time step. For this, the numerical model adheres to the Basic Model Interface (http://csdms.colorado.edu/wiki), which allows external control and the exchange of variables through pointers while the model is running. In our presentation we further explain our method and show examples of interactive design of salinity intrusion measures in the Rhine-Meuse delta.

Versatility of Cooperative Transcriptional Activation: A Thermodynamical Modeling Analysis for Greater-Than-Additive and Less-Than-Additive Effects

PubMed Central

Frank, Till D.; Carmody, Aimée M.; Kholodenko, Boris N.

2012-01-01

We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when transcription factors and RNA polymerase interact by means of three-body interactions. Overall, we show that versatility of transcriptional activation is brought about by nonlinearities of transcriptional response functions and interactions between transcription factors, RNA polymerase and DNA. PMID:22506020

Synergistic effect of interaction between perceived health and social activity on depressive symptoms in the middle-aged and elderly: a population-based longitudinal study.

PubMed

Chun, Sung-Youn; Han, Kyu-Tae; Lee, Seo Yoon; Kim, Chan Ok; Park, Eun-Cheol

2015-03-13

To examine the synergistic effect of interaction between perceived health and social activity on depressive symptoms. We investigated whether the interaction between perceived health and social activity has a synergistic effect on depressive symptoms in the middle-aged and elderly using data from 6590 respondents aged 45 and older in the Korean Longitudinal Study on Aging (KLoSA), 2006-2012. A generalised linear mixed-effects model was used to investigate the association in a longitudinal data form. Depressive symptoms were measured using the Center for Epidemiological Studies Depression 10 Scale (CES-D10). Perceived health and level of social activity were categorical variables with three values. Participation in six social activities was assessed. Interactions between perceived health status and social activity were statistically significant for almost all social activity/perceived health combinations. Addition of the interaction term significantly decreased CES-D10 scores, confirming the synergistic effect of the interaction between perceived health status and social activity ('normal×moderate', β=-0.1826; 'poor×moderate', β=-0.5739; 'poor×active', β=-0.8935). In addition, we performed stratified analyses by region: urban or rural. In urban respondents, the additional effect of the interaction term decreased CES-D10 scores and all social activity/perceived health combinations were statistically significant ('normal×moderate', β=-0.2578; 'normal×active', β=-0.3945; 'poor×moderate', β=-0.5739; 'poor×active', β=-0.8935). In rural respondents, only one social activity/perceived health combination was statistically significant, and the additional effect of the interaction term showed no consistent trend on CES-D10 scores. The interaction between perceived health and social activity has a synergistic effect on depressive symptoms; the additional effect of the interaction term significantly decreased CES-D10 scores in our models. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Effective Dynamics of Microorganisms That Interact with Their Own Trail

NASA Astrophysics Data System (ADS)

Kranz, W. Till; Gelimson, Anatolij; Zhao, Kun; Wong, Gerard C. L.; Golestanian, Ramin

2016-07-01

Like ants, some microorganisms are known to leave trails on surfaces to communicate. We explore how trail-mediated self-interaction could affect the behavior of individual microorganisms when diffusive spreading of the trail is negligible on the time scale of the microorganism using a simple phenomenological model for an actively moving particle and a finite-width trail. The effective dynamics of each microorganism takes on the form of a stochastic integral equation with the trail interaction appearing in the form of short-term memory. For a moderate coupling strength below an emergent critical value, the dynamics exhibits effective diffusion in both orientation and position after a phase of superdiffusive reorientation. We report experimental verification of a seemingly counterintuitive perpendicular alignment mechanism that emerges from the model.

The Effects of Interactive and Passive Distraction on Cold Pressor Pain in Preschool-aged Children

PubMed Central

Dahlquist, Lynnda M.; Wohlheiter, Karen

2011-01-01

Objective Using a mixed model design, this study examined the effects of interactive versus passive distraction on healthy preschool-aged children’s cold pressor pain tolerance. Methods Sixty-one children aged 3–5 years were randomly assigned to one of the following: interactive distraction, passive distraction, or no distraction control. Participants underwent a baseline cold pressor trial followed by interactive distraction trial, passive distraction trial, or second baseline trial. One or two additional trials followed. Children originally assigned to distraction received the alternate distraction intervention. Controls participated in both interactive and passive distraction trials in counterbalanced order. Results Participants showed significantly higher pain tolerance during both interactive and passive distraction relative to baseline. The two distraction conditions did not differ. Conclusions Interactive and passive video game distraction appear to be effective for preschool-aged children during laboratory pain exposure. Future studies should examine whether more extensive training would enhance effects of interactive video game distraction. PMID:21278378

Local interactions lead to pathogen-driven change to host population dynamics.

PubMed

Boots, Michael; Childs, Dylan; Reuman, Daniel C; Mealor, Michael

2009-10-13

Individuals tend to interact more strongly with nearby individuals or within particular social groups. Recent theoretical advances have demonstrated that these within-population relationships can have fundamental implications for ecological and evolutionary dynamics. In particular, contact networks are crucial to the spread and evolution of disease. However, the theory remains largely untested experimentally. Here, we manipulate habitat viscosity and thereby the frequency of local interactions in an insect-pathogen model system in which the virus had previously been shown to have little effect on host population dynamics. At high viscosity, the pathogen caused the collapse of dominant and otherwise stable host generation cycles. Modeling shows that this collapse can be explained by an increase in the frequency of intracohort interactions relative to intercohort interactions, leading to more disease transmission. Our work emphasizes that spatial structure can subtly mediate intraspecific competition and the effects of natural enemies. A decrease in dispersal in a population may actually (sometimes rather counterintuitively) intensify the effects of parasites. Broadly, because anthropological and environmental change often cause changes in population mixing, our work highlights the potential for dramatic changes in the effects of parasites on host populations.

Effects of calcium carbonate, magnesium oxide and sodium citrate bicarbonate health supplements on the urinary risk factors for kidney stone formation.

PubMed

Allie, Shameez; Rodgers, Allen

2003-01-01

We describe a model to illustrate different chemical interactions that can occur in urine following ingestion of individual and combined health supplements. Two types of interactions are defined: synergism and addition. The model was applied to eight healthy males who participated in a study to investigate the chemical interactions between calcium carbonate, magnesium oxide and sodium citrate-bicarbonate health supplements on calcium oxalate urinary stone risk factors. Subjects ingested these components individually and in combination for 7 days. Twenty-four-hour urines were collected at baseline and during the final day of supplementation. These were analysed using standard laboratory techniques. Three different chemical interactions, all involving citrate, were identified: magnesium and citrate exerted a synergistic effect on lowering the relative superaturation (RS) of brushite; the same two components produced a synergistic effect on raising pH; finally, calcium and citrate exerted an additive effect on lowering the RS of uric acid. We propose that the novel approach described in this paper allows for the evaluation of individual, additive and synergistic interactions in the assessment of the efficacy of stone-risk reducing preparations.

Religious Engagement in a Risky Family Model Predicting Health in Older Black and White Seventh-day Adventists.

PubMed

Morton, Kelly R; Lee, Jerry W; Haviland, Mark G; Fraser, Gary E

2012-11-01

In a structural equation model, associations among latent variables - Child Poverty, Risky Family exposure, Religious Engagement, Negative Social Interactions, Negative Emotionality, and Perceived Physical Health - were evaluated in 6,753 Black and White adults aged 35-106 years (M = 60.5, SD = 13.0). All participants were members of the Seventh-day Adventist church surveyed in the Biopsychosocial Religion and Health Study (BRHS). Child Poverty was positively associated with both Risky Family exposure (conflict, neglect, abuse) and Religious Engagement (intrinsic religiosity, religious coping, religiousness). Risky Family was negatively associated with Religious Engagement and positively associated with both Negative Social Interactions (intrusive, failed to help, insensitive, rejecting) and Negative Emotionality (depression, negative affect, neuroticism). Religious Engagement was negatively associated with Negative Emotionality and Negative Social Interactions at a given level of risky family. Negative Social Interactions was positively associated with Negative Emotionality, which had a direct, negative effect on Perceived Physical Health. All constructs had indirect effects on Perceived Physical Health through Negative Emotionality. The effects of a risky family environment appear to be enduring, negatively affecting one's adult religious life, emotionality, social interactions, and perceived health. Religious engagement, however, may counteract the damaging effects of early life stress.

Modeling and tachometer feedback in the control of an experimental single link flexible structure

NASA Technical Reports Server (NTRS)

Garcia, Ephrahim; Inman, Daniel J.

1990-01-01

In this work a formulation for the modeling of a single link flexible structure will be introduced that includes the effects of dynamic interaction between the actuator and structure. These effects are the rotational modal participation factors for the structure's vibratory motion that occurs at the slewing axis. It will be shown, both theoretically and experimentally, that this dynamic interaction can be advantageous for vibration suppression of the flexible modes of the system during slewing positioning maneuvers.

The effect of front-to-rear propeller spacing on the interaction noise at cruise conditions of a model counterrotation propeller having a reduced diameter aft propeller

NASA Technical Reports Server (NTRS)

Dittmar, James H.; Gordon, Eliott B.; Jeracki, Robert J.

1988-01-01

The effect of forward-to-aft propeller spacing on the interaction noise of a counterrotation propeller with reduced aft diameter was measured at cruise conditions. In general, the tones at 100 percent speed decreased from close to nominal spacing as expected from a wake decay model. However, when the spacing was further increased to the far position, the noise did not decrease as expected and in some cases increased. The behavior at the far spacing was attributed to changing forward propeller performance, which produced larger wakes. The results of this experiment indicate that simple wake decay model is sufficient to describe the behavior of the interaction noise only if the aerodynamic coupling of the two propellers does not change with spacing. If significant coupling occurs such that the loading of the forward propeller is altered, the interaction noise does not necessarily decrease with larger forward-to-aft propeller spacing.

What experimental approaches (eg, in vivo, in vitro, tissue retrieval) are effective in investigating the biologic effects of particles?

PubMed Central

Bostrom, Mathias; O'Keefe, Regis

2009-01-01

Understanding the complex cellular and tissue mechanisms and interactions resulting in periprosthetic osteolysis requires a number of experimental approaches, each of which has its own set of advantages and limitations. In vitro models allow for the isolation of individual cell populations and have furthered our understanding of particle-cell interactions; however, they are limited because they do not mimic the complex tissue environment in which multiple cell interactions occur. In vivo animal models investigate the tissue interactions associated with periprosthetic osteolysis, but the choice of species and whether the implant system is subjected to mechanical load or to unloaded conditions are critical in assessing whether these models can be extrapolated to the clinical condition. Rigid analysis of retrieved tissue from clinical cases of osteolysis offers a different approach to studying the biologic process of osteolysis, but it is limited in that the tissue analyzed represents the end-stage of this process and, thus, may not reflect this process adequately. PMID:18612016

What experimental approaches (eg, in vivo, in vitro, tissue retrieval) are effective in investigating the biologic effects of particles?

PubMed

Bostrom, Mathias; O'Keefe, Regis

2008-01-01

Understanding the complex cellular and tissue mechanisms and interactions resulting in periprosthetic osteolysis requires a number of experimental approaches, each of which has its own set of advantages and limitations. In vitro models allow for the isolation of individual cell populations and have furthered our understanding of particle-cell interactions; however, they are limited because they do not mimic the complex tissue environment in which multiple cell interactions occur. In vivo animal models investigate the tissue interactions associated with periprosthetic osteolysis, but the choice of species and whether the implant system is subjected to mechanical load or to unloaded conditions are critical in assessing whether these models can be extrapolated to the clinical condition. Rigid analysis of retrieved tissue from clinical cases of osteolysis offers a different approach to studying the biologic process of osteolysis, but it is limited in that the tissue analyzed represents the end-stage of this process and, thus, may not reflect this process adequately.

Make dark matter charged again

NASA Astrophysics Data System (ADS)

Agrawal, Prateek; Cyr-Racine, Francis-Yan; Randall, Lisa; Scholtz, Jakub

2017-05-01

We revisit constraints on dark matter that is charged under a U(1) gauge group in the dark sector, decoupled from Standard Model forces. We find that the strongest constraints in the literature are subject to a number of mitigating factors. For instance, the naive dark matter thermalization timescale in halos is corrected by saturation effects that slow down isotropization for modest ellipticities. The weakened bounds uncover interesting parameter space, making models with weak-scale charged dark matter viable, even with electromagnetic strength interaction. This also leads to the intriguing possibility that dark matter self-interactions within small dwarf galaxies are extremely large, a relatively unexplored regime in current simulations. Such strong interactions suppress heat transfer over scales larger than the dark matter mean free path, inducing a dynamical cutoff length scale above which the system appears to have only feeble interactions. These effects must be taken into account to assess the viability of darkly-charged dark matter. Future analyses and measurements should probe a promising region of parameter space for this model.

Modeling the interaction between the intra-aortic balloon pump and the cardiovascular system: the effect of timing.

PubMed

Schampaert, Stéphanie; Rutten, Marcel C M; van T Veer, Marcel; van Nunen, Lokien X; Tonino, Pim A L; Pijls, Nico H J; van de Vosse, Frans N

2013-01-01

Because of the large number of interaction factors involved, the effects of the intra-aortic balloon pump (IABP) have not been investigated deeply. To enhance its clinical efficiency and to better define indications for use, advanced models are required to test the interaction between the IABP and the cardiovascular system. A patient with mild blood pressure depression and a lowered cardiac output is modeled in a lumped parameter computational model, developed with physiologically representative elements for relevant components of circulation and device. IABP support is applied, and the moments of balloon inflation and deflation are varied around their conventional timing modes. For validation purposes, timing is adapted within acceptable ranges in ten patients undergoing IABP therapy for typical clinical indications. In both model and patients, the IABP induces a diastolic blood pressure augmentation as well as a systolic reduction in afterload. The support capabilities of the IABP benefit the most when the balloon is deflated simultaneously with ventricular contraction, whereas inflation before onset of diastole unconditionally interferes with ejection. The physiologic response makes the model an excellent tool for testing the interaction between the IABP and the cardiovascular system, and how alterations of specific IABP parameters (i.e., timing) affect this coupling.

The Moderating Effect of Interaction Avoidance Between Abusive Supervision and Subordinates' Job Promotions.

PubMed

Peltokorpi, Vesa

2017-10-03

While abusive supervision is shown to have negative stress-related effects on targets, less is known about the factors capable of mitigating these negative effects and their career-related outcomes. In this paper, we drew on the transactional model of stress and coping (Lazarus & Folkman, 1986) and the upward mobility theory (Turner, 1960) to explore the moderating effect of subordinates' interaction avoidance between abusive supervision and job promotions. To test this moderating effect, we collected data from 604 full-time employees at three points in time over a 12-month time period in Japan. The findings suggest that interaction avoidance moderates the relationship between abusive supervision and promotions, such that this relationship will be less negative as interaction avoidance increases.

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.

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.

On effective holographic Mott insulators

NASA Astrophysics Data System (ADS)

Baggioli, Matteo; Pujolàs, Oriol

2016-12-01

We present a class of holographic models that behave effectively as prototypes of Mott insulators — materials where electron-electron interactions dominate transport phenomena. The main ingredient in the gravity dual is that the gauge-field dynamics contains self-interactions by way of a particular type of non-linear electrodynamics. The electrical response in these models exhibits typical features of Mott-like states: i) the low-temperature DC conductivity is unboundedly low; ii) metal-insulator transitions appear by varying various parameters; iii) for large enough self-interaction strength, the conductivity can even decrease with increasing doping (density of carriers) — which appears as a sharp manifestation of `traffic-jam'-like behaviour; iv) the insulating state becomes very unstable towards superconductivity at large enough doping. We exhibit some of the properties of the resulting insulator-superconductor transition, which is sensitive to the momentum dissipation rate in a specific way. These models imply a clear and generic correlation between Mott behaviour and significant effects in the nonlinear electrical response. We compute the nonlinear current-voltage curve in our model and find that indeed at large voltage the conductivity is largely reduced.

A computer model of solar panel-plasma interactions

NASA Technical Reports Server (NTRS)

Cooke, D. L.; Freeman, J. W.

1980-01-01

High power solar arrays for satellite power systems are presently being planned with dimensions of kilometers, and with tens of kilovolts distributed over their surface. Such systems face many plasma interaction problems, such as power leakage to the plasma, particle focusing, and anomalous arcing. These effects cannot be adequately modeled without detailed knowledge of the plasma sheath structure and space charge effects. Laboratory studies of 1 by 10 meter solar array in a simulated low Earth orbit plasma are discussed. The plasma screening process is discussed, program theory is outlined, and a series of calibration models is presented. These models are designed to demonstrate that PANEL is capable of accurate self consistant space charge calculations. Such models include PANEL predictions for the Child-Langmuir diode problem.

A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data.

PubMed

He, Liang; Zhbannikov, Ilya; Arbeev, Konstantin G; Yashin, Anatoliy I; Kulminski, Alexander M

2017-11-01

Unraveling the underlying biological mechanisms or pathways behind the effects of genetic variations on complex diseases remains one of the major challenges in the post-GWAS (where GWAS is genome-wide association study) era. To further explore the relationship between genetic variations, biomarkers, and diseases for elucidating underlying pathological mechanism, a huge effort has been placed on examining pleiotropic and gene-environmental interaction effects. We propose a novel genetic stochastic process model (GSPM) that can be applied to GWAS and jointly investigate the genetic effects on longitudinally measured biomarkers and risks of diseases. This model is characterized by more profound biological interpretation and takes into account the dynamics of biomarkers during follow-up when investigating the hazards of a disease. We illustrate the rationale and evaluate the performance of the proposed model through two GWAS. One is to detect single nucleotide polymorphisms (SNPs) having interaction effects on type 2 diabetes (T2D) with body mass index (BMI) and the other is to detect SNPs affecting the optimal BMI level for protecting from T2D. We identified multiple SNPs that showed interaction effects with BMI on T2D, including a novel SNP rs11757677 in the CDKAL1 gene (P = 5.77 × 10 -7 ). We also found a SNP rs1551133 located on 2q14.2 that reversed the effect of BMI on T2D (P = 6.70 × 10 -7 ). In conclusion, the proposed GSPM provides a promising and useful tool in GWAS of longitudinal data for interrogating pleiotropic and interaction effects to gain more insights into the relationship between genes, quantitative biomarkers, and risks of complex diseases. © 2017 WILEY PERIODICALS, INC.

Hierarchical Interactions Model for Predicting Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) Conversion

PubMed Central

Li, Han; Liu, Yashu; Gong, Pinghua; Zhang, Changshui; Ye, Jieping

2014-01-01

Identifying patients with Mild Cognitive Impairment (MCI) who are likely to convert to dementia has recently attracted increasing attention in Alzheimer's disease (AD) research. An accurate prediction of conversion from MCI to AD can aid clinicians to initiate treatments at early stage and monitor their effectiveness. However, existing prediction systems based on the original biosignatures are not satisfactory. In this paper, we propose to fit the prediction models using pairwise biosignature interactions, thus capturing higher-order relationship among biosignatures. Specifically, we employ hierarchical constraints and sparsity regularization to prune the high-dimensional input features. Based on the significant biosignatures and underlying interactions identified, we build classifiers to predict the conversion probability based on the selected features. We further analyze the underlying interaction effects of different biosignatures based on the so-called stable expectation scores. We have used 293 MCI subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) database that have MRI measurements at the baseline to evaluate the effectiveness of the proposed method. Our proposed method achieves better classification performance than state-of-the-art methods. Moreover, we discover several significant interactions predictive of MCI-to-AD conversion. These results shed light on improving the prediction performance using interaction features. PMID:24416143

Metacontrast masking and attention do not interact.

PubMed

Agaoglu, Sevda; Breitmeyer, Bruno; Ogmen, Haluk

2016-07-01

Visual masking and attention have been known to control the transfer of information from sensory memory to visual short-term memory. A natural question is whether these processes operate independently or interact. Recent evidence suggests that studies that reported interactions between masking and attention suffered from ceiling and/or floor effects. The objective of the present study was to investigate whether metacontrast masking and attention interact by using an experimental design in which saturation effects are avoided. We asked observers to report the orientation of a target bar randomly selected from a display containing either two or six bars. The mask was a ring that surrounded the target bar. Attentional load was controlled by set-size and masking strength by the stimulus onset asynchrony between the target bar and the mask ring. We investigated interactions between masking and attention by analyzing two different aspects of performance: (i) the mean absolute response errors and (ii) the distribution of signed response errors. Our results show that attention affects observers' performance without interacting with masking. Statistical modeling of response errors suggests that attention and metacontrast masking exert their effects by independently modulating the probability of "guessing" behavior. Implications of our findings for models of attention are discussed.

Finite element modeling of trolling-mode AFM.

PubMed

Sajjadi, Mohammadreza; Pishkenari, Hossein Nejat; Vossoughi, Gholamreza

2018-06-01

Trolling mode atomic force microscopy (TR-AFM) has overcome many imaging problems in liquid environments by considerably reducing the liquid-resonator interaction forces. The finite element model of the TR-AFM resonator considering the effects of fluid and nanoneedle flexibility is presented in this research, for the first time. The model is verified by ABAQUS software. The effect of installation angle of the microbeam relative to the horizon and the effect of fluid on the system behavior are investigated. Using the finite element model, frequency response curve of the system is obtained and validated around the frequency of the operating mode by the available experimental results, in air and liquid. The changes in the natural frequencies in the presence of liquid are studied. The effects of tip-sample interaction on the excitation of higher order modes of the system are also investigated in air and liquid environments. Copyright © 2018 Elsevier B.V. All rights reserved.

A model for the salt effect on adsorption equilibrium of basic protein to dye-ligand affinity adsorbent.

PubMed

Zhang, Songping; Sun, Yan

2004-01-01

A model describing the salt effect on adsorption equilibrium of a basic protein, lysozyme, to Cibacron Blue 3GA-modified Sepharose CL-6B (CB-Sepharose) has been developed. In this model, it is assumed that the presence of salt causes a fraction of dye-ligand molecules to lodge to the surface of the agarose gel, resulting from the induced strong hydrophobic interaction between dye ligand and agarose matrix. The salt effect on the lodging of dye-ligand is expressed by the equilibrium between salt and dye-ligand. For the interactions between protein and vacant binding sites, stoichiometric equations based either on cation exchanges or on hydrophobic interactions are proposed since the CB dye can be regarded as a cation exchanger contributed by the sulfonate groups on it. Combining with the basic concept of steric mass-action theory for ion exchange, which considers both the multipoint nature and the macromolecular steric shielding of protein adsorption, an explicit isotherm for protein adsorption equilibrium on the dye-ligand adsorbent is formulated, involving salt concentration as a variable. Analysis of the model parameters has yielded better understanding of the mechanism of salt effects on adsorption of the basic protein. Moreover, the model predictions are in good agreement with the experimental data over a wide range of salt and ligand concentrations, indicating the predictive nature of the model.

Interactive coupling of regional climate and sulfate aerosol models over eastern Asia

NASA Astrophysics Data System (ADS)

Qian, Yun; Giorgi, Filippo

1999-03-01

The NCAR regional climate model (RegCM) is interactively coupled to a simple radiatively active sulfate aerosol model over eastern Asia. Both direct and indirect aerosol effects are represented. The coupled model system is tested for two simulation periods, November 1994 and July 1995, with aerosol sources representative of present-day anthropogenic sulfur emissions. The model sensitivity to the intensity of the aerosol source is also studied. The main conclusions from our work are as follows: (1) The aerosol distribution and cycling processes show substantial regional spatial variability, and temporal variability varying on a range of scales, from the diurnal scale of boundary layer and cumulus cloud evolution to the 3-10 day scale of synoptic scale events and the interseasonal scale of general circulation features; (2) both direct and indirect aerosol forcings have regional effects on surface climate; (3) the regional climate response to the aerosol forcing is highly nonlinear, especially during the summer, due to the interactions with cloud and precipitation processes; (4) in our simulations the role of the aerosol indirect effects is dominant over that of direct effects; (5) aerosol-induced feedback processes can affect the aerosol burdens at the subregional scale. This work constitutes the first step in a long term research project aimed at coupling a hierarchy of chemistry/aerosol models to the RegCM over the eastern Asia region.

ROTAS: a rotamer-dependent, atomic statistical potential for assessment and prediction of protein structures.

PubMed

Park, Jungkap; Saitou, Kazuhiro

2014-09-18

Multibody potentials accounting for cooperative effects of molecular interactions have shown better accuracy than typical pairwise potentials. The main challenge in the development of such potentials is to find relevant structural features that characterize the tightly folded proteins. Also, the side-chains of residues adopt several specific, staggered conformations, known as rotamers within protein structures. Different molecular conformations result in different dipole moments and induce charge reorientations. However, until now modeling of the rotameric state of residues had not been incorporated into the development of multibody potentials for modeling non-bonded interactions in protein structures. In this study, we develop a new multibody statistical potential which can account for the influence of rotameric states on the specificity of atomic interactions. In this potential, named "rotamer-dependent atomic statistical potential" (ROTAS), the interaction between two atoms is specified by not only the distance and relative orientation but also by two state parameters concerning the rotameric state of the residues to which the interacting atoms belong. It was clearly found that the rotameric state is correlated to the specificity of atomic interactions. Such rotamer-dependencies are not limited to specific type or certain range of interactions. The performance of ROTAS was tested using 13 sets of decoys and was compared to those of existing atomic-level statistical potentials which incorporate orientation-dependent energy terms. The results show that ROTAS performs better than other competing potentials not only in native structure recognition, but also in best model selection and correlation coefficients between energy and model quality. A new multibody statistical potential, ROTAS accounting for the influence of rotameric states on the specificity of atomic interactions was developed and tested on decoy sets. The results show that ROTAS has improved ability to recognize native structure from decoy models compared to other potentials. The effectiveness of ROTAS may provide insightful information for the development of many applications which require accurate side-chain modeling such as protein design, mutation analysis, and docking simulation.

A new approach to modeling aerosol effects on East Asian climate: Parametric uncertainties associated with emissions, cloud microphysics, and their interactions: AEROSOL EFFECTS ON EAST ASIAN CLIMATE

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

Yan, Huiping; Qian, Yun; Zhao, Chun

2015-09-09

In this study, we adopt a parametric sensitivity analysis framework that integrates the quasi-Monte Carlo parameter sampling approach and a surrogate model to examine aerosol effects on the East Asian Monsoon climate simulated in the Community Atmosphere Model (CAM5). A total number of 256 CAM5 simulations are conducted to quantify the model responses to the uncertain parameters associated with cloud microphysics parameterizations and aerosol (e.g., sulfate, black carbon (BC), and dust) emission factors and their interactions. Results show that the interaction terms among parameters are important for quantifying the sensitivity of fields of interest, especially precipitation, to the parameters. Themore » relative importance of cloud-microphysics parameters and emission factors (strength) depends on evaluation metrics or the model fields we focused on, and the presence of uncertainty in cloud microphysics imposes an additional challenge in quantifying the impact of aerosols on cloud and climate. Due to their different optical and microphysical properties and spatial distributions, sulfate, BC, and dust aerosols have very different impacts on East Asian Monsoon through aerosol-cloud-radiation interactions. The climatic effects of aerosol do not always have a monotonic response to the change of emission factors. The spatial patterns of both sign and magnitude of aerosol-induced changes in radiative fluxes, cloud, and precipitation could be different, depending on the aerosol types, when parameters are sampled in different ranges of values. We also identify the different cloud microphysical parameters that show the most significant impact on climatic effect induced by sulfate, BC and dust, respectively, in East Asia.« less

Effect of added mass on the interaction of bubbles in a low-Reynolds-number shear flow.

PubMed

Lavrenteva, Olga; Prakash, Jai; Nir, Avinoam

2016-02-01

Equal size air bubbles that are entrapped by a Taylor vortex of the secondary flow in a Couette device, thereby defying buoyancy, slowly form a stable ordered ring with equal separation distances between all neighbors. We present two models of the process dynamics based on force balance on a bubble in the presence of other bubbles positioned on the same streamline in a simple shear flow. The forces taken into account are the viscous resistance, the added mass force, and the inertia-induced repulsing force between two bubbles in a low-Reynolds-number shear flow obtained in Prakash et al. [J. Prakash et al., Phys. Rev. E 87, 043002 (2013)]. The first model of the process assumes that each bubble interacts solely with its nearest neighbors. The second model takes into account pairwise interactions among all the bubbles in the ring. The performed dynamic simulations were compared to the experimental results reported in Prakash et al. [J. Prakash et al., Phys. Rev. E 87, 043002 (2013)] and to the results of quasistationary models (ignoring the added mass effect) suggested in that paper. It is demonstrated that taking into account the effect of added mass, the models describe the major effect of the bubbles' ordering, provide good estimation of the relaxation time, and also predict nonmonotonic behavior of the separation distance between the bubbles, which exhibit over- and undershooting of equilibrium separations. The latter effects were observed in experiments, but are not predicted by the quasistationary models.

A model for family-based case-control studies of genetic imprinting and epistasis.

PubMed

Li, Xin; Sui, Yihan; Liu, Tian; Wang, Jianxin; Li, Yongci; Lin, Zhenwu; Hegarty, John; Koltun, Walter A; Wang, Zuoheng; Wu, Rongling

2014-11-01

Genetic imprinting, or called the parent-of-origin effect, has been recognized to play an important role in the formation and pathogenesis of human diseases. Although the epigenetic mechanisms that establish genetic imprinting have been a focus of many genetic studies, our knowledge about the number of imprinting genes and their chromosomal locations and interactions with other genes is still scarce, limiting precise inference of the genetic architecture of complex diseases. In this article, we present a statistical model for testing and estimating the effects of genetic imprinting on complex diseases using a commonly used case-control design with family structure. For each subject sampled from a case and control population, we not only genotype its own single nucleotide polymorphisms (SNPs) but also collect its parents' genotypes. By tracing the transmission pattern of SNP alleles from parental to offspring generation, the model allows the characterization of genetic imprinting effects based on Pearson tests of a 2 × 2 contingency table. The model is expanded to test the interactions between imprinting effects and additive, dominant and epistatic effects in a complex web of genetic interactions. Statistical properties of the model are investigated, and its practical usefulness is validated by a real data analysis. The model will provide a useful tool for genome-wide association studies aimed to elucidate the picture of genetic control over complex human diseases. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Investigating the Interaction Between Sleep Symptoms of Arousal and Acquired Capability in Predicting Suicidality.

PubMed

Hochard, Kevin D; Heym, Nadja; Townsend, Ellen

2017-06-01

Heightened arousal significantly interacts with acquired capability to predict suicidality. We explore this interaction with insomnia and nightmares independently of waking state arousal symptoms, and test predictions of the Interpersonal Theory of Suicide (IPTS) and Escape Theory in relation to these sleep arousal symptoms. Findings from our e-survey (n = 540) supported the IPTS over models of Suicide as Escape. Sleep-specific measurements of arousal (insomnia and nightmares) showed no main effect, yet interacted with acquired capability to predict increased suicidality. The explained variance in suicidality by the interaction (1%-2%) using sleep-specific measures was comparable to variance explained by interactions previously reported in the literature using measurements composed of a mix of waking and sleep state arousal symptoms. Similarly, when entrapment (inability to escape) was included in models, main effects of sleep symptoms arousal were not detected yet interacted with entrapment to predict suicidality. We discuss findings in relation to treatment options suggesting that sleep-specific interventions be considered for the long-term management of at-risk individuals. © 2016 The American Association of Suicidology.

Communication, Reasoning, and Planned Behaviors: Unveiling the Effect of Interactive Communication in an Anti-Smoking Social Media Campaign.

PubMed

Namkoong, Kang; Nah, Seungahn; Record, Rachael A; Van Stee, Stephanie K

2017-01-01

This study examines direct and indirect effects of interactive communication in an antismoking social media campaign. To that end, we pose a multitheoretical framework that integrates communication mediation models and the Theory of Planned Behavior. To test the theorized model, we conducted an experiment using a two-group pretest-posttest design. Participants (N = 201) were randomly assigned into two experimental conditions: "campaign message reception only" as a control group and "message reception and social interaction" as a treatment group, in which the participants contributed to the antismoking campaign by posting their own campaign ideas and information they found through mediated and interpersonal communication. The findings show that interactive communication catalyzes the participants' information searching behaviors through diverse communication channels. In turn, increased media use plays a crucial role in changing their attitudes and perceived social norms about smoking behaviors, and eventually reducing smoking intention. This study affirms that the theory of planned behavior is effective in predicting behavioral intention and demonstrates the usefulness of a multitheoretical approach in interactive campaign research on social media.

Strangeness S =-1 hyperon-nucleon interactions: Chiral effective field theory versus lattice QCD

NASA Astrophysics Data System (ADS)

Song, Jing; Li, Kai-Wen; Geng, Li-Sheng

2018-06-01

Hyperon-nucleon interactions serve as basic inputs to studies of hypernuclear physics and dense (neutron) stars. Unfortunately, a precise understanding of these important quantities has lagged far behind that of the nucleon-nucleon interaction due to lack of high-precision experimental data. Historically, hyperon-nucleon interactions are either formulated in quark models or meson exchange models. In recent years, lattice QCD simulations and chiral effective field theory approaches start to offer new insights from first principles. In the present work, we contrast the state-of-the-art lattice QCD simulations with the latest chiral hyperon-nucleon forces and show that the leading order relativistic chiral results can already describe the lattice QCD data reasonably well. Given the fact that the lattice QCD simulations are performed with pion masses ranging from the (almost) physical point to 700 MeV, such studies provide a useful check on both the chiral effective field theory approaches as well as lattice QCD simulations. Nevertheless more precise lattice QCD simulations are eagerly needed to refine our understanding of hyperon-nucleon interactions.

Free energy and phase transition of the matrix model on a plane wave

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

Hadizadeh, Shirin; Ramadanovic, Bojan; Semenoff, Gordon W.

2005-03-15

It has recently been observed that the weakly coupled plane-wave matrix model has a density of states which grows exponentially at high energy. This implies that the model has a phase transition. The transition appears to be of first order. However, its exact nature is sensitive to interactions. In this paper, we analyze the effect of interactions by computing the relevant parts of the effective potential for the Polyakov loop operator in the finite temperature plane-wave matrix model to three-loop order. We show that the phase transition is indeed of first order. We also compute the correction to the Hagedornmore » temperature to order two loops.« less

Research on key factors and their interaction effects of electromagnetic force of high-speed solenoid valve.

PubMed

Liu, Peng; Fan, Liyun; Hayat, Qaisar; Xu, De; Ma, Xiuzhen; Song, Enzhe

2014-01-01

Analysis consisting of numerical simulations along with lab experiments of interaction effects between key parameters on the electromagnetic force based on response surface methodology (RSM) has been also proposed to optimize the design of high-speed solenoid valve (HSV) and improve its performance. Numerical simulation model of HSV has been developed in Ansoft Maxwell environment and its accuracy has been validated through lab experiments. Effect of change of core structure, coil structure, armature structure, working air gap, and drive current on the electromagnetic force of HSV has been analyzed through simulation model and influence rules of various parameters on the electromagnetic force have been established. The response surface model of the electromagnetic force has been utilized to analyze the interaction effect between major parameters. It has been concluded that six interaction factors including working air gap with armature radius, drive current with armature thickness, coil turns with side pole radius, armature thickness with its radius, armature thickness with side pole radius, and armature radius with side pole radius have significant influence on the electromagnetic force. Optimal match values between coil turns and side pole radius; armature thickness and side pole radius; and armature radius and side pole radius have also been determined.

Research on Key Factors and Their Interaction Effects of Electromagnetic Force of High-Speed Solenoid Valve

PubMed Central

Fan, Liyun; Xu, De; Ma, Xiuzhen; Song, Enzhe

2014-01-01

Analysis consisting of numerical simulations along with lab experiments of interaction effects between key parameters on the electromagnetic force based on response surface methodology (RSM) has been also proposed to optimize the design of high-speed solenoid valve (HSV) and improve its performance. Numerical simulation model of HSV has been developed in Ansoft Maxwell environment and its accuracy has been validated through lab experiments. Effect of change of core structure, coil structure, armature structure, working air gap, and drive current on the electromagnetic force of HSV has been analyzed through simulation model and influence rules of various parameters on the electromagnetic force have been established. The response surface model of the electromagnetic force has been utilized to analyze the interaction effect between major parameters. It has been concluded that six interaction factors including working air gap with armature radius, drive current with armature thickness, coil turns with side pole radius, armature thickness with its radius, armature thickness with side pole radius, and armature radius with side pole radius have significant influence on the electromagnetic force. Optimal match values between coil turns and side pole radius; armature thickness and side pole radius; and armature radius and side pole radius have also been determined. PMID:25243217

[Effects of functional interactions between nonhomologous insulators Wari and Su(Hw)].

PubMed

Erokhin, M M; Georgiev, P G; Chetverina, D A

2010-01-01

Insulators are regulatory DNA elements restricting gene activation by enhancers. Interactions between insulators can lead to both insulation and activation of promoters by enhancers. In this work, we analyzed the effects of interaction of two Drosophila insulators, Wari and Su(Hw). The functional interaction between these insulators was found to enhance the activity of the Su(Hw) insulator only, but not of the Wari insulator. This suggests that the formation of a chromatin loop between interacting insulators is not a key factor for enhancement of insulation, which is in disagreement with the main idea of structural models. In addition, the effect of interaction between Wari and Su(Hw) depends on a distance between them and on the position in the system relative to other regulatory elements.

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.

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.

Cannabidiol exhibits anxiolytic but not antipsychotic property evaluated in the social interaction test.

PubMed

Almeida, Valéria; Levin, Raquel; Peres, Fernanda Fiel; Niigaki, Suzy T; Calzavara, Mariana B; Zuardi, Antônio W; Hallak, Jaime E; Crippa, José A; Abílio, Vanessa C

2013-03-05

Cannabidiol (CBD), a non-psychotomimetic compound of the Cannabis sativa, has been reported to have central therapeutic actions, such as antipsychotic and anxiolytic effects. We have recently reported that Spontaneously Hypertensive Rats (SHRs) present a deficit in social interaction that is ameliorated by atypical antipsychotics. In addition, SHRs present a hyperlocomotion that is reverted by typical and atypical antipsychotics, suggesting that this strain could be useful to study negative symptoms (modeled by a decrease in social interaction) and positive symptoms (modeled by hyperlocomotion) of schizophrenia as well as the effects of potential antipsychotics drugs. At the same time, an increase in social interaction in control animals similar to that induced by benzodiazepines is used to screen potential anxiolytic drugs. The aim of this study was to investigate the effects of CBD on social interaction presented by control animals (Wistar) and SHRs. The lowest dose of CBD (1mg/kg) increased passive and total social interaction of Wistar rats. However, the hyperlocomotion and the deficit in social interaction displayed by SHRs were not altered by any dose of CBD. Our results do not support an antipsychotic property of cannabidiol on symptoms-like behaviors in SHRs but reinforce the anxiolytic profile of this compound in control rats. Copyright © 2012 Elsevier Inc. All rights reserved.

Interaction of polar and nonpolar organic pollutants with soil organic matter: sorption experiments and molecular dynamics simulation.

PubMed

Ahmed, Ashour A; Thiele-Bruhn, Sören; Aziz, Saadullah G; Hilal, Rifaat H; Elroby, Shaaban A; Al-Youbi, Abdulrahman O; Leinweber, Peter; Kühn, Oliver

2015-03-01

The fate of organic pollutants in the environment is influenced by several factors including the type and strength of their interactions with soil components especially SOM. However, a molecular level answer to the question "How organic pollutants interact with SOM?" is still lacking. In order to explore mechanisms of this interaction, we have developed a new SOM model and carried out molecular dynamics (MD) simulations in parallel with sorption experiments. The new SOM model comprises free SOM functional groups (carboxylic acid and naphthalene) as well as SOM cavities (with two different sizes), simulating the soil voids, containing the same SOM functional groups. To examine the effect of the hydrophobicity on the interaction, the organic pollutants hexachlorobenzene (HCB, non-polar) and sulfanilamide (SAA, polar) were considered. The experimental and theoretical investigations explored four major points regarding sorption of SAA and HCB on soil, yielding the following results. 1--The interaction depends on the SOM chemical composition more than the SOM content. 2--The interaction causes a site-specific adsorption on the soil surfaces. 3--Sorption hysteresis occurs, which can be explained by inclusion of these pollutants inside soil voids. 4--The hydrophobic HCB is adsorbed on soil stronger than the hydrophilic SAA. Moreover, the theoretical results showed that HCB forms stable complexes with all SOM models in the aqueous solution, while most of SAA-SOM complexes are accompanied by dissociation into SAA and the free SOM models. The SOM-cavity modeling had a significant effect on binding of organic pollutants to SOM. Both HCB and SAA bind to the SOM models in the order of models with a small cavity>a large cavity>no cavity. Although HCB binds to all SOM models stronger than SAA, the latter is more affected by the presence of the cavity. Finally, HCB and SAA bind to the hydrophobic functional group (naphthalene) stronger than to the hydrophilic one (carboxylic acid) for all SOM models containing a cavity. For models without a cavity, SAA binds to carboxylic acid stronger than to naphthalene. Copyright © 2014 Elsevier B.V. All rights reserved.

A multiscale modeling study of particle size effects on the tissue penetration efficacy of drug-delivery nanoparticles.

PubMed

Islam, Mohammad Aminul; Barua, Sutapa; Barua, Dipak

2017-11-25

Particle size is a key parameter for drug-delivery nanoparticle design. It is believed that the size of a nanoparticle may have important effects on its ability to overcome the transport barriers in biological tissues. Nonetheless, such effects remain poorly understood. Using a multiscale model, this work investigates particle size effects on the tissue distribution and penetration efficacy of drug-delivery nanoparticles. We have developed a multiscale spatiotemporal model of nanoparticle transport in biological tissues. The model implements a time-adaptive Brownian Dynamics algorithm that links microscale particle-cell interactions and adhesion dynamics to tissue-scale particle dispersion and penetration. The model accounts for the advection, diffusion, and cellular uptakes of particles. Using the model, we have analyzed how particle size affects the intra-tissue dispersion and penetration of drug delivery nanoparticles. We focused on two published experimental works that investigated particle size effects in in vitro and in vivo tissue conditions. By analyzing experimental data reported in these two studies, we show that particle size effects may appear pronounced in an in vitro cell-free tissue system, such as collagen matrix. In an in vivo tissue system, the effects of particle size could be relatively modest. We provide a detailed analysis on how particle-cell interactions may determine distribution and penetration of nanoparticles in a biological tissue. Our work suggests that the size of a nanoparticle may play a less significant role in its ability to overcome the intra-tissue transport barriers. We show that experiments involving cell-free tissue systems may yield misleading observations of particle size effects due to the absence of advective transport and particle-cell interactions.

Bayesian spatiotemporal crash frequency models with mixture components for space-time interactions.

PubMed

Cheng, Wen; Gill, Gurdiljot Singh; Zhang, Yongping; Cao, Zhong

2018-03-01

The traffic safety research has developed spatiotemporal models to explore the variations in the spatial pattern of crash risk over time. Many studies observed notable benefits associated with the inclusion of spatial and temporal correlation and their interactions. However, the safety literature lacks sufficient research for the comparison of different temporal treatments and their interaction with spatial component. This study developed four spatiotemporal models with varying complexity due to the different temporal treatments such as (I) linear time trend; (II) quadratic time trend; (III) Autoregressive-1 (AR-1); and (IV) time adjacency. Moreover, the study introduced a flexible two-component mixture for the space-time interaction which allows greater flexibility compared to the traditional linear space-time interaction. The mixture component allows the accommodation of global space-time interaction as well as the departures from the overall spatial and temporal risk patterns. This study performed a comprehensive assessment of mixture models based on the diverse criteria pertaining to goodness-of-fit, cross-validation and evaluation based on in-sample data for predictive accuracy of crash estimates. The assessment of model performance in terms of goodness-of-fit clearly established the superiority of the time-adjacency specification which was evidently more complex due to the addition of information borrowed from neighboring years, but this addition of parameters allowed significant advantage at posterior deviance which subsequently benefited overall fit to crash data. The Base models were also developed to study the comparison between the proposed mixture and traditional space-time components for each temporal model. The mixture models consistently outperformed the corresponding Base models due to the advantages of much lower deviance. For cross-validation comparison of predictive accuracy, linear time trend model was adjudged the best as it recorded the highest value of log pseudo marginal likelihood (LPML). Four other evaluation criteria were considered for typical validation using the same data for model development. Under each criterion, observed crash counts were compared with three types of data containing Bayesian estimated, normal predicted, and model replicated ones. The linear model again performed the best in most scenarios except one case of using model replicated data and two cases involving prediction without including random effects. These phenomena indicated the mediocre performance of linear trend when random effects were excluded for evaluation. This might be due to the flexible mixture space-time interaction which can efficiently absorb the residual variability escaping from the predictable part of the model. The comparison of Base and mixture models in terms of prediction accuracy further bolstered the superiority of the mixture models as the mixture ones generated more precise estimated crash counts across all four models, suggesting that the advantages associated with mixture component at model fit were transferable to prediction accuracy. Finally, the residual analysis demonstrated the consistently superior performance of random effect models which validates the importance of incorporating the correlation structures to account for unobserved heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

A model to predict thermal conductivity of irradiated U-Mo dispersion fuel

NASA Astrophysics Data System (ADS)

Burkes, Douglas E.; Huber, Tanja K.; Casella, Andrew M.

2016-05-01

Numerous global programs are focused on the continued development of existing and new research and test reactor fuels to achieve maximum attainable uranium loadings to support the conversion of a number of the world's remaining high-enriched uranium fueled reactors to low-enriched uranium fuel. Some of these programs are focused on assisting with the development and qualification of a fuel design that consists of a uranium-molybdenum (U-Mo) alloy dispersed in an aluminum matrix as one option for reactor conversion. Thermal conductivity is an important consideration in determining the operational temperature of the fuel and can be influenced by interaction layer formation between the dispersed phase and matrix and upon the concentration of the dispersed phase within the matrix. This paper extends the use of a simple model developed previously to study the influence of interaction layer formation as well as the size and volume fraction of fuel particles dispersed in the matrix, Si additions to the matrix, and Mo concentration in the fuel particles on the effective thermal conductivity of the U-Mo/Al composite during irradiation. The model has been compared to experimental measurements recently conducted on U-Mo/Al dispersion fuels at two different fission densities with acceptable agreement. Observations of the modeled results indicate that formation of an interaction layer and subsequent consumption of the matrix reveals a rather significant effect on effective thermal conductivity. The modeled interaction layer formation and subsequent consumption of the high thermal conductivity matrix was sensitive to the average dispersed fuel particle size, suggesting this parameter as one of the most effective in minimizing thermal conductivity degradation of the composite, while the influence of Si additions to the matrix in the model was highly dependent upon irradiation conditions.

In-beam γ -ray spectroscopy of Mn 63

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

Baugher, T.; Gade, A.; Janssens, R. V. F.

2016-01-01

Background: Neutron-rich, even-mass chromium and iron isotopes approaching neutron number N = 40 have been important benchmarks in the development of shell-model effective interactions incorporating the effects of shell evolution in the exotic regime. Odd-mass manganese nuclei have received less attention, but provide important and complementary sensitivity to these interactions. Purpose: We report the observation of two new γ -ray transitions in 63 Mn , which establish the ( 9 / 2 - ) and ( 11 / 2 - ) levels on top of the previously known ( 7 / 2 - ) first-excited state. The lifetime for themore » ( 7 / 2 - ) and ( 9 / 2 - ) excited states were determined for the first time, while an upper limit could be established for the ( 11 / 2 - ) level. Method: Excited states in 63 Mn have been populated in inelastic scattering from a 9 Be target and in the fragmentation of 65 Fe . γ γ coincidence relationships were used to establish the decay level scheme. A Doppler line-shape analysis for the Doppler-broadened ( 7 / 2 - ) → 5 / 2 - , ( 9 / 2 - ) → ( 7 / 2 - ) , and ( 11 / 2 - ) → ( 9 / 2 - ) transitions was used to determine (limits for) the corresponding excited-state lifetimes. Results: The low-lying level scheme and the excited-state lifetimes were compared with large-scale shell-model calculations using different model spaces and effective interactions in order to isolate important aspects of shell evolution in this region of structural change. Conclusions: While the theoretical ( 7 / 2 - ) and ( 9 / 2 - ) excitation energies show little dependence on the model space, the calculated lifetime of the ( 7 / 2 - ) level and calculated energy of the ( 11 / 2 - ) level reveal the importance of including the neutron g 9 / 2 and d 5 / 2 orbitals in the model space. The LNPS effective shell-model interaction provides the best overall agreement with the new data.« less

A model to predict thermal conductivity of irradiated U–Mo dispersion fuel

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

Burkes, Douglas E.; Huber, Tanja K.; Casella, Andrew M.

The Office of Materials Management and Minimization Reactor Conversion Program continues to develop existing and new research and test reactor fuels to achieve maximum attainable uranium loadings to support the conversion of a number of the world’s remaining high-enriched uranium fueled reactors to low-enriched uranium fuel. The program is focused on assisting with the development and qualification of a fuel design that consists of a uranium-molybdenum (U-Mo) alloy dispersed in an aluminum matrix as one option for reactor conversion. Thermal conductivity is an important consideration in determining the operational temperature of the fuel and can be influenced by interaction layermore » formation between the dispersed phase and matrix and upon the concentration of the dispersed phase within the matrix. This paper extends the use of a simple model developed previously to study the influence of interaction layer formation as well as the size and volume fraction of fuel particles dispersed in the matrix, Si additions to the matrix, and Mo concentration in the fuel particles on the effective thermal conductivity of the U-Mo/Al composite during irradiation. The model has been compared to experimental measurements recently conducted on U-Mo/Al dispersion fuels at two different fission densities with acceptable agreement. Observations of the modeled results indicate that formation of an interaction layer and subsequent consumption of the matrix reveals a rather significant effect on effective thermal conductivity. The modeled interaction layer formation and subsequent consumption of the high thermal conductivity matrix was sensitive to the average dispersed fuel particle size, suggesting this parameter as one of the most effective in minimizing thermal conductivity degradation of the composite, while the influence of Si additions to the matrix in the model was highly dependent upon irradiation conditions.« less

Gene-environment studies: any advantage over environmental studies?

PubMed

Bermejo, Justo Lorenzo; Hemminki, Kari

2007-07-01

Gene-environment studies have been motivated by the likely existence of prevalent low-risk genes that interact with common environmental exposures. The present study assessed the statistical advantage of the simultaneous consideration of genes and environment to investigate the effect of environmental risk factors on disease. In particular, we contemplated the possibility that several genes modulate the environmental effect. Environmental exposures, genotypes and phenotypes were simulated according to a wide range of parameter settings. Different models of gene-gene-environment interaction were considered. For each parameter combination, we estimated the probability of detecting the main environmental effect, the power to identify the gene-environment interaction and the frequency of environmentally affected individuals at which environmental and gene-environment studies show the same statistical power. The proportion of cases in the population attributable to the modeled risk factors was also calculated. Our data indicate that environmental exposures with weak effects may account for a significant proportion of the population prevalence of the disease. A general result was that, if the environmental effect was restricted to rare genotypes, the power to detect the gene-environment interaction was higher than the power to identify the main environmental effect. In other words, when few individuals contribute to the overall environmental effect, individual contributions are large and result in easily identifiable gene-environment interactions. Moreover, when multiple genes interacted with the environment, the statistical benefit of gene-environment studies was limited to those studies that included major contributors to the gene-environment interaction. The advantage of gene-environment over plain environmental studies also depends on the inheritance mode of the involved genes, on the study design and, to some extend, on the disease prevalence.

Short-term effects of meteorological factors on hand, foot and mouth disease among children in Shenzhen, China: Non-linearity, threshold and interaction.

PubMed

Zhang, Zhen; Xie, Xu; Chen, Xiliang; Li, Yuan; Lu, Yan; Mei, Shujiang; Liao, Yuxue; Lin, Hualiang

2016-01-01

Various meteorological factors have been associated with hand, foot and mouth disease (HFMD) among children; however, fewer studies have examined the non-linearity and interaction among the meteorological factors. A generalized additive model with a log link allowing Poisson auto-regression and over-dispersion was applied to investigate the short-term effects daily meteorological factors on children HFMD with adjustment of potential confounding factors. We found positive effects of mean temperature and wind speed, the excess relative risk (ERR) was 2.75% (95% CI: 1.98%, 3.53%) for one degree increase in daily mean temperature on lag day 6, and 3.93% (95% CI: 2.16% to 5.73%) for 1m/s increase in wind speed on lag day 3. We found a non-linear effect of relative humidity with thresholds with the low threshold at 45% and high threshold at 85%, within which there was positive effect, the ERR was 1.06% (95% CI: 0.85% to 1.27%) for 1 percent increase in relative humidity on lag day 5. No significant effect was observed for rainfall and sunshine duration. For the interactive effects, we found a weak additive interaction between mean temperature and relative humidity, and slightly antagonistic interaction between mean temperature and wind speed, and between relative humidity and wind speed in the additive models, but the interactions were not statistically significant. This study suggests that mean temperature, relative humidity and wind speed might be risk factors of children HFMD in Shenzhen, and the interaction analysis indicates that these meteorological factors might have played their roles individually. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

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.

Interactive modelling with stakeholders in two cases in flood management

NASA Astrophysics Data System (ADS)

Leskens, Johannes; Brugnach, Marcela

2013-04-01

New policies on flood management called Multi-Level Safety (MLS), demand for an integral and collaborative approach. The goal of MLS is to minimize flood risks by a coherent package of protection measures, crisis management and flood resilience measures. To achieve this, various stakeholders, such as water boards, municipalities and provinces, have to collaborate in composing these measures. Besides the many advances this integral and collaborative approach gives, the decision-making environment becomes also more complex. Participants have to consider more criteria than they used to do and have to take a wide network of participants into account, all with specific perspectives, cultures and preferences. In response, sophisticated models are developed to support decision-makers in grasping this complexity. These models provide predictions of flood events and offer the opportunity to test the effectiveness of various measures under different criteria. Recent model advances in computation speed and model flexibility allow stakeholders to directly interact with a hydrological hydraulic model during meetings. Besides a better understanding of the decision content, these interactive models are supposed to support the incorporation of stakeholder knowledge in modelling and to support mutual understanding of different perspectives of stakeholders To explore the support of interactive modelling in integral and collaborate policies, such as MLS, we tested a prototype of an interactive flood model (3Di) with respect to a conventional model (Sobek) in two cases. The two cases included the designing of flood protection measures in Amsterdam and a flood event exercise in Delft. These case studies yielded two main results. First, we observed that in the exploration phase of a decision-making process, stakeholders participated actively in interactive modelling sessions. This increased the technical understanding of complex problems and the insight in the effectiveness of various integral measures. Second, when measures became more concrete, the model played a minor role, as stakeholders were still bounded to goals, responsibilities and budgets of their own organization. Model results in this phase are mainly used in a political way to maximize the goals of particular organizations.

Estimation of the solubility parameters of model plant surfaces and agrochemicals: a valuable tool for understanding plant surface interactions

PubMed Central

2012-01-01

Background Most aerial plant parts are covered with a hydrophobic lipid-rich cuticle, which is the interface between the plant organs and the surrounding environment. Plant surfaces may have a high degree of hydrophobicity because of the combined effects of surface chemistry and roughness. The physical and chemical complexity of the plant cuticle limits the development of models that explain its internal structure and interactions with surface-applied agrochemicals. In this article we introduce a thermodynamic method for estimating the solubilities of model plant surface constituents and relating them to the effects of agrochemicals. Results Following the van Krevelen and Hoftyzer method, we calculated the solubility parameters of three model plant species and eight compounds that differ in hydrophobicity and polarity. In addition, intact tissues were examined by scanning electron microscopy and the surface free energy, polarity, solubility parameter and work of adhesion of each were calculated from contact angle measurements of three liquids with different polarities. By comparing the affinities between plant surface constituents and agrochemicals derived from (a) theoretical calculations and (b) contact angle measurements we were able to distinguish the physical effect of surface roughness from the effect of the chemical nature of the epicuticular waxes. A solubility parameter model for plant surfaces is proposed on the basis of an increasing gradient from the cuticular surface towards the underlying cell wall. Conclusions The procedure enabled us to predict the interactions among agrochemicals, plant surfaces, and cuticular and cell wall components, and promises to be a useful tool for improving our understanding of biological surface interactions. PMID:23151272

Estimation of the solubility parameters of model plant surfaces and agrochemicals: a valuable tool for understanding plant surface interactions.

PubMed

Khayet, Mohamed; Fernández, Victoria

2012-11-14

Most aerial plant parts are covered with a hydrophobic lipid-rich cuticle, which is the interface between the plant organs and the surrounding environment. Plant surfaces may have a high degree of hydrophobicity because of the combined effects of surface chemistry and roughness. The physical and chemical complexity of the plant cuticle limits the development of models that explain its internal structure and interactions with surface-applied agrochemicals. In this article we introduce a thermodynamic method for estimating the solubilities of model plant surface constituents and relating them to the effects of agrochemicals. Following the van Krevelen and Hoftyzer method, we calculated the solubility parameters of three model plant species and eight compounds that differ in hydrophobicity and polarity. In addition, intact tissues were examined by scanning electron microscopy and the surface free energy, polarity, solubility parameter and work of adhesion of each were calculated from contact angle measurements of three liquids with different polarities. By comparing the affinities between plant surface constituents and agrochemicals derived from (a) theoretical calculations and (b) contact angle measurements we were able to distinguish the physical effect of surface roughness from the effect of the chemical nature of the epicuticular waxes. A solubility parameter model for plant surfaces is proposed on the basis of an increasing gradient from the cuticular surface towards the underlying cell wall. The procedure enabled us to predict the interactions among agrochemicals, plant surfaces, and cuticular and cell wall components, and promises to be a useful tool for improving our understanding of biological surface interactions.

A kernel regression approach to gene-gene interaction detection for case-control studies.

PubMed

Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

Direction of Amygdala-Neocortex Interaction During Dynamic Facial Expression Processing.

PubMed

Sato, Wataru; Kochiyama, Takanori; Uono, Shota; Yoshikawa, Sakiko; Toichi, Motomi

2017-03-01

Dynamic facial expressions of emotion strongly elicit multifaceted emotional, perceptual, cognitive, and motor responses. Neuroimaging studies revealed that some subcortical (e.g., amygdala) and neocortical (e.g., superior temporal sulcus and inferior frontal gyrus) brain regions and their functional interaction were involved in processing dynamic facial expressions. However, the direction of the functional interaction between the amygdala and the neocortex remains unknown. To investigate this issue, we re-analyzed functional magnetic resonance imaging (fMRI) data from 2 studies and magnetoencephalography (MEG) data from 1 study. First, a psychophysiological interaction analysis of the fMRI data confirmed the functional interaction between the amygdala and neocortical regions. Then, dynamic causal modeling analysis was used to compare models with forward, backward, or bidirectional effective connectivity between the amygdala and neocortical networks in the fMRI and MEG data. The results consistently supported the model of effective connectivity from the amygdala to the neocortex. Further increasing time-window analysis of the MEG demonstrated that this model was valid after 200 ms from the stimulus onset. These data suggest that emotional processing in the amygdala rapidly modulates some neocortical processing, such as perception, recognition, and motor mimicry, when observing dynamic facial expressions of emotion. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Diversity of charge orderings in correlated systems

NASA Astrophysics Data System (ADS)

Kapcia, Konrad Jerzy; Barański, Jan; Ptok, Andrzej

2017-10-01

The phenomenon associated with inhomogeneous distribution of electron density is known as a charge ordering. In this work, we study the zero-bandwidth limit of the extended Hubbard model, which can be considered as a simple effective model of charge ordered insulators. It consists of the on-site interaction U and the intersite density-density interactions W1 and W2 between nearest neighbors and next-nearest neighbors, respectively. We derived the exact ground state diagrams for different lattice dimensionalities and discuss effects of small finite temperatures in the limit of high dimensions. In particular, we estimated the critical interactions for which new ordered phases emerge (laminar or stripe and four-sublattice-type). Our analysis show that the ground state of the model is highly degenerated. One of the most intriguing finding is that the nonzero temperature removes these degenerations.

Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review

PubMed Central

McClelland, James L.

2013-01-01

This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered. PMID:23970868

Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review.

PubMed

McClelland, James L

2013-01-01

This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered.

Effect of the microtubule-associated protein tau on dynamics of single-headed motor proteins KIF1A

NASA Astrophysics Data System (ADS)

Sparacino, J.; Farías, M. G.; Lamberti, P. W.

2014-02-01

Intracellular transport based on molecular motors and its regulation are crucial to the functioning of cells. Filamentary tracks of the cells are abundantly decorated with nonmotile microtubule-associated proteins, such as tau. Motivated by experiments on kinesin-tau interactions [Dixit et al., Science 319, 1086 (2008), 10.1126/science.1152993] we developed a stochastic model of interacting single-headed motor proteins KIF1A that also takes into account the interactions between motor proteins and tau molecules. Our model reproduces experimental observations and predicts significant effects of tau on bound time and run length which suggest an important role of tau in regulation of kinesin-based transport.

Effects of polarons on static polarizabilities and second order hyperpolarizabilities of conjugated polymers

NASA Astrophysics Data System (ADS)

Wang, Ya-Dong; Meng, Yan; Di, Bing; Wang, Shu-Ling; An, Zhong

2010-12-01

According to the one-dimensional tight-binding Su—Schrieffer—Heeger model, we have investigated the effects of charged polarons on the static polarizability, αxx, and the second order hyperpolarizabilities, γxxxx, of conjugated polymers. Our results are consistent qualitatively with previous ab initio and semi-empirical calculations. The origin of the universal growth is discussed using a local-view formalism that is based on the local atomic charge derivatives. Furthermore, combining the Su-Schrieffer-Heeger model and the extended Hubbard model, we have investigated systematically the effects of electron-electron interactions on αxx and γxxxx of charged polymer chains. For a fixed value of the nearest-neighbour interaction V, the values of αxx and γxxxx increase as the on-site Coulomb interaction U increases for U < Uc and decrease with U for U > Uc, where Uc is a critical value of U at which the static polarizability or the second order hyperpolarizability reaches a maximal value of αmax or γmax. It is found that the effect of the e-e interaction on the value of αxx is dependent on the ratio between U and V for either a short or a long charged polymer. Whereas, that effect on the value of γxxxx is sensitive both to the ratio of U to V and to the size of the molecule.

Using Clickers to Facilitate Interactive Engagement Activities in a Lecture Room for Improved Performance by Students

ERIC Educational Resources Information Center

Tlhoaele, Malefyane; Hofman, Adriaan; Naidoo, Ari; Winnips, Koos

2014-01-01

What impact can interactive engagement (IE) activities using clickers have on students' motivation and academic performance during lectures as compared to attending traditional types of lectures? This article positions the research on IE within the comprehensive model of educational effectiveness and Gagné's instructional events model. For the…

A Roy Model of Social Interactions. NBER Working Paper No. 16880

ERIC Educational Resources Information Center

Cicala, Steve; Fryer, Roland G., Jr.; Spenkuch, Jorg L.

2011-01-01

We develop a Roy model of social interactions in which individuals sort into peer groups based on comparative advantage. Two key results emerge: First, when comparative advantage is the guiding principle of peer group organization, the effect of moving a student into an environment with higher-achieving peers depends on where in the ability…

Helping Students Assess the Relative Importance of Different Intermolecular Interactions

ERIC Educational Resources Information Center

Jasien, Paul G.

2008-01-01

A semi-quantitative model has been developed to estimate the relative effects of dispersion, dipole-dipole interactions, and H-bonding on the normal boiling points ("T[subscript b]") for a subset of simple organic systems. The model is based upon a statistical analysis using multiple linear regression on a series of straight-chain organic…

Development of a railway wagon-track interaction model: Case studies on excited tracks

NASA Astrophysics Data System (ADS)

Xu, Lei; Chen, Xianmai; Li, Xuwei; He, Xianglin

2018-02-01

In this paper, a theoretical framework for modeling the railway wagon-ballast track interactions is presented, in which the dynamic equations of motion of wagon-track systems are constructed by effectively coupling the linear and nonlinear dynamic characteristics of system components. For the linear components, the energy-variational principle is directly used to derive their dynamic matrices, while for the nonlinear components, the dynamic equilibrium method is implemented to deduce the load vectors, based on which a novel railway wagon-ballast track interaction model is developed, and being validated by comparing with the experimental data measured from a heavy haul railway and another advanced model. With this study, extensive contributions in figuring out the critical speed of instability, limits and localizations of track irregularities over derailment accidents are presented by effectively integrating the dynamic simulation model, the track irregularity probabilistic model and time-frequency analysis method. The proposed approaches can provide crucial information to guarantee the running safety and stability of the wagon-track system when considering track geometries and various running speeds.

Flow resistance interactions on hillslopes with heterogeneous attributes: Effects on runoff hydrograph characteristics

USDA-ARS?s Scientific Manuscript database

An improved modeling framework for capturing the effects of dynamic resistance to overland flow is developed for intensively managed landscapes. The framework builds on the WEPP model but it removes the limitations of the “equivalent” plane and static roughness assumption. The enhanced model therefo...

Assessing NARCCAP climate model effects using spatial confidence regions.

PubMed

French, Joshua P; McGinnis, Seth; Schwartzman, Armin

2017-01-01

We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

A systematic review and meta-analysis of comprehensive interventions for pre-school children with autism spectrum disorder (ASD).

PubMed

Tachibana, Yoshiyuki; Miyazaki, Celine; Ota, Erika; Mori, Rintaro; Hwang, Yeonhee; Kobayashi, Eriko; Terasaka, Akiko; Tang, Julian; Kamio, Yoko

2017-01-01

There has an increasing number of published trials on psychosocial intervention programmes for pre-school children with autism spectrum disorder (ASD). To achieve better quality of unbiased evidence for the effectiveness of ASD interventions, it is necessary to conduct a comprehensive review that covers studies with adequate quality standards, such as randomised controlled trials (RCTs), and different types of intervention In this study, we categorize interventions for ASD as behavioural, social-communication focused, and multimodal developmental based on Howlin's classification of early interventions for children with ASD. The aim of this study was to compare these three models and investigate the strengths and weaknesses of each type of intervention and to identify the approaches that contribute to a successful outcome for children with autism. We performed a systematic review and meta-analysis. We included RCTs targeting children with ASD 6 years old or younger. A random effects model was used to present the effect estimate for the outcomes. This study also performed combined meta-analyses of all the three models to investigate the overall effectiveness of the intervention programmes. 32 randomized controlled studies were found to be eligible for inclusion. The synthesized data included 594 children from 14 RCTs. There was no statistically significant difference in the effects on autism general symptoms between the social-communication-focused model and the multimodal developmental model (p = 0.83). The results suggest that there is evidence of an effect on 'reciprocity of social interaction towards others' (standard mean difference [95% confidential interval] = 0.53[0.29,0.78], p<0.01) and 'parental synchrony' (SMD = 0.99[0.70,1.29], p<0.01). The small number of studies included in the present study limited the ability to make inferences when comparing the three models and investigating the strengths and weaknesses of each type of intervention with respect to important outcomes. Since the outcome of 'reciprocity of social interaction towards others' could be a dependent variable that might be context-bound to interactions with the child's parent, we cannot conclude the interventions for pre-school children with ASD have significant effects on a generalized skill to engage in reciprocal interactions with others. However, the outcomes of 'reciprocity of social interaction towards others' and 'parental synchrony' may be promising targets for interventions involving pre-school children with ASD. Prospero CRD42011001349.

Effects of Working Memory Capacity and Domain Knowledge on Recall for Grocery Prices.

PubMed

Bermingham, Douglas; Gardner, Michael K; Woltz, Dan J

2016-01-01

Hambrick and Engle (2002) proposed 3 models of how domain knowledge and working memory capacity may work together to influence episodic memory: a "rich-get-richer" model, a "building blocks" model, and a "compensatory" model. Their results supported the rich-get-richer model, although later work by Hambrick and Oswald (2005) found support for a building blocks model. We investigated the effects of domain knowledge and working memory on recall of studied grocery prices. Working memory was measured with 3 simple span tasks. A contrast of realistic versus fictitious foods in the episodic memory task served as our manipulation of domain knowledge, because participants could not have domain knowledge of fictitious food prices. There was a strong effect for domain knowledge (realistic food-price pairs were easier to remember) and a moderate effect for working memory capacity (higher working memory capacity produced better recall). Furthermore, the interaction between domain knowledge and working memory produced a small but significant interaction in 1 measure of price recall. This supported the compensatory model and stands in contrast to previous research.

Replication of Early B-cell Factor 1 (EBF1) Gene-by-psychosocial Stress Interaction Effects on Central Adiposity in a Korean Population.

PubMed

Kim, Hyun-Jin; Min, Jin-Young; Min, Kyoung-Bok

2016-09-01

Central obesity plays a major role in the development of many chronic diseases, including cardiovascular disease and cancer. Chronic stress may be involved in the pathophysiology of central obesity. Although several large-scale genome-wide association studies have reported susceptibility genes for central adiposity, the effects of interactions between genes and psychosocial stress on central adiposity have rarely been examined. A recent study focusing on Caucasians discovered the novel gene early B-cell factor 1 (EBF1) , which was associated with central obesity-related traits via interactions with stress levels. We aimed to evaluate EBF1 gene-by-stress interaction effects on central adiposity traits, including visceral adipose tissue (VAT), in Korean adults. A total of 1467 Korean adults were included in this study. We selected 22 single-nucleotide polymorphisms (SNPs) in the EBF1 gene and analyzed their interactions with stress on central adiposity using additive, dominant, and recessive genetic modeling. The four SNPs that had strong linkage disequilibrium relationships (rs10061900, rs10070743, rs4704967, and rs10056564) demonstrated significant interactions with the waist-hip ratio in the dominant model ( p int <0.007). In addition, two other SNPs (rs6556377 and rs13180086) were associated with VAT by interactions with stress levels, especially in the recessive genetic model ( p int <0.007). As stress levels increased, the mean values of central adiposity traits according to SNP genotypes exhibited gradual but significant changes ( p <0.05). These results suggest that the common genetic variants for EBF1 are associated with central adiposity through interactions with stress levels, emphasizing the importance of managing stress in the prevention of central obesity.

Cloud-Resolving Model Simulations of Aerosol-Cloud Interactions Triggered by Strong Aerosol Emissions in the Arctic

NASA Astrophysics Data System (ADS)

Wang, H.; Kravitz, B.; Rasch, P. J.; Morrison, H.; Solomon, A.

2014-12-01

Previous process-oriented modeling studies have highlighted the dependence of effectiveness of cloud brightening by aerosols on cloud regimes in warm marine boundary layer. Cloud microphysical processes in clouds that contain ice, and hence the mechanisms that drive aerosol-cloud interactions, are more complicated than in warm clouds. Interactions between ice particles and liquid drops add additional levels of complexity to aerosol effects. A cloud-resolving model is used to study aerosol-cloud interactions in the Arctic triggered by strong aerosol emissions, through either geoengineering injection or concentrated sources such as shipping and fires. An updated cloud microphysical scheme with prognostic aerosol and cloud particle numbers is employed. Model simulations are performed in pure super-cooled liquid and mixed-phase clouds, separately, with or without an injection of aerosols into either a clean or a more polluted Arctic boundary layer. Vertical mixing and cloud scavenging of particles injected from the surface is still quite efficient in the less turbulent cold environment. Overall, the injection of aerosols into the Arctic boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. The pure liquid clouds are more susceptible to the increase in aerosol number concentration than the mixed-phase clouds. Rain production processes are more effectively suppressed by aerosol injection, whereas ice precipitation (snow) is affected less; thus the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. Aerosol injection into a clean boundary layer results in a greater cloud albedo increase than injection into a polluted one, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, the impact of dynamical feedback due to precipitation changes is small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering/shipping could have substantial local radiative effects, but is unlikely to be effective as the sole means of counterbalancing warming due to climate change.

sdg boson model in the SU(3) scheme

NASA Astrophysics Data System (ADS)

Akiyama, Yoshimi

1985-02-01

Basic properties of the interacting boson model with s-, d- and g-bosons are investigated in rotational nuclei. An SU(3)-seniority scheme is found for the classification of physically important states according to a group reduction chain U(15) ⊃ SU(3). The capability of describing rotational bands increases enormously in comparison with the ordinary sd interacting boson model. The sdg boson model is shown to be able to describe the so-called anharmonicity effect recently observed in the 168Er nucleus.

A model of interaction between anticorruption authority and corruption groups

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

Neverova, Elena G.; Malafeyef, Oleg A.

The paper provides a model of interaction between anticorruption unit and corruption groups. The main policy functions of the anticorruption unit involve reducing corrupt practices in some entities through an optimal approach to resource allocation and effective anticorruption policy. We develop a model based on Markov decision-making process and use Howard’s policy-improvement algorithm for solving an optimal decision strategy. We examine the assumption that corruption groups retaliate against the anticorruption authority to protect themselves. This model was implemented through stochastic game.

Complexity in African savannas: Direct, indirect, and cascading effects of animal densities, rainfall and vegetation availability

PubMed Central

Leeuwis, Tim; Peel, Mike

2018-01-01

Savanna ecosystems are popular subjects for interaction studies. Multiple studies have been done on the impact of elephants on vegetation, the impact of grass and browse availability on animal densities or on competition between herbivore species. Previous studies showed that elephant densities are frequently negatively correlated with densities of tall trees, and that browse and grass availability are correlated with browser and grazer density respectively. Additionally, a competition effect between browse and grass availability has been reported. These relationships are usually analysed by testing direct relationships between e.g., herbivore densities and food availability, without addressing competition effects or other indirect effects. In this study, multiple interactions in a savanna system have been analysed simultaneously using Partial Least Square-Path Modelling (PLS-PM) using mammal and vegetation data from three different wildlife reserves in southern KwaZulu-Natal. The results showed that the processes that three separate models for the three areas provided the best understanding of the importance of the different interactions. These models suggest that elephants had a negative impact on trees, but also on grass availability. The impact is stronger when elephants are not able to migrate during the dry season. Browsers and grazers were correlated with browse and grass availability, but competition between browse and grass was not detected. This study shows that due to the complexity of the interactions in an ecosystem and differences in environmental factors, these interactions are best studied per area. PLS-PM can be a useful tool for estimating direct, indirect, and cascading effects of changing animal densities in conservation areas. PMID:29768481

The development of interior noise and vibration criteria

NASA Technical Reports Server (NTRS)

Leatherwood, J. D.; Clevenson, S. A.; Stephens, D. G.

1990-01-01

A generalized model was developed for estimating passenger discomfort response to combined noise and vibration. This model accounts for broadband noise and vibration spectra and multiple axes of vibration as well as the interactive effects of combined noise and vibration. The model has the unique capability of transforming individual components of noise/vibration environment into subjective comfort units and then combining these comfort units to produce a total index of passenger discomfort and useful sub-indices that typify passenger comfort within the environment. An overview of the model development is presented including the methodology employed, major elements of the model, model applications, and a brief description of a commercially available portable ride comfort meter based directly upon the model algorithms. Also discussed are potential criteria formats that account for the interactive effects of noise and vibration on human discomfort response.

Partially composite particle physics with and without supersymmetry

NASA Astrophysics Data System (ADS)

Kramer, Thomas A.

Theories in which the Standard Model fields are partially compositeness provide elegant and phenomenologically viable solutions to the Hierarchy Problem. In this thesis we will study types of models from two different perspectives. We first derive an effective field theory describing the interactions of the Standard Models fields with their lightest composite partners based on two weakly coupled sectors. Technically, via the AdS/CFT correspondence, our model is dual to a highly deconstructed theory with a single warped extra-dimension. This two sector theory provides a simplified approach to the phenomenology of this important class of theories. We then use this effective field theoretic approach to study models with weak scale accidental supersymmetry. Particularly, we will investigate the possibility that the Standard Model Higgs field is a member of a composite supersymmetric sector interacting weakly with the known Standard Model fields.

Criticality of the electron-nucleus cusp condition to local effective potential-energy theories

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

Pan Xiaoyin; Sahni, Viraht; Graduate School of the City University of New York, 360 Fifth Avenue, New York, New York 10016

2003-01-01

Local(multiplicative) effective potential energy-theories of electronic structure comprise the transformation of the Schroedinger equation for interacting Fermi systems to model noninteracting Fermi or Bose systems whereby the equivalent density and energy are obtained. By employing the integrated form of the Kato electron-nucleus cusp condition, we prove that the effective electron-interaction potential energy of these model fermions or bosons is finite at a nucleus. The proof is general and valid for arbitrary system whether it be atomic, molecular, or solid state, and for arbitrary state and symmetry. This then provides justification for all prior work in the literature based on themore » assumption of finiteness of this potential energy at a nucleus. We further demonstrate the criticality of the electron-nucleus cusp condition to such theories by an example of the hydrogen molecule. We show thereby that both model system effective electron-interaction potential energies, as determined from densities derived from accurate wave functions, will be singular at the nucleus unless the wave function satisfies the electron-nucleus cusp condition.« less