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

NASA Astrophysics Data System (ADS)

Liang, Tengfei; Li, Qi; Ye, Wenjing

2018-01-01

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

Ferromagnetic interaction model of activity level in workplace communication

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

Specifying and Refining a Measurement Model for a Computer-Based Interactive Assessment

ERIC Educational Resources Information Center

Levy, Roy; Mislevy, Robert J.

2004-01-01

The challenges of modeling students' performance in computer-based interactive assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance. This article describes a Bayesian approach to modeling and estimating cognitive models…

Description of alpha-nucleus interaction cross sections for cosmic ray shielding studies

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Townsend, Lawrence W.; Wilson, John W.

1993-01-01

Nuclear interactions of high-energy alpha particles with target nuclei important for cosmic ray studies are discussed. Models for elastic, quasi-elastic, and breakup reactions are presented and compared with experimental data. Energy-dependent interaction cross sections and secondary spectra are presented based on theoretical models and the limited experimental data base.

Hadron-nucleus interactions at high energies

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

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

1982-06-01

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

Hadron-nucleus interactions at high energies

NASA Astrophysics Data System (ADS)

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

1982-06-01

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

A model-based executive for commanding robot teams

NASA Technical Reports Server (NTRS)

Barrett, Anthony

2005-01-01

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

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

PubMed

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

PubMed Central

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation. PMID:28596730

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.

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.

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

PubMed Central

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

2013-01-01

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

Integrating Biodiversity into Biosphere-Atmosphere Interactions Using Individual-Based Models (IBM)

NASA Astrophysics Data System (ADS)

Wang, B.; Shugart, H. H., Jr.; Lerdau, M.

2017-12-01

A key component regulating complex, nonlinear, and dynamic biosphere-atmosphere interactions is the inherent diversity of biological systems. The model frameworks currently widely used, i.e., Plant Functional Type models) do not even begin to capture the metabolic and taxonomic diversity found in many terrestrial systems. We propose that a transition from PFT-based to individual-based modeling approaches (hereafter referred to as IBM) is essential for integrating biodiversity into research on biosphere-atmosphere interactions. The proposal emerges from our studying the interactions of forests with atmospheric processes in the context of climate change using an individual-based forest volatile organic compounds model, UVAFME-VOC. This individual-based model can explicitly simulate VOC emissions based on an explicit modelling of forest dynamics by computing the growth, death, and regeneration of each individual tree of different species and their competition for light, moisture, and nutrient, from which system-level VOC emissions are simulated by explicitly computing and summing up each individual's emissions. We found that elevated O3 significantly altered the forest dynamics by favoring species that are O3-resistant, which, meanwhile, are producers of isoprene. Such compositional changes, on the one hand, resulted in unsuppressed forest productivity and carbon stock because of the compensation by O3-resistant species. On the other hand, with more isoprene produced arising from increased producers, a possible positive feedback loop between tropospheric O3 and forest thereby emerged. We also found that climate warming will not always stimulate isoprene emissions because warming simultaneously reduces isoprene emissions by causing a decline in the abundance of isoprene-emitting species. These results suggest that species diversity is of great significance and that individual-based modelling strategies should be applied in studying biosphere-atmosphere interactions.

Automated visualization of rule-based models

PubMed Central

Tapia, Jose-Juan; Faeder, James R.

2017-01-01

Frameworks such as BioNetGen, Kappa and Simmune use “reaction rules” to specify biochemical interactions compactly, where each rule specifies a mechanism such as binding or phosphorylation and its structural requirements. Current rule-based models of signaling pathways have tens to hundreds of rules, and these numbers are expected to increase as more molecule types and pathways are added. Visual representations are critical for conveying rule-based models, but current approaches to show rules and interactions between rules scale poorly with model size. Also, inferring design motifs that emerge from biochemical interactions is an open problem, so current approaches to visualize model architecture rely on manual interpretation of the model. Here, we present three new visualization tools that constitute an automated visualization framework for rule-based models: (i) a compact rule visualization that efficiently displays each rule, (ii) the atom-rule graph that conveys regulatory interactions in the model as a bipartite network, and (iii) a tunable compression pipeline that incorporates expert knowledge and produces compact diagrams of model architecture when applied to the atom-rule graph. The compressed graphs convey network motifs and architectural features useful for understanding both small and large rule-based models, as we show by application to specific examples. Our tools also produce more readable diagrams than current approaches, as we show by comparing visualizations of 27 published models using standard graph metrics. We provide an implementation in the open source and freely available BioNetGen framework, but the underlying methods are general and can be applied to rule-based models from the Kappa and Simmune frameworks also. We expect that these tools will promote communication and analysis of rule-based models and their eventual integration into comprehensive whole-cell models. PMID:29131816

An Interactive Model of Career Decision Making.

ERIC Educational Resources Information Center

Amundson, Norman E.

1995-01-01

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

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Global structure–activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors

PubMed Central

Cunningham, Albert R.; Trent, John O.

2012-01-01

Structure–activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby’s structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity. PMID:22678118

Global structure-activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors.

PubMed

Cunningham, Albert R; Carrasquer, C Alex; Qamar, Shahid; Maguire, Jon M; Cunningham, Suzanne L; Trent, John O

2012-10-01

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby's structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity.

Method and apparatus for modeling interactions

DOEpatents

Xavier, Patrick G.

2002-01-01

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

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

PubMed

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

2017-10-25

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

Web-based Interactive Landform Simulation Model - Grand Canyon

NASA Astrophysics Data System (ADS)

Luo, W.; Pelletier, J. D.; Duffin, K.; Ormand, C. J.; Hung, W.; Iverson, E. A.; Shernoff, D.; Zhai, X.; Chowdary, A.

2013-12-01

Earth science educators need interactive tools to engage and enable students to better understand how Earth systems work over geologic time scales. The evolution of landforms is ripe for interactive, inquiry-based learning exercises because landforms exist all around us. The Web-based Interactive Landform Simulation Model - Grand Canyon (WILSIM-GC, http://serc.carleton.edu/landform/) is a continuation and upgrade of the simple cellular automata (CA) rule-based model (WILSIM-CA, http://www.niu.edu/landform/) that can be accessed from anywhere with an Internet connection. Major improvements in WILSIM-GC include adopting a physically based model and the latest Java technology. The physically based model is incorporated to illustrate the fluvial processes involved in land-sculpting pertaining to the development and evolution of one of the most famous landforms on Earth: the Grand Canyon. It is hoped that this focus on a famous and specific landscape will attract greater student interest and provide opportunities for students to learn not only how different processes interact to form the landform we observe today, but also how models and data are used together to enhance our understanding of the processes involved. The latest development in Java technology (such as Java OpenGL for access to ubiquitous fast graphics hardware, Trusted Applet for file input and output, and multithreaded ability to take advantage of modern multi-core CPUs) are incorporated into building WILSIM-GC and active, standards-aligned curricula materials guided by educational psychology theory on science learning will be developed to accompany the model. This project is funded NSF-TUES program.

Tertiary structure-based analysis of microRNA–target interactions

PubMed Central

Gan, Hin Hark; Gunsalus, Kristin C.

2013-01-01

Current computational analysis of microRNA interactions is based largely on primary and secondary structure analysis. Computationally efficient tertiary structure-based methods are needed to enable more realistic modeling of the molecular interactions underlying miRNA-mediated translational repression. We incorporate algorithms for predicting duplex RNA structures, ionic strength effects, duplex entropy and free energy, and docking of duplex–Argonaute protein complexes into a pipeline to model and predict miRNA–target duplex binding energies. To ensure modeling accuracy and computational efficiency, we use an all-atom description of RNA and a continuum description of ionic interactions using the Poisson–Boltzmann equation. Our method predicts the conformations of two constructs of Caenorhabditis elegans let-7 miRNA–target duplexes to an accuracy of ∼3.8 Å root mean square distance of their NMR structures. We also show that the computed duplex formation enthalpies, entropies, and free energies for eight miRNA–target duplexes agree with titration calorimetry data. Analysis of duplex–Argonaute docking shows that structural distortions arising from single-base-pair mismatches in the seed region influence the activity of the complex by destabilizing both duplex hybridization and its association with Argonaute. Collectively, these results demonstrate that tertiary structure-based modeling of miRNA interactions can reveal structural mechanisms not accessible with current secondary structure-based methods. PMID:23417009

Systems engineering interfaces: A model based approach

NASA Astrophysics Data System (ADS)

Fosse, E.; Delp, C. L.

The engineering of interfaces is a critical function of the discipline of Systems Engineering. Included in interface engineering are instances of interaction. Interfaces provide the specifications of the relevant properties of a system or component that can be connected to other systems or components while instances of interaction are identified in order to specify the actual integration to other systems or components. Current Systems Engineering practices rely on a variety of documents and diagrams to describe interface specifications and instances of interaction. The SysML[1] specification provides a precise model based representation for interfaces and interface instance integration. This paper will describe interface engineering as implemented by the Operations Revitalization Task using SysML, starting with a generic case and culminating with a focus on a Flight System to Ground Interaction. The reusability of the interface engineering approach presented as well as its extensibility to more complex interfaces and interactions will be shown. Model-derived tables will support the case studies shown and are examples of model-based documentation products.

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...

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Using a contextualized sensemaking model for interaction design: A case study of tumor contouring.

PubMed

Aselmaa, Anet; van Herk, Marcel; Laprie, Anne; Nestle, Ursula; Götz, Irina; Wiedenmann, Nicole; Schimek-Jasch, Tanja; Picaud, Francois; Syrykh, Charlotte; Cagetti, Leonel V; Jolnerovski, Maria; Song, Yu; Goossens, Richard H M

2017-01-01

Sensemaking theories help designers understand the cognitive processes of a user when he/she performs a complicated task. This paper introduces a two-step approach of incorporating sensemaking support within the design of health information systems by: (1) modeling the sensemaking process of physicians while performing a task, and (2) identifying software interaction design requirements that support sensemaking based on this model. The two-step approach is presented based on a case study of the tumor contouring clinical task for radiotherapy planning. In the first step of the approach, a contextualized sensemaking model was developed to describe the sensemaking process based on the goal, the workflow and the context of the task. In the second step, based on a research software prototype, an experiment was conducted where three contouring tasks were performed by eight physicians respectively. Four types of navigation interactions and five types of interaction sequence patterns were identified by analyzing the gathered interaction log data from those twenty-four cases. Further in-depth study on each of the navigation interactions and interaction sequence patterns in relation to the contextualized sensemaking model revealed five main areas for design improvements to increase sensemaking support. Outcomes of the case study indicate that the proposed two-step approach was beneficial for gaining a deeper understanding of the sensemaking process during the task, as well as for identifying design requirements for better sensemaking support. Copyright © 2016. Published by Elsevier Inc.

Development of an Interactive Computer-Based Learning Strategy to Assist in Teaching Water Quality Modelling

ERIC Educational Resources Information Center

Zigic, Sasha; Lemckert, Charles J.

2007-01-01

The following paper presents a computer-based learning strategy to assist in introducing and teaching water quality modelling to undergraduate civil engineering students. As part of the learning strategy, an interactive computer-based instructional (CBI) aid was specifically developed to assist students to set up, run and analyse the output from a…

Thermodynamic perturbation theory for fused sphere hard chain fluids using nonadditive interactions

NASA Astrophysics Data System (ADS)

Abu-Sharkh, Basel F.; Sunaidi, Abdallah; Hamad, Esam Z.

2004-03-01

A model is developed for the equation of state of fused chains based on Wertheim thermodynamic perturbation theory and nonadditive size interactions. The model also assumes that the structure (represented by the radial distribution function) of the fused chain fluid is the same as that of the touching hard sphere chain fluid. The model is completely based on spherical additive and nonadditive size interactions. The model has the advantage of offering good agreement with simulation data while at the same time being independent of fitted parameters. The model is most accurate for short chains, small values of Δ (slightly fused spheres) and at intermediate (liquidlike) densities.

Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods

NASA Astrophysics Data System (ADS)

Sippl, Wolfgang

2000-08-01

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient ( r 2 = 0.617, q 2 LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained ( r 2 = 0.991, q 2 LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment ( r 2 = 0.951, q 2 LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.

Comparison of a Conceptual Groundwater Model and Physically Based Groundwater Mode

NASA Astrophysics Data System (ADS)

Yang, J.; Zammit, C.; Griffiths, J.; Moore, C.; Woods, R. A.

2017-12-01

Groundwater is a vital resource for human activities including agricultural practice and urban water demand. Hydrologic modelling is an important way to study groundwater recharge, movement and discharge, and its response to both human activity and climate change. To understand the groundwater hydrologic processes nationally in New Zealand, we have developed a conceptually based groundwater flow model, which is fully integrated into a national surface-water model (TopNet), and able to simulate groundwater recharge, movement, and interaction with surface water. To demonstrate the capability of this groundwater model (TopNet-GW), we applied the model to an irrigated area with water shortage and pollution problems in the upper Ruamahanga catchment in Great Wellington Region, New Zealand, and compared its performance with a physically-based groundwater model (MODFLOW). The comparison includes river flow at flow gauging sites, and interaction between groundwater and river. Results showed that the TopNet-GW produced similar flow and groundwater interaction patterns as the MODFLOW model, but took less computation time. This shows the conceptually-based groundwater model has the potential to simulate national groundwater process, and could be used as a surrogate for the more physically based model.

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

PubMed

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

2008-12-01

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

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

PubMed

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

PubMed Central

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

Understanding Parental Monitoring through Analysis of Monitoring Episodes in Context

ERIC Educational Resources Information Center

Hayes, Louise; Hudson, Alan; Matthews, Jan

2007-01-01

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

Method and apparatus for modeling interactions

DOEpatents

Xavier, Patrick G.

2000-08-08

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

Modeling of Complex Coupled Fluid-Structure Interaction Systems in Arbitrary Water Depth

DTIC Science & Technology

2008-01-01

model in a particle finite element method ( PFEM ) based framework for the ALE-RANS solver and submitted a journal paper recently [1]. In the paper, we...developing a fluid-flexible structure interaction model without free surface using ALE-RANS and k-ε turbulence closure model implemented by PFEM . In...the ALE_RANS and k-ε turbulence closure model based on the particle finite element Method ( PFEM ) and obtained some satisfying results [1-2]. The

Traffic and Driving Simulator Based on Architecture of Interactive Motion.

PubMed

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination.

Traffic and Driving Simulator Based on Architecture of Interactive Motion

PubMed Central

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination. PMID:26491711

A continuum mechanics-based musculo-mechanical model for esophageal transport

NASA Astrophysics Data System (ADS)

Kou, Wenjun; Griffith, Boyce E.; Pandolfino, John E.; Kahrilas, Peter J.; Patankar, Neelesh A.

2017-11-01

In this work, we extend our previous esophageal transport model using an immersed boundary (IB) method with discrete fiber-based structural model, to one using a continuum mechanics-based model that is approximated based on finite elements (IB-FE). To deal with the leakage of flow when the Lagrangian mesh becomes coarser than the fluid mesh, we employ adaptive interaction quadrature points to deal with Lagrangian-Eulerian interaction equations based on a previous work (Griffith and Luo [1]). In particular, we introduce a new anisotropic adaptive interaction quadrature rule. The new rule permits us to vary the interaction quadrature points not only at each time-step and element but also at different orientations per element. This helps to avoid the leakage issue without sacrificing the computational efficiency and accuracy in dealing with the interaction equations. For the material model, we extend our previous fiber-based model to a continuum-based model. We present formulations for general fiber-reinforced material models in the IB-FE framework. The new material model can handle non-linear elasticity and fiber-matrix interactions, and thus permits us to consider more realistic material behavior of biological tissues. To validate our method, we first study a case in which a three-dimensional short tube is dilated. Results on the pressure-displacement relationship and the stress distribution matches very well with those obtained from the implicit FE method. We remark that in our IB-FE case, the three-dimensional tube undergoes a very large deformation and the Lagrangian mesh-size becomes about 6 times of Eulerian mesh-size in the circumferential orientation. To validate the performance of the method in handling fiber-matrix material models, we perform a second study on dilating a long fiber-reinforced tube. Errors are small when we compare numerical solutions with analytical solutions. The technique is then applied to the problem of esophageal transport. We use two fiber-reinforced models for the esophageal tissue: a bi-linear model and an exponential model. We present three cases on esophageal transport that differ in the material model and the muscle fiber architecture. The overall transport features are consistent with those observed from the previous model. We remark that the continuum-based model can handle more realistic and complicated material behavior. This is demonstrated in our third case where a spatially varying fiber architecture is included based on experimental study. We find that this unique muscle fiber architecture could generate a so-called pressure transition zone, which is a luminal pressure pattern that is of clinical interest. This suggests an important role of muscle fiber architecture in esophageal transport.

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…

Stacking interactions and DNA intercalation

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

Li, Dr. Shen; Cooper, Valentino R; Thonhauser, Prof. Timo

2009-01-01

The relationship between stacking interactions and the intercalation of proflavine and ellipticine within DNA is investigated using a nonempirical van der Waals density functional for the correlation energy. Our results, employing a binary stack model, highlight fundamental, qualitative differences between base-pair base-pair interactions and that of the stacked intercalator base pair system. Most notable result is the paucity of torque which so distinctively defines the Twist of DNA. Surprisingly, this model, when combined with a constraint on the twist of the surrounding base-pair steps to match the observed unwinding of the sugar-phosphate backbone, was sufficient for explaining the experimentally observedmore » proflavine intercalator configuration. Our extensive mapping of the potential energy surface of base-pair intercalator interactions can provide valuable information for future nonempirical studies of DNA intercalation dynamics.« less

Modelling surface water-groundwater interaction with a conceptual approach: model development and application in New Zealand

NASA Astrophysics Data System (ADS)

Yang, J.; Zammit, C.; McMillan, H. K.

2016-12-01

As in most countries worldwide, water management in lowland areas is a big concern for New Zealand due to its economic importance for water related human activities. As a result, the estimation of available water resources in these areas (e.g., for irrigation and water supply purpose) is crucial and often requires an understanding of complex hydrological processes, which are often characterized by strong interactions between surface water and groundwater (usually expressed as losing and gaining rivers). These processes are often represented and simulated using integrated physically based hydrological models. However models with physically based groundwater modules typically require large amount of non-readily available geologic and aquifer information and are computationally intensive. Instead, this paper presents a conceptual groundwater model that is fully integrated into New Zealand's national hydrological model TopNet based on TopModel concepts (Beven, 1992). Within this conceptual framework, the integrated model can simulate not only surface processes, but also groundwater processes and surface water-groundwater interaction processes (including groundwater flow, river-groundwater interaction, and groundwater interaction with external watersheds). The developed model was applied to two New Zealand catchments with different hydro-geological and climate characteristics (Pareora catchment in the Canterbury Plains and Grey catchment on the West Coast). Previous studies have documented strong interactions between the river and groundwater, based on the analysis of a large number of concurrent flow measurements and associated information along the river main stem. Application of the integrated hydrological model indicates flow simulation (compared to the original hydrological model conceptualisation) during low flow conditions are significantly improved and further insights on local river dynamics are gained. Due to its conceptual characteristics and low level of data requirement, the integrated model could be used at local and national scales to improve the simulation of hydrological processes in non-topographically driven areas (where groundwater processes are important), and to assess impact of climate change on the integrated hydrological cycle in these areas.

Interactive Visualization of DGA Data Based on Multiple Views

NASA Astrophysics Data System (ADS)

Geng, Yujie; Lin, Ying; Ma, Yan; Guo, Zhihong; Gu, Chao; Wang, Mingtao

2017-01-01

The commission and operation of dissolved gas analysis (DGA) online monitoring makes up for the weakness of traditional DGA method. However, volume and high-dimensional DGA data brings a huge challenge for monitoring and analysis. In this paper, we present a novel interactive visualization model of DGA data based on multiple views. This model imitates multi-angle analysis by combining parallel coordinates, scatter plot matrix and data table. By offering brush, collaborative filter and focus + context technology, this model provides a convenient and flexible interactive way to analyze and understand the DGA data.

Quantitative Prediction of Drug–Drug Interactions Involving Inhibitory Metabolites in Drug Development: How Can Physiologically Based Pharmacokinetic Modeling Help?

PubMed Central

Chen, Y; Mao, J; Lin, J; Yu, H; Peters, S; Shebley, M

2016-01-01

This subteam under the Drug Metabolism Leadership Group (Innovation and Quality Consortium) investigated the quantitative role of circulating inhibitory metabolites in drug–drug interactions using physiologically based pharmacokinetic (PBPK) modeling. Three drugs with major circulating inhibitory metabolites (amiodarone, gemfibrozil, and sertraline) were systematically evaluated in addition to the literature review of recent examples. The application of PBPK modeling in drug interactions by inhibitory parent–metabolite pairs is described and guidance on strategic application is provided. PMID:27642087

A Suggested Model for a Working Cyberschool.

ERIC Educational Resources Information Center

Javid, Mahnaz A.

2000-01-01

Suggests a model for a working cyberschool based on a case study of Kamiak Cyberschool (Washington), a technology-driven public high school. Topics include flexible hours; one-to-one interaction with teachers; a supportive school environment; use of computers, interactive media, and online resources; and self-paced, project-based learning.…

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

PubMed

Dabek, Filip; Caban, Jesus J

2017-01-01

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

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.

Identification of walking human model using agent-based modelling

NASA Astrophysics Data System (ADS)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

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

PubMed

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

2014-03-01

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

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

All-particle energy spectrum of KASCADE-Grande based on shower size and different hadronic interaction models

NASA Astrophysics Data System (ADS)

Kang, D.; Apel, W. D.; Arteaga-Velazquez, J. C.; Bekk, K.; Bertaina, M.; Blümer, J.; Bozdog, H.; Brancus, I. M.; Cantoni, E.; Chiavassa, A.; Cossavella, F.; Daumiller, K.; de Souza, V.; Di Pierro, F.; Doll, P.; Engel, R.; Engler, J.; Finger, M.; Fuchs, B.; Fuhrmann, D.; Gils, H. J.; Glasstetter, R.; Grupen, C.; Haungs, A.; Heck, D.; Hörandel, J. R.; Huber, D.; Huege, T.; Kampert, K.-H.; Klages, H. O.; Link, K.; Łuczak, P.; Ludwig, M.; Mathes, H. J.; Mayer, H. J.; Melissas, M.; Milke, J.; Morello, C.; Oehlschläger, J.; Ostapchenko, S.; Palmieri, N.; Petcu, M.; Pierog, T.; Rebel, H.; Roth, M.; Schieler, H.; Schoo, S.; Schroder, F.; Sima, O.; Toma, G.; Trinchero, G. C.; Ulrich, H.; Weindl, A.; Wochele, J.; Wommer, M.; Zabierowski, J.

2013-02-01

KASCADE-Grande is a large detector array for observations of the energy spectrum as well as the chemical composition of cosmic ray air showers up to primary energies of 1 EeV. The multi-detector arrangement allows to measure the electromagnetic and muonic components for individual air showers. In this analysis, the reconstruction of the all-particle energy spectrum is based on the size spectra of the charged particle component. The energy is calibrated by using Monte Carlo simulations performed with CORSIKA and high-energy interaction models QGSJet, EPOS and SIBYLL. In all cases FLUKA has been used as low-energy interaction model. In this contribution the resulting spectra by means of different hadronic interaction models will be compared and discussed.

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

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

The role of perceived interactivity in virtual communities: building trust and increasing stickiness

NASA Astrophysics Data System (ADS)

Wang, Hongwei; Meng, Yuan; Wang, Wei

2013-03-01

Although previous research has explored factors affecting trust building in websites, little research has been analysed from the perceived interactivity perspective in virtual communities (VCs). A research model for verifying interactivity antecedents to trust and its impact on member stickiness behaviour is presented. Two social interactivity components and two system interactivity components are, respectively, theorised as process-based antecedents and institution-based antecedents to trust in the model. Data were collected from 310 members of VCs to test the model. The results show that connectedness and reciprocity are important antecedents to trust in members, while responsiveness and active control are important antecedents to trust in systems. The results also indicate that trust has significant influence on the members' duration and retention, which are two dimensions of member stickiness measured in this research. These findings have theoretical implications for online interaction-related literature and critical business implications for practitioners of VCs.

Enhancing Learning Outcomes with an Interactive Knowledge-Based Learning Environment Providing Narrative Feedback

ERIC Educational Resources Information Center

Stranieri, Andrew; Yearwood, John

2008-01-01

This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…

Unified Deep Learning Architecture for Modeling Biology Sequence.

PubMed

Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

2017-10-09

Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

An Examination of Interactive Whiteboard Perceptions using the Concerns-Based Adoption Model Stages of Concern and the Apple Classrooms of Tomorrow Model of Instructional Evolution

ERIC Educational Resources Information Center

Hall, Jeffrey; Chamblee, Gregory; Slough, Scott

2013-01-01

Two high school mathematics teachers who use Interactive Whiteboards (IWBs) in the classroom were interviewed annually over the course of three years regarding their perceptions of the technology. During the third year, the two teachers were asked to complete the Concerns-Based Adoption Model Stages of Concern Questionnaire. The data obtained from…

Robust Weak Chimeras in Oscillator Networks with Delayed Linear and Quadratic Interactions

NASA Astrophysics Data System (ADS)

Bick, Christian; Sebek, Michael; Kiss, István Z.

2017-10-01

We present an approach to generate chimera dynamics (localized frequency synchrony) in oscillator networks with two populations of (at least) two elements using a general method based on a delayed interaction with linear and quadratic terms. The coupling design yields robust chimeras through a phase-model-based design of the delay and the ratio of linear and quadratic components of the interactions. We demonstrate the method in the Brusselator model and experiments with electrochemical oscillators. The technique opens the way to directly bridge chimera dynamics in phase models and real-world oscillator networks.

Mathematical Analysis for Non-reciprocal-interaction-based Model of Collective Behavior

NASA Astrophysics Data System (ADS)

Kano, Takeshi; Osuka, Koichi; Kawakatsu, Toshihiro; Ishiguro, Akio

2017-12-01

In many natural and social systems, collective behaviors emerge as a consequence of non-reciprocal interaction between their constituents. As a first step towards understanding the core principle that underlies these phenomena, we previously proposed a minimal model of collective behavior based on non-reciprocal interactions by drawing inspiration from friendship formation in human society, and demonstrated via simulations that various non-trivial patterns emerge by changing parameters. In this study, a mathematical analysis of the proposed model wherein the system size is small is performed. Through the analysis, the mechanism of the transition between several patterns is elucidated.

Scaling and modeling of turbulent suspension flows

NASA Technical Reports Server (NTRS)

Chen, C. P.

1989-01-01

Scaling factors determining various aspects of particle-fluid interactions and the development of physical models to predict gas-solid turbulent suspension flow fields are discussed based on two-fluid, continua formulation. The modes of particle-fluid interactions are discussed based on the length and time scale ratio, which depends on the properties of the particles and the characteristics of the flow turbulence. For particle size smaller than or comparable with the Kolmogorov length scale and concentration low enough for neglecting direct particle-particle interaction, scaling rules can be established in various parameter ranges. The various particle-fluid interactions give rise to additional mechanisms which affect the fluid mechanics of the conveying gas phase. These extra mechanisms are incorporated into a turbulence modeling method based on the scaling rules. A multiple-scale two-phase turbulence model is developed, which gives reasonable predictions for dilute suspension flow. Much work still needs to be done to account for the poly-dispersed effects and the extension to dense suspension flows.

Log-Linear Models for Gene Association

PubMed Central

Hu, Jianhua; Joshi, Adarsh; Johnson, Valen E.

2009-01-01

We describe a class of log-linear models for the detection of interactions in high-dimensional genomic data. This class of models leads to a Bayesian model selection algorithm that can be applied to data that have been reduced to contingency tables using ranks of observations within subjects, and discretization of these ranks within gene/network components. Many normalization issues associated with the analysis of genomic data are thereby avoided. A prior density based on Ewens’ sampling distribution is used to restrict the number of interacting components assigned high posterior probability, and the calculation of posterior model probabilities is expedited by approximations based on the likelihood ratio statistic. Simulation studies are used to evaluate the efficiency of the resulting algorithm for known interaction structures. Finally, the algorithm is validated in a microarray study for which it was possible to obtain biological confirmation of detected interactions. PMID:19655032

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

PubMed

Portouli, Evangelia; Nathanael, Dimitris; Marmaras, Nicolas

2014-01-01

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

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.

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.

Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters

PubMed Central

Shang, Yu; Sikorski, Johannes; Bonkowski, Michael; Fiore-Donno, Anna-Maria; Kandeler, Ellen; Marhan, Sven; Boeddinghaus, Runa S.; Solly, Emily F.; Schrumpf, Marion; Schöning, Ingo; Wubet, Tesfaye; Buscot, Francois; Overmann, Jörg

2017-01-01

Interactions occur between two or more organisms affecting each other. Interactions are decisive for the ecology of the organisms. Without direct experimental evidence the analysis of interactions is difficult. Correlation analyses that are based on co-occurrences are often used to approximate interaction. Here, we present a new mathematical model to estimate the interaction strengths between taxa, based on changes in their relative abundances across environmental gradients. PMID:28288199

An experimental-computational platform for investigating microbial interactions and dynamics in communities with two codependent species

NASA Astrophysics Data System (ADS)

Fuentes-Cabrera, Miguel; Anderson, John D.; Wilmoth, Jared; Ginovart, Marta; Prats, Clara; Portell-Canal, Xavier; Retterer, Scott

Microbial interactions are critical for governing community behavior and structure in natural environments. Examination of microbial interactions in the lab involves growth under ideal conditions in batch culture; conditions that occur in nature are, however, characterized by disequilibrium. Of particular interest is the role that system variables play in shaping cell-to-cell interactions and organization at ultrafine spatial scales. We seek to use experiments and agent-based modeling to help discover mechanisms relevant to microbial dynamics and interactions in the environment. Currently, we are using an agent-based model to simulate microbial growth, dynamics and interactions that occur on a microwell-array device developed in our lab. Bacterial cells growing in the microwells of this platform can be studied with high-throughput and high-content image analyses using brightfield and fluorescence microscopy. The agent-based model is written in the language Netlogo, which in turn is ''plugged into'' a computational framework that allows submitting many calculations in parallel for different initial parameters; visualizing the outcomes in an interactive phase-like diagram; and searching, with a genetic algorithm, for the parameters that lead to the most optimal simulation outcome.

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

ERIC Educational Resources Information Center

Montemurro, Theodore J.

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

A definitional framework for the human/biometric sensor interaction model

NASA Astrophysics Data System (ADS)

Elliott, Stephen J.; Kukula, Eric P.

2010-04-01

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

Pain expressiveness and altruistic behavior: an exploration using agent-based modeling.

PubMed

de C Williams, Amanda C; Gallagher, Elizabeth; Fidalgo, Antonio R; Bentley, Peter J

2016-03-01

Predictions which invoke evolutionary mechanisms are hard to test. Agent-based modeling in artificial life offers a way to simulate behaviors and interactions in specific physical or social environments over many generations. The outcomes have implications for understanding adaptive value of behaviors in context. Pain-related behavior in animals is communicated to other animals that might protect or help, or might exploit or predate. An agent-based model simulated the effects of displaying or not displaying pain (expresser/nonexpresser strategies) when injured and of helping, ignoring, or exploiting another in pain (altruistic/nonaltruistic/selfish strategies). Agents modeled in MATLAB interacted at random while foraging (gaining energy); random injury interrupted foraging for a fixed time unless help from an altruistic agent, who paid an energy cost, speeded recovery. Environmental and social conditions also varied, and each model ran for 10,000 iterations. Findings were meaningful in that, in general, contingencies that evident from experimental work with a variety of mammals, over a few interactions, were replicated in the agent-based model after selection pressure over many generations. More energy-demanding expression of pain reduced its frequency in successive generations, and increasing injury frequency resulted in fewer expressers and altruists. Allowing exploitation of injured agents decreased expression of pain to near zero, but altruists remained. Decreasing costs or increasing benefits of helping hardly changed its frequency, whereas increasing interaction rate between injured agents and helpers diminished the benefits to both. Agent-based modeling allows simulation of complex behaviors and environmental pressures over evolutionary time.

A Study of Fan Stage/Casing Interaction Models

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Carney, Kelly; Gallardo, Vicente

2003-01-01

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

cDF Theory Software for mesoscopic modeling of equilibrium and transport phenomena

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

2015-12-01

The approach is based on classical Density Functional Theory ((cDFT) coupled with the Poisson-Nernst-Planck (PNP) transport kinetics model and quantum mechanical description of short-range interaction and elementary transport processes. The model we proposed and implemented is fully atomistic, taking into account pairwise short-range and manybody long-range interactions. But in contrast to standard molecular dynamics (MD) simulations, where long-range manybody interactions are evaluated as a sum of pair-wise atom-atom contributions, we include them analytically based on wellestablished theories of electrostatic and excluded volume interactions in multicomponent systems. This feature of the PNP/cDFT approach allows us to reach well beyond the length-scalesmore » accessible to MD simulations, while retaining the essential physics of interatomic interactions from first principles and in a parameter-free fashion.« less

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.

Methodologies for validating ray-based forward model using finite element method in ultrasonic array data simulation

NASA Astrophysics Data System (ADS)

Zhang, Jie; Nixon, Andrew; Barber, Tom; Budyn, Nicolas; Bevan, Rhodri; Croxford, Anthony; Wilcox, Paul

2018-04-01

In this paper, a methodology of using finite element (FE) model to validate a ray-based model in the simulation of full matrix capture (FMC) ultrasonic array data set is proposed. The overall aim is to separate signal contributions from different interactions in FE results for easier comparing each individual component in the ray-based model results. This is achieved by combining the results from multiple FE models of the system of interest that include progressively more geometrical features while preserving the same mesh structure. It is shown that the proposed techniques allow the interactions from a large number of different ray-paths to be isolated in FE results and compared directly to the results from a ray-based forward model.

The BioGRID interaction database: 2013 update.

PubMed

Chatr-Aryamontri, Andrew; Breitkreutz, Bobby-Joe; Heinicke, Sven; Boucher, Lorrie; Winter, Andrew; Stark, Chris; Nixon, Julie; Ramage, Lindsay; Kolas, Nadine; O'Donnell, Lara; Reguly, Teresa; Breitkreutz, Ashton; Sellam, Adnane; Chen, Daici; Chang, Christie; Rust, Jennifer; Livstone, Michael; Oughtred, Rose; Dolinski, Kara; Tyers, Mike

2013-01-01

The Biological General Repository for Interaction Datasets (BioGRID: http//thebiogrid.org) is an open access archive of genetic and protein interactions that are curated from the primary biomedical literature for all major model organism species. As of September 2012, BioGRID houses more than 500 000 manually annotated interactions from more than 30 model organisms. BioGRID maintains complete curation coverage of the literature for the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe and the model plant Arabidopsis thaliana. A number of themed curation projects in areas of biomedical importance are also supported. BioGRID has established collaborations and/or shares data records for the annotation of interactions and phenotypes with most major model organism databases, including Saccharomyces Genome Database, PomBase, WormBase, FlyBase and The Arabidopsis Information Resource. BioGRID also actively engages with the text-mining community to benchmark and deploy automated tools to expedite curation workflows. BioGRID data are freely accessible through both a user-defined interactive interface and in batch downloads in a wide variety of formats, including PSI-MI2.5 and tab-delimited files. BioGRID records can also be interrogated and analyzed with a series of new bioinformatics tools, which include a post-translational modification viewer, a graphical viewer, a REST service and a Cytoscape plugin.

On Interactive Teaching Model of Translation Course Based on Wechat

ERIC Educational Resources Information Center

Lin, Wang

2017-01-01

Constructivism is a theory related to knowledge and learning, focusing on learners' subjective initiative, based on which the interactive approach has been proved to play a crucial role in language learning. Accordingly, the interactive approach can also be applied to translation teaching since translation itself is a bilingual transformational…

Narrative-Based Interactive Learning Environments from Modelling Reasoning

ERIC Educational Resources Information Center

Yearwood, John; Stranieri, Andrew

2007-01-01

Narrative and story telling has a long history of use in structuring, organising and communicating human experience. This paper describes a narrative based interactive intelligent learning environment which aims to elucidate practical reasoning using interactive emergent narratives that can be used in training novices in decision making. Its…

A Three-Level Analysis of Collaborative Learning in Dual-Interaction Spaces

ERIC Educational Resources Information Center

Lonchamp, Jacques

2009-01-01

CSCL systems which follow the dual-interaction spaces paradigm support the synchronous construction and discussion of shared artifacts by distributed or colocated small groups of learners. The most recent generic dual-interaction space environments, either model based or component based, can be deeply customized by teachers for supporting…

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

ERIC Educational Resources Information Center

Gong, Yu

2017-01-01

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

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

ERIC Educational Resources Information Center

Sato, Masatoshi

2017-01-01

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

Modelling vortex-induced fluid-structure interaction.

PubMed

Benaroya, Haym; Gabbai, Rene D

2008-04-13

The principal goal of this research is developing physics-based, reduced-order, analytical models of nonlinear fluid-structure interactions associated with offshore structures. Our primary focus is to generalize the Hamilton's variational framework so that systems of flow-oscillator equations can be derived from first principles. This is an extension of earlier work that led to a single energy equation describing the fluid-structure interaction. It is demonstrated here that flow-oscillator models are a subclass of the general, physical-based framework. A flow-oscillator model is a reduced-order mechanical model, generally comprising two mechanical oscillators, one modelling the structural oscillation and the other a nonlinear oscillator representing the fluid behaviour coupled to the structural motion.Reduced-order analytical model development continues to be carried out using a Hamilton's principle-based variational approach. This provides flexibility in the long run for generalizing the modelling paradigm to complex, three-dimensional problems with multiple degrees of freedom, although such extension is very difficult. As both experimental and analytical capabilities advance, the critical research path to developing and implementing fluid-structure interaction models entails-formulating generalized equations of motion, as a superset of the flow-oscillator models; and-developing experimentally derived, semi-analytical functions to describe key terms in the governing equations of motion. The developed variational approach yields a system of governing equations. This will allow modelling of multiple d.f. systems. The extensions derived generalize the Hamilton's variational formulation for such problems. The Navier-Stokes equations are derived and coupled to the structural oscillator. This general model has been shown to be a superset of the flow-oscillator model. Based on different assumptions, one can derive a variety of flow-oscillator models.

On quantum integrable models related to nonlinear quantum optics. An algebraic Bethe ansatz approach

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

1989-08-01

A unified approach based on Bethe ansatz in a large variety of integrable models in quantum optics is given. Second harmonics generation, three-boson interaction, the Dicke model, and some cases of four-boson interaction as special cases of su(2)⊕su(1,1)-Gaudin models are included.

An Interactive Teaching System for Bond Graph Modeling and Simulation in Bioengineering

ERIC Educational Resources Information Center

Roman, Monica; Popescu, Dorin; Selisteanu, Dan

2013-01-01

The objective of the present work was to implement a teaching system useful in modeling and simulation of biotechnological processes. The interactive system is based on applications developed using 20-sim modeling and simulation software environment. A procedure for the simulation of bioprocesses modeled by bond graphs is proposed and simulators…

Information Interaction Study for DER and DMS Interoperability

NASA Astrophysics Data System (ADS)

Liu, Haitao; Lu, Yiming; Lv, Guangxian; Liu, Peng; Chen, Yu; Zhang, Xinhui

The Common Information Model (CIM) is an abstract data model that can be used to represent the major objects in Distribution Management System (DMS) applications. Because the Common Information Model (CIM) doesn't modeling the Distributed Energy Resources (DERs), it can't meet the requirements of DER operation and management for Distribution Management System (DMS) advanced applications. Modeling of DER were studied based on a system point of view, the article initially proposed a CIM extended information model. By analysis the basic structure of the message interaction between DMS and DER, a bidirectional messaging mapping method based on data exchange was proposed.

Analysis of Feedback Processes in Online Group Interaction: A Methodological Model

ERIC Educational Resources Information Center

Espasa, Anna; Guasch, Teresa; Alvarez, Ibis M.

2013-01-01

The aim of this article is to present a methodological model to analyze students' group interaction to improve their essays in online learning environments, based on asynchronous and written communication. In these environments teacher and student scaffolds for discussion are essential to promote interaction. One of these scaffolds can be the…

Model-based video segmentation for vision-augmented interactive games

NASA Astrophysics Data System (ADS)

Liu, Lurng-Kuo

2000-04-01

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

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

PubMed

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

2009-04-29

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

UTOPIAN: user-driven topic modeling based on interactive nonnegative matrix factorization.

PubMed

Choo, Jaegul; Lee, Changhyun; Reddy, Chandan K; Park, Haesun

2013-12-01

Topic modeling has been widely used for analyzing text document collections. Recently, there have been significant advancements in various topic modeling techniques, particularly in the form of probabilistic graphical modeling. State-of-the-art techniques such as Latent Dirichlet Allocation (LDA) have been successfully applied in visual text analytics. However, most of the widely-used methods based on probabilistic modeling have drawbacks in terms of consistency from multiple runs and empirical convergence. Furthermore, due to the complicatedness in the formulation and the algorithm, LDA cannot easily incorporate various types of user feedback. To tackle this problem, we propose a reliable and flexible visual analytics system for topic modeling called UTOPIAN (User-driven Topic modeling based on Interactive Nonnegative Matrix Factorization). Centered around its semi-supervised formulation, UTOPIAN enables users to interact with the topic modeling method and steer the result in a user-driven manner. We demonstrate the capability of UTOPIAN via several usage scenarios with real-world document corpuses such as InfoVis/VAST paper data set and product review data sets.

Development of innovative problem based learning model with PMRI-scientific approach using ICT to increase mathematics literacy and independence-character of junior high school students

NASA Astrophysics Data System (ADS)

Wardono; Waluya, B.; Kartono; Mulyono; Mariani, S.

2018-03-01

This research is very urgent in relation to the national issue of human development and the nation's competitiveness because of the ability of Indonesian Junior High School students' mathematics literacy results of the Programme for International Student Assessment (PISA) by OECD field of Mathematics is still very low compared to other countries. Curriculum 2013 launched one of them reflect the results of PISA which is still far from the expectations of the Indonesian nation and to produce a better quality of education, PISA ratings that reflect the nation's better competitiveness need to be developed innovative, interactive learning models such as innovative interactive learning Problem Based Learning (PBL) based on the approach of Indonesian Realistic Mathematics Education (PMRI) and the Scientific approach using Information and Communication Technology (ICT).The research was designed using Research and Development (R&D), research that followed up the development and dissemination of a product/model. The result of the research shows the innovative interactive learning PBL model based on PMRI-Scientific using ICT that developed valid, practical and effective and can improve the ability of mathematics literacy and independence-character of junior high school students. While the quality of innovative interactive learning PBL model based on PMRI-Scientific using ICT meet the good category.

Implicit prosody mining based on the human eye image capture technology

NASA Astrophysics Data System (ADS)

Gao, Pei-pei; Liu, Feng

2013-08-01

The technology of eye tracker has become the main methods of analyzing the recognition issues in human-computer interaction. Human eye image capture is the key problem of the eye tracking. Based on further research, a new human-computer interaction method introduced to enrich the form of speech synthetic. We propose a method of Implicit Prosody mining based on the human eye image capture technology to extract the parameters from the image of human eyes when reading, control and drive prosody generation in speech synthesis, and establish prosodic model with high simulation accuracy. Duration model is key issues for prosody generation. For the duration model, this paper put forward a new idea for obtaining gaze duration of eyes when reading based on the eye image capture technology, and synchronous controlling this duration and pronunciation duration in speech synthesis. The movement of human eyes during reading is a comprehensive multi-factor interactive process, such as gaze, twitching and backsight. Therefore, how to extract the appropriate information from the image of human eyes need to be considered and the gaze regularity of eyes need to be obtained as references of modeling. Based on the analysis of current three kinds of eye movement control model and the characteristics of the Implicit Prosody reading, relative independence between speech processing system of text and eye movement control system was discussed. It was proved that under the same text familiarity condition, gaze duration of eyes when reading and internal voice pronunciation duration are synchronous. The eye gaze duration model based on the Chinese language level prosodic structure was presented to change previous methods of machine learning and probability forecasting, obtain readers' real internal reading rhythm and to synthesize voice with personalized rhythm. This research will enrich human-computer interactive form, and will be practical significance and application prospect in terms of disabled assisted speech interaction. Experiments show that Implicit Prosody mining based on the human eye image capture technology makes the synthesized speech has more flexible expressions.

Interactive Visual Analysis within Dynamic Ocean Models

NASA Astrophysics Data System (ADS)

Butkiewicz, T.

2012-12-01

The many observation and simulation based ocean models available today can provide crucial insights for all fields of marine research and can serve as valuable references when planning data collection missions. However, the increasing size and complexity of these models makes leveraging their contents difficult for end users. Through a combination of data visualization techniques, interactive analysis tools, and new hardware technologies, the data within these models can be made more accessible to domain scientists. We present an interactive system that supports exploratory visual analysis within large-scale ocean flow models. The currents and eddies within the models are illustrated using effective, particle-based flow visualization techniques. Stereoscopic displays and rendering methods are employed to ensure that the user can correctly perceive the complex 3D structures of depth-dependent flow patterns. Interactive analysis tools are provided which allow the user to experiment through the introduction of their customizable virtual dye particles into the models to explore regions of interest. A multi-touch interface provides natural, efficient interaction, with custom multi-touch gestures simplifying the otherwise challenging tasks of navigating and positioning tools within a 3D environment. We demonstrate the potential applications of our visual analysis environment with two examples of real-world significance: Firstly, an example of using customized particles with physics-based behaviors to simulate pollutant release scenarios, including predicting the oil plume path for the 2010 Deepwater Horizon oil spill disaster. Secondly, an interactive tool for plotting and revising proposed autonomous underwater vehicle mission pathlines with respect to the surrounding flow patterns predicted by the model; as these survey vessels have extremely limited energy budgets, designing more efficient paths allows for greater survey areas.

Study of Personalized Network Tutoring System Based on Emotional-cognitive Interaction

NASA Astrophysics Data System (ADS)

Qi, Manfei; Ma, Ding; Wang, Wansen

Aiming at emotion deficiency in present Network tutoring system, a lot of negative effects is analyzed and corresponding countermeasures are proposed. The model of Personalized Network tutoring system based on Emotional-cognitive interaction is constructed in the paper. The key techniques of realizing the system such as constructing emotional model and adjusting teaching strategies are also introduced.

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

PubMed

Chen, Duan

2016-08-01

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

Investigation of Compressibility Effect for Aeropropulsive Shear Flows

NASA Technical Reports Server (NTRS)

Balasubramanyam, M. S.; Chen, C. P.

2005-01-01

Rocket Based Combined Cycle (RBCC) engines operate within a wide range of Mach numbers and altitudes. Fundamental fluid dynamic mechanisms involve complex choking, mass entrainment, stream mixing and wall interactions. The Propulsion Research Center at the University of Alabama in Huntsville is involved in an on- going experimental and numerical modeling study of non-axisymmetric ejector-based combined cycle propulsion systems. This paper attempts to address the modeling issues related to mixing, shear layer/wall interaction in a supersonic Strutjet/ejector flow field. Reynolds Averaged Navier-Stokes (RANS) solutions incorporating turbulence models are sought and compared to experimental measurements to characterize detailed flow dynamics. The effect of compressibility on fluids mixing and wall interactions were investigated using an existing CFD methodology. The compressibility correction to conventional incompressible two- equation models is found to be necessary for the supersonic mixing aspect of the ejector flows based on 2-D simulation results. 3-D strut-base flows involving flow separations were also investigated.

Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions.

PubMed

Nehaniv, Chrystopher L; Rhodes, John; Egri-Nagy, Attila; Dini, Paolo; Morris, Eric Rothstein; Horváth, Gábor; Karimi, Fariba; Schreckling, Daniel; Schilstra, Maria J

2015-07-28

Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in systems biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, the Krebs cycle and p53-mdm2 genetic regulation constructed from systems biology models have canonically associated algebraic structures (their transformation semigroups). These contain permutation groups (local substructures exhibiting symmetry) that correspond to 'pools of reversibility'. These natural subsystems are related to one another in a hierarchical manner by the notion of 'weak control'. We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-Abelian groups are found in biological examples and can be harnessed to realize finitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.

Designing Interactive Learning Systems.

ERIC Educational Resources Information Center

Barker, Philip

1990-01-01

Describes multimedia, computer-based interactive learning systems that support various forms of individualized study. Highlights include design models; user interfaces; design guidelines; media utilization paradigms, including hypermedia and learner-controlled models; metaphors and myths; authoring tools; optical media; workstations; four case…

The dopamine D2 receptor dimer and its interaction with homobivalent antagonists: homology modeling, docking and molecular dynamics.

PubMed

Kaczor, Agnieszka A; Jörg, Manuela; Capuano, Ben

2016-09-01

In order to apply structure-based drug design techniques to G protein-coupled receptor complexes, it is essential to model their 3D structure and to identify regions that are suitable for selective drug binding. For this purpose, we have developed and tested a multi-component protocol to model the inactive conformation of the dopamine D2 receptor dimer, suitable for interaction with homobivalent antagonists. Our approach was based on protein-protein docking, applying the Rosetta software to obtain populations of dimers as present in membranes with all the main possible interfaces. Consensus scoring based on the values and frequencies of best interfaces regarding four scoring parameters, Rosetta interface score, interface area, free energy of binding and energy of hydrogen bond interactions indicated that the best scored dimer model possesses a TM4-TM5-TM7-TM1 interface, which is in agreement with experimental data. This model was used to study interactions of the previously published dopamine D2 receptor homobivalent antagonists based on clozapine,1,4-disubstituted aromatic piperidines/piperazines and arylamidoalkyl substituted phenylpiperazine pharmacophores. It was found that the homobivalent antagonists stabilize the receptor-inactive conformation by maintaining the ionic lock interaction, and change the dimer interface by disrupting a set of hydrogen bonds and maintaining water- and ligand-mediated hydrogen bonds in the extracellular and intracellular part of the interface. Graphical Abstract Structure of the final model of the dopamine D2 receptor homodimer, indicating the distancebetween Tyr37 and Tyr 5.42 in the apo form (left) and in the complex with the ligand (right).

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

Pigeon interaction mode switch-based UAV distributed flocking control under obstacle environments.

PubMed

Qiu, Huaxin; Duan, Haibin

2017-11-01

Unmanned aerial vehicle (UAV) flocking control is a serious and challenging problem due to local interactions and changing environments. In this paper, a pigeon flocking model and a pigeon coordinated obstacle-avoiding model are proposed based on a behavior that pigeon flocks will switch between hierarchical and egalitarian interaction mode at different flight phases. Owning to the similarity between bird flocks and UAV swarms in essence, a distributed flocking control algorithm based on the proposed pigeon flocking and coordinated obstacle-avoiding models is designed to coordinate a heterogeneous UAV swarm to fly though obstacle environments with few informed individuals. The comparative simulation results are elaborated to show the feasibility, validity and superiority of our proposed algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A DGS Gesture Dictionary for Modelling on Mobile Devices

ERIC Educational Resources Information Center

Isotani, Seiji; Reis, Helena M.; Alvares, Danilo; Brandão, Anarosa A. F.; Brandão, Leônidas O.

2018-01-01

Interactive or Dynamic Geometry System (DGS) is a tool that help to teach and learn geometry using a computer-based interactive environment. Traditionally, the interaction with DGS is based on keyboard and mouse events where the functionalities are accessed using a menu of icons. Nevertheless, recent findings suggest that such a traditional model…

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.

a New Multi-Criteria Evaluation Model Based on the Combination of Non-Additive Fuzzy Ahp, Choquet Integral and Sugeno λ-MEASURE

NASA Astrophysics Data System (ADS)

Nadi, S.; Samiei, M.; Salari, H. R.; Karami, N.

2017-09-01

This paper proposes a new model for multi-criteria evaluation under uncertain condition. In this model we consider the interaction between criteria as one of the most challenging issues especially in the presence of uncertainty. In this case usual pairwise comparisons and weighted sum cannot be used to calculate the importance of criteria and to aggregate them. Our model is based on the combination of non-additive fuzzy linguistic preference relation AHP (FLPRAHP), Choquet integral and Sugeno λ-measure. The proposed model capture fuzzy preferences of users and fuzzy values of criteria and uses Sugeno λ -measure to determine the importance of criteria and their interaction. Then, integrating Choquet integral and FLPRAHP, all the interaction between criteria are taken in to account with least number of comparison and the final score for each alternative is determined. So we would model a comprehensive set of interactions between criteria that can lead us to more reliable result. An illustrative example presents the effectiveness and capability of the proposed model to evaluate different alternatives in a multi-criteria decision problem.

Physiologically Based Pharmacokinetic Modeling Suggests Limited Drug–Drug Interaction Between Clopidogrel and Dasabuvir

PubMed Central

Fu, W; Badri, P; Bow, DAJ; Fischer, V

2017-01-01

Dasabuvir, a nonnucleoside NS5B polymerase inhibitor, is a sensitive substrate of cytochrome P450 (CYP) 2C8 with a potential for drug–drug interaction (DDI) with clopidogrel. A physiologically based pharmacokinetic (PBPK) model was developed for dasabuvir to evaluate the DDI potential with clopidogrel, the acyl‐β‐D glucuronide metabolite of which has been reported as a strong mechanism‐based inhibitor of CYP2C8 based on an interaction with repaglinide. In addition, the PBPK model for clopidogrel and its metabolite were updated with additional in vitro data. Sensitivity analyses using these PBPK models suggested that CYP2C8 inhibition by clopidogrel acyl‐β‐D glucuronide may not be as potent as previously suggested. The dasabuvir and updated clopidogrel PBPK models predict a moderate increase of 1.5–1.9‐fold for Cmax and 1.9–2.8‐fold for AUC of dasabuvir when coadministered with clopidogrel. While the PBPK results suggest there is a potential for DDI between dasabuvir and clopidogrel, the magnitude is not expected to be clinically relevant. PMID:28411400

Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity.

PubMed

Li, Guanghui; Luo, Jiawei; Xiao, Qiu; Liang, Cheng; Ding, Pingjian

2018-05-12

Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases. Copyright © 2018. Published by Elsevier Inc.

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

PubMed

Dong, Xu; Foteinou, Panagiota T; Calvano, Steven E; Lowry, Stephen F; Androulakis, Ioannis P

2010-02-18

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

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.

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

PubMed

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

2018-04-26

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

Prediction of hot regions in protein-protein interaction by combining density-based incremental clustering with feature-based classification.

PubMed

Hu, Jing; Zhang, Xiaolong; Liu, Xiaoming; Tang, Jinshan

2015-06-01

Discovering hot regions in protein-protein interaction is important for drug and protein design, while experimental identification of hot regions is a time-consuming and labor-intensive effort; thus, the development of predictive models can be very helpful. In hot region prediction research, some models are based on structure information, and others are based on a protein interaction network. However, the prediction accuracy of these methods can still be improved. In this paper, a new method is proposed for hot region prediction, which combines density-based incremental clustering with feature-based classification. The method uses density-based incremental clustering to obtain rough hot regions, and uses feature-based classification to remove the non-hot spot residues from the rough hot regions. Experimental results show that the proposed method significantly improves the prediction performance of hot regions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integration of Dynamic Models in Range Operations

NASA Technical Reports Server (NTRS)

Bardina, Jorge; Thirumalainambi, Rajkumar

2004-01-01

This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.

DNS and modeling of the interaction between turbulent premixed flames and walls

NASA Technical Reports Server (NTRS)

Poinsot, T. J.; Haworth, D. C.

1992-01-01

The interaction between turbulent premixed flames and walls is studied using a two-dimensional full Navier-Stokes solver with simple chemistry. The effects of wall distance on the local and global flame structure are investigated. Quenching distances and maximum wall heat fluxes during quenching are computed in laminar cases and are found to be comparable to experimental and analytical results. For turbulent cases, it is shown that quenching distances and maximum heat fluxes remain of the same order as for laminar flames. Based on simulation results, a 'law-of-the-wall' model is derived to describe the interaction between a turbulent premixed flame and a wall. This model is constructed to provide reasonable behavior of flame surface density near a wall under the assumption that flame-wall interaction takes place at scales smaller than the computational mesh. It can be implemented in conjunction with any of several recent flamelet models based on a modeled surface density equation, with no additional constraints on mesh size or time step.

A Critical Look at Entropy-Based Gene-Gene Interaction Measures.

PubMed

Lee, Woojoo; Sjölander, Arvid; Pawitan, Yudi

2016-07-01

Several entropy-based measures for detecting gene-gene interaction have been proposed recently. It has been argued that the entropy-based measures are preferred because entropy can better capture the nonlinear relationships between genotypes and traits, so they can be useful to detect gene-gene interactions for complex diseases. These suggested measures look reasonable at intuitive level, but so far there has been no detailed characterization of the interactions captured by them. Here we study analytically the properties of some entropy-based measures for detecting gene-gene interactions in detail. The relationship between interactions captured by the entropy-based measures and those of logistic regression models is clarified. In general we find that the entropy-based measures can suffer from a lack of specificity in terms of target parameters, i.e., they can detect uninteresting signals as interactions. Numerical studies are carried out to confirm theoretical findings. © 2016 WILEY PERIODICALS, INC.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-01-01

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

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

PubMed

Froese, Tom; Iizuka, Hiroyuki; Ikegami, Takashi

2013-08-01

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

D Modelling and Interactive Web-Based Visualization of Cultural Heritage Objects

NASA Astrophysics Data System (ADS)

Koeva, M. N.

2016-06-01

Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria - a country with thousands of years of history and cultural heritage dating back to ancient civilizations. This motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage. In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1) image-based modelling using a non-metric hand-held camera; (2) 3D visualization based on spherical panoramic images; (3) and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This comparative study discusses the advantages and disadvantages of these three approaches and their integration in multiple domains, such as web-based 3D city modelling, tourism and architectural 3D visualization. It was concluded that image-based modelling and panoramic visualisation are simple, fast and effective techniques suitable for simultaneous virtual representation of many objects. However, additional measurements or CAD information will be beneficial for obtaining higher accuracy.

Introducing a model of pairing based on base pair specific interactions between identical DNA sequences

NASA Astrophysics Data System (ADS)

(O' Lee, Dominic J.

2018-02-01

At present, there have been suggested two types of physical mechanism that may facilitate preferential pairing between DNA molecules, with identical or similar base pair texts, without separation of base pairs. One mechanism solely relies on base pair specific patterns of helix distortion being the same on the two molecules, discussed extensively in the past. The other mechanism proposes that there are preferential interactions between base pairs of the same composition. We introduce a model, built on this second mechanism, where both thermal stretching and twisting fluctuations are included, as well as the base pair specific helix distortions. Firstly, we consider an approximation for weak pairing interactions, or short molecules. This yields a dependence of the energy on the square root of the molecular length, which could explain recent experimental data. However, analysis suggests that this approximation is no longer valid at large DNA lengths. In a second approximation, for long molecules, we define two adaptation lengths for twisting and stretching, over which the pairing interaction can limit the accumulation of helix disorder. When the pairing interaction is sufficiently strong, both adaptation lengths are finite; however, as we reduce pairing strength, the stretching adaptation length remains finite but the torsional one becomes infinite. This second state persists to arbitrarily weak values of the pairing strength; suggesting that, if the molecules are long enough, the pairing energy scales as length. To probe differences between the two pairing mechanisms, we also construct a model of similar form. However, now, pairing between identical sequences solely relies on the intrinsic helix distortion patterns. Between the two models, we see interesting qualitative differences. We discuss our findings, and suggest new work to distinguish between the two mechanisms.

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

PubMed Central

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

2016-01-01

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

Towards development of enhanced fully-Lagrangian mesh-free computational methods for fluid-structure interaction

NASA Astrophysics Data System (ADS)

Khayyer, Abbas; Gotoh, Hitoshi; Falahaty, Hosein; Shimizu, Yuma

2018-02-01

Simulation of incompressible fluid flow-elastic structure interactions is targeted by using fully-Lagrangian mesh-free computational methods. A projection-based fluid model (moving particle semi-implicit (MPS)) is coupled with either a Newtonian or a Hamiltonian Lagrangian structure model (MPS or HMPS) in a mathematically-physically consistent manner. The fluid model is founded on the solution of Navier-Stokes and continuity equations. The structure models are configured either in the framework of Newtonian mechanics on the basis of conservation of linear and angular momenta, or Hamiltonian mechanics on the basis of variational principle for incompressible elastodynamics. A set of enhanced schemes are incorporated for projection-based fluid model (Enhanced MPS), thus, the developed coupled solvers for fluid structure interaction (FSI) are referred to as Enhanced MPS-MPS and Enhanced MPS-HMPS. Besides, two smoothed particle hydrodynamics (SPH)-based FSI solvers, being developed by the authors, are considered and their potential applicability and comparable performance are briefly discussed in comparison with MPS-based FSI solvers. The SPH-based FSI solvers are established through coupling of projection-based incompressible SPH (ISPH) fluid model and SPH-based Newtonian/Hamiltonian structure models, leading to Enhanced ISPH-SPH and Enhanced ISPH-HSPH. A comparative study is carried out on the performances of the FSI solvers through a set of benchmark tests, including hydrostatic water column on an elastic plate, high speed impact of an elastic aluminum beam, hydroelastic slamming of a marine panel and dam break with elastic gate.

Estimating Colloidal Contact Model Parameters Using Quasi-Static Compression Simulations.

PubMed

Bürger, Vincent; Briesen, Heiko

2016-10-05

For colloidal particles interacting in suspensions, clusters, or gels, contact models should attempt to include all physical phenomena experimentally observed. One critical point when formulating a contact model is to ensure that the interaction parameters can be easily obtained from experiments. Experimental determinations of contact parameters for particles either are based on bulk measurements for simulations on the macroscopic scale or require elaborate setups for obtaining tangential parameters such as using atomic force microscopy. However, on the colloidal scale, a simple method is required to obtain all interaction parameters simultaneously. This work demonstrates that quasi-static compression of a fractal-like particle network provides all the necessary information to obtain particle interaction parameters using a simple spring-based contact model. These springs provide resistances against all degrees of freedom associated with two-particle interactions, and include critical forces or moments where such springs break, indicating a bond-breakage event. A position-based cost function is introduced to show the identifiability of the two-particle contact parameters, and a discrete, nonlinear, and non-gradient-based global optimization method (simplex with simulated annealing, SIMPSA) is used to minimize the cost function calculated from deviations of particle positions. Results show that, in principle, all necessary contact parameters for an arbitrary particle network can be identified, although numerical efficiency as well as experimental noise must be addressed when applying this method. Such an approach lays the groundwork for identifying particle-contact parameters from a position-based particle analysis for a colloidal system using just one experiment. Spring constants also directly influence the time step of the discrete-element method, and a detailed knowledge of all necessary interaction parameters will help to improve the efficiency of colloidal particle simulations.

A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

ERIC Educational Resources Information Center

Gu, X.; Blackmore, K. L.

2015-01-01

This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

Integrating Mathematical Modeling for Undergraduate Pre-Service Science Education Learning and Instruction in Middle School Classrooms

ERIC Educational Resources Information Center

Carrejo, David; Robertson, William H.

2011-01-01

Computer-based mathematical modeling in physics is a process of constructing models of concepts and the relationships between them in the scientific characteristics of work. In this manner, computer-based modeling integrates the interactions of natural phenomenon through the use of models, which provide structure for theories and a base for…

Fluid dynamic mechanisms and interactions within separated flows and their effects on missile aerodynamics

NASA Astrophysics Data System (ADS)

Addy, A. L.; Chow, W. L.; Korst, H. H.; White, R. A.

1983-05-01

Significant data and detailed results of a joint research effort investigating the fluid dynamic mechanisms and interactions within separated flows are presented. The results were obtained through analytical, experimental, and computational investigations of base flow related configurations. The research objectives focus on understanding the component mechanisms and interactions which establish and maintain separated flow regions. Flow models and theoretical analyses were developed to describe the base flowfield. The research approach has been to conduct extensive small-scale experiments on base flow configurations and to analyze these flows by component models and finite-difference techniques. The modeling of base flows of missiles (both powered and unpowered) for transonic and supersonic freestreams has been successful by component models. Research on plume effects and plume modeling indicated the need to match initial plume slope and plume surface curvature for valid wind tunnel simulation of an actual rocket plume. The assembly and development of a state-of-the-art laser Doppler velocimeter (LDV) system for experiments with two-dimensional small-scale models has been completed and detailed velocity and turbulence measurements are underway. The LDV experiments include the entire range of base flowfield mechanisms - shear layer development, recompression/reattachment, shock-induced separation, and plume-induced separation.

Leveraging Modeling Approaches: Reaction Networks and Rules

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatio-temporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks – the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks. PMID:22161349

Leveraging modeling approaches: reaction networks and rules.

PubMed

Blinov, Michael L; Moraru, Ion I

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high-resolution and/or high-throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks - the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.

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

PubMed

Zhu, Wei; Wang, Wei; Yuan, Gannan

2016-06-01

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

Integrative Approach for Computationally Inferring Interactions between the Alpha and Beta Subunits of the Calcium-Activated Potassium Channel (BK): a Docking Study

PubMed Central

González, Janneth; Gálvez, Angela; Morales, Ludis; Barreto, George E.; Capani, Francisco; Sierra, Omar; Torres, Yolima

2013-01-01

Three-dimensional models of the alpha- and beta-1 subunits of the calcium-activated potassium channel (BK) were predicted by threading modeling. A recursive approach comprising of sequence alignment and model building based on three templates was used to build these models, with the refinement of non-conserved regions carried out using threading techniques. The complex formed by the subunits was studied by means of docking techniques, using 3D models of the two subunits, and an approach based on rigid-body structures. Structural effects of the complex were analyzed with respect to hydrogen-bond interactions and binding-energy calculations. Potential interaction sites of the complex were determined by referencing a study of the difference accessible surface area (DASA) of the protein subunits in the complex. PMID:23492851

A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs.

PubMed

Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

2018-02-28

We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the $\\mathcal {E}$SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base-phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation.

Simulation of blood flow in deformable vessels using subject-specific geometry and spatially varying wall properties

PubMed Central

Xiong, Guanglei; Figueroa, C. Alberto; Xiao, Nan; Taylor, Charles A.

2011-01-01

SUMMARY Simulation of blood flow using image-based models and computational fluid dynamics has found widespread application to quantifying hemodynamic factors relevant to the initiation and progression of cardiovascular diseases and for planning interventions. Methods for creating subject-specific geometric models from medical imaging data have improved substantially in the last decade but for many problems, still require significant user interaction. In addition, while fluid–structure interaction methods are being employed to model blood flow and vessel wall dynamics, tissue properties are often assumed to be uniform. In this paper, we propose a novel workflow for simulating blood flow using subject-specific geometry and spatially varying wall properties. The geometric model construction is based on 3D segmentation and geometric processing. Variable wall properties are assigned to the model based on combining centerline-based and surface-based methods. We finally demonstrate these new methods using an idealized cylindrical model and two subject-specific vascular models with thoracic and cerebral aneurysms. PMID:21765984

POD Analysis of Jet-Plume/Afterbody-Wake Interaction

NASA Astrophysics Data System (ADS)

Murray, Nathan E.; Seiner, John M.; Jansen, Bernard J.; Gui, Lichuan; Sockwell, Shuan; Joachim, Matthew

2009-11-01

The understanding of the flow physics in the base region of a powered rocket is one of the keys to designing the next generation of reusable launchers. The base flow features affect the aerodynamics and the heat loading at the base of the vehicle. Recent efforts at the National Center for Physical Acoustics at the University of Mississippi have refurbished two models for studying jet-plume/afterbody-wake interactions in the NCPA's 1-foot Tri-Sonic Wind Tunnel Facility. Both models have a 2.5 inch outer diameter with a nominally 0.5 inch diameter centered exhaust nozzle. One of the models is capable of being powered with gaseous H2 and O2 to study the base flow in a fully combusting senario. The second model uses hi-pressure air to drive the exhaust providing an unheated representative flow field. This unheated model was used to acquire PIV data of the base flow. Subsequently, a POD analysis was performed to provide a first look at the large-scale structures present for the interaction between an axisymmetric jet and an axisymmetric afterbody wake. PIV and Schlieren data are presented for a single jet-exhaust to free-stream flow velocity along with the POD analysis of the base flow field.

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.

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

Teaching Sustainable and Integrated Resource Management Using an Interactive Nexus Model

ERIC Educational Resources Information Center

Bajzelj, Bojana; Fenner, Richard A.; Curmi, Elizabeth; Richards, Keith S.

2016-01-01

Purpose: The purpose of this paper was to enhance and complement teaching about resource system feedbacks and environmental modelling. Students were given an interactive exercise based on a research model (ForeseerTM), developed by an inter-disciplinary research team, that explores the interconnectivity of water, energy and land resources. Two…

Learning Tasks, Peer Interaction, and Cognition Process: An Online Collaborative Design Model

ERIC Educational Resources Information Center

Du, Jianxia; Durrington, Vance A.

2013-01-01

This paper illustrates a model for Online Group Collaborative Learning. The authors based the foundation of the Online Collaborative Design Model upon Piaget's concepts of assimilation and accommodation, and Vygotsky's theory of social interaction. The four components of online collaborative learning include: individual processes, the task(s)…

Microfluidic devices for modeling cell-cell and particle-cell interactions in the microvasculature

PubMed Central

Prabhakarpandian, Balabhaskar; Shen, Ming-Che; Pant, Kapil; Kiani, Mohammad F.

2011-01-01

Cell-fluid and cell-cell interactions are critical components of many physiological and pathological conditions in the microvasculature. Similarly, particle-cell interactions play an important role in targeted delivery of therapeutics to tissue. Development of in vitro fluidic devices to mimic these microcirculatory processes has been a critical step forward in our understanding of the inflammatory process, development of nano-particulate drug carriers, and developing realistic in vitro models of the microvasculature and its surrounding tissue. However, widely used parallel plate flow based devices and assays have a number of important limitations for studying the physiological conditions in vivo. In addition, these devices are resource hungry and time consuming for performing various assays. Recently developed, more realistic, microfluidic based devices have been able to overcome many of these limitations. In this review, an overview of the fluidic devices and their use in studying the effects of shear forces on cell-cell and cell-particle interactions is presented. In addition, use of mathematical models and Computational Fluid Dynamics (CFD) based models for interpreting the complex flow patterns in the microvasculature are highlighted. Finally, the potential of 3D microfluidic devices and imaging for better representing in vivo conditions under which cell-cell and cell-particle interactions take place are discussed. PMID:21763328

The interaction model of client health behavior: application to the study of community-based elders.

PubMed

Cox, C L

1986-10-01

The Interaction Model of Client Health Behavior (IMCHB) was used to direct a systematic and comprehensive description of community-based elders. The abstract concepts, constructs, factors, and variables described by one element of the model were able to account for 54% of the variance in elders' health status and 47% of the variance in their well-being. The model, as operationalized in this study, pointed to clear demographic, social, and health profiles that identified the elder at risk for decreased health, well-being, and self-care potential. The IMCHB would appear to be a useful framework with which to establish an empirical base on which nursing interventions could be developed.

Reconstruction of interaction rate in holographic dark energy

NASA Astrophysics Data System (ADS)

Mukherjee, Ankan

2016-11-01

The present work is based on the holographic dark energy model with Hubble horizon as the infrared cut-off. The interaction rate between dark energy and dark matter has been reconstructed for three different parameterizations of the deceleration parameter. Observational constraints on the model parameters have been obtained by maximum likelihood analysis using the observational Hubble parameter data (OHD), type Ia supernovab data (SNe), baryon acoustic oscillation data (BAO) and the distance prior of cosmic microwave background (CMB) namely the CMB shift parameter data (CMBShift). The interaction rate obtained in the present work remains always positive and increases with expansion. It is very similar to the result obtained by Sen and Pavon [1] where the interaction rate has been reconstructed for a parametrization of the dark energy equation of state. Tighter constraints on the interaction rate have been obtained in the present work as it is based on larger data sets. The nature of the dark energy equation of state parameter has also been studied for the present models. Though the reconstruction is done from different parametrizations, the overall nature of the interaction rate is very similar in all the cases. Different information criteria and the Bayesian evidence, which have been invoked in the context of model selection, show that the these models are at close proximity of each other.

Agent based models for wealth distribution with preference in interaction

NASA Astrophysics Data System (ADS)

Goswami, Sanchari; Sen, Parongama

2014-12-01

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

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

An Investigation into the Community of Inquiry Model in the Malaysian ESL Learners' Context

ERIC Educational Resources Information Center

Annamalai, Nagaletchimee

2017-01-01

Purpose: This study aims to explore how the Community of Inquiry (CoI) model (2000) is used to categorize students' and teachers' interactions in an asynchronous discussion and how these interactions are able to help students add quality to their narrative writing. Design/methodology/approach: The interactions were categorized based on teaching,…

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

NASA Astrophysics Data System (ADS)

Jain, Sankalp; Grandits, Melanie; Richter, Lars; Ecker, Gerhard F.

2017-06-01

The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

Influence of dipolar interactions on the superparamagnetic relaxation time of γ-Fe2O3

NASA Astrophysics Data System (ADS)

Labzour, A.; Housni, A.; Limame, K.; Essahlaoui, A.; Sayouri, S.

2017-03-01

Influence of dipolar interactions on the Néel superparamagnetic relaxation time, τ , of an assembly of ultrafine ferromagnetic particles (γ-Fe2O3 ) with uniaxial anisotropy and of different sizes has been widely studied using Mössbauer technique. These studies, based on different analytical approaches, have shown that τ decreases with increasing interactions between particles. To interpret these results, we propose a model where interaction effects are considered as being due to a constant and external randomly oriented magnetic field B(Ψ, ϕ). The model is based on the resolution of the Fokker-Planck equation (FPE), generalizes previous calculations and gives satisfactory interpretation of the relaxation phenomenon in such systems.

Topology-based modeling of intrinsically disordered proteins: balancing intrinsic folding and intermolecular interactions.

PubMed

Ganguly, Debabani; Chen, Jianhan

2011-04-01

Coupled binding and folding is frequently involved in specific recognition of so-called intrinsically disordered proteins (IDPs), a newly recognized class of proteins that rely on a lack of stable tertiary fold for function. Here, we exploit topology-based Gō-like modeling as an effective tool for the mechanism of IDP recognition within the theoretical framework of minimally frustrated energy landscape. Importantly, substantial differences exist between IDPs and globular proteins in both amino acid sequence and binding interface characteristics. We demonstrate that established Gō-like models designed for folded proteins tend to over-estimate the level of residual structures in unbound IDPs, whereas under-estimating the strength of intermolecular interactions. Such systematic biases have important consequences in the predicted mechanism of interaction. A strategy is proposed to recalibrate topology-derived models to balance intrinsic folding propensities and intermolecular interactions, based on experimental knowledge of the overall residual structure level and binding affinity. Applied to pKID/KIX, the calibrated Gō-like model predicts a dominant multistep sequential pathway for binding-induced folding of pKID that is initiated by KIX binding via the C-terminus in disordered conformations, followed by binding and folding of the rest of C-terminal helix and finally the N-terminal helix. This novel mechanism is consistent with key observations derived from a recent NMR titration and relaxation dispersion study and provides a molecular-level interpretation of kinetic rates derived from dispersion curve analysis. These case studies provide important insight into the applicability and potential pitfalls of topology-based modeling for studying IDP folding and interaction in general. Copyright © 2011 Wiley-Liss, Inc.

A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

PubMed Central

Zhang, Feng; Xu, Yuetong; Chou, Jarong

2016-01-01

The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples. PMID:27681730

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.

Stability of subsystem solutions in agent-based models

NASA Astrophysics Data System (ADS)

Perc, Matjaž

2018-01-01

The fact that relatively simple entities, such as particles or neurons, or even ants or bees or humans, give rise to fascinatingly complex behaviour when interacting in large numbers is the hallmark of complex systems science. Agent-based models are frequently employed for modelling and obtaining a predictive understanding of complex systems. Since the sheer number of equations that describe the behaviour of an entire agent-based model often makes it impossible to solve such models exactly, Monte Carlo simulation methods must be used for the analysis. However, unlike pairwise interactions among particles that typically govern solid-state physics systems, interactions among agents that describe systems in biology, sociology or the humanities often involve group interactions, and they also involve a larger number of possible states even for the most simplified description of reality. This begets the question: when can we be certain that an observed simulation outcome of an agent-based model is actually stable and valid in the large system-size limit? The latter is key for the correct determination of phase transitions between different stable solutions, and for the understanding of the underlying microscopic processes that led to these phase transitions. We show that a satisfactory answer can only be obtained by means of a complete stability analysis of subsystem solutions. A subsystem solution can be formed by any subset of all possible agent states. The winner between two subsystem solutions can be determined by the average moving direction of the invasion front that separates them, yet it is crucial that the competing subsystem solutions are characterised by a proper composition and spatiotemporal structure before the competition starts. We use the spatial public goods game with diverse tolerance as an example, but the approach has relevance for a wide variety of agent-based models.

Pilot Inventory Complex Adaptive System (PICAS): An Artificial Life Approach to Managing Pilot Retention.

DTIC Science & Technology

1999-03-01

mates) and base their behaviors on this interactive information. This alone defines the nature of a complex adaptive system and it is based on this...world policy initiatives. 2.3.4. User Interaction Building the model with extensive user interaction gives the entire system a more appealing feel...complex behavior that hopefully mimics trends observed in reality . User interaction also allows for easier justification of assumptions used within

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

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

West, J.T.; Murphy, J.

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

In Vitro Drug Interaction Modeling of Combinations of Azoles with Terbinafine against Clinical Scedosporium prolificans Isolates

PubMed Central

Meletiadis, Joseph; Mouton, Johan W.; Meis, Jacques F. G. M.; Verweij, Paul E.

2003-01-01

The in vitro interaction between terbinafine and the azoles voriconazole, miconazole, and itraconazole against five clinical Scedosporium prolificans isolates after 48 and 72 h of incubation was tested by a microdilution checkerboard (eight-by-twelve) technique. The antifungal effects of the drugs alone and in combination on the fungal biomass as well as on the metabolic activity of fungi were measured using a spectrophotometric method and two colorimetric methods, based on the lowest drug concentrations showed 75 and 50% growth inhibition (MIC-1 and MIC-2, respectively). The nature and the intensity of the interactions were assessed using a nonparametric approach (fractional inhibitory concentration [FIC] index model) and a fully parametric response surface approach (Greco model) of the Loewe additivity (LA) no-interaction theory as well as a nonparametric (Prichard model) and a semiparametric response surface approaches of the Bliss independence (BI) no-interaction theory. Statistically significant synergy was found between each of the three azoles and terbinafine in all cases, although with different intensities. A 27- to 64-fold and 16- to 90-fold reduction of the geometric mean of the azole and terbinafine MICs, respectively, was observed when they were combined, resulting in FIC indices of <1 to 0.02. Using the MIC-1 higher levels of synergy were obtained, , which were more consistent between the two incubation periods than using the MIC-2. The strongest synergy among the azoles was found with miconazole using the BI-based models and with voriconazole using the LA-based models. The synergistic effects both on fungal growth and metabolic activity were more potent after 72 h of incubation. Fully parametric approaches in combination with the modified colorimetric method might prove useful for testing the in vitro interaction of antifungal drugs against filamentous fungi. PMID:12499177

Comparing the Discrete and Continuous Logistic Models

ERIC Educational Resources Information Center

Gordon, Sheldon P.

2008-01-01

The solutions of the discrete logistic growth model based on a difference equation and the continuous logistic growth model based on a differential equation are compared and contrasted. The investigation is conducted using a dynamic interactive spreadsheet. (Contains 5 figures.)

Which model based on fluorescence quenching is suitable to study the interaction between trans-resveratrol and BSA?

NASA Astrophysics Data System (ADS)

Wei, Xin Lin; Xiao, Jian Bo; Wang, Yuanfeng; Bai, Yalong

2010-01-01

There are several models by means of quenching fluorescence of BSA to determine the binding parameters. The binding parameters obtained from different models are quite different from each other. Which model is suitable to study the interaction between trans-resveratrol and BSA? Herein, twelve models based fluorescence quenching of BSA were compared. The number of binding sites increasing with increased binding constant for similar compounds binding to BSA maybe one approach to resolve this question. For example, here eleven flavonoids were tested to illustrate that the double logarithm regression curve is suitable to study binding polyphenols to BSA.

Seldon v.3.0

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

Berry, Nina; Ko, Teresa; Shneider, Max

Seldon is an agent-based social simulation framework that uniquely integrates concepts from a variety of different research areas including psychology, social science, and agent-based modeling. Development has been taking place for a number of years, previously focusing on gang and terrorist recruitment. The toolkit consists of simple agents (individuals) and abstract agents (groups of individuals representing social/institutional concepts) that interact according to exchangeable rule sets (i.e. linear attraction, linear reinforcement). Each agent has a set of customizable attributes that get modified during the interactions. Interactions create relationships between agents, and each agent has a maximum amount of relationship energy thatmore » it can expend. As relationships evolve, they form multiple levels of social networks (i.e. acquaintances, friends, cliques) that in turn drive future interactions. Agents can also interact randomly if they are not connected through a network, mimicking the chance interactions that real people have in everyday life. We are currently integrating Seldon with the cognitive framework (also developed at Sandia). Each individual agent has a lightweight cognitive model that is created automatically from textual sources. Cognitive information is exchanged during interactions, and can also be injected into a running simulation. The entire framework has been parallelized to allow for larger simulations in an HPC environment. We have also added more detail to the agents themselves (a"Big Five" personality model) and their interactions (an enhanced relationship model) for a more realistic representation.« less

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.

Brief Report: Effects of Video-Based Group Instruction on Spontaneous Social Interaction of Adolescents with Autism Spectrum Disorders.

PubMed

Plavnick, Joshua B; Dueñas, Ana D

2018-06-01

Four adolescents with autism spectrum disorder (ASD) were taught to interact with peers by asking social questions or commenting about others during game play or group activities. Participants were shown a video model and then given an opportunity to perform the social behavior depicted in the model when playing a game with one another. All participants demonstrated an increase in both social interaction skills, replicating previous research on video-based group instruction for adolescents with ASD. The results suggest the procedure may be useful for teaching social skills that occur under natural conditions.

HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy.

PubMed

Hu, Huan; Zhang, Li; Ai, Haixin; Zhang, Hui; Fan, Yetian; Zhao, Qi; Liu, Hongsheng

2018-03-27

LncRNA plays an important role in many biological and disease progression by binding to related proteins. However, the experimental methods for studying lncRNA-protein interactions are time-consuming and expensive. Although there are a few models designed to predict the interactions of ncRNA-protein, they all have some common drawbacks that limit their predictive performance. In this study, we present a model called HLPI-Ensemble designed specifically for human lncRNA-protein interactions. HLPI-Ensemble adopts the ensemble strategy based on three mainstream machine learning algorithms of Support Vector Machines (SVM), Random Forests (RF) and Extreme Gradient Boosting (XGB) to generate HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble, respectively. The results of 10-fold cross-validation show that HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble achieved AUCs of 0.95, 0.96 and 0.96, respectively, in the test dataset. Furthermore, we compared the performance of the HLPI-Ensemble models with the previous models through external validation dataset. The results show that the false positives (FPs) of HLPI-Ensemble models are much lower than that of the previous models, and other evaluation indicators of HLPI-Ensemble models are also higher than those of the previous models. It is further showed that HLPI-Ensemble models are superior in predicting human lncRNA-protein interaction compared with previous models. The HLPI-Ensemble is publicly available at: http://ccsipb.lnu.edu.cn/hlpiensemble/ .

Model for an RNA tertiary interaction from the structure of an intermolecular complex between a GAAA tetraloop and an RNA helix.

PubMed

Pley, H W; Flaherty, K M; McKay, D B

1994-11-03

In large structured RNAs, RNA hairpins in which the strands of the duplex stem are connected by a tetraloop of the consensus sequence 5'-GNRA (where N is any nucleotide, and R is either G or A) are unusually frequent. In group I introns there is a covariation in sequence between nucleotides in the third and fourth positions of the loop with specific distant base pairs in putative RNA duplex stems: GNAA loops correlate with successive 5'-C-C.G-C base pairs in stems, whereas GNGA loops correlate with 5'-C-U.G-A. This has led to the suggestion that GNRA tetraloops may be involved in specific long-range tertiary interactions, with each A in position 3 or 4 of the loop interacting with a C-G base pair in the duplex, and G in position 3 interacting with a U-A base pair. This idea is supported experimentally for the GAAA loop of the P5b extension of the group I intron of Tetrahymena thermophila and the L9 GUGA terminal loop of the td intron of bacteriophage T4 (ref. 4). NMR has revealed the overall structure of the tetraloop for 12-nucleotide hairpins with GCAA and GAAA loops and models have been proposed for the interaction of GNRA tetraloops with base pairs in the minor groove of A-form RNA. Here we describe the crystal structure of an intermolecular complex between a GAAA tetraloop and an RNA helix. The interactions we observe correlate with the specificity of GNRA tetraloops inferred from phylogenetic studies, suggesting that this complex is a legitimate model for intramolecular tertiary interactions mediated by GNRA tetraloops in large structured RNAs.

Two-character motion analysis and synthesis.

PubMed

Kwon, Taesoo; Cho, Young-Sang; Park, Sang Il; Shin, Sung Yong

2008-01-01

In this paper, we deal with the problem of synthesizing novel motions of standing-up martial arts such as Kickboxing, Karate, and Taekwondo performed by a pair of human-like characters while reflecting their interactions. Adopting an example-based paradigm, we address three non-trivial issues embedded in this problem: motion modeling, interaction modeling, and motion synthesis. For the first issue, we present a semi-automatic motion labeling scheme based on force-based motion segmentation and learning-based action classification. We also construct a pair of motion transition graphs each of which represents an individual motion stream. For the second issue, we propose a scheme for capturing the interactions between two players. A dynamic Bayesian network is adopted to build a motion transition model on top of the coupled motion transition graph that is constructed from an example motion stream. For the last issue, we provide a scheme for synthesizing a novel sequence of coupled motions, guided by the motion transition model. Although the focus of the present work is on martial arts, we believe that the framework of the proposed approach can be conveyed to other two-player motions as well.

An individual-based modeling approach to simulate the effects of cellular nutrient competition on Escherichia coli K-12 MG1655 colony behavior and interactions in aerobic structured food systems.

PubMed

Tack, Ignace L M M; Logist, Filip; Noriega Fernández, Estefanía; Van Impe, Jan F M

2015-02-01

Traditional kinetic models in predictive microbiology reliably predict macroscopic dynamics of planktonically-growing cell cultures in homogeneous liquid food systems. However, most food products have a semi-solid structure, where microorganisms grow locally in colonies. Individual colony cells exhibit strongly different and non-normally distributed behavior due to local nutrient competition. As a result, traditional models considering average population behavior in a homogeneous system do not describe colony dynamics in full detail. To incorporate local resource competition and individual cell differences, an individual-based modeling approach has been applied to Escherichia coli K-12 MG1655 colonies, considering the microbial cell as modeling unit. The first contribution of this individual-based model is to describe single colony growth under nutrient-deprived conditions. More specifically, the linear and stationary phase in the evolution of the colony radius, the evolution from a disk-like to branching morphology, and the emergence of a starvation zone in the colony center are simulated and compared to available experimental data. These phenomena occur earlier at more severe nutrient depletion conditions, i.e., at lower nutrient diffusivity and initial nutrient concentration in the medium. Furthermore, intercolony interactions have been simulated. Higher inoculum densities lead to stronger intercolony interactions, such as colony merging and smaller colony sizes, due to nutrient competition. This individual-based model contributes to the elucidation of characteristic experimentally observed colony behavior from mechanistic information about cellular physiology and interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ecological covariates based predictive model of malaria risk in the state of Chhattisgarh, India.

PubMed

Kumar, Rajesh; Dash, Chinmaya; Rani, Khushbu

2017-09-01

Malaria being an endemic disease in the state of Chhattisgarh and ecologically dependent mosquito-borne disease, the study is intended to identify the ecological covariates of malaria risk in districts of the state and to build a suitable predictive model based on those predictors which could assist developing a weather based early warning system. This secondary data based analysis used one month lagged district level malaria positive cases as response variable and ecological covariates as independent variables which were tested with fixed effect panelled negative binomial regression models. Interactions among the covariates were explored using two way factorial interaction in the model. Although malaria risk in the state possesses perennial characteristics, higher parasitic incidence was observed during the rainy and winter seasons. The univariate analysis indicated that the malaria incidence risk was statistically significant associated with rainfall, maximum humidity, minimum temperature, wind speed, and forest cover ( p  < 0.05). The efficient predictive model include the forest cover [IRR-1.033 (1.024-1.042)], maximum humidity [IRR-1.016 (1.013-1.018)], and two-way factorial interactions between district specific averaged monthly minimum temperature and monthly minimum temperature, monthly minimum temperature was statistically significant [IRR-1.44 (1.231-1.695)] whereas the interaction term has a protective effect [IRR-0.982 (0.974-0.990)] against malaria infections. Forest cover, maximum humidity, minimum temperature and wind speed emerged as potential covariates to be used in predictive models for modelling the malaria risk in the state which could be efficiently used for early warning systems in the state.

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

Detection of time delays and directional interactions based on time series from complex dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

2017-07-01

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

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.

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.

KASCADE-Grande energy reconstruction based on the lateral density distribution using the QGSJet-II.04 interaction model

NASA Astrophysics Data System (ADS)

Gherghel-Lascu, A.; Apel, W. D.; Arteaga-Velázquez, J. C.; Bekk, K.; Bertania, M.; Blümer, J.; Bozdog, H.; Brancus, I. M.; Cantoni, E.; Chiavassa, A.; Cossavella, F.; Daumiller, K.; de Souza, V.; Di Pierro, F.; Doll, P.; Engel, R.; Fuhrmann, D.; Gils, H. J.; Glasstetter, R.; Grupen, C.; Haungs, A.; Heck, D.; Hörandel, J. R.; Huber, D.; Huege, T.; Kampert, K.-H.; Kang, D.; Klages, H. O.; Link, K.; Łuczak, P.; Mathes, H. J.; Mayer, H. J.; Milke, J.; Mitrica, B.; Morello, C.; Oehlschläger, J.; Ostapchenko, S.; Palmieri, N.; Pierog, T.; Rebel, H.; Roth, M.; Schieler, H.; Schoo, S.; Schröder, F. G.; Sima, O.; Toma, G.; Trinchero, G. C.; Ulrich, H.; Weindl, A.; Wochele, J.; Zabierowski, J.

2017-06-01

The charged particle densities obtained from CORSIKA simulated EAS, using the QGSJet-II.04 hadronic interaction model are used for primary energy reconstruction. Simulated data are reconstructed by using Lateral Energy Correction Functions computed with a new realistic model of the Grande stations implemented in Geant4.10.

How interactions between animal movement and landscape processes modify range dynamics and extinction risk

EPA Science Inventory

Range dynamics models now incorporate many of the mechanisms and interactions that drive species distributions. However, connectivity continues to be studied using overly simple distance-based dispersal models with little consideration of how the individual behavior of dispersin...

Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

NASA Astrophysics Data System (ADS)

Murphy, James T.; Walshe, Ray; Devocelle, Marc

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

Human-machine interactions

DOEpatents

Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM

2009-04-28

Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.

Evaluation of HardSys/HardDraw, An Expert System for Electromagnetic Interactions Modelling

DTIC Science & Technology

1993-05-01

interactions ir complex systems. This report gives a description of HardSys/HardDraw and reviews the main concepts used in its design. Various aspects of its ...HardDraw, an expert system for the modelling of electromagnetic interactions in complex systems. It consists of two main components: HardSys and HardDraw...HardSys is the advisor part of the expert system. It is knowledge-based, that is it contains a database of models and properties for various types of

Improving 3D Genome Reconstructions Using Orthologous and Functional Constraints

PubMed Central

Diament, Alon; Tuller, Tamir

2015-01-01

The study of the 3D architecture of chromosomes has been advancing rapidly in recent years. While a number of methods for 3D reconstruction of genomic models based on Hi-C data were proposed, most of the analyses in the field have been performed on different 3D representation forms (such as graphs). Here, we reproduce most of the previous results on the 3D genomic organization of the eukaryote Saccharomyces cerevisiae using analysis of 3D reconstructions. We show that many of these results can be reproduced in sparse reconstructions, generated from a small fraction of the experimental data (5% of the data), and study the properties of such models. Finally, we propose for the first time a novel approach for improving the accuracy of 3D reconstructions by introducing additional predicted physical interactions to the model, based on orthologous interactions in an evolutionary-related organism and based on predicted functional interactions between genes. We demonstrate that this approach indeed leads to the reconstruction of improved models. PMID:26000633

Network community-based model reduction for vortical flows

NASA Astrophysics Data System (ADS)

Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya G.; Taira, Kunihiko

2018-06-01

A network community-based reduced-order model is developed to capture key interactions among coherent structures in high-dimensional unsteady vortical flows. The present approach is data-inspired and founded on network-theoretic techniques to identify important vortical communities that are comprised of vortical elements that share similar dynamical behavior. The overall interaction-based physics of the high-dimensional flow field is distilled into the vortical community centroids, considerably reducing the system dimension. Taking advantage of these vortical interactions, the proposed methodology is applied to formulate reduced-order models for the inter-community dynamics of vortical flows, and predict lift and drag forces on bodies in wake flows. We demonstrate the capabilities of these models by accurately capturing the macroscopic dynamics of a collection of discrete point vortices, and the complex unsteady aerodynamic forces on a circular cylinder and an airfoil with a Gurney flap. The present formulation is found to be robust against simulated experimental noise and turbulence due to its integrating nature of the system reduction.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

PubMed

Deodhar, Suruchi; Bisset, Keith R; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V

2014-07-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology

PubMed Central

Deodhar, Suruchi; Bisset, Keith R.; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V.

2014-01-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity. PMID:25530914

Variance-based interaction index measuring heteroscedasticity

NASA Astrophysics Data System (ADS)

Ito, Keiichi; Couckuyt, Ivo; Poles, Silvia; Dhaene, Tom

2016-06-01

This work is motivated by the need to deal with models with high-dimensional input spaces of real variables. One way to tackle high-dimensional problems is to identify interaction or non-interaction among input parameters. We propose a new variance-based sensitivity interaction index that can detect and quantify interactions among the input variables of mathematical functions and computer simulations. The computation is very similar to first-order sensitivity indices by Sobol'. The proposed interaction index can quantify the relative importance of input variables in interaction. Furthermore, detection of non-interaction for screening can be done with as low as 4 n + 2 function evaluations, where n is the number of input variables. Using the interaction indices based on heteroscedasticity, the original function may be decomposed into a set of lower dimensional functions which may then be analyzed separately.

A model of urban scaling laws based on distance dependent interactions

NASA Astrophysics Data System (ADS)

Ribeiro, Fabiano L.; Meirelles, Joao; Ferreira, Fernando F.; Neto, Camilo Rodrigues

2017-03-01

Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log-log plot, the so-called superlinear scaling. Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences.

A model of urban scaling laws based on distance dependent interactions.

PubMed

Ribeiro, Fabiano L; Meirelles, Joao; Ferreira, Fernando F; Neto, Camilo Rodrigues

2017-03-01

Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log-log plot, the so-called superlinear scaling . Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences.

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.

Study of the 190Hg Nucleus: Testing the Existence of U(5) Symmetry

NASA Astrophysics Data System (ADS)

Jahangiri Tazekand, Z.; Mohseni, M.; Mohammadi, M. A.; Sabri, H.

2018-06-01

In this paper, we have considered the energy spectra, quadrupole transition probabilities, energy surface, charge radii, and quadrupole moment of the190Hg nucleus to describe the interplay between phase transitions and configuration mixing of intruder excitations. To this aim, we have used four different formalisms: (i) interacting boson model including configuration mixing, (ii) Z(5) critical symmetry, (iii) U(6)-based transitional Hamiltonian, and (iv) a transitional interacting boson model Hamiltonian in both interacting boson model (IBM)-1 and IBM-2 versions which are based on affine \\widehat{SU(1,1)} Lie algebra. Results show the advantages of configuration mixing and transitional Hamiltonians, in particular IBM-2 formalism, to reproduce the experimental counterparts when the weight of spherical symmetry increased.

Asymmetric Evolutionary Games.

PubMed

McAvoy, Alex; Hauert, Christoph

2015-08-01

Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner's Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games.

Prediction of Ras-effector interactions using position energy matrices.

PubMed

Kiel, Christina; Serrano, Luis

2007-09-01

One of the more challenging problems in biology is to determine the cellular protein interaction network. Progress has been made to predict protein-protein interactions based on structural information, assuming that structural similar proteins interact in a similar way. In a previous publication, we have determined a genome-wide Ras-effector interaction network based on homology models, with a high accuracy of predicting binding and non-binding domains. However, for a prediction on a genome-wide scale, homology modelling is a time-consuming process. Therefore, we here successfully developed a faster method using position energy matrices, where based on different Ras-effector X-ray template structures, all amino acids in the effector binding domain are sequentially mutated to all other amino acid residues and the effect on binding energy is calculated. Those pre-calculated matrices can then be used to score for binding any Ras or effector sequences. Based on position energy matrices, the sequences of putative Ras-binding domains can be scanned quickly to calculate an energy sum value. By calibrating energy sum values using quantitative experimental binding data, thresholds can be defined and thus non-binding domains can be excluded quickly. Sequences which have energy sum values above this threshold are considered to be potential binding domains, and could be further analysed using homology modelling. This prediction method could be applied to other protein families sharing conserved interaction types, in order to determine in a fast way large scale cellular protein interaction networks. Thus, it could have an important impact on future in silico structural genomics approaches, in particular with regard to increasing structural proteomics efforts, aiming to determine all possible domain folds and interaction types. All matrices are deposited in the ADAN database (http://adan-embl.ibmc.umh.es/). Supplementary data are available at Bioinformatics online.

Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold

PubMed Central

Huber, Roland G.; Bond, Peter J.

2017-01-01

An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge) are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners. PMID:29016650

Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold.

PubMed

Ivanov, Stefan M; Cawley, Andrew; Huber, Roland G; Bond, Peter J; Warwicker, Jim

2017-01-01

An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge) are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners.

Systematic analysis of Ca2+ homeostasis in Saccharomyces cerevisiae based on chemical-genetic interaction profiles

PubMed Central

Ghanegolmohammadi, Farzan; Yoshida, Mitsunori; Ohnuki, Shinsuke; Sukegawa, Yuko; Okada, Hiroki; Obara, Keisuke; Kihara, Akio; Suzuki, Kuninori; Kojima, Tetsuya; Yachie, Nozomu; Hirata, Dai; Ohya, Yoshikazu

2017-01-01

We investigated the global landscape of Ca2+ homeostasis in budding yeast based on high-dimensional chemical-genetic interaction profiles. The morphological responses of 62 Ca2+-sensitive (cls) mutants were quantitatively analyzed with the image processing program CalMorph after exposure to a high concentration of Ca2+. After a generalized linear model was applied, an analysis of covariance model was used to detect significant Ca2+–cls interactions. We found that high-dimensional, morphological Ca2+–cls interactions were mixed with positive (86%) and negative (14%) chemical-genetic interactions, whereas one-dimensional fitness Ca2+–cls interactions were all negative in principle. Clustering analysis with the interaction profiles revealed nine distinct gene groups, six of which were functionally associated. In addition, characterization of Ca2+–cls interactions revealed that morphology-based negative interactions are unique signatures of sensitized cellular processes and pathways. Principal component analysis was used to discriminate between suppression and enhancement of the Ca2+-sensitive phenotypes triggered by inactivation of calcineurin, a Ca2+-dependent phosphatase. Finally, similarity of the interaction profiles was used to reveal a connected network among the Ca2+ homeostasis units acting in different cellular compartments. Our analyses of high-dimensional chemical-genetic interaction profiles provide novel insights into the intracellular network of yeast Ca2+ homeostasis. PMID:28566553

A Gas-Surface Interaction Model based on Accelerated Reactive Molecular Dynamics for Hypersonic Conditions including Thermal Conduction

DTIC Science & Technology

2012-02-28

Interaction Model based on Accelerated Reactive Molecular Dynamics for Hypersonic conditions including Thermal Conduction FA9550-09-1-0157 Schwartzentruber...Dynamics for Hypersonic Conditions including Thermal Conduction Grant/Contract Number: FA9550-09-1-0157 Program Manager: Dr. John Schmisseur PI...through the boundary layer and may chemically react with the vehicle’s thermal protection system (TPS). Many TPS materials act as a catalyst for the

Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

PubMed Central

Sun, Baoliang; Jiang, Chunlan; Li, Ming

2016-01-01

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs. PMID:27809271

Fashion sketch design by interactive genetic algorithms

NASA Astrophysics Data System (ADS)

Mok, P. Y.; Wang, X. X.; Xu, J.; Kwok, Y. L.

2012-11-01

Computer aided design is vitally important for the modern industry, particularly for the creative industry. Fashion industry faced intensive challenges to shorten the product development process. In this paper, a methodology is proposed for sketch design based on interactive genetic algorithms. The sketch design system consists of a sketch design model, a database and a multi-stage sketch design engine. First, a sketch design model is developed based on the knowledge of fashion design to describe fashion product characteristics by using parameters. Second, a database is built based on the proposed sketch design model to define general style elements. Third, a multi-stage sketch design engine is used to construct the design. Moreover, an interactive genetic algorithm (IGA) is used to accelerate the sketch design process. The experimental results have demonstrated that the proposed method is effective in helping laypersons achieve satisfied fashion design sketches.

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

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

Dmitrasinovic, V.

2005-05-01

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

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

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

Jeffrey D. Evanseck; Jeffry D. Madura

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

Monte Carlo calculations of positron emitter yields in proton radiotherapy.

PubMed

Seravalli, E; Robert, C; Bauer, J; Stichelbaut, F; Kurz, C; Smeets, J; Van Ngoc Ty, C; Schaart, D R; Buvat, I; Parodi, K; Verhaegen, F

2012-03-21

Positron emission tomography (PET) is a promising tool for monitoring the three-dimensional dose distribution in charged particle radiotherapy. PET imaging during or shortly after proton treatment is based on the detection of annihilation photons following the ß(+)-decay of radionuclides resulting from nuclear reactions in the irradiated tissue. Therapy monitoring is achieved by comparing the measured spatial distribution of irradiation-induced ß(+)-activity with the predicted distribution based on the treatment plan. The accuracy of the calculated distribution depends on the correctness of the computational models, implemented in the employed Monte Carlo (MC) codes that describe the interactions of the charged particle beam with matter and the production of radionuclides and secondary particles. However, no well-established theoretical models exist for predicting the nuclear interactions and so phenomenological models are typically used based on parameters derived from experimental data. Unfortunately, the experimental data presently available are insufficient to validate such phenomenological hadronic interaction models. Hence, a comparison among the models used by the different MC packages is desirable. In this work, starting from a common geometry, we compare the performances of MCNPX, GATE and PHITS MC codes in predicting the amount and spatial distribution of proton-induced activity, at therapeutic energies, to the already experimentally validated PET modelling based on the FLUKA MC code. In particular, we show how the amount of ß(+)-emitters produced in tissue-like media depends on the physics model and cross-sectional data used to describe the proton nuclear interactions, thus calling for future experimental campaigns aiming at supporting improvements of MC modelling for clinical application of PET monitoring. © 2012 Institute of Physics and Engineering in Medicine

ANNIE - INTERACTIVE PROCESSING OF DATA BASES FOR HYDROLOGIC MODELS.

USGS Publications Warehouse

Lumb, Alan M.; Kittle, John L.

1985-01-01

ANNIE is a data storage and retrieval system that was developed to reduce the time and effort required to calibrate, verify, and apply watershed models that continuously simulate water quantity and quality. Watershed models have three categories of input: parameters to describe segments of a drainage area, linkage of the segments, and time-series data. Additional goals for ANNIE include the development of software that is easily implemented on minicomputers and some microcomputers and software that has no special requirements for interactive display terminals. Another goal is for the user interaction to be based on the experience of the user so that ANNIE is helpful to the inexperienced user and yet efficient and brief for the experienced user. Finally, the code should be designed so that additional hydrologic models can easily be added to ANNIE.

Analytical theory of polymer-network-mediated interaction between colloidal particles

PubMed Central

Di Michele, Lorenzo; Zaccone, Alessio; Eiser, Erika

2012-01-01

Nanostructured materials based on colloidal particles embedded in a polymer network are used in a variety of applications ranging from nanocomposite rubbers to organic-inorganic hybrid solar cells. Further, polymer-network-mediated colloidal interactions are highly relevant to biological studies whereby polymer hydrogels are commonly employed to probe the mechanical response of living cells, which can determine their biological function in physiological environments. The performance of nanomaterials crucially relies upon the spatial organization of the colloidal particles within the polymer network that depends, in turn, on the effective interactions between the particles in the medium. Existing models based on nonlocal equilibrium thermodynamics fail to clarify the nature of these interactions, precluding the way toward the rational design of polymer-composite materials. In this article, we present a predictive analytical theory of these interactions based on a coarse-grained model for polymer networks. We apply the theory to the case of colloids partially embedded in cross-linked polymer substrates and clarify the origin of attractive interactions recently observed experimentally. Monte Carlo simulation results that quantitatively confirm the theoretical predictions are also presented. PMID:22679289

CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2015-12-01

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

Finite element method (FEM) model of the mechanical stress on phospholipid membranes from shock waves produced in nanosecond electric pulses (nsEP)

NASA Astrophysics Data System (ADS)

Barnes, Ronald; Roth, Caleb C.; Shadaram, Mehdi; Beier, Hope; Ibey, Bennett L.

2015-03-01

The underlying mechanism(s) responsible for nanoporation of phospholipid membranes by nanosecond pulsed electric fields (nsEP) remains unknown. The passage of a high electric field through a conductive medium creates two primary contributing factors that may induce poration: the electric field interaction at the membrane and the shockwave produced from electrostriction of a polar submersion medium exposed to an electric field. Previous work has focused on the electric field interaction at the cell membrane, through such models as the transport lattice method. Our objective is to model the shock wave cell membrane interaction induced from the density perturbation formed at the rising edge of a high voltage pulse in a polar liquid resulting in a shock wave propagating away from the electrode toward the cell membrane. Utilizing previous data from cell membrane mechanical parameters, and nsEP generated shockwave parameters, an acoustic shock wave model based on the Helmholtz equation for sound pressure was developed and coupled to a cell membrane model with finite-element modeling in COMSOL. The acoustic structure interaction model was developed to illustrate the harmonic membrane displacements and stresses resulting from shockwave and membrane interaction based on Hooke's law. Poration is predicted by utilizing membrane mechanical breakdown parameters including cortical stress limits and hydrostatic pressure gradients.

Polaron mobility obtained by a variational approach for lattice Fröhlich models

NASA Astrophysics Data System (ADS)

Kornjača, Milan; Vukmirović, Nenad

2018-04-01

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

Wave–turbulence interaction-induced vertical mixing and its effects in ocean and climate models

PubMed Central

Qiao, Fangli; Yuan, Yeli; Deng, Jia; Dai, Dejun; Song, Zhenya

2016-01-01

Heated from above, the oceans are stably stratified. Therefore, the performance of general ocean circulation models and climate studies through coupled atmosphere–ocean models depends critically on vertical mixing of energy and momentum in the water column. Many of the traditional general circulation models are based on total kinetic energy (TKE), in which the roles of waves are averaged out. Although theoretical calculations suggest that waves could greatly enhance coexisting turbulence, no field measurements on turbulence have ever validated this mechanism directly. To address this problem, a specially designed field experiment has been conducted. The experimental results indicate that the wave–turbulence interaction-induced enhancement of the background turbulence is indeed the predominant mechanism for turbulence generation and enhancement. Based on this understanding, we propose a new parametrization for vertical mixing as an additive part to the traditional TKE approach. This new result reconfirmed the past theoretical model that had been tested and validated in numerical model experiments and field observations. It firmly establishes the critical role of wave–turbulence interaction effects in both general ocean circulation models and atmosphere–ocean coupled models, which could greatly improve the understanding of the sea surface temperature and water column properties distributions, and hence model-based climate forecasting capability. PMID:26953182

A utility-based design for randomized comparative trials with ordinal outcomes and prognostic subgroups.

PubMed

Murray, Thomas A; Yuan, Ying; Thall, Peter F; Elizondo, Joan H; Hofstetter, Wayne L

2018-01-22

A design is proposed for randomized comparative trials with ordinal outcomes and prognostic subgroups. The design accounts for patient heterogeneity by allowing possibly different comparative conclusions within subgroups. The comparative testing criterion is based on utilities for the levels of the ordinal outcome and a Bayesian probability model. Designs based on two alternative models that include treatment-subgroup interactions are considered, the proportional odds model and a non-proportional odds model with a hierarchical prior that shrinks toward the proportional odds model. A third design that assumes homogeneity and ignores possible treatment-subgroup interactions also is considered. The three approaches are applied to construct group sequential designs for a trial of nutritional prehabilitation versus standard of care for esophageal cancer patients undergoing chemoradiation and surgery, including both untreated patients and salvage patients whose disease has recurred following previous therapy. A simulation study is presented that compares the three designs, including evaluation of within-subgroup type I and II error probabilities under a variety of scenarios including different combinations of treatment-subgroup interactions. © 2018, The International Biometric Society.

Gaussian approximation potential modeling of lithium intercalation in carbon nanostructures

NASA Astrophysics Data System (ADS)

Fujikake, So; Deringer, Volker L.; Lee, Tae Hoon; Krynski, Marcin; Elliott, Stephen R.; Csányi, Gábor

2018-06-01

We demonstrate how machine-learning based interatomic potentials can be used to model guest atoms in host structures. Specifically, we generate Gaussian approximation potential (GAP) models for the interaction of lithium atoms with graphene, graphite, and disordered carbon nanostructures, based on reference density functional theory data. Rather than treating the full Li-C system, we demonstrate how the energy and force differences arising from Li intercalation can be modeled and then added to a (prexisting and unmodified) GAP model of pure elemental carbon. Furthermore, we show the benefit of using an explicit pair potential fit to capture "effective" Li-Li interactions and to improve the performance of the GAP model. This provides proof-of-concept for modeling guest atoms in host frameworks with machine-learning based potentials and in the longer run is promising for carrying out detailed atomistic studies of battery materials.

VISUALIZATION-BASED ANALYSIS FOR A MIXED-INHIBITION BINARY PBPK MODEL: DETERMINATION OF INHIBITION MECHANISM

EPA Science Inventory

A physiologically-based pharmacokinetic (PBPK) model incorporating mixed enzyme inhibition was used to determine the mechanism of metabolic interactions occurring during simultaneous exposures to the organic solvents chloroform and trichloroethylene (TCE). Visualization-based se...

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.

Digital Immersive Virtual Environments and Instructional Computing

ERIC Educational Resources Information Center

Blascovich, Jim; Beall, Andrew C.

2010-01-01

This article reviews theory and research relevant to the development of digital immersive virtual environment-based instructional computing systems. The review is organized within the context of a multidimensional model of social influence and interaction within virtual environments that models the interaction of four theoretical factors: theory…

Analyses of track shift under high-speed vehicle-track interaction : safety of high speed ground transportation systems

DOT National Transportation Integrated Search

1997-06-01

This report describes analysis tools to predict shift under high-speed vehicle- : track interaction. The analysis approach is based on two fundamental models : developed (as part of this research); the first model computes the track lateral : residua...

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

PubMed Central

Peetla, Chiranjeevi; Stine, Andrew; Labhasetwar, Vinod

2009-01-01

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

A protein domain-based interactome network for C. elegans early embryogenesis

PubMed Central

Boxem, Mike; Maliga, Zoltan; Klitgord, Niels; Li, Na; Lemmens, Irma; Mana, Miyeko; de Lichtervelde, Lorenzo; Mul, Joram D.; van de Peut, Diederik; Devos, Maxime; Simonis, Nicolas; Yildirim, Muhammed A.; Cokol, Murat; Kao, Huey-Ling; de Smet, Anne-Sophie; Wang, Haidong; Schlaitz, Anne-Lore; Hao, Tong; Milstein, Stuart; Fan, Changyu; Tipsword, Mike; Drew, Kevin; Galli, Matilde; Rhrissorrakrai, Kahn; Drechsel, David; Koller, Daphne; Roth, Frederick P.; Iakoucheva, Lilia M.; Dunker, A. Keith; Bonneau, Richard; Gunsalus, Kristin C.; Hill, David E.; Piano, Fabio; Tavernier, Jan; van den Heuvel, Sander; Hyman, Anthony A.; Vidal, Marc

2008-01-01

Summary Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or “interactome” networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed new insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms. PMID:18692475

Building Interactive Simulations in Web Pages without Programming.

PubMed

Mailen Kootsey, J; McAuley, Grant; Bernal, Julie

2005-01-01

A software system is described for building interactive simulations and other numerical calculations in Web pages. The system is based on a new Java-based software architecture named NumberLinX (NLX) that isolates each function required to build the simulation so that a library of reusable objects could be assembled. The NLX objects are integrated into a commercial Web design program for coding-free page construction. The model description is entered through a wizard-like utility program that also functions as a model editor. The complete system permits very rapid construction of interactive simulations without coding. A wide range of applications are possible with the system beyond interactive calculations, including remote data collection and processing and collaboration over a network.

Construction of a three-dimensional interactive model of the skull base and cranial nerves.

PubMed

Kakizawa, Yukinari; Hongo, Kazuhiro; Rhoton, Albert L

2007-05-01

The goal was to develop an interactive three-dimensional (3-D) computerized anatomic model of the skull base for teaching microneurosurgical anatomy and for operative planning. The 3-D model was constructed using commercially available software (Maya 6.0 Unlimited; Alias Systems Corp., Delaware, MD), a personal computer, four cranial specimens, and six dry bones. Photographs from at least two angles of the superior and lateral views were imported to the 3-D software. Many photographs were needed to produce the model in anatomically complex areas. Careful dissection was needed to expose important structures in the two views. Landmarks, including foramen, bone, and dura mater, were used as reference points. The 3-D model of the skull base and related structures was constructed using more than 300,000 remodeled polygons. The model can be viewed from any angle. It can be rotated 360 degrees in any plane using any structure as the focal point of rotation. The model can be reduced or enlarged using the zoom function. Variable transparencies could be assigned to any structures so that the structures at any level can be seen. Anatomic labels can be attached to the structures in the 3-D model for educational purposes. This computer-generated 3-D model can be observed and studied repeatedly without the time limitations and stresses imposed by surgery. This model may offer the potential to create interactive surgical exercises useful in evaluating multiple surgical routes to specific target areas in the skull base.

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

PubMed

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

2017-01-01

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

Developing Computer Model-Based Assessment of Chemical Reasoning: A Feasibility Study

ERIC Educational Resources Information Center

Liu, Xiufeng; Waight, Noemi; Gregorius, Roberto; Smith, Erica; Park, Mihwa

2012-01-01

This paper reports a feasibility study on developing computer model-based assessments of chemical reasoning at the high school level. Computer models are flash and NetLogo environments to make simultaneously available three domains in chemistry: macroscopic, submicroscopic, and symbolic. Students interact with computer models to answer assessment…

Configurations of base-pair complexes in solutions. [nucleotide chemistry

NASA Technical Reports Server (NTRS)

Egan, J. T.; Nir, S.; Rein, R.; Macelroy, R.

1978-01-01

A theoretical search for the most stable conformations (i.e., stacked or hydrogen bonded) of the base pairs A-U and G-C in water, CCl4, and CHCl3 solutions is presented. The calculations of free energies indicate a significant role of the solvent in determining the conformations of the base-pair complexes. The application of the continuum method yields preferred conformations in good agreement with experiment. Results of the calculations with this method emphasize the importance of both the electrostatic interactions between the two bases in a complex, and the dipolar interaction of the complex with the entire medium. In calculations with the solvation shell method, the last term, i.e., dipolar interaction of the complex with the entire medium, was added. With this modification the prediction of the solvation shell model agrees both with the continuum model and with experiment, i.e., in water the stacked conformation of the bases is preferred.

Reconstruction of interaction rate in holographic dark energy

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

Mukherjee, Ankan, E-mail: ankan_ju@iiserkol.ac.in

2016-11-01

The present work is based on the holographic dark energy model with Hubble horizon as the infrared cut-off. The interaction rate between dark energy and dark matter has been reconstructed for three different parameterizations of the deceleration parameter. Observational constraints on the model parameters have been obtained by maximum likelihood analysis using the observational Hubble parameter data (OHD), type Ia supernovab data (SNe), baryon acoustic oscillation data (BAO) and the distance prior of cosmic microwave background (CMB) namely the CMB shift parameter data (CMBShift). The interaction rate obtained in the present work remains always positive and increases with expansion. Itmore » is very similar to the result obtained by Sen and Pavon [1] where the interaction rate has been reconstructed for a parametrization of the dark energy equation of state. Tighter constraints on the interaction rate have been obtained in the present work as it is based on larger data sets. The nature of the dark energy equation of state parameter has also been studied for the present models. Though the reconstruction is done from different parametrizations, the overall nature of the interaction rate is very similar in all the cases. Different information criteria and the Bayesian evidence, which have been invoked in the context of model selection, show that the these models are at close proximity of each other.« less

To Control False Positives in Gene-Gene Interaction Analysis: Two Novel Conditional Entropy-Based Approaches

PubMed Central

Lin, Meihua; Li, Haoli; Zhao, Xiaolei; Qin, Jiheng

2013-01-01

Genome-wide analysis of gene-gene interactions has been recognized as a powerful avenue to identify the missing genetic components that can not be detected by using current single-point association analysis. Recently, several model-free methods (e.g. the commonly used information based metrics and several logistic regression-based metrics) were developed for detecting non-linear dependence between genetic loci, but they are potentially at the risk of inflated false positive error, in particular when the main effects at one or both loci are salient. In this study, we proposed two conditional entropy-based metrics to challenge this limitation. Extensive simulations demonstrated that the two proposed metrics, provided the disease is rare, could maintain consistently correct false positive rate. In the scenarios for a common disease, our proposed metrics achieved better or comparable control of false positive error, compared to four previously proposed model-free metrics. In terms of power, our methods outperformed several competing metrics in a range of common disease models. Furthermore, in real data analyses, both metrics succeeded in detecting interactions and were competitive with the originally reported results or the logistic regression approaches. In conclusion, the proposed conditional entropy-based metrics are promising as alternatives to current model-based approaches for detecting genuine epistatic effects. PMID:24339984

An information driven strategy to support multidisciplinary design

NASA Technical Reports Server (NTRS)

Rangan, Ravi M.; Fulton, Robert E.

1990-01-01

The design of complex engineering systems such as aircraft, automobiles, and computers is primarily a cooperative multidisciplinary design process involving interactions between several design agents. The common thread underlying this multidisciplinary design activity is the information exchange between the various groups and disciplines. The integrating component in such environments is the common data and the dependencies that exist between such data. This may be contrasted to classical multidisciplinary analyses problems where there is coupling between distinct design parameters. For example, they may be expressed as mathematically coupled relationships between aerodynamic and structural interactions in aircraft structures, between thermal and structural interactions in nuclear plants, and between control considerations and structural interactions in flexible robots. These relationships provide analytical based frameworks leading to optimization problem formulations. However, in multidisciplinary design problems, information based interactions become more critical. Many times, the relationships between different design parameters are not amenable to analytical characterization. Under such circumstances, information based interactions will provide the best integration paradigm, i.e., there is a need to model the data entities and their dependencies between design parameters originating from different design agents. The modeling of such data interactions and dependencies forms the basis for integrating the various design agents.

Density-Dependent Formulation of Dispersion-Repulsion Interactions in Hybrid Multiscale Quantum/Molecular Mechanics (QM/MM) Models.

PubMed

Curutchet, Carles; Cupellini, Lorenzo; Kongsted, Jacob; Corni, Stefano; Frediani, Luca; Steindal, Arnfinn Hykkerud; Guido, Ciro A; Scalmani, Giovanni; Mennucci, Benedetta

2018-03-13

Mixed multiscale quantum/molecular mechanics (QM/MM) models are widely used to explore the structure, reactivity, and electronic properties of complex chemical systems. Whereas such models typically include electrostatics and potentially polarization in so-called electrostatic and polarizable embedding approaches, respectively, nonelectrostatic dispersion and repulsion interactions are instead commonly described through classical potentials despite their quantum mechanical origin. Here we present an extension of the Tkatchenko-Scheffler semiempirical van der Waals (vdW TS ) scheme aimed at describing dispersion and repulsion interactions between quantum and classical regions within a QM/MM polarizable embedding framework. Starting from the vdW TS expression, we define a dispersion and a repulsion term, both of them density-dependent and consistently based on a Lennard-Jones-like potential. We explore transferable atom type-based parametrization strategies for the MM parameters, based on either vdW TS calculations performed on isolated fragments or on a direct estimation of the parameters from atomic polarizabilities taken from a polarizable force field. We investigate the performance of the implementation by computing self-consistent interaction energies for the S22 benchmark set, designed to represent typical noncovalent interactions in biological systems, in both equilibrium and out-of-equilibrium geometries. Overall, our results suggest that the present implementation is a promising strategy to include dispersion and repulsion in multiscale QM/MM models incorporating their explicit dependence on the electronic density.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

Model-Based Design of Air Traffic Controller-Automation Interaction

NASA Technical Reports Server (NTRS)

Romahn, Stephan; Callantine, Todd J.; Palmer, Everett A.; Null, Cynthia H. (Technical Monitor)

1998-01-01

A model of controller and automation activities was used to design the controller-automation interactions necessary to implement a new terminal area air traffic management concept. The model was then used to design a controller interface that provides the requisite information and functionality. Using data from a preliminary study, the Crew Activity Tracking System (CATS) was used to help validate the model as a computational tool for describing controller performance.

Role of ion hydration for the differential capacitance of an electric double layer.

PubMed

Caetano, Daniel L Z; Bossa, Guilherme V; de Oliveira, Vinicius M; Brown, Matthew A; de Carvalho, Sidney J; May, Sylvio

2016-10-12

The influence of soft, hydration-mediated ion-ion and ion-surface interactions on the differential capacitance of an electric double layer is investigated using Monte Carlo simulations and compared to various mean-field models. We focus on a planar electrode surface at physiological concentration of monovalent ions in a uniform dielectric background. Hydration-mediated interactions are modeled on the basis of Yukawa potentials that add to the Coulomb and excluded volume interactions between ions. We present a mean-field model that includes hydration-mediated anion-anion, anion-cation, and cation-cation interactions of arbitrary strengths. In addition, finite ion sizes are accounted for through excluded volume interactions, described either on the basis of the Carnahan-Starling equation of state or using a lattice gas model. Both our Monte Carlo simulations and mean-field approaches predict a characteristic double-peak (the so-called camel shape) of the differential capacitance; its decrease reflects the packing of the counterions near the electrode surface. The presence of hydration-mediated ion-surface repulsion causes a thin charge-depleted region close to the surface, which is reminiscent of a Stern layer. We analyze the interplay between excluded volume and hydration-mediated interactions on the differential capacitance and demonstrate that for small surface charge density our mean-field model based on the Carnahan-Starling equation is able to capture the Monte Carlo simulation results. In contrast, for large surface charge density the mean-field approach based on the lattice gas model is preferable.

Teaching Experience: How to Make and Use PowerPoint-Based Interactive Simulations for Undergraduate IR Teaching

ERIC Educational Resources Information Center

Meibauer, Gustav; Aagaard Nøhr, Andreas

2018-01-01

This article is about designing and implementing PowerPoint-based interactive simulations for use in International Relations (IR) introductory undergraduate classes based on core pedagogical literature, models of human skill acquisition, and previous research on simulations in IR teaching. We argue that simulations can be usefully employed at the…

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.

Predicting loop–helix tertiary structural contacts in RNA pseudoknots

PubMed Central

Cao, Song; Giedroc, David P.; Chen, Shi-Jie

2010-01-01

Tertiary interactions between loops and helical stems play critical roles in the biological function of many RNA pseudoknots. However, quantitative predictions for RNA tertiary interactions remain elusive. Here we report a statistical mechanical model for the prediction of noncanonical loop–stem base-pairing interactions in RNA pseudoknots. Central to the model is the evaluation of the conformational entropy for the pseudoknotted folds with defined loop–stem tertiary structural contacts. We develop an RNA virtual bond-based conformational model (Vfold model), which permits a rigorous computation of the conformational entropy for a given fold that contains loop–stem tertiary contacts. With the entropy parameters predicted from the Vfold model and the energy parameters for the tertiary contacts as inserted parameters, we can then predict the RNA folding thermodynamics, from which we can extract the tertiary contact thermodynamic parameters from theory–experimental comparisons. These comparisons reveal a contact enthalpy (ΔH) of −14 kcal/mol and a contact entropy (ΔS) of −38 cal/mol/K for a protonated C+•(G–C) base triple at pH 7.0, and (ΔH = −7 kcal/mol, ΔS = −19 cal/mol/K) for an unprotonated base triple. Tests of the model for a series of pseudoknots show good theory–experiment agreement. Based on the extracted energy parameters for the tertiary structural contacts, the model enables predictions for the structure, stability, and folding pathways for RNA pseudoknots with known or postulated loop–stem tertiary contacts from the nucleotide sequence alone. PMID:20100813

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

PubMed

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

2018-01-01

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

A modeling approach to soil type and precipitation seasonality interactions on bioenergy crop production

USDA-ARS?s Scientific Manuscript database

Precipitation limits primary production by affecting soil moisture, and soil type interacts with soil moisture to determine soil water availability to plants. We used ALMANAC, a process-based model, to simulate switchgrass (Panicum virgatum var. Alamo) biomass production in Central Texas under thre...

Modeling Interactions in Small Groups

ERIC Educational Resources Information Center

Heise, David R.

2013-01-01

A new theory of interaction within small groups posits that group members initiate actions when tension mounts between the affective meanings of their situational identities and impressions produced by recent events. Actors choose partners and behaviors so as to reduce the tensions. A computer model based on this theory, incorporating reciprocal…

Data publication and dissemination of interactive keys under the open access model

USDA-ARS?s Scientific Manuscript database

The concepts of publication, citation and dissemination of interactive keys and other online keys are discussed and illustrated by a sample paper published in the present issue (doi: 10.3897/zookeys.21.271). The present model is based on previous experience with several existing examples of publishi...

JSC interactive basic accounting system

NASA Technical Reports Server (NTRS)

Spitzer, J. F.

1978-01-01

Design concepts for an interactive basic accounting system (IBAS) are considered in terms of selecting the design option which provides the best response at the lowest cost. Modeling the IBAS workload and applying this workload to a U1108 EXEC 8 based system using both a simulation model and the real system is discussed.

An Interactive Model for Studying Student Retention. AIR 1990 Annual Forum Paper.

ERIC Educational Resources Information Center

Glover, Robert H.; Wilcox, Jerry

A design for improving the quality of information available for continuous operational study of student retention at the University of Hartford in Connecticut was examined involving a microcomputer based decision support system for student retention research. The system, an interactive modeling approach to conduct longitudinal and comparative…

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.

Complex networks generated by the Penna bit-string model: Emergence of small-world and assortative mixing

NASA Astrophysics Data System (ADS)

Li, Chunguang; Maini, Philip K.

2005-10-01

The Penna bit-string model successfully encompasses many phenomena of population evolution, including inheritance, mutation, evolution, and aging. If we consider social interactions among individuals in the Penna model, the population will form a complex network. In this paper, we first modify the Verhulst factor to control only the birth rate, and introduce activity-based preferential reproduction of offspring in the Penna model. The social interactions among individuals are generated by both inheritance and activity-based preferential increase. Then we study the properties of the complex network generated by the modified Penna model. We find that the resulting complex network has a small-world effect and the assortative mixing property.

Design of Intelligent Robot as A Tool for Teaching Media Based on Computer Interactive Learning and Computer Assisted Learning to Improve the Skill of University Student

NASA Astrophysics Data System (ADS)

Zuhrie, M. S.; Basuki, I.; Asto B, I. G. P.; Anifah, L.

2018-01-01

The focus of the research is the teaching module which incorporates manufacturing, planning mechanical designing, controlling system through microprocessor technology and maneuverability of the robot. Computer interactive and computer-assisted learning is strategies that emphasize the use of computers and learning aids (computer assisted learning) in teaching and learning activity. This research applied the 4-D model research and development. The model is suggested by Thiagarajan, et.al (1974). 4-D Model consists of four stages: Define Stage, Design Stage, Develop Stage, and Disseminate Stage. This research was conducted by applying the research design development with an objective to produce a tool of learning in the form of intelligent robot modules and kit based on Computer Interactive Learning and Computer Assisted Learning. From the data of the Indonesia Robot Contest during the period of 2009-2015, it can be seen that the modules that have been developed confirm the fourth stage of the research methods of development; disseminate method. The modules which have been developed for students guide students to produce Intelligent Robot Tool for Teaching Based on Computer Interactive Learning and Computer Assisted Learning. Results of students’ responses also showed a positive feedback to relate to the module of robotics and computer-based interactive learning.

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

PubMed

Patsahan, O

2013-08-01

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

A neural network model of metaphor understanding with dynamic interaction based on a statistical language analysis: targeting a human-like model.

PubMed

Terai, Asuka; Nakagawa, Masanori

2007-08-01

The purpose of this paper is to construct a model that represents the human process of understanding metaphors, focusing specifically on similes of the form an "A like B". Generally speaking, human beings are able to generate and understand many sorts of metaphors. This study constructs the model based on a probabilistic knowledge structure for concepts which is computed from a statistical analysis of a large-scale corpus. Consequently, this model is able to cover the many kinds of metaphors that human beings can generate. Moreover, the model implements the dynamic process of metaphor understanding by using a neural network with dynamic interactions. Finally, the validity of the model is confirmed by comparing model simulations with the results from a psychological experiment.

Comparison of an Agent-based Model of Disease Propagation with the Generalised SIR Epidemic Model

DTIC Science & Technology

2009-08-01

has become a practical method for conducting Epidemiological Modelling. In the agent- based approach the whole township can be modelled as a system of...SIR system was initially developed based on a very simplified model of social interaction. For instance an assumption of uniform population mixing was...simulating the progress of a disease within a host and of transmission between hosts is based upon Transportation Analysis and Simulation System

Energy-based and process-based constraints on aerosol-climate interaction

NASA Astrophysics Data System (ADS)

Suzuki, K.; Sato, Y.; Takemura, T.; Michibata, T.; Goto, D.; Oikawa, E.

2017-12-01

Recent advance in both satellite observations and global modeling provides us with a novel opportunity to investigate the long-standing aerosol-climate interaction issue at a fundamental process level, particularly with a combined use of them. In this presentation, we will highlight our recent progress in understanding the aerosol-cloud-precipitation interaction and its implication for global climate with a synergistic use of a state-of-the-art global climate model (MIROC), a global cloud-resolving model (NICAM) and recent satellite observations (A-Train). In particular, we explore two different aspects of the aerosol-climate interaction issue, i.e. (i) the global energy balance perspective with its modulation due to aerosols and (ii) the process-level characteristics of the aerosol-induced perturbations to cloud and precipitation. For the former, climate model simulations are used to quantify how components of global energy budget are modulated by the aerosol forcing. The moist processes are shown to be a critical pathway that links the forcing efficacy and the hydrologic sensitivity arising from aerosol perturbations. Effects of scattering (e.g. sulfate) and absorbing (e.g. black carbon) aerosols are compared in this context to highlight their distinctively different impacts on climate and hydrologic cycle. The aerosol-induced modulation of moist processes is also investigated in the context of the second aspect above to facilitate recent arguments on possible overestimates of the aerosol-cloud interaction in climate models. Our recent simulations with NICAM are shown to highlight how diverse responses of cloud to aerosol perturbation, which have been failed to represent in traditional climate models, are reproduced by the high-resolution global model with sophisticated cloud microphysics. We will discuss implications of these findings for a linkage between the two aspects above to aid advance process-based understandings of the aerosol-climate interaction and also to mitigate a "dichotomy" recently found by the authors between the two aspects in the context of the climate projection.

Yoink: An interaction-based partitioning API.

PubMed

Zheng, Min; Waller, Mark P

2018-05-15

Herein, we describe the implementation details of our interaction-based partitioning API (application programming interface) called Yoink for QM/MM modeling and fragment-based quantum chemistry studies. Interactions are detected by computing density descriptors such as reduced density gradient, density overlap regions indicator, and single exponential decay detector. Only molecules having an interaction with a user-definable QM core are added to the QM region of a hybrid QM/MM calculation. Moreover, a set of molecule pairs having density-based interactions within a molecular system can be computed in Yoink, and an interaction graph can then be constructed. Standard graph clustering methods can then be applied to construct fragments for further quantum chemical calculations. The Yoink API is licensed under Apache 2.0 and can be accessed via yoink.wallerlab.org. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Particle-based membrane model for mesoscopic simulation of cellular dynamics

NASA Astrophysics Data System (ADS)

Sadeghi, Mohsen; Weikl, Thomas R.; Noé, Frank

2018-01-01

We present a simple and computationally efficient coarse-grained and solvent-free model for simulating lipid bilayer membranes. In order to be used in concert with particle-based reaction-diffusion simulations, the model is purely based on interacting and reacting particles, each representing a coarse patch of a lipid monolayer. Particle interactions include nearest-neighbor bond-stretching and angle-bending and are parameterized so as to reproduce the local membrane mechanics given by the Helfrich energy density over a range of relevant curvatures. In-plane fluidity is implemented with Monte Carlo bond-flipping moves. The physical accuracy of the model is verified by five tests: (i) Power spectrum analysis of equilibrium thermal undulations is used to verify that the particle-based representation correctly captures the dynamics predicted by the continuum model of fluid membranes. (ii) It is verified that the input bending stiffness, against which the potential parameters are optimized, is accurately recovered. (iii) Isothermal area compressibility modulus of the membrane is calculated and is shown to be tunable to reproduce available values for different lipid bilayers, independent of the bending rigidity. (iv) Simulation of two-dimensional shear flow under a gravity force is employed to measure the effective in-plane viscosity of the membrane model and show the possibility of modeling membranes with specified viscosities. (v) Interaction of the bilayer membrane with a spherical nanoparticle is modeled as a test case for large membrane deformations and budding involved in cellular processes such as endocytosis. The results are shown to coincide well with the predicted behavior of continuum models, and the membrane model successfully mimics the expected budding behavior. We expect our model to be of high practical usability for ultra coarse-grained molecular dynamics or particle-based reaction-diffusion simulations of biological systems.

Study of cosmic ray interaction model based on atmospheric muons for the neutrino flux calculation

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

Sanuki, T.; Honda, M.; Kajita, T.

2007-02-15

We have studied the hadronic interaction for the calculation of the atmospheric neutrino flux by summarizing the accurately measured atmospheric muon flux data and comparing with simulations. We find the atmospheric muon and neutrino fluxes respond to errors in the {pi}-production of the hadronic interaction similarly, and compare the atmospheric muon flux calculated using the HKKM04 [M. Honda, T. Kajita, K. Kasahara, and S. Midorikawa, Phys. Rev. D 70, 043008 (2004).] code with experimental measurements. The {mu}{sup +}+{mu}{sup -} data show good agreement in the 1{approx}30 GeV/c range, but a large disagreement above 30 GeV/c. The {mu}{sup +}/{mu}{sup -} ratiomore » shows sizable differences at lower and higher momenta for opposite directions. As the disagreements are considered to be due to assumptions in the hadronic interaction model, we try to improve it phenomenologically based on the quark parton model. The improved interaction model reproduces the observed muon flux data well. The calculation of the atmospheric neutrino flux will be reported in the following paper [M. Honda et al., Phys. Rev. D 75, 043006 (2007).].« less

The physicochemical process of bacterial attachment to abiotic surfaces: Challenges for mechanistic studies, predictability and the development of control strategies.

PubMed

Wang, Yi; Lee, Sui Mae; Dykes, Gary

2015-01-01

Bacterial attachment to abiotic surfaces can be explained as a physicochemical process. Mechanisms of the process have been widely studied but are not yet well understood due to their complexity. Physicochemical processes can be influenced by various interactions and factors in attachment systems, including, but not limited to, hydrophobic interactions, electrostatic interactions and substratum surface roughness. Mechanistic models and control strategies for bacterial attachment to abiotic surfaces have been established based on the current understanding of the attachment process and the interactions involved. Due to a lack of process control and standardization in the methodologies used to study the mechanisms of bacterial attachment, however, various challenges are apparent in the development of models and control strategies. In this review, the physicochemical mechanisms, interactions and factors affecting the process of bacterial attachment to abiotic surfaces are described. Mechanistic models established based on these parameters are discussed in terms of their limitations. Currently employed methods to study these parameters and bacterial attachment are critically compared. The roles of these parameters in the development of control strategies for bacterial attachment are reviewed, and the challenges that arise in developing mechanistic models and control strategies are assessed.

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

NASA Astrophysics Data System (ADS)

Armstrong, Robert A.

2003-11-01

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

Systematic Uncertainties in High-Energy Hadronic Interaction Models

NASA Astrophysics Data System (ADS)

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

2003-07-01

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

A Nonlinear Interactions Approximation Model for Large-Eddy Simulation

NASA Astrophysics Data System (ADS)

Haliloglu, Mehmet U.; Akhavan, Rayhaneh

2003-11-01

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

Photorealistic virtual anatomy based on Chinese Visible Human data.

PubMed

Heng, P A; Zhang, S X; Xie, Y M; Wong, T T; Chui, Y P; Cheng, C Y

2006-04-01

Virtual reality based learning of human anatomy is feasible when a database of 3D organ models is available for the learner to explore, visualize, and dissect in virtual space interactively. In this article, we present our latest work on photorealistic virtual anatomy applications based on the Chinese Visible Human (CVH) data. We have focused on the development of state-of-the-art virtual environments that feature interactive photo-realistic visualization and dissection of virtual anatomical models constructed from ultra-high resolution CVH datasets. We also outline our latest progress in applying these highly accurate virtual and functional organ models to generate realistic look and feel to advanced surgical simulators. (c) 2006 Wiley-Liss, Inc.

Framework for scalable adsorbate–adsorbate interaction models

DOE PAGES

Hoffmann, Max J.; Medford, Andrew J.; Bligaard, Thomas

2016-06-02

Here, we present a framework for physically motivated models of adsorbate–adsorbate interaction between small molecules on transition and coinage metals based on modifications to the substrate electronic structure due to adsorption. We use this framework to develop one model for transition and one for coinage metal surfaces. The models for transition metals are based on the d-band center position, and the models for coinage metals are based on partial charges. The models require no empirical parameters, only two first-principles calculations per adsorbate as input, and therefore scale linearly with the number of reaction intermediates. By theory to theory comparison withmore » explicit density functional theory calculations over a wide range of adsorbates and surfaces, we show that the root-mean-squared error for differential adsorption energies is less than 0.2 eV for up to 1 ML coverage.« less

Exact solutions for a type of electron pairing model with spin-orbit interactions and Zeeman coupling.

PubMed

Liu, Jia; Han, Qiang; Shao, L B; Wang, Z D

2011-07-08

A type of electron pairing model with spin-orbit interactions or Zeeman coupling is solved exactly in the framework of the Richardson ansatz. Based on the exact solutions for the case with spin-orbit interactions, it is shown rigorously that the pairing symmetry is of the p + ip wave and the ground state possesses time-reversal symmetry, regardless of the strength of the pairing interaction. Intriguingly, how Majorana fermions can emerge in the system is also elaborated. Exact results are illustrated for two systems, respectively, with spin-orbit interactions and Zeeman coupling.

A Grammatical Approach to RNA-RNA Interaction Prediction

NASA Astrophysics Data System (ADS)

Kato, Yuki; Akutsu, Tatsuya; Seki, Hiroyuki

2007-11-01

Much attention has been paid to two interacting RNA molecules involved in post-transcriptional control of gene expression. Although there have been a few studies on RNA-RNA interaction prediction based on dynamic programming algorithm, no grammar-based approach has been proposed. The purpose of this paper is to provide a new modeling for RNA-RNA interaction based on multiple context-free grammar (MCFG). We present a polynomial time parsing algorithm for finding the most likely derivation tree for the stochastic version of MCFG, which is applicable to RNA joint secondary structure prediction including kissing hairpin loops. Also, elementary tests on RNA-RNA interaction prediction have shown that the proposed method is comparable to Alkan et al.'s method.

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.

When push comes to shove: Exclusion processes with nonlocal consequences

NASA Astrophysics Data System (ADS)

Almet, Axel A.; Pan, Michael; Hughes, Barry D.; Landman, Kerry A.

2015-11-01

Stochastic agent-based models are useful for modelling collective movement of biological cells. Lattice-based random walk models of interacting agents where each site can be occupied by at most one agent are called simple exclusion processes. An alternative motility mechanism to simple exclusion is formulated, in which agents are granted more freedom to move under the compromise that interactions are no longer necessarily local. This mechanism is termed shoving. A nonlinear diffusion equation is derived for a single population of shoving agents using mean-field continuum approximations. A continuum model is also derived for a multispecies problem with interacting subpopulations, which either obey the shoving rules or the simple exclusion rules. Numerical solutions of the derived partial differential equations compare well with averaged simulation results for both the single species and multispecies processes in two dimensions, while some issues arise in one dimension for the multispecies case.

Template-based protein-protein docking exploiting pairwise interfacial residue restraints.

PubMed

Xue, Li C; Rodrigues, João P G L M; Dobbs, Drena; Honavar, Vasant; Bonvin, Alexandre M J J

2017-05-01

Although many advanced and sophisticated ab initio approaches for modeling protein-protein complexes have been proposed in past decades, template-based modeling (TBM) remains the most accurate and widely used approach, given a reliable template is available. However, there are many different ways to exploit template information in the modeling process. Here, we systematically evaluate and benchmark a TBM method that uses conserved interfacial residue pairs as docking distance restraints [referred to as alpha carbon-alpha carbon (CA-CA)-guided docking]. We compare it with two other template-based protein-protein modeling approaches, including a conserved non-pairwise interfacial residue restrained docking approach [referred to as the ambiguous interaction restraint (AIR)-guided docking] and a simple superposition-based modeling approach. Our results show that, for most cases, the CA-CA-guided docking method outperforms both superposition with refinement and the AIR-guided docking method. We emphasize the superiority of the CA-CA-guided docking on cases with medium to large conformational changes, and interactions mediated through loops, tails or disordered regions. Our results also underscore the importance of a proper refinement of superimposition models to reduce steric clashes. In summary, we provide a benchmarked TBM protocol that uses conserved pairwise interface distance as restraints in generating realistic 3D protein-protein interaction models, when reliable templates are available. The described CA-CA-guided docking protocol is based on the HADDOCK platform, which allows users to incorporate additional prior knowledge of the target system to further improve the quality of the resulting models. © The Author 2016. Published by Oxford University Press.

On the context-dependent scaling of consumer feeding rates.

PubMed

Barrios-O'Neill, Daniel; Kelly, Ruth; Dick, Jaimie T A; Ricciardi, Anthony; MacIsaac, Hugh J; Emmerson, Mark C

2016-06-01

The stability of consumer-resource systems can depend on the form of feeding interactions (i.e. functional responses). Size-based models predict interactions - and thus stability - based on consumer-resource size ratios. However, little is known about how interaction contexts (e.g. simple or complex habitats) might alter scaling relationships. Addressing this, we experimentally measured interactions between a large size range of aquatic predators (4-6400 mg over 1347 feeding trials) and an invasive prey that transitions among habitats: from the water column (3D interactions) to simple and complex benthic substrates (2D interactions). Simple and complex substrates mediated successive reductions in capture rates - particularly around the unimodal optimum - and promoted prey population stability in model simulations. Many real consumer-resource systems transition between 2D and 3D interactions, and along complexity gradients. Thus, Context-Dependent Scaling (CDS) of feeding interactions could represent an unrecognised aspect of food webs, and quantifying the extent of CDS might enhance predictive ecology. © The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

MESA: An Interactive Modeling and Simulation Environment for Intelligent Systems Automation

NASA Technical Reports Server (NTRS)

Charest, Leonard

1994-01-01

This report describes MESA, a software environment for creating applications that automate NASA mission opterations. MESA enables intelligent automation by utilizing model-based reasoning techniques developed in the field of Artificial Intelligence. Model-based reasoning techniques are realized in Mesa through native support of causal modeling and discrete event simulation.

A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs

PubMed Central

Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

2018-01-01

Abstract We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$\\mathcal {E}$\\end{document}SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base–phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation. PMID:29272539

A Model for Student Adoption of Online Interactivity

ERIC Educational Resources Information Center

Karamanos, Neophytos; Gibbs, Paul

2012-01-01

Acknowledging the general difficulty of new e-learning pedagogical approaches in achieving wide acceptance and use, the study described in this article examines a class of MBA students' adoption of a proposed online interactive learning environment. To this end, a web-based, case-based constructivist learning environment was developed, embedding…

The Asthma Dialogues: A Model of Interactive Education for Skills

ERIC Educational Resources Information Center

Morrow, Robert; Fletcher, Jason; Mulvihill, Michael; Park, Heidi

2007-01-01

Introduction: A gap exists between asthma guidelines and actual care delivered. We developed an educational intervention using simulated physician-patient encounters as part of a project to improve asthma management by community-based primary care providers. We hypothesized that this type of skills-based interactive training would improve…

User Interface Models for Multidisciplinary Bibliographic Information Dissemination Centers.

ERIC Educational Resources Information Center

Zipperer, W. C.

Two information dissemination centers at University of California at Los Angeles and University of Georgia studied the interactions between computer based search facilities and their users. The study, largely descriptive in nature, investigated the interaction processes between data base users and profile analysis or information specialists in…

A modeling approach to account for toxicokinetic interactions in the calculation of biological hazard index for chemical mixtures.

PubMed

Haddad, S; Tardif, R; Viau, C; Krishnan, K

1999-09-05

Biological hazard index (BHI) is defined as biological level tolerable for exposure to mixture, and is calculated by an equation similar to the conventional hazard index. The BHI calculation, at the present time, is advocated for use in situations where toxicokinetic interactions do not occur among mixture constituents. The objective of this study was to develop an approach for calculating interactions-based BHI for chemical mixtures. The approach consisted of simulating the concentration of exposure indicator in the biological matrix of choice (e.g. venous blood) for each component of the mixture to which workers are exposed and then comparing these to the established BEI values, for calculating the BHI. The simulation of biomarker concentrations was performed using a physiologically-based toxicokinetic (PBTK) model which accounted for the mechanism of interactions among all mixture components (e.g. competitive inhibition). The usefulness of the present approach is illustrated by calculating BHI for varying ambient concentrations of a mixture of three chemicals (toluene (5-40 ppm), m-xylene (10-50 ppm), and ethylbenzene (10-50 ppm)). The results show that the interactions-based BHI can be greater or smaller than that calculated on the basis of additivity principle, particularly at high exposure concentrations. At lower exposure concentrations (e.g. 20 ppm each of toluene, m-xylene and ethylbenzene), the BHI values obtained using the conventional methodology are similar to the interactions-based methodology, confirming that the consequences of competitive inhibition are negligible at lower concentrations. The advantage of the PBTK model-based methodology developed in this study relates to the fact that, the concentrations of individual chemicals in mixtures that will not result in a significant increase in the BHI (i.e. > 1) can be determined by iterative simulation.

A Probabilistic Model of Social Working Memory for Information Retrieval in Social Interactions.

PubMed

Li, Liyuan; Xu, Qianli; Gan, Tian; Tan, Cheston; Lim, Joo-Hwee

2018-05-01

Social working memory (SWM) plays an important role in navigating social interactions. Inspired by studies in psychology, neuroscience, cognitive science, and machine learning, we propose a probabilistic model of SWM to mimic human social intelligence for personal information retrieval (IR) in social interactions. First, we establish a semantic hierarchy as social long-term memory to encode personal information. Next, we propose a semantic Bayesian network as the SWM, which integrates the cognitive functions of accessibility and self-regulation. One subgraphical model implements the accessibility function to learn the social consensus about IR-based on social information concept, clustering, social context, and similarity between persons. Beyond accessibility, one more layer is added to simulate the function of self-regulation to perform the personal adaptation to the consensus based on human personality. Two learning algorithms are proposed to train the probabilistic SWM model on a raw dataset of high uncertainty and incompleteness. One is an efficient learning algorithm of Newton's method, and the other is a genetic algorithm. Systematic evaluations show that the proposed SWM model is able to learn human social intelligence effectively and outperforms the baseline Bayesian cognitive model. Toward real-world applications, we implement our model on Google Glass as a wearable assistant for social interaction.

A coupled modeling framework for sustainable watershed management in transboundary river basins

NASA Astrophysics Data System (ADS)

Furqan Khan, Hassaan; Yang, Y. C. Ethan; Xie, Hua; Ringler, Claudia

2017-12-01

There is a growing recognition among water resource managers that sustainable watershed management needs to not only account for the diverse ways humans benefit from the environment, but also incorporate the impact of human actions on the natural system. Coupled natural-human system modeling through explicit modeling of both natural and human behavior can help reveal the reciprocal interactions and co-evolution of the natural and human systems. This study develops a spatially scalable, generalized agent-based modeling (ABM) framework consisting of a process-based semi-distributed hydrologic model (SWAT) and a decentralized water system model to simulate the impacts of water resource management decisions that affect the food-water-energy-environment (FWEE) nexus at a watershed scale. Agents within a river basin are geographically delineated based on both political and watershed boundaries and represent key stakeholders of ecosystem services. Agents decide about the priority across three primary water uses: food production, hydropower generation and ecosystem health within their geographical domains. Agents interact with the environment (streamflow) through the SWAT model and interact with other agents through a parameter representing willingness to cooperate. The innovative two-way coupling between the water system model and SWAT enables this framework to fully explore the feedback of human decisions on the environmental dynamics and vice versa. To support non-technical stakeholder interactions, a web-based user interface has been developed that allows for role-play and participatory modeling. The generalized ABM framework is also tested in two key transboundary river basins, the Mekong River basin in Southeast Asia and the Niger River basin in West Africa, where water uses for ecosystem health compete with growing human demands on food and energy resources. We present modeling results for crop production, energy generation and violation of eco-hydrological indicators at both the agent and basin-wide levels to shed light on holistic FWEE management policies in these two basins.

Finite-Rate Ablation Boundary Conditions for Carbon-Phenolic Heat-Shield

NASA Technical Reports Server (NTRS)

Chen, Y.-K.; Milos, Frank S.

2003-01-01

A formulation of finite-rate ablation surface boundary conditions, including oxidation, nitridation, and sublimation of carbonaceous material with pyrolysis gas injection, has been developed based on surface species mass conservation. These surface boundary conditions are discretized and integrated with a Navier-Stokes solver. This numerical procedure can predict aerothermal heating, chemical species concentration, and carbonaceous material ablation rate over the heatshield surface of re-entry space vehicles. In this study, the gas-gas and gas-surface interactions are established for air flow over a carbon-phenolic heatshield. Two finite-rate gas-surface interaction models are considered in the present study. The first model is based on the work of Park, and the second model includes the kinetics suggested by Zhluktov and Abe. Nineteen gas phase chemical reactions and four gas-surface interactions are considered in the present model. There is a total of fourteen gas phase chemical species, including five species for air and nine species for ablation products. Three test cases are studied in this paper. The first case is a graphite test model in the arc-jet stream; the second is a light weight Phenolic Impregnated Carbon Ablator at the Stardust re-entry peak heating conditions, and the third is a fully dense carbon-phenolic heatshield at the peak heating point of a proposed Mars Sample Return Earth Entry Vehicle. Predictions based on both finite-rate gas- surface interaction models are compared with those obtained using B' tables, which were created based on the chemical equilibrium assumption. Stagnation point convective heat fluxes predicted using Park's finite-rate model are far below those obtained from chemical equilibrium B' tables and Zhluktov's model. Recession predictions from Zhluktov's model are generally lower than those obtained from Park's model and chemical equilibrium B' tables. The effect of species mass diffusion on predicted ablation rate is also examined.

Modeling Wood Encroachment in Abandoned Grasslands in the Eifel National Park – Model Description and Testing

PubMed Central

Hudjetz, Silvana; Lennartz, Gottfried; Krämer, Klara; Roß-Nickoll, Martina; Gergs, André; Preuss, Thomas G.

2014-01-01

The degradation of natural and semi-natural landscapes has become a matter of global concern. In Germany, semi-natural grasslands belong to the most species-rich habitat types but have suffered heavily from changes in land use. After abandonment, the course of succession at a specific site is often difficult to predict because many processes interact. In order to support decision making when managing semi-natural grasslands in the Eifel National Park, we built the WoodS-Model (Woodland Succession Model). A multimodeling approach was used to integrate vegetation dynamics in both the herbaceous and shrub/tree layer. The cover of grasses and herbs was simulated in a compartment model, whereas bushes and trees were modelled in an individual-based manner. Both models worked and interacted in a spatially explicit, raster-based landscape. We present here the model description, parameterization and testing. We show highly detailed projections of the succession of a semi-natural grassland including the influence of initial vegetation composition, neighborhood interactions and ungulate browsing. We carefully weighted the single processes against each other and their relevance for landscape development under different scenarios, while explicitly considering specific site conditions. Model evaluation revealed that the model is able to emulate successional patterns as observed in the field as well as plausible results for different population densities of red deer. Important neighborhood interactions such as seed dispersal, the protection of seedlings from browsing ungulates by thorny bushes, and the inhibition of wood encroachment by the herbaceous layer, have been successfully reproduced. Therefore, not only a detailed model but also detailed initialization turned out to be important for spatially explicit projections of a given site. The advantage of the WoodS-Model is that it integrates these many mutually interacting processes of succession. PMID:25494057

An efficient and scalable deformable model for virtual reality-based medical applications.

PubMed

Choi, Kup-Sze; Sun, Hanqiu; Heng, Pheng-Ann

2004-09-01

Modeling of tissue deformation is of great importance to virtual reality (VR)-based medical simulations. Considerable effort has been dedicated to the development of interactively deformable virtual tissues. In this paper, an efficient and scalable deformable model is presented for virtual-reality-based medical applications. It considers deformation as a localized force transmittal process which is governed by algorithms based on breadth-first search (BFS). The computational speed is scalable to facilitate real-time interaction by adjusting the penetration depth. Simulated annealing (SA) algorithms are developed to optimize the model parameters by using the reference data generated with the linear static finite element method (FEM). The mechanical behavior and timing performance of the model have been evaluated. The model has been applied to simulate the typical behavior of living tissues and anisotropic materials. Integration with a haptic device has also been achieved on a generic personal computer (PC) platform. The proposed technique provides a feasible solution for VR-based medical simulations and has the potential for multi-user collaborative work in virtual environment.

A model of urban scaling laws based on distance dependent interactions

PubMed Central

Ribeiro, Fabiano L.; Meirelles, Joao; Ferreira, Fernando F.

2017-01-01

Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log–log plot, the so-called superlinear scaling. Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences. PMID:28405381

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

HexSim - A general purpose framework for spatially-explicit, individual-based modeling

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

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

PubMed

Wheeler, Steven E; Bloom, Jacob W G

2014-08-14

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

The Algebra of Sleepiness: Investigating the Interaction of Homeostatic (S) and Circadian (C) Processes in Sleepiness Using Linear Metrics"

ERIC Educational Resources Information Center

Mairesse, Olivier; Hofmans, Joeri; Neu, Daniel; Dinis Monica de Oliveira, Armando Luis; Cluydts, Raymond; Theuns, Peter

2010-01-01

The present studies were conducted to contribute to the debate on the interaction between circadian (C) and homeostatic (S) processes in models of sleep regulation. The Two-Process Model of Sleep Regulation assumes a linear relationship between processes S and C. However, recent elaborations of the model, based on data from forced desynchrony…

A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design

PubMed Central

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods. PMID:23620809

A PLSPM-based test statistic for detecting gene-gene co-association in genome-wide association study with case-control design.

PubMed

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.

An interactive program for pharmacokinetic modeling.

PubMed

Lu, D R; Mao, F

1993-05-01

A computer program, PharmK, was developed for pharmacokinetic modeling of experimental data. The program was written in C computer language based on the high-level user-interface Macintosh operating system. The intention was to provide a user-friendly tool for users of Macintosh computers. An interactive algorithm based on the exponential stripping method is used for the initial parameter estimation. Nonlinear pharmacokinetic model fitting is based on the maximum likelihood estimation method and is performed by the Levenberg-Marquardt method based on chi 2 criterion. Several methods are available to aid the evaluation of the fitting results. Pharmacokinetic data sets have been examined with the PharmK program, and the results are comparable with those obtained with other programs that are currently available for IBM PC-compatible and other types of computers.

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

Three Approaches to Modeling Gene-Environment Interactions in Longitudinal Family Data: Gene-Smoking Interactions in Blood Pressure.

PubMed

Basson, Jacob; Sung, Yun Ju; de Las Fuentes, Lisa; Schwander, Karen L; Vazquez, Ana; Rao, Dabeeru C

2016-01-01

Blood pressure (BP) has been shown to be substantially heritable, yet identified genetic variants explain only a small fraction of the heritability. Gene-smoking interactions have detected novel BP loci in cross-sectional family data. Longitudinal family data are available and have additional promise to identify BP loci. However, this type of data presents unique analysis challenges. Although several methods for analyzing longitudinal family data are available, which method is the most appropriate and under what conditions has not been fully studied. Using data from three clinic visits from the Framingham Heart Study, we performed association analysis accounting for gene-smoking interactions in BP at 31,203 markers on chromosome 22. We evaluated three different modeling frameworks: generalized estimating equations (GEE), hierarchical linear modeling, and pedigree-based mixed modeling. The three models performed somewhat comparably, with multiple overlaps in the most strongly associated loci from each model. Loci with the greatest significance were more strongly supported in the longitudinal analyses than in any of the component single-visit analyses. The pedigree-based mixed model was more conservative, with less inflation in the variant main effect and greater deflation in the gene-smoking interactions. The GEE, but not the other two models, resulted in substantial inflation in the tail of the distribution when variants with minor allele frequency <1% were included in the analysis. The choice of analysis method should depend on the model and the structure and complexity of the familial and longitudinal data. © 2015 WILEY PERIODICALS, INC.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Modelling the interactions between ammonium and nitrate uptake in marine phytoplankton

PubMed Central

Flynn, K. J.; Fasham, M. J. R.; Hipkin, C. R.

1997-01-01

An empirically based mathematical model is presented which can simulate the major features of the interactions between ammonium and nitrate transport and assimilation in phytoplankton. The model (ammonium-nitrate interaction model), which is configured to simulate a generic microalga rather than a specified species, is constructed on simplified biochemical bases. A major requirement for parametrization is that the N:C ratio of the algae must be known and that transport and internal pool sizes need to be expressed per unit of cell C. The model uses the size of an internal pool of an early organic product of N assimilation (glutamine) to regulate rapid responses in ammonium-nitrate interactions. The synthesis of enzymes for the reduction of nitrate through to ammonium is induced by the size of the internal nitrate pool and repressed by the size of the glutamine pool. The assimilation of intracellular ammonium (into glutamine) is considered to be a constitutive process subjected to regulation by the size of the glutamine pool. Longer term responses have been linked to the nutrient history of the cell using the N:C cell quota. N assimilation in darkness is made a function of the amount of surplus C present and thus only occurs at low values of N:C. The model can simulate both qualitative and quantitative temporal shifts in the ammonium-nitrate interaction, while inclusion of a derivation of the standard quota model enables a concurrent simulation of cell growth and changes in nutrient status.

Non-equilibrium many-body dynamics following a quantum quench

NASA Astrophysics Data System (ADS)

Vyas, Manan

2017-12-01

We study analytically and numerically the non-equilibrium dynamics of an isolated interacting many-body quantum system following a random quench. We model the system Hamiltonian by Embedded Gaussian Orthogonal Ensemble (EGOE) of random matrices with one plus few-body interactions for fermions. EGOE are paradigmatic models to study the crossover from integrability to chaos in interacting many-body quantum systems. We obtain a generic formulation, based on spectral variances, for describing relaxation dynamics of survival probabilities as a function of rank of interactions. Our analytical results are in good agreement with numerics.

The McLuhan Global Classroom: A Singapore-U.S. One-Year Instructional Interaction.

ERIC Educational Resources Information Center

Aune, Adonica Schultz; Lim, Dan

WebCT was integrated and modeled in a global Instructional Technology (IT) Certification Summer Institute offered through the University of Minnesota. Courses were first introduced with an on-site certification where technology integration was modeled in each course through the use of highly interactive web-based learning applications and games…

Physical Foundations for Socio-Economic Modeling for Transportation Planning : Part 1. Interaction Between Urban Centers as a Potential Process.

DOT National Transportation Integrated Search

1977-09-01

The objective of this research is to make use of a physically based social system model to study the determinants of city sizes and their interactions in a nation. In particular, it was required that attention be paid to how new transportation system...

GRASP - A Prototype Interactive Graphic Sawing Program - (Forest Products Journal)

Treesearch

Luis G. Occeña; Daniel L. Schmoldt

1996-01-01

A versatile microcomputer-based interactive graphics sawing program has been developed as a tool for modeling various hardwood processes, from bucking and topping to log sawing, lumber edging, secondary processing, and even veneering. The microcomputer platform makes the tool affordable and accessible. A solid modeling basis provides the tool with a sound geometrical...

GRASP - A Prototype Interactive Graphic Sawing Program - (MU-IE Technical Report)

Treesearch

Luis G. Occeña; Daniel L. Schmoldt

1995-01-01

A versatile microcomputer-based interactive graphics program has been developed as a tool for modeling various hardwood processes, from bucking and topping to log sawing, lumber edging, secondary processing, even veneering. The microcomputer platform makes the tool affordable and accessible.A solid modeling basis provides the tool with a sound geometrical and...

Neutron Reflectivity as a Tool for Physics-Based Studies of Model Bacterial Membranes.

PubMed

Barker, Robert D; McKinley, Laura E; Titmuss, Simon

2016-01-01

The principles of neutron reflectivity and its application as a tool to provide structural information at the (sub-) molecular unit length scale from models for bacterial membranes are described. The model membranes can take the form of a monolayer for a single leaflet spread at the air/water interface, or bilayers of increasing complexity at the solid/liquid interface. Solid-supported bilayers constrain the bilayer to 2D but can be used to characterize interactions with antimicrobial peptides and benchmark high throughput lab-based techniques. Floating bilayers allow for membrane fluctuations, making the phase behaviour more representative of native membranes. Bilayers of varying levels of compositional accuracy can now be constructed, facilitating studies with aims that range from characterizing the fundamental physical interactions, through to the characterization of accurate mimetics for the inner and outer membranes of Gram-negative bacteria. Studies of the interactions of antimicrobial peptides with monolayer and bilayer models for the inner and outer membranes have revealed information about the molecular control of the outer membrane permeability, and the mode of interaction of antimicrobials with both inner and outer membranes.

Finding shared decisions in stakeholder networks: An agent-based approach

NASA Astrophysics Data System (ADS)

Le Pira, Michela; Inturri, Giuseppe; Ignaccolo, Matteo; Pluchino, Alessandro; Rapisarda, Andrea

2017-01-01

We address the problem of a participatory decision-making process where a shared priority list of alternatives has to be obtained while avoiding inconsistent decisions. An agent-based model (ABM) is proposed to mimic this process in different social networks of stakeholders who interact according to an opinion dynamics model. Simulations' results show the efficacy of interaction in finding a transitive and, above all, shared decision. These findings are in agreement with real participation experiences regarding transport planning decisions and can give useful suggestions on how to plan an effective participation process for sustainable policy-making based on opinion consensus.

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.

Nonlinear complexity of random visibility graph and Lempel-Ziv on multitype range-intensity interacting financial dynamics

NASA Astrophysics Data System (ADS)

Zhang, Yali; Wang, Jun

2017-09-01

In an attempt to investigate the nonlinear complex evolution of financial dynamics, a new financial price model - the multitype range-intensity contact (MRIC) financial model, is developed based on the multitype range-intensity interacting contact system, in which the interaction and transmission of different types of investment attitudes in a stock market are simulated by viruses spreading. Two new random visibility graph (VG) based analyses and Lempel-Ziv complexity (LZC) are applied to study the complex behaviors of return time series and the corresponding random sorted series. The VG method is the complex network theory, and the LZC is a non-parametric measure of complexity reflecting the rate of new pattern generation of a series. In this work, the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, the numerical empirical study shows the similar complexity behaviors between the model and the real markets, the research confirms that the financial model is reasonable to some extent.

The Role of Multiphysics Simulation in Multidisciplinary Analysis

NASA Technical Reports Server (NTRS)

Rifai, Steven M.; Ferencz, Robert M.; Wang, Wen-Ping; Spyropoulos, Evangelos T.; Lawrence, Charles; Melis, Matthew E.

1998-01-01

This article describes the applications of the Spectrum(Tm) Solver in Multidisciplinary Analysis (MDA). Spectrum, a multiphysics simulation software based on the finite element method, addresses compressible and incompressible fluid flow, structural, and thermal modeling as well as the interaction between these disciplines. Multiphysics simulation is based on a single computational framework for the modeling of multiple interacting physical phenomena. Interaction constraints are enforced in a fully-coupled manner using the augmented-Lagrangian method. Within the multiphysics framework, the finite element treatment of fluids is based on Galerkin-Least-Squares (GLS) method with discontinuity capturing operators. The arbitrary-Lagrangian-Eulerian method is utilized to account for deformable fluid domains. The finite element treatment of solids and structures is based on the Hu-Washizu variational principle. The multiphysics architecture lends itself naturally to high-performance parallel computing. Aeroelastic, propulsion, thermal management and manufacturing applications are presented.

3D-QSAR studies of some reversible Acetyl cholinesterase inhibitors based on CoMFA and ligand protein interaction fingerprints using PC-LS-SVM and PLS-LS-SVM.

PubMed

Ghafouri, Hamidreza; Ranjbar, Mohsen; Sakhteman, Amirhossein

2017-08-01

A great challenge in medicinal chemistry is to develop different methods for structural design based on the pattern of the previously synthesized compounds. In this study two different QSAR methods were established and compared for a series of piperidine acetylcholinesterase inhibitors. In one novel approach, PC-LS-SVM and PLS-LS-SVM was used for modeling 3D interaction descriptors, and in the other method the same nonlinear techniques were used to build QSAR equations based on field descriptors. Different validation methods were used to evaluate the models and the results revealed the more applicability and predictive ability of the model generated by field descriptors (Q 2 LOO-CV =1, R 2 ext =0.97). External validation criteria revealed that both methods can be used in generating reasonable QSAR models. It was concluded that due to ability of interaction descriptors in prediction of binding mode, using this approach can be implemented in future 3D-QSAR softwares. Copyright © 2017 Elsevier Ltd. All rights reserved.

Radiation doses and neutron irridation effects on human cells based on calculations

NASA Astrophysics Data System (ADS)

Radojevic, B. B.; Cukavac, M.; Jovanovic, D.

In general, main aim of our paper is to follow influence of neutron's radiation on materials, but one of possible applications of fast neutrons in therapeutical reasons i.e. their influence on carcinom cells of difficuilt geometries in human bodies too. Interactions between neutrons and human cells of tissue are analysed here. We know that the light nuclei of hydrogen, nitrogen, carbon, and oxygen are main constituents of human cells, and that different nuclear models are usually used to present interactions of nuclear particles with mentioned elements. Some of most widely used pre-equilibrium nuclear models are: intranuclear cascade model (ICN), Harp-Miller-Berne (HMB), geometry-dependent hybrid (GDH) and exciton models (EM). In this paper is studied and calculated the primary energetic spectra of the secundary particles (neutrons, protons, and gamas) emitted from this interactions, and followed by corresponding integral cross sections, based on exciton model (EM). The total emission cross-section is the sum of emissions in all stages of energies. Obtained spectra for interactions type of (n, n'), (n, p), and (n, ?), for various incident neutron energies in the interval from 3 MeV up to 30 MeV are analysed too. Some results of calculations are presented here.

Polyelectrolyte properties of single stranded DNA measured using SAXS and single molecule FRET: beyond the wormlike chain model

PubMed Central

Meisburger, Steve P.; Sutton, Julie L.; Chen, Huimin; Pabit, Suzette A.; Kirmizialtin, Serdal; Elber, Ron; Pollack, Lois

2013-01-01

Nucleic acids are highly charged polyelectrolytes that interact strongly with salt ions. Rigid, base-paired regions are successfully described with worm like chain models, but non base-paired single stranded regions have fundamentally different polymer properties because of their greater flexibility. Recently, attention has turned to single stranded nucleic acids due to the growing recognition of their biological importance, as well as the availability of sophisticated experimental techniques sensitive to the conformation of individual molecules. We investigate polyelectrolyte properties of poly(dT), an important and widely studied model system for flexible single stranded nucleic acids, in physiologically important mixed mono- and di-valent salt. We report measurements of the form factor and interparticle interactions using SAXS, end to end distances using smFRET, and number of excess ions using ASAXS. We present a coarse-grained model that accounts for flexibility, excluded volume, and electrostatic interactions in these systems. Predictions of the model are validated against experiment. We also discuss the state of all-atom, explicit solvent Molecular Dynamics simulations of poly(dT), the next step in understanding the complexities of ion interactions with these highly charged and flexible polymers. PMID:23606337

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

PubMed Central

Dinh, Thanh; Kim, Younghan

2016-01-01

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud. PMID:27367689

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud.

PubMed

Dinh, Thanh; Kim, Younghan

2016-06-28

This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud.

Physiologically-Based Pharmacokinetic Modeling of Macitentan: Prediction of Drug-Drug Interactions.

PubMed

de Kanter, Ruben; Sidharta, Patricia N; Delahaye, Stéphane; Gnerre, Carmela; Segrestaa, Jerome; Buchmann, Stephan; Kohl, Christopher; Treiber, Alexander

2016-03-01

Macitentan is a novel dual endothelin receptor antagonist for the treatment of pulmonary arterial hypertension (PAH). It is metabolized by cytochrome P450 (CYP) enzymes, mainly CYP3A4, to its active metabolite ACT-132577. A physiological-based pharmacokinetic (PBPK) model was developed by combining observations from clinical studies and physicochemical parameters as well as absorption, distribution, metabolism and excretion parameters determined in vitro. The model predicted the observed pharmacokinetics of macitentan and its active metabolite ACT-132577 after single and multiple dosing. It performed well in recovering the observed effect of the CYP3A4 inhibitors ketoconazole and cyclosporine, and the CYP3A4 inducer rifampicin, as well as in predicting interactions with S-warfarin and sildenafil. The model was robust enough to allow prospective predictions of macitentan-drug combinations not studied, including an alternative dosing regimen of ketoconazole and nine other CYP3A4-interacting drugs. Among these were the HIV drugs ritonavir and saquinavir, which were included because HIV infection is a known risk factor for the development of PAH. This example of the application of PBPK modeling to predict drug-drug interactions was used to support the labeling of macitentan (Opsumit).

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

NASA Technical Reports Server (NTRS)

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

1982-01-01

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

The Development of Interactive Mathematics Learning Material Based on Local Wisdom with .swf Format

NASA Astrophysics Data System (ADS)

Abadi, M. K.; Asih, E. C. M.; Jupri, A.

2018-05-01

Learning materials used by students and schools in Serang district are lacking because they do not contain local wisdom content. The aim of this study is to improve the deficiencies in learning materials used by students by making interactive materials based on local wisdom content with format .swf. The method in this research is research and development (RnD) with ADDIE model. In making this interactive learning materials in accordance with the stages of the ADDIE study. The results of this study include interactive learning materials based on local wisdom. This learning material is suitable for digital students.

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.

An interactive modeling program for the generation of planar polygons for boundary type solids representations of wire frame models

NASA Technical Reports Server (NTRS)

Ozsoy, T.; Ochs, J. B.

1984-01-01

The development of a general link between three dimensional wire frame models and rigid solid models is discussed. An interactive computer graphics program was developed to serve as a front end to an algorithm (COSMIC Program No. ARC-11446) which offers a general solution to the hidden line problem where the input data is either line segments of n-sided planar polygons of the most general type with internal boundaries. The program provides a general interface to CAD/CAM data bases and is implemented for models created on the Unigraphics VAX 11/780-based CAD/CAM systems with the display software written for DEC's VS11 color graphics devices.

Multi-Physics MRI-Based Two-Layer Fluid-Structure Interaction Anisotropic Models of Human Right and Left Ventricles with Different Patch Materials: Cardiac Function Assessment and Mechanical Stress Analysis

PubMed Central

Tang, Dalin; Yang, Chun; Geva, Tal; Gaudette, Glenn; del Nido, Pedro J.

2011-01-01

Multi-physics right and left ventricle (RV/LV) fluid-structure interaction (FSI) models were introduced to perform mechanical stress analysis and evaluate the effect of patch materials on RV function. The FSI models included three different patch materials (Dacron scaffold, treated pericardium, and contracting myocardium), two-layer construction, fiber orientation, and active anisotropic material properties. The models were constructed based on cardiac magnetic resonance (CMR) images acquired from a patient with severe RV dilatation and solved by ADINA. Our results indicate that the patch model with contracting myocardium leads to decreased stress level in the patch area, improved RV function and patch area contractility. PMID:21765559

Punctuated equilibrium dynamics in human communications

NASA Astrophysics Data System (ADS)

Peng, Dan; Han, Xiao-Pu; Wei, Zong-Wen; Wang, Bing-Hong

2015-10-01

A minimal model based on network incorporating individual interactions is proposed to study the non-Poisson statistical properties of human behavior: individuals in system interact with their neighbors, the probability of an individual acting correlates to its activity, and all the individuals involved in action will change their activities randomly. The model reproduces varieties of spatial-temporal patterns observed in empirical studies of human daily communications, providing insight into various human activities and embracing a range of realistic social interacting systems, particularly, intriguing bimodal phenomenon. This model bridges priority queueing theory and punctuated equilibrium dynamics, and our modeling and analysis is likely to shed light on non-Poisson phenomena in many complex systems.

CADDIS Volume 5. Causal Databases: Interactive Conceptual Diagrams (ICDs)

EPA Pesticide Factsheets

In Interactive Conceptual Diagram (ICD) section of CADDIS allows users to create conceptual model diagrams, search a literature-based evidence database, and then attach that evidence to their diagrams.

Observation-Based Dissipation and Input Terms for Spectral Wave Models, with End-User Testing

DTIC Science & Technology

2014-09-30

scale influence of the Great barrier reef matrix on wave attenuation, Coral Reefs [published, refereed] Ghantous, M., and A.V. Babanin, 2014: One...Observation-Based Dissipation and Input Terms for Spectral Wave Models...functions, based on advanced understanding of physics of air-sea interactions, wave breaking and swell attenuation, in wave - forecast models. OBJECTIVES The

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

PubMed

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Inferring Interaction Force from Visual Information without Using Physical Force Sensors.

PubMed

Hwang, Wonjun; Lim, Soo-Chul

2017-10-26

In this paper, we present an interaction force estimation method that uses visual information rather than that of a force sensor. Specifically, we propose a novel deep learning-based method utilizing only sequential images for estimating the interaction force against a target object, where the shape of the object is changed by an external force. The force applied to the target can be estimated by means of the visual shape changes. However, the shape differences in the images are not very clear. To address this problem, we formulate a recurrent neural network-based deep model with fully-connected layers, which models complex temporal dynamics from the visual representations. Extensive evaluations show that the proposed learning models successfully estimate the interaction forces using only the corresponding sequential images, in particular in the case of three objects made of different materials, a sponge, a PET bottle, a human arm, and a tube. The forces predicted by the proposed method are very similar to those measured by force sensors.

Asymmetric Evolutionary Games

PubMed Central

McAvoy, Alex; Hauert, Christoph

2015-01-01

Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner’s Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games. PMID:26308326

Kinetic Models for Topological Nearest-Neighbor Interactions

NASA Astrophysics Data System (ADS)

Blanchet, Adrien; Degond, Pierre

2017-12-01

We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal and human behavior. Precisely, the system consists of a finite number of particles characterized by their positions and velocities. At random times a randomly chosen particle, the follower, adopts the velocity of its closest neighbor, the leader. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit kinetic equation is a non-standard spatial diffusion equation for the particle distribution function. We also study the case wherein the particles interact with their K closest neighbors and show that the corresponding kinetic equation is the same. Finally, we prove that these models can be seen as a singular limit of the smooth rank-based model previously studied in Blanchet and Degond (J Stat Phys 163:41-60, 2016). The proofs are based on a combinatorial interpretation of the rank as well as some concentration of measure arguments.

Construction of Interaction Layer on Socio-Environmental Simulation

NASA Astrophysics Data System (ADS)

Torii, Daisuke; Ishida, Toru

In this study, we propose a method to construct a system based on a legacy socio-environmental simulator which enables to design more realistic interaction models in socio-environmetal simulations. First, to provide a computational model suitable for agent interactions, an interaction layer is constructed and connected from outside of a legacy socio-environmental simulator. Next, to configure the agents interacting ability, connection description for controlling the flow of information in the connection area is provided. As a concrete example, we realized an interaction layer by Q which is a scenario description language and connected it to CORMAS, a socio-envirionmental simulator. Finally, we discuss the capability of our method, using the system, in the Fire-Fighter domain.

Fragment and knowledge-based design of selective GSK-3beta inhibitors using virtual screening models.

PubMed

Vadivelan, S; Sinha, Barij Nayan; Tajne, Sunita; Jagarlapudi, Sarma A R P

2009-06-01

Glycogen Synthase Kinase 3beta is one of the important targets in the treatment of type II diabetes and Alzheimer's disease. Currently this target is in pursuit for type II diabetes and a few GSK-3beta inhibitors have been now advanced to Phases I and II of clinical trials. The best validated HypoGen model consists of four pharmacophore features; 1) two hydrogen bond acceptors, 2) one hydrogen bond donor and 3) one hydrophobic. This pharmacophore model correlates well with the docking model, one hydrogen bond acceptor is necessary for the H-bond interaction with VAL135, and second hydrogen bond acceptor is important for the H-bond interactions with ARG141 and the hydrophobic feature may be required for the weak H-bond interactions with ASP133. The comparative model was developed from analogue and structure-based models like Catalyst, Glide SP & XP, Gold Fitness & ChemScore and Ligand Fit using multiple linear regression analysis. A virtual library of 10,000 molecules was generated employing fragment and knowledge-based approach and the comparative model was used to predict the activities of these molecules. The H-bond with ARG141 appears to be unique to GSK-3beta and explains the high GSK-3beta selectivity observed for 1H-Quinazolin-4-ones and Benzo[e][1,3]oxazin-4-ones. This understanding of protein-ligand interactions and molecular recognition increases the rapid development of potent and selective inhibitors, and also helps to eliminate the increase in number of false positives and negatives.

Hospital's activity-based financing system and manager-physician [corrected] interaction.

PubMed

Crainich, David; Leleu, Hervé; Mauleon, Ana

2011-10-01

This paper examines the consequences of the introduction of an activity-based reimbursement system on the behavior of physicians and hospital's managers. We consider a private for-profit sector where both hospitals and physicians are initially paid on a fee-for-service basis. We show that the benefit of the introduction of an activity-based system depends on the type of interaction between managers and physicians (simultaneous or sequential decision-making games). It is shown that, under the activity-based system, a sequential interaction with physician leader could be beneficial for both agents in the private sector. We further model an endogenous timing game à la Hamilton and Slutsky (Games Econ Behav 2: 29-46, 1990) in which the type of interaction is determined endogenously. We show that, under the activity-based system, the sequential interaction with physician leader is the unique subgame perfect equilibrium.

Interaction with Machine Improvisation

NASA Astrophysics Data System (ADS)

Assayag, Gerard; Bloch, George; Cont, Arshia; Dubnov, Shlomo

We describe two multi-agent architectures for an improvisation oriented musician-machine interaction systems that learn in real time from human performers. The improvisation kernel is based on sequence modeling and statistical learning. We present two frameworks of interaction with this kernel. In the first, the stylistic interaction is guided by a human operator in front of an interactive computer environment. In the second framework, the stylistic interaction is delegated to machine intelligence and therefore, knowledge propagation and decision are taken care of by the computer alone. The first framework involves a hybrid architecture using two popular composition/performance environments, Max and OpenMusic, that are put to work and communicate together, each one handling the process at a different time/memory scale. The second framework shares the same representational schemes with the first but uses an Active Learning architecture based on collaborative, competitive and memory-based learning to handle stylistic interactions. Both systems are capable of processing real-time audio/video as well as MIDI. After discussing the general cognitive background of improvisation practices, the statistical modelling tools and the concurrent agent architecture are presented. Then, an Active Learning scheme is described and considered in terms of using different improvisation regimes for improvisation planning. Finally, we provide more details about the different system implementations and describe several performances with the system.

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

PubMed Central

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

2018-01-01

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

Microstructure-sensitive Crystal Viscoplasticity for Ni-base Superalloys Targeting Long-term Creep-Fatigue Interaction Modeling

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

Neu, Richard W.

The aim of this project is to develop a microstructure-sensitive crystal viscoplasticity (CVP) model for single-crystal Ni-base superalloys to model the behavior of the material and components in the hot gas path sections of industrial gas turbines (IGT). Microstructure degradation associated with aging critical to predicting long-term creep-fatigue interactions will be embedded into the model through the γ' precipitate morphology evolution by coupling the coarsening drivers and kinetics into the constitutive equations of the CVP model. Model parameters will be determined using new experimental protocols that involve systematically artificially aging the alloy under different stress conditions to determine the relationshipmore » between the size and morphology g' precipitates on the creep and thermomechanical fatigue response.« less

Microstructure-sensitive Crystal Viscoelasticity for Ni-base Superalloys Targeting Long-term Creep-Fatigue Interaction Modeling

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

Neu, Richard W

The aim of this project is to develop a microstructure-sensitive crystal viscoplasticity (CVP) model for single-crystal Ni-base superalloys to model the behavior of the material and components in the hot gas path sections of industrial gas turbines (IGT). Microstructure degradation associated with aging critical to predicting long-term creep-fatigue interactions will be embedded into the model through the γ' precipitate morphology evolution by coupling the coarsening drivers and kinetics into the constitutive equations of the CVP model. Model parameters will be determined using new experimental protocols that involve systematically artificially aging the alloy under different stress conditions to determine the relationshipmore » between the size and morphology g' precipitates on the creep and thermomechanical fatigue response.« less

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.

Games network and application to PAs system.

PubMed

Chettaoui, C; Delaplace, F; Manceny, M; Malo, M

2007-02-01

In this article, we present a game theory based framework, named games network, for modeling biological interactions. After introducing the theory, we more precisely describe the methodology to model biological interactions. Then we apply it to the plasminogen activator system (PAs) which is a signal transduction pathway involved in cancer cell migration. The games network theory extends game theory by including the locality of interactions. Each game in a games network represents local interactions between biological agents. The PAs system is implicated in cytoskeleton modifications via regulation of actin and microtubules, which in turn favors cell migration. The games network model has enabled us a better understanding of the regulation involved in the PAs system.

A Serious Look at the 4MAT Model.

ERIC Educational Resources Information Center

Scott, Harry V.

4MAT is an 8-step, sequential instructional model based on two theoretical constructs: Kolb's model of learning styles and the concept of brain hemisphericity. The model, developed by B. McCarthy (1987), is derived by interacting each of Kolb's four quadrants with both left and right brain. Kolb outlined four learning styles based on the four…

Modeling interactions between a β-O-4 type lignin model compound and 1-allyl-3-methylimidazolium chloride ionic liquid.

PubMed

Zhu, Youtao; Yan, Jing; Liu, Chengbu; Zhang, Dongju

2017-08-01

Aiming at understanding the molecular mechanism of the lignin dissolution in imidazolium-based ionic liquids (ILs), this work presents a combined quantum chemistry (QC) calculation and molecular dynamics (MD) simulation study on the interaction of the lignin model compound, veratrylglycerol-β-guaiacyl ether (VG) with 1-allyl-3-methylimidazolium chloride ([Amim]Cl). The monomer of VG is shown to feature a strong intramolecular hydrogen bond, and its dimer is indicated to present important π-π stacking and intermolecular hydrogen bonding interactions. The interactions of both the cation and anion of [Amim]Cl with VG are shown to be stronger than that between the two monomers, indicating that [Amim]Cl is capable of dissolving lignin. While Cl - anion forms a hydrogen-bonded complex with VG, the imidazolium cation interacts with VG via both the π-π stacking and intermolecular hydrogen bonding. The calculated interaction energies between VG and the IL or its components (the cation, anion, and ion pair) indicate the anion plays a more important role than the cation for the dissolution of lignin in the IL. Theoretical results provide help for understanding the molecular mechanism of lignin dissolution in imidazolium-based IL. The theoretical calculations on the interaction between the lignin model compound and [Amim]Cl ionic liquid indicate that the anion of [Amim]Cl plays a more important role for lignin dissolution although the cation also makes a substantial contribution. © 2017 Wiley Periodicals, Inc.

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

Creating COMFORT: A Communication-Based Model for Breaking Bad News

ERIC Educational Resources Information Center

Villagran, Melinda; Goldsmith, Joy; Wittenberg-Lyles, Elaine; Baldwin, Paula

2010-01-01

This study builds upon existing protocols for breaking bad news (BBN), and offers an interaction-based approach to communicating comfort to patients and their families. The goal was to analyze medical students' (N = 21) videotaped standardized patient BBN interactions after completing an instructional unit on a commonly used BBN protocol, commonly…

Agent-based paradigm for integration of interactive cable television operations and business support systems

NASA Astrophysics Data System (ADS)

Wattawa, Scott

1995-11-01

Offering interactive services and data in a hybrid fiber/coax cable system requires the coordination of a host of operations and business support systems. New service offerings and network growth and evolution create never-ending changes in the network infrastructure. Agent-based enterprise models provide a flexible mechanism for systems integration of service and support systems. Agent models also provide a mechanism to decouple interactive services from network architecture. By using the Java programming language, agents may be made safe, portable, and intelligent. This paper investigates the application of the Object Management Group's Common Object Request Brokering Architecture to the integration of a multiple services metropolitan area network.

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.

Physics-based interactive volume manipulation for sharing surgical process.

PubMed

Nakao, Megumi; Minato, Kotaro

2010-05-01

This paper presents a new set of techniques by which surgeons can interactively manipulate patient-specific volumetric models for sharing surgical process. To handle physical interaction between the surgical tools and organs, we propose a simple surface-constraint-based manipulation algorithm to consistently simulate common surgical manipulations such as grasping, holding and retraction. Our computation model is capable of simulating soft-tissue deformation and incision in real time. We also present visualization techniques in order to rapidly visualize time-varying, volumetric information on the deformed image. This paper demonstrates the success of the proposed methods in enabling the simulation of surgical processes, and the ways in which this simulation facilitates preoperative planning and rehearsal.

Integrated Turbine-Based Combined Cycle Dynamic Simulation Model

NASA Technical Reports Server (NTRS)

Haid, Daniel A.; Gamble, Eric J.

2011-01-01

A Turbine-Based Combined Cycle (TBCC) dynamic simulation model has been developed to demonstrate all modes of operation, including mode transition, for a turbine-based combined cycle propulsion system. The High Mach Transient Engine Cycle Code (HiTECC) is a highly integrated tool comprised of modules for modeling each of the TBCC systems whose interactions and controllability affect the TBCC propulsion system thrust and operability during its modes of operation. By structuring the simulation modeling tools around the major TBCC functional modes of operation (Dry Turbojet, Afterburning Turbojet, Transition, and Dual Mode Scramjet) the TBCC mode transition and all necessary intermediate events over its entire mission may be developed, modeled, and validated. The reported work details the use of the completed model to simulate a TBCC propulsion system as it accelerates from Mach 2.5, through mode transition, to Mach 7. The completion of this model and its subsequent use to simulate TBCC mode transition significantly extends the state-of-the-art for all TBCC modes of operation by providing a numerical simulation of the systems, interactions, and transient responses affecting the ability of the propulsion system to transition from turbine-based to ramjet/scramjet-based propulsion while maintaining constant thrust.

3D interactive augmented reality-enhanced digital learning systems for mobile devices

NASA Astrophysics Data System (ADS)

Feng, Kai-Ten; Tseng, Po-Hsuan; Chiu, Pei-Shuan; Yang, Jia-Lin; Chiu, Chun-Jie

2013-03-01

With enhanced processing capability of mobile platforms, augmented reality (AR) has been considered a promising technology for achieving enhanced user experiences (UX). Augmented reality is to impose virtual information, e.g., videos and images, onto a live-view digital display. UX on real-world environment via the display can be e ectively enhanced with the adoption of interactive AR technology. Enhancement on UX can be bene cial for digital learning systems. There are existing research works based on AR targeting for the design of e-learning systems. However, none of these work focuses on providing three-dimensional (3-D) object modeling for en- hanced UX based on interactive AR techniques. In this paper, the 3-D interactive augmented reality-enhanced learning (IARL) systems will be proposed to provide enhanced UX for digital learning. The proposed IARL systems consist of two major components, including the markerless pattern recognition (MPR) for 3-D models and velocity-based object tracking (VOT) algorithms. Realistic implementation of proposed IARL system is conducted on Android-based mobile platforms. UX on digital learning can be greatly improved with the adoption of proposed IARL systems.

Interactive Acoustic Simulation in Urban and Complex Environments

DTIC Science & Technology

2015-03-21

and validity of the solution given by the two methods. Transfer functions are used to model two-way couplings to allow multiple orders of acoustic...Function ( BRDF )[79, 137]. The ray models have also been applied to inhomogeneous outdoor media by numerical integration of the differential ray...surface, the interaction can be modeled by specular reflection, Snell’s law refraction, or BRDF -based reflection, depending on the surface properties

A Hybrid Physics-Based Data-Driven Approach for Point-Particle Force Modeling

NASA Astrophysics Data System (ADS)

Moore, Chandler; Akiki, Georges; Balachandar, S.

2017-11-01

This study improves upon the physics-based pairwise interaction extended point-particle (PIEP) model. The PIEP model leverages a physical framework to predict fluid mediated interactions between solid particles. While the PIEP model is a powerful tool, its pairwise assumption leads to increased error in flows with high particle volume fractions. To reduce this error, a regression algorithm is used to model the differences between the current PIEP model's predictions and the results of direct numerical simulations (DNS) for an array of monodisperse solid particles subjected to various flow conditions. The resulting statistical model and the physical PIEP model are superimposed to construct a hybrid, physics-based data-driven PIEP model. It must be noted that the performance of a pure data-driven approach without the model-form provided by the physical PIEP model is substantially inferior. The hybrid model's predictive capabilities are analyzed using more DNS. In every case tested, the hybrid PIEP model's prediction are more accurate than those of physical PIEP model. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1315138 and the U.S. DOE, NNSA, ASC Program, as a Cooperative Agreement under Contract No. DE-NA0002378.

Influence of grain boundaries on the distribution of components in binary alloys

NASA Astrophysics Data System (ADS)

L'vov, P. E.; Svetukhin, V. V.

2017-12-01

Based on the free-energy density functional method (the Cahn-Hilliard equation), a phenomenological model that describes the influence of grain boundaries on the distribution of components in binary alloys has been developed. The model is built on the assumption of the difference between the interaction parameters of solid solution components in the bulk and at the grain boundary. The difference scheme based on the spectral method is proposed to solve the Cahn-Hilliard equation with interaction parameters depending on coordinates. Depending on the ratio between the interaction parameters in the bulk and at the grain boundary, temperature, and alloy composition, the model can give rise to different types of distribution of a dissolved component, namely, either depletion or enrichment of the grain-boundary area, preferential grainboundary precipitation, competitive precipitation in the bulk and at the grain boundary, etc.

The Effects of Web-Based Interactive Virtual Tours on the Development of Prospective Mathematics Teachers' Spatial Skills

ERIC Educational Resources Information Center

Kurtulus, Aytac

2013-01-01

The aim of this study was to investigate the effects of web-based interactive virtual tours on the development of prospective mathematics teachers' spatial skills. The study was designed based on experimental method. The "one-group pre-test post-test design" of this method was taken as the research model. The study was conducted with 3rd year…

An Assessment of Phylogenetic Tools for Analyzing the Interplay Between Interspecific Interactions and Phenotypic Evolution.

PubMed

Drury, J P; Grether, G F; Garland, T; Morlon, H

2018-05-01

Much ecological and evolutionary theory predicts that interspecific interactions often drive phenotypic diversification and that species phenotypes in turn influence species interactions. Several phylogenetic comparative methods have been developed to assess the importance of such processes in nature; however, the statistical properties of these methods have gone largely untested. Focusing mainly on scenarios of competition between closely-related species, we assess the performance of available comparative approaches for analyzing the interplay between interspecific interactions and species phenotypes. We find that many currently used statistical methods often fail to detect the impact of interspecific interactions on trait evolution, that sister-taxa analyses are particularly unreliable in general, and that recently developed process-based models have more satisfactory statistical properties. Methods for detecting predictors of species interactions are generally more reliable than methods for detecting character displacement. In weighing the strengths and weaknesses of different approaches, we hope to provide a clear guide for empiricists testing hypotheses about the reciprocal effect of interspecific interactions and species phenotypes and to inspire further development of process-based models.

Application of Molecular Interaction Volume Model for Phase Equilibrium of Sn-Based Binary System in Vacuum Distillation

NASA Astrophysics Data System (ADS)

Kong, Lingxin; Yang, Bin; Xu, Baoqiang; Li, Yifu

2014-09-01

Based on the molecular interaction volume model (MIVM), the activities of components of Sn-Sb, Sb-Bi, Sn-Zn, Sn-Cu, and Sn-Ag alloys were predicted. The predicted values are in good agreement with the experimental data, which indicate that the MIVM is of better stability and reliability due to its good physical basis. A significant advantage of the MIVM lies in its ability to predict the thermodynamic properties of liquid alloys using only two parameters. The phase equilibria of Sn-Sb and Sn-Bi alloys were calculated based on the properties of pure components and the activity coefficients, which indicates that Sn-Sb and Sn-Bi alloys can be separated thoroughly by vacuum distillation. This study extends previous investigations and provides an effective and convenient model on which to base refining simulations for Sn-based alloys.

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

PubMed

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

2017-01-01

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

Constraint programming based biomarker optimization.

PubMed

Zhou, Manli; Luo, Youxi; Sun, Guoquan; Mai, Guoqin; Zhou, Fengfeng

2015-01-01

Efficient and intuitive characterization of biological big data is becoming a major challenge for modern bio-OMIC based scientists. Interactive visualization and exploration of big data is proven to be one of the successful solutions. Most of the existing feature selection algorithms do not allow the interactive inputs from users in the optimizing process of feature selection. This study investigates this question as fixing a few user-input features in the finally selected feature subset and formulates these user-input features as constraints for a programming model. The proposed algorithm, fsCoP (feature selection based on constrained programming), performs well similar to or much better than the existing feature selection algorithms, even with the constraints from both literature and the existing algorithms. An fsCoP biomarker may be intriguing for further wet lab validation, since it satisfies both the classification optimization function and the biomedical knowledge. fsCoP may also be used for the interactive exploration of bio-OMIC big data by interactively adding user-defined constraints for modeling.

A multiscale MD-FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure.

PubMed

Kojic, M; Milosevic, M; Kojic, N; Kim, K; Ferrari, M; Ziemys, A

2014-02-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts.

A multiscale MD–FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure

PubMed Central

Kojic, M.; Milosevic, M.; Kojic, N.; Kim, K.; Ferrari, M.; Ziemys, A.

2014-01-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts. PMID:24578582

Particle-based simulations of self-motile suspensions

NASA Astrophysics Data System (ADS)

Hinz, Denis F.; Panchenko, Alexander; Kim, Tae-Yeon; Fried, Eliot

2015-11-01

A simple model for simulating flows of active suspensions is investigated. The approach is based on dissipative particle dynamics. While the model is potentially applicable to a wide range of self-propelled particle systems, the specific class of self-motile bacterial suspensions is considered as a modeling scenario. To mimic the rod-like geometry of a bacterium, two dissipative particle dynamics particles are connected by a stiff harmonic spring to form an aggregate dissipative particle dynamics molecule. Bacterial motility is modeled through a constant self-propulsion force applied along the axis of each such aggregate molecule. The model accounts for hydrodynamic interactions between self-propelled agents through the pairwise dissipative interactions conventional to dissipative particle dynamics. Numerical simulations are performed using a customized version of the open-source software package LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) software package. Detailed studies of the influence of agent concentration, pairwise dissipative interactions, and Stokes friction on the statistics of the system are provided. The simulations are used to explore the influence of hydrodynamic interactions in active suspensions. For high agent concentrations in combination with dominating pairwise dissipative forces, strongly correlated motion patterns and a fluid-like spectral distributions of kinetic energy are found. In contrast, systems dominated by Stokes friction exhibit weaker spatial correlations of the velocity field. These results indicate that hydrodynamic interactions may play an important role in the formation of spatially extended structures in active suspensions.

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

PubMed

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

2017-01-02

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

Full-wave and ray-based modeling of cross-beam energy transfer between laser beams with distributed phase plates and polarization smoothing

DOE PAGES

Follett, R. K.; Edgell, D. H.; Froula, D. H.; ...

2017-10-20

Radiation-hydrodynamic simulations of inertial confinement fusion (ICF) experiments rely on ray-based cross-beam energy transfer (CBET) models to calculate laser energy deposition. The ray-based models assume locally plane-wave laser beams and polarization averaged incoherence between laser speckles for beams with polarization smoothing. The impact of beam speckle and polarization smoothing on crossbeam energy transfer (CBET) are studied using the 3-D wave-based laser-plasma-interaction code LPSE. The results indicate that ray-based models under predict CBET when the assumption of spatially averaged longitudinal incoherence across the CBET interaction region is violated. A model for CBET between linearly-polarized speckled beams is presented that uses raymore » tracing to solve for the real speckle pattern of the unperturbed laser beams within the eikonal approximation and gives excellent agreement with the wavebased calculations. Lastly, OMEGA-scale 2-D LPSE calculations using ICF relevant plasma conditions suggest that the impact of beam speckle on laser absorption calculations in ICF implosions is small (< 1%).« less

Full-wave and ray-based modeling of cross-beam energy transfer between laser beams with distributed phase plates and polarization smoothing

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

Follett, R. K.; Edgell, D. H.; Froula, D. H.

Radiation-hydrodynamic simulations of inertial confinement fusion (ICF) experiments rely on ray-based cross-beam energy transfer (CBET) models to calculate laser energy deposition. The ray-based models assume locally plane-wave laser beams and polarization averaged incoherence between laser speckles for beams with polarization smoothing. The impact of beam speckle and polarization smoothing on crossbeam energy transfer (CBET) are studied using the 3-D wave-based laser-plasma-interaction code LPSE. The results indicate that ray-based models under predict CBET when the assumption of spatially averaged longitudinal incoherence across the CBET interaction region is violated. A model for CBET between linearly-polarized speckled beams is presented that uses raymore » tracing to solve for the real speckle pattern of the unperturbed laser beams within the eikonal approximation and gives excellent agreement with the wavebased calculations. Lastly, OMEGA-scale 2-D LPSE calculations using ICF relevant plasma conditions suggest that the impact of beam speckle on laser absorption calculations in ICF implosions is small (< 1%).« less

Focusing on Interactions between Content and Cognition: A New Perspective on Gender Differences in Mathematical Sub-Competencies

ERIC Educational Resources Information Center

George, Ann Cathrice; Robitzsch, Alexander

2018-01-01

This article presents a new perspective on measuring gender differences in the large-scale assessment study Trends in International Science Study (TIMSS). The suggested empirical model is directly based on the theoretical competence model of the domain mathematics and thus includes the interaction between content and cognitive sub-competencies.…

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…

Engaging Fans and the Community in Social Media: Interaction with Institutions of Higher Education on Facebook

ERIC Educational Resources Information Center

Brech, Felicitas M.; Messer, Uwe; Vander Schee, Brian A.; Rauschnabel, Philipp A.; Ivens, Bjoern S.

2017-01-01

Although many universities use social media to interact with stakeholders, little is known about the underlying mechanisms. Drawing on theories of self-presentation and community engagement, we develop a theoretical model to explain these crucial outcome factors. We then test the model based on secondary data from 159 universities. Our findings…

CHEMFLO-2000: INTERACTIVE SOFTWARE FOR PREDICTING AND VISUALIZING TRANSIENT WATER AND CHEMICAL MOVEMENT IN SOILS AND ASSOCIATED UNCERTAINTIES

EPA Science Inventory

An interactive Java applet and a stand-alone application program will be developed based on the CHEMFLO model developed in the mid-1980s and published as an EPA report (EPA/600/8-89/076). The model solves Richards Equation for transient water movement in unsaturated soils, and so...

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…

VISUALIZATION-BASED ANALYSIS FOR A MIXED-INHIBITION BINARY PBPK MODEL: DETERMINATION OF INHIBITION MECHANISM

EPA Science Inventory

A physiologically-based pharmacokinetic (PBPK) model incorporating mixed enzyme inhibition was used to determine mechanism of the metabolic interactions occurring during simultaneous inhalation exposures to the organic solvents chloroform and trichloroethylene (TCE).

V...

Using genome-wide measurements for computational prediction of SH2–peptide interactions

PubMed Central

Wunderlich, Zeba; Mirny, Leonid A.

2009-01-01

Peptide-recognition modules (PRMs) are used throughout biology to mediate protein–protein interactions, and many PRMs are members of large protein domain families. Recent genome-wide measurements describe networks of peptide–PRM interactions. In these networks, very similar PRMs recognize distinct sets of peptides, raising the question of how peptide-recognition specificity is achieved using similar protein domains. The analysis of individual protein complex structures often gives answers that are not easily applicable to other members of the same PRM family. Bioinformatics-based approaches, one the other hand, may be difficult to interpret physically. Here we integrate structural information with a large, quantitative data set of SH2 domain–peptide interactions to study the physical origin of domain–peptide specificity. We develop an energy model, inspired by protein folding, based on interactions between the amino-acid positions in the domain and peptide. We use this model to successfully predict which SH2 domains and peptides interact and uncover the positions in each that are important for specificity. The energy model is general enough that it can be applied to other members of the SH2 family or to new peptides, and the cross-validation results suggest that these energy calculations will be useful for predicting binding interactions. It can also be adapted to study other PRM families, predict optimal peptides for a given SH2 domain, or study other biological interactions, e.g. protein–DNA interactions. PMID:19502496

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.

Model of mobile agents for sexual interactions networks

NASA Astrophysics Data System (ADS)

González, M. C.; Lind, P. G.; Herrmann, H. J.

2006-02-01

We present a novel model to simulate real social networks of complex interactions, based in a system of colliding particles (agents). The network is build by keeping track of the collisions and evolves in time with correlations which emerge due to the mobility of the agents. Therefore, statistical features are a consequence only of local collisions among its individual agents. Agent dynamics is realized by an event-driven algorithm of collisions where energy is gained as opposed to physical systems which have dissipation. The model reproduces empirical data from networks of sexual interactions, not previously obtained with other approaches.

Inception of self-interacting dark matter with dark charge conjugation symmetry

DOE PAGES

Ma, Ernest

2017-07-04

A new understanding of the stability of self-interacting dark matter is pointed out, based on the simplest spontaneously broken Abelian gauge model with one complex scalar and one Dirac fermion. The key is the imposition of dark charge conjugation symmetry. It allows the possible existence of two stable particles: the Dirac fermion and the vector gauge boson which acts as a light mediator for the former's self-interaction. Since this light mediator does not decay, it avoids the strong cosmological constraints recently obtained for all such models where the light mediator decays into standard-model particles.

Mechanism-based pharmacokinetic modeling to evaluate transporter-enzyme interplay in drug interactions and pharmacogenetics of glyburide.

PubMed

Varma, Manthena V S; Scialis, Renato J; Lin, Jian; Bi, Yi-An; Rotter, Charles J; Goosen, Theunis C; Yang, Xin

2014-07-01

The purpose of this study is to characterize the involvement of hepato-biliary transport and cytochrome-P450 (CYP)-mediated metabolism in the disposition of glyburide and predict its pharmacokinetic variability due to drug interactions and genetic variations. Comprehensive in vitro studies suggested that glyburide is a highly permeable drug with substrate affinity to multiple efflux pumps and to organic anion transporting polypeptide (OATP)1B1 and OATP2B1. Active hepatic uptake was found to be significantly higher than the passive uptake clearance (15.8 versus 5.3 μL/min/10(6)-hepatocytes), using the sandwich-cultured hepatocyte model. In vitro, glyburide is metabolized (intrinsic clearance, 52.9 μL/min/mg-microsomal protein) by CYP3A4, CYP2C9, and CYP2C8 with fraction metabolism of 0.53, 0.36, and 0.11, respectively. Using these in vitro data, physiologically based pharmacokinetic models, assuming rapid-equilibrium between blood and liver compartments or permeability-limited hepatic disposition, were built to describe pharmacokinetics and evaluate drug interactions. Permeability-limited model successfully predicted glyburide interactions with rifampicin and other perpetrator drugs. Conversely, model assuming rapid-equilibrium mispredicted glyburide interactions, overall, suggesting hepatic uptake as the primary rate-determining process in the systemic clearance of glyburide. Further modeling and simulations indicated that the impairment of CYP2C9 function has a minimal effect on the systemic exposure, implying discrepancy in the contribution of CYP2C9 to glyburide clearance.

Improving the efficiency of a user-driven learning system with reconfigurable hardware. Application to DNA splicing.

PubMed

Lemoine, E; Merceron, D; Sallantin, J; Nguifo, E M

1999-01-01

This paper describes a new approach to problem solving by splitting up problem component parts between software and hardware. Our main idea arises from the combination of two previously published works. The first one proposed a conceptual environment of concept modelling in which the machine and the human expert interact. The second one reported an algorithm based on reconfigurable hardware system which outperforms any kind of previously published genetic data base scanning hardware or algorithms. Here we show how efficient the interaction between the machine and the expert is when the concept modelling is based on reconfigurable hardware system. Their cooperation is thus achieved with an real time interaction speed. The designed system has been partially applied to the recognition of primate splice junctions sites in genetic sequences.

New strategy for protein interactions and application to structure-based drug design

NASA Astrophysics Data System (ADS)

Zou, Xiaoqin

One of the greatest challenges in computational biophysics is to predict interactions between biological molecules, which play critical roles in biological processes and rational design of therapeutic drugs. Biomolecular interactions involve delicate interplay between multiple interactions, including electrostatic interactions, van der Waals interactions, solvent effect, and conformational entropic effect. Accurate determination of these complex and subtle interactions is challenging. Moreover, a biological molecule such as a protein usually consists of thousands of atoms, and thus occupies a huge conformational space. The large degrees of freedom pose further challenges for accurate prediction of biomolecular interactions. Here, I will present our development of physics-based theory and computational modeling on protein interactions with other molecules. The major strategy is to extract microscopic energetics from the information embedded in the experimentally-determined structures of protein complexes. I will also present applications of the methods to structure-based therapeutic design. Supported by NSF CAREER Award DBI-0953839, NIH R01GM109980, and the American Heart Association (Midwest Affiliate) [13GRNT16990076].

Emerging Models of the New Paradigm.

ERIC Educational Resources Information Center

Howser, Lee; Schwinn, Carole

Working with the Philadelphia-based Institute of Interactive Management, several teams at Jackson Community College (JCC), in Michigan, set out in 1994 to learn and apply an interactive design methodology to selected college subsystems. Interactive design begins with understanding problems faced by the system as a whole, which in the case of JCC…

A computational approach to climate science education with CLIMLAB

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2017-12-01

CLIMLAB is a Python-based software toolkit for interactive, process-oriented climate modeling for use in education and research. It is motivated by the need for simpler tools and more reproducible workflows with which to "fill in the gaps" between blackboard-level theory and the results of comprehensive climate models. With CLIMLAB you can interactively mix and match physical model components, or combine simpler process models together into a more comprehensive model. I use CLIMLAB in the classroom to put models in the hands of students (undergraduate and graduate), and emphasize a hierarchical, process-oriented approach to understanding the key emergent properties of the climate system. CLIMLAB is equally a tool for climate research, where the same needs exist for more robust, process-based understanding and reproducible computational results. I will give an overview of CLIMLAB and an update on recent developments, including: a full-featured, well-documented, interactive implementation of a widely-used radiation model (RRTM) packaging with conda-forge for compiler-free (and hassle-free!) installation on Mac, Windows and Linux interfacing with xarray for i/o and graphics with gridded model data a rich and growing collection of examples and self-computing lecture notes in Jupyter notebook format

Staging scientific controversies: a gallery test on science museums' interactivity.

PubMed

Yaneva, Albena; Rabesandratana, Tania Mara; Greiner, Birgit

2009-01-01

The "transfer" model in science communication has been addressed critically from different perspectives, while the advantages of the interactive model have been continuously praised. Yet, little is done to account for the specific role of the interactive model in communicating "unfinished science." The traditional interactive methods in museums are not sufficient to keep pace with rapid scientific developments. Interactive exchanges between laypeople and experts are thought mainly through the lens of a dialogue that is facilitated and framed by the traditional "conference room" architecture. Drawing on the results of a small-scale experiment in a gallery space, we argue for the need for a new "architecture of interaction" in museum settings based on art installation and simulation techniques, which will enhance the communication potentials of science museums and will provide conditions for a fruitful even-handed exchange of expert and lay knowledge.

Using the Constructivist Tridimensional Design Model for Online Continuing Education for Health Care Clinical Faculty

ERIC Educational Resources Information Center

Seo, Kay Kyeong-Ju; Engelhard, Chalee

2014-01-01

This article presents a new paradigm for continuing education of Clinical Instructors (CIs): the Constructivist Tridimensional (CTD) model for the design of an online curriculum. Based on problem-based learning, self-regulated learning, and adult learning theory, the CTD model was designed to facilitate interactive, collaborative, and authentic…

Emergent properties of climate-vegetation feedbacks in the North American Monsoon Macrosystem

NASA Astrophysics Data System (ADS)

Mathias, A.; Niu, G.; Zeng, X.

2012-12-01

The ability of ecosystems to adapt naturally to climate change and associated disturbances (e.g. wildfires, spread of invasive species) is greatly affected by the stability of feedback interactions between climate and vegetation. In order to study climate-vegetation interactions, such as CO2 and H2O exchange in the North American Monsoon System (NAMS), we plan to couple a community land surface model (NoahMP or CLM) used in regional climate models (WRF) with an individual based, spatially explicit vegetation model (ECOTONE). Individual based modeling makes it possible to link individual plant traits with properties of plant communities. Community properties, such as species composition and species distribution arise from dynamic interactions of individual plants with each other, and with their environment. Plants interact with each other through intra- and interspecific competition for resources (H2O, nitrogen), and the outcome of these interactions depends on the properties of the plant community and the environment itself. In turn, the environment is affected by the resulting change in community structure, which may have an impact on the drivers of climate change. First, we performed sensitivity tests of ECOTONE to assess its ability to reproduce vegetation distribution in the NAMS. We compared the land surface model and ECOTONE with regard to their capability to accurately simulate soil moisture, CO2 flux and above ground biomass. For evaluating the models we used the eddy-correlation sensible and latent heat fluxes, CO2 flux and observations of other climate and environmental variables (e.g. soil temperature and moisture) from the Santa Rita experimental range. The model intercomparison helped us understand the advantages and disadvantages of each model, providing us guidance for coupling the community land surface model (NoahMP or CLM) with ECOTONE.

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications.

PubMed

Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

2017-03-01

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model.

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications †

PubMed Central

Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

2017-01-01

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model. PMID:28257067

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.

Results of EAS characteristics calculations in the framework of the universal hadronic interaction model NEXUS

NASA Astrophysics Data System (ADS)

Kalmykov, N. N.; Ostapchenko, S. S.; Werner, K.

An extensive air shower (EAS) calculation scheme based on cascade equations and some EAS characteristics for energies 1014 -1017 eV are presented. The universal hadronic interaction model NEXUS is employed to provide the necessary data concerning hadron-air collisions. The influence of model assumptions on the longitudinal EAS development is discussed in the framework of the NEXUS and QGSJET models. Applied to EAS simulations, perspectives of combined Monte Carlo and numerical methods are considered.

Insights into DNA-mediated interparticle interactions from a coarse-grained model

NASA Astrophysics Data System (ADS)

Ding, Yajun; Mittal, Jeetain

2014-11-01

DNA-functionalized particles have great potential for the design of complex self-assembled materials. The major hurdle in realizing crystal structures from DNA-functionalized particles is expected to be kinetic barriers that trap the system in metastable amorphous states. Therefore, it is vital to explore the molecular details of particle assembly processes in order to understand the underlying mechanisms. Molecular simulations based on coarse-grained models can provide a convenient route to explore these details. Most of the currently available coarse-grained models of DNA-functionalized particles ignore key chemical and structural details of DNA behavior. These models therefore are limited in scope for studying experimental phenomena. In this paper, we present a new coarse-grained model of DNA-functionalized particles which incorporates some of the desired features of DNA behavior. The coarse-grained DNA model used here provides explicit DNA representation (at the nucleotide level) and complementary interactions between Watson-Crick base pairs, which lead to the formation of single-stranded hairpin and double-stranded DNA. Aggregation between multiple complementary strands is also prevented in our model. We study interactions between two DNA-functionalized particles as a function of DNA grafting density, lengths of the hybridizing and non-hybridizing parts of DNA, and temperature. The calculated free energies as a function of pair distance between particles qualitatively resemble experimental measurements of DNA-mediated pair interactions.

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.

PolyA Single Strand DNA Translocation Through an Alpha-Hemolysin Pore Stem

NASA Technical Reports Server (NTRS)

OKeeffe, James; Cozmuta, Ioana; Stolc, Viktor

2003-01-01

A new model for the polymer-pore interaction energy is introduced, based on an atomic-scale description of coulombic polymer-pore interaction. The enhanced drift velocity, experimentally observed for short polymers, is successfully accounted for, using this interaction energy model. For R/R(sub 0)>4 (R(sub 0)=7 angstroms) the translocation velocity approaches the free space drift velocity v(sub 0). This motivates the need to appropriately derivatize artificial nanopores, where R>R(sub 0).

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.

Recent Advances in the Theory and Simulation of Model Colloidal Microphase Formers.

PubMed

Zhuang, Yuan; Charbonneau, Patrick

2016-08-18

This mini-review synthesizes our understanding of the equilibrium behavior of particle-based models with short-range attractive and long-range repulsive (SALR) interactions. These models, which can form stable periodic microphases, aim to reproduce the essence of colloidal suspensions with competing interparticle interactions. Ordered structures, however, have yet to be obtained in experiments. In order to better understand the hurdles to periodic microphase assembly, marked theoretical and simulation advances have been made over the past few years. Here, we present recent progress in the study of microphases in models with SALR interactions using liquid-state theory and density-functional theory as well as numerical simulations. Combining these various approaches provides a description of periodic microphases, and gives insights into the rich phenomenology of the surrounding disordered regime. Ongoing research directions in the thermodynamics of models with SALR interactions are also presented.

Test of Hadronic Interaction Models with the KASCADE Hadron Calorimeter

NASA Astrophysics Data System (ADS)

Milke, J.; KASCADE Collaboration

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

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.

In vitro-in vivo extrapolation of CYP2D6 inactivation by paroxetine: prediction of nonstationary pharmacokinetics and drug interaction magnitude.

PubMed

Venkatakrishnan, Karthik; Obach, R Scott

2005-06-01

Attempts at predicting drug-drug interactions perpetrated by paroxetine from in vitro data have utilized reversible enzyme inhibition models and have been unsuccessful to date, grossly underpredicting interaction magnitude. Recent data have provided evidence for mechanism-based inactivation of CYP2D6 by paroxetine. We have predicted the pharmacokinetic consequences of CYP2D6 inactivation by paroxetine from in vitro inactivation kinetics (kinact 0.17 min(-1), unbound KI 0.315 microM), in vivo inhibitor concentrations, and an estimated CYP2D6 degradation half-life of 51 h, using a mathematical model of mechanism-based inhibition. The model-predicted accumulation ratio of paroxetine was 5 times that expected from single-dose kinetics and in excellent agreement with the observed 5- to 6-fold greater accumulation. Magnitudes of interactions produced by paroxetine (20-30 mg/day) with desipramine, risperidone, perphenazine, atomoxetine, (S)-metoprolol, and (R)-metoprolol were predicted, considering the contribution of CYP2D6 to their oral clearance. Predicted fold-increases in victim drug AUC were 5-, 6-, 5-, 6-, 4-, and 6-fold, respectively, and are in reasonable agreement with observed values of 5-, 6-, >7-, 7-, 5-, and 8-fold, respectively. Failure to consider microsomal binding in vitro adversely affected predictive accuracy. Simulation of the sensitivities of these predictions to model inputs suggests a 2-fold underprediction of interaction magnitude when a CYP2D6 degradation half-life of 14 h (reported for rat CYP3A) is used. In summary, the scaling model for mechanism-based inactivation successfully predicted the pharmacokinetic consequences of CYP2D6 inactivation by paroxetine from in vitro data.

Solving the scalability issue in quantum-based refinement: Q|R#1.

PubMed

Zheng, Min; Moriarty, Nigel W; Xu, Yanting; Reimers, Jeffrey R; Afonine, Pavel V; Waller, Mark P

2017-12-01

Accurately refining biomacromolecules using a quantum-chemical method is challenging because the cost of a quantum-chemical calculation scales approximately as n m , where n is the number of atoms and m (≥3) is based on the quantum method of choice. This fundamental problem means that quantum-chemical calculations become intractable when the size of the system requires more computational resources than are available. In the development of the software package called Q|R, this issue is referred to as Q|R#1. A divide-and-conquer approach has been developed that fragments the atomic model into small manageable pieces in order to solve Q|R#1. Firstly, the atomic model of a crystal structure is analyzed to detect noncovalent interactions between residues, and the results of the analysis are represented as an interaction graph. Secondly, a graph-clustering algorithm is used to partition the interaction graph into a set of clusters in such a way as to minimize disruption to the noncovalent interaction network. Thirdly, the environment surrounding each individual cluster is analyzed and any residue that is interacting with a particular cluster is assigned to the buffer region of that particular cluster. A fragment is defined as a cluster plus its buffer region. The gradients for all atoms from each of the fragments are computed, and only the gradients from each cluster are combined to create the total gradients. A quantum-based refinement is carried out using the total gradients as chemical restraints. In order to validate this interaction graph-based fragmentation approach in Q|R, the entire atomic model of an amyloid cross-β spine crystal structure (PDB entry 2oNA) was refined.

Credibilistic multi-period portfolio optimization based on scenario tree

NASA Astrophysics Data System (ADS)

Mohebbi, Negin; Najafi, Amir Abbas

2018-02-01

In this paper, we consider a multi-period fuzzy portfolio optimization model with considering transaction costs and the possibility of risk-free investment. We formulate a bi-objective mean-VaR portfolio selection model based on the integration of fuzzy credibility theory and scenario tree in order to dealing with the markets uncertainty. The scenario tree is also a proper method for modeling multi-period portfolio problems since the length and continuity of their horizon. We take the return and risk as well cardinality, threshold, class, and liquidity constraints into consideration for further compliance of the model with reality. Then, an interactive dynamic programming method, which is based on a two-phase fuzzy interactive approach, is employed to solve the proposed model. In order to verify the proposed model, we present an empirical application in NYSE under different circumstances. The results show that the consideration of data uncertainty and other real-world assumptions lead to more practical and efficient solutions.

Interactive classification and content-based retrieval of tissue images

NASA Astrophysics Data System (ADS)

Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

2002-11-01

We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

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

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.

Automated optimization of water-water interaction parameters for a coarse-grained model.

PubMed

Fogarty, Joseph C; Chiu, See-Wing; Kirby, Peter; Jakobsson, Eric; Pandit, Sagar A

2014-02-13

We have developed an automated parameter optimization software framework (ParOpt) that implements the Nelder-Mead simplex algorithm and applied it to a coarse-grained polarizable water model. The model employs a tabulated, modified Morse potential with decoupled short- and long-range interactions incorporating four water molecules per interaction site. Polarizability is introduced by the addition of a harmonic angle term defined among three charged points within each bead. The target function for parameter optimization was based on the experimental density, surface tension, electric field permittivity, and diffusion coefficient. The model was validated by comparison of statistical quantities with experimental observation. We found very good performance of the optimization procedure and good agreement of the model with experiment.

Integrated VR platform for 3D and image-based models: a step toward interactive image-based virtual environments

NASA Astrophysics Data System (ADS)

Yoon, Jayoung; Kim, Gerard J.

2003-04-01

Traditionally, three dimension models have been used for building virtual worlds, and a data structure called the "scene graph" is often employed to organize these 3D objects in the virtual space. On the other hand, image-based rendering has recently been suggested as a probable alternative VR platform for its photo-realism, however, due to limited interactivity, it has only been used for simple navigation systems. To combine the merits of these two approaches to object/scene representations, this paper proposes for a scene graph structure in which both 3D models and various image-based scenes/objects can be defined, traversed, and rendered together. In fact, as suggested by Shade et al., these different representations can be used as different LOD's for a given object. For instance, an object might be rendered using a 3D model at close range, a billboard at an intermediate range, and as part of an environment map at far range. The ultimate objective of this mixed platform is to breath more interactivity into the image based rendered VE's by employing 3D models as well. There are several technical challenges in devising such a platform: designing scene graph nodes for various types of image based techniques, establishing criteria for LOD/representation selection, handling their transitions, implementing appropriate interaction schemes, and correctly rendering the overall scene. Currently, we have extended the scene graph structure of the Sense8's WorldToolKit, to accommodate new node types for environment maps billboards, moving textures and sprites, "Tour-into-the-Picture" structure, and view interpolated objects. As for choosing the right LOD level, the usual viewing distance and image space criteria are used, however, the switching between the image and 3D model occurs at a distance from the user where the user starts to perceive the object's internal depth. Also, during interaction, regardless of the viewing distance, a 3D representation would be used, it if exists. Before rendering, objects are conservatively culled from the view frustum using the representation with the largest volume. Finally, we carried out experiments to verify the theoretical derivation of the switching rule and obtained positive results.

Thermodynamic properties and atomic structure of Ca-based liquid alloys

NASA Astrophysics Data System (ADS)

Poizeau, Sophie

To identify the most promising positive electrodes for Ca-based liquid metal batteries, the thermodynamic properties of diverse Ca-based liquid alloys were investigated. The thermodynamic properties of Ca-Sb alloys were determined by emf measurements. It was found that Sb as positive electrode would provide the highest voltage for Ca-based liquid metal batteries (1 V). The price of such a battery would be competitive for the grid-scale energy storage market. The impact of Pb, a natural impurity of Sb, was predicted successfully and confirmed via electrochemical measurements. It was shown that the impact on the open circuit voltage would be minor. Indeed, the interaction between Ca and Sb was demonstrated to be much stronger than between Ca and Pb using thermodynamic modeling, which explains why the partial thermodynamic properties of Ca would not vary much with the addition of Pb to Sb. However, the usage of the positive electrode would be reduced, which would limit the interest of a Pb-Sb positive electrode. Throughout this work, the molecular interaction volume model (MIVM) was used for the first time for alloys with thermodynamic properties showing strong negative deviation from ideality. This model showed that systems such as Ca-Sb have strong short-range order: Ca is most stable when its first nearest neighbors are Sb. This is consistent with what the more traditional thermodynamic model, the regular association model, would predict. The advantages of the MIVM are the absence of assumption regarding the composition of an associate, and the reduced number of fitting parameters (2 instead of 5). Based on the parameters derived from the thermodynamic modeling using the MIVM, a new potential of mixing for liquid alloys was defined to compare the strength of interaction in different Ca-based alloys. Comparing this trend with the strength of interaction in the solid state of these systems (assessed by the energy of formation of the intermetallics), the systems with the most stable intermetallics were found to have the strongest interaction in the liquid state. Eventually, a new criteria was formulated to select electrode materials for liquid metal batteries. Systems with the most stable intermetallics, which can be evaluated by the enthalpy of formation of these systems, will yield the highest voltage when assembled as positive and negative electrodes in a liquid metal battery. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

Data Intensive Systems (DIS) Benchmark Performance Summary

DTIC Science & Technology

2003-08-01

models assumed by today’s conventional architectures. Such applications include model- based Automatic Target Recognition (ATR), synthetic aperture...radar (SAR) codes, large scale dynamic databases/battlefield integration, dynamic sensor- based processing, high-speed cryptanalysis, high speed...distributed interactive and data intensive simulations, data-oriented problems characterized by pointer- based and other highly irregular data structures

HAWQS Beta Flyer

EPA Pesticide Factsheets

HAWQS is a web-based interactive water quantity and quality modeling system that provides users with interactive web interfaces and maps; pre-loaded input data; outputs that include tables, charts, graphs and raw output data; and a user guide.

HAWQS beta flyer

EPA Pesticide Factsheets

HAWQS is a web-based interactive water quantity and quality modeling system that provides users with interactive web interfaces and maps; pre-loaded input data; outputs that include tables, charts, graphs and raw output data; and a user guide.

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

An Interactive Web-Based Program for Stepfamilies: Development and Evaluation of Efficacy

ERIC Educational Resources Information Center

Gelatt, Vicky A.; Adler-Baeder, Francesca; Seeley, John R.

2010-01-01

This study evaluated the efficacy of a family life education program for stepfamilies that is self-administered, interactive, and web-based. The program uses behavior-modeling videos to demonstrate effective couple, parenting, and stepparenting practices. A diverse sample of 300 parents/stepparents of a child aged 11-15 years were randomized into…

Dynamic Fuzzy Logic-Based Quality of Interaction within Blended-Learning: The Rare and Contemporary Dance Cases

ERIC Educational Resources Information Center

Dias, Sofia B.; Diniz, José A.; Hadjileontiadis, Leontios J.

2014-01-01

The combination of the process of pedagogical planning within the Blended (b-) learning environment with the users' quality of interaction ("QoI") with the Learning Management System (LMS) is explored here. The required "QoI" (both for professors and students) is estimated by adopting a fuzzy logic-based modeling approach,…

Investigating the Effectiveness of an Active Learning Based-Interactive Conceptual Instruction (ALBICI) on Electric Field Concept

ERIC Educational Resources Information Center

Samsudin, Achmad; Suhandi, Andi; Rusdiana, Dadi; Kaniawati, Ida; Costu, Bayram

2016-01-01

The aim of this study was to develop an Active Learning Based-Interactive Conceptual Instruction (ALBICI) model through PDEODE*E tasks (stands for Predict, Discuss, Explain, Observe, Discuss, Explore, and Explain) for promoting conceptual change and investigating its effectiveness of pre-service physics teachers' understanding on electric field…

Effective screening strategy using ensembled pharmacophore models combined with cascade docking: application to p53-MDM2 interaction inhibitors.

PubMed

Xue, Xin; Wei, Jin-Lian; Xu, Li-Li; Xi, Mei-Yang; Xu, Xiao-Li; Liu, Fang; Guo, Xiao-Ke; Wang, Lei; Zhang, Xiao-Jin; Zhang, Ming-Ye; Lu, Meng-Chen; Sun, Hao-Peng; You, Qi-Dong

2013-10-28

Protein-protein interactions (PPIs) play a crucial role in cellular function and form the backbone of almost all biochemical processes. In recent years, protein-protein interaction inhibitors (PPIIs) have represented a treasure trove of potential new drug targets. Unfortunately, there are few successful drugs of PPIIs on the market. Structure-based pharmacophore (SBP) combined with docking has been demonstrated as a useful Virtual Screening (VS) strategy in drug development projects. However, the combination of target complexity and poor binding affinity prediction has thwarted the application of this strategy in the discovery of PPIIs. Here we report an effective VS strategy on p53-MDM2 PPI. First, we built a SBP model based on p53-MDM2 complex cocrystal structures. The model was then simplified by using a Receptor-Ligand complex-based pharmacophore model considering the critical binding features between MDM2 and its small molecular inhibitors. Cascade docking was subsequently applied to improve the hit rate. Based on this strategy, we performed VS on NCI and SPECS databases and successfully discovered 6 novel compounds from 15 hits with the best, compound 1 (NSC 5359), K(i) = 180 ± 50 nM. These compounds can serve as lead compounds for further optimization.

Constitutive law for seismicity rate based on rate and state friction: Dieterich 1994 revisited.

NASA Astrophysics Data System (ADS)

Heimisson, E. R.; Segall, P.

2017-12-01

Dieterich [1994] derived a constitutive law for seismicity rate based on rate and state friction, which has been applied widely to aftershocks, earthquake triggering, and induced seismicity in various geological settings. Here, this influential work is revisited, and re-derived in a more straightforward manner. By virtue of this new derivation the model is generalized to include changes in effective normal stress associated with background seismicity. Furthermore, the general case when seismicity rate is not constant under constant stressing rate is formulated. The new derivation provides directly practical integral expressions for the cumulative number of events and rate of seismicity for arbitrary stressing history. Arguably, the most prominent limitation of Dieterich's 1994 theory is the assumption that seismic sources do not interact. Here we derive a constitutive relationship that considers source interactions between sub-volumes of the crust, where the stress in each sub-volume is assumed constant. Interactions are considered both under constant stressing rate conditions and for arbitrary stressing history. This theory can be used to model seismicity rate due to stress changes or to estimate stress changes using observed seismicity from triggered earthquake swarms where earthquake interactions and magnitudes are take into account. We identify special conditions under which influence of interactions cancel and the predictions reduces to those of Dieterich 1994. This remarkable result may explain the apparent success of the model when applied to observations of triggered seismicity. This approach has application to understanding and modeling induced and triggered seismicity, and the quantitative interpretation of geodetic and seismic data. It enables simultaneous modeling of geodetic and seismic data in a self-consistent framework. To date physics-based modeling of seismicity with or without geodetic data has been found to give insight into various processes related to aftershocks, VT and injection-induced seismicity. However, the role of various processes such as earthquake interactions and magnitudes and effective normal stress has been unclear. The new theory presented resolves some of the pertinent issues raised in the literature with application of the Dieterich 1994 model.

Global Quantitative Modeling of Chromatin Factor Interactions

PubMed Central

Zhou, Jian; Troyanskaya, Olga G.

2014-01-01

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

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.

Mathematical model of rolling an elastic wheel over deformable support base

NASA Astrophysics Data System (ADS)

Volskaia, V. N.; Zhileykin, M. M.; Zakharov, A. Y.

2018-02-01

One of the main direction of economic growth in Russia remains to be a speedy development of north and northeast regions that are the constituents of the 60 percent of the country territory. The further development of these territories requires new methods and technologies for solving transport and technological problems when off-road transportation of cargoes and people is conducting. One of the fundamental methods of patency prediction is imitation modeling of wheeled vehicles movement in different operating conditions. Both deformable properties of tires and physical and mechanical properties of the ground: normal tire deflection and gauge depth; variation of contact patch area depending on the load and pressure of air in the tire; existence of hysteresis losses in the tire material which are influencing on the rolling resistance due to friction processes between tire and ground in the contact patch; existence of the tangential reaction from the ground by entire contact area influence on the tractive patency. Nowadays there are two main trends in theoretical research of interaction wheeled propulsion device with ground: analytical method involving mathematical description of explored process and finite element method based on computational modeling. Mathematical models of interaction tire with the ground are used both in processes of interaction individual wheeled propulsion device with ground and researches of mobile vehicle dynamical models operated in specific road and climate conditions. One of the most significant imperfection of these models is the description of interaction wheel with flat deformable support base whereas profile of real support base surface has essential height of unevenness which is commensurate with radius of the wheel. The description of processes taking place in the ground under influence of the wheeled propulsion device using the finite element method is relatively new but most applicable lately. The application of this method allows to provide the most accurate description of the interaction process of a wheeled propulsion devices and the ground, also this method allows to define tension in the ground, deformation of the ground and the tire and ground’s compression. However, the high laboriousness of computations is essential shortcoming of that method therefore it’s hard to use these models as part of the general motion model of multi-axis wheeled vehicles. The purpose of this research is the elaboration of mathematical model of elastic wheel rolling over deformable rough support base taking into account the contact patch deformation. The mathematical model of rectilinear rolling an elastic wheel over rough deformable support base, taking into account variation of contact patch area and variation in the direction of the radial and tangential reactions also load bearing capacity of the ground, is developed. The efficiency of developed mathematical model of rectilinear rolling an elastic wheel over rough deformable support base is proved by the simulation methods.

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

PubMed

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

2017-04-01

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

Empirical Behavioral Models to Support Alternative Tools for the Analysis of Mixed-Priority Pedestrian-Vehicle Interaction in a Highway Capacity Context

PubMed Central

Rouphail, Nagui M.

2011-01-01

This paper presents behavioral-based models for describing pedestrian gap acceptance at unsignalized crosswalks in a mixed-priority environment, where some drivers yield and some pedestrians cross in gaps. Logistic regression models are developed to predict the probability of pedestrian crossings as a function of vehicle dynamics, pedestrian assertiveness, and other factors. In combination with prior work on probabilistic yielding models, the results can be incorporated in a simulation environment, where they can more fully describe the interaction of these two modes. The approach is intended to supplement HCM analytical procedure for locations where significant interaction occurs between drivers and pedestrians, including modern roundabouts. PMID:21643488

Fluid-structure interaction simulation of floating structures interacting with complex, large-scale ocean waves and atmospheric turbulence with application to floating offshore wind turbines

NASA Astrophysics Data System (ADS)

Calderer, Antoni; Guo, Xin; Shen, Lian; Sotiropoulos, Fotis

2018-02-01

We develop a numerical method for simulating coupled interactions of complex floating structures with large-scale ocean waves and atmospheric turbulence. We employ an efficient large-scale model to develop offshore wind and wave environmental conditions, which are then incorporated into a high resolution two-phase flow solver with fluid-structure interaction (FSI). The large-scale wind-wave interaction model is based on a two-fluid dynamically-coupled approach that employs a high-order spectral method for simulating the water motion and a viscous solver with undulatory boundaries for the air motion. The two-phase flow FSI solver is based on the level set method and is capable of simulating the coupled dynamic interaction of arbitrarily complex bodies with airflow and waves. The large-scale wave field solver is coupled with the near-field FSI solver with a one-way coupling approach by feeding into the latter waves via a pressure-forcing method combined with the level set method. We validate the model for both simple wave trains and three-dimensional directional waves and compare the results with experimental and theoretical solutions. Finally, we demonstrate the capabilities of the new computational framework by carrying out large-eddy simulation of a floating offshore wind turbine interacting with realistic ocean wind and waves.

Influence of Hofmeister ions on the structure of proline-based peptide models: A combined experimental and molecular modeling study

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

Brohl, Andreas; Albrecht, Benjamin; Zhang, Yong

Here, the influence of three sodium salts, covering a wide range of the Hofmeister series, on the conformation of three proline-based peptide models in aqueous solution is examined using a combination of nuclear magnetic resonance spectroscopy and molecular dynamics simulations. The anions preferentially interact with the cis conformers of the peptide models, which is rationalized by the respective electrostatic potential surfaces. These preferred interactions have a strong impact on the thermodynamics of the cis/trans equilibria, leading to a higher population of the cis conformers. In distinct cases, these equilibria are nearly independent of temperature, showing that the salts are alsomore » able to stabilize the conformers over wide temperature ranges.« less

An agent-based model for queue formation of powered two-wheelers in heterogeneous traffic

NASA Astrophysics Data System (ADS)

Lee, Tzu-Chang; Wong, K. I.

2016-11-01

This paper presents an agent-based model (ABM) for simulating the queue formation of powered two-wheelers (PTWs) in heterogeneous traffic at a signalized intersection. The main novelty is that the proposed interaction rule describing the position choice behavior of PTWs when queuing in heterogeneous traffic can capture the stochastic nature of the decision making process. The interaction rule is formulated as a multinomial logit model, which is calibrated by using a microscopic traffic trajectory dataset obtained from video footage. The ABM is validated against the survey data for the vehicular trajectory patterns, queuing patterns, queue lengths, and discharge rates. The results demonstrate that the proposed model is capable of replicating the observed queue formation process for heterogeneous traffic.

Influence of Hofmeister Ions on the Structure of Proline-Based Peptide Models: A Combined Experimental and Molecular Modeling Study.

PubMed

Bröhl, Andreas; Albrecht, Benjamin; Zhang, Yong; Maginn, Edward; Giernoth, Ralf

2017-03-09

The influence of three sodium salts, covering a wide range of the Hofmeister series, on the conformation of three proline-based peptide models in aqueous solution is examined using a combination of nuclear magnetic resonance spectroscopy and molecular dynamics simulations. The anions preferentially interact with the cis conformers of the peptide models, which is rationalized by the respective electrostatic potential surfaces. These preferred interactions have a strong impact on the thermodynamics of the cis/trans equilibria, leading to a higher population of the cis conformers. In distinct cases, these equilibria are nearly independent of temperature, showing that the salts are also able to stabilize the conformers over wide temperature ranges.

Influence of Hofmeister ions on the structure of proline-based peptide models: A combined experimental and molecular modeling study

DOE PAGES

Brohl, Andreas; Albrecht, Benjamin; Zhang, Yong; ...

2017-02-13

Here, the influence of three sodium salts, covering a wide range of the Hofmeister series, on the conformation of three proline-based peptide models in aqueous solution is examined using a combination of nuclear magnetic resonance spectroscopy and molecular dynamics simulations. The anions preferentially interact with the cis conformers of the peptide models, which is rationalized by the respective electrostatic potential surfaces. These preferred interactions have a strong impact on the thermodynamics of the cis/trans equilibria, leading to a higher population of the cis conformers. In distinct cases, these equilibria are nearly independent of temperature, showing that the salts are alsomore » able to stabilize the conformers over wide temperature ranges.« less

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development. Currently there is no fully coupled computational tool to analyze this fluid/structure interaction process. The objective of this study was to develop a fully coupled aeroelastic modeling capability to describe the fluid/structure interaction process during the transient nozzle operations. The aeroelastic model composes of three components: the computational fluid dynamics component based on an unstructured-grid, pressure-based computational fluid dynamics formulation, the computational structural dynamics component developed in the framework of modal analysis, and the fluid-structural interface component. The developed aeroelastic model was applied to the transient nozzle startup process of the Space Shuttle Main Engine at sea level. The computed nozzle side loads and the axial nozzle wall pressure profiles from the aeroelastic nozzle are compared with those of the published rigid nozzle results, and the impact of the fluid/structure interaction on nozzle side loads is interrogated and presented.

The BioGRID interaction database: 2017 update

PubMed Central

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

2017-01-01

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

Mycotoxins co-contamination: Methodological aspects and biological relevance of combined toxicity studies.

PubMed

Alassane-Kpembi, Imourana; Schatzmayr, Gerd; Taranu, Ionelia; Marin, Daniela; Puel, Olivier; Oswald, Isabelle Paule

2017-11-02

Mycotoxins are secondary fungal metabolites produced mainly by Aspergillus, Penicillium, and Fusarium. As evidenced by large-scale surveys, humans and animals are simultaneously exposed to several mycotoxins. Simultaneous exposure could result in synergistic, additive or antagonistic effects. However, most toxicity studies addressed the effects of mycotoxins separately. We present the experimental designs and we discuss the conclusions drawn from in vitro experiments exploring toxicological interactions of mycotoxins. We report more than 80 publications related to mycotoxin interactions. The studies explored combinations involving the regulated groups of mycotoxins, especially aflatoxins, ochratoxins, fumonisins, zearalenone and trichothecenes, but also the "emerging" mycotoxins beauvericin and enniatins. Over 50 publications are based on the arithmetic model of additivity. Few studies used the factorial designs or the theoretical biology-based models of additivity. The latter approaches are gaining increased attention. These analyses allow determination of the type of interaction and, optionally, its magnitude. The type of interaction reported for mycotoxin combinations depended on several factors, in particular cell models and the tested dose ranges. However, synergy among Fusarium toxins was highlighted in several studies. This review indicates that well-addressed in vitro studies remain valuable tools for the screening of interactive potential in mycotoxin mixtures.

FragFit: a web-application for interactive modeling of protein segments into cryo-EM density maps.

PubMed

Tiemann, Johanna K S; Rose, Alexander S; Ismer, Jochen; Darvish, Mitra D; Hilal, Tarek; Spahn, Christian M T; Hildebrand, Peter W

2018-05-21

Cryo-electron microscopy (cryo-EM) is a standard method to determine the three-dimensional structures of molecular complexes. However, easy to use tools for modeling of protein segments into cryo-EM maps are sparse. Here, we present the FragFit web-application, a web server for interactive modeling of segments of up to 35 amino acids length into cryo-EM density maps. The fragments are provided by a regularly updated database containing at the moment about 1 billion entries extracted from PDB structures and can be readily integrated into a protein structure. Fragments are selected based on geometric criteria, sequence similarity and fit into a given cryo-EM density map. Web-based molecular visualization with the NGL Viewer allows interactive selection of fragments. The FragFit web-application, accessible at http://proteinformatics.de/FragFit, is free and open to all users, without any login requirements.

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes

PubMed Central

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M.; Zimmermann, Ulrich S.; Schlagenhauf, Florian; Smolka, Michael N.; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities. PMID:28642696

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes.

PubMed

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M; Zimmermann, Ulrich S; Schlagenhauf, Florian; Smolka, Michael N; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities.

An Integrated Crustal Dynamics Simulator

NASA Astrophysics Data System (ADS)

Xing, H. L.; Mora, P.

2007-12-01

Numerical modelling offers an outstanding opportunity to gain an understanding of the crustal dynamics and complex crustal system behaviour. This presentation provides our long-term and ongoing effort on finite element based computational model and software development to simulate the interacting fault system for earthquake forecasting. A R-minimum strategy based finite-element computational model and software tool, PANDAS, for modelling 3-dimensional nonlinear frictional contact behaviour between multiple deformable bodies with the arbitrarily-shaped contact element strategy has been developed by the authors, which builds up a virtual laboratory to simulate interacting fault systems including crustal boundary conditions and various nonlinearities (e.g. from frictional contact, materials, geometry and thermal coupling). It has been successfully applied to large scale computing of the complex nonlinear phenomena in the non-continuum media involving the nonlinear frictional instability, multiple material properties and complex geometries on supercomputers, such as the South Australia (SA) interacting fault system, South California fault model and Sumatra subduction model. It has been also extended and to simulate the hot fractured rock (HFR) geothermal reservoir system in collaboration of Geodynamics Ltd which is constructing the first geothermal reservoir system in Australia and to model the tsunami generation induced by earthquakes. Both are supported by Australian Research Council.

Development of Turbulent Biological Closure Parameterizations

DTIC Science & Technology

2011-09-30

LONG-TERM GOAL: The long-term goals of this project are: (1) to develop a theoretical framework to quantify turbulence induced NPZ interactions. (2) to apply the theory to develop parameterizations to be used in realistic environmental physical biological coupling numerical models. OBJECTIVES: Connect the Goodman and Robinson (2008) statistically based pdf theory to Advection Diffusion Reaction (ADR) modeling of NPZ interaction.

The Virtual Museum of Minerals and Molecules: Molecular Visualization in a Virtual Hands-On Museum

ERIC Educational Resources Information Center

Barak, Phillip; Nater, Edward A.

2005-01-01

The Virtual Museum of Minerals and Molecules (VMMM) is a web-based resource presenting interactive, 3-D, research-grade molecular models of more than 150 minerals and molecules of interest to chemical, earth, plant, and environmental sciences. User interactivity with the 3-D display allows models to be rotated, zoomed, and specific regions 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…

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation.

PubMed

Bardhan, Jaydeep P; Knepley, Matthew G; Anitescu, Mihai

2009-03-14

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation

NASA Astrophysics Data System (ADS)

Bardhan, Jaydeep P.; Knepley, Matthew G.; Anitescu, Mihai

2009-03-01

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Host-to-host variation of ecological interactions in polymicrobial infections

NASA Astrophysics Data System (ADS)

Mukherjee, Sayak; Weimer, Kristin E.; Seok, Sang-Cheol; Ray, Will C.; Jayaprakash, C.; Vieland, Veronica J.; Swords, W. Edward; Das, Jayajit

2015-02-01

Host-to-host variability with respect to interactions between microorganisms and multicellular hosts are commonly observed in infection and in homeostasis. However, the majority of mechanistic models used to analyze host-microorganism relationships, as well as most of the ecological theories proposed to explain coevolution of hosts and microbes, are based on averages across a host population. By assuming that observed variations are random and independent, these models overlook the role of differences between hosts. Here, we analyze mechanisms underlying host-to-host variations of bacterial infection kinetics, using the well characterized experimental infection model of polymicrobial otitis media (OM) in chinchillas, in combination with population dynamic models and a maximum entropy (MaxEnt) based inference scheme. We find that the nature of the interactions between bacterial species critically regulates host-to-host variations in these interactions. Surprisingly, seemingly unrelated phenomena, such as the efficiency of individual bacterial species in utilizing nutrients for growth, and the microbe-specific host immune response, can become interdependent in a host population. The latter finding suggests a potential mechanism that could lead to selection of specific strains of bacterial species during the coevolution of the host immune response and the bacterial species.

Energetics of protein-DNA interactions.

PubMed

Donald, Jason E; Chen, William W; Shakhnovich, Eugene I

2007-01-01

Protein-DNA interactions are vital for many processes in living cells, especially transcriptional regulation and DNA modification. To further our understanding of these important processes on the microscopic level, it is necessary that theoretical models describe the macromolecular interaction energetics accurately. While several methods have been proposed, there has not been a careful comparison of how well the different methods are able to predict biologically important quantities such as the correct DNA binding sequence, total binding free energy and free energy changes caused by DNA mutation. In addition to carrying out the comparison, we present two important theoretical models developed initially in protein folding that have not yet been tried on protein-DNA interactions. In the process, we find that the results of these knowledge-based potentials show a strong dependence on the interaction distance and the derivation method. Finally, we present a knowledge-based potential that gives comparable or superior results to the best of the other methods, including the molecular mechanics force field AMBER99.

Branch: an interactive, web-based tool for testing hypotheses and developing predictive models.

PubMed

Gangavarapu, Karthik; Babji, Vyshakh; Meißner, Tobias; Su, Andrew I; Good, Benjamin M

2016-07-01

Branch is a web application that provides users with the ability to interact directly with large biomedical datasets. The interaction is mediated through a collaborative graphical user interface for building and evaluating decision trees. These trees can be used to compose and test sophisticated hypotheses and to develop predictive models. Decision trees are built and evaluated based on a library of imported datasets and can be stored in a collective area for sharing and re-use. Branch is hosted at http://biobranch.org/ and the open source code is available at http://bitbucket.org/sulab/biobranch/ asu@scripps.edu or bgood@scripps.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Phenytoin-Bovine Serum Albumin interactions - modeling plasma protein - drug binding: A multi-spectroscopy and in silico-based correlation

NASA Astrophysics Data System (ADS)

Suresh, P. K.; Divya, Naik; Nidhi, Shah; Rajasekaran, R.

2018-03-01

The study focused on the analysis of the nature and site of binding of Phenytoin (PHT) -(a model hydrophobic drug) with Bovine Serum Albumin (BSA) (a model protein used as a surrogate for HSA). Interactions with defined amounts of Phenytoin and BSA demonstrated a blue shift (hypsochromic -change in the microenvironment of the tryptophan residue with decrease in the polar environment and more of hydrophobicity) with respect to the albumin protein and a red shift (bathochromic -hydrophobicity and polarity related changes) in the case of the model hydrophobic drug. This shift, albeit lower in magnitude, has been substantiated by a fairly convincing, Phenytoin-mediated quenching of the endogenous fluorophore in BSA. Spectral shifts studied at varying pH, temperatures and incubation periods (at varying concentrations of PHT with a defined/constant BSA concentration) showed no significant differences (data not shown). FTIR analysis provided evidence of the interaction of PHT with BSA with a stretching vibration of 1737.86 cm- 1, apart from the vibrations characteristically associated with the amine and carboxyl groups respectively. Our in vitro findings were extended to molecular docking of BSA with PHT (with the different ionized forms of the drug) and the subsequent LIGPLOT-based analysis. In general, a preponderance of hydrophobic interactions was observed. These hydrophobic interactions corroborate the tryptophan-based spectral shifts and the fluorescence quenching data. These results substantiates our hitherto unreported in vitro/in silico experimental flow and provides a basis for screening other hydrophobic drugs in its class.

Modelling Safe Interface Interactions in Web Applications

NASA Astrophysics Data System (ADS)

Brambilla, Marco; Cabot, Jordi; Grossniklaus, Michael

Current Web applications embed sophisticated user interfaces and business logic. The original interaction paradigm of the Web based on static content pages that are browsed by hyperlinks is, therefore, not valid anymore. In this paper, we advocate a paradigm shift for browsers and Web applications, that improves the management of user interaction and browsing history. Pages are replaced by States as basic navigation nodes, and Back/Forward navigation along the browsing history is replaced by a full-fledged interactive application paradigm, supporting transactions at the interface level and featuring Undo/Redo capabilities. This new paradigm offers a safer and more precise interaction model, protecting the user from unexpected behaviours of the applications and the browser.

Reconstructing the Alcatraz escape

NASA Astrophysics Data System (ADS)

Baart, F.; Hoes, O.; Hut, R.; Donchyts, G.; van Leeuwen, E.

2014-12-01

In the night of June 12, 1962 three inmates used a raft made of raincoatsto escaped the ultimate maximum security prison island Alcatraz in SanFrancisco, United States. History is unclear about what happened tothe escapees. At what time did they step into the water, did theysurvive, if so, where did they reach land? The fate of the escapees has been the subject of much debate: did theymake landfall on Angel Island, or did the current sweep them out ofthe bay and into the cold pacific ocean? In this presentation, we try to shed light on this historic case using avisualization of a high-resolution hydrodynamic simulation of the San Francisco Bay, combined with historical tidal records. By reconstructing the hydrodynamic conditions and using a particle based simulation of the escapees we show possible scenarios. The interactive model is visualized using both a 3D photorealistic and web based visualization. The "Escape from Alcatraz" scenario demonstrates the capabilities of the 3Di platform. This platform is normally used for overland flooding (1D/2D). The model engine uses a quad tree structure, resulting in an order of magnitude speedup. The subgrid approach takes detailed bathymetry information into account. The inter-model variability is tested by comparing the results with the DFlow Flexible Mesh (DFlowFM) San Francisco Bay model. Interactivity is implemented by converting the models from static programs to interactive libraries, adhering to the Basic ModelInterface (BMI). Interactive models are more suitable for answeringexploratory research questions such as this reconstruction effort. Although these hydrodynamic simulations only provide circumstantialevidence for solving the mystery of what happened during the foggy darknight of June 12, 1962, it can be used as a guidance and provides aninteresting testcase to apply interactive modelling.

Translucent Radiosity: Efficiently Combining Diffuse Inter-Reflection and Subsurface Scattering.

PubMed

Sheng, Yu; Shi, Yulong; Wang, Lili; Narasimhan, Srinivasa G

2014-07-01

It is hard to efficiently model the light transport in scenes with translucent objects for interactive applications. The inter-reflection between objects and their environments and the subsurface scattering through the materials intertwine to produce visual effects like color bleeding, light glows, and soft shading. Monte-Carlo based approaches have demonstrated impressive results but are computationally expensive, and faster approaches model either only inter-reflection or only subsurface scattering. In this paper, we present a simple analytic model that combines diffuse inter-reflection and isotropic subsurface scattering. Our approach extends the classical work in radiosity by including a subsurface scattering matrix that operates in conjunction with the traditional form factor matrix. This subsurface scattering matrix can be constructed using analytic, measurement-based or simulation-based models and can capture both homogeneous and heterogeneous translucencies. Using a fast iterative solution to radiosity, we demonstrate scene relighting and dynamically varying object translucencies at near interactive rates.

A Systems Model for Ursodeoxycholic Acid Metabolism in Healthy and Patients With Primary Biliary Cirrhosis

PubMed Central

Dobbins, RL; O'Connor‐Semmes, RL; Young, MA

2016-01-01

A systems model was developed to describe the metabolism and disposition of ursodeoxycholic acid (UDCA) and its conjugates in healthy subjects based on pharmacokinetic (PK) data from published studies in order to study the distribution of oral UDCA and potential interactions influencing therapeutic effects upon interruption of its enterohepatic recirculation. The base model was empirically adapted to patients with primary biliary cirrhosis (PBC) based on current understanding of disease pathophysiology and clinical measurements. Simulations were performed for patients with PBC under two competing hypotheses: one for inhibition of ileal absorption of both UDCA and conjugates and the other only of conjugates. The simulations predicted distinctly different bile acid distribution patterns in plasma and bile. The UDCA model adapted to patients with PBC provides a platform to investigate a complex therapeutic drug interaction among UDCA, UDCA conjugates, and inhibition of ileal bile acid transport in this rare disease population. PMID:27537780

PyPLIF: Python-based Protein-Ligand Interaction Fingerprinting.

PubMed

Radifar, Muhammad; Yuniarti, Nunung; Istyastono, Enade Perdana

2013-01-01

Structure-based virtual screening (SBVS) methods often rely on docking score. The docking score is an over-simplification of the actual ligand-target binding. Its capability to model and predict the actual binding reality is limited. Recently, interaction fingerprinting (IFP) has come and offered us an alternative way to model reality. IFP provides us an alternate way to examine protein-ligand interactions. The docking score indicates the approximate affinity and IFP shows the interaction specificity. IFP is a method to convert three dimensional (3D) protein-ligand interactions into one dimensional (1D) bitstrings. The bitstrings are subsequently employed to compare the protein-ligand interaction predicted by the docking tool against the reference ligand. These comparisons produce scores that can be used to enhance the quality of SBVS campaigns. However, some IFP tools are either proprietary or using a proprietary library, which limits the access to the tools and the development of customized IFP algorithm. Therefore, we have developed PyPLIF, a Python-based open source tool to analyze IFP. In this article, we describe PyPLIF and its application to enhance the quality of SBVS in order to identify antagonists for estrogen α receptor (ERα). PyPLIF is freely available at http://code.google.com/p/pyplif.

The Volume Field Model about Strong Interaction and Weak Interaction

NASA Astrophysics Data System (ADS)

Liu, Rongwu

2016-03-01

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

Quantitative study of interactions between oxygen lone pair and aromatic rings: substituent effect and the importance of closeness of contact.

PubMed

Gung, Benjamin W; Zou, Yan; Xu, Zhigang; Amicangelo, Jay C; Irwin, Daniel G; Ma, Shengqian; Zhou, Hong-Cai

2008-01-18

Current models describe aromatic rings as polar groups based on the fact that benzene and hexafluorobenzene are known to have large and permanent quadrupole moments. This report describes a quantitative study of the interactions between oxygen lone pair and aromatic rings. We found that even electron-rich aromatic rings and oxygen lone pairs exhibit attractive interactions. Free energies of interactions are determined using the triptycene scaffold and the equilibrium constants were determined by low-temperature 1H NMR spectroscopy. An X-ray structure analysis for one of the model compounds confirms the close proximity between the oxygen and the center of the aromatic ring. Theoretical calculations at the MP2/aug-cc-pVTZ level corroborate the experimental results. The origin of attractive interactions was explored by using aromatic rings with a wide range of substituents. The interactions between an oxygen lone pair and an aromatic ring are attractive at van der Waals' distance even with electron-donating substituents. Electron-withdrawing groups increase the strength of the attractive interactions. The results from this study can be only partly rationalized by using the current models of aromatic system. Electrostatic-based models are consistent with the fact that stronger electron-withdrawing groups lead to stronger attractions, but fail to predict or rationalize the fact that weak attractions even exist between electron-rich arenes and oxygen lone pairs. The conclusion from this study is that aromatic rings cannot be treated as a simple quadrupolar functional group at van der Waals' distance. Dispersion forces and local dipole should also be considered.

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

PubMed

Aurich, Maike K; Thiele, Ines

2016-01-01

Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

A Bayesian approach to estimating hidden variables as well as missing and wrong molecular interactions in ordinary differential equation-based mathematical models.

PubMed

Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger

2017-06-01

Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).

Course Design and Technology for Synchronous Interaction in an Online Course

ERIC Educational Resources Information Center

Kreie, Jennifer; Johnson, Sandra; Lebsock, Michelle

2017-01-01

Online course offerings in higher education continue to grow because of the strong demand. Though many online courses are based on an asynchronous model, there are courses that require real-time interaction between students themselves and between students and the instructor, which means synchronous interaction is necessary. The technology exists…

Quantitative Analysis of Complex Drug-Drug Interactions Between Repaglinide and Cyclosporin A/Gemfibrozil Using Physiologically Based Pharmacokinetic Models With In Vitro Transporter/Enzyme Inhibition Data.

PubMed

Kim, Soo-Jin; Toshimoto, Kota; Yao, Yoshiaki; Yoshikado, Takashi; Sugiyama, Yuichi

2017-09-01

Quantitative analysis of transporter- and enzyme-mediated complex drug-drug interactions (DDIs) is challenging. Repaglinide (RPG) is transported into the liver by OATP1B1 and then is metabolized by CYP2C8 and CYP3A4. The purpose of this study was to describe the complex DDIs of RPG quantitatively based on unified physiologically based pharmacokinetic (PBPK) models using in vitro K i values for OATP1B1, CYP3A4, and CYP2C8. Cyclosporin A (CsA) or gemfibrozil (GEM) increased the blood concentrations of RPG. The time profiles of RPG and the inhibitors were analyzed by PBPK models, considering the inhibition of OATP1B1 and CYP3A4 by CsA or OATP1B1 inhibition by GEM and its glucuronide and the mechanism-based inhibition of CYP2C8 by GEM glucuronide. RPG-CsA interaction was closely predicted using a reported in vitro K i,OATP1B1 value in the presence of CsA preincubation. RPG-GEM interaction was underestimated compared with observed data, but the simulation was improved with the increase of f m,CYP2C8 . These results based on in vitro K i values for transport and metabolism suggest the possibility of a bottom-up approach with in vitro inhibition data for the prediction of complex DDIs using unified PBPK models and in vitro f m value of a substrate for multiple enzymes should be considered carefully for the prediction. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

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

PubMed

Keum, Jongsoo; Nam, Hojung

2017-01-01

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

Explicit ions/implicit water generalized Born model for nucleic acids

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

Tolokh, Igor S.; Thomas, Dennis G.; Onufriev, Alexey V.

Ion atmosphere around highly charged nucleic acid molecules plays a significant role in their dynamics, structure and interactions. Here we utilized the implicit solvent framework to develop a model for the explicit treatment of ions interacting with nucleic acid molecules. The proposed explicit ions/implicit water model is based on a significantly modified generalized Born (GB) model, and utilizes a non-standard approach to defining the solute/solvent dielectric boundary. Specifically, the model includes modifications to the GB interaction terms for the case of multiple interacting solutes – disconnected dielectric boundary around the solute-ion or ion-ion pairs. Fully analytical description of all energymore » components for charge-charge interactions is provided. The effectiveness of the approach is demonstrated by calculating the potential of mean force (PMF) for Na+-Cl− ion pair and by carrying out a set of Monte Carlo (MC) simulations of mono- and trivalent ions interacting with DNA and RNA duplexes. The monovalent (Na+) and trivalent (CoHex3+) counterion distributions predicted by the model are in close quantitative agreement with all-atom explicit water molecular dynamics simulations used as reference. Expressed in the units of energy, the maximum deviations of local ion concentrations from the reference are within kBT. The proposed explicit ions/implicit water GB model is able to resolve subtle features and differences of CoHex distributions around DNA and RNA duplexes. These features include preferential CoHex binding inside the major groove of RNA duplex, in contrast to CoHex biding at the "external" surface of the sugar-phosphate backbone of DNA duplex; these differences in the counterion binding patters were shown earlier to be responsible for the observed drastic differences in condensation propensities between short DNA and RNA duplexes. MC simulations of CoHex ions interacting with homopolymeric poly(dA·dT) DNA duplex with modified (de-methylated) and native Thymine bases are used to explore the physics behind CoHex-Thymine interactions. The simulations suggest that the ion desolvation penalty due to proximity to the low dielectric volume of the methyl group can contribute significantly to CoHex-Thymine interactions. Compared to the steric repulsion between the ion and the methyl group, the desolvation penalty interaction has a longer range, and may be important to consider in the context of methylation effects on DNA condensation.« less

Explicit ions/implicit water generalized Born model for nucleic acids

NASA Astrophysics Data System (ADS)

Tolokh, Igor S.; Thomas, Dennis G.; Onufriev, Alexey V.

2018-05-01

The ion atmosphere around highly charged nucleic acid molecules plays a significant role in their dynamics, structure, and interactions. Here we utilized the implicit solvent framework to develop a model for the explicit treatment of ions interacting with nucleic acid molecules. The proposed explicit ions/implicit water model is based on a significantly modified generalized Born (GB) model and utilizes a non-standard approach to define the solute/solvent dielectric boundary. Specifically, the model includes modifications to the GB interaction terms for the case of multiple interacting solutes—disconnected dielectric boundary around the solute-ion or ion-ion pairs. A fully analytical description of all energy components for charge-charge interactions is provided. The effectiveness of the approach is demonstrated by calculating the potential of mean force for Na+-Cl- ion pair and by carrying out a set of Monte Carlo (MC) simulations of mono- and trivalent ions interacting with DNA and RNA duplexes. The monovalent (Na+) and trivalent (CoHex3+) counterion distributions predicted by the model are in close quantitative agreement with all-atom explicit water molecular dynamics simulations used as reference. Expressed in the units of energy, the maximum deviations of local ion concentrations from the reference are within kBT. The proposed explicit ions/implicit water GB model is able to resolve subtle features and differences of CoHex distributions around DNA and RNA duplexes. These features include preferential CoHex binding inside the major groove of the RNA duplex, in contrast to CoHex biding at the "external" surface of the sugar-phosphate backbone of the DNA duplex; these differences in the counterion binding patters were earlier shown to be responsible for the observed drastic differences in condensation propensities between short DNA and RNA duplexes. MC simulations of CoHex ions interacting with the homopolymeric poly(dA.dT) DNA duplex with modified (de-methylated) and native thymine bases are used to explore the physics behind CoHex-thymine interactions. The simulations suggest that the ion desolvation penalty due to proximity to the low dielectric volume of the methyl group can contribute significantly to CoHex-thymine interactions. Compared to the steric repulsion between the ion and the methyl group, the desolvation penalty interaction has a longer range and may be important to consider in the context of methylation effects on DNA condensation.

Building protein-protein interaction networks for Leishmania species through protein structural information.

PubMed

Dos Santos Vasconcelos, Crhisllane Rafaele; de Lima Campos, Túlio; Rezende, Antonio Mauro

2018-03-06

Systematic analysis of a parasite interactome is a key approach to understand different biological processes. It makes possible to elucidate disease mechanisms, to predict protein functions and to select promising targets for drug development. Currently, several approaches for protein interaction prediction for non-model species incorporate only small fractions of the entire proteomes and their interactions. Based on this perspective, this study presents an integration of computational methodologies, protein network predictions and comparative analysis of the protozoan species Leishmania braziliensis and Leishmania infantum. These parasites cause Leishmaniasis, a worldwide distributed and neglected disease, with limited treatment options using currently available drugs. The predicted interactions were obtained from a meta-approach, applying rigid body docking tests and template-based docking on protein structures predicted by different comparative modeling techniques. In addition, we trained a machine-learning algorithm (Gradient Boosting) using docking information performed on a curated set of positive and negative protein interaction data. Our final model obtained an AUC = 0.88, with recall = 0.69, specificity = 0.88 and precision = 0.83. Using this approach, it was possible to confidently predict 681 protein structures and 6198 protein interactions for L. braziliensis, and 708 protein structures and 7391 protein interactions for L. infantum. The predicted networks were integrated to protein interaction data already available, analyzed using several topological features and used to classify proteins as essential for network stability. The present study allowed to demonstrate the importance of integrating different methodologies of interaction prediction to increase the coverage of the protein interaction of the studied protocols, besides it made available protein structures and interactions not previously reported.

Proceedings of the 2006 Toxicology and Risk Assessment Conference: Applying Mode of Action in Risk Assessment

DTIC Science & Technology

2006-07-01

physiologically-based pharmacokinetic modeling of interactions and multiple route exposure assessment; and integrating relative potency factors with response...defaults, while at the other end is the use of extensive chemical-specific data in physiologically based pharmacokinetic (PBPK) modeling or even...for internal dosimetry as well as an in depth prospective on the use and limitations of physiologically based pharmacokinetic (PBPK) models in

Screening of benzamidine-based thrombin inhibitors via a linear interaction energy in continuum electrostatics model

NASA Astrophysics Data System (ADS)

Nicolotti, Orazio; Giangreco, Ilenia; Miscioscia, Teresa Fabiola; Convertino, Marino; Leonetti, Francesco; Pisani, Leonardo; Carotti, Angelo

2010-02-01

A series of 27 benzamidine inhibitors covering a wide range of biological activity and chemical diversity was analysed to derive a Linear Interaction Energy in Continuum Electrostatics (LIECE) model for analysing the thrombin inhibitory activity. The main interactions occurring at the thrombin binding site and the preferred binding conformations of inhibitors were explicitly biased by including into the LIECE model 10 compounds extracted from X-ray solved thrombin-inhibitor complexes available from the Protein Data Bank (PDB). Supported by a robust statistics ( r 2 = 0.698; q 2 = 0.662), the LIECE model was successful in predicting the inhibitory activity for about 76% of compounds ( r ext 2 ≥ 0.600) from a larger external test set encompassing 88 known thrombin inhibitors and, more importantly, in retrieving, at high sensitivity and with better performance than docking and shape-based methods, active compounds from a thrombin combinatorial library of 10240 mimetic chemical products. The herein proposed LIECE model has the potential for successfully driving the design of novel thrombin inhibitors with benzamidine and/or benzamidine-like chemical structure.

Cogenerating and pre-annihilating dark matter by a new gauge interaction in a unified model

DOE PAGES

Barr, S. M.; Scherrer, Robert J.

2016-05-31

Here, grand unified theories based on large groups (with rank ≥ 6) are a natural context for dark matter models. They contain Standard-Model-singlet fermions that could be dark matter candidates, and can contain new non-abelian interactions whose sphalerons convert baryons, leptons, and dark matter into each other, ''cogenerating" a dark matter asymmetry comparable to the baryon asymmetry. In this paper it is shown that the same non-abelian interactions can ''pre-annihilate" the symmetric component of heavy dark matter particles χ, which then decay late into light stable dark matter particles ζ that inherit their asymmetry. We derive cosmological constraints on themore » parameters of such models. The mass of χ must be < 3000 TeV and their decays must happen when 2 × 10 –7 < T dec/mχ < 10 –4. It is shown that such decays can come from d=5 operators with coefficients of order 1/MGUT or 1/M Pℓ. We present a simple realization of our model based on the group SU(7).« less

Sequence memory based on coherent spin-interaction neural networks.

PubMed

Xia, Min; Wong, W K; Wang, Zhijie

2014-12-01

Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.

Three Dimensional Explicit Model for Cometary Tail Ions Interactions with Solar Wind

NASA Astrophysics Data System (ADS)

Al Bermani, M. J. F.; Alhamed, S. A.; Khalaf, S. Z.; Ali, H. Sh.; Selman, A. A.

2009-06-01

The different interactions between cometary tail and solar wind ions are studied in the present paper based on three-dimensional Lax explicit method. The model used in this research is based on the continuity equations describing the cometary tail-solar wind interactions. Three dimensional system was considered in this paper. Simulation of the physical system was achieved using computer code written using Matlab 7.0. The parameters studied here assumed Halley comet type and include the particle density rho, the particles velocity v, the magnetic field strength B, dynamic pressure p and internal energy E. The results of the present research showed that the interaction near the cometary nucleus is mainly affected by the new ions added to the plasma of the solar wind, which increases the average molecular weight and result in many unique characteristics of the cometary tail. These characteristics were explained in the presence of the IMF.

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

The research of distributed interactive simulation based on HLA in coal mine industry inherent safety

NASA Astrophysics Data System (ADS)

Dou, Zhi-Wu

2010-08-01

To solve the inherent safety problem puzzling the coal mining industry, analyzing the characteristic and the application of distributed interactive simulation based on high level architecture (DIS/HLA), a new method is proposed for developing coal mining industry inherent safety distributed interactive simulation adopting HLA technology. Researching the function and structure of the system, a simple coal mining industry inherent safety is modeled with HLA, the FOM and SOM are developed, and the math models are suggested. The results of the instance research show that HLA plays an important role in developing distributed interactive simulation of complicated distributed system and the method is valid to solve the problem puzzling coal mining industry. To the coal mining industry, the conclusions show that the simulation system with HLA plays an important role to identify the source of hazard, to make the measure for accident, and to improve the level of management.

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

An analytically-based method for predicting the noise generated by the interaction between turbulence and a serrated leading edge

NASA Astrophysics Data System (ADS)

Mathews, J. R.; Peake, N.

2018-05-01

This paper considers the interaction of turbulence with a serrated leading edge. We investigate the noise produced by an aerofoil moving through a turbulent perturbation to uniform flow by considering the scattered pressure from the leading edge. We model the aerofoil as an infinite half plane with a leading edge serration, and develop an analytical model using a Green's function based upon the work of Howe. This allows us to consider both deterministic eddies and synthetic turbulence interacting with the leading edge. We show that it is possible to reduce the noise by using a serrated leading edge compared with a straight edge, but the optimal noise-reducing choice of serration is hard to predict due to the complex interaction. We also consider the effect of angle of attack, and find that in general the serrations are less effective at higher angles of attack.

Research on monocentric model of urbanization by agent-based simulation

NASA Astrophysics Data System (ADS)

Xue, Ling; Yang, Kaizhong

2008-10-01

Over the past years, GIS have been widely used for modeling urbanization from a variety of perspectives such as digital terrain representation and overlay analysis using cell-based data platform. Similarly, simulation of urban dynamics has been achieved with the use of Cellular Automata. In contrast to these approaches, agent-based simulation provides a much more powerful set of tools. This allows researchers to set up a counterpart for real environmental and urban systems in computer for experimentation and scenario analysis. This Paper basically reviews the research on the economic mechanism of urbanization and an agent-based monocentric model is setup for further understanding the urbanization process and mechanism in China. We build an endogenous growth model with dynamic interactions between spatial agglomeration and urban development by using agent-based simulation. It simulates the migration decisions of two main types of agents, namely rural and urban households between rural and urban area. The model contains multiple economic interactions that are crucial in understanding urbanization and industrial process in China. These adaptive agents can adjust their supply and demand according to the market situation by a learning algorithm. The simulation result shows this agent-based urban model is able to perform the regeneration and to produce likely-to-occur projections of reality.

Approximating recreation site choice: the predictive capability of a lexicographic semi-order model

Treesearch

Alan E. Watson; Joseph W. Roggenbuck

1985-01-01

The relevancy of a lexicographic semi-order model, as a basis for development of a microcomputer-based decision aid for backcountry hikers, was investigated. In an interactive microcomputer exercise, it was found that a decision aid based upon this model may assist recreationists in reduction of an alternative set to a cognitively manageable number.

A Model-Based Cluster Analysis of Maternal Emotion Regulation and Relations to Parenting Behavior.

PubMed

Shaffer, Anne; Whitehead, Monica; Davis, Molly; Morelen, Diana; Suveg, Cynthia

2017-10-15

In a diverse community sample of mothers (N = 108) and their preschool-aged children (M age  = 3.50 years), this study conducted person-oriented analyses of maternal emotion regulation (ER) based on a multimethod assessment incorporating physiological, observational, and self-report indicators. A model-based cluster analysis was applied to five indicators of maternal ER: maternal self-report, observed negative affect in a parent-child interaction, baseline respiratory sinus arrhythmia (RSA), and RSA suppression across two laboratory tasks. Model-based cluster analyses revealed four maternal ER profiles, including a group of mothers with average ER functioning, characterized by socioeconomic advantage and more positive parenting behavior. A dysregulated cluster demonstrated the greatest challenges with parenting and dyadic interactions. Two clusters of intermediate dysregulation were also identified. Implications for assessment and applications to parenting interventions are discussed. © 2017 Family Process Institute.

A time domain frequency-selective multivariate Granger causality approach.

PubMed

Leistritz, Lutz; Witte, Herbert

2016-08-01

The investigation of effective connectivity is one of the major topics in computational neuroscience to understand the interaction between spatially distributed neuronal units of the brain. Thus, a wide variety of methods has been developed during the last decades to investigate functional and effective connectivity in multivariate systems. Their spectrum ranges from model-based to model-free approaches with a clear separation into time and frequency range methods. We present in this simulation study a novel time domain approach based on Granger's principle of predictability, which allows frequency-selective considerations of directed interactions. It is based on a comparison of prediction errors of multivariate autoregressive models fitted to systematically modified time series. These modifications are based on signal decompositions, which enable a targeted cancellation of specific signal components with specific spectral properties. Depending on the embedded signal decomposition method, a frequency-selective or data-driven signal-adaptive Granger Causality Index may be derived.

The Atlas of Physiology and Pathophysiology: Web-based multimedia enabled interactive simulations.

PubMed

Kofranek, Jiri; Matousek, Stanislav; Rusz, Jan; Stodulka, Petr; Privitzer, Pavol; Matejak, Marek; Tribula, Martin

2011-11-01

The paper is a presentation of the current state of development for the Atlas of Physiology and Pathophysiology (Atlas). Our main aim is to provide a novel interactive multimedia application that can be used for biomedical education where (a) simulations are combined with tutorials and (b) the presentation layer is simplified while the underlying complexity of the model is retained. The development of the Atlas required the cooperation of many professionals including teachers, system analysts, artists, and programmers. During the design of the Atlas, tools were developed that allow for component-based creation of simulation models, creation of interactive multimedia and their final coordination into a compact unit based on the given design. The Atlas is a freely available online application, which can help to explain the function of individual physiological systems and the causes and symptoms of their disorders. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Simulation of Hydraulic and Natural Fracture Interaction Using a Coupled DFN-DEM Model

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

Zhou, J.; Huang, H.; Deo, M.

2016-03-01

The presence of natural fractures will usually result in a complex fracture network due to the interactions between hydraulic and natural fracture. The reactivation of natural fractures can generally provide additional flow paths from formation to wellbore which play a crucial role in improving the hydrocarbon recovery in these ultra-low permeability reservoir. Thus, accurate description of the geometry of discrete fractures and bedding is highly desired for accurate flow and production predictions. Compared to conventional continuum models that implicitly represent the discrete feature, Discrete Fracture Network (DFN) models could realistically model the connectivity of discontinuities at both reservoir scale andmore » well scale. In this work, a new hybrid numerical model that couples Discrete Fracture Network (DFN) and Dual-Lattice Discrete Element Method (DL-DEM) is proposed to investigate the interaction between hydraulic fracture and natural fractures. Based on the proposed model, the effects of natural fracture orientation, density and injection properties on hydraulic-natural fractures interaction are investigated.« less

Simulation of Hydraulic and Natural Fracture Interaction Using a Coupled DFN-DEM Model

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

J. Zhou; H. Huang; M. Deo

The presence of natural fractures will usually result in a complex fracture network due to the interactions between hydraulic and natural fracture. The reactivation of natural fractures can generally provide additional flow paths from formation to wellbore which play a crucial role in improving the hydrocarbon recovery in these ultra-low permeability reservoir. Thus, accurate description of the geometry of discrete fractures and bedding is highly desired for accurate flow and production predictions. Compared to conventional continuum models that implicitly represent the discrete feature, Discrete Fracture Network (DFN) models could realistically model the connectivity of discontinuities at both reservoir scale andmore » well scale. In this work, a new hybrid numerical model that couples Discrete Fracture Network (DFN) and Dual-Lattice Discrete Element Method (DL-DEM) is proposed to investigate the interaction between hydraulic fracture and natural fractures. Based on the proposed model, the effects of natural fracture orientation, density and injection properties on hydraulic-natural fractures interaction are investigated.« less

Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273

The Role of Twinning Deformation on the Hardening Response of Polycrystalline Magnesium from Discrete Dislocation Dynamics Simulations

DTIC Science & Technology

2015-01-01

polycrystalline magnesium (Mg) was studied using three-dimensional discrete dislocation dynamics ( DDD ). A systematic interaction model between dislocations...and f1012g tension twin boundaries (TBs) was proposed and introduced into the DDD framework. In addition, a nominal grain boundary (GB) model based...dynamics ( DDD ). A systematic interaction model between dislocations and f10 12g tension twin boundaries (TBs) was proposed and introduced into the DDD

Dynamical network interactions in distributed control of robots

NASA Astrophysics Data System (ADS)

Buscarino, Arturo; Fortuna, Luigi; Frasca, Mattia; Rizzo, Alessandro

2006-03-01

In this paper the dynamical network model of the interactions within a group of mobile robots is investigated and proposed as a possible strategy for controlling the robots without central coordination. Motivated by the results of the analysis of our simple model, we show that the system performance in the presence of noise can be improved by including long-range connections between the robots. Finally, a suitable strategy based on this model to control exploration and transport is introduced.

An Agent-Based Modeling Framework and Application for the Generic Nuclear Fuel Cycle

NASA Astrophysics Data System (ADS)

Gidden, Matthew J.

Key components of a novel methodology and implementation of an agent-based, dynamic nuclear fuel cycle simulator, Cyclus , are presented. The nuclear fuel cycle is a complex, physics-dependent supply chain. To date, existing dynamic simulators have not treated constrained fuel supply, time-dependent, isotopic-quality based demand, or fuel fungibility particularly well. Utilizing an agent-based methodology that incorporates sophisticated graph theory and operations research techniques can overcome these deficiencies. This work describes a simulation kernel and agents that interact with it, highlighting the Dynamic Resource Exchange (DRE), the supply-demand framework at the heart of the kernel. The key agent-DRE interaction mechanisms are described, which enable complex entity interaction through the use of physics and socio-economic models. The translation of an exchange instance to a variant of the Multicommodity Transportation Problem, which can be solved feasibly or optimally, follows. An extensive investigation of solution performance and fidelity is then presented. Finally, recommendations for future users of Cyclus and the DRE are provided.

Hydrodynamic Equations for Flocking Models without Velocity Alignment

NASA Astrophysics Data System (ADS)

Peruani, Fernando

2017-10-01

The spontaneous emergence of collective motion patterns is usually associated with the presence of a velocity alignment mechanism that mediates the interactions among the moving individuals. Despite of this widespread view, it has been shown recently that several flocking behaviors can emerge in the absence of velocity alignment and as a result of short-range, position-based, attractive forces that act inside a vision cone. Here, we derive the corresponding hydrodynamic equations of a microscopic position-based flocking model, reviewing and extending previous reported results. In particular, we show that three distinct macroscopic collective behaviors can be observed: i) the coarsening of aggregates with no orientational order, ii) the emergence of static, elongated nematic bands, and iii) the formation of moving, locally polar structures, which we call worms. The derived hydrodynamic equations indicate that active particles interacting via position-based interactions belong to a distinct class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems.

Numerical studies of wall–plasma interactions and ionization phenomena in an ablative pulsed plasma thruster

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

Yang, Lei; School of Astronautics, Beihang University, Beijing 100191; Zeng, Guangshang

2016-07-15

Wall–plasma interactions excited by ablation controlled arcs are very critical physical processes in pulsed plasma thrusters (PPTs). Their effects on the ionization processes of ablated vapor into discharge plasma directly determine PPT performances. To reveal the physics governing the ionization phenomena in PPT discharge, a modified model taking into account the pyrolysis effect of heated polytetrafluoroethylene propellant on the wall–plasma interactions was developed. The feasibility of the modified model was analyzed by creating a one-dimensional simulation of a rectangular ablative PPT. The wall–plasma interaction results based on this modified model were found to be more realistic than for the unmodifiedmore » model; this reflects the dynamic changes of the inflow parameters during discharge in our model. Furthermore, the temporal and spatial variations of the different plasma species in the discharge chamber were numerically studied. The numerical studies showed that polytetrafluoroethylene plasma was mainly composed of monovalent ions; carbon and fluorine ions were concentrated in the upstream and downstream discharge chamber, respectively. The results based on this modified model were in good agreement with the experimental formation times of the various plasma species. A large number of short-lived and highly ionized carbon and fluorine species (divalent and trivalent ions) were created during initial discharge. These highly ionized species reached their peak density earlier than the singly ionized species.« less

An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks

PubMed Central

Huff, Emily Silver; Leahy, Jessica E.; Hiebeler, David; Weiskittel, Aaron R.; Noblet, Caroline L.

2015-01-01

Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner’s management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of ‘harvest readiness’ and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior. PMID:26562429

Template-Based Modeling of Protein-RNA Interactions.

PubMed

Zheng, Jinfang; Kundrotas, Petras J; Vakser, Ilya A; Liu, Shiyong

2016-09-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes.

Interactive activation and mutual constraint satisfaction in perception and cognition.

PubMed

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

2014-08-01

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

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

PubMed

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

2018-06-02

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

A mathematical model for the interactive behavior of sulfate-reducing bacteria and methanogens during anaerobic digestion.

PubMed

Ahammad, S Ziauddin; Gomes, James; Sreekrishnan, T R

2011-09-01

Anaerobic degradation of waste involves different classes of microorganisms, and there are different types of interactions among them for substrates, terminal electron acceptors, and so on. A mathematical model is developed based on the mass balance of different substrates, products, and microbes present in the system to study the interaction between methanogens and sulfate-reducing bacteria (SRB). The performance of major microbial consortia present in the system, such as propionate-utilizing acetogens, butyrate-utilizing acetogens, acetoclastic methanogens, hydrogen-utilizing methanogens, and SRB were considered and analyzed in the model. Different substrates consumed and products formed during the process also were considered in the model. The experimental observations and model predictions showed very good prediction capabilities of the model. Model prediction was validated statistically. It was observed that the model-predicted values matched the experimental data very closely, with an average error of 3.9%.

Conductance in inhomogeneous quantum wires: Luttinger liquid predictions and quantum Monte Carlo results

NASA Astrophysics Data System (ADS)

Morath, D.; Sedlmayr, N.; Sirker, J.; Eggert, S.

2016-09-01

We study electron and spin transport in interacting quantum wires contacted by noninteracting leads. We theoretically model the wire and junctions as an inhomogeneous chain where the parameters at the junction change on the scale of the lattice spacing. We study such systems analytically in the appropriate limits based on Luttinger liquid theory and compare the results to quantum Monte Carlo calculations of the conductances and local densities near the junction. We first consider an inhomogeneous spinless fermion model with a nearest-neighbor interaction and then generalize our results to a spinful model with an on-site Hubbard interaction.

Mechanistic modeling to predict the transporter- and enzyme-mediated drug-drug interactions of repaglinide.

PubMed

Varma, Manthena V S; Lai, Yurong; Kimoto, Emi; Goosen, Theunis C; El-Kattan, Ayman F; Kumar, Vikas

2013-04-01

Quantitative prediction of complex drug-drug interactions (DDIs) is challenging. Repaglinide is mainly metabolized by cytochrome-P-450 (CYP)2C8 and CYP3A4, and is also a substrate of organic anion transporting polypeptide (OATP)1B1. The purpose is to develop a physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and DDIs of repaglinide. In vitro hepatic transport of repaglinide, gemfibrozil and gemfibrozil 1-O-β-glucuronide was characterized using sandwich-culture human hepatocytes. A PBPK model, implemented in Simcyp (Sheffield, UK), was developed utilizing in vitro transport and metabolic clearance data. In vitro studies suggested significant active hepatic uptake of repaglinide. Mechanistic model adequately described repaglinide pharmacokinetics, and successfully predicted DDIs with several OATP1B1 and CYP3A4 inhibitors (<10% error). Furthermore, repaglinide-gemfibrozil interaction at therapeutic dose was closely predicted using in vitro fraction metabolism for CYP2C8 (0.71), when primarily considering reversible inhibition of OATP1B1 and mechanism-based inactivation of CYP2C8 by gemfibrozil and gemfibrozil 1-O-β-glucuronide. This study demonstrated that hepatic uptake is rate-determining in the systemic clearance of repaglinide. The model quantitatively predicted several repaglinide DDIs, including the complex interactions with gemfibrozil. Both OATP1B1 and CYP2C8 inhibition contribute significantly to repaglinide-gemfibrozil interaction, and need to be considered for quantitative rationalization of DDIs with either drug.

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.

Interactions of sugar-based bolaamphiphiles with biomimetic systems of plasma membranes.

PubMed

Nasir, Mehmet Nail; Crowet, Jean-Marc; Lins, Laurence; Obounou Akong, Firmin; Haudrechy, Arnaud; Bouquillon, Sandrine; Deleu, Magali

2016-11-01

Glycolipids constitute a class of molecules with various biological activities. Among them, sugar-based bolaamphiphiles characterized by their biocompatibility, biodegradability and lower toxicity, became interesting for the development of efficient and low cost lipid-based drug delivery systems. Their activity seems to be closely related to their interactions with the lipid components of the plasma membrane of target cells. Despite many works devoted to the chemical synthesis and characterization of sugar-based bolaamphiphiles, their interactions with plasma membrane have not been completely elucidated. In this work, two sugar-based bolaamphiphiles differing only at the level of their sugar residues were chemically synthetized. Their interactions with membranes have been investigated using model membranes containing or not sterol and with in silico approaches. Our findings indicate that the nature of sugar residues has no significant influence for their membrane interacting properties, while the presence of sterol attenuates the interactions of both bolaamphiphiles with the membrane systems. The understanding of this distinct behavior of bolaamphiphiles towards sterol-containing membrane systems could be useful for their applications as drug delivery systems. Copyright © 2016. Published by Elsevier B.V.

Constraint-Based Modeling: From Cognitive Theory to Computer Tutoring--and Back Again

ERIC Educational Resources Information Center

Ohlsson, Stellan

2016-01-01

The ideas behind the constraint-based modeling (CBM) approach to the design of intelligent tutoring systems (ITSs) grew out of attempts in the 1980's to clarify how declarative and procedural knowledge interact during skill acquisition. The learning theory that underpins CBM was based on two conceptual innovations. The first innovation was to…

Development of Support Service for Prevention and Recovery from Dementia and Science of Lethe

NASA Astrophysics Data System (ADS)

Otake, Mihoko

Purpose of this study is to explore service design method through the development of support service for prevention and recovery from dementia towards science of lethe. We designed and implemented conversation support service via coimagination method based on multiscale service design method, both were proposed by the author. Multiscale service model consists of tool, event, human, network, style and rule. Service elements at different scales are developed according to the model. Interactive conversation supported by coimagination method activates cognitive functions so as to prevent progress of dementia. This paper proposes theoretical bases for science of lethe. Firstly, relationship among coimagination method and three cognitive functions including division of attention, planning, episodic memory which decline at mild cognitive imparement. Secondly, thought state transition model during conversation which describes cognitive enhancement via interactive communication. Thirdly, Set Theoretical Measure of Interaction is proposed for evaluating effectiveness of conversation to cognitive enhancement. Simulation result suggests that the ideas which cannot be explored by each speaker are explored during interactive conversation. Finally, coimagination method compared with reminiscence therapy and its possibility for collaboration is discussed.

Complex molecular assemblies at hand via interactive simulations.

PubMed

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

2009-11-30

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

Cooperative Learning and Dyadic Interactions: Two Modes of Knowledge Construction in Socio-Constructivist Settings for Team-Sport Teaching

ERIC Educational Resources Information Center

Darnis, Florence; Lafont, Lucile

2015-01-01

Background: Within a socio-constructivist perspective, this study is situated at the crossroads of three theoretical approaches. First, it is based upon team sport and the tactical act model in games teaching. Second, it took place in dyadic or small group learning conditions with verbal interaction. Furthermore, these interventions were based on…

Transition to parenthood: the role of social interaction and endogenous networks.

PubMed

Diaz, Belinda Aparicio; Fent, Thomas; Prskawetz, Alexia; Bernardi, Laura

2011-05-01

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdependencies across individuals' transition to parenthood and its timing, we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics: age, intended education, and parity. Agents endogenously form their network based on social closeness. Network members may then influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social interactions can explain the shift of first-birth probabilities in Austria during the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

Image-based 3D reconstruction and virtual environmental walk-through

NASA Astrophysics Data System (ADS)

Sun, Jifeng; Fang, Lixiong; Luo, Ying

2001-09-01

We present a 3D reconstruction method, which combines geometry-based modeling, image-based modeling and rendering techniques. The first component is an interactive geometry modeling method which recovery of the basic geometry of the photographed scene. The second component is model-based stereo algorithm. We discus the image processing problems and algorithms of walking through in virtual space, then designs and implement a high performance multi-thread wandering algorithm. The applications range from architectural planning and archaeological reconstruction to virtual environments and cinematic special effects.

A Novel and Freely Available Interactive 3d Model of the Internal Carotid Artery.

PubMed

Valera-Melé, Marc; Puigdellívol-Sánchez, Anna; Mavar-Haramija, Marija; Juanes-Méndez, Juan A; San-Román, Luis; de Notaris, Matteo; Prats-Galino, Alberto

2018-03-05

We describe a new and freely available 3D interactive model of the intracranial internal carotid artery (ICA) and the skull base that also allows to display and compare its main segment classifications. High-resolution 3D human angiography (isometric voxel's size 0.36 mm) and Computed Tomography angiography images were exported to Virtual Reality Modeling Language (VRML) format for processing in a 3D software platform and embedding in a 3D Portable Document Format (PDF) document that can be freely downloaded at http://diposit.ub.edu/dspace/handle/2445/112442 and runs under Acrobat Reader on Mac and Windows computers and Windows 10 tablets. The 3D-PDF allows for visualisation and interaction through JavaScript-based functions (including zoom, rotation, selective visualization and transparentation of structures or a predefined sequence view of the main segment classifications if desired). The ICA and its main branches and loops, the Gasserian ganglion, the petrolingual ligament and the proximal and distal dural rings within the skull base environment (anterior and posterior clinoid processes, silla turcica, ethmoid and sphenoid bones, orbital fossae) may be visualized from different perspectives. This interactive 3D-PDF provides virtual views of the ICA and becomes an innovative tool to improve the understanding of the neuroanatomy of the ICA and surrounding structures.

Guided exploration in virtual environments

NASA Astrophysics Data System (ADS)

Beckhaus, Steffi; Eckel, Gerhard; Strothotte, Thomas

2001-06-01

We describe an application supporting alternating interaction and animation for the purpose of exploration in a surround- screen projection-based virtual reality system. The exploration of an environment is a highly interactive and dynamic process in which the presentation of objects of interest can give the user guidance while exploring the scene. Previous systems for automatic presentation of models or scenes need either cinematographic rules, direct human interaction, framesets or precalculation (e.g. precalculation of paths to a predefined goal). We report on the development of a system that can deal with rapidly changing user interest in objects of a scene or model as well as with dynamic models and changes of the camera position introduced interactively by the user. It is implemented as a potential-field based camera data generating system. In this paper we describe the implementation of our approach in a virtual art museum on the CyberStage, our surround-screen projection-based stereoscopic display. The paradigm of guided exploration is introduced describing the freedom of the user to explore the museum autonomously. At the same time, if requested by the user, guided exploration provides just-in-time navigational support. The user controls this support by specifying the current field of interest in high-level search criteria. We also present an informal user study evaluating this approach.

High-performance biocomputing for simulating the spread of contagion over large contact networks

PubMed Central

2012-01-01

Background Many important biological problems can be modeled as contagion diffusion processes over interaction networks. This article shows how the EpiSimdemics interaction-based simulation system can be applied to the general contagion diffusion problem. Two specific problems, computational epidemiology and human immune system modeling, are given as examples. We then show how the graphics processing unit (GPU) within each compute node of a cluster can effectively be used to speed-up the execution of these types of problems. Results We show that a single GPU can accelerate the EpiSimdemics computation kernel by a factor of 6 and the entire application by a factor of 3.3, compared to the execution time on a single core. When 8 CPU cores and 2 GPU devices are utilized, the speed-up of the computational kernel increases to 9.5. When combined with effective techniques for inter-node communication, excellent scalability can be achieved without significant loss of accuracy in the results. Conclusions We show that interaction-based simulation systems can be used to model disparate and highly relevant problems in biology. We also show that offloading some of the work to GPUs in distributed interaction-based simulations can be an effective way to achieve increased intra-node efficiency. PMID:22537298

Teaching Evidence-Based Medicine: A Regional Dissemination Model.

ERIC Educational Resources Information Center

Leipzig, Rosanne M.; Wallace, Eleanor Z.; Smith, Lawrence G.; Sullivant, Jean; Dunn, Kathel; McGinn, Thomas

2003-01-01

Described and evaluated an interactive course designed to create a cadre of medical school faculty in New York who could integrate evidence-based medicine into their training programs. Findings for representatives of 30 internal medicine residency programs show the usefulness of the regional dissemination model used. (SLD)

Logic-Based Models for the Analysis of Cell Signaling Networks†

PubMed Central

2010-01-01

Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks. PMID:20225868

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.

Dispersion Interactions between Urea and Nucleobases Contribute to the Destabilization of RNA by Urea in Aqueous Solution

PubMed Central

Kasavajhala, Koushik; Bikkina, Swetha; Patil, Indrajit; MacKerell, Alexander D.; Priyakumar, U. Deva

2015-01-01

Urea has long been used to investigate protein folding and, more recently, RNA folding. Studies have proposed that urea denatures RNA by participating in stacking interactions and hydrogen bonds with nucleic acid bases. In this study, the ability of urea to form unconventional stacking interactions with RNA bases is investigated using ab initio calculations (RI-MP2 and CCSD(T) methods with the aug-cc-pVDZ basis set). A total of 29 stable nucleobase-urea stacked complexes are identified in which the intermolecular interaction energies (up to −14 kcal/mol) are dominated by dispersion effects. Natural bond orbital (NBO) and atoms in molecules (AIM) calculations further confirm strong interactions between urea and nucleobases. Calculations on model systems with multiple urea and water molecules interacting with a guanine base lead to a hypothesis that urea molecules along with water are able to form cage-like structures capable of trapping nucleic acid bases in extrahelical states by forming both hydrogen bonded and dispersion interactions, thereby contributing to the unfolding of RNA in the presence of urea in aqueous solution. PMID:25668757

Biophysical interactions between plant and soil: theory and practice

NASA Astrophysics Data System (ADS)

van der Ploeg, Martine

2016-04-01

Vegetation plays an essential role in the hydrological cycle, as it regulates the water flux to the atmosphere through evapotranspiration, while it is dependent on adequate water supply. Vegetation shapes the land surface by changing infiltration characteristics as a result of root growth, and controls soil moisture storage, which in turn affect runoff characteristics and groundwater recharge. Vegetation and the underlying geology are in constant interaction, wherein water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. Models are a useful tool to explore interaction and feedbacks between vegetation, soil and landscape. Plants respond biochemically to their environment, while the models used for hydrology are often based on physical interactions. Gene-expression and genotype adaptation may complicate our modelling efforts in for example climate change impacts. Combination of new techniques to assess soil and plant properties facilitates assessment of biophysical interactions. This poster will review these techniques and compare the obtained insights of soil-plant relationships with the current modeling approaches.

Experimental Models to Study the Role of Microbes in Host-Parasite Interactions.

PubMed

Hahn, Megan A; Dheilly, Nolwenn M

2016-01-01

Until recently, parasitic infections have been primarily studied as interactions between the parasite and the host, leaving out crucial players: microbes. The recent realization that microbes play key roles in the biology of all living organisms is not only challenging our understanding of host-parasite evolution, but it also provides new clues to develop new therapies and remediation strategies. In this paper we provide a review of promising and advanced experimental organismal systems to examine the dynamic of host-parasite-microbe interactions. We address the benefits of developing new experimental models appropriate to this new research area and identify systems that offer the best promises considering the nature of the interactions among hosts, parasites, and microbes. Based on these systems, we identify key criteria for selecting experimental models to elucidate the fundamental principles of these complex webs of interactions. It appears that no model is ideal and that complementary studies should be performed on different systems in order to understand the driving roles of microbes in host and parasite evolution.

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Facial animation on an anatomy-based hierarchical face model

NASA Astrophysics Data System (ADS)

Zhang, Yu; Prakash, Edmond C.; Sung, Eric

2003-04-01

In this paper we propose a new hierarchical 3D facial model based on anatomical knowledge that provides high fidelity for realistic facial expression animation. Like real human face, the facial model has a hierarchical biomechanical structure, incorporating a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators and underlying skull structure. The deformable skin model has multi-layer structure to approximate different types of soft tissue. It takes into account the nonlinear stress-strain relationship of the skin and the fact that soft tissue is almost incompressible. Different types of muscle models have been developed to simulate distribution of the muscle force on the skin due to muscle contraction. By the presence of the skull model, our facial model takes advantage of both more accurate facial deformation and the consideration of facial anatomy during the interactive definition of facial muscles. Under the muscular force, the deformation of the facial skin is evaluated using numerical integration of the governing dynamic equations. The dynamic facial animation algorithm runs at interactive rate with flexible and realistic facial expressions to be generated.

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Trease, Brian; Arvidson, Raymond; Lindemann, Randel; Bennett, Keith; Zhou, Feng; Iagnemma, Karl; Senatore, Carmine; Van Dyke, Lauren

2011-01-01

To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover (MER) project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting tool, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction Simulator), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using MSC-Adams dynamic modeling software. Newly modeled terrain-rover interactions include the rut-formation effect of deformable soils, using the classical Bekker-Wong implementation of compaction resistances and bull-dozing effects. The paper presents the details and implementation of the model with two case studies based on actual MER telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.

Development of a Computationally Efficient, High Fidelity, Finite Element Based Hall Thruster Model

NASA Technical Reports Server (NTRS)

Jacobson, David (Technical Monitor); Roy, Subrata

2004-01-01

This report documents the development of a two dimensional finite element based numerical model for efficient characterization of the Hall thruster plasma dynamics in the framework of multi-fluid model. Effect of the ionization and the recombination has been included in the present model. Based on the experimental data, a third order polynomial in electron temperature is used to calculate the ionization rate. The neutral dynamics is included only through the neutral continuity equation in the presence of a uniform neutral flow. The electrons are modeled as magnetized and hot, whereas ions are assumed magnetized and cold. The dynamics of Hall thruster is also investigated in the presence of plasma-wall interaction. The plasma-wall interaction is a function of wall potential, which in turn is determined by the secondary electron emission and sputtering yield. The effect of secondary electron emission and sputter yield has been considered simultaneously, Simulation results are interpreted in the light of experimental observations and available numerical solutions in the literature.

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

PubMed

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

2014-12-23

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

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

NASA Astrophysics Data System (ADS)

Umut Caglar, Mehmet; Pal, Ranadip

2010-10-01

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

Compartmental and Spatial Rule-Based Modeling with Virtual Cell.

PubMed

Blinov, Michael L; Schaff, James C; Vasilescu, Dan; Moraru, Ion I; Bloom, Judy E; Loew, Leslie M

2017-10-03

In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule-based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations deterministic solvers or the Smoldyn stochastic simulator. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Reconstructing spatial organizations of chromosomes through manifold learning

PubMed Central

Deng, Wenxuan; Hu, Hailin; Ma, Rui; Zhang, Sai; Yang, Jinglin; Peng, Jian; Kaplan, Tommy; Zeng, Jianyang

2018-01-01

Abstract Decoding the spatial organizations of chromosomes has crucial implications for studying eukaryotic gene regulation. Recently, chromosomal conformation capture based technologies, such as Hi-C, have been widely used to uncover the interaction frequencies of genomic loci in a high-throughput and genome-wide manner and provide new insights into the folding of three-dimensional (3D) genome structure. In this paper, we develop a novel manifold learning based framework, called GEM (Genomic organization reconstructor based on conformational Energy and Manifold learning), to reconstruct the three-dimensional organizations of chromosomes by integrating Hi-C data with biophysical feasibility. Unlike previous methods, which explicitly assume specific relationships between Hi-C interaction frequencies and spatial distances, our model directly embeds the neighboring affinities from Hi-C space into 3D Euclidean space. Extensive validations demonstrated that GEM not only greatly outperformed other state-of-art modeling methods but also provided a physically and physiologically valid 3D representations of the organizations of chromosomes. Furthermore, we for the first time apply the modeled chromatin structures to recover long-range genomic interactions missing from original Hi-C data. PMID:29408992

Reconstructing spatial organizations of chromosomes through manifold learning.

PubMed

Zhu, Guangxiang; Deng, Wenxuan; Hu, Hailin; Ma, Rui; Zhang, Sai; Yang, Jinglin; Peng, Jian; Kaplan, Tommy; Zeng, Jianyang

2018-05-04

Decoding the spatial organizations of chromosomes has crucial implications for studying eukaryotic gene regulation. Recently, chromosomal conformation capture based technologies, such as Hi-C, have been widely used to uncover the interaction frequencies of genomic loci in a high-throughput and genome-wide manner and provide new insights into the folding of three-dimensional (3D) genome structure. In this paper, we develop a novel manifold learning based framework, called GEM (Genomic organization reconstructor based on conformational Energy and Manifold learning), to reconstruct the three-dimensional organizations of chromosomes by integrating Hi-C data with biophysical feasibility. Unlike previous methods, which explicitly assume specific relationships between Hi-C interaction frequencies and spatial distances, our model directly embeds the neighboring affinities from Hi-C space into 3D Euclidean space. Extensive validations demonstrated that GEM not only greatly outperformed other state-of-art modeling methods but also provided a physically and physiologically valid 3D representations of the organizations of chromosomes. Furthermore, we for the first time apply the modeled chromatin structures to recover long-range genomic interactions missing from original Hi-C data.

Investigation of head group behaviour of lamellar liquid crystals

NASA Astrophysics Data System (ADS)

Delikatny, E. J.; Burnell, E. E.

A mean field equilibrium statistical mechanical model, based on the Samulski inertial frame model, was developed to simulate experimental dipolar and quadrupolar nmr couplings of isotopically substituted potassium palmitates. An isolated four spin system was synthesized (2,2,3,3,-H4-palmitic acid-d27) and in conjunction with data presented in a previous paper on perdeuterated and carbon 13 labelled soaps, the head group behaviour of the molecule was investigated. Two interactions were considered in the modelling procedure: a mean field steric interaction characterized by a constraining cylinder, and a head group interaction characterized by a mass on the end of a rod of variable length. The rod lies along the first C-C bond direction and accounts for the interaction between polar head group and water via its effect on the moment of inertia of the molecule. In potassium palmitate mean field steric repulsive forces remain constant over the entire temperature range studied. In contrast, electrostatic interactions between polar head group and water, approximately constant at higher temperatures, increase dramatically as the phase transition is approached. This evidence supports a previously proposed model of lipidwater interaction.

Quantum dynamics modeled by interacting trajectories

NASA Astrophysics Data System (ADS)

Cruz-Rodríguez, L.; Uranga-Piña, L.; Martínez-Mesa, A.; Meier, C.

2018-03-01

We present quantum dynamical simulations based on the propagation of interacting trajectories where the effect of the quantum potential is mimicked by effective pseudo-particle interactions. The method is applied to several quantum systems, both for bound and scattering problems. For the bound systems, the quantum ground state density and zero point energy are shown to be perfectly obtained by the interacting trajectories. In the case of time-dependent quantum scattering, the Eckart barrier and uphill ramp are considered, with transmission coefficients in very good agreement with standard quantum calculations. Finally, we show that via wave function synthesis along the trajectories, correlation functions and energy spectra can be obtained based on the dynamics of interacting trajectories.

Learning Petri net models of non-linear gene interactions.

PubMed

Mayo, Michael

2005-10-01

Understanding how an individual's genetic make-up influences their risk of disease is a problem of paramount importance. Although machine-learning techniques are able to uncover the relationships between genotype and disease, the problem of automatically building the best biochemical model or "explanation" of the relationship has received less attention. In this paper, I describe a method based on random hill climbing that automatically builds Petri net models of non-linear (or multi-factorial) disease-causing gene-gene interactions. Petri nets are a suitable formalism for this problem, because they are used to model concurrent, dynamic processes analogous to biochemical reaction networks. I show that this method is routinely able to identify perfect Petri net models for three disease-causing gene-gene interactions recently reported in the literature.

Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion

PubMed Central

Andasari, Vivi; Roper, Ryan T.; Swat, Maciej H.; Chaplain, Mark A. J.

2012-01-01

In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model) and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008) where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and -catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach. PMID:22461894

Interactive Inverse Groundwater Modeling - Addressing User Fatigue

NASA Astrophysics Data System (ADS)

Singh, A.; Minsker, B. S.

2006-12-01

This paper builds on ongoing research on developing an interactive and multi-objective framework to solve the groundwater inverse problem. In this work we solve the classic groundwater inverse problem of estimating a spatially continuous conductivity field, given field measurements of hydraulic heads. The proposed framework is based on an interactive multi-objective genetic algorithm (IMOGA) that not only considers quantitative measures such as calibration error and degree of regularization, but also takes into account expert knowledge about the structure of the underlying conductivity field expressed as subjective rankings of potential conductivity fields by the expert. The IMOGA converges to the optimal Pareto front representing the best trade- off among the qualitative as well as quantitative objectives. However, since the IMOGA is a population-based iterative search it requires the user to evaluate hundreds of solutions. This leads to the problem of 'user fatigue'. We propose a two step methodology to combat user fatigue in such interactive systems. The first step is choosing only a few highly representative solutions to be shown to the expert for ranking. Spatial clustering is used to group the search space based on the similarity of the conductivity fields. Sampling is then carried out from different clusters to improve the diversity of solutions shown to the user. Once the expert has ranked representative solutions from each cluster a machine learning model is used to 'learn user preference' and extrapolate these for the solutions not ranked by the expert. We investigate different machine learning models such as Decision Trees, Bayesian learning model, and instance based weighting to model user preference. In addition, we also investigate ways to improve the performance of these models by providing information about the spatial structure of the conductivity fields (which is what the expert bases his or her rank on). Results are shown for each of these machine learning models and the advantages and disadvantages for each approach are discussed. These results indicate that using the proposed two-step methodology leads to significant reduction in user-fatigue without deteriorating the solution quality of the IMOGA.

A fast GPU-based Monte Carlo simulation of proton transport with detailed modeling of nonelastic interactions.

PubMed

Wan Chan Tseung, H; Ma, J; Beltran, C

2015-06-01

Very fast Monte Carlo (MC) simulations of proton transport have been implemented recently on graphics processing units (GPUs). However, these MCs usually use simplified models for nonelastic proton-nucleus interactions. Our primary goal is to build a GPU-based proton transport MC with detailed modeling of elastic and nonelastic proton-nucleus collisions. Using the cuda framework, the authors implemented GPU kernels for the following tasks: (1) simulation of beam spots from our possible scanning nozzle configurations, (2) proton propagation through CT geometry, taking into account nuclear elastic scattering, multiple scattering, and energy loss straggling, (3) modeling of the intranuclear cascade stage of nonelastic interactions when they occur, (4) simulation of nuclear evaporation, and (5) statistical error estimates on the dose. To validate our MC, the authors performed (1) secondary particle yield calculations in proton collisions with therapeutically relevant nuclei, (2) dose calculations in homogeneous phantoms, (3) recalculations of complex head and neck treatment plans from a commercially available treatment planning system, and compared with (GEANT)4.9.6p2/TOPAS. Yields, energy, and angular distributions of secondaries from nonelastic collisions on various nuclei are in good agreement with the (GEANT)4.9.6p2 Bertini and Binary cascade models. The 3D-gamma pass rate at 2%-2 mm for treatment plan simulations is typically 98%. The net computational time on a NVIDIA GTX680 card, including all CPU-GPU data transfers, is ∼ 20 s for 1 × 10(7) proton histories. Our GPU-based MC is the first of its kind to include a detailed nuclear model to handle nonelastic interactions of protons with any nucleus. Dosimetric calculations are in very good agreement with (GEANT)4.9.6p2/TOPAS. Our MC is being integrated into a framework to perform fast routine clinical QA of pencil-beam based treatment plans, and is being used as the dose calculation engine in a clinically applicable MC-based IMPT treatment planning system. The detailed nuclear modeling will allow us to perform very fast linear energy transfer and neutron dose estimates on the GPU.

Change in BMI accurately predicted by social exposure to acquaintances.

PubMed

Oloritun, Rahman O; Ouarda, Taha B M J; Moturu, Sai; Madan, Anmol; Pentland, Alex Sandy; Khayal, Inas

2013-01-01

Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R(2). This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends.