multi-factor interaction model: Topics by Science.gov

Sample records for multi-factor interaction model

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2008-01-01

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points, the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.
Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2008-01-01

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.
Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data

USGS Publications Warehouse

Yuan, Shuai; Zhou, Jiayu; Tan, Pang-Ning; Fergus, Emi; Wagner, Tyler; Sorrano, Patricia

2017-01-01

Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.
A Unique Computational Algorithm to Simulate Probabilistic Multi-Factor Interaction Model Complex Material Point Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2010-01-01

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points--the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.
Probabilistic Usage of the Multi-Factor Interaction Model

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A Multi-Factor Interaction Model (MFIM) is used to predict the insulating foam mass expulsion during the ascending of a space vehicle. The exponents in the MFIM are evaluated by an available approach which consists of least squares and an optimization algorithm. These results were subsequently used to probabilistically evaluate the effects of the uncertainties in each participating factor in the mass expulsion. The probabilistic results show that the surface temperature dominates at high probabilities and the pressure which causes the mass expulsion at low probabil
Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis.

PubMed

Cullis, B R; Smith, A B; Beeck, C P; Cowling, W A

2010-11-01

Exploring and exploiting variety by environment (V × E) interaction is one of the major challenges facing plant breeders. In paper I of this series, we presented an approach to modelling V × E interaction in the analysis of complex multi-environment trials using factor analytic models. In this paper, we develop a range of statistical tools which explore V × E interaction in this context. These tools include graphical displays such as heat-maps of genetic correlation matrices as well as so-called E-scaled uniplots that are a more informative alternative to the classical biplot for large plant breeding multi-environment trials. We also present a new approach to prediction for multi-environment trials that include pedigree information. This approach allows meaningful selection indices to be formed either for potential new varieties or potential parents.
Biological adaptive control model: a mechanical analogue of multi-factorial bone density adaptation.

PubMed

Davidson, Peter L; Milburn, Peter D; Wilson, Barry D

2004-03-21

The mechanism of how bone adapts to every day demands needs to be better understood to gain insight into situations in which the musculoskeletal system is perturbed. This paper offers a novel multi-factorial mathematical model of bone density adaptation which combines previous single-factor models in a single adaptation system as a means of gaining this insight. Unique aspects of the model include provision for interaction between factors and an estimation of the relative contribution of each factor. This interacting system is considered analogous to a Newtonian mechanical system and the governing response equation is derived as a linear version of the adaptation process. The transient solution to sudden environmental change is found to be exponential or oscillatory depending on the balance between cellular activation and deactivation frequencies.
Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

DOE PAGES

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika; ...

2016-01-19

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less
Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

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

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less
The influence of the interactions between anthropogenic activities and multiple ecological factors on land surface temperatures of urban forests

NASA Astrophysics Data System (ADS)

Ren, Y.

2017-12-01

Context Land surface temperatures (LSTs) spatio-temporal distribution pattern of urban forests are influenced by many ecological factors; the identification of interaction between these factors can improve simulations and predictions of spatial patterns of urban cold islands. This quantitative research requires an integrated method that combines multiple sources data with spatial statistical analysis. Objectives The purpose of this study was to clarify urban forest LST influence interaction between anthropogenic activities and multiple ecological factors using cluster analysis of hot and cold spots and Geogdetector model. We introduced the hypothesis that anthropogenic activity interacts with certain ecological factors, and their combination influences urban forests LST. We also assumed that spatio-temporal distributions of urban forest LST should be similar to those of ecological factors and can be represented quantitatively. Methods We used Jinjiang as a representative city in China as a case study. Population density was employed to represent anthropogenic activity. We built up a multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) on a unified urban scale to support urban forest LST influence interaction research. Through a combination of spatial statistical analysis results, multi-source spatial data, and Geogdetector model, the interaction mechanisms of urban forest LST were revealed. Results Although different ecological factors have different influences on forest LST, in two periods with different hot spots and cold spots, the patch area and dominant tree species were the main factors contributing to LST clustering in urban forests. The interaction between anthropogenic activity and multiple ecological factors increased LST in urban forest stands, linearly and nonlinearly. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. Conclusions In conclusion, a combination of spatial statistics and GeogDetector models should be effective for quantitatively evaluating interactive relationships among ecological factors, anthropogenic activity and LST.
Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO 2 enrichment experiment

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

De Kauwe, Martin G.; Medlyn, Belinda E.; Walker, Anthony P.

Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2 yr -1). Comparison with data highlighted model failures particularlymore » in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against single-factors was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO 2-induced water savings to extend growing season length. Observed interactive (CO 2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. Finally, we outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.« less
Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO 2 enrichment experiment

DOE PAGES

De Kauwe, Martin G.; Medlyn, Belinda E.; Walker, Anthony P.; ...

2017-02-01

Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2 yr -1). Comparison with data highlighted model failures particularlymore » in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against single-factors was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO 2-induced water savings to extend growing season length. Observed interactive (CO 2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. Finally, we outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.« less
Quantifying the influences of various ecological factors on land surface temperature of urban forests.

PubMed

Ren, Yin; Deng, Lu-Ying; Zuo, Shu-Di; Song, Xiao-Dong; Liao, Yi-Lan; Xu, Cheng-Dong; Chen, Qi; Hua, Li-Zhong; Li, Zheng-Wei

2016-09-01

Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST. Copyright © 2016 Elsevier Ltd. All rights reserved.
Inference on the Strength of Balancing Selection for Epistatically Interacting Loci

PubMed Central

Buzbas, Erkan Ozge; Joyce, Paul; Rosenberg, Noah A.

2011-01-01

Existing inference methods for estimating the strength of balancing selection in multi-locus genotypes rely on the assumption that there are no epistatic interactions between loci. Complex systems in which balancing selection is prevalent, such as sets of human immune system genes, are known to contain components that interact epistatically. Therefore, current methods may not produce reliable inference on the strength of selection at these loci. In this paper, we address this problem by presenting statistical methods that can account for epistatic interactions in making inference about balancing selection. A theoretical result due to Fearnhead (2006) is used to build a multi-locus Wright-Fisher model of balancing selection, allowing for epistatic interactions among loci. Antagonistic and synergistic types of interactions are examined. The joint posterior distribution of the selection and mutation parameters is sampled by Markov chain Monte Carlo methods, and the plausibility of models is assessed via Bayes factors. As a component of the inference process, an algorithm to generate multi-locus allele frequencies under balancing selection models with epistasis is also presented. Recent evidence on interactions among a set of human immune system genes is introduced as a motivating biological system for the epistatic model, and data on these genes are used to demonstrate the methods. PMID:21277883
Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2010-01-01

Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required to represent the ejected foam. The exponents were evaluated by least squares method from experimental data. The equation is used and it can represent multiple factors in other problems as well; for example, evaluation of fatigue life, creep life, fracture toughness, and structural fracture, as well as optimization functions. The software is rather simplistic. Required inputs are initial value, final value, and an exponent for each factor. The number of factors is open-ended. The value is updated as each factor is evaluated. If a factor goes to zero, the previous value is used in the evaluation.
Selection of higher order regression models in the analysis of multi-factorial transcription data.

PubMed

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

2014-01-01

Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.
Application of the Multi-Doorway Continuum Shell Model to the Magnetic Dipole Strength Distribution in 58Ni

NASA Astrophysics Data System (ADS)

Spangenberger, H.; Beck, F.; Richter, A.

The usual continuum shell model is extended so as to include a statistical treatment of multi-doorway processes. The total configuration space of the nuclear reaction problem is subdivided into the primary doorway states which are coupled by the initial excitation to the nuclear ground state and the secondary doorway states which represent the complicated nature of multi-step reactions. The latter are evaluated within the exciton model which gives the coupling widths between the various finestructure subspaces. This coupling is determined by a statistical factor related to the exciton model and a dynamical factor given by the interaction matrix elements of the interacting excitons. The whole structure defines the multi-doorway continuum shell model. In this work it is applied to the highly fragmented magnetic dipole strength in 58Ni observed in high resolution electron scattering.Translated AbstractAnwendung des Multi-Doorway-Kontinuum-Schalenmodells auf die Verteilung der magnetischen Dipolstärke von 58NiDas Kontinuum-Schalenmodell wurde so erweitert, daß auch statistische Multi-Doorway-Prozesse berücksichtigt werden können. Hierzu wird der Konfigurationsraum unterteilt in den Raum der primären Doorway-Zustände, die direkt aus dem Grundzustand angeregt werden, und den der sekundären Doorway-Zustände, die die komplizierte Struktur der Multi-Step-Reaktionen repräsentieren. Während die primären Doorway-Zustände inclusive ihrer Anregungen mittels üblicher Schalenmodellmethoden beschrieben werden können, werden die sekundären Doorway-Zustände sowie ihre verschiedenen Kopplungen im Rahmen des Exciton-Modells behandelt. Diese Kopplungen sind durch einen aus dem Exciton-Modell resultierenden Faktor sowie durch einen dynamischen Faktor bestimmt, der sich aus dem Matrixelement der wechselwirkenden Excitonen berechnet. Die Struktur der Kopplungen definiert das Multi-Doorway-Kontinuum-Schalenmodell, das hier auf die Beschreibung der stark fragmentierten magnetischen Dipolstärke in 58Ni angewendet wird.
Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model.

PubMed

Gürsoy, Gamze; Xu, Yun; Liang, Jie

2017-07-01

Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.
Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques

PubMed Central

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

2011-01-01

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

PubMed

Kirkilionis, Markus; Janus, Ulrich; Sbano, Luca

2011-09-01

We present a new approach or framework to model dynamic regulatory genetic activity. The framework is using a multi-scale analysis based upon generic assumptions on the relative time scales attached to the different transitions of molecular states defining the genetic system. At micro-level such systems are regulated by the interaction of two kinds of molecular players: macro-molecules like DNA or polymerases, and smaller molecules acting as transcription factors. The proposed genetic model then represents the larger less abundant molecules with a finite discrete state space, for example describing different conformations of these molecules. This is in contrast to the representations of the transcription factors which are-like in classical reaction kinetics-represented by their particle number only. We illustrate the method by considering the genetic activity associated to certain configurations of interacting genes that are fundamental to modelling (synthetic) genetic clocks. A largely unknown question is how different molecular details incorporated via this more realistic modelling approach lead to different macroscopic regulatory genetic models which dynamical behaviour might-in general-be different for different model choices. The theory will be applied to a real synthetic clock in a second accompanying article (Kirkilioniset al., Theory Biosci, 2011).

multiDE: a dimension reduced model based statistical method for differential expression analysis using RNA-sequencing data with multiple treatment conditions.

PubMed

Kang, Guangliang; Du, Li; Zhang, Hong

2016-06-22

The growing complexity of biological experiment design based on high-throughput RNA sequencing (RNA-seq) is calling for more accommodative statistical tools. We focus on differential expression (DE) analysis using RNA-seq data in the presence of multiple treatment conditions. We propose a novel method, multiDE, for facilitating DE analysis using RNA-seq read count data with multiple treatment conditions. The read count is assumed to follow a log-linear model incorporating two factors (i.e., condition and gene), where an interaction term is used to quantify the association between gene and condition. The number of the degrees of freedom is reduced to one through the first order decomposition of the interaction, leading to a dramatically power improvement in testing DE genes when the number of conditions is greater than two. In our simulation situations, multiDE outperformed the benchmark methods (i.e. edgeR and DESeq2) even if the underlying model was severely misspecified, and the power gain was increasing in the number of conditions. In the application to two real datasets, multiDE identified more biologically meaningful DE genes than the benchmark methods. An R package implementing multiDE is available publicly at http://homepage.fudan.edu.cn/zhangh/softwares/multiDE . When the number of conditions is two, multiDE performs comparably with the benchmark methods. When the number of conditions is greater than two, multiDE outperforms the benchmark methods.
Examining dynamic interactions among experimental factors influencing hydrologic data assimilation with the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Baetz, B. W.; Cai, X. M.; Ancell, B. C.; Fan, Y. R.

2017-11-01

The ensemble Kalman filter (EnKF) is recognized as a powerful data assimilation technique that generates an ensemble of model variables through stochastic perturbations of forcing data and observations. However, relatively little guidance exists with regard to the proper specification of the magnitude of the perturbation and the ensemble size, posing a significant challenge in optimally implementing the EnKF. This paper presents a robust data assimilation system (RDAS), in which a multi-factorial design of the EnKF experiments is first proposed for hydrologic ensemble predictions. A multi-way analysis of variance is then used to examine potential interactions among factors affecting the EnKF experiments, achieving optimality of the RDAS with maximized performance of hydrologic predictions. The RDAS is applied to the Xiangxi River watershed which is the most representative watershed in China's Three Gorges Reservoir region to demonstrate its validity and applicability. Results reveal that the pairwise interaction between perturbed precipitation and streamflow observations has the most significant impact on the performance of the EnKF system, and their interactions vary dynamically across different settings of the ensemble size and the evapotranspiration perturbation. In addition, the interactions among experimental factors vary greatly in magnitude and direction depending on different statistical metrics for model evaluation including the Nash-Sutcliffe efficiency and the Box-Cox transformed root-mean-square error. It is thus necessary to test various evaluation metrics in order to enhance the robustness of hydrologic prediction systems.
New insights into the multi-scale climatic drivers of the "Karakoram anomaly"

NASA Astrophysics Data System (ADS)

Collier, S.; Moelg, T.; Nicholson, L. I.; Maussion, F.; Scherer, D.; Bush, A. B.

2012-12-01

Glacier behaviour in the Karakoram region of the northwestern Himalaya shows strong spatial and temporal heterogeneity and, in some basins, anomalous trends compared with glaciers elsewhere in High Asia. Our knowledge of the mass balance fluctuations of Karakoram glaciers as well as of the important driving factors and interactions between them is limited by a scarcity of in-situ measurements and other studies. Here we employ a novel approach to simulating atmosphere-cryosphere interactions - coupled high-resolution atmospheric and physically-based surface mass balance modelling - to examine the surface energy and mass fluxes of glaciers in this region. We discuss the mesoscale climatic drivers behind surface mass balance fluctuations as well as the influence of local forcing factors, such as debris cover and feedbacks from the glacier surface to the atmosphere. The coupled modelling approach therefore provides an innovative, multi-scale solution to the paucity of information we have to date on the much-debated "Karakoram anomaly."
Modeling Vascularized Bone Regeneration Within a Porous Biodegradable CaP Scaffold Loaded with Growth Factors

PubMed Central

Sun, X; Kang, Y; Bao, J; Zhang, Y; Yang, Y; Zhou, X

2013-01-01

Osteogenetic microenvironment is a complex constitution in which extracellular matrix (ECM) molecules, stem cells and growth factors each interact to direct the coordinate regulation of bone tissue development. Importantly, angiogenesis improvement and revascularization are critical for osteogenesis during bone tissue regeneration processes. In this study, we developed a three-dimensional (3D) multi-scale system model to study cell response to growth factors released from a 3D biodegradable porous calcium phosphate (CaP) scaffold. Our model reconstructed the 3D bone regeneration system and examined the effects of pore size and porosity on bone formation and angiogenesis. The results suggested that scaffold porosity played a more dominant role in affecting bone formation and angiogenesis compared with pore size, while the pore size could be controlled to tailor the growth factor release rate and release fraction. Furthermore, a combination of gradient VEGF with BMP2 and Wnt released from the multi-layer scaffold promoted angiogenesis and bone formation more readily than single growth factors. These results demonstrated that the developed model can be potentially applied to predict vascularized bone regeneration with specific scaffold and growth factors. PMID:23566802
Probabilistic simulation of the human factor in structural reliability

NASA Technical Reports Server (NTRS)

Shah, Ashwin R.; Chamis, Christos C.

1991-01-01

Many structural failures have occasionally been attributed to human factors in engineering design, analyses maintenance, and fabrication processes. Every facet of the engineering process is heavily governed by human factors and the degree of uncertainty associated with them. Factors such as societal, physical, professional, psychological, and many others introduce uncertainties that significantly influence the reliability of human performance. Quantifying human factors and associated uncertainties in structural reliability require: (1) identification of the fundamental factors that influence human performance, and (2) models to describe the interaction of these factors. An approach is being developed to quantify the uncertainties associated with the human performance. This approach consists of a multi factor model in conjunction with direct Monte-Carlo simulation.
Gene-environment interaction and suicidal behavior.

PubMed

Roy, Alec; Sarchiopone, Marco; Carli, Vladimir

2009-07-01

Studies have increasingly shown that gene-environment interactions are important in psychiatry. Suicidal behavior is a major public health problem. Suicide is generally considered to be a multi-determined act involving various areas of proximal and distal risk. Genetic risk factors are estimated to account for approximately 30% to 40% of the variance in suicidal behavior. In this article, the authors review relevant studies concerning the interaction between the serotonin transporter gene and environmental variables as a model of gene-environment interactions that may have an impact on suicidal behavior. The findings reviewed here suggest that there may be meaningful interactions between distal and proximal suicide risk factors that may amplify the risk of suicidal behavior. Future studies of suicidal behavior should examine both genetic and environmental variables and examine for gene-environment interactions.
Model of interaction in Smart Grid on the basis of multi-agent system

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

ERIC Educational Resources Information Center

Baker, Ryan S.

2016-01-01

The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…
Magnetohydrodynamic simulation of the interaction between two interplanetary magnetic clouds and its consequent geoeffectiveness

NASA Astrophysics Data System (ADS)

Xiong, Ming; Zheng, Huinan; Wu, S. T.; Wang, Yuming; Wang, Shui

2007-11-01

Numerical studies of the interplanetary "multiple magnetic clouds (Multi-MC)" are performed by a 2.5-dimensional ideal magnetohydrodynamic (MHD) model in the heliospheric meridional plane. Both slow MC1 and fast MC2 are initially emerged along the heliospheric equator, one after another with different time intervals. The coupling of two MCs could be considered as the comprehensive interaction between two systems, each comprising of an MC body and its driven shock. The MC2-driven shock and MC2 body are successively involved into interaction with MC1 body. The momentum is transferred from MC2 to MC1. After the passage of MC2-driven shock front, magnetic field lines in MC1 medium previously compressed by MC2-driven shock are prevented from being restored by the MC2 body pushing. MC1 body undergoes the most violent compression from the ambient solar wind ahead, continuous penetration of MC2-driven shock through MC1 body, and persistent pushing of MC2 body at MC1 tail boundary. As the evolution proceeds, the MC1 body suffers from larger and larger compression, and its original vulnerable magnetic elasticity becomes stiffer and stiffer. So there exists a maximum compressibility of Multi-MC when the accumulated elasticity can balance the external compression. This cutoff limit of compressibility mainly decides the maximally available geoeffectiveness of Multi-MC because the geoeffectiveness enhancement of MCs interacting is ascribed to the compression. Particularly, the greatest geoeffectiveness is excited among all combinations of each MC helicity, if magnetic field lines in the interacting region of Multi-MC are all southward. Multi-MC completes its final evolutionary stage when the MC2-driven shock is merged with MC1-driven shock into a stronger compound shock. With respect to Multi-MC geoeffectiveness, the evolution stage is a dominant factor, whereas the collision intensity is a subordinate one. The magnetic elasticity, magnetic helicity of each MC, and compression between each other are the key physical factors for the formation, propagation, evolution, and resulting geoeffectiveness of interplanetary Multi-MC.
Multi-gas interaction modeling on decorated semiconductor interfaces: A novel Fermi distribution-based response isotherm and the inverse hard/soft acid/base concept

NASA Astrophysics Data System (ADS)

Laminack, William; Gole, James

2015-12-01

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

NASA Astrophysics Data System (ADS)

Bondarenko, Y.

I. Goal and Scope. Human birth rate decrease, death-rate growth and increase of mu- tagenic deviations risk take place in geopathogenic and anthropogenic hazard zones. Such zones create unfavourable conditions for reproductive process of future genera- tions. These negative trends should be considered as a protective answer of the com- plex biosocial system to the appearance of natural and anthropogenic risk factors that are unfavourable for human health. The major goals of scientific evaluation and de- crease of risk of appearance of hazardous processes on the territory of Dnipropetrovsk, along with creation of the multi-factor predictive Spirit-Energy-Information Space "SEIS" & GIS Model of ecological, genetical and population health risk in connection with dangerous bio-geodynamic processes, were: multi-factor modeling and correla- tion of natural and anthropogenic environmental changes and those of human health; determination of indicators that show the risk of destruction structures appearance on different levels of organization and functioning of the city ecosystem (geophys- ical and geochemical fields, soil, hydrosphere, atmosphere, biosphere); analysis of regularities of natural, anthropogenic, and biological rhythms' interactions. II. Meth- ods. The long spatio-temporal researches (Y. Bondarenko, 1996, 2000) have proved that the ecological, genetic and epidemiological processes are in connection with de- velopment of dangerous bio-geophysical and bio-geodynamic processes. Mathemat- ical processing of space photos, lithogeochemical and geophysical maps with use of JEIS o and ERDAS o computer systems was executed at the first stage of forma- tion of multi-layer geoinformation model "Dnipropetrovsk ARC View GIS o. The multi-factor nonlinear correlation between solar activity and cosmic ray variations, geophysical, geodynamic, geochemical, atmospheric, technological, biological, socio- economical processes and oncologic case rate frequency, general and primary popula- tion sickness cases in Dnipropetrovsk City (1.2 million persons) are described by the multi-factor predictive SEIS & GIS model of geopathogenic zones that determines the human health risk and hazards. Results and Conclusions. We have created the SEIS system and multi-factor predictive SEIS model for the analysis of phase-metric spatio- 1 temporal nonlinear correlation and variations of rhythms of human health, ecological, genetic, epidemiological risks, demographic, socio-economic, bio-geophysical, bio- geodynamic processes in geopathogenic hazard zones. Cosmophotomaps "CPM" of vegetation index, anthropogenic-landscape and landscape-geophysical human health risk of Dnipropetrovsk City present synthesis-based elements of multi-layer GIS, which include multispectral images SPOT o, maps of different geophysical, geochem- ical, anthropogenic and citogenic risk factors, maps of integral oncologic case rate frequency, general and primary population sickness cases for administrative districts. Results of multi-layer spatio-temporal correlation of geophysical field parameters and variations of population sickness rate rhythms have enabled us to state grounds and to develop medico-biological and bio-geodynamic classification of geopathogenic zones. Bio-geodynamic model has served to define contours of anthropogenic-landscape and landscape-geophysical human health risk in Dnipropetrovsk City. Biorhythmic vari- ations give foundation for understanding physiological mechanisms of organism`s adaptation to extreme helio-geophysical and bio-geodynamic environmental condi- tions, which are dictated by changes in Multi-factor Correlation Stress Field "MCSF" with deformation of 5D SEIS. Interaction between organism and environment results in continuous superpositioning of external (exogenic) Nuclear-Molecular-Cristallic "NMC" MCSF rhythms on internal (endogenic) Nuclear-Molecular-Cellular "NMCl" MCSF rhythms. Their resonance wave (energy-information) integration and disinte- gration are responsible for structural and functional state of different physiological systems. Herewith, complex restructurization of defense functions blocks the adapta- tion process and may turn to be the primary reason for phase shifting, process and biorhythms hindering, appearance of different deseases. Interaction of biorhythms with natural and anthropogenic rhythms specify the peculiar features of environ- mental adaptation of living species. Such interaction results in correlation of sea- sonal rhythms in variations of thermo-baro-geodynamic "TBG" parameters of am- bient air with toxic concentration and human health risk in Dnipropetrovsk City. Bio-geodynamic analysis of medical and demographic situations has provided for search of spatio-temporal correlation between rhythms of general and primary pop- ulation sickness cases and oncologic case rate frequency, other medico-demographic rhythms, natural processes (helio-geophysical, thermodynamic, geodynamic) and an- thropogenic processes (industrial and houschold waste disposal, toxic emissions and their concentration in ambient air). The year of 1986, the year of minimum helio- geophysical activity "2G1dG1" and maximum anthropogenic processes associated with changes in sickness and death rates of the population of Earth were synchronized. With account of quantum character of SEIS rhythms, 5 reference levels of desyn- chronized helio-geophysical and bio-geodynamic processes affecting population sick- ness rate have been specified within bio-geodynamic models. The first reference level 2 of SEIS desynchronization includes rhythms with period of 22,5 years: ... 1958,2; 1980,7; 2003,2; .... The second reference level of SEIS desynchronization includes rhythms with period of 11,25 years: ... 1980,7; 1992; 2003,2;.... The third reference level covers 5,625-years periodic rhythms2:... 1980,7; 1986,3; 1992; 1997,6; 2003,2; .... The fourth quantum reference level includes rhythms 3 with period of 2,8125 years: ... 1980,7; 1983,5; 1986,3; 1989,1; 1992; 1994,8; 1997,6; 2000,4; 2003,2; .... Rhythms with 1,40625-years period fall is fifth reference level of SEIS desynchro- nization: ...1980,7; 1982,1; 1983,5; 1984,9; 1986,3; 1987,7; 1989,1; 1990,5; 1992; 1993,3; 1994,8; 1996,2; 1997,6; 1999; 2000,4; 2001,8; 2003,2;.... Analysis of alternat- ing medical and demographic situation in Ukraine (1981-1992)and in Dnipropetrovsk (1988-1995)has allowed to back up theoretical model of various-level rhythm quan- tum, with non-linear regularities due to phase-metric spatio-temporal deformation be- ing specified. Application of new technologies of Risk Analysis, Sinthesis and SEIS Modeling at the choice of a burial place for dangerous radioactive wastes in the zone of Chernobyl nuclear disaster (Shestopalov V., Bondarenko Y...., 1998) has shown their very high efficiency in comparison with GIS Analysis. IV.Recommendations and Outlook. In order to draw a conclusion regarding bio-geodynamic modeling of spatio-temporal structure of areas where common childhood sickness rate exists, it is necessary to mention that the only thing that can favour to exact predicting of where and when important catastrophes and epidemies will take place is correct and complex bio-geodynamic modeling. Imperfection of present GIS is the result of the lack of interactive facilities for multi-factor modeling of nonlinear natural and an- thropogenic processes. Equations' coefficients calculated for some areas are often irrelevant when applied to others. In this connection there arises a number of prob- lems concerning practical application and reliability of GIS-models that are used to carry out efficient ecological monitoring. References Bondarenko Y., 1997, Drawing up Cosmophotomaps and Multi-factor Forecasting of Hazard of Development of Dan- gerous Geodynamic Processes in Dnipropetrovsk,The Technically-Natural Problems of failures and catastrophes in connection with development of dangerous geological processes, Kiev, Ukraine, 1997. Bondarenko Y., 1997, The Methodology of a State the Value of Quality of the Ground and the House Level them Ecology-Genetic-Toxic of the human health risk based on multi-layer cartographical model", Experience of application GIS - Technologies for creating Cadastral Systems, Yalta, Ukraine, 1997, p. 39-40. Shestopalov V., Bondarenko Y., Zayonts I., Rudenko Y. , Bohuslavsky A., 1998, Complexation of Structural-Geodynamical and Hydrogeological Methods of Studying Areas to Reveal Geological Structural Perspectives for Deep Isolation of Radioactive Wastes, Field Testing and Associated Modeling of Potential High-Level Nuclear Waste Geologic Disposal Sites, Berkeley, USA, 1998, p.81-82. 3
A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

NASA Astrophysics Data System (ADS)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.
Multi-scale models of grassland passerine abundance in a fragmented system in Wisconsin

USGS Publications Warehouse

Renfrew, R.B.; Ribic, C.A.

2008-01-01

Fragmentation of grasslands has been implicated in grassland bird population declines. Multi-scale models are being increasingly used to assess potential factors that influence grassland bird presence, abundance, and productivity. However, studies rarely assess fragmentation metrics, and seldom evaluate more than two scales or interactions among scales. We evaluated the relative importance of characteristics at multiple scales to patterns in relative abundance of Savannah Sparrow (Passerculus sandwichensis), Grasshopper Sparrow (Ammodramus savannarum), Eastern Meadowlark (Sturnella magna), and Bobolink (Dolichonyx oryzivorus). We surveyed birds in 74 southwestern Wisconsin pastures from 1997 to 1999 and compared models with explanatory variables from multiple scales: within-patch vegetation structure (microhabitat), patch (macrohabitat), and three landscape extents. We also examined interactions between macrohabitat and landscape factors. Core area of pastures was an important predictor of relative abundance, and composition of the landscape was more important than configuration. Relative abundance was frequently higher in pastures with more core area and in landscapes with more grassland and less wooded area. The direction and strength of the effect of core pasture size on relative abundance changed depending on amount of wooded area in the landscape. Relative abundance of grassland birds was associated with landscape variables more frequently at the 1200-m scale than at smaller scales. To develop better predictive models, parameters at multiple scales and their interactive effects should be included, and results should be evaluated in the context of microhabitat variability, landscape composition, and fragmentation in the study area. ?? 2007 Springer Science+Business Media B.V.
Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.

PubMed

Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A; Kardia, Sharon L R; Allison, Matthew; Diez Roux, Ana V

2016-11-01

There has been an increased interest in identifying gene-environment interaction (G × E) in the context of multiple environmental exposures. Most G × E studies analyze one exposure at a time, but we are exposed to multiple exposures in reality. Efficient analysis strategies for complex G × E with multiple environmental factors in a single model are still lacking. Using the data from the Multiethnic Study of Atherosclerosis, we illustrate a two-step approach for modeling G × E with multiple environmental factors. First, we utilize common clustering and classification strategies (e.g., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. Second, we illustrate the use of an additive main effects and multiplicative interaction model, instead of the conventional saturated interaction model using product terms of factors, to study G × E with the data-driven exposure subgroups defined in the first step. We demonstrate useful analytical approaches to translate multiple environmental exposures into one summary class. These tools not only allow researchers to consider several environmental exposures in G × E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead of examining effect modification for each exposure in isolation.
A multi-process model of self-regulation: influences of mindfulness, integrative self-knowledge and self-control in Iran.

PubMed

Ghorbani, Nima; Watson, P J; Farhadi, Mehran; Chen, Zhuo

2014-04-01

Self-regulation presumably rests upon multiple processes that include an awareness of ongoing self-experience, enduring self-knowledge and self-control. The present investigation tested this multi-process model using the Five-Facet Mindfulness Questionnaire (FFMQ) and the Integrative Self-Knowledge and Brief Self-Control Scales. Using a sample of 1162 Iranian university students, we confirmed the five-factor structure of the FFMQ in Iran and documented its factorial invariance across males and females. Self-regulatory variables correlated negatively with Perceived Stress, Depression, and Anxiety and positively with Self-Esteem and Satisfaction with Life. Partial mediation effects confirmed that self-regulatory measures ameliorated the disturbing effects of Perceived Stress. Integrative Self-Knowledge and Self-Control interacted to partially mediate the association of Perceived Stress with lower levels of Satisfaction with Life. Integrative Self-Knowledge, alone or in interaction with Self-Control, was the only self-regulation variable to display the expected mediation of Perceived Stress associations with all other measures. Self-Control failed to be implicated in self-regulation only in the mediation of Anxiety. These data confirmed the need to further examine this multi-process model of self-regulation. © 2014 International Union of Psychological Science.
Cognitive Vulnerability-Stress Model of Depression during Adolescence: Investigating Depressive Symptom Specificity in a Multi-Wave Prospective Study

ERIC Educational Resources Information Center

Hankin, Benjamin L.

2008-01-01

Depression commonly co-occurs with anxiety and externalizing problems. Etiological factors from a central cognitive theory of depression, the Hopelessness Theory (Abramson et al. "Psychological Review," 96, 358-372, 1989), were examined to evaluate whether a negative inferential style about cause, consequence, and self interacted with stressors…
Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

NASA Astrophysics Data System (ADS)

Yang, Qiu

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

NASA Astrophysics Data System (ADS)

Field, C. B.

2012-12-01

Modeling climate change impacts is challenging for a variety of reasons. Some of these are related to causation. A weather or climate event is rarely the sole cause of an impact, and, for many impacts, social, economic, cultural, or ecological factors may play a larger role than climate. Other challenges are related to outcomes. Consequences of an event are often most severe when several kinds of responses interact, typically in unexpected ways. Many kinds of consequences are difficult to quantify, especially when they include a mix of market, cultural, personal, and ecological values. In addition, scale can be tremendously important. Modest impacts over large areas present very different challenges than severe but very local impacts. Finally, impacts may respond non-linearly to forcing, with behavior that changes qualitatively at one or more thresholds and with unexpected outcomes in extremes. Modeling these potentially complex interactions between drivers and impacts presents one set of challenges. Evaluating the models presents another. At least five kinds of approaches can contribute to the evaluation of impact models designed to provide insights in multi-driver, multi-responder, multi-scale, and extreme-driven contexts, even though none of these approaches is a complete or "silver-bullet" solution. The starting point for much of the evaluation in this space is case studies. Case studies can help illustrate links between processes and scales. They can highlight factors that amplify or suppress sensitivity to climate drivers, and they can suggest the consequences of intervening at different points. While case studies rarely provide concrete evidence about mechanisms, they can help move a mechanistic case from circumstantial to sound. Novel approaches to data collection, including crowd sourcing, can potentially provide tools and the number of relevant examples to develop case studies as statistically robust data sources. A critical condition for progress in this area is the ability to utilize data of uneven quality and standards. Novel approaches to meta-analysis provide other options for taking advantage of diverse case studies. Techniques for summarizing responses across impacts, drivers, and scales can play a huge role in increasing the value of information from case studies. In some cases, expert elicitation may provide alternatives for identifying mechanisms or for interpreting multi-factor drivers or responses. Especially when designed to focus on a well-defined set of observations, a sophisticated elicitation can establish formal confidence limits on responses that are otherwise difficult to constrain. A final possible approach involves a focus on the mechanisms contributing to an impact, rather than the impact itself. Approaches based on quantified mechanisms are especially appealing in the context of models where the number of interactions makes it difficult to intuitively understand the chain of connections from cause to effect, when actors differ in goals or sensitivities, or when scale affects parts of the system differently. With all of these approaches, useful evidence may not conform to traditional levels of statistical confidence. Some of the biggest challenges in taking advantage of the potential tools will involve defining what constitutes a meaningful evaluation.
Coarse-grained molecular dynamics simulations for giant protein-DNA complexes

NASA Astrophysics Data System (ADS)

Takada, Shoji

Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.
Distinct self-interaction domains promote Multi Sex Combs accumulation in and formation of the Drosophila histone locus body

PubMed Central

Terzo, Esteban A.; Lyons, Shawn M.; Poulton, John S.; Temple, Brenda R. S.; Marzluff, William F.; Duronio, Robert J.

2015-01-01

Nuclear bodies (NBs) are structures that concentrate proteins, RNAs, and ribonucleoproteins that perform functions essential to gene expression. How NBs assemble is not well understood. We studied the Drosophila histone locus body (HLB), a NB that concentrates factors required for histone mRNA biosynthesis at the replication-dependent histone gene locus. We coupled biochemical analysis with confocal imaging of both fixed and live tissues to demonstrate that the Drosophila Multi Sex Combs (Mxc) protein contains multiple domains necessary for HLB assembly. An important feature of this assembly process is the self-interaction of Mxc via two conserved N-terminal domains: a LisH domain and a novel self-interaction facilitator (SIF) domain immediately downstream of the LisH domain. Molecular modeling suggests that the LisH and SIF domains directly interact, and mutation of either the LisH or the SIF domain severely impairs Mxc function in vivo, resulting in reduced histone mRNA accumulation. A region of Mxc between amino acids 721 and 1481 is also necessary for HLB assembly independent of the LisH and SIF domains. Finally, the C-terminal 195 amino acids of Mxc are required for recruiting FLASH, an essential histone mRNA-processing factor, to the HLB. We conclude that multiple domains of the Mxc protein promote HLB assembly in order to concentrate factors required for histone mRNA biosynthesis. PMID:25694448

Stakeholder conceptualisation of multi-level HIV and AIDS determinants in a Black epicentre.

PubMed

Brawner, Bridgette M; Reason, Janaiya L; Hanlon, Kelsey; Guthrie, Barbara; Schensul, Jean J

2017-09-01

HIV has reached epidemic proportions among African Americans in the USA but certain urban contexts appear to experience a disproportionate disease burden. Geographic information systems mapping in Philadelphia indicates increased HIV incidence and prevalence in predominantly Black census tracts, with major differences across adjacent communities. What factors shape these geographic HIV disparities among Black Philadelphians? This descriptive study was designed to refine and validate a conceptual model developed to better understand multi-level determinants of HIV-related risk among Black Philadelphians. We used an expanded ecological approach to elicit reflective perceptions from administrators, direct service providers and community members about individual, social and structural factors that interact to protect against or increase the risk for acquiring HIV within their community. Gender equity, social capital and positive cultural mores (e.g., monogamy, abstinence) were seen as the main protective factors. Historical negative contributory influences of racial residential segregation, poverty and incarceration were among the most salient risk factors. This study was a critical next step toward initiating theory-based, multi-level community-based HIV prevention initiatives.
Effects of different dispersal patterns on the presence-absence of multiple species

NASA Astrophysics Data System (ADS)

Mohd, Mohd Hafiz; Murray, Rua; Plank, Michael J.; Godsoe, William

2018-03-01

Predicting which species will be present (or absent) across a geographical region remains one of the key problems in ecology. Numerous studies have suggested several ecological factors that can determine species presence-absence: environmental factors (i.e. abiotic environments), interactions among species (i.e. biotic interactions) and dispersal process. While various ecological factors have been considered, less attention has been given to the problem of understanding how different dispersal patterns, in interaction with other factors, shape community assembly in the presence of priority effects (i.e. where relative initial abundances determine the long-term presence-absence of each species). By employing both local and non-local dispersal models, we investigate the consequences of different dispersal patterns on the occurrence of priority effects and coexistence in multi-species communities. In the case of non-local, but short-range dispersal, we observe agreement with the predictions of local models for weak and medium dispersal strength, but disagreement for relatively strong dispersal levels. Our analysis shows the existence of a threshold value in dispersal strength (i.e. saddle-node bifurcation) above which priority effects disappear. These results also reveal a co-dimension 2 point, corresponding to a degenerate transcritical bifurcation: at this point, the transcritical bifurcation changes from subcritical to supercritical with corresponding creation of a saddle-node bifurcation curve. We observe further contrasting effects of non-local dispersal as dispersal distance changes: while very long-range dispersal can lead to species extinctions, intermediate-range dispersal can permit more outcomes with multi-species coexistence than short-range dispersal (or purely local dispersal). Overall, our results show that priority effects are more pronounced in the non-local dispersal models than in the local dispersal models. Taken together, our findings highlight the profound delicacy in the mediation of priority effects by dispersal processes: ;big steps; can have more influence than many ;small steps;.
Data-driven modelling of social forces and collective behaviour in zebrafish.

PubMed

Zienkiewicz, Adam K; Ladu, Fabrizio; Barton, David A W; Porfiri, Maurizio; Bernardo, Mario Di

2018-04-14

Zebrafish are rapidly emerging as a powerful model organism in hypothesis-driven studies targeting a number of functional and dysfunctional processes. Mathematical models of zebrafish behaviour can inform the design of experiments, through the unprecedented ability to perform pilot trials on a computer. At the same time, in-silico experiments could help refining the analysis of real data, by enabling the systematic investigation of key neurobehavioural factors. Here, we establish a data-driven model of zebrafish social interaction. Specifically, we derive a set of interaction rules to capture the primary response mechanisms which have been observed experimentally. Contrary to previous studies, we include dynamic speed regulation in addition to turning responses, which together provide attractive, repulsive and alignment interactions between individuals. The resulting multi-agent model provides a novel, bottom-up framework to describe both the spontaneous motion and individual-level interaction dynamics of zebrafish, inferred directly from experimental observations. Copyright © 2018 Elsevier Ltd. All rights reserved.
A Study on the Application of the Extended Matrices Based on TRIZ in Constructing a Collaborative Model of Enterprise Network

NASA Astrophysics Data System (ADS)

Yang, Yan; Shao, Yunfei; Tang, Xiaowo

Based on mass related literature on enterprise network, the key influence factors are reduced to Trust, Control, Relationship and Interaction. Meanwhile, the specific contradiction matrices, judgment matrices and strategy collections based on TRIZ are constructed which make the connotation of contradiction matrices in TRIZ extended. Finally they are applied to the construction of the collaborative model on enterprise network based on Multi Agent System (MAS).
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
Integration of multi-omics data for integrative gene regulatory network inference.

PubMed

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun; Kang, Mingon

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called 'multi-omics data', that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN's capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed.
Integration of multi-omics data for integrative gene regulatory network inference

PubMed Central

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called ‘multi-omics data’, that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN’s capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed. PMID:29354189
Parameter Estimation of Computationally Expensive Watershed Models Through Efficient Multi-objective Optimization and Interactive Decision Analytics

NASA Astrophysics Data System (ADS)

Akhtar, Taimoor; Shoemaker, Christine

2016-04-01

Watershed model calibration is inherently a multi-criteria problem. Conflicting trade-offs exist between different quantifiable calibration criterions indicating the non-existence of a single optimal parameterization. Hence, many experts prefer a manual approach to calibration where the inherent multi-objective nature of the calibration problem is addressed through an interactive, subjective, time-intensive and complex decision making process. Multi-objective optimization can be used to efficiently identify multiple plausible calibration alternatives and assist calibration experts during the parameter estimation process. However, there are key challenges to the use of multi objective optimization in the parameter estimation process which include: 1) multi-objective optimization usually requires many model simulations, which is difficult for complex simulation models that are computationally expensive; and 2) selection of one from numerous calibration alternatives provided by multi-objective optimization is non-trivial. This study proposes a "Hybrid Automatic Manual Strategy" (HAMS) for watershed model calibration to specifically address the above-mentioned challenges. HAMS employs a 3-stage framework for parameter estimation. Stage 1 incorporates the use of an efficient surrogate multi-objective algorithm, GOMORS, for identification of numerous calibration alternatives within a limited simulation evaluation budget. The novelty of HAMS is embedded in Stages 2 and 3 where an interactive visual and metric based analytics framework is available as a decision support tool to choose a single calibration from the numerous alternatives identified in Stage 1. Stage 2 of HAMS provides a goodness-of-fit measure / metric based interactive framework for identification of a small subset (typically less than 10) of meaningful and diverse set of calibration alternatives from the numerous alternatives obtained in Stage 1. Stage 3 incorporates the use of an interactive visual analytics framework for decision support in selection of one parameter combination from the alternatives identified in Stage 2. HAMS is applied for calibration of flow parameters of a SWAT model, (Soil and Water Assessment Tool) designed to simulate flow in the Cannonsville watershed in upstate New York. Results from the application of HAMS to Cannonsville indicate that efficient multi-objective optimization and interactive visual and metric based analytics can bridge the gap between the effective use of both automatic and manual strategies for parameter estimation of computationally expensive watershed models.
Building a maintenance policy through a multi-criterion decision-making model

NASA Astrophysics Data System (ADS)

Faghihinia, Elahe; Mollaverdi, Naser

2012-08-01

A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.
Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

PubMed

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.
Non-Equilibrium Turbulence Modeling for High Lift Aerodynamics

NASA Technical Reports Server (NTRS)

Durbin, P. A.

1998-01-01

This phase is discussed in ('Non linear kappa - epsilon - upsilon(sup 2) modeling with application to high lift', Application of the kappa - epsilon -upsilon(sup 2) model to multi-component airfoils'). Further results are presented in 'Non-linear upsilon(sup 2) - f modeling with application to high-lift' The ADI solution method in the initial implementation was very slow to converge on multi-zone chimera meshes. I modified the INS implementation to use GMRES. This provided improved convergence and less need for user intervention in the solution process. There were some difficulties with implementation into the NASA compressible codes, due to their use of approximate factorization. The Helmholtz equation for f is not an evolution equation, so it is not of the form assumed by the approximate factorization method. Although The Kalitzin implementation involved a new solution algorithm ('An implementation of the upsilon(sup 2) - f model with application to transonic flows'). The algorithm involves introducing a relaxation term in the f-equation so that it can be factored. The factorization can be into a plane and a line, with GMRES used in the plane. The NASA code already evaluated coefficients in planes, so no additional memory is required except that associated the the GMRES algorithm. So the scope of this project has expanded via these interactions. . The high-lift work has dovetailed into turbine applications.
Mean-field velocity difference model considering the average effect of multi-vehicle interaction

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

PubMed Central

Chauhan, Rinki; Ravi, Janani; Datta, Pratik; Chen, Tianlong; Schnappinger, Dirk; Bassler, Kevin E.; Balázsi, Gábor; Gennaro, Maria Laura

2016-01-01

Accessory sigma factors, which reprogram RNA polymerase to transcribe specific gene sets, activate bacterial adaptive responses to noxious environments. Here we reconstruct the complete sigma factor regulatory network of the human pathogen Mycobacterium tuberculosis by an integrated approach. The approach combines identification of direct regulatory interactions between M. tuberculosis sigma factors in an E. coli model system, validation of selected links in M. tuberculosis, and extensive literature review. The resulting network comprises 41 direct interactions among all 13 sigma factors. Analysis of network topology reveals (i) a three-tiered hierarchy initiating at master regulators, (ii) high connectivity and (iii) distinct communities containing multiple sigma factors. These topological features are likely associated with multi-layer signal processing and specialized stress responses involving multiple sigma factors. Moreover, the identification of overrepresented network motifs, such as autoregulation and coregulation of sigma and anti-sigma factor pairs, provides structural information that is relevant for studies of network dynamics. PMID:27029515
Developing a multi-systemic fall prevention model, incorporating the physical environment, the care process and technology: a systematic review.

PubMed

Choi, Young-Seon; Lawler, Erin; Boenecke, Clayton A; Ponatoski, Edward R; Zimring, Craig M

2011-12-01

This paper reports a review that assessed the effectiveness and characteristics of fall prevention interventions implemented in hospitals. A multi-systemic fall prevention model that establishes a practical framework was developed from the evidence. Falls occur through complex interactions between patient-related and environmental risk factors, suggesting a need for multifaceted fall prevention approaches that address both factors. We searched Medline, CINAHL, PsycInfo and the Web of Science databases for references published between January 1990 and June 2009 and scrutinized secondary references from acquired papers. Due to the heterogeneity of interventions and populations, we conducted a quantitative systematic review without a meta-analysis and used a narrative summary to report findings. From the review, three distinct characteristics of fall prevention interventions emerged: (1) the physical environment, (2) the care process and culture and (3) technology. While clinically significant evidence shows the efficacy of environment-related interventions in reducing falls and fall-related injuries, the literature identified few hospitals that had introduced environment-related interventions in their multifaceted fall intervention strategies. Using the multi-systemic fall prevention model, hospitals should promote a practical strategy that benefits from the collective effects of the physical environment, the care process and culture and technology to prevent falls and fall-related injuries. By doing so, they can more effectively address the various risk factors for falling and therefore, prevent falls. Studies that test the proposed model need to be conducted to establish the efficacy of the model in practice. © 2011 The Authors. Journal of Advanced Nursing © 2011 Blackwell Publishing Ltd.
Probabilistic simulation of the human factor in structural reliability

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1993-01-01

A formal approach is described in an attempt to computationally simulate the probable ranges of uncertainties of the human factor in structural probabilistic assessments. A multi-factor interaction equation (MFIE) model has been adopted for this purpose. Human factors such as marital status, professional status, home life, job satisfaction, work load and health, are considered to demonstrate the concept. Parametric studies in conjunction with judgment are used to select reasonable values for the participating factors (primitive variables). Suitability of the MFIE in the subsequently probabilistic sensitivity studies are performed to assess the validity of the whole approach. Results obtained show that the uncertainties for no error range from five to thirty percent for the most optimistic case.
The interactions between vegetation and climate seasonality, topography on different time scales under the Budyko framework: case study in China's Loess Plateau

NASA Astrophysics Data System (ADS)

Liu, W.; Ning, T.; Shen, H.; Li, Z.

2017-12-01

Vegetation, climate seasonality and topography are the main impact factors controlling the water and heat balance over a catchment, and they are usually empirically formulated into the controlling parameter in Budyko model. However, their interactions on different time scales have not been fully addressed. Taking 30 catchments in China's Loess Plateau as an example, on annual scale, vegetation coverage was found poorly correlated with climate seasonality index; therefore, they could be both parameterized into the Budyko model. On the long-term scale, vegetation coverage tended to have close relationships with topographic conditions and climate seasonality, which was confirmed by the multi-collinearity problems; in that sense, vegetation information could fit the controlling parameter exclusively. Identifying the dominant controlling factors over different time scales, this study simplified the empirical parameterization of the Budyko formula. Though the above relationships further investigation over the other regions/catchments.
A multi-scaled approach to evaluating the fish assemblage structure within southern Appalachian streams USA.

USGS Publications Warehouse

Kirsch, Joseph; Peterson, James T.

2014-01-01

There is considerable uncertainty about the relative roles of stream habitat and landscape characteristics in structuring stream-fish assemblages. We evaluated the relative importance of environmental characteristics on fish occupancy at the local and landscape scales within the upper Little Tennessee River basin of Georgia and North Carolina. Fishes were sampled using a quadrat sample design at 525 channel units within 48 study reaches during two consecutive years. We evaluated species–habitat relationships (local and landscape factors) by developing hierarchical, multispecies occupancy models. Modeling results suggested that fish occupancy within the Little Tennessee River basin was primarily influenced by stream topology and topography, urban land coverage, and channel unit types. Landscape scale factors (e.g., urban land coverage and elevation) largely controlled the fish assemblage structure at a stream-reach level, and local-scale factors (i.e., channel unit types) influenced fish distribution within stream reaches. Our study demonstrates the utility of a multi-scaled approach and the need to account for hierarchy and the interscale interactions of factors influencing assemblage structure prior to monitoring fish assemblages, developing biological management plans, or allocating management resources throughout a stream system.
Self-tuning multivariable pole placement control of a multizone crystal growth furnace

NASA Technical Reports Server (NTRS)

Batur, C.; Sharpless, R. B.; Duval, W. M. B.; Rosenthal, B. N.

1992-01-01

This paper presents the design and implementation of a multivariable self-tuning temperature controller for the control of lead bromide crystal growth. The crystal grows inside a multizone transparent furnace. There are eight interacting heating zones shaping the axial temperature distribution inside the furnace. A multi-input, multi-output furnace model is identified on-line by a recursive least squares estimation algorithm. A multivariable pole placement controller based on this model is derived and implemented. Comparison between single-input, single-output and multi-input, multi-output self-tuning controllers demonstrates that the zone-to-zone interactions can be minimized better by a multi-input, multi-output controller design. This directly affects the quality of crystal grown.
Multi-Resolution Rapid Prototyping of Vehicle Cooling Systems: Approach and Test Results

DTIC Science & Technology

2014-08-01

where the A/C was working. Figure 21: Comparison model/experiment for condenser refrigerant power; heat transfer factor = 0.8 The figure...previously. To demonstrate stable interactions with a more realistic environment, we have connected the four heat exchangers (two radiators, condenser ...simulations of any vehicle (or other) cooling systems. It can be seen that the underHood heat exchangers (transaxle radiator, condenser and ICE
A multi-scale mathematical modeling framework to investigate anti-viral therapeutic opportunities in targeting HIV-1 accessory proteins

PubMed Central

Suryawanshi, Gajendra W.; Hoffmann, Alexander

2015-01-01

Human immunodeficiency virus-1 (HIV-1) employs accessory proteins to evade innate immune responses by neutralizing the anti-viral activity of host restriction factors. Apolipoprotein B mRNA-editing enzyme 3G (APOBEC3G, A3G) and bone marrow stromal cell antigen 2 (BST2) are host resistance factors that potentially inhibit HIV-1 infection. BST2 reduces viral production by tethering budding HIV-1 particles to virus producing cells, while A3G inhibits the reverse transcription (RT) process and induces viral genome hypermutation through cytidine deamination, generating fewer replication competent progeny virus. Two HIV-1 proteins counter these cellular restriction factors: Vpu, which reduces surface BST2, and Vif, which degrades cellular A3G. The contest between these host and viral proteins influences whether HIV-1 infection is established and progresses towards AIDS. In this work, we present an age-structured multi-scale viral dynamics model of in vivo HIV-1 infection. We integrated the intracellular dynamics of anti-viral activity of the host factors and their neutralization by HIV-1 accessory proteins into the virus/cell population dynamics model. We calculate the basic reproductive ratio (Ro) as a function of host-viral protein interaction coefficients, and numerically simulated the multi-scale model to understand HIV-1 dynamics following host factor-induced perturbations. We found that reducing the influence of Vpu triggers a drop in Ro, revealing the impact of BST2 on viral infection control. Reducing Vif’s effect reveals the restrictive efficacy of A3G in blocking RT and in inducing lethal hypermutations, however, neither of these factors alone is sufficient to fully restrict HIV-1 infection. Interestingly, our model further predicts that BST2 and A3G function synergistically, and delineates their relative contribution in limiting HIV-1 infection and disease progression. We provide a robust modeling framework for devising novel combination therapies that target HIV-1 accessory proteins and boost antiviral activity of host factors. PMID:26385832

Modeling synthetic lethality

PubMed Central

Le Meur, Nolwenn; Gentleman, Robert

2008-01-01

Background Synthetic lethality defines a genetic interaction where the combination of mutations in two or more genes leads to cell death. The implications of synthetic lethal screens have been discussed in the context of drug development as synthetic lethal pairs could be used to selectively kill cancer cells, but leave normal cells relatively unharmed. A challenge is to assess genome-wide experimental data and integrate the results to better understand the underlying biological processes. We propose statistical and computational tools that can be used to find relationships between synthetic lethality and cellular organizational units. Results In Saccharomyces cerevisiae, we identified multi-protein complexes and pairs of multi-protein complexes that share an unusually high number of synthetic genetic interactions. As previously predicted, we found that synthetic lethality can arise from subunits of an essential multi-protein complex or between pairs of multi-protein complexes. Finally, using multi-protein complexes allowed us to take into account the pleiotropic nature of the gene products. Conclusions Modeling synthetic lethality using current estimates of the yeast interactome is an efficient approach to disentangle some of the complex molecular interactions that drive a cell. Our model in conjunction with applied statistical methods and computational methods provides new tools to better characterize synthetic genetic interactions. PMID:18789146
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.
Hazard Interactions and Interaction Networks (Cascades) within Multi-Hazard Methodologies

NASA Astrophysics Data System (ADS)

Gill, Joel; Malamud, Bruce D.

2016-04-01

Here we combine research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between 'multi-layer single hazard' approaches and 'multi-hazard' approaches that integrate such interactions. This synthesis suggests that ignoring interactions could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. We proceed to present an enhanced multi-hazard framework, through the following steps: (i) describe and define three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment; (ii) outline three types of interaction relationship (triggering, increased probability, and catalysis/impedance); and (iii) assess the importance of networks of interactions (cascades) through case-study examples (based on literature, field observations and semi-structured interviews). We further propose visualisation frameworks to represent these networks of interactions. Our approach reinforces the importance of integrating interactions between natural hazards, anthropogenic processes and technological hazards/disasters into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential, and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability between successive hazards, and (iii) prioritise resource allocation for mitigation and disaster risk reduction.
Quantum-mechanical parameters for the risk assessment of multi-walled carbon-nanotubes: A study using adsorption of probe compounds and its application to biomolecules.

PubMed

Chayawan; Vikas

2016-11-01

This work forwards new insights into the risk-assessment of multi-walled carbon-nanotubes (MWCNTs) while analysing the role of quantum-mechanical interactions between the electrons in the adsorption of probe compounds and biomolecules by MWCNTs. For this, the quantitative models are developed using quantum-chemical descriptors and their electron-correlation contribution. The major quantum-chemical factors contributing to the adsorption are found to be mean polarizability, electron-correlation energy, and electron-correlation contribution to the absolute electronegativity and LUMO energy. The proposed models, based on only three quantum-chemical factors, are found to be even more robust and predictive than the previously known five or four factors based linear free-energy and solvation-energy relationships. The proposed models are employed to predict the adsorption of biomolecules including steroid hormones and DNA bases. The steroid hormones are predicted to be strongly adsorbed by the MWCNTs, with the order: hydrocortisone > aldosterone > progesterone > ethinyl-oestradiol > testosterone > oestradiol, whereas the DNA bases are found to be relatively less adsorbed but follow the order as: guanine > adenine > thymine > cytosine > uracil. Besides these, the developed electron-correlation based models predict several insecticides, pesticides, herbicides, fungicides, plasticizers and antimicrobial agents in cosmetics, to be strongly adsorbed by the carbon-nanotubes. The present study proposes that the instantaneous inter-electronic interactions may be quite significant in various physico-chemical processes involving MWCNTs, and can be used as a reliable predictor for their risk assessment. Copyright © 2016 Elsevier Ltd. All rights reserved.
A novel approach to simulate gene-environment interactions in complex diseases.

PubMed

Amato, Roberto; Pinelli, Michele; D'Andrea, Daniel; Miele, Gennaro; Nicodemi, Mario; Raiconi, Giancarlo; Cocozza, Sergio

2010-01-05

Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study.
Synchronization of multi-agent systems with metric-topological interactions.

PubMed

Wang, Lin; Chen, Guanrong

2016-09-01

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

NASA Astrophysics Data System (ADS)

Li, X. Z.; Kong, J. M.

2013-10-01

Prediction of landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. Support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ) of SVM model. In this study, we presented an application of GA-SVM method with parameter optimization in landslide displacement rate prediction. We selected a typical large-scale landslide in some hydro - electrical engineering area of Southwest China as a case. On the basis of analyzing the basic characteristics and monitoring data of the landslide, a single-factor GA-SVM model and a multi-factor GA-SVM model of the landslide were built. Moreover, the models were compared with single-factor and multi-factor SVM models of the landslide. The results show that, the four models have high prediction accuracies, but the accuracies of GA-SVM models are slightly higher than those of SVM models and the accuracies of multi-factor models are slightly higher than those of single-factor models for the landslide prediction. The accuracy of the multi-factor GA-SVM models is the highest, with the smallest RSME of 0.0009 and the biggest RI of 0.9992.
A multiphase three-dimensional multi-relaxation time (MRT) lattice Boltzmann model with surface tension adjustment

NASA Astrophysics Data System (ADS)

Ammar, Sami; Pernaudat, Guillaume; Trépanier, Jean-Yves

2017-08-01

The interdependence of surface tension and density ratio is a weakness of pseudo-potential based lattice Boltzmann models (LB). In this paper, we propose a 3D multi-relaxation time (MRT) model for multiphase flows at large density ratios. The proposed model is capable of adjusting the surface tension independently of the density ratio. We also present the 3D macroscopic equations recovered by the proposed forcing scheme. A high order of isotropy for the interaction force is used to reduce the amplitude of spurious currents. The proposed 3D-MRT model is validated by verifying Laplace's law and by analyzing its thermodynamic consistency and the oscillation period of a deformed droplet. The model is then applied to the simulation of the impact of a droplet on a dry surface. Impact dynamics are determined and the maximum spread factor calculated for different Reynolds and Weber numbers. The numerical results are in agreement with data published in the literature. The influence of surface wettability on the spread factor is also investigated. Finally, our 3D-MRT model is applied to the simulation of the impact of a droplet on a wet surface. The propagation of transverse waves is observed on the liquid surface.
Development of multi-metal interaction model for Daphnia magna: Significance of metallothionein in cellular redistribution.

PubMed

Wang, Xiangrui; Liu, Jianyu; Tan, Qiaoguo; Ren, Jinqian; Liang, Dingyuan; Fan, Wenhong

2018-04-30

Despite the great progress made in metal-induced toxicity mechanisms, a critical knowledge gap still exists in predicting adverse effects of heavy metals on living organisms in the natural environment, particularly during exposure to multi-metals. In this study, a multi-metal interaction model of Daphnia manga was developed in an effort to provide reasonable explanations regarding the joint effects resulting from exposure to multi-metals. Metallothionein (MT), a widely used biomarker, was selected. In this model, MT was supposed to play the role of a crucial transfer protein rather than detoxifying protein. Therefore, competitive complexation of metals to MT could highly affect the cellular metal redistribution. Thus, competitive complexation of MT in D. magna with metals like Pb 2+ , Cd 2+ and Cu 2+ was qualitatively studied. The results suggested that Cd 2+ had the highest affinity towards MT, followed by Pb 2+ and Cu 2+ . On the other hand, the combination of MT with Cu 2+ appeared to alter its structure which resulted in higher affinity towards Pb 2+ . Overall, the predicted bioaccumulation of metals under multi-metal exposure was consisted with earlier reported studies. This model provided an alternative angle for joint effect through a combination of kinetic process and internal interactions, which could help to develop future models predicting toxicity to multi-metal exposure. Copyright © 2017 Elsevier Inc. All rights reserved.
TH-CD-207B-06: Swank Factor of Segmented Scintillators in Multi-Slice CT Detectors: Pulse Height Spectra and Light Escape

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

Howansky, A; Peng, B; Lubinsky, A

Purpose: Pulse height spectra (PHS) have been used to determine the Swank factor of a scintillator by measuring fluctuations in its light output per x-ray interaction. The Swank factor and x-ray quantum efficiency of a scintillator define the upper limit to its imaging performance, i.e. DQE(0). The Swank factor below the K-edge is dominated by optical properties, i.e. variations in light escape efficiency from different depths of interaction, denoted e(z). These variations can be optimized to improve tradeoffs in x-ray absorption, light yield, and spatial resolution. This work develops a quantitative model for interpreting measured PHS, and estimating e(z) onmore » an absolute scale. The method is used to investigate segmented ceramic GOS scintillators used in multi-slice CT detectors. Methods: PHS of a ceramic GOS plate (1 mm thickness) and segmented GOS array (1.4 mm thick) were measured at 46 keV. Signal and noise propagation through x-ray conversion gain, light escape, detection by a photomultiplier tube and dynode amplification were modeled using a cascade of stochastic gain stages. PHS were calculated with these expressions and compared to measurements. Light escape parameters were varied until modeled PHS agreed with measurements. The resulting estimates of e(z) were used to calculate PHS without measurement noise to determine the inherent Swank factor. Results: The variation in e(z) was 67.2–89.7% in the plate and 40.2–70.8% in the segmented sample, corresponding to conversion gains of 28.6–38.1 keV{sup −1} and 17.1–30.1 keV{sup −1}, respectively. The inherent Swank factors of the plate and segmented sample were 0.99 and 0.95, respectively. Conclusion: The high light escape efficiency in the ceramic GOS samples yields high Swank factors and DQE(0) in CT applications. The PHS model allows the intrinsic optical properties of scintillators to be deduced from PHS measurements, thus it provides new insights for evaluating the imaging performance of segmented ceramic GOS scintillators.« less
Application of multi-factorial design of experiments to successfully optimize immunoassays for robust measurements of therapeutic proteins.

PubMed

Ray, Chad A; Patel, Vimal; Shih, Judy; Macaraeg, Chris; Wu, Yuling; Thway, Theingi; Ma, Mark; Lee, Jean W; Desilva, Binodh

2009-02-20

Developing a process that generates robust immunoassays that can be used to support studies with tight timelines is a common challenge for bioanalytical laboratories. Design of experiments (DOEs) is a tool that has been used by many industries for the purpose of optimizing processes. The approach is capable of identifying critical factors and their interactions with a minimal number of experiments. The challenge for implementing this tool in the bioanalytical laboratory is to develop a user-friendly approach that scientists can understand and apply. We have successfully addressed these challenges by eliminating the screening design, introducing automation, and applying a simple mathematical approach for the output parameter. A modified central composite design (CCD) was applied to three ligand binding assays. The intra-plate factors selected were coating, detection antibody concentration, and streptavidin-HRP concentrations. The inter-plate factors included incubation times for each step. The objective was to maximize the logS/B (S/B) of the low standard to the blank. The maximum desirable conditions were determined using JMP 7.0. To verify the validity of the predictions, the logS/B prediction was compared against the observed logS/B during pre-study validation experiments. The three assays were optimized using the multi-factorial DOE. The total error for all three methods was less than 20% which indicated method robustness. DOE identified interactions in one of the methods. The model predictions for logS/B were within 25% of the observed pre-study validation values for all methods tested. The comparison between the CCD and hybrid screening design yielded comparable parameter estimates. The user-friendly design enables effective application of multi-factorial DOE to optimize ligand binding assays for therapeutic proteins. The approach allows for identification of interactions between factors, consistency in optimal parameter determination, and reduced method development time.
Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort.

PubMed

Abdullah, N; Abdul Murad, N A; Mohd Haniff, E A; Syafruddin, S E; Attia, J; Oldmeadow, C; Kamaruddin, M A; Abd Jalal, N; Ismail, N; Ishak, M; Jamal, R; Scott, R J; Holliday, E G

2017-08-01

Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. The models including environmental risk factors only had pseudo R 2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10 -4 -4.83 × 10 -12 ) and increased the pseudo R 2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. Copyright © 2017 The Royal Society for Public Health. All rights reserved.
Outcome based state budget allocation for diabetes prevention programs using multi-criteria optimization with robust weights.

PubMed

Mehrotra, Sanjay; Kim, Kibaek

2011-12-01

We consider the problem of outcomes based budget allocations to chronic disease prevention programs across the United States (US) to achieve greater geographical healthcare equity. We use Diabetes Prevention and Control Programs (DPCP) by the Center for Disease Control and Prevention (CDC) as an example. We present a multi-criteria robust weighted sum model for such multi-criteria decision making in a group decision setting. The principal component analysis and an inverse linear programming techniques are presented and used to study the actual 2009 budget allocation by CDC. Our results show that the CDC budget allocation process for the DPCPs is not likely model based. In our empirical study, the relative weights for different prevalence and comorbidity factors and the corresponding budgets obtained under different weight regions are discussed. Parametric analysis suggests that money should be allocated to states to promote diabetes education and to increase patient-healthcare provider interactions to reduce disparity across the US.
Multi-Compartmentalisation in the MAPK Signalling Pathway Contributes to the Emergence of Oscillatory Behaviour and to Ultrasensitivity

PubMed Central

Shuaib, Aban; Hartwell, Adam; Kiss-Toth, Endre; Holcombe, Mike

2016-01-01

Signal transduction through the Mitogen Activated Protein Kinase (MAPK) pathways is evolutionarily highly conserved. Many cells use these pathways to interpret changes to their environment and respond accordingly. The pathways are central to triggering diverse cellular responses such as survival, apoptosis, differentiation and proliferation. Though the interactions between the different MAPK pathways are complex, nevertheless, they maintain a high level of fidelity and specificity to the original signal. There are numerous theories explaining how fidelity and specificity arise within this complex context; spatio-temporal regulation of the pathways and feedback loops are thought to be very important. This paper presents an agent based computational model addressing multi-compartmentalisation and how this influences the dynamics of MAPK cascade activation. The model suggests that multi-compartmentalisation coupled with periodic MAPK kinase (MAPKK) activation may be critical factors for the emergence of oscillation and ultrasensitivity in the system. Finally, the model also establishes a link between the spatial arrangements of the cascade components and temporal activation mechanisms, and how both contribute to fidelity and specificity of MAPK mediated signalling. PMID:27243235
Actor-network Procedures: Modeling Multi-factor Authentication, Device Pairing, Social Interactions

DTIC Science & Technology

2011-08-29

unmodifiable properties of your body; or the capabilities that you cannot convey to others, such as your handwriting . An identity can thus be determined by...network, two principals with the same set of secrets but, say , different computational powers, can be distinguished by timing their responses. Or they... says that configurations are finite sets. Partially ordered multisets, or pomsets were introduced and extensively studied by Vaughan Pratt and his
Topological invariant and cotranslational symmetry in strongly interacting multi-magnon systems

NASA Astrophysics Data System (ADS)

Qin, Xizhou; Mei, Feng; Ke, Yongguan; Zhang, Li; Lee, Chaohong

2018-01-01

It is still an outstanding challenge to characterize and understand the topological features of strongly interacting states such as bound states in interacting quantum systems. Here, by introducing a cotranslational symmetry in an interacting multi-particle quantum system, we systematically develop a method to define a Chern invariant, which is a generalization of the well-known Thouless-Kohmoto-Nightingale-den Nijs invariant, for identifying strongly interacting topological states. As an example, we study the topological multi-magnon states in a generalized Heisenberg XXZ model, which can be realized by the currently available experiment techniques of cold atoms (Aidelsburger et al 2013 Phys. Rev. Lett. 111, 185301; Miyake et al 2013 Phys. Rev. Lett. 111, 185302). Through calculating the two-magnon excitation spectrum and the defined Chern number, we explore the emergence of topological edge bound states and give their topological phase diagram. We also analytically derive an effective single-particle Hofstadter superlattice model for a better understanding of the topological bound states. Our results not only provide a new approach to defining a topological invariant for interacting multi-particle systems, but also give insights into the characterization and understanding of strongly interacting topological states.
Multi-Collinearity Based Model Selection for Landslide Susceptibility Mapping: A Case Study from Ulus District of Karabuk, Turkey

NASA Astrophysics Data System (ADS)

Sahin, E. K.; Colkesen, I., , Dr; Kavzoglu, T.

2017-12-01

Identification of localities prone to landslide areas plays an important role for emergency planning, disaster management and recovery planning. Due to its great importance for disaster management, producing accurate and up-to-date landslide susceptibility maps is essential for hazard mitigation purpose and regional planning. The main objective of the present study was to apply multi-collinearity based model selection approach for the production of a landslide susceptibility map of Ulus district of Karabuk, Turkey. It is a fact that data do not contain enough information to describe the problem under consideration when the factors are highly correlated with each other. In such cases, choosing a subset of the original features will often lead to better performance. This paper presents multi-collinearity based model selection approach to deal with the high correlation within the dataset. Two collinearity diagnostic factors (Tolerance (TOL) and the Variance Inflation Factor (VIF)) are commonly used to identify multi-collinearity. Values of VIF that exceed 10.0 and TOL values less than 1.0 are often regarded as indicating multi-collinearity. Five causative factors (slope length, curvature, plan curvature, profile curvature and topographical roughness index) were found highly correlated with each other among 15 factors available for the study area. As a result, the five correlated factors were removed from the model estimation, and performances of the models including the remaining 10 factors (aspect, drainage density, elevation, lithology, land use/land cover, NDVI, slope, sediment transport index, topographical position index and topographical wetness index) were evaluated using logistic regression. The performance of prediction model constructed with 10 factors was compared to that of 15-factor model. The prediction performance of two susceptibility maps was evaluated by overall accuracy and the area under the ROC curve (AUC) values. Results showed that overall accuracy and AUC was calculated as 77.15% and 96.62% respectively for the model with 10 selected factors whilst they were estimated as 73.45% and 89.45% respectively for the model with all factors. It is clear that the multi-collinearity based model outperformed the conventional model in the mapping of landslide susceptibility.
Individual Characteristics, Family Factors, and Classroom Experiences as Predictors of Low-Income Kindergarteners' Social Skills.

PubMed

Griffith, Shayl; Arnold, David; Voegler-Lee, Mary-Ellen; Kupersmidt, Janis

2016-01-01

There has been increasing awareness of the need for research and theory to take into account the intersection of individual characteristics and environmental contexts when examining predictors of child outcomes. The present longitudinal, multi-informant study examined the cumulative and interacting contributions of child characteristics (language skills, inattention/hyperactivity, and aggression) and preschool and family contextual factors in predicting kindergarten social skills in 389 low-income preschool children. Child characteristics and classroom factors, but not family factors, predicted teacher-rated kindergarten social skills, while child characteristics alone predicted change in teacher-rated social skills from preschool to kindergarten. Child characteristics and family factors, but not classroom factors, predicted parent-rated kindergarten social skills. Family factors alone predicted change in parent-rated social skills from preschool to kindergarten. Individual child characteristics did not interact with family or classroom factors in predicting parent- or teacher-rated social skills, and support was therefore found for an incremental, rather than an interactive, predictive model of social skills. The findings underscore the importance of assessing outcomes in more than one context, and of considering the impact of both individual and environmental contextual factors on children's developing social skills when designing targeted intervention programs to prepare children for kindergarten.
Individual Characteristics, Family Factors, and Classroom Experiences as Predictors of Low-Income Kindergarteners’ Social Skills

PubMed Central

Griffith, Shayl; Arnold, David; Voegler-Lee, Mary-Ellen; Kupersmidt, Janis

2017-01-01

There has been increasing awareness of the need for research and theory to take into account the intersection of individual characteristics and environmental contexts when examining predictors of child outcomes. The present longitudinal, multi-informant study examined the cumulative and interacting contributions of child characteristics (language skills, inattention/hyperactivity, and aggression) and preschool and family contextual factors in predicting kindergarten social skills in 389 low-income preschool children. Child characteristics and classroom factors, but not family factors, predicted teacher-rated kindergarten social skills, while child characteristics alone predicted change in teacher-rated social skills from preschool to kindergarten. Child characteristics and family factors, but not classroom factors, predicted parent-rated kindergarten social skills. Family factors alone predicted change in parent-rated social skills from preschool to kindergarten. Individual child characteristics did not interact with family or classroom factors in predicting parent- or teacher-rated social skills, and support was therefore found for an incremental, rather than an interactive, predictive model of social skills. The findings underscore the importance of assessing outcomes in more than one context, and of considering the impact of both individual and environmental contextual factors on children’s developing social skills when designing targeted intervention programs to prepare children for kindergarten. PMID:28804528
A Multi-Agent System for Intelligent Online Education.

ERIC Educational Resources Information Center

O'Riordan, Colm; Griffith, Josephine

1999-01-01

Describes the system architecture of an intelligent Web-based education system that includes user modeling agents, information filtering agents for automatic information gathering, and the multi-agent interaction. Discusses information management; user interaction; support for collaborative peer-peer learning; implementation; testing; and future…

To be or not to be associated: power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies

PubMed Central

Vaumourin, Elise; Vourc'h, Gwenaël; Telfer, Sandra; Lambin, Xavier; Salih, Diaeldin; Seitzer, Ulrike; Morand, Serge; Charbonnel, Nathalie; Vayssier-Taussat, Muriel; Gasqui, Patrick

2014-01-01

A growing number of studies are reporting simultaneous infections by parasites in many different hosts. The detection of whether these parasites are significantly associated is important in medicine and epidemiology. Numerous approaches to detect associations are available, but only a few provide statistical tests. Furthermore, they generally test for an overall detection of association and do not identify which parasite is associated with which other one. Here, we developed a new approach, the association screening approach, to detect the overall and the detail of multi-parasite associations. We studied the power of this new approach and of three other known ones (i.e., the generalized chi-square, the network and the multinomial GLM approaches) to identify parasite associations either due to parasite interactions or to confounding factors. We applied these four approaches to detect associations within two populations of multi-infected hosts: (1) rodents infected with Bartonella sp., Babesia microti and Anaplasma phagocytophilum and (2) bovine population infected with Theileria sp. and Babesia sp. We found that the best power is obtained with the screening model and the generalized chi-square test. The differentiation between associations, which are due to confounding factors and parasite interactions was not possible. The screening approach significantly identified associations between Bartonella doshiae and B. microti, and between T. parva, T. mutans, and T. velifera. Thus, the screening approach was relevant to test the overall presence of parasite associations and identify the parasite combinations that are significantly over- or under-represented. Unraveling whether the associations are due to real biological interactions or confounding factors should be further investigated. Nevertheless, in the age of genomics and the advent of new technologies, it is a considerable asset to speed up researches focusing on the mechanisms driving interactions between parasites. PMID:24860791
An Interactive Multi-Model for Consensus on Climate Change

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

Kocarev, Ljupco

This project purports to develop a new scheme for forming consensus among alternative climate models, that give widely divergent projections as to the details of climate change, that is more intelligent than simply averaging the model outputs, or averaging with ex post facto weighting factors. The method under development effectively allows models to assimilate data from one another in run time with weights that are chosen in an adaptive training phase using 20th century data, so that the models synchronize with one another as well as with reality. An alternate approach that is being explored in parallel is the automatedmore » combination of equations from different models in an expert-system-like framework.« less
Consistency of multi-time Dirac equations with general interaction potentials

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

Deckert, Dirk-André, E-mail: deckert@math.lmu.de; Nickel, Lukas, E-mail: nickel@math.lmu.de

In 1932, Dirac proposed a formulation in terms of multi-time wave functions as candidate for relativistic many-particle quantum mechanics. A well-known consistency condition that is necessary for existence of solutions strongly restricts the possible interaction types between the particles. It was conjectured by Petrat and Tumulka that interactions described by multiplication operators are generally excluded by this condition, and they gave a proof of this claim for potentials without spin-coupling. Under suitable assumptions on the differentiability of possible solutions, we show that there are potentials which are admissible, give an explicit example, however, show that none of them fulfills themore » physically desirable Poincaré invariance. We conclude that in this sense, Dirac’s multi-time formalism does not allow to model interaction by multiplication operators, and briefly point out several promising approaches to interacting models one can instead pursue.« less
Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

NASA Astrophysics Data System (ADS)

Gill, Joel C.; Malamud, Bruce D.

2016-08-01

This paper combines research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between multi-layer single-hazard approaches and multi-hazard approaches that integrate such interactions. This synthesis suggests that ignoring interactions between important environmental and anthropogenic processes could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. In this paper we proceed to present an enhanced multi-hazard framework through the following steps: (i) description and definition of three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment, (ii) outlining of three types of interaction relationship (triggering, increased probability, and catalysis/impedance), and (iii) assessment of the importance of networks of interactions (cascades) through case study examples (based on the literature, field observations and semi-structured interviews). We further propose two visualisation frameworks to represent these networks of interactions: hazard interaction matrices and hazard/process flow diagrams. Our approach reinforces the importance of integrating interactions between different aspects of the Earth system, together with human activity, into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability between successive hazards, and (iii) prioritise resource allocation for mitigation and disaster risk reduction.
Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

ERIC Educational Resources Information Center

Dickes, Amanda Catherine; Sengupta, Pratim

2013-01-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…
Latent feature decompositions for integrative analysis of multi-platform genomic data

PubMed Central

Gregory, Karl B.; Momin, Amin A.; Coombes, Kevin R.; Baladandayuthapani, Veerabhadran

2015-01-01

Increased availability of multi-platform genomics data on matched samples has sparked research efforts to discover how diverse molecular features interact both within and between platforms. In addition, simultaneous measurements of genetic and epigenetic characteristics illuminate the roles their complex relationships play in disease progression and outcomes. However, integrative methods for diverse genomics data are faced with the challenges of ultra-high dimensionality and the existence of complex interactions both within and between platforms. We propose a novel modeling framework for integrative analysis based on decompositions of the large number of platform-specific features into a smaller number of latent features. Subsequently we build a predictive model for clinical outcomes accounting for both within- and between-platform interactions based on Bayesian model averaging procedures. Principal components, partial least squares and non-negative matrix factorization as well as sparse counterparts of each are used to define the latent features, and the performance of these decompositions is compared both on real and simulated data. The latent feature interactions are shown to preserve interactions between the original features and not only aid prediction but also allow explicit selection of outcome-related features. The methods are motivated by and applied to, a glioblastoma multiforme dataset from The Cancer Genome Atlas to predict patient survival times integrating gene expression, microRNA, copy number and methylation data. For the glioblastoma data, we find a high concordance between our selected prognostic genes and genes with known associations with glioblastoma. In addition, our model discovers several relevant cross-platform interactions such as copy number variation associated gene dosing and epigenetic regulation through promoter methylation. On simulated data, we show that our proposed method successfully incorporates interactions within and between genomic platforms to aid accurate prediction and variable selection. Our methods perform best when principal components are used to define the latent features. PMID:26146492
RNAi High-Throughput Screening of Single- and Multi-Cell-Type Tumor Spheroids: A Comprehensive Analysis in Two and Three Dimensions.

PubMed

Fu, Jiaqi; Fernandez, Daniel; Ferrer, Marc; Titus, Steven A; Buehler, Eugen; Lal-Nag, Madhu A

2017-06-01

The widespread use of two-dimensional (2D) monolayer cultures for high-throughput screening (HTS) to identify targets in drug discovery has led to attrition in the number of drug targets being validated. Solid tumors are complex, aberrantly growing microenvironments that harness structural components from stroma, nutrients fed through vasculature, and immunosuppressive factors. Increasing evidence of stromally-derived signaling broadens the complexity of our understanding of the tumor microenvironment while stressing the importance of developing better models that reflect these interactions. Three-dimensional (3D) models may be more sensitive to certain gene-silencing events than 2D models because of their components of hypoxia, nutrient gradients, and increased dependence on cell-cell interactions and therefore are more representative of in vivo interactions. Colorectal cancer (CRC) and breast cancer (BC) models composed of epithelial cells only, deemed single-cell-type tumor spheroids (SCTS) and multi-cell-type tumor spheroids (MCTS), containing fibroblasts were developed for RNAi HTS in 384-well microplates with flat-bottom wells for 2D screening and round-bottom, ultra-low-attachment wells for 3D screening. We describe the development of a high-throughput assay platform that can assess physiologically relevant phenotypic differences between screening 2D versus 3D SCTS, 3D SCTS, and MCTS in the context of different cancer subtypes. This assay platform represents a paradigm shift in how we approach drug discovery that can reduce the attrition rate of drugs that enter the clinic.
A review on machine learning principles for multi-view biological data integration.

PubMed

Li, Yifeng; Wu, Fang-Xiang; Ngom, Alioune

2018-03-01

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.
Scale Interactions in the Tropics from a Simple Multi-Cloud Model

NASA Astrophysics Data System (ADS)

Niu, X.; Biello, J. A.

2017-12-01

Our lack of a complete understanding of the interaction between the moisture convection and equatorial waves remains an impediment in the numerical simulation of large-scale organization, such as the Madden-Julian Oscillation (MJO). The aim of this project is to understand interactions across spatial scales in the tropics from a simplified framework for scale interactions while a using a simplified framework to describe the basic features of moist convection. Using multiple asymptotic scales, Biello and Majda[1] derived a multi-scale model of moist tropical dynamics (IMMD[1]), which separates three regimes: the planetary scale climatology, the synoptic scale waves, and the planetary scale anomalies regime. The scales and strength of the observed MJO would categorize it in the regime of planetary scale anomalies - which themselves are forced from non-linear upscale fluxes from the synoptic scales waves. In order to close this model and determine whether it provides a self-consistent theory of the MJO. A model for diabatic heating due to moist convection must be implemented along with the IMMD. The multi-cloud parameterization is a model proposed by Khouider and Majda[2] to describe the three basic cloud types (congestus, deep and stratiform) that are most responsible for tropical diabatic heating. We implement a simplified version of the multi-cloud model that is based on results derived from large eddy simulations of convection [3]. We present this simplified multi-cloud model and show results of numerical experiments beginning with a variety of convective forcing states. Preliminary results on upscale fluxes, from synoptic scales to planetary scale anomalies, will be presented. [1] Biello J A, Majda A J. Intraseasonal multi-scale moist dynamics of the tropical atmosphere[J]. Communications in Mathematical Sciences, 2010, 8(2): 519-540. [2] Khouider B, Majda A J. A simple multicloud parameterization for convectively coupled tropical waves. Part I: Linear analysis[J]. Journal of the atmospheric sciences, 2006, 63(4): 1308-1323. [3] Dorrestijn J, Crommelin D T, Biello J A, et al. A data-driven multi-cloud model for stochastic parametrization of deep convection[J]. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 2013, 371(1991): 20120374.
Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials.

PubMed

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A; Burgueño, Juan; Bandeira E Sousa, Massaine; Crossa, José

2018-03-28

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines ([Formula: see text]) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. Copyright © 2018 Cuevas et al.
Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

PubMed Central

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

2018-01-01

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023
Over-expression and purification strategies for recombinant multi-protein oligomers: a case study of Mycobacterium tuberculosis σ/anti-σ factor protein complexes.

PubMed

Thakur, Krishan Gopal; Jaiswal, Ravi Kumar; Shukla, Jinal K; Praveena, T; Gopal, B

2010-12-01

The function of a protein in a cell often involves coordinated interactions with one or several regulatory partners. It is thus imperative to characterize a protein both in isolation as well as in the context of its complex with an interacting partner. High resolution structural information determined by X-ray crystallography and Nuclear Magnetic Resonance offer the best route to characterize protein complexes. These techniques, however, require highly purified and homogenous protein samples at high concentration. This requirement often presents a major hurdle for structural studies. Here we present a strategy based on co-expression and co-purification to obtain recombinant multi-protein complexes in the quantity and concentration range that can enable hitherto intractable structural projects. The feasibility of this strategy was examined using the σ factor/anti-σ factor protein complexes from Mycobacterium tuberculosis. The approach was successful across a wide range of σ factors and their cognate interacting partners. It thus appears likely that the analysis of these complexes based on variations in expression constructs and procedures for the purification and characterization of these recombinant protein samples would be widely applicable for other multi-protein systems. Copyright © 2010 Elsevier Inc. All rights reserved.
Scalable non-negative matrix tri-factorization.

PubMed

Čopar, Andrej; Žitnik, Marinka; Zupan, Blaž

2017-01-01

Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining. Matrix factorization learns a latent data model that takes a data matrix and transforms it into a latent feature space enabling generalization, noise removal and feature discovery. However, factorization algorithms are numerically intensive, and hence there is a pressing challenge to scale current algorithms to work with large datasets. Our focus in this paper is matrix tri-factorization, a popular method that is not limited by the assumption of standard matrix factorization about data residing in one latent space. Matrix tri-factorization solves this by inferring a separate latent space for each dimension in a data matrix, and a latent mapping of interactions between the inferred spaces, making the approach particularly suitable for biomedical data mining. We developed a block-wise approach for latent factor learning in matrix tri-factorization. The approach partitions a data matrix into disjoint submatrices that are treated independently and fed into a parallel factorization system. An appealing property of the proposed approach is its mathematical equivalence with serial matrix tri-factorization. In a study on large biomedical datasets we show that our approach scales well on multi-processor and multi-GPU architectures. On a four-GPU system we demonstrate that our approach can be more than 100-times faster than its single-processor counterpart. A general approach for scaling non-negative matrix tri-factorization is proposed. The approach is especially useful parallel matrix factorization implemented in a multi-GPU environment. We expect the new approach will be useful in emerging procedures for latent factor analysis, notably for data integration, where many large data matrices need to be collectively factorized.
Factors Associated with Cognition in Adults: The Seattle Longitudinal Study

PubMed Central

Yu, Fang; Ryan, Lindsay H.; Schaie, K. Warner; Willis, Sherry L.; Kolanowski, Ann

2010-01-01

A better understanding of factors that affect cognition could lead to improved health and greater independence for older adults. We examined the association of four modifiable factors (leisure-time physical activity, leisure-time cognitive activity, self-directed work, and hypertension) with changes in two aspects of fluid intelligence (verbal memory and inductive reasoning). Data for 626 adults collected over 14 years (three time points) were analyzed by multi-level modeling. A component of self-directed work, higher work control, was associated with better verbal memory (p < .05) and inductive reasoning (p < .01). There were no significant interactions among these factors. The findings suggest that a strong sense of control at work may be protective for fluid intelligence in adults. PMID:19606423
Modeling complex and multi-component food systems in molecular dynamics simulations on the example of chocolate conching.

PubMed

Greiner, Maximilian; Sonnleitner, Bettina; Mailänder, Markus; Briesen, Heiko

2014-02-01

Additional benefits of foods are an increasing factor in the consumer's purchase. To produce foods with the properties the consumer demands, understanding the micro- and nanostructure is becoming more important in food research today. We present molecular dynamics (MD) simulations as a tool to study complex and multi-component food systems on the example of chocolate conching. The process of conching is chosen because of the interesting challenges it provides: the components (fats, emulsifiers and carbohydrates) contain diverse functional groups, are naturally fluctuating in their chemical composition, and have a high number of internal degrees of freedom. Further, slow diffusion in the non-aqueous medium is expected. All of these challenges are typical to food systems in general. Simulation results show the suitability of present force fields to correctly model the liquid and crystal density of cocoa butter and sucrose, respectively. Amphiphilic properties of emulsifiers are observed by micelle formation in water. For non-aqueous media, pulling simulations reveal high energy barriers for motion in the viscous cocoa butter. The work for detachment of an emulsifier from the sucrose crystal is calculated and matched with detachment of the head and tail groups separately. Hydrogen bonding is shown to be the dominant interaction between the emulsifier and the crystal surface. Thus, MD simulations are suited to model the interaction between the emulsifier and sugar crystal interface in non-aqueous media, revealing detailed information about the structuring and interactions on a molecular level. With interaction parameters being available for a wide variety of chemical groups, MD simulations are a valuable tool to understand complex and multi-component food systems in general. MD simulations provide a substantial benefit to researchers to verify their hypothesis in dynamic simulations with an atomistic resolution. Rapid rise of computational resources successively increases the complexity and the size of the systems that can be studied.
A computational intelligent approach to multi-factor analysis of violent crime information system

NASA Astrophysics Data System (ADS)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.
Multi-objective optimization for generating a weighted multi-model ensemble

NASA Astrophysics Data System (ADS)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic ensemble mean and may provide reliable future projections.
Multi-disciplinary coupling for integrated design of propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions for determining the true response of propulsion systems. Results are presented for propulsion system responses including multi-discipline coupling effects via (1) coupled multi-discipline tailoring, (2) an integrated system of multidisciplinary simulators, (3) coupled material-behavior/fabrication-process tailoring, (4) sensitivities using a probabilistic simulator, and (5) coupled materials/structures/fracture/probabilistic behavior simulator. The results show that the best designs can be determined if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated interactive multi-discipline numerical propulsion system simulator.
Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

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

NASA Astrophysics Data System (ADS)

Tabrizi, Babak H.; Razmi, Jafar

2013-05-01

Supply chain management is taken into account as an inseparable component in satisfying customers' requirements. This paper deals with the distribution network design (DND) problem which is a critical issue in achieving supply chain accomplishments. A capable DND can guarantee the success of the entire network performance. However, there are many factors that can cause fluctuations in input data determining market treatment, with respect to short-term planning, on the one hand. On the other hand, network performance may be threatened by the changes that take place within practicing periods, with respect to long-term planning. Thus, in order to bring both kinds of changes under control, we considered a new multi-period, multi-commodity, multi-source DND problem in circumstances where the network encounters uncertain demands. The fuzzy logic is applied here as an efficient tool for controlling the potential customers' demand risk. The defuzzifying framework leads the practitioners and decision-makers to interact with the solution procedure continuously. The fuzzy model is then validated by a sensitivity analysis test, and a typical problem is solved in order to illustrate the implementation steps. Finally, the formulation is tested by some different-sized problems to show its total performance.

When high pressure, system constraints, and a social justice mission collide: A socio-structural analysis of emergency department social work services.

PubMed

Moore, Megan; Cristofalo, Margaret; Dotolo, Danae; Torres, Nicole; Lahdya, Alexandra; Ho, Leyna; Vogel, Mia; Forrester, Mollie; Conley, Bonnie; Fouts, Susan

2017-04-01

The emergency department (ED) can be a critical intervention point for many patients with multifaceted needs. Social workers have long been part of interdisciplinary ED teams. This study aimed to contribute to the limited understanding of social worker-patient interactions and factors influencing social work services in this setting. This paper reports a qualitative content analysis of social work medical record notes (N = 1509) of services provided to trauma patients in an urban, public, level 1 trauma center and an in-depth analysis of semi-structured interviews with ED social workers (N = 10). Eight major social work roles were identified: investigator, gatekeeper, resource broker, care coordinator, problem solver, crisis manager, advocate, discharge planner. Analyses revealed a complex interplay between ED social work services and multi-layered contexts. Using a social-ecological framework, we identified the interactions between micro or individual level factors, mezzo or local system level factors and macro environmental and systemic factors that play a role in ED interactions and patient services. Macro-level contextual influences were socio-structural forces including socioeconomic barriers to health, social hierarchies that reflected power differentials between providers and patients, and distrust or bias. Mezzo-level forces were limited resources, lack of healthcare system coordination, a challenging hierarchy within the medical model and the pressure to discharge patients quickly. Micro-level factors included characteristics of patients and social workers, complexity of patient stressors, empathic strain, lack of closure and compassion. All of these forces were at play in patient-social worker interactions and impacted service provision. Social workers were at times able to successfully navigate these forces, yet at other times these challenges were insurmountable. A conceptual model of ED social work and the influences on the patient-social worker interactions was developed to assist in guiding innovative research and practice models to improve services and outcomes in the complex, fast-paced ED. Copyright © 2017 Elsevier Ltd. All rights reserved.
When high pressure, system constraints, and a social justice mission collide: a socio-structural analysis of emergency department social work services

PubMed Central

Cristofalo, Margaret; Dotolo, Danae; Torres, Nicole; Lahdya, Alexandra; Ho, Leyna; Vogel, Mia; Forrester, Mollie; Conley, Bonnie; Fouts, Susan

2017-01-01

The emergency department (ED) can be a critical intervention point for many patients with multifaceted needs. Social workers have long been part of interdisciplinary ED teams. This study aimed to contribute to the limited understanding of social worker-patient interactions and factors influencing social work services in this setting. This paper reports a qualitative content analysis of social work medical record notes (N=1,509) of services provided to trauma patients in an urban, public, level 1 trauma center and an in-depth analysis of semi-structured interviews with ED social workers (N=10). Eight major social work roles were identified: investigator, gatekeeper, resource broker, care coordinator, problem solver, crisis manager, advocate, discharge planner. Analyses revealed a complex interplay between ED social work services and multi-layered contexts. Using a social-ecological framework, we identified the interactions between micro or individual level factors, mezzo or local system level factors and macro environmental and systemic factors that play a role in ED interactions and patient services. Macro-level contextual influences were socio-structural forces including socioeconomic barriers to health, social hierarchies that reflected power differentials between providers and patients, and distrust or bias. Mezzo-level forces were limited resources, lack of healthcare system coordination, a challenging hierarchy within the medical model and the pressure to discharge patients quickly. Micro-level factors included characteristics of patients and social workers, complexity of patient stressors, empathic strain, lack of closure and compassion. All of these forces were at play in patient-social worker interactions and impacted service provision. Social workers were at times able to successfully navigate these forces, yet at other times these challenges were insurmountable. A conceptual model of ED social work and the influences on the patient-social worker interactions was developed to assist in guiding innovative research and practice models to improve services and outcomes in the complex, fast-paced ED. PMID:28214722
Computational Aerodynamic Modeling of Small Quadcopter Vehicles

NASA Technical Reports Server (NTRS)

Yoon, Seokkwan; Ventura Diaz, Patricia; Boyd, D. Douglas; Chan, William M.; Theodore, Colin R.

2017-01-01

High-fidelity computational simulations have been performed which focus on rotor-fuselage and rotor-rotor aerodynamic interactions of small quad-rotor vehicle systems. The three-dimensional unsteady Navier-Stokes equations are solved on overset grids using high-order accurate schemes, dual-time stepping, low Mach number preconditioning, and hybrid turbulence modeling. Computational results for isolated rotors are shown to compare well with available experimental data. Computational results in hover reveal the differences between a conventional configuration where the rotors are mounted above the fuselage and an unconventional configuration where the rotors are mounted below the fuselage. Complex flow physics in forward flight is investigated. The goal of this work is to demonstrate that understanding of interactional aerodynamics can be an important factor in design decisions regarding rotor and fuselage placement for next-generation multi-rotor drones.
Distinct self-interaction domains promote Multi Sex Combs accumulation in and formation of the Drosophila histone locus body.

PubMed

Terzo, Esteban A; Lyons, Shawn M; Poulton, John S; Temple, Brenda R S; Marzluff, William F; Duronio, Robert J

2015-04-15

Nuclear bodies (NBs) are structures that concentrate proteins, RNAs, and ribonucleoproteins that perform functions essential to gene expression. How NBs assemble is not well understood. We studied the Drosophila histone locus body (HLB), a NB that concentrates factors required for histone mRNA biosynthesis at the replication-dependent histone gene locus. We coupled biochemical analysis with confocal imaging of both fixed and live tissues to demonstrate that the Drosophila Multi Sex Combs (Mxc) protein contains multiple domains necessary for HLB assembly. An important feature of this assembly process is the self-interaction of Mxc via two conserved N-terminal domains: a LisH domain and a novel self-interaction facilitator (SIF) domain immediately downstream of the LisH domain. Molecular modeling suggests that the LisH and SIF domains directly interact, and mutation of either the LisH or the SIF domain severely impairs Mxc function in vivo, resulting in reduced histone mRNA accumulation. A region of Mxc between amino acids 721 and 1481 is also necessary for HLB assembly independent of the LisH and SIF domains. Finally, the C-terminal 195 amino acids of Mxc are required for recruiting FLASH, an essential histone mRNA-processing factor, to the HLB. We conclude that multiple domains of the Mxc protein promote HLB assembly in order to concentrate factors required for histone mRNA biosynthesis. © 2015 Terzo et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Bimanual Interaction with Interscopic Multi-Touch Surfaces

NASA Astrophysics Data System (ADS)

Schöning, Johannes; Steinicke, Frank; Krüger, Antonio; Hinrichs, Klaus; Valkov, Dimitar

Multi-touch interaction has received considerable attention in the last few years, in particular for natural two-dimensional (2D) interaction. However, many application areas deal with three-dimensional (3D) data and require intuitive 3D interaction techniques therefore. Indeed, virtual reality (VR) systems provide sophisticated 3D user interface, but then lack efficient 2D interaction, and are therefore rarely adopted by ordinary users or even by experts. Since multi-touch interfaces represent a good trade-off between intuitive, constrained interaction on a touch surface providing tangible feedback, and unrestricted natural interaction without any instrumentation, they have the potential to form the foundation of the next generation user interface for 2D as well as 3D interaction. In particular, stereoscopic display of 3D data provides an additional depth cue, but until now the challenges and limitations for multi-touch interaction in this context have not been considered. In this paper we present new multi-touch paradigms and interactions that combine both traditional 2D interaction and novel 3D interaction on a touch surface to form a new class of multi-touch systems, which we refer to as interscopic multi-touch surfaces (iMUTS). We discuss iMUTS-based user interfaces that support interaction with 2D content displayed in monoscopic mode and 3D content usually displayed stereoscopically. In order to underline the potential of the proposed iMUTS setup, we have developed and evaluated two example interaction metaphors for different domains. First, we present intuitive navigation techniques for virtual 3D city models, and then we describe a natural metaphor for deforming volumetric datasets in a medical context.
The cosmology of interacting spin-2 fields

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

Tamanini, Nicola; Saridakis, Emmanuel N.; Koivisto, Tomi S., E-mail: n.tamanini.11@ucl.ac.uk, E-mail: Emmanuel_Saridakis@baylor.edu, E-mail: t.s.koivisto@astro.uio.no

2014-02-01

We investigate the cosmology of interacting spin-2 particles, formulating the multi-gravitational theory in terms of vierbeins and without imposing any Deser-van Nieuwen-huizen-like constraint. The resulting multi-vierbein theory represents a wider class of gravitational theories if compared to the corresponding multi-metric models. Moreover, as opposed to its metric counterpart which in general seems to contain ghosts, it has already been proved to be ghost-free. We outline a discussion about the possible matter couplings and we focus on the study of cosmological scenarios in the case of three and four interacting vierbeins. We find rich behavior, including de Sitter solutions with anmore » effective cosmological constant arising from the multi-vierbein interaction, dark-energy solutions and nonsingular bouncing behavior.« less
A penny-shaped crack in a filament reinforced matrix. 1: The filament model

NASA Technical Reports Server (NTRS)

Erdogan, F.; Pacella, A. H.

1973-01-01

The electrostatic problem of a penny-shaped crack in an elastic matrix which reinforced by filaments or fibers perpendicular to the plane of the crack was studied. The elastic filament model was developed for application to evaluation studies of the stress intensity factor along the periphery of the crack, the stresses in the filaments or fibers, and the interface shear between the matrix and the filaments or fibers. The requirements expected of the model are a sufficiently accurate representation of the filament and applicability to the interaction problems involving a cracked elastic continuum with multi-filament reinforcements. The technique for developing the model and numerical examples of it are shown.
Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

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

2010-01-01

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.
Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

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

NASA Astrophysics Data System (ADS)

Yang, R.-J.; Lin, S.-J.

1991-01-01

The Rai method of single-stage rotor/stator flow interaction is extended to handle multistage configurations. In this study, a two-dimensional Navier-Stokes multi-zone approach was used to investigate unsteady flow interactions within two multistage axial turbines. The governing equations are solved by an iterative, factored, implicit finite-difference, upwind algorithm. Numerical accuracy is checked by investigating the effect of time step size, the effect of subiteration in the Newton-Raphson technique, and the effect of full viscous versus thin-layer approximation. Computer results compared well with experimental data. Unsteady flow interactions, wake cutting, and the associated evolution of vortical entities are discussed.
A System for Modelling Cell–Cell Interactions during Plant Morphogenesis

PubMed Central

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

2008-01-01

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

NASA Technical Reports Server (NTRS)

Shi, J.; Chen, K. S.; Kim, Chung-Li Y.; Van Zyl, J. J.; Njoku, E.; Sun, G.; O'Neill, P.; Jackson, T.; Entekhabi, D.

2004-01-01

Through analyses of the model simulated data-base, we developed a technique to estimate surface soil moisture under HYDROS radar sensor (L-band multi-polarizations and 40deg incidence) configuration. This technique includes two steps. First, it decomposes the total backscattering signals into two components - the surface scattering components (the bare surface backscattering signals attenuated by the overlaying vegetation layer) and the sum of the direct volume scattering components and surface-volume interaction components at different polarizations. From the model simulated data-base, our decomposition technique works quit well in estimation of the surface scattering components with RMSEs of 0.12,0.25, and 0.55 dB for VV, HH, and VH polarizations, respectively. Then, we use the decomposed surface backscattering signals to estimate the soil moisture and the combined surface roughness and vegetation attenuation correction factors with all three polarizations.
Modeling activity recognition of multi resident using label combination of multi label classification in smart home

NASA Astrophysics Data System (ADS)

Mohamed, Raihani; Perumal, Thinagaran; Sulaiman, Md Nasir; Mustapha, Norwati; Zainudin, M. N. Shah

2017-10-01

Pertaining to the human centric concern and non-obtrusive way, the ambient sensor type technology has been selected, accepted and embedded in the environment in resilient style. Human activities, everyday are gradually becoming complex and thus complicate the inferences of activities when it involving the multi resident in the same smart environment. Current works solutions focus on separate model between the resident, activities and interactions. Some study use data association and extra auxiliary of graphical nodes to model human tracking information in an environment and some produce separate framework to incorporate the auxiliary for interaction feature model. Thus, recognizing the activities and which resident perform the activity at the same time in the smart home are vital for the smart home development and future applications. This paper will cater the above issue by considering the simplification and efficient method using the multi label classification framework. This effort eliminates time consuming and simplifies a lot of pre-processing tasks comparing with previous approach. Applications to the multi resident multi label learning in smart home problems shows the LC (Label Combination) using Decision Tree (DT) as base classifier can tackle the above problems.
Utilization of a Multi-Disciplinary Approach to Building Effective Command Centers: Process and Products

DTIC Science & Technology

2005-06-01

cognitive task analysis , organizational information dissemination and interaction, systems engineering, collaboration and communications processes, decision-making processes, and data collection and organization. By blending these diverse disciplines command centers can be designed to support decision-making, cognitive analysis, information technology, and the human factors engineering aspects of Command and Control (C2). This model can then be used as a baseline when dealing with work in areas of business processes, workflow engineering, information management,
The framework of a UAS-aided flash flood modeling system for coastal regions

NASA Astrophysics Data System (ADS)

Zhang, H.; Xu, H.

2016-02-01

Flash floods cause severe economic damage and are one of the leading causes of fatalities connected with natural disasters in the Gulf Coast region. Current flash flood modeling systems rely on empirical hydrological models driven by precipitation estimates only. Although precipitation is the driving factor for flash floods, soil moisture, urban drainage system and impervious surface have been recognized to have significant impacts on the development of flash floods. We propose a new flash flooding modeling system that integrates 3-D hydrological simulation with satellite and multi-UAS observations. It will have three advantages over existing modeling systems. First, it will incorporate 1-km soil moisture data through integrating satellite images from European SMOS mission and NASA's SMAP mission. The utilization of high-resolution satellite images will provide essential information to determine antecedent soil moisture condition, which is an essential control on flood generation. Second, this system is able to adjust flood forecasting based on real-time inundation information collected by multi-UAS. A group of UAS will be deployed during storm events to capture the changing extent of flooded areas and water depth at multiple critical locations simultaneously. Such information will be transmitted to a hydrological model to validate and improve flood simulation. Third, the backbone of this system is a state-of-the-art 3-D hydrological model that assimilates the hydrological information from satellites and multi-UAS. The model is able to address surface water-groundwater interactions and reflect the effects of various infrastructures. Using Web-GIS technologies, the modeling results will be available online as interactive flood maps accessible to the public. To support the development and verification of this modeling system, surface and subsurface hydrological observations will be conducted in a number of small watersheds in the Coastal Bend region. We envision this system will provide an innovative means to benefit the forecasting, evaluation and mitigation of flash floods in costal regions.
A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities across Categories

ERIC Educational Resources Information Center

Duvvuri, Sri Devi; Gruca, Thomas S.

2010-01-01

Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…
Users matter : multi-agent systems model of high performance computing cluster users.

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

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less
Orientation of airborne laser scanning point clouds with multi-view, multi-scale image blocks.

PubMed

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters.
Orientation of Airborne Laser Scanning Point Clouds with Multi-View, Multi-Scale Image Blocks

PubMed Central

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters. PMID:22454569
A multi-band, multi-level, multi-electron model for efficient FDTD simulations of electromagnetic interactions with semiconductor quantum wells

NASA Astrophysics Data System (ADS)

Ravi, Koustuban; Wang, Qian; Ho, Seng-Tiong

2015-08-01

We report a new computational model for simulations of electromagnetic interactions with semiconductor quantum well(s) (SQW) in complex electromagnetic geometries using the finite-difference time-domain method. The presented model is based on an approach of spanning a large number of electron transverse momentum states in each SQW sub-band (multi-band) with a small number of discrete multi-electron states (multi-level, multi-electron). This enables accurate and efficient two-dimensional (2-D) and three-dimensional (3-D) simulations of nanophotonic devices with SQW active media. The model includes the following features: (1) Optically induced interband transitions between various SQW conduction and heavy-hole or light-hole sub-bands are considered. (2) Novel intra sub-band and inter sub-band transition terms are derived to thermalize the electron and hole occupational distributions to the correct Fermi-Dirac distributions. (3) The terms in (2) result in an explicit update scheme which circumvents numerically cumbersome iterative procedures. This significantly augments computational efficiency. (4) Explicit update terms to account for carrier leakage to unconfined states are derived, which thermalize the bulk and SQW populations to a common quasi-equilibrium Fermi-Dirac distribution. (5) Auger recombination and intervalence band absorption are included. The model is validated by comparisons to analytic band-filling calculations, simulations of SQW optical gain spectra, and photonic crystal lasers.

Co-transcriptional nuclear actin dynamics

PubMed Central

Percipalle, Piergiorgio

2013-01-01

Actin is a key player for nuclear structure and function regulating both chromosome organization and gene activity. In the cell nucleus actin interacts with many different proteins. Among these proteins several studies have identified classical nuclear factors involved in chromatin structure and function, transcription and RNA processing as well as proteins that are normally involved in controlling the actin cytoskeleton. These discoveries have raised the possibility that nuclear actin performs its multi task activities through tight interactions with different sets of proteins. This high degree of promiscuity in the spectrum of protein-to-protein interactions correlates well with the conformational plasticity of actin and the ability to undergo regulated changes in its polymerization states. Several of the factors involved in controlling head-to-tail actin polymerization have been shown to be in the nucleus where they seem to regulate gene activity. By focusing on the multiple tasks performed by actin and actin-binding proteins, possible models of how actin dynamics controls the different phases of the RNA polymerase II transcription cycle are being identified. PMID:23138849
Simulations of Turbulent Flows with Strong Shocks and Density Variations: Final Report

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

Sanjiva Lele

2012-10-01

The target of this SciDAC Science Application was to develop a new capability based on high-order and high-resolution schemes to simulate shock-turbulence interactions and multi-material mixing in planar and spherical geometries, and to study Rayleigh-Taylor and Richtmyer-Meshkov turbulent mixing. These fundamental problems have direct application in high-speed engineering flows, such as inertial confinement fusion (ICF) capsule implosions and scramjet combustion, and also in the natural occurrence of supernovae explosions. Another component of this project was the development of subgrid-scale (SGS) models for large-eddy simulations of flows involving shock-turbulence interaction and multi-material mixing, that were to be validated with the DNSmore » databases generated during the program. The numerical codes developed are designed for massively-parallel computer architectures, ensuring good scaling performance. Their algorithms were validated by means of a sequence of benchmark problems. The original multi-stage plan for this five-year project included the following milestones: 1) refinement of numerical algorithms for application to the shock-turbulence interaction problem and multi-material mixing (years 1-2); 2) direct numerical simulations (DNS) of canonical shock-turbulence interaction (years 2-3), targeted at improving our understanding of the physics behind the combined two phenomena and also at guiding the development of SGS models; 3) large-eddy simulations (LES) of shock-turbulence interaction (years 3-5), improving SGS models based on the DNS obtained in the previous phase; 4) DNS of planar/spherical RM multi-material mixing (years 3-5), also with the two-fold objective of gaining insight into the relevant physics of this instability and aiding in devising new modeling strategies for multi-material mixing; 5) LES of planar/spherical RM mixing (years 4-5), integrating the improved SGS and multi-material models developed in stages 3 and 5. This final report is outlined as follows. Section 2 shows an assessment of numerical algorithms that are best suited for the numerical simulation of compressible flows involving turbulence and shock phenomena. Sections 3 and 4 deal with the canonical shock-turbulence interaction problem, from the DNS and LES perspectives, respectively. Section 5 considers the shock-turbulence inter-action in spherical geometry, in particular, the interaction of a converging shock with isotropic turbulence as well as the problem of the blast wave. Section 6 describes the study of shock-accelerated mixing through planar and spherical Richtmyer-Meshkov mixing as well as the shock-curtain interaction problem In section 7 we acknowledge the different interactions between Stanford and other institutions participating in this SciDAC project, as well as several external collaborations made possible through it. Section 8 presents a list of publications and presentations that have been generated during the course of this SciDAC project. Finally, section 9 concludes this report with the list of personnel at Stanford University funded by this SciDAC project.« less
Emergent Stratification in Solid Tumors Selects for Reduced Cohesion of Tumor Cells: A Multi-Cell, Virtual-Tissue Model of Tumor Evolution Using CompuCell3D.

PubMed

Swat, Maciej H; Thomas, Gilberto L; Shirinifard, Abbas; Clendenon, Sherry G; Glazier, James A

2015-01-01

Tumor cells and structure both evolve due to heritable variation of cell behaviors and selection over periods of weeks to years (somatic evolution). Micro-environmental factors exert selection pressures on tumor-cell behaviors, which influence both the rate and direction of evolution of specific behaviors, especially the development of tumor-cell aggression and resistance to chemotherapies. In this paper, we present, step-by-step, the development of a multi-cell, virtual-tissue model of tumor somatic evolution, simulated using the open-source CompuCell3D modeling environment. Our model includes essential cell behaviors, microenvironmental components and their interactions. Our model provides a platform for exploring selection pressures leading to the evolution of tumor-cell aggression, showing that emergent stratification into regions with different cell survival rates drives the evolution of less cohesive cells with lower levels of cadherins and higher levels of integrins. Such reduced cohesivity is a key hallmark in the progression of many types of solid tumors.
Emergent Stratification in Solid Tumors Selects for Reduced Cohesion of Tumor Cells: A Multi-Cell, Virtual-Tissue Model of Tumor Evolution Using CompuCell3D

PubMed Central

Swat, Maciej H.; Thomas, Gilberto L.; Shirinifard, Abbas; Clendenon, Sherry G.; Glazier, James A.

2015-01-01

Tumor cells and structure both evolve due to heritable variation of cell behaviors and selection over periods of weeks to years (somatic evolution). Micro-environmental factors exert selection pressures on tumor-cell behaviors, which influence both the rate and direction of evolution of specific behaviors, especially the development of tumor-cell aggression and resistance to chemotherapies. In this paper, we present, step-by-step, the development of a multi-cell, virtual-tissue model of tumor somatic evolution, simulated using the open-source CompuCell3D modeling environment. Our model includes essential cell behaviors, microenvironmental components and their interactions. Our model provides a platform for exploring selection pressures leading to the evolution of tumor-cell aggression, showing that emergent stratification into regions with different cell survival rates drives the evolution of less cohesive cells with lower levels of cadherins and higher levels of integrins. Such reduced cohesivity is a key hallmark in the progression of many types of solid tumors. PMID:26083246
IMPETUS - Interactive MultiPhysics Environment for Unified Simulations.

PubMed

Ha, Vi Q; Lykotrafitis, George

2016-12-08

We introduce IMPETUS - Interactive MultiPhysics Environment for Unified Simulations, an object oriented, easy-to-use, high performance, C++ program for three-dimensional simulations of complex physical systems that can benefit a large variety of research areas, especially in cell mechanics. The program implements cross-communication between locally interacting particles and continuum models residing in the same physical space while a network facilitates long-range particle interactions. Message Passing Interface is used for inter-processor communication for all simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.
Comparison of analytical models for zonal flow generation in ion-temperature-gradient mode turbulence

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

Anderson, J.; Miki, K.; Uzawa, K.

2006-11-30

During the past years the understanding of the multi scale interaction problems have increased significantly. However, at present there exists a flora of different analytical models for investigating multi scale interactions and hardly any specific comparisons have been performed among these models. In this work two different models for the generation of zonal flows from ion-temperature-gradient (ITG) background turbulence are discussed and compared. The methods used are the coherent mode coupling model and the wave kinetic equation model (WKE). It is shown that the two models give qualitatively the same results even though the assumption on the spectral difference ismore » used in the (WKE) approach.« less
Patterns of Risk Using an Integrated Spatial Multi-Hazard Model (PRISM Model)

EPA Science Inventory

Multi-hazard risk assessment has long centered on small scale needs, whereby a single community or group of communities’ exposures are assessed to determine potential mitigation strategies. While this approach has advanced the understanding of hazard interactions, it is li...
Modeling and Evaluating Emotions Impact on Cognition

DTIC Science & Technology

2013-07-01

Causality and Responsibility Judgment in Multi-Agent Interactions: Extended abstract. 23rd International Joint Conference on Artificial Inteligence ...responsibility judgment in multi-agent interactions." Journal of Artificial Intelligence Research v44(1), 223- 273. • Morteza Dehghani, Jonathan Gratch... Artificial Intelligence (AAAI’11). Grant related invited talks: • Keynote speaker, Workshop on Empathic and Emotional Agents at the International
Effect of Turbulent Fluctuations on Infrared Radiation from a Tactical Missile Plume

DTIC Science & Technology

1982-02-01

Reacting Flows ...... 21 Reacting Flow Calculations ..................................... 21 Turbulence- Chemistry Interaction...a two-equation, turbulence kinetic energy model. The code is capable of handling multi-species, multi-step chemistry . However, it does not calculate...that are expected to be important in turbulence- chemistry and turbulence-radiation interactions. The program calculates only two turbulence guantities
Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

PubMed Central

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

2016-01-01

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

PubMed

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

2017-01-05

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

PubMed

Panić, Sanja; Rakić, Dušan; Guzsvány, Valéria; Kiss, Erne; Boskovic, Goran; Kónya, Zoltán; Kukovecz, Ákos

2015-12-01

The aim of this work was to evaluate significant factors affecting the thiamethoxam adsorption efficiency using oxidized multi-walled carbon nanotubes (MWCNTs) as adsorbents. Five factors (initial solution concentration of thiamethoxam in water, temperature, solution pH, MWCNTs weight and contact time) were investigated using 2V(5-1) fractional factorial design. The obtained linear model was statistically tested using analysis of variance (ANOVA) and the analysis of residuals was used to investigate the model validity. It was observed that the factors and their second-order interactions affecting the thiamethoxam removal can be divided into three groups: very important, moderately important and insignificant ones. The initial solution concentration was found to be the most influencing parameter on thiamethoxam adsorption from water. Optimization of the factors levels was carried out by minimizing those parameters which are usually critical in real life: the temperature (energy), contact time (money) and weight of MWCNTs (potential health hazard), in order to maximize the adsorbed amount of the pollutant. The results of maximal adsorbed thiamethoxam amount in both real and optimized experiments indicate that among minimized parameters the adsorption time is one that makes the largest difference. The results of this study indicate that fractional factorial design is very useful tool for screening the higher number of parameters and reducing the number of adsorption experiments. Copyright © 2015 Elsevier Ltd. All rights reserved.
Multi-symptom illnesses, unexplained illness and Gulf War Syndrome

PubMed Central

Ismail, Khalida; Lewis, Glyn

2006-01-01

Explanatory models for the increased prevalence of ill health in Gulf veterans compared to those not deployed to the Gulf War 1990–1991 remain elusive. This article addresses whether multi-symptom reporting in Gulf veterans are types of medically unexplained symptoms and whether the alleged Gulf War Syndrome is best understood as a medically unexplained syndrome. A review of the epidemiological studies, overwhelmingly cross-sectional, describing ill health was conducted including those that used factor analysis to search for underlying or latent clinical constructs. The overwhelming evidence was that symptoms in Gulf veterans were either in keeping with currently defined psychiatric disorders such as depression and anxiety or were medically unexplained. The application of factor analysis methods had varied widely with a risk of over interpretation in some studies and limiting the validity of their findings. We concluded that ill health in Gulf veterans and the alleged Gulf War Syndrome is best understood within the medically unexplained symptoms and syndromes constructs. The cause of increased reporting in Gulf veterans are still not clear and requires further inquiry into the interaction between sociological factors and symptomatic distress. PMID:16687260
Seeking a Multi-Construct Model of Morality

ERIC Educational Resources Information Center

McDaniel, Brenda L.; Grice, James W.; Eason, E. Allen

2010-01-01

The present study explored a multi-construct model of moral development. Variables commonly seen in the moral development literature, such as family interactions, spiritual life, ascription to various sources of moral authority, empathy, shame, guilt and moral judgement competence, were investigated. Results from the current study support previous…
Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

PubMed

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.
Structural modelling and molecular dynamics of a multi-stress responsive WRKY TF-DNA complex towards elucidating its role in stress signalling mechanisms in chickpea.

PubMed

Konda, Aravind Kumar; Farmer, Rohit; Soren, Khela Ram; P S, Shanmugavadivel; Setti, Aravind

2017-07-28

Chickpea is a premier food legume crop with high nutritional quality and attains prime importance in the current era of 795 million people being undernourished worldwide. Chickpea production encounters setbacks due to various stresses and understanding the role of key transcription factors (TFs) involved in multiple stresses becomes inevitable. We have recently identified a multi-stress responsive WRKY TF in chickpea. The present study was conducted to predict the structure of WRKY TF to identify the DNA-interacting residues and decipher DNA-protein interactions. Comparative modelling approach produced 3D model of the WRKY TF with good stereochemistry, local/global quality and further revealed W19, R20, K21, and Y22 motifs within a vicinity of 5 Å to the DNA amongst R18, G23, Q24, K25, Y36, Y37, R38 and K47 and these positions were equivalent to the 2LEX WRKY domain of Arabidopsis. Molecular simulations analysis of reference protein -PDB ID 2LEX, along with Car-WRKY TF modelled structure with the DNA coordinates derived from PDB ID 2LEX and docked using HADDOCK were executed. Root Mean Square (RMS) Deviation and RMS Fluctuation values yielded consistently stable trajectories over 50 ns simulation. Strengthening the obtained results, neither radius of gyration, distance and total energy showed any signs of DNA-WRKY complex falling apart nor any significant dissociation event over 50 ns run. Therefore, the study provides first insights into the structural properties of multi-stress responsive WRKY TF-DNA complex in chickpea, enabling genome wide identification of TF binding sites and thereby deciphers their gene regulatory networks.
The design of a multi-harmonic step-tunable gyrotron

NASA Astrophysics Data System (ADS)

Qi, Xiang-Bo; Du, Chao-Hai; Zhu, Juan-Feng; Pan, Shi; Liu, Pu-Kun

2017-03-01

The theoretical study of a step-tunable gyrotron controlled by successive excitation of multi-harmonic modes is presented in this paper. An axis-encircling electron beam is employed to eliminate the harmonic mode competition. Physics images are depicted to elaborate the multi-harmonic interaction mechanism in determining the operating parameters at which arbitrary harmonic tuning can be realized by magnetic field sweeping to achieve controlled multiband frequencies' radiation. An important principle is revealed that a weak coupling coefficient under a high-harmonic interaction can be compensated by a high Q-factor. To some extent, the complementation between the high Q-factor and weak coupling coefficient makes the high-harmonic mode potential to achieve high efficiency. Based on a previous optimized magnetic cusp gun, the multi-harmonic step-tunable gyrotron is feasible by using harmonic tuning of first-to-fourth harmonic modes. Multimode simulation shows that the multi-harmonic gyrotron can operate on the 34 GHz first-harmonic TE11 mode, 54 GHz second-harmonic TE21 mode, 74 GHz third-harmonic TE31 mode, and 94 GHz fourth-harmonic TE41 mode, corresponding to peak efficiencies of 28.6%, 35.7%, 17.1%, and 11.4%, respectively. The multi-harmonic step-tunable gyrotron provides new possibilities in millimeter-terahertz source development especially for advanced terahertz applications.
Multi-agent simulation of the von Thunen model formation mechanism

NASA Astrophysics Data System (ADS)

Tao, Haiyan; Li, Xia; Chen, Xiaoxiang; Deng, Chengbin

2008-10-01

This research tries to explain the internal driving forces of circular structure formation in urban geography via the simulation of interaction between individual behavior and market. On the premise of single city center, unchanged scale merit and complete competition, enterprise migration theory as well, an R-D algorithm, that has agents searched the best behavior rules in some given locations, is introduced with agent-based modeling technique. The experiment conducts a simulation on Swarm platform, whose result reflects and replays the formation process of Von Thünen circular structure. Introducing and considering some heterogeneous factors, such as traffic roads, the research verifies several landuse models and discusses the self-adjustment function of price mechanism.
Understanding Interactions between Hydrogeologic Factors, Design Variables, and System Operations for Multi-Well Aquifer Storage and Recovery Systems

NASA Astrophysics Data System (ADS)

Majumdar, S.; Miller, G. R.; Smith, B.; Sheng, Z.

2017-12-01

Aquifer Storage and Recovery (ASR) system is a powerful tool for managing our present and future freshwater supplies. It involves injection of excess water into an aquifer, storing and later recovering it when needed, such as in a drought or during peak demand periods. Multi-well ASR systems, such as the Twin Oaks Facility in San Antonio, consist of a group of wells that are used for simultaneous injection and extraction of stored water. While significant research has gone into examining the effects of hydraulic and operational factors on recovery efficiency for single ASR well, little is known about how multi-well systems respond to these factors and how energy uses may vary. In this study, we created a synthetic ASR model in MODFLOW to test a range of multi-well scenarios. We altered design parameters (well spacing, pumping capacity, well configuration), hydrogeologic factors (regional hydraulic gradient, hydraulic conductivity, dispersivity), and operational variables (injection and withdrawal durations; pumping rates) to determine the response of the system across a realistic range of interrelated parameters. We then computed energy use for each simulation, based on the hydraulic head in each well and standard pump factors, as well as recovery efficiency, based on tracer concentration in recovered water from the wells. The tracer concentration in the groundwater was determined using MT3DMS. We observed that the recovery and energy efficiencies for the Multi-well ASR system decrease with the increase in well spacing and hydraulic gradient. When longitudinal dispersivity was doubled, the recovery and energy efficiencies were nearly halved. Another finding from our study suggests that we can recover nearly 90% of the water after two successive cycles of operation. The results will be used to develop generalized operational guidelines for meeting freshwater demands and also optimise the energy consumed during pumping.
Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data

NASA Astrophysics Data System (ADS)

Shi, Guoliang; Peng, Xing; Huangfu, Yanqi; Wang, Wei; Xu, Jiao; Tian, Yingze; Feng, Yinchang; Ivey, Cesunica E.; Russell, Armistead G.

2017-07-01

Source apportionment technologies are used to understand the impacts of important sources of particulate matter (PM) air quality, and are widely used for both scientific studies and air quality management. Generally, receptor models apportion speciated PM data from a single sampling site. With the development of large scale monitoring networks, PM speciation are observed at multiple sites in an urban area. For these situations, the models should account for three factors, or dimensions, of the PM, including the chemical species concentrations, sampling periods and sampling site information, suggesting the potential power of a three-dimensional source apportionment approach. However, the principle of three-dimensional Parallel Factor Analysis (Ordinary PARAFAC) model does not always work well in real environmental situations for multi-site receptor datasets. In this work, a new three-way receptor model, called "multi-site three way factor analysis" model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between estimated and true contributions) for extracted sources were all less than 50%. Additionally, three-dimensional ambient datasets from a Chinese mega-city, Chengdu, were analyzed using this new model to assess the application. Four factors are extracted by the multi-site WFA3 model: secondary source have the highest contributions (64.73 and 56.24 μg/m3), followed by vehicular exhaust (30.13 and 33.60 μg/m3), crustal dust (26.12 and 29.99 μg/m3) and coal combustion (10.73 and 14.83 μg/m3). The model was also compared to PMF, with general agreement, though PMF suggested a lower crustal contribution.

Genome-wide assessment of gene-by-smoking interactions in COPD.

PubMed

Park, Boram; Koo, So-My; An, Jaehoon; Lee, MoonGyu; Kang, Hae Yeon; Qiao, Dandi; Cho, Michael H; Sung, Joohon; Silverman, Edwin K; Yang, Hyeon-Jong; Won, Sungho

2018-06-18

Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on lung function using Korea Associated Resource (KARE) data with the spirometric variables-forced expiratory volume in 1 s (FEV 1 ). We found that variations in FEV 1 were different among smoking status. Thus, we considered a linear mixed model for association analysis under heteroscedasticity according to smoking status. We found a previously identified locus near SOX9 on chromosome 17 to be the most significant based on a joint test of the main and interaction effects of smoking. Smoking interactions were replicated with Gene-Environment of Interaction and phenotype (GENIE), Multi-Ethnic Study of Atherosclerosis-Lung (MESA-Lung), and COPDGene studies. We found that individuals with minor alleles, rs17765644, rs17178251, rs11870732, and rs4793541, tended to have lower FEV 1 values, and lung function decreased much faster with age for smokers. There have been very few reports to replicate a common variant gene-smoking interaction, and our results revealed that statistical models for gene-smoking interaction analyses should be carefully selected.
Electrical receptive fields of retinal ganglion cells: Influence of presynaptic neurons

PubMed Central

Apollo, Nicholas V.; Garrett, David J.

2018-01-01

Implantable retinal stimulators activate surviving neurons to restore a sense of vision in people who have lost their photoreceptors through degenerative diseases. Complex spatial and temporal interactions occur in the retina during multi-electrode stimulation. Due to these complexities, most existing implants activate only a few electrodes at a time, limiting the repertoire of available stimulation patterns. Measuring the spatiotemporal interactions between electrodes and retinal cells, and incorporating them into a model may lead to improved stimulation algorithms that exploit the interactions. Here, we present a computational model that accurately predicts both the spatial and temporal nonlinear interactions of multi-electrode stimulation of rat retinal ganglion cells (RGCs). The model was verified using in vitro recordings of ON, OFF, and ON-OFF RGCs in response to subretinal multi-electrode stimulation with biphasic pulses at three stimulation frequencies (10, 20, 30 Hz). The model gives an estimate of each cell’s spatiotemporal electrical receptive fields (ERFs); i.e., the pattern of stimulation leading to excitation or suppression in the neuron. All cells had excitatory ERFs and many also had suppressive sub-regions of their ERFs. We show that the nonlinearities in observed responses arise largely from activation of presynaptic interneurons. When synaptic transmission was blocked, the number of sub-regions of the ERF was reduced, usually to a single excitatory ERF. This suggests that direct cell activation can be modeled accurately by a one-dimensional model with linear interactions between electrodes, whereas indirect stimulation due to summated presynaptic responses is nonlinear. PMID:29432411
Modelling multi-species interactions in the Barents Sea ecosystem with special emphasis on minke whales and their interactions with cod, herring and capelin

NASA Astrophysics Data System (ADS)

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

2009-10-01

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

PubMed

Sallam, Mohamed F; Fizer, Chelsea; Pilant, Andrew N; Whung, Pai-Yei

2017-10-16

Asian tiger and yellow fever mosquitoes ( Aedes albopictus and Ae. aegypti ) are global nuisances and are competent vectors for viruses such as Chikungunya (CHIKV), Dengue (DV), and Zika (ZIKV). This review aims to analyze available spatiotemporal distribution models of Aedes mosquitoes and their influential factors. A combination of five sets of 3-5 keywords were used to retrieve all relevant published models. Five electronic search databases were used: PubMed, MEDLINE, EMBASE, Scopus, and Google Scholar through 17 May 2017. We generated a hierarchical decision tree for article selection. We identified 21 relevant published studies that highlight different combinations of methodologies, models and influential factors. Only a few studies adopted a comprehensive approach highlighting the interaction between environmental, socioeconomic, meteorological and topographic systems. The selected articles showed inconsistent findings in terms of number and type of influential factors affecting the distribution of Aedes vectors, which is most likely attributed to: (i) limited availability of high-resolution data for physical variables, (ii) variation in sampling methods; Aedes feeding and oviposition behavior; (iii) data collinearity and statistical distribution of observed data. This review highlights the need and sets the stage for a rigorous multi-system modeling approach to improve our knowledge about Aedes presence/abundance within their flight range in response to the interaction between environmental, socioeconomic, and meteorological systems.
Fluid-structure interaction with the entropic lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Dorschner, B.; Chikatamarla, S. S.; Karlin, I. V.

2018-02-01

We propose a fluid-structure interaction (FSI) scheme using the entropic multi-relaxation time lattice Boltzmann (KBC) model for the fluid domain in combination with a nonlinear finite element solver for the structural part. We show the validity of the proposed scheme for various challenging setups by comparison to literature data. Beyond validation, we extend the KBC model to multiphase flows and couple it with a finite element method (FEM) solver. Robustness and viability of the entropic multi-relaxation time model for complex FSI applications is shown by simulations of droplet impact on elastic superhydrophobic surfaces.
A Bulk Comptonization Model for the Prompt GRB Emission and its Relation to the Fermi GRB Spectra

NASA Technical Reports Server (NTRS)

Kazanas, Demosthenes

2010-01-01

We present a model in which the GRB prompt emission at E E(sub peak) is due to bulk Comptonization by the relativistic blast wave motion of either its own synchrotron photons of ambient photons of the stellar configuration that gave birth to the GRB. The bulk Comptonization process then induces the production of relativistic electrons of Lorentz factor equal to that of the blast wave through interactions with its ambient protons. The inverse compton emission of these electrons produces a power law component that extends to multi GeV energies in good agreement with the LAT GRB observations.
Emergence of microbial diversity due to cross-feeding interactions in a spatial model of gut microbial metabolism.

PubMed

Hoek, Milan J A van; Merks, Roeland M H

2017-05-16

The human gut contains approximately 10 14 bacteria, belonging to hundreds of different species. Together, these microbial species form a complex food web that can break down nutrient sources that our own digestive enzymes cannot handle, including complex polysaccharides, producing short chain fatty acids and additional metabolites, e.g., vitamin K. Microbial diversity is important for colonic health: Changes in the composition of the microbiota have been associated with inflammatory bowel disease, diabetes, obesity and Crohn's disease, and make the microbiota more vulnerable to infestation by harmful species, e.g., Clostridium difficile. To get a grip on the controlling factors of microbial diversity in the gut, we here propose a multi-scale, spatiotemporal dynamic flux-balance analysis model to study the emergence of metabolic diversity in a spatial gut-like, tubular environment. The model features genome-scale metabolic models (GEM) of microbial populations, resource sharing via extracellular metabolites, and spatial population dynamics and evolution. In this model, cross-feeding interactions emerge readily, despite the species' ability to metabolize sugars autonomously. Interestingly, the community requires cross-feeding for producing a realistic set of short-chain fatty acids from an input of glucose, If we let the composition of the microbial subpopulations change during invasion of adjacent space, a complex and stratified microbiota evolves, with subspecies specializing on cross-feeding interactions via a mechanism of compensated trait loss. The microbial diversity and stratification collapse if the flux through the gut is enhanced to mimic diarrhea. In conclusion, this in silico model is a helpful tool in systems biology to predict and explain the controlling factors of microbial diversity in the gut. It can be extended to include, e.g., complex nutrient sources, and host-microbiota interactions via the intestinal wall.
Application of Intel Many Integrated Core (MIC) architecture to the Yonsei University planetary boundary layer scheme in Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Huang, Melin; Huang, Bormin; Huang, Allen H.

2014-10-01

The Weather Research and Forecasting (WRF) model provided operational services worldwide in many areas and has linked to our daily activity, in particular during severe weather events. The scheme of Yonsei University (YSU) is one of planetary boundary layer (PBL) models in WRF. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transports in the whole atmospheric column, determines the flux profiles within the well-mixed boundary layer and the stable layer, and thus provide atmospheric tendencies of temperature, moisture (including clouds), and horizontal momentum in the entire atmospheric column. The YSU scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. To accelerate the computation process of the YSU scheme, we employ Intel Many Integrated Core (MIC) Architecture as it is a multiprocessor computer structure with merits of efficient parallelization and vectorization essentials. Our results show that the MIC-based optimization improved the performance of the first version of multi-threaded code on Xeon Phi 5110P by a factor of 2.4x. Furthermore, the same CPU-based optimizations improved the performance on Intel Xeon E5-2603 by a factor of 1.6x as compared to the first version of multi-threaded code.
Capturing remote mixing due to internal tides using multi-scale modeling tool: SOMAR-LES

NASA Astrophysics Data System (ADS)

Santilli, Edward; Chalamalla, Vamsi; Scotti, Alberto; Sarkar, Sutanu

2016-11-01

Internal tides that are generated during the interaction of an oscillating barotropic tide with the bottom bathymetry dissipate only a fraction of their energy near the generation region. The rest is radiated away in the form of low- high-mode internal tides. These internal tides dissipate energy at remote locations when they interact with the upper ocean pycnocline, continental slope, and large scale eddies. Capturing the wide range of length and time scales involved during the life-cycle of internal tides is computationally very expensive. A recently developed multi-scale modeling tool called SOMAR-LES combines the adaptive grid refinement features of SOMAR with the turbulence modeling features of a Large Eddy Simulation (LES) to capture multi-scale processes at a reduced computational cost. Numerical simulations of internal tide generation at idealized bottom bathymetries are performed to demonstrate this multi-scale modeling technique. Although each of the remote mixing phenomena have been considered independently in previous studies, this work aims to capture remote mixing processes during the life cycle of an internal tide in more realistic settings, by allowing multi-level (coarse and fine) grids to co-exist and exchange information during the time stepping process.
Quantifying the abnormal hemodynamics of sickle cell anemia

NASA Astrophysics Data System (ADS)

Lei, Huan; Karniadakis, George

2012-02-01

Sickle red blood cells (SS-RBC) exhibit heterogeneous morphologies and abnormal hemodynamics in deoxygenated states. A multi-scale model for SS-RBC is developed based on the Dissipative Particle Dynamics (DPD) method. Different cell morphologies (sickle, granular, elongated shapes) typically observed in deoxygenated states are constructed and quantified by the Asphericity and Elliptical shape factors. The hemodynamics of SS-RBC suspensions is studied in both shear and pipe flow systems. The flow resistance obtained from both systems exhibits a larger value than the healthy blood flow due to the abnormal cell properties. Moreover, SS-RBCs exhibit abnormal adhesive interactions with both the vessel endothelium cells and the leukocytes. The effect of the abnormal adhesive interactions on the hemodynamics of sickle blood is investigated using the current model. It is found that both the SS-RBC - endothelium and the SS-RBC - leukocytes interactions, can potentially trigger the vicious ``sickling and entrapment'' cycles, resulting in vaso-occlusion phenomena widely observed in micro-circulation experiments.
Smart Grid as Multi-layer Interacting System for Complex Decision Makings

NASA Astrophysics Data System (ADS)

Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico

This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.
Risk analysis based on hazards interactions

NASA Astrophysics Data System (ADS)

Rossi, Lauro; Rudari, Roberto; Trasforini, Eva; De Angeli, Silvia; Becker, Joost

2017-04-01

Despite an increasing need for open, transparent, and credible multi-hazard risk assessment methods, models, and tools, the availability of comprehensive risk information needed to inform disaster risk reduction is limited, and the level of interaction across hazards is not systematically analysed. Risk assessment methodologies for different hazards often produce risk metrics that are not comparable. Hazard interactions (consecutive occurrence two or more different events) are generally neglected, resulting in strongly underestimated risk assessment in the most exposed areas. This study presents cases of interaction between different hazards, showing how subsidence can affect coastal and river flood risk (Jakarta and Bandung, Indonesia) or how flood risk is modified after a seismic event (Italy). The analysis of well documented real study cases, based on a combination between Earth Observation and in-situ data, would serve as basis the formalisation of a multi-hazard methodology, identifying gaps and research frontiers. Multi-hazard risk analysis is performed through the RASOR platform (Rapid Analysis and Spatialisation Of Risk). A scenario-driven query system allow users to simulate future scenarios based on existing and assumed conditions, to compare with historical scenarios, and to model multi-hazard risk both before and during an event (www.rasor.eu).
Cellular Particle Dynamics simulation of biomechanical relaxation processes of multi-cellular systems

NASA Astrophysics Data System (ADS)

McCune, Matthew; Kosztin, Ioan

2013-03-01

Cellular Particle Dynamics (CPD) is a theoretical-computational-experimental framework for describing and predicting the time evolution of biomechanical relaxation processes of multi-cellular systems, such as fusion, sorting and compression. In CPD, cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through numerical integration of their equations of motion. Here we present CPD simulation results for the fusion of both spherical and cylindrical multi-cellular aggregates. First, we calibrate the relevant CPD model parameters for a given cell type by comparing the CPD simulation results for the fusion of two spherical aggregates to the corresponding experimental results. Next, CPD simulations are used to predict the time evolution of the fusion of cylindrical aggregates. The latter is relevant for the formation of tubular multi-cellular structures (i.e., primitive blood vessels) created by the novel bioprinting technology. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.
Multi-omics analysis provides insight to the Ignicoccus hospitalis - Nanoarchaeum equitans association

DOE PAGES

Rawle, Rachel A.; Hamerly, Timothy; Tripet, Brian P.; ...

2017-06-04

Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted ‘omics’ analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized usingmore » interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis–N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. In conclusion, this multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis–N. equitans association. This study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies.« less
Multi-omics analysis provides insight to the Ignicoccus hospitalis-Nanoarchaeum equitans association.

PubMed

Rawle, Rachel A; Hamerly, Timothy; Tripet, Brian P; Giannone, Richard J; Wurch, Louie; Hettich, Robert L; Podar, Mircea; Copié, Valerie; Bothner, Brian

2017-09-01

Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted 'omics' analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized using interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis-N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. This multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis-N. equitans association. Our study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies. Copyright © 2017 Elsevier B.V. All rights reserved.
Could a Weak Coupling Massless SU(5) Theory Underly the Standard Model S-Matrix

NASA Astrophysics Data System (ADS)

White, Alan R.

2011-04-01

The unitary Critical Pomeron connects to a unique massless left-handed SU(5) theory that, remarkably, might provide an unconventional underlying unification for the Standard Model. Multi-regge theory suggests the existence of a bound-state high-energy S-Matrix that replicates Standard Model states and interactions via massless fermion anomaly dynamics. Configurations of anomalous wee gauge boson reggeons play a vacuum-like role. All particles, including neutrinos, are bound-states with dynamical masses (there is no Higgs field) that are formed (in part) by anomaly poles. The contributing zero-momentum chirality transitions break the SU(5) symmetry to vector SU(3)⊗U(1) in the S-Matrix. The high-energy interactions are vector reggeon exchanges accompanied by wee boson sums (odd-signature for the strong interaction and even-signature for the electroweak interaction) that strongly enhance couplings. The very small SU(5) coupling, αQUD ≲ 1/120, should be reflected in small (Majorana) neutrino masses. A color sextet quark sector, still to be discovered, produces both Dark Matter and Electroweak Symmetry Breaking. Anomaly color factors imply this sector could be produced at the LHC with large cross-sections, and would be definitively identified in double pomeron processes.
Suicide risk factors for young adults: testing a model across ethnicities.

PubMed

Gutierrez, P M; Rodriguez, P J; Garcia, P

2001-06-01

A general path model based on existing suicide risk research was developed to test factors contributing to current suicidal ideation in young adults. A sample of 673 undergraduate students completed a packet of questionnaires containing the Beck Depression Inventory, Adult Suicidal Ideation Questionnaire, and Multi-Attitude Suicide Tendency Scale. They also provided information on history of suicidality and exposure to attempted and completed suicide in others. Structural equation modeling was used to test the fit of the data to the hypothesized model. Goodness-of-fit indices were adequate and supported the interactive effects of exposure, repulsion by life, depression, and history of self-harm on current ideation. Model fit for three subgroups based on race/ethnicity (i.e., White, Black, and Hispanic) determined that repulsion by life and depression function differently across groups. Implications of these findings for current methods of suicide risk assessment and future research are discussed in the context of the importance of culture.
Multi-species hybrid modeling of plasma interactions at Io and Europa

NASA Astrophysics Data System (ADS)

Sebek, O.; Travnicek, P. M.; Walker, R. J.; Hellinger, P.

2017-12-01

We study the plasma interactions of Galilean satellites, Io and Europa, by means of multi-species global hybrid simulations. For both satellites we consider multi-species background plasma composed of oxygen and sulphur ions and multi-component neutral atmospheres. We consider ionization processes of the neutral atmosphere which is then a source of dense population of pick-up ions. We apply variable background plasma conditions (density, temperature, magnetic field magnitude and orientation) in order to cover the variability in conditions experienced by the satellites when located in different regions of the Jovian plasma torus. We examine global structure of the interactions, formation of Alfvén wings, development of temperature anisotropies and corresponding instabilities, and the fine phenomena caused by the multi-specie nature of the plasma. The results are in good agreement with in situ measurements of magnetic field and plasma density made by the Galileo spacecraft.
Pathology Dynamics Predict Spinal Cord Injury Therapeutic Success

PubMed Central

Mitchell, Cassie S.

2008-01-01

Abstract Secondary injury, the complex cascade of cellular events following spinal cord injury (SCI), is a major source of post-insult neuron death. Experimental work has focused on the details of individual factors or mechanisms that contribute to secondary injury, but little is known about the interactions among factors leading to the overall pathology dynamics that underlie its propagation. Prior hypotheses suggest that the pathology is dominated by interactions, with therapeutic success lying in combinations of neuroprotective treatments. In this study, we provide the first comprehensive, system-level characterization of the entire secondary injury process using a novel relational model methodology that aggregates the findings of ~250 experimental studies. Our quantitative examination of the overall pathology dynamics suggests that, while the pathology is initially dominated by “fire-like,” rate-dependent interactions, it quickly switches to a “flood-like,” accumulation-dependent process with contributing factors being largely independent. Our evaluation of ~20,000 potential single and combinatorial treatments indicates this flood-like pathology results in few highly influential factors at clinically realistic treatment time frames, with multi-factor treatments being merely additive rather than synergistic in reducing neuron death. Our findings give new fundamental insight into the understanding of the secondary injury pathology as a whole, provide direction for alternative therapeutic strategies, and suggest that ultimate success in treating SCI lies in the pursuit of pathology dynamics in addition to individually involved factors. PMID:19125684
Modelling the Evolution of Social Structure

PubMed Central

Sutcliffe, A. G.; Dunbar, R. I. M.; Wang, D.

2016-01-01

Although simple social structures are more common in animal societies, some taxa (mainly mammals) have complex, multi-level social systems, in which the levels reflect differential association. We develop a simulation model to explore the conditions under which multi-level social systems of this kind evolve. Our model focuses on the evolutionary trade-offs between foraging and social interaction, and explores the impact of alternative strategies for distributing social interaction, with fitness criteria for wellbeing, alliance formation, risk, stress and access to food resources that reward social strategies differentially. The results suggest that multi-level social structures characterised by a few strong relationships, more medium ties and large numbers of weak ties emerge only in a small part of the overall fitness landscape, namely where there are significant fitness benefits from wellbeing and alliance formation and there are high levels of social interaction. In contrast, ‘favour-the-few’ strategies are more competitive under a wide range of fitness conditions, including those producing homogeneous, single-level societies of the kind found in many birds and mammals. The simulations suggest that the development of complex, multi-level social structures of the kind found in many primates (including humans) depends on a capacity for high investment in social time, preferential social interaction strategies, high mortality risk and/or differential reproduction. These conditions are characteristic of only a few mammalian taxa. PMID:27427758

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.
Family and home correlates of children's physical activity in a multi-ethnic population: the cross-sectional child heart and health study in england (CHASE)

PubMed Central

2011-01-01

Background The influence of the family and home environment on childhood physical activity (PA) and whether this differs between ethnic groups remains uncertain. This paper investigates associations between family and home factors and childhood PA in a multi-ethnic population and explores whether associations differ between ethnic groups. Methods Cross-sectional study of 9-10 year-old schoolchildren, in which PA was objectively measured by Actigraph GT1 M accelerometers for ≤7 days to estimate average activity counts per minute (CPM). Information on 11 family and home environmental factors were collected from questionnaires. Associations between these factors and CPM were quantified using multi-level linear regression. Interactions with ethnicity were explored using likelihood ratio tests. Results 2071 children (mean ± SD age: 9.95 ± 0.38 years; 47.8% male) participated, including 25% white European, 28% black African-Caribbean, 24% South Asian, and 24% other ethnic origin. Family PA support and having a pet were associated with higher average CPM (adjusted mean difference: 6 (95%CI:1,10) and 13 (95%CI:3,23), respectively) while car ownership and having internet access at home were associated with lower average CPM (adjusted mean difference: -19 (95%CI:-30,-8) and -10 (95%CI:-19,0), respectively). These associations did not differ by ethnicity. Although the number of siblings showed no overall association with PA, there was some evidence of interaction with ethnicity (p for ethnicity interaction = 0.04, 0.05 in a fully-adjusted model); a positive significant association with number of siblings was observed in white Europeans (per sibling CPM difference 10.3 (95% CI 1.7, 18.9)) and a positive non-significant association was observed in black African-Caribbeans (per sibling CPM difference: 3.5 (-4.2, 11.2)) while a negative, non-significant association was observed in South Asians (per sibling CPM difference -6.0 (-15.5, 3.4)). Conclusions Some family and home environmental factors have modest associations with childhood PA and these are mostly similar across different ethnic groups. This suggests that targeting these factors in an intervention to promote PA would be relevant for children in different ethnic groups. PMID:21324105
Family and home correlates of children's physical activity in a multi-ethnic population: the cross-sectional Child Heart and Health Study in England (CHASE).

PubMed

McMinn, Alison M; van Sluijs, Esther M F; Nightingale, Claire M; Griffin, Simon J; Cook, Derek G; Owen, Chris G; Rudnicka, Alicja R; Whincup, Peter H

2011-02-15

The influence of the family and home environment on childhood physical activity (PA) and whether this differs between ethnic groups remains uncertain. This paper investigates associations between family and home factors and childhood PA in a multi-ethnic population and explores whether associations differ between ethnic groups. Cross-sectional study of 9-10 year-old schoolchildren, in which PA was objectively measured by Actigraph GT1 M accelerometers for ≤7 days to estimate average activity counts per minute (CPM). Information on 11 family and home environmental factors were collected from questionnaires. Associations between these factors and CPM were quantified using multi-level linear regression. Interactions with ethnicity were explored using likelihood ratio tests. 2071 children (mean ± SD age: 9.95 ± 0.38 years; 47.8% male) participated, including 25% white European, 28% black African-Caribbean, 24% South Asian, and 24% other ethnic origin. Family PA support and having a pet were associated with higher average CPM (adjusted mean difference: 6 (95%CI:1,10) and 13 (95%CI:3,23), respectively) while car ownership and having internet access at home were associated with lower average CPM (adjusted mean difference: -19 (95%CI:-30,-8) and -10 (95%CI:-19,0), respectively). These associations did not differ by ethnicity. Although the number of siblings showed no overall association with PA, there was some evidence of interaction with ethnicity (p for ethnicity interaction=0.04, 0.05 in a fully-adjusted model); a positive significant association with number of siblings was observed in white Europeans (per sibling CPM difference 10.3 (95% CI 1.7, 18.9)) and a positive non-significant association was observed in black African-Caribbeans (per sibling CPM difference: 3.5 (-4.2, 11.2)) while a negative, non-significant association was observed in South Asians (per sibling CPM difference -6.0 (-15.5, 3.4)). Some family and home environmental factors have modest associations with childhood PA and these are mostly similar across different ethnic groups. This suggests that targeting these factors in an intervention to promote PA would be relevant for children in different ethnic groups. © 2011 McMinn et al; licensee BioMed Central Ltd.
A quantitative model of application slow-down in multi-resource shared systems

DOE PAGES

Lim, Seung-Hwan; Kim, Youngjae

2016-12-26

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job ismore » characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.« less
A quantitative model of application slow-down in multi-resource shared systems

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

Lim, Seung-Hwan; Kim, Youngjae

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job ismore » characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.« less
Socioeconomic Status and the Health of Youth: A Multi-level, Multi-domain Approach to Conceptualizing Pathways

PubMed Central

Schreier, Hannah M. C.; Chen, Edith

2012-01-01

Previous research has clearly established associations between low socioeconomic status (SES) and poor youth physical health outcomes. This article provides an overview of the main pathways through which low SES environments come to influence youth health. We focus on two of the most prevalent chronic health problems in youth today, asthma and obesity. We review and propose a model that encompasses (1) multiple levels of influence, including the neighborhood, family and person level, (2) both social and physical domains in the environment, and finally (3) dynamic relationships between these factors. A synthesis of existing research and our proposed model draw attention to the notion of adverse physical and social exposures in youth’s neighborhood environments altering family characteristics and youth psychosocial and behavioral profiles, thereby increasing youth’s risk for health problems. We also note the importance of acknowledging reciprocal influences across levels and domains (e.g., between family and child) that create self-perpetuating patterns of influence that further accentuate the impact of these factors on youth health. Finally, we document that factors across levels can interact (e.g., environmental pollution levels with child stress) to create unique, synergistic effects on youth health. Our model stresses the importance of evaluating influences on youth’s physical health not in isolation but in the context of the broader social and physical environments in which youth live. Understanding the complex relationships between the factors that link low SES to youth’s long-term health trajectories is necessary for the creation and implementation of successful interventions and policies to ultimately reduce health disparities. PMID:22845752
Simultaneous segmentation of the bone and cartilage surfaces of a knee joint in 3D

NASA Astrophysics Data System (ADS)

Yin, Y.; Zhang, X.; Anderson, D. D.; Brown, T. D.; Hofwegen, C. Van; Sonka, M.

2009-02-01

We present a novel framework for the simultaneous segmentation of multiple interacting surfaces belonging to multiple mutually interacting objects. The method is a non-trivial extension of our previously reported optimal multi-surface segmentation. Considering an example application of knee-cartilage segmentation, the framework consists of the following main steps: 1) Shape model construction: Building a mean shape for each bone of the joint (femur, tibia, patella) from interactively segmented volumetric datasets. Using the resulting mean-shape model - identification of cartilage, non-cartilage, and transition areas on the mean-shape bone model surfaces. 2) Presegmentation: Employment of iterative optimal surface detection method to achieve approximate segmentation of individual bone surfaces. 3) Cross-object surface mapping: Detection of inter-bone equidistant separating sheets to help identify corresponding vertex pairs for all interacting surfaces. 4) Multi-object, multi-surface graph construction and final segmentation: Construction of a single multi-bone, multi-surface graph so that two surfaces (bone and cartilage) with zero and non-zero intervening distances can be detected for each bone of the joint, according to whether or not cartilage can be locally absent or present on the bone. To define inter-object relationships, corresponding vertex pairs identified using the separating sheets were interlinked in the graph. The graph optimization algorithm acted on the entire multiobject, multi-surface graph to yield a globally optimal solution. The segmentation framework was tested on 16 MR-DESS knee-joint datasets from the Osteoarthritis Initiative database. The average signed surface positioning error for the 6 detected surfaces ranged from 0.00 to 0.12 mm. When independently initialized, the signed reproducibility error of bone and cartilage segmentation ranged from 0.00 to 0.26 mm. The results showed that this framework provides robust, accurate, and reproducible segmentation of the knee joint bone and cartilage surfaces of the femur, tibia, and patella. As a general segmentation tool, the developed framework can be applied to a broad range of multi-object segmentation problems.
Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

2016-03-01

In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.
Development of a Patient-Specific Multi-Scale Model to Understand Atherosclerosis and Calcification Locations: Comparison with In vivo Data in an Aortic Dissection

PubMed Central

Alimohammadi, Mona; Pichardo-Almarza, Cesar; Agu, Obiekezie; Díaz-Zuccarini, Vanessa

2016-01-01

Vascular calcification results in stiffening of the aorta and is associated with hypertension and atherosclerosis. Atherogenesis is a complex, multifactorial, and systemic process; the result of a number of factors, each operating simultaneously at several spatial and temporal scales. The ability to predict sites of atherogenesis would be of great use to clinicians in order to improve diagnostic and treatment planning. In this paper, we present a mathematical model as a tool to understand why atherosclerotic plaque and calcifications occur in specific locations. This model is then used to analyze vascular calcification and atherosclerotic areas in an aortic dissection patient using a mechanistic, multi-scale modeling approach, coupling patient-specific, fluid-structure interaction simulations with a model of endothelial mechanotransduction. A number of hemodynamic factors based on state-of-the-art literature are used as inputs to the endothelial permeability model, in order to investigate plaque and calcification distributions, which are compared with clinical imaging data. A significantly improved correlation between elevated hydraulic conductivity or volume flux and the presence of calcification and plaques was achieved by using a shear index comprising both mean and oscillatory shear components (HOLMES) and a non-Newtonian viscosity model as inputs, as compared to widely used hemodynamic indicators. The proposed approach shows promise as a predictive tool. The improvements obtained using the combined biomechanical/biochemical modeling approach highlight the benefits of mechanistic modeling as a powerful tool to understand complex phenomena and provides insight into the relative importance of key hemodynamic parameters. PMID:27445834
TopicLens: Efficient Multi-Level Visual Topic Exploration of Large-Scale Document Collections.

PubMed

Kim, Minjeong; Kang, Kyeongpil; Park, Deokgun; Choo, Jaegul; Elmqvist, Niklas

2017-01-01

Topic modeling, which reveals underlying topics of a document corpus, has been actively adopted in visual analytics for large-scale document collections. However, due to its significant processing time and non-interactive nature, topic modeling has so far not been tightly integrated into a visual analytics workflow. Instead, most such systems are limited to utilizing a fixed, initial set of topics. Motivated by this gap in the literature, we propose a novel interaction technique called TopicLens that allows a user to dynamically explore data through a lens interface where topic modeling and the corresponding 2D embedding are efficiently computed on the fly. To support this interaction in real time while maintaining view consistency, we propose a novel efficient topic modeling method and a semi-supervised 2D embedding algorithm. Our work is based on improving state-of-the-art methods such as nonnegative matrix factorization and t-distributed stochastic neighbor embedding. Furthermore, we have built a web-based visual analytics system integrated with TopicLens. We use this system to measure the performance and the visualization quality of our proposed methods. We provide several scenarios showcasing the capability of TopicLens using real-world datasets.
Strain Interactions as a Mechanism for Dominant Strain Alternation and Incidence Oscillation in Infectious Diseases: Seasonal Influenza as a Case Study

PubMed Central

Zhang, Xu-Sheng

2015-01-01

Background Many human infectious diseases are caused by pathogens that have multiple strains and show oscillation in infection incidence and alternation of dominant strains which together are referred to as epidemic cycling. Understanding the underlying mechanisms of epidemic cycling is essential for forecasting outbreaks of epidemics and therefore important for public health planning. Current theoretical effort is mainly focused on the factors that are extrinsic to the pathogens themselves (“extrinsic factors”) such as environmental variation and seasonal change in human behaviours and susceptibility. Nevertheless, co-circulation of different strains of a pathogen was usually observed and thus strains interact with one another within concurrent infection and during sequential infection. The existence of these intrinsic factors is common and may be involved in the generation of epidemic cycling of multi-strain pathogens. Methods and Findings To explore the mechanisms that are intrinsic to the pathogens themselves (“intrinsic factors”) for epidemic cycling, we consider a multi-strain SIRS model including cross-immunity and infectivity enhancement and use seasonal influenza as an example to parameterize the model. The Kullback-Leibler information distance was calculated to measure the match between the model outputs and the typical features of seasonal flu (an outbreak duration of 11 weeks and an annual attack rate of 15%). Results show that interactions among strains can generate seasonal influenza with these characteristic features, provided that: the infectivity of a single strain within concurrent infection is enhanced 2−7 times that within a single infection; cross-immunity as a result of past infection is 0.5–0.8 and lasts 2–9 years; while other parameters are within their widely accepted ranges (such as a 2–3 day infectious period and the basic reproductive number of 1.8–3.0). Moreover, the observed alternation of the dominant strain among epidemics emerges naturally from the best fit model. Alternative modelling that also includes seasonal forcing in transmissibility shows that both external mechanisms (i.e. seasonal forcing) and the intrinsic mechanisms (i.e., strain interactions) are equally able to generate the observed time-series in seasonal flu. Conclusions The intrinsic mechanism of strain interactions alone can generate the observed patterns of seasonal flu epidemics, but according to Kullback-Leibler information distance the importance of extrinsic mechanisms cannot be excluded. The intrinsic mechanism illustrated here to explain seasonal flu may also apply to other infectious diseases caused by polymorphic pathogens. PMID:26562668
Modeling and predicting urban growth pattern of the Tokyo metropolitan area based on cellular automata

NASA Astrophysics Data System (ADS)

Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji

2008-10-01

The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.
Fabrication of uniform multi-compartment particles using microfludic electrospray technology for cell co-culture studies.

PubMed

Liu, Zhou; Shum, Ho Cheung

2013-01-01

In this work, we demonstrate a robust and reliable approach to fabricate multi-compartment particles for cell co-culture studies. By taking advantage of the laminar flow within our microfluidic nozzle, multiple parallel streams of liquids flow towards the nozzle without significant mixing. Afterwards, the multiple parallel streams merge into a single stream, which is sprayed into air, forming monodisperse droplets under an electric field with a high field strength. The resultant multi-compartment droplets are subsequently cross-linked in a calcium chloride solution to form calcium alginate micro-particles with multiple compartments. Each compartment of the particles can be used for encapsulating different types of cells or biological cell factors. These hydrogel particles with cross-linked alginate chains show similarity in the physical and mechanical environment as the extracellular matrix of biological cells. Thus, the multi-compartment particles provide a promising platform for cell studies and co-culture of different cells. In our study, cells are encapsulated in the multi-compartment particles and the viability of cells is quantified using a fluorescence microscope after the cells are stained for a live/dead assay. The high cell viability after encapsulation indicates the cytocompatibility and feasibility of our technique. Our multi-compartment particles have great potential as a platform for studying cell-cell interactions as well as interactions of cells with extracellular factors.
Fabrication of uniform multi-compartment particles using microfludic electrospray technology for cell co-culture studies

PubMed Central

Liu, Zhou; Shum, Ho Cheung

2013-01-01

In this work, we demonstrate a robust and reliable approach to fabricate multi-compartment particles for cell co-culture studies. By taking advantage of the laminar flow within our microfluidic nozzle, multiple parallel streams of liquids flow towards the nozzle without significant mixing. Afterwards, the multiple parallel streams merge into a single stream, which is sprayed into air, forming monodisperse droplets under an electric field with a high field strength. The resultant multi-compartment droplets are subsequently cross-linked in a calcium chloride solution to form calcium alginate micro-particles with multiple compartments. Each compartment of the particles can be used for encapsulating different types of cells or biological cell factors. These hydrogel particles with cross-linked alginate chains show similarity in the physical and mechanical environment as the extracellular matrix of biological cells. Thus, the multi-compartment particles provide a promising platform for cell studies and co-culture of different cells. In our study, cells are encapsulated in the multi-compartment particles and the viability of cells is quantified using a fluorescence microscope after the cells are stained for a live/dead assay. The high cell viability after encapsulation indicates the cytocompatibility and feasibility of our technique. Our multi-compartment particles have great potential as a platform for studying cell-cell interactions as well as interactions of cells with extracellular factors. PMID:24404050
NUCLEAR FACTOR Y Transcription Factors Have Both Opposing and Additive Roles in ABA-Mediated Seed Germination

PubMed Central

Kumimoto, Roderick W.; Siriwardana, Chamindika L.; Gayler, Krystal K.; Risinger, Jan R.; Siefers, Nicholas; Holt, Ben F.

2013-01-01

In the model organism Arabidopsis thaliana the heterotrimeric transcription factor NUCLEAR FACTOR Y (NF-Y) has been shown to play multiple roles in facilitating plant growth and development. Although NF-Y itself represents a multi-protein transcriptional complex, recent studies have shown important interactions with other transcription factors, especially those in the bZIP family. Here we add to the growing evidence that NF-Y and bZIP form common complexes to affect many processes. We carried out transcriptional profiling on nf-yc mutants and through subsequent analyses found an enrichment of bZIP binding sites in the promoter elements of misregulated genes. Using NF-Y as bait, yeast two hybrid assays yielded interactions with bZIP proteins that are known to control ABA signaling. Accordingly, we find that plants mutant for several NF-Y subunits show characteristic phenotypes associated with the disruption of ABA signaling. While previous reports have shown additive roles for NF-YC family members in photoperiodic flowering, we found that they can have opposing roles in ABA signaling. Collectively, these results demonstrated the importance and complexity of NF-Y in the integration of environmental and hormone signals. PMID:23527203
Epidermal Growth Factor Receptor (EGFR) and its Cross-Talks with Topoisomerases: Challenges and Opportunities for Multi-Target Anticancer Drugs.

PubMed

Chauhan, Monika; Sharma, Gourav; Joshi, Gaurav; Kumar, Raj

2016-01-01

The interactions of Epidermal Growth Factor Receptor (EGFR) and topoisomerases have been seen in various cancer including brain, breast, ovarian, colorectal, gastric, etc. The studies in adenocarcinoma patients, chromogenic in situ hybridization, western blotting, receptor binding assay and electromobility shift assays, etc. threw light on the biophysical and biochemical features of EGFR and Topoisomerase cross-talks. It has been revealed that both the isomers of topoisomerase (Topo I and Topo II) interact via different mechanisms with EGFR. Topo II and HER2 share the same location i.e. 17q12-21 regions which could be a possible cause of predominant interactions seen between them. Topo I and EGFR interactions are mechanically related to the nucleolar translocation of heparenase by EGF and c-Jun. We compiled literature findings including the mechanistic interventions, signaling pathways, patents, in vitro and in vivo data of tested inhibitors and combinations in clinical trials, which provide convincing confirmations for the interactions of EGFR and topoisomerases. These interactions may be used for deriving a consistent route of mechanism, design and development of standard drug combinations and dual or multi inhibitors.
Dynamic analysis of space structures including elastic, multibody, and control behavior

NASA Technical Reports Server (NTRS)

Pinson, Larry; Soosaar, Keto

1989-01-01

The problem is to develop analysis methods, modeling stategies, and simulation tools to predict with assurance the on-orbit performance and integrity of large complex space structures that cannot be verified on the ground. The problem must incorporate large reliable structural models, multi-body flexible dynamics, multi-tier controller interaction, environmental models including 1g and atmosphere, various on-board disturbances, and linkage to mission-level performance codes. All areas are in serious need of work, but the weakest link is multi-body flexible dynamics.
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
Obesity in sub-Saharan Africa: development of an ecological theoretical framework.

PubMed

Scott, Alison; Ejikeme, Chinwe Stella; Clottey, Emmanuel Nii; Thomas, Joy Goens

2013-03-01

The prevalence of overweight and obesity is increasing in sub-Saharan Africa (SSA). There is a need for theoretical frameworks to catalyze further research and to inform the development of multi-level, context-appropriate interventions. In this commentary, we propose a preliminary ecological theoretical framework to conceptualize factors that contribute to increases in overweight and obesity in SSA. The framework is based on a Causality Continuum model [Coreil et al. Social and Behavioral Foundations of Public Health. Sage Publications, Thousand Oaks] that considers distant, intermediate and proximate influences. The influences incorporated in the model include globalization and urbanization as distant factors; occupation, social relationships, built environment and cultural perceptions of weight as intermediate factors and caloric intake, physical inactivity and genetics as proximate factors. The model illustrates the interaction of factors along a continuum, from the individual to the global marketplace, in shaping trends in overweight and obesity in SSA. The framework will be presented, each influence elucidated and implications for research and intervention development discussed. There is a tremendous need for further research on obesity in SSA. An improved evidence base will serve to validate and develop the proposed framework further.
Impact of elevated precipitation, nitrogen deposition and warming on soil respiration in a temperate desert

NASA Astrophysics Data System (ADS)

Yue, Ping; Cui, Xiaoqing; Gong, Yanming; Li, Kaihui; Goulding, Keith; Liu, Xuejun

2018-04-01

Soil respiration (Rs) is the most important source of carbon dioxide emissions from soil to atmosphere. However, it is unclear what the interactive response of Rs would be to environmental changes such as elevated precipitation, nitrogen (N) deposition and warming, especially in unique temperate desert ecosystems. To investigate this an in situ field experiment was conducted in the Gurbantunggut Desert, northwest China, from September 2014 to October 2016. The results showed that precipitation and N deposition significantly increased Rs, but warming decreased Rs, except in extreme precipitation events, which was mainly through its impact on the variation of soil moisture at 5 cm depth. In addition, the interactive response of Rs to combinations of the factors was much less than that of any single-factor, and the main response was a positive effect, except for the response from the interaction of increased precipitation and high N deposition (60 kg N ha-1 yr-1). Although Rs was found to show a unimodal change pattern with the variation of soil moisture, soil temperature and soil NH4+-N content, and it was significantly positively correlated to soil dissolved organic carbon (DOC) and pH, a structural equation model found that soil temperature was the most important controlling factor. Those results indicated that Rs was mainly interactively controlled by the soil multi-environmental factors and soil nutrients, and was very sensitive to elevated precipitation, N deposition and warming. However, the interactions of multiple factors largely reduced between-year variation of Rs more than any single-factor, suggesting that the carbon cycle in temperate deserts could be profoundly influenced by positive carbon-climate feedback.

Multiscale modeling of sickle anemia blood blow by Dissipative Partice Dynamics

NASA Astrophysics Data System (ADS)

Lei, Huan; Caswell, Bruce; Karniadakis, George

2011-11-01

A multi-scale model for sickle red blood cell is developed based on Dissipative Particle Dynamics (DPD). Different cell morphologies (sickle, granular, elongated shapes) typically observed in in vitro and in vivo are constructed and the deviations from the biconcave shape is quantified by the Asphericity and Elliptical shape factors. The rheology of sickle blood is studied in both shear and pipe flow systems. The flow resistance obtained from both systems exhibits a larger value than the healthy blood flow due to the abnormal cell properties. However, the vaso-occulusion phenomenon, reported in a recent microfluid experiment, is not observed in the pipe flow system unless the adhesive interactions between sickle blood cells and endothelium properly introduced into the model.
A queueing model of pilot decision making in a multi-task flight management situation

NASA Technical Reports Server (NTRS)

Walden, R. S.; Rouse, W. B.

1977-01-01

Allocation of decision making responsibility between pilot and computer is considered and a flight management task, designed for the study of pilot-computer interaction, is discussed. A queueing theory model of pilot decision making in this multi-task, control and monitoring situation is presented. An experimental investigation of pilot decision making and the resulting model parameters are discussed.
Interaction in Balanced Cross Nested Designs

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

NASA Astrophysics Data System (ADS)

Holsman, Kirstin K.; Ianelli, James; Aydin, Kerim; Punt, André E.; Moffitt, Elizabeth A.

2016-12-01

Multi-species statistical catch at age models (MSCAA) can quantify interacting effects of climate and fisheries harvest on species populations, and evaluate management trade-offs for fisheries that target several species in a food web. We modified an existing MSCAA model to include temperature-specific growth and predation rates and applied the modified model to three fish species, walleye pollock (Gadus chalcogrammus), Pacific cod (Gadus macrocephalus) and arrowtooth flounder (Atheresthes stomias), from the eastern Bering Sea (USA). We fit the model to data from 1979 through 2012, with and without trophic interactions and temperature effects, and use projections to derive single- and multi-species biological reference points (BRP and MBRP, respectively) for fisheries management. The multi-species model achieved a higher over-all goodness of fit to the data (i.e. lower negative log-likelihood) for pollock and Pacific cod. Variability from water temperature typically resulted in 5-15% changes in spawning, survey, and total biomasses, but did not strongly impact recruitment estimates or mortality. Despite this, inclusion of temperature in projections did have a strong effect on BRPs, including recommended yield, which were higher in single-species models for Pacific cod and arrowtooth flounder that included temperature compared to the same models without temperature effects. While the temperature-driven multi-species model resulted in higher yield MBPRs for arrowtooth flounder than the same model without temperature, we did not observe the same patterns in multi-species models for pollock and Pacific cod, where variability between harvest scenarios and predation greatly exceeded temperature-driven variability in yield MBRPs. Annual predation on juvenile pollock (primarily cannibalism) in the multi-species model was 2-5 times the annual harvest of adult fish in the system, thus predation represents a strong control on population dynamics that exceeds temperature-driven changes to growth and is attenuated through harvest-driven reductions in predator populations. Additionally, although we observed differences in spawning biomasses at the accepted biological catch (ABC) proxy between harvest scenarios and single- and multi-species models, discrepancies in spawning stock biomass estimates did not translate to large differences in yield. We found that multi-species models produced higher estimates of combined yield for aggregate maximum sustainable yield (MSY) targets than single species models, but were more conservative than single-species models when individual MSY targets were used, with the exception of scenarios where minimum biomass thresholds were imposed. Collectively our results suggest that climate and trophic drivers can interact to affect MBRPs, but for prey species with high predation rates, trophic- and management-driven changes may exceed direct effects of temperature on growth and predation. Additionally, MBRPs are not inherently more conservative than single-species BRPs. This framework provides a basis for the application of MSCAA models for tactical ecosystem-based fisheries management decisions under changing climate conditions.
Effects of Maternal Nutrition, Resource Use and Multi-Predator Risk on Neonatal White-Tailed Deer Survival

PubMed Central

Duquette, Jared F.; Belant, Jerrold L.; Svoboda, Nathan J.; Beyer, Dean E.; Lederle, Patrick E.

2014-01-01

Growth of ungulate populations is typically most sensitive to survival of neonates, which in turn is influenced by maternal nutritional condition and trade-offs in resource selection and avoidance of predators. We assessed whether resource use, multi-predator risk, maternal nutritional effects, hiding cover, or interactions among these variables best explained variation in daily survival of free-ranging neonatal white-tailed deer (Odocoileus virginianus) during their post-partum period (14 May–31 Aug) in Michigan, USA. We used Cox proportional hazards mixed-effects models to assess survival related to covariates of resource use, composite predation risk of 4 mammalian predators, fawn body mass at birth, winter weather, and vegetation growth phenology. Predation, particularly from coyotes (Canis latrans), was the leading cause of mortality; however, an additive model of non-ideal resource use and maternal nutritional effects explained 71% of the variation in survival. This relationship suggested that dams selected areas where fawns had poor resources, while greater predation in these areas led to additive mortalities beyond those related to resource use alone. Also, maternal nutritional effects suggested that severe winters resulted in dams producing smaller fawns, which decreased their likelihood of survival. Fawn resource use appeared to reflect dam avoidance of lowland forests with poor forage and greater use by wolves (C. lupus), their primary predator. While this strategy led to greater fawn mortality, particularly by coyotes, it likely promoted the life-long reproductive success of dams because many reached late-age (>10 years old) and could have produced multiple generations of fawns. Studies often link resource selection and survival of ungulates, but our results suggested that multiple factors can mediate that relationship, including multi-predator risk. We emphasize the importance of identifying interactions among biological and environmental factors when assessing survival of ungulates. PMID:24968318
High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia

PubMed Central

Plis, Sergey M; Sui, Jing; Lane, Terran; Roy, Sushmita; Clark, Vincent P; Potluru, Vamsi K; Huster, Rene J; Michael, Andrew; Sponheim, Scott R; Weisend, Michael P; Calhoun, Vince D

2013-01-01

Identifying the complex activity relationships present in rich, modern neuroimaging data sets remains a key challenge for neuroscience. The problem is hard because (a) the underlying spatial and temporal networks may be nonlinear and multivariate and (b) the observed data may be driven by numerous latent factors. Further, modern experiments often produce data sets containing multiple stimulus contexts or tasks processed by the same subjects. Fusing such multi-session data sets may reveal additional structure, but raises further statistical challenges. We present a novel analysis method for extracting complex activity networks from such multifaceted imaging data sets. Compared to previous methods, we choose a new point in the trade-off space, sacrificing detailed generative probability models and explicit latent variable inference in order to achieve robust estimation of multivariate, nonlinear group factors (“network clusters”). We apply our method to identify relationships of task-specific intrinsic networks in schizophrenia patients and control subjects from a large fMRI study. After identifying network-clusters characterized by within- and between-task interactions, we find significant differences between patient and control groups in interaction strength among networks. Our results are consistent with known findings of brain regions exhibiting deviations in schizophrenic patients. However, we also find high-order, nonlinear interactions that discriminate groups but that are not detected by linear, pair-wise methods. We additionally identify high-order relationships that provide new insights into schizophrenia but that have not been found by traditional univariate or second-order methods. Overall, our approach can identify key relationships that are missed by existing analysis methods, without losing the ability to find relationships that are known to be important. PMID:23876245
Dysfunctional Attitudes and Affective Responses to Daily Stressors: Separating Cognitive, Genetic, and Clinical Influences on Stress Reactivity

PubMed Central

Conway, Christopher C.; Slavich, George M.; Hammen, Constance

2016-01-01

Despite decades of research examining diathesis-stress models of emotional disorders, it remains unclear whether dysfunctional attitudes interact with stressful experiences to shape affect on a daily basis and, if so, how clinical and genetic factors influence these associations. To address these issues, we conducted a multi-level daily diary study that examined how dysfunctional attitudes and stressful events relate to daily fluctuations in negative and positive affect in 104 young adults. Given evidence that clinical and genetic factors underlie stress sensitivity, we also examined how daily affect is influenced by internalizing and externalizing symptoms and brain-derived neurotrophic factor (BDNF) genotype, which have been shown to influence neural, endocrine, and affective responses to stress. In multivariate models, internalizing symptoms and BDNF Val66Met genotype independently predicted heightened negative affect on stressful days, but dysfunctional attitudes did not. Specifically, the BDNF Met allele and elevated baseline internalizing symptomatology predicted greater increases in negative affect in stressful circumstances. These data are the first to demonstrate that BDNF genotype and stress are jointly associated with daily fluctuations in negative affect, and they challenge the assumption that maladaptive beliefs play a strong independent role in determining affective responses to everyday stressors. The results may thus inform the development of new multi-level theories of psychopathology and guide future research on predictors of affective lability. PMID:27041782
Insight into the heterogeneous adsorption of humic acid fluorescent components on multi-walled carbon nanotubes by excitation-emission matrix and parallel factor analysis.

PubMed

Yang, Chenghu; Liu, Yangzhi; Cen, Qiulin; Zhu, Yaxian; Zhang, Yong

2018-02-01

The heterogeneous adsorption behavior of commercial humic acid (HA) on pristine and functionalized multi-walled carbon nanotubes (MWCNTs) was investigated by fluorescence excitation-emission matrix and parallel factor (EEM- PARAFAC) analysis. The kinetics, isotherms, thermodynamics and mechanisms of adsorption of HA fluorescent components onto MWCNTs were the focus of the present study. Three humic-like fluorescent components were distinguished, including one carboxylic-like fluorophore C1 (λ ex /λ em = (250, 310) nm/428nm), and two phenolic-like fluorophores, C2 (λ ex /λ em = (300, 460) nm/552nm) and C3 (λ ex /λ em = (270, 375) nm/520nm). The Lagergren pseudo-second-order model can be used to describe the adsorption kinetics of the HA fluorescent components. In addition, both the Freundlich and Langmuir models can be suitably employed to describe the adsorption of the HA fluorescent components onto MWCNTs with significantly high correlation coefficients (R 2 > 0.94, P< 0.05). The dissimilarity in the adsorption affinity (K d ) and nonlinear adsorption degree from the HA fluorescent components to MWCNTs was clearly observed. The adsorption mechanism suggested that the π-π electron donor-acceptor (EDA) interaction played an important role in the interaction between HA fluorescent components and the three MWCNTs. Furthermore, the values of the thermodynamic parameters, including the Gibbs free energy change (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°), showed that the adsorption of the HA fluorescent components on MWCNTs was spontaneous and exothermic. Copyright © 2017 Elsevier Inc. All rights reserved.
Identifying functional zones of denitrification in heterogeneous aquifer systems by numerical simulations - a case study

NASA Astrophysics Data System (ADS)

Jang, E.; Kalbacher, T.; He, W.; Shao, H.; Schueth, C.; Kolditz, O.

2014-12-01

Nitrate contamination in shallow groundwater is still one of the common problems in many countries. Because of its high solubility and anionic nature, nitrate can easily leach through soil and persist in groundwater for decades. High nitrate concentration has been suggested as a major cause of accelerated eutrophication, methemoglobinemia and gastric cancer. There are several factors influencing the fate of nitrate in groundwater system, which is e.g. distribution of N- sources to soil and groundwater, distribution and amount of reactive substances maintaining denitrification, rate of nitrate degradation and its kinetics, and geological characteristics of the aquifer. Nitrate transport and redox transformation processes are closely linked to complex and spatially distributed physical and chemical interaction, therefore it is difficult to predict and quantify in the field and laboratory experiment. Models can play a key role in elucidation of nitrate reduction pathway in groundwater system and in the design and evaluation of field tests to investigate in situ remediation technologies as well. The goal of the current study is to predict groundwater vulnerability to nitrate, to identify functional zones of denitrification in heterogeneous aquifer systems and to describe the uncertainty of the predictions due to scale effects. For this aim, we developed a kinetic model using multi-component mass transport code OpenGeoSys coupling with IPhreeqc module of the geochemical solver PHREEQC. The developed model included sequential aerobic and nitrate-based respiration, multi-Monod kinetics, multi-species biogeochemical reactions, and geological characteristics of the groundwater aquifer. Moreover water-rock interaction such as secondary mineral precipitation was also included in this model. In this presentation, we focused on the general modelling approach and present the simulation results of nitrate transport simulation in a hypothetical aquifer systems based on data from Hessian Ried, an important groundwater resource for the densely populated Rhine-Main region in Germany.
Fuzzy Edge Connectivity of Graphical Fuzzy State Space Model in Multi-connected System

NASA Astrophysics Data System (ADS)

Harish, Noor Ainy; Ismail, Razidah; Ahmad, Tahir

2010-11-01

Structured networks of interacting components illustrate complex structure in a direct or intuitive way. Graph theory provides a mathematical modeling for studying interconnection among elements in natural and man-made systems. On the other hand, directed graph is useful to define and interpret the interconnection structure underlying the dynamics of the interacting subsystem. Fuzzy theory provides important tools in dealing various aspects of complexity, imprecision and fuzziness of the network structure of a multi-connected system. Initial development for systems of Fuzzy State Space Model (FSSM) and a fuzzy algorithm approach were introduced with the purpose of solving the inverse problems in multivariable system. In this paper, fuzzy algorithm is adapted in order to determine the fuzzy edge connectivity between subsystems, in particular interconnected system of Graphical Representation of FSSM. This new approach will simplify the schematic diagram of interconnection of subsystems in a multi-connected system.
Computational Analysis of Multi-Rotor Flows

NASA Technical Reports Server (NTRS)

Yoon, Seokkwan; Lee, Henry C.; Pulliam, Thomas H.

2016-01-01

Interactional aerodynamics of multi-rotor flows has been studied for a quadcopter representing a generic quad tilt-rotor aircraft in hover. The objective of the present study is to investigate the effects of the separation distances between rotors, and also fuselage and wings on the performance and efficiency of multirotor systems. Three-dimensional unsteady Navier-Stokes equations are solved using a spatially 5th order accurate scheme, dual-time stepping, and the Detached Eddy Simulation turbulence model. The results show that the separation distances as well as the wings have significant effects on the vertical forces of quadroror systems in hover. Understanding interactions in multi-rotor flows would help improve the design of next generation multi-rotor drones.
A multi-agent safety response model in the construction industry.

PubMed

Meliá, José L

2015-01-01

The construction industry is one of the sectors with the highest accident rates and the most serious accidents. A multi-agent safety response approach allows a useful diagnostic tool in order to understand factors affecting risk and accidents. The special features of the construction sector can influence the relationships among safety responses along the model of safety influences. The purpose of this paper is to test a model explaining risk and work-related accidents in the construction industry as a result of the safety responses of the organization, the supervisors, the co-workers and the worker. 374 construction employees belonging to 64 small Spanish construction companies working for two main companies participated in the study. Safety responses were measured using a 45-item Likert-type questionnaire. The structure of the measure was analyzed using factor analysis and the model of effects was tested using a structural equation model. Factor analysis clearly identifies the multi-agent safety dimensions hypothesized. The proposed safety response model of work-related accidents, involving construction specific results, showed a good fit. The multi-agent safety response approach to safety climate is a useful framework for the assessment of organizational and behavioral risks in construction.
[Location selection for Shenyang urban parks based on GIS and multi-objective location allocation model].

PubMed

Zhou, Yuan; Shi, Tie-Mao; Hu, Yuan-Man; Gao, Chang; Liu, Miao; Song, Lin-Qi

2011-12-01

Based on geographic information system (GIS) technology and multi-objective location-allocation (LA) model, and in considering of four relatively independent objective factors (population density level, air pollution level, urban heat island effect level, and urban land use pattern), an optimized location selection for the urban parks within the Third Ring of Shenyang was conducted, and the selection results were compared with the spatial distribution of existing parks, aimed to evaluate the rationality of the spatial distribution of urban green spaces. In the location selection of urban green spaces in the study area, the factor air pollution was most important, and, compared with single objective factor, the weighted analysis results of multi-objective factors could provide optimized spatial location selection of new urban green spaces. The combination of GIS technology with LA model would be a new approach for the spatial optimizing of urban green spaces.
Optimal region of latching activity in an adaptive Potts model for networks of neurons

NASA Astrophysics Data System (ADS)

Abdollah-nia, Mohammad-Farshad; Saeedghalati, Mohammadkarim; Abbassian, Abdolhossein

2012-02-01

In statistical mechanics, the Potts model is a model for interacting spins with more than two discrete states. Neural networks which exhibit features of learning and associative memory can also be modeled by a system of Potts spins. A spontaneous behavior of hopping from one discrete attractor state to another (referred to as latching) has been proposed to be associated with higher cognitive functions. Here we propose a model in which both the stochastic dynamics of Potts models and an adaptive potential function are present. A latching dynamics is observed in a limited region of the noise(temperature)-adaptation parameter space. We hence suggest noise as a fundamental factor in such alternations alongside adaptation. From a dynamical systems point of view, the noise-adaptation alternations may be the underlying mechanism for multi-stability in attractor-based models. An optimality criterion for realistic models is finally inferred.
The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.
A 3D Multi-fluid MHD Study of the Interaction of the Solar Wind with the Ionosphere/Atmosphere System of Mars.

NASA Astrophysics Data System (ADS)

Najib, Dalal; Nagy, Andrew; Toth, Gabor; Ma, Yingjuan

We use our new four species multi-fluid model to study the interaction of the solar wind with Mars. The lower boundary of our model is at 100 km, below the main ionospheric peak, and the radial resolution is about 10 km in the ionosphere, thus the model does a very good job in reproducing the ionosphere and the associated processes. We carry out calculations for high and low solar activity conditions and establish the importance of mass loading by the extended exosphere of Mars. We also calculate the atmospheric escape of the ionospheric species, including pick up ions. Finally, we compare our model results with the Viking, MGS and Mars Express observations.
Coupled Modeling of Rhizosphere and Reactive Transport Processes

NASA Astrophysics Data System (ADS)

Roque-Malo, S.; Kumar, P.

2017-12-01

The rhizosphere, as a bio-diverse plant root-soil interface, hosts many hydrologic and biochemical processes, including nutrient cycling, hydraulic redistribution, and soil carbon dynamics among others. The biogeochemical function of root networks, including the facilitation of nutrient cycling through absorption and rhizodeposition, interaction with micro-organisms and fungi, contribution to biomass, etc., plays an important role in myriad Critical Zone processes. Despite this knowledge, the role of the rhizosphere on watershed-scale ecohydrologic functions in the Critical Zone has not been fully characterized, and specifically, the extensive capabilities of reactive transport models (RTMs) have not been applied to these hydrobiogeochemical dynamics. This study uniquely links rhizospheric processes with reactive transport modeling to couple soil biogeochemistry, biological processes, hydrologic flow, hydraulic redistribution, and vegetation dynamics. Key factors in the novel modeling approach are: (i) bi-directional effects of root-soil interaction, such as simultaneous root exudation and nutrient absorption; (ii) multi-state biomass fractions in soil (i.e. living, dormant, and dead biological and root materials); (iii) expression of three-dimensional fluxes to represent both vertical and lateral interconnected flows and processes; and (iv) the potential to include the influence of non-stationary external forcing and climatic factors. We anticipate that the resulting model will demonstrate the extensive effects of plant root dynamics on ecohydrologic functions at the watershed scale and will ultimately contribute to a better characterization of efflux from both agricultural and natural systems.
Bifactor Approach to Modeling Multidimensionality of Physical Self-Perception Profile

ERIC Educational Resources Information Center

Chung, ChihMing; Liao, Xiaolan; Song, Hairong; Lee, Taehun

2016-01-01

The multi-dimensionality of Physical Self-Perception Profile (PSPP) has been acknowledged by the use of correlated-factor model and second-order model. In this study, the authors critically endorse the bifactor model, as a substitute to address the multi-dimensionality of PSPP. To cross-validate the models, analyses are conducted first in…
The prevalence and structure of obsessive-compulsive personality disorder in Hispanic psychiatric outpatients

PubMed Central

Ansell, Emily B.; Pinto, Anthony; Crosby, Ross D.; Becker, Daniel F.; Añez, Luis M.; Paris, Manuel; Grilo, Carlos M.

2010-01-01

This study sought to confirm a multi-factor model of Obsessive-compulsive personality disorder (OCPD) in a Hispanic outpatient sample and to explore associations of the OCPD factors with aggression, depression, and suicidal thoughts. One hundred and thirty monolingual, Spanish-speaking participants were recruited from a community mental health center and were assessed by bilingual doctoral level clinicians. OCPD was highly prevalent (26%) in this sample. Multi-factor models of OCPD were tested and the two factors - perfectionism and interpersonal rigidity - provided the best model fit. Interpersonal rigidity was associated with aggression and anger while perfectionism was associated with depression and suicidal thoughts. PMID:20227063
Early Life Stress, Air Pollution, Inflammation, and Disease: An Integrative Review and Immunologic Model of Social-Environmental Adversity and Lifespan Health.

PubMed

Olvera Alvarez, Hector A; Kubzansky, Laura D; Campen, Matthew J; Slavich, George M

2018-06-03

Socially disadvantaged individuals are at greater risk for simultaneously being exposed to adverse social and environmental conditions. Although the mechanisms underlying joint effects remain unclear, one hypothesis is that toxic social and environmental exposures have synergistic effects on inflammatory processes that underlie the development of chronic diseases, including cardiovascular disease, diabetes, depression, and certain types of cancer. In the present review, we examine how exposure to two risk factors that commonly occur with social disadvantage-early life stress and air pollution-affect health. Specifically, we identify neuroimmunologic pathways that could link early life stress, inflammation, air pollution, and poor health, and use this information to propose an integrated, multi-level model that describes how these factors may interact and cause health disparity across individuals based on social disadvantage. This model highlights the importance of interdisciplinary research considering multiple exposures across domains and the potential for synergistic, cross-domain effects on health, and may help identify factors that could potentially be targeted to reduce disease risk and improve lifespan health. Copyright © 2018. Published by Elsevier Ltd.

Entangled time in flocking: Multi-time-scale interaction reveals emergence of inherent noise

PubMed Central

Murakami, Hisashi

2018-01-01

Collective behaviors that seem highly ordered and result in collective alignment, such as schooling by fish and flocking by birds, arise from seamless shuffling (such as super-diffusion) and bustling inside groups (such as Lévy walks). However, such noisy behavior inside groups appears to preclude the collective behavior: intuitively, we expect that noisy behavior would lead to the group being destabilized and broken into small sub groups, and high alignment seems to preclude shuffling of neighbors. Although statistical modeling approaches with extrinsic noise, such as the maximum entropy approach, have provided some reasonable descriptions, they ignore the cognitive perspective of the individuals. In this paper, we try to explain how the group tendency, that is, high alignment, and highly noisy individual behavior can coexist in a single framework. The key aspect of our approach is multi-time-scale interaction emerging from the existence of an interaction radius that reflects short-term and long-term predictions. This multi-time-scale interaction is a natural extension of the attraction and alignment concept in many flocking models. When we apply this method in a two-dimensional model, various flocking behaviors, such as swarming, milling, and schooling, emerge. The approach also explains the appearance of super-diffusion, the Lévy walk in groups, and local equilibria. At the end of this paper, we discuss future developments, including extending our model to three dimensions. PMID:29689074
Ground-Based Telescope Parametric Cost Model

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.
Multi-agent modeling and simulation of farmland use change in the farming-pastoral zone: A case study of Qianjingou Town in Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Yan, H.

2015-12-01

Farmland is the most basic material conditions for guaranteeing rural livelihoods and national food security, and exploring management strategies that take both of the sustainable rural livelihoods and sustainable farmland use into account has vital significance of theory and practice. Farmland is a complex and self-adaptive system that couples human and natural systems together, and natural factors and social factors that are related to its changing process need to be considered when modeling farmland changing process. This paper takes Qianjingou Town in Inner Mongolia farming-pastoral zone as study area. From the perspective of the relationship between households' livelihoods and farmland use, this study builds the process mechanism of farmland use change based on questionnaires data, and constructs multi-agent simulation model of farmland use change with the help of Eclipse and Repast toolbox. Through simulating the relationship between natural factors (with geographical location) and households' behaviors, this paper systematically simulates households' renting and abandoning farmland behaviors, and truly describes dynamic interactions between households' livelihoods and factors related to farmland use change. These factors include natural factors (net primary productivity, road accessibility, slope and relief amplitude) and social factors (households' family structures, economic development and government policies). In the end, this study scientifically predicts farmland use change trend in the future 30 years. The simulation results show that, the number of abandoned and sublet farmland plots has a gradually increasing trend, the number of non-farm households and pure-outwork households has a remarkable increasing trend, and the number of part-farm households and pure-farm households shows a decreasing trend. Households' livelihoods sustainability in the study area is confronted with increasing pressure, and households' nonfarm employment has an increasing trend, while regional appropriate-scale agricultural management can be maintained. The research results establish the theory foundation and basic method for developing sustainable farmland use managements that can both meet households' willing and guarantee grain and ecology security.
Recent Developments in Smart Adaptive Structures for Solar Sailcraft

NASA Technical Reports Server (NTRS)

Whorton, M. S.; Kim, Y. K.; Oakley, J.; Adetona, O.; Keel, L. H.

2007-01-01

The "Smart Adaptive Structures for Solar Sailcraft" development activity at MSFC has investigated issues associated with understanding how to model and scale the subsystem and multi-body system dynamics of a gossamer solar sailcraft with the objective of designing sailcraft attitude control systems. This research and development activity addressed three key tasks that leveraged existing facilities and core competencies of MSFC to investigate dynamics and control issues of solar sails. Key aspects of this effort included modeling and testing of a 30 m deployable boom; modeling of the multi-body system dynamics of a gossamer sailcraft; investigation of control-structures interaction for gossamer sailcraft; and development and experimental demonstration of adaptive control technologies to mitigate control-structures interaction.
Advancing a sociotechnical systems approach to workplace safety – developing the conceptual framework

PubMed Central

Carayon, Pascale; Hancock, Peter; Leveson, Nancy; Noy, Ian; Sznelwar, Laerte; van Hootegem, Geert

2015-01-01

Traditional efforts to deal with the enormous problem of workplace safety have proved insufficient, as they have tended to neglect the broader sociotechnical environment that surrounds workers. Here, we advocate a sociotechnical systems approach that describes the complex multi-level system factors that contribute to workplace safety. From the literature on sociotechnical systems, complex systems and safety, we develop a sociotechnical model of workplace safety with concentric layers of the work system, socio-organisational context and the external environment. The future challenges that are identified through the model are highlighted. Practitioner Summary: Understanding the environmental, organisational and work system factors that contribute to workplace safety will help to develop more effective and integrated solutions to deal with persistent workplace safety problems. Solutions to improve workplace safety need to recognise the broad sociotechnical system and the respective interactions between the system elements and levels. PMID:25831959
Advancing a sociotechnical systems approach to workplace safety--developing the conceptual framework.

PubMed

Carayon, Pascale; Hancock, Peter; Leveson, Nancy; Noy, Ian; Sznelwar, Laerte; van Hootegem, Geert

2015-01-01

Traditional efforts to deal with the enormous problem of workplace safety have proved insufficient, as they have tended to neglect the broader sociotechnical environment that surrounds workers. Here, we advocate a sociotechnical systems approach that describes the complex multi-level system factors that contribute to workplace safety. From the literature on sociotechnical systems, complex systems and safety, we develop a sociotechnical model of workplace safety with concentric layers of the work system, socio-organisational context and the external environment. The future challenges that are identified through the model are highlighted. Understanding the environmental, organisational and work system factors that contribute to workplace safety will help to develop more effective and integrated solutions to deal with persistent workplace safety problems. Solutions to improve workplace safety need to recognise the broad sociotechnical system and the respective interactions between the system elements and levels.
Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups.

PubMed

Shiao, S Pamela K; Grayson, James; Yu, Chong Ho; Wasek, Brandi; Bottiglieri, Teodoro

2018-02-16

For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene-environment interactions and predictors of colorectal cancer (CRC) by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black). We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls ( p < 0.05), on MTHFR C677T , MTR A2756G , MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05) except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike's information criterion and leave-one-out cross validation methods. Body mass index (BMI) and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene-environment interactions in the prevention of CRC.
Year of Tropical Convection (YOTC): Status and Research Agenda

NASA Astrophysics Data System (ADS)

Moncrieff, M. W.; Waliser, D. E.

2009-12-01

The realistic representation of tropical convection in global models is a long-standing challenge for numerical weather prediction and an emerging grand challenge for climate prediction in respect to its physical basis. Insufficient knowledge and practical capabilities in this area disadvantage the modeling and prediction of prominent multi-scale phenomena such as the ITCZ, ENSO, monsoons and their active/break periods, the MJO, subtropical stratus decks, near-surface ocean properties, and tropical cyclones. Science elements include the diurnal cycle of precipitation, multi-scale convective organization, the global energy and water cycle, and interaction between the tropics and extra-tropics which interact strongly on timescales of weeks-to-months: the intersection of weather and climate. To address such challenges, the WCRP and WWRP/THORPEX are conducting a joint international research project, the Year of Tropical Convection (YOTC) which is a coordinated observing, modeling and forecasting project. The focus-year and integrated framework is intended to exploit the vast observational datasets, the modern high-resolution modeling frameworks, and theoretical insights. The over-arching objective is to advance the characterization, diagnosis, modeling, parameterization and prediction of multi-scale organized tropical phenomena and their interaction with the global circulation. The “Year” (May 2008 - April 2010) is intended to leverage recent major investments in Earth Science infrastructure and overlapping observational activities, e.g., Asian Monsoon Years (AMY) and the THORPEX Pacific Asian Regional Campaign (T-PARC). The research agenda involves phenomena and scale-interactions that are problematic for prediction models and have important socio-economic implications: MJO and convectively coupled equatorial waves; easterly waves and tropical cyclones; the monsoons including their intraseasonal variability; the diurnal cycle of precipitation; and two-way tropical-extratropical interaction. This presentation will summarize the status of the above.
Visualising landscape evolution: the effects of resolution on soil redistribution

NASA Astrophysics Data System (ADS)

Schoorl, Jeroen M.; Claessens, Lieven; (A) Veldkamp, Tom

2017-04-01

Landscape forming processes such as erosion by water, land sliding by water and gravity or ploughing by gravity, are closely related to resolution and land use changes. These processes may be controlled and influenced by multiple bio-physical and socio-economic driving factors, resulting in a complex multi-scale system. Consequently, land use changes should not be analysed in isolation without accounting for both on-site and off-site effects of these landscape processes in landscapes where water driven and or gravity driven processes are very active,. Especially the visualisation of these on- and off-site effects as a movie of evolving time series and changes is a potential valuable possibility in DEM modelling approaches. To investigate the interactions between land use, land use change, resolution of DEMs and landscape processes, a case study for the Álora region in southern Spain will presented, mainly as movies of modelling time-series, Starting from a baseline scenario of land use change, different levels of resolutions, interactions and feedbacks are added to the coupled LAPSUS model framework: Quantities and spatial patterns of both land use change and soil redistribution are compared between the baseline scenario without interactions and with each of the interaction mechanisms implemented consecutively. All as a function of spatial resolution. Keywords: LAPSUS; land use change; soil erosion, movie;
Multi Modal Anticipation in Fuzzy Space

NASA Astrophysics Data System (ADS)

Asproth, Viveca; Holmberg, Stig C.; Hâkansson, Anita

2006-06-01

We are all stakeholders in the geographical space, which makes up our common living and activity space. This means that a careful, creative, and anticipatory planning, design, and management of that space will be of paramount importance for our sustained life on earth. Here it is shown that the quality of such planning could be significantly increased with help of a computer based modelling and simulation tool. Further, the design and implementation of such a tool ought to be guided by the conceptual integration of some core concepts like anticipation and retardation, multi modal system modelling, fuzzy space modelling, and multi actor interaction.
Coupling a three-dimensional subsurface flow model with a land surface model to simulate stream-aquifer-land interactions

NASA Astrophysics Data System (ADS)

Huang, M.; Bisht, G.; Zhou, T.; Chen, X.; Dai, H.; Hammond, G. E.; Riley, W. J.; Downs, J.; Liu, Y.; Zachara, J. M.

2016-12-01

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively-parallel multi-physics reactive tranport model (PFLOTRAN). The coupled model (CLM-PFLOTRAN) is applied to a 400m×400m study domain instrumented with groundwater monitoring wells in the Hanford 300 Area along the Columbia River. CLM-PFLOTRAN simulations are performed at three different spatial resolutions over the period 2011-2015 to evaluate the impact of spatial resolution on simulated variables. To demonstrate the difference in model simulations with and without lateral subsurface flow, a vertical-only CLM-PFLOTRAN simulation is also conducted for comparison. Results show that the coupled model is skillful in simulating stream-aquifer interactions, and the land-surface energy partitioning can be strongly modulated by groundwater-river water interactions in high water years due to increased soil moisture availability caused by elevated groundwater table. In addition, spatial resolution does not seem to impact the land surface energy flux simulations, although it is a key factor for accurately estimating the mass exchange rates at the boundaries and associated biogeochemical reactions in the aquifer. The coupled model developed in this study establishes a solid foundation for understanding co-evolution of hydrology and biogeochemistry along the river corridors under historical and future hydro-climate changes.
Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.
Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

PubMed Central

Wen, Xiaotong; Rangarajan, Govindan; Ding, Mingzhou

2013-01-01

Granger causality is increasingly being applied to multi-electrode neurophysiological and functional imaging data to characterize directional interactions between neurons and brain regions. For a multivariate dataset, one might be interested in different subsets of the recorded neurons or brain regions. According to the current estimation framework, for each subset, one conducts a separate autoregressive model fitting process, introducing the potential for unwanted variability and uncertainty. In this paper, we propose a multivariate framework for estimating Granger causality. It is based on spectral density matrix factorization and offers the advantage that the estimation of such a matrix needs to be done only once for the entire multivariate dataset. For any subset of recorded data, Granger causality can be calculated through factorizing the appropriate submatrix of the overall spectral density matrix. PMID:23858479
Side-chain conformational space analysis (SCSA): A multi conformation-based QSAR approach for modeling and prediction of protein-peptide binding affinities

NASA Astrophysics Data System (ADS)

Zhou, Peng; Chen, Xiang; Shang, Zhicai

2009-03-01

In this article, the concept of multi conformation-based quantitative structure-activity relationship (MCB-QSAR) is proposed, and based upon that, we describe a new approach called the side-chain conformational space analysis (SCSA) to model and predict protein-peptide binding affinities. In SCSA, multi-conformations (rather than traditional single-conformation) have received much attention, and the statistical average information on multi-conformations of side chains is determined using self-consistent mean field theory based upon side chain rotamer library. Thereby, enthalpy contributions (including electrostatic, steric, hydrophobic interaction and hydrogen bond) and conformational entropy effects to the binding are investigated in terms of occurrence probability of residue rotamers. Then, SCSA was applied into the dataset of 419 HLA-A*0201 binding peptides, and nonbonding contributions of each position in peptide ligands are well determined. For the peptides, the hydrogen bond and electrostatic interactions of the two ends are essential to the binding specificity, van der Waals and hydrophobic interactions of all the positions ensure strong binding affinity, and the loss of conformational entropy at anchor positions partially counteracts other favorable nonbonding effects.
[Multilevel model analysis on the relevant factors influencing the total amount of drinking water consumed daily by Beijing residents].

PubMed

Zhao, Jinhui; Wei, Jianrong; Chen, Huajie; Liu, Yumin; Li, Tiantian; Sun, Qinghua; Liu, Qiaolan

2012-09-01

To investigate the influencing factors for daily water intake of Beijing residents. A multi-stage sampling method was constructed to interview 270 Beijing residents in the winter of 2009 and in the summer of 2010 by using a questionnaire to collect data on daily drinking water consumption. Multilevel models were used to analyze the variation and influencing factors for the amount of water intake. Multilevel model results showed that the average daily water intake of residents living in different villages or neighborhood committees was statistically significant (sigma2 mu0 = = 0.030 (0.009), P < 0.05). The individual variation in the same village or neighborhood committee was also significant (sigma2 e0 = 0.157 (0.010), P < 0.05). Season, gender, and body weight affected the daily water intake (P < 0.05). There were interaction between season and source of water supply. The average daily water intake of residents was affected by several factors. In the health risk assessment of drinking water, it needs considering not only the individual characteristics but also the differences of villages/neighborhood committees and the seasonal variation.
Multi-criteria ranking and receptor modelling of airborne fine particles at three sites in the Pearl River Delta region of China.

PubMed

Friend, Adrian J; Ayoko, Godwin A; Guo, Hai

2011-01-15

The multi-criteria decision making methods, Preference Ranking Organization METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site>urban site>roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8±8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region. Copyright © 2010 Elsevier B.V. All rights reserved.
Role of motivation to respond to provocation, the social environment, and trait aggression in alcohol-related aggression.

PubMed

Tremblay, Paul F; Mihic, Ljiljana; Graham, Kathryn; Jelley, Jennifer

2007-01-01

Little attention has been paid to the motivation to respond to provocation and to the interaction between this motivation, alcohol, the drinking environment, and individual characteristics. Undergraduates at six Canadian universities (N = 1,232) read three vignettes describing conflict situations with social environmental manipulations while imagining themselves as either sober or intoxicated. Self-ratings assessed likelihood of assertive and aggressive responses and motivational indices of anger, offensiveness of the instigator's actions, and importance to respond to the provocation. Respondents also completed a measure of trait aggression. Multi-group structural equation models supported the hypothesis that perceived likelihood of reactive aggression is influenced by perceived alcohol intoxication, gender, trait aggression, social environmental factors, and motivation to respond to the provocation. In addition, a number of interactions were found among the predictors. These results provide insight into the types of factors that may influence aggression in drinking situations. Copyright 2007 Wiley-Liss, Inc.
[The system-oriented model of psychosocial rehabilitation].

PubMed

Iastrebov V S; Mitikhin, V G; Solokhina, T A; Mikhaĭlova, I I

2008-01-01

A model of psychosocial rehabilitation based on the system approach that allows taking into account both the patient-centered approach of the rehabilitation service, the development of its resource basis, the effectiveness of this care system in whole and its patterns as well has been worked out. In the framework of this model, the authors suggest to single out three basic stages of the psychosocial rehabilitation process: evaluation and planning, rehabilitation interventions per se, achievement of the result. In author's opinion, the most successful way for constructing a modern model of psychosocial rehabilitation is a method of hierarchic modeling which can reveal a complex chain of interactions between all participants of the rehabilitation process and factors involved in this process and at the same time specify the multi-level hierarchic character of these interactions and factors. An important advantage of this method is the possibility of obtaining as static as well dynamic evaluations of the rehabilitation service activity that may be used on the following levels: 1) patient; 2) his/her close environment; 3) macrosocial level. The obvious merits of the system-oriented model appear to be the possibility of application of its principles in the organization of specialized care for psychiatric patients on the local, regional and federal levels. The authors emphasize that hierarchic models have universal character and can be implemented in the elaboration of information-analytical systems aimed at solving the problems of monitoring and analysis of social-medical service activity in order to increase its effectiveness.
Implementation of 5-layer thermal diffusion scheme in weather research and forecasting model with Intel Many Integrated Cores

NASA Astrophysics Data System (ADS)

Huang, Melin; Huang, Bormin; Huang, Allen H.

2014-10-01

For weather forecasting and research, the Weather Research and Forecasting (WRF) model has been developed, consisting of several components such as dynamic solvers and physical simulation modules. WRF includes several Land- Surface Models (LSMs). The LSMs use atmospheric information, the radiative and precipitation forcing from the surface layer scheme, the radiation scheme, and the microphysics/convective scheme all together with the land's state variables and land-surface properties, to provide heat and moisture fluxes over land and sea-ice points. The WRF 5-layer thermal diffusion simulation is an LSM based on the MM5 5-layer soil temperature model with an energy budget that includes radiation, sensible, and latent heat flux. The WRF LSMs are very suitable for massively parallel computation as there are no interactions among horizontal grid points. The features, efficient parallelization and vectorization essentials, of Intel Many Integrated Core (MIC) architecture allow us to optimize this WRF 5-layer thermal diffusion scheme. In this work, we present the results of the computing performance on this scheme with Intel MIC architecture. Our results show that the MIC-based optimization improved the performance of the first version of multi-threaded code on Xeon Phi 5110P by a factor of 2.1x. Accordingly, the same CPU-based optimizations improved the performance on Intel Xeon E5- 2603 by a factor of 1.6x as compared to the first version of multi-threaded code.
Obese parents--obese children? Psychological-psychiatric risk factors of parental behavior and experience for the development of obesity in children aged 0-3: study protocol.

PubMed

Grube, Matthias; Bergmann, Sarah; Keitel, Anja; Herfurth-Majstorovic, Katharina; Wendt, Verena; von Klitzing, Kai; Klein, Annette M

2013-12-17

The incidences of childhood overweight and obesity have increased substantially and with them the prevalence of associated somatic and psychiatric health problems. Therefore, it is important to identify modifiable risk factors for early childhood overweight in order to develop effective prevention or intervention programs. Besides biological factors, familial interactions and parental behavioral patterns may influence children's weight development. Longitudinal investigation of children at overweight risk could help to detect significant risk and protective factors. We aim to describe infants' weight development over time and identify risk and protective factors for the incidence of childhood obesity. Based on our findings we will draw up a risk model that will lay the foundation for an intervention/prevention program. We present the protocol of a prospective longitudinal study in which we investigate families with children aged from 6 months to 47 months. In half of the families at least one parent is obese (risk group), in the other half both parents are normal weight (control group). Based on developmental and health-psychological models, we consider measurements at three levels: the child, the parents and parent-child-relationship. Three assessment points are approximately one year apart. At each assessment point we evaluate the psychological, social, and behavioral situation of the parents as well as the physical and psychosocial development of the child. Parents are interviewed, fill in questionnaires, and take part in standardized interaction tasks with their child in a feeding and in a playing context in our research laboratory. The quality of these video-taped parent-child interactions is assessed by analyzing them with standardized, validated instruments according to scientific standards. Strengths of the presented study are the prospective longitudinal design, the multi-informant approach, including the fathers, and the observation of parent-child interaction. A limitation is the variation in children's age.

Obese parents – obese children? Psychological-psychiatric risk factors of parental behavior and experience for the development of obesity in children aged 0–3: study protocol

PubMed Central

2013-01-01

Background The incidences of childhood overweight and obesity have increased substantially and with them the prevalence of associated somatic and psychiatric health problems. Therefore, it is important to identify modifiable risk factors for early childhood overweight in order to develop effective prevention or intervention programs. Besides biological factors, familial interactions and parental behavioral patterns may influence children’s weight development. Longitudinal investigation of children at overweight risk could help to detect significant risk and protective factors. We aim to describe infants’ weight development over time and identify risk and protective factors for the incidence of childhood obesity. Based on our findings we will draw up a risk model that will lay the foundation for an intervention/prevention program. Methods/Design We present the protocol of a prospective longitudinal study in which we investigate families with children aged from 6 months to 47 months. In half of the families at least one parent is obese (risk group), in the other half both parents are normal weight (control group). Based on developmental and health-psychological models, we consider measurements at three levels: the child, the parents and parent–child-relationship. Three assessment points are approximately one year apart. At each assessment point we evaluate the psychological, social, and behavioral situation of the parents as well as the physical and psychosocial development of the child. Parents are interviewed, fill in questionnaires, and take part in standardized interaction tasks with their child in a feeding and in a playing context in our research laboratory. The quality of these video-taped parent–child interactions is assessed by analyzing them with standardized, validated instruments according to scientific standards. Discussion Strengths of the presented study are the prospective longitudinal design, the multi-informant approach, including the fathers, and the observation of parent–child interaction. A limitation is the variation in children’s age. PMID:24341703
Scaling and criticality in a stochastic multi-agent model of a financial market

NASA Astrophysics Data System (ADS)

Lux, Thomas; Marchesi, Michele

1999-02-01

Financial prices have been found to exhibit some universal characteristics that resemble the scaling laws characterizing physical systems in which large numbers of units interact. This raises the question of whether scaling in finance emerges in a similar way - from the interactions of a large ensemble of market participants. However, such an explanation is in contradiction to the prevalent `efficient market hypothesis' in economics, which assumes that the movements of financial prices are an immediate and unbiased reflection of incoming news about future earning prospects. Within this hypothesis, scaling in price changes would simply reflect similar scaling in the `input' signals that influence them. Here we describe a multi-agent model of financial markets which supports the idea that scaling arises from mutual interactions of participants. Although the `news arrival process' in our model lacks both power-law scaling and any temporal dependence in volatility, we find that it generates such behaviour as a result of interactions between agents.
Habitat-based constraints on food web structure and parasite life cycles.

PubMed

Rossiter, Wayne; Sukhdeo, Michael V K

2014-04-01

Habitat is frequently implicated as a powerful determinant of community structure and species distributions, but few studies explicitly evaluate the relationship between habitat-based patterns of species' distributions and the presence or absence of trophic interactions. The complex (multi-host) life cycles of parasites are directly affected by these factors, but almost no data exist on the role of habitat in constraining parasite-host interactions at the community level. In this study the relationship(s) between species abundances, distributions and trophic interactions (including parasitism) were evaluated in the context of habitat structure (classic geomorphic designations of pools, riffles and runs) in a riverine community (Raritan River, Hunterdon County, NJ, USA). We report 121 taxa collected over a 2-year period, and compare the observed food web patterns to null model expectations. The results show that top predators are constrained to particular habitat types, and that species' distributions are biased towards pool habitats. However, our null model (which incorporates cascade model assumptions) accurately predicts the observed patterns of trophic interactions. Thus, habitat strongly dictates species distributions, and patterns of trophic interactions arise as a consequence of these distributions. Additionally, we find that hosts utilized in parasite life cycles are more overlapping in their distributions, and this pattern is more pronounced among those involved in trophic transmission. We conclude that habitat structure may be a strong predictor of parasite transmission routes, particularly within communities that occupy heterogeneous habitats.
The effect of desolvation on the binding of inhibitors to HIV-1 protease and cyclin-dependent kinases: Causes of resistance.

PubMed

Fong, Clifford W

2016-08-01

Studies of the cyclin-dependent kinase inhibitors and HIV-1 protease inhibitors have confirmed that ligand-protein binding is dependent on desolvation effects. It has been found that a four parameter linear model incorporating desolvation energy, lipophilicity, dipole moment and molecular volume of the ligands is a good model to describe the binding between ligands and kinases or proteases. The resistance shown by MDR proteases to the anti-viral drugs is multi-faceted involving varying changes in desolvation, lipophilicity and dipole moment interaction compared to the non-resistant protease. Desolvation has been shown to be the dominant factor influencing the effect of inhibitors against the cyclin-dependent kinases, but lipophilicity and dipole moment are also significant factors. The model can differentiate between the inhibitory activity of CDK2/cycE, CDK1/cycB and CDK4/cycD enzymes. Copyright © 2016 Elsevier Ltd. All rights reserved.
Long Island Sound Tropospheric Ozone Study (LISTOS) Fact Sheet

EPA Pesticide Factsheets

EPA scientists are collaborating on a multi-agency field study to investigate the complex interaction of emissions, chemistry and meteorological factors contributing to elevated ozone levels along the Long Island Sound shoreline.
Uranium plume persistence impacted by hydrologic and geochemical heterogeneity in the groundwater and river water interaction zone of Hanford site

NASA Astrophysics Data System (ADS)

Chen, X.; Zachara, J. M.; Vermeul, V. R.; Freshley, M.; Hammond, G. E.

2015-12-01

The behavior of a persistent uranium plume in an extended groundwater- river water (GW-SW) interaction zone at the DOE Hanford site is dominantly controlled by river stage fluctuations in the adjacent Columbia River. The plume behavior is further complicated by substantial heterogeneity in physical and geochemical properties of the host aquifer sediments. Multi-scale field and laboratory experiments and reactive transport modeling were integrated to understand the complex plume behavior influenced by highly variable hydrologic and geochemical conditions in time and space. In this presentation we (1) describe multiple data sets from field-scale uranium adsorption and desorption experiments performed at our experimental well-field, (2) develop a reactive transport model that incorporates hydrologic and geochemical heterogeneities characterized from multi-scale and multi-type datasets and a surface complexation reaction network based on laboratory studies, and (3) compare the modeling and observation results to provide insights on how to refine the conceptual model and reduce prediction uncertainties. The experimental results revealed significant spatial variability in uranium adsorption/desorption behavior, while modeling demonstrated that ambient hydrologic and geochemical conditions and heterogeneities in sediment physical and chemical properties both contributed to complex plume behavior and its persistence. Our analysis provides important insights into the characterization, understanding, modeling, and remediation of groundwater contaminant plumes influenced by surface water and groundwater interactions.
Theoretical basal Ca II fluxes for late-type stars: results from magnetic wave models with time-dependent ionization and multi-level radiation treatments

NASA Astrophysics Data System (ADS)

Fawzy, Diaa E.; Stȩpień, K.

2018-03-01

In the current study we present ab initio numerical computations of the generation and propagation of longitudinal waves in magnetic flux tubes embedded in the atmospheres of late-type stars. The interaction between convective turbulence and the magnetic structure is computed and the obtained longitudinal wave energy flux is used in a self-consistent manner to excite the small-scale magnetic flux tubes. In the current study we reduce the number of assumptions made in our previous studies by considering the full magnetic wave energy fluxes and spectra as well as time-dependent ionization (TDI) of hydrogen, employing multi-level Ca II atomic models, and taking into account departures from local thermodynamic equilibrium. Our models employ the recently confirmed value of the mixing-length parameter α=1.8. Regions with strong magnetic fields (magnetic filling factors of up to 50%) are also considered in the current study. The computed Ca II emission fluxes show a strong dependence on the magnetic filling factors, and the effect of time-dependent ionization (TDI) turns out to be very important in the atmospheres of late-type stars heated by acoustic and magnetic waves. The emitted Ca II fluxes with TDI included into the model are decreased by factors that range from 1.4 to 5.5 for G0V and M0V stars, respectively, compared to models that do not consider TDI. The results of our computations are compared with observations. Excellent agreement between the observed and predicted basal flux is obtained. The predicted trend of Ca II emission flux with magnetic filling factor and stellar surface temperature also agrees well with the observations but the calculated maximum fluxes for stars of different spectral types are about two times lower than observations. Though the longitudinal MHD waves considered here are important for chromosphere heating in high activity stars, additional heating mechanism(s) are apparently present.
Asymptotic behaviour of two-point functions in multi-species models

NASA Astrophysics Data System (ADS)

Kozlowski, Karol K.; Ragoucy, Eric

2016-05-01

We extract the long-distance asymptotic behaviour of two-point correlation functions in massless quantum integrable models containing multi-species excitations. For such a purpose, we extend to these models the method of a large-distance regime re-summation of the form factor expansion of correlation functions. The key feature of our analysis is a technical hypothesis on the large-volume behaviour of the form factors of local operators in such models. We check the validity of this hypothesis on the example of the SU (3)-invariant XXX magnet by means of the determinant representations for the form factors of local operators in this model. Our approach confirms the structure of the critical exponents obtained previously for numerous models solvable by the nested Bethe Ansatz.
Multi-Agent Framework for Virtual Learning Spaces.

ERIC Educational Resources Information Center

Sheremetov, Leonid; Nunez, Gustavo

1999-01-01

Discussion of computer-supported collaborative learning, distributed artificial intelligence, and intelligent tutoring systems focuses on the concept of agents, and describes a virtual learning environment that has a multi-agent system. Describes a model of interactions in collaborative learning and discusses agents for Web-based virtual…
Multi-scale modeling in cell biology

PubMed Central

Meier-Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick

2009-01-01

Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling. PMID:20448808
Multi-Scale Multi-Domain Model | Transportation Research | NREL

Science.gov Websites

framework for NREL's MSMD model. NREL's MSMD model quantifies the impacts of electrical/thermal pathway : NREL Macroscopic design factors and highly dynamic environmental conditions significantly influence the design of affordable, long-lasting, high-performing, and safe large battery systems. The MSMD framework
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.
The prevalence and structure of obsessive-compulsive personality disorder in Hispanic psychiatric outpatients.

PubMed

Ansell, Emily B; Pinto, Anthony; Crosby, Ross D; Becker, Daniel F; Añez, Luis M; Paris, Manuel; Grilo, Carlos M

2010-09-01

This study sought to confirm a multi-factor model of Obsessive-compulsive personality disorder (OCPD) in a Hispanic outpatient sample and to explore associations of the OCPD factors with aggression, depression, and suicidal thoughts. One hundred and thirty monolingual, Spanish-speaking participants were recruited from a community mental health center and were assessed by bilingual doctoral-level clinicians. OCPD was highly prevalent (26%) in this sample. Multi-factor models of OCPD were tested and the two factors - perfectionism and interpersonal rigidity - provided the best model fit. Interpersonal rigidity was associated with aggression and anger while perfectionism was associated with depression and suicidal thoughts. (c) 2010 Elsevier Ltd. All rights reserved.
Characteristics of Behavior of Robots with Emotion Model

NASA Astrophysics Data System (ADS)

Sato, Shigehiko; Nozawa, Akio; Ide, Hideto

Cooperated multi robots system has much dominance in comparison with single robot system. It is able to adapt to various circumstances and has a flexibility for variation of tasks. However it has still problems to control each robot, though methods for control multi robots system have been studied. Recently, the robots have been coming into real scene. And emotion and sensitivity of the robots have been widely studied. In this study, human emotion model based on psychological interaction was adapt to multi robots system to achieve methods for organization of multi robots. The characteristics of behavior of multi robots system achieved through computer simulation were analyzed. As a result, very complexed and interesting behavior was emerged even though it has rather simple configuration. And it has flexiblity in various circumstances. Additional experiment with actual robots will be conducted based on the emotion model.
Influences of coupled fire-atmosphere interaction on wildfire behavior

NASA Astrophysics Data System (ADS)

Linn, R.; Winterkamp, J.; Jonko, A. K.; Runde, I.; Canfield, J.; Parsons, R.; Sieg, C.

2017-12-01

Two-way interactions between fire and the environment affect fire behavior at scales ranging from buoyancy-induced mixing and turbulence to fire-scale circulations that retard or increase fire spread. Advances in computing have created new opportunities for the exploration of coupled fire-atmosphere behavior using numerical models that represent interactions between the dominant processes driving wildfire behavior, including convective and radiative heat transfer, aerodynamic drag and buoyant response of the atmosphere to heat released by the fire. Such models are not practical for operational, faster-than-real-time fire prediction due to their computational and data requirements. However, they are valuable tools for exploring influences of fire-atmosphere feedbacks on fire behavior as they explicitly simulate atmospheric motions surrounding fires from meter to kilometer scales. We use the coupled fire-atmosphere model FIRETEC to gain new insights into aspects of fire behavior that have been observed in the field and laboratory, to carry out sensitivity analysis that is impractical through observations and to pose new hypotheses that can be tested experimentally. Specifically, we use FIRETEC to study the following multi-scale coupled fire-atmosphere interactions: 1) 3D fire-atmosphere interaction that dictates multi-scale fire line dynamics; 2) influence of vegetation heterogeneity and variability in wind fields on predictability of fire spread; 3) fundamental impacts of topography on fire spread. These numerical studies support new conceptual models for the dominant roles of multi-scale fluid dynamics in determining fire spread, including the roles of crosswind fire line-intensity variations on heat transfer to unburned fuels and the role of fire line depth expansion in upslope acceleration of fires.
A hybrid formulation for the numerical simulation of condensed phase explosives

NASA Astrophysics Data System (ADS)

Michael, L.; Nikiforakis, N.

2016-07-01

In this article we present a new formulation and an associated numerical algorithm, for the simulation of combustion and transition to detonation of condensed-phase commercial- and military-grade explosives, which are confined by (or in general interacting with one or more) compliant inert materials. Examples include confined rate-stick problems and interaction of shock waves with gas cavities or solid particles in explosives. This formulation is based on an augmented Euler approach to account for the mixture of the explosive and its products, and a multi-phase diffuse interface approach to solve for the immiscible interaction between the mixture and the inert materials, so it is in essence a hybrid (augmented Euler and multi-phase) model. As such, it has many of the desirable features of the two approaches and, critically for our applications of interest, it provides the accurate recovery of temperature fields across all components. Moreover, it conveys a lot more physical information than augmented Euler, without the complexity of full multi-phase Baer-Nunziato-type models or the lack of robustness of augmented Euler models in the presence of more than two components. The model can sustain large density differences across material interfaces without the presence of spurious oscillations in velocity and pressure, and it can accommodate realistic equations of state and arbitrary (pressure- or temperature-based) reaction-rate laws. Under certain conditions, we show that the formulation reduces to well-known augmented Euler or multi-phase models, which have been extensively validated and used in practice. The full hybrid model and its reduced forms are validated against problems with exact (or independently-verified numerical) solutions and evaluated for robustness for rate-stick and shock-induced cavity collapse case-studies.
Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

The following reports are presented on this project:A first year progress report on: Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; A second year progress report on: Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design; Interactive, Secure Web-enabled Aircraft Engine Simulation Using XML Databinding Integration; and Improving the Aircraft Design Process Using Web-based Modeling and Simulation.
Scoring functions for protein-protein interactions.

PubMed

Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.
The triel bond: a potential force for tuning anion-π interactions

NASA Astrophysics Data System (ADS)

Esrafili, Mehdi D.; Mousavian, Parisasadat

2018-02-01

Using ab-initio calculations, the mutual influence between anion-π and B···N or B···C triel bond interactions is investigated in some model complexes. The properties of these complexes are studied by molecular electrostatic potential, noncovalent interaction index, quantum theory of atoms in molecules (QTAIM) and natural bond orbital (NBO) analyses. According to the results, the formation of B···N or B···C triel bond interactions in the multi-component systems makes a significant shortening of anion-π distance. Such remarkable variation in the anion-π distances has not been reported previously. The strengthening of the anion-π bonding in the multi-component systems depend significantly on the nature of the anion, and it becomes larger in the order Br- > Cl- > F-. The parameters derived from the QTAIM and NBO methodologies are used to study the mechanism of the cooperativity between the anion-π and triel bond interactions in the multi-component complexes.
A relativistically interacting exactly solvable multi-time model for two massless Dirac particles in 1 + 1 dimensions

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

Lienert, Matthias, E-mail: lienert@math.lmu.de

2015-04-15

The question how to Lorentz transform an N-particle wave function naturally leads to the concept of a so-called multi-time wave function, i.e., a map from (space-time){sup N} to a spin space. This concept was originally proposed by Dirac as the basis of relativistic quantum mechanics. In such a view, interaction potentials are mathematically inconsistent. This fact motivates the search for new mechanisms for relativistic interactions. In this paper, we explore the idea that relativistic interaction can be described by boundary conditions on the set of coincidence points of two particles in space-time. This extends ideas from zero-range physics to amore » relativistic setting. We illustrate the idea at the simplest model which still possesses essential physical properties like Lorentz invariance and a positive definite density: two-time equations for massless Dirac particles in 1 + 1 dimensions. In order to deal with a spatio-temporally non-trivial domain, a necessity in the multi-time picture, we develop a new method to prove existence and uniqueness of classical solutions: a generalized version of the method of characteristics. Both mathematical and physical considerations are combined to precisely formulate and answer the questions of probability conservation, Lorentz invariance, interaction, and antisymmetry.« less

Translational models of tumor angiogenesis: A nexus of in silico and in vitro models.

PubMed

Soleimani, Shirin; Shamsi, Milad; Ghazani, Mehran Akbarpour; Modarres, Hassan Pezeshgi; Valente, Karolina Papera; Saghafian, Mohsen; Ashani, Mehdi Mohammadi; Akbari, Mohsen; Sanati-Nezhad, Amir

2018-03-05

Emerging evidence shows that endothelial cells are not only the building blocks of vascular networks that enable oxygen and nutrient delivery throughout a tissue but also serve as a rich resource of angiocrine factors. Endothelial cells play key roles in determining cancer progression and response to anti-cancer drugs. Furthermore, the endothelium-specific deposition of extracellular matrix is a key modulator of the availability of angiocrine factors to both stromal and cancer cells. Considering tumor vascular network as a decisive factor in cancer pathogenesis and treatment response, these networks need to be an inseparable component of cancer models. Both computational and in vitro experimental models have been extensively developed to model tumor-endothelium interactions. While informative, they have been developed in different communities and do not yet represent a comprehensive platform. In this review, we overview the necessity of incorporating vascular networks for both in vitro and in silico cancer models and discuss recent progresses and challenges of in vitro experimental microfluidic cancer vasculature-on-chip systems and their in silico counterparts. We further highlight how these two approaches can merge together with the aim of presenting a predictive combinatorial platform for studying cancer pathogenesis and testing the efficacy of single or multi-drug therapeutics for cancer treatment. Copyright © 2018. Published by Elsevier Inc.
Multi-level molecular modelling for plasma medicine

NASA Astrophysics Data System (ADS)

Bogaerts, Annemie; Khosravian, Narjes; Van der Paal, Jonas; Verlackt, Christof C. W.; Yusupov, Maksudbek; Kamaraj, Balu; Neyts, Erik C.

2016-02-01

Modelling at the molecular or atomic scale can be very useful for obtaining a better insight in plasma medicine. This paper gives an overview of different atomic/molecular scale modelling approaches that can be used to study the direct interaction of plasma species with biomolecules or the consequences of these interactions for the biomolecules on a somewhat longer time-scale. These approaches include density functional theory (DFT), density functional based tight binding (DFTB), classical reactive and non-reactive molecular dynamics (MD) and united-atom or coarse-grained MD, as well as hybrid quantum mechanics/molecular mechanics (QM/MM) methods. Specific examples will be given for three important types of biomolecules, present in human cells, i.e. proteins, DNA and phospholipids found in the cell membrane. The results show that each of these modelling approaches has its specific strengths and limitations, and is particularly useful for certain applications. A multi-level approach is therefore most suitable for obtaining a global picture of the plasma-biomolecule interactions.
Probabilistic Methods for Structural Reliability and Risk

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multi-factor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.
Robots with language.

PubMed

Parisi, Domenico

2010-01-01

Trying to understand human language by constructing robots that have language necessarily implies an embodied view of language, where the meaning of linguistic expressions is derived from the physical interactions of the organism with the environment. The paper describes a neural model of language according to which the robot's behaviour is controlled by a neural network composed of two sub-networks, one dedicated to the non-linguistic interactions of the robot with the environment and the other one to processing linguistic input and producing linguistic output. We present the results of a number of simulations using the model and we suggest how the model can be used to account for various language-related phenomena such as disambiguation, the metaphorical use of words, the pervasive idiomaticity of multi-word expressions, and mental life as talking to oneself. The model implies a view of the meaning of words and multi-word expressions as a temporal process that takes place in the entire brain and has no clearly defined boundaries. The model can also be extended to emotional words if we assume that an embodied view of language includes not only the interactions of the robot's brain with the external environment but also the interactions of the brain with what is inside the body.
Study on the characteristics of multi-infeed HVDC

NASA Astrophysics Data System (ADS)

Li, Ming; Song, Xinli; Liu, Wenzhuo; Xiang, Yinxing; Zhao, Shutao; Su, Zhida; Meng, Hang

2017-09-01

China has built more than ten HVDC transmission projects in recent years [1]. Now, east China has formed a multi-HVDC feed pattern grid. It is imminent to study the interaction of the multi-HVDC and the characteristics of it. In this paper, an electromechanical-electromagnetic hybrid model is built with electromechanical data of a certain power network. We use electromagnetic models to simulate the HVDC section and electromechanical models simulate the AC power network [2]. In order to study the characteristics of the grid, this paper adds some faults to the line and analysed the fault characteristics. At last give analysis of the fault characteristics.
A 3D Multi-fluid MHD Study of the Interaction of the Solar Wind with the Ionosphere/Atmosphere System of Venus.

NASA Astrophysics Data System (ADS)

Najib, D.; Nagy, A.; Toth, G.; Ma, Y.-J.

2011-10-01

We use the latest version of our four species multifluid model to study the interaction of the solar wind with Venus. The model solves simultaneously the continuity, momentum and energy equations of the different ions. The lower boundary of our model is at 100 km, below the main ionospheric peak, and the radial resolution is about 10 km in the ionosphere, thus the model does a very good job in reproducing the ionosphere and the associated processes. We carry out calculations for high and low solar activity conditions and establish the importance of mass loading by the extended exosphere of Venus. We demonstrate the importance of using the multi-fluid rather than a single fluid model. We also calculate the atmospheric escape of the ionospheric species and compare our model results with the observed parameters from Pioneer Venus and Venus Express.
A statistical approach to the brittle fracture of a multi-phase solid

NASA Technical Reports Server (NTRS)

Liu, W. K.; Lua, Y. I.; Belytschko, T.

1991-01-01

A stochastic damage model is proposed to quantify the inherent statistical distribution of the fracture toughness of a brittle, multi-phase solid. The model, based on the macrocrack-microcrack interaction, incorporates uncertainties in locations and orientations of microcracks. Due to the high concentration of microcracks near the macro-tip, a higher order analysis based on traction boundary integral equations is formulated first for an arbitrary array of cracks. The effects of uncertainties in locations and orientations of microcracks at a macro-tip are analyzed quantitatively by using the boundary integral equations method in conjunction with the computer simulation of the random microcrack array. The short range interactions resulting from surrounding microcracks closet to the main crack tip are investigated. The effects of microcrack density parameter are also explored in the present study. The validity of the present model is demonstrated by comparing its statistical output with the Neville distribution function, which gives correct fits to sets of experimental data from multi-phase solids.
Bridge-in-a-backpack(TM) : task 3.2: investigating soil - structure interaction - modeling and experimental results of steel arches.

DOT National Transportation Integrated Search

2015-07-01

This report includes fulfillment of Task 3.2 of a multi-task contract to further enhance concrete filled FRP tubes, or : the Bridge in a Backpack. Task 3 is an investigation of soil-structure interaction for the FRP tubes. Task 3.2 is the : modeling ...
Bridge-in-a-backpack(TM) task 3.3 : investigate soil-structure interaction-modeling and experimental results of concrete filled FRP tube arches.

DOT National Transportation Integrated Search

2015-12-01

This report includes fulfillment of Task 3.3 of a multi-task contract to further enhance concrete filled FRP tubes, or : the Bridge in a Backpack. Task 3 is an investigation of soil-structure interaction for the FRP tubes. Task 3.3 is the : modeling ...
Optimal Drug Synergy in Antimicrobial Treatments

PubMed Central

Torella, Joseph Peter; Chait, Remy; Kishony, Roy

2010-01-01

The rapid proliferation of antibiotic-resistant pathogens has spurred the use of drug combinations to maintain clinical efficacy and combat the evolution of resistance. Drug pairs can interact synergistically or antagonistically, yielding inhibitory effects larger or smaller than expected from the drugs' individual potencies. Clinical strategies often favor synergistic interactions because they maximize the rate at which the infection is cleared from an individual, but it is unclear how such interactions affect the evolution of multi-drug resistance. We used a mathematical model of in vivo infection dynamics to determine the optimal treatment strategy for preventing the evolution of multi-drug resistance. We found that synergy has two conflicting effects: it clears the infection faster and thereby decreases the time during which resistant mutants can arise, but increases the selective advantage of these mutants over wild-type cells. When competition for resources is weak, the former effect is dominant and greater synergy more effectively prevents multi-drug resistance. However, under conditions of strong resource competition, a tradeoff emerges in which greater synergy increases the rate of infection clearance, but also increases the risk of multi-drug resistance. This tradeoff breaks down at a critical level of drug interaction, above which greater synergy has no effect on infection clearance, but still increases the risk of multi-drug resistance. These results suggest that the optimal strategy for suppressing multi-drug resistance is not always to maximize synergy, and that in some cases drug antagonism, despite its weaker efficacy, may better suppress the evolution of multi-drug resistance. PMID:20532210
Controlling the transmitted information of a multi-photon interacting with a single-Cooper pair box

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

Kadry, Heba, E-mail: hkadry1@yahoo.com; Abdel-Aty, Abdel-Haleem, E-mail: hkadry1@yahoo.com; Zakaria, Nordin, E-mail: hkadry1@yahoo.com

2014-10-24

We study a model of a multi-photon interaction of a single Cooper pair box with a cavity field. The exchange of the information using this system is studied. We quantify the fidelity of the transmitted information. The effect of the system parameters (detuning parameter, field photons, state density and mean photon number) in the fidelity of the transmitted information is investigated. We found that the fidelity of the transmitted information can be controlled using the system parameters.
Multi-disciplinary coupling effects for integrated design of propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions which govern the accurate response of propulsion systems. Results are presented for propulsion system responses including multi-disciplinary coupling effects using coupled multi-discipline thermal, structural, and acoustic tailoring; an integrated system of multi-disciplinary simulators; coupled material behavior/fabrication process tailoring; sensitivities using a probabilistic simulator; and coupled materials, structures, fracture, and probabilistic behavior simulator. The results demonstrate that superior designs can be achieved if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated coupled multi-discipline numerical propulsion system simulator.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Rawle, Rachel A.; Hamerly, Timothy; Tripet, Brian P.

Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted ‘omics’ analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized usingmore » interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis–N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. In conclusion, this multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis–N. equitans association. This study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies.« less
SmaggIce 2.0: Additional Capabilities for Interactive Grid Generation of Iced Airfoils

NASA Technical Reports Server (NTRS)

Kreeger, Richard E.; Baez, Marivell; Braun, Donald C.; Schilling, Herbert W.; Vickerman, Mary B.

2008-01-01

The Surface Modeling and Grid Generation for Iced Airfoils (SmaggIce) software toolkit has been extended to allow interactive grid generation for multi-element iced airfoils. The essential phases of an icing effects study include geometry preparation, block creation and grid generation. SmaggIce Version 2.0 now includes these main capabilities for both single and multi-element airfoils, plus an improved flow solver interface and a variety of additional tools to enhance the efficiency and accuracy of icing effects studies. An overview of these features is given, especially the new multi-element blocking strategy using the multiple wakes method. Examples are given which illustrate the capabilities of SmaggIce for conducting an icing effects study for both single and multi-element airfoils.
A non-oscillatory energy-splitting method for the computation of compressible multi-fluid flows

NASA Astrophysics Data System (ADS)

Lei, Xin; Li, Jiequan

2018-04-01

This paper proposes a new non-oscillatory energy-splitting conservative algorithm for computing multi-fluid flows in the Eulerian framework. In comparison with existing multi-fluid algorithms in the literature, it is shown that the mass fraction model with isobaric hypothesis is a plausible choice for designing numerical methods for multi-fluid flows. Then we construct a conservative Godunov-based scheme with the high order accurate extension by using the generalized Riemann problem solver, through the detailed analysis of kinetic energy exchange when fluids are mixed under the hypothesis of isobaric equilibrium. Numerical experiments are carried out for the shock-interface interaction and shock-bubble interaction problems, which display the excellent performance of this type of schemes and demonstrate that nonphysical oscillations are suppressed around material interfaces substantially.
Crack propagation of brittle rock under high geostress

NASA Astrophysics Data System (ADS)

Liu, Ning; Chu, Weijiang; Chen, Pingzhi

2018-03-01

Based on fracture mechanics and numerical methods, the characteristics and failure criterions of wall rock cracks including initiation, propagation, and coalescence are analyzed systematically under different conditions. In order to consider the interaction among cracks, adopt the sliding model of multi-cracks to simulate the splitting failure of rock in axial compress. The reinforcement of bolts and shotcrete supporting to rock mass can control the cracks propagation well. Adopt both theory analysis and simulation method to study the mechanism of controlling the propagation. The best fixed angle of bolts is calculated. Then use ansys to simulate the crack arrest function of bolt to crack. Analyze the influence of different factors on stress intensity factor. The method offer more scientific and rational criterion to evaluate the splitting failure of underground engineering under high geostress.
Order statistics inference for describing topological coupling and mechanical symmetry breaking in multidomain proteins

NASA Astrophysics Data System (ADS)

Kononova, Olga; Jones, Lee; Barsegov, V.

2013-09-01

Cooperativity is a hallmark of proteins, many of which show a modular architecture comprising discrete structural domains. Detecting and describing dynamic couplings between structural regions is difficult in view of the many-body nature of protein-protein interactions. By utilizing the GPU-based computational acceleration, we carried out simulations of the protein forced unfolding for the dimer WW - WW of the all-β-sheet WW domains used as a model multidomain protein. We found that while the physically non-interacting identical protein domains (WW) show nearly symmetric mechanical properties at low tension, reflected, e.g., in the similarity of their distributions of unfolding times, these properties become distinctly different when tension is increased. Moreover, the uncorrelated unfolding transitions at a low pulling force become increasingly more correlated (dependent) at higher forces. Hence, the applied force not only breaks "the mechanical symmetry" but also couples the physically non-interacting protein domains forming a multi-domain protein. We call this effect "the topological coupling." We developed a new theory, inspired by order statistics, to characterize protein-protein interactions in multi-domain proteins. The method utilizes the squared-Gaussian model, but it can also be used in conjunction with other parametric models for the distribution of unfolding times. The formalism can be taken to the single-molecule experimental lab to probe mechanical cooperativity and domain communication in multi-domain proteins.
Relations among Teachers’ Emotion Socialization Beliefs and Practices, and Preschoolers’ Emotional Competence

PubMed Central

Morris, Carol A.S.; Denham, Susanne A.; Bassett, Hideko H.; Curby, Timothy W.

2013-01-01

Research Findings Utilizing a three-part model of emotion socialization that includes Modeling, Contingent Responding, and Teaching, this study examined the associations between 44 teachers’ self-reported and observed emotion socialization practices and 326 preschoolers’ emotion knowledge and observed emotional behavior. Multi-level analyses revealed that the majority of the variance in the children’s emotion knowledge scores and observed emotional behavior was predicted by factors within, rather than between, classrooms. Teachers’ use of all three emotion socialization techniques did contribute to the prediction of the children’s scores; however, the nature of these associations differed by children’s age and gender. Practice or Policy The development of children’s emotional competence is a complex, multi-faceted process in which many interaction partners play a role; early childhood teachers act as emotion socialization agents for the children in their care by modeling emotions, responding either supportively or punitively to children’s expressions of emotions, and engaging in direct instruction regarding emotional experience. This research may provide a basis for potential future interventions designed to assist teachers in developing their own emotion socialization skills so that they can be more effective emotion socialization agents for the children in their care. PMID:24159256
BioAge: Toward A Multi-Determined, Mechanistic Account of Cognitive Aging

PubMed Central

DeCarlo, Correne A.; Tuokko, Holly A.; Williams, Dorothy; Dixon, Roger A.; MacDonald, Stuart W.S.

2014-01-01

The search for reliable early indicators of age-related cognitive decline represents a critical avenue for progress in aging research. Chronological age is a commonly used developmental index; however, it offers little insight into the mechanisms underlying cognitive decline. In contrast, biological age (BioAge), reflecting the vitality of essential biological systems, represents a promising operationalization of developmental time. Current BioAge models have successfully predicted age-related cognitive deficits. Research on aging-related cognitive function indicates that the interaction of multiple risk and protective factors across the human lifespan confers individual risk for late-life cognitive decline, implicating a multi-causal explanation. In this review, we explore current BioAge models, describe three broad yet pathologically relevant biological processes linked to cognitive decline, and propose a novel operationalization of BioAge accounting for both moderating and causal mechanisms of cognitive decline and dementia. We argue that a multivariate and mechanistic BioAge approach will lead to a greater understanding of disease pathology as well as more accurate prediction and early identification of late-life cognitive decline. PMID:25278166
BioAge: toward a multi-determined, mechanistic account of cognitive aging.

PubMed

DeCarlo, Correne A; Tuokko, Holly A; Williams, Dorothy; Dixon, Roger A; MacDonald, Stuart W S

2014-11-01

The search for reliable early indicators of age-related cognitive decline represents a critical avenue for progress in aging research. Chronological age is a commonly used developmental index; however, it offers little insight into the mechanisms underlying cognitive decline. In contrast, biological age (BioAge), reflecting the vitality of essential biological systems, represents a promising operationalization of developmental time. Current BioAge models have successfully predicted age-related cognitive deficits. Research on aging-related cognitive function indicates that the interaction of multiple risk and protective factors across the human lifespan confers individual risk for late-life cognitive decline, implicating a multi-causal explanation. In this review, we explore current BioAge models, describe three broad yet pathologically relevant biological processes linked to cognitive decline, and propose a novel operationalization of BioAge accounting for both moderating and causal mechanisms of cognitive decline and dementia. We argue that a multivariate and mechanistic BioAge approach will lead to a greater understanding of disease pathology as well as more accurate prediction and early identification of late-life cognitive decline. Copyright © 2014 Elsevier B.V. All rights reserved.

Electrostatic interactions between diffuse soft multi-layered (bio)particles: beyond Debye-Hückel approximation and Deryagin formulation.

PubMed

Duval, Jérôme F L; Merlin, Jenny; Narayana, Puranam A L

2011-01-21

We report a steady-state theory for the evaluation of electrostatic interactions between identical or dissimilar spherical soft multi-layered (bio)particles, e.g. microgels or microorganisms. These generally consist of a rigid core surrounded by concentric ion-permeable layers that may differ in thickness, soft material density, chemical composition and degree of dissociation for the ionogenic groups. The formalism allows the account of diffuse interphases where distributions of ionogenic groups from one layer to the other are position-dependent. The model is valid for any number of ion-permeable layers around the core of the interacting soft particles and covers all limiting situations in terms of nature of interacting particles, i.e. homo- and hetero-interactions between hard, soft or entirely porous colloids. The theory is based on a rigorous numerical solution of the non-linearized Poisson-Boltzmann equation including radial and angular distortions of the electric field distribution within and outside the interacting soft particles in approach. The Gibbs energy of electrostatic interaction is obtained from a general expression derived following the method by Verwey and Overbeek based on appropriate electric double layer charging mechanisms. Original analytical solutions are provided here for cases where interaction takes place between soft multi-layered particles whose size and charge density are in line with Deryagin treatment and Debye-Hückel approximation. These situations include interactions between hard and soft particles, hard plate and soft particle or soft plate and soft particle. The flexibility of the formalism is highlighted by the discussion of few situations which clearly illustrate that electrostatic interaction between multi-layered particles may be partly or predominantly governed by potential distribution within the most internal layers. A major consequence is that both amplitude and sign of Gibbs electrostatic interaction energy may dramatically change depending on the interplay between characteristic Debye length, thickness of ion-permeable layers and their respective protolytic features (e.g. location, magnitude and sign of charge density). This formalism extends a recent model by Ohshima which is strictly limited to interaction between soft mono-shell particles within Deryagin and Debye-Hückel approximations under conditions where ionizable sites are completely dissociated.
Soil Moisture fusion across scales using a multiscale nonstationary Spatial Hierarchical Model

NASA Astrophysics Data System (ADS)

Kathuria, D.; Mohanty, B.; Katzfuss, M.

2017-12-01

Soil moisture (SM) datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors, on the other hand, provide observations on a finer spatial scale (meter scale or less) but are sparsely available. SM is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables and these interactions change dynamically with footprint scales. Past literature has largely focused on the scale specific effect of these covariates on soil moisture. The present study proposes a robust Multiscale-Nonstationary Spatial Hierarchical Model (MN-SHM) which can assimilate SM from point to RS footprints. The spatial structure of SM across footprints is modeled by a class of scalable covariance functions whose nonstationary depends on atmospheric forcings (such as precipitation) and surface physical controls (such as topography, soil-texture and vegetation). The proposed model is applied to fuse point and airborne ( 1.5 km) SM data obtained during the SMAPVEX12 campaign in the Red River watershed in Southern Manitoba, Canada with SMOS ( 30km) data. It is observed that precipitation, soil-texture and vegetation are the dominant factors which affect the SM distribution across various footprint scales (750 m, 1.5 km, 3 km, 9 km,15 km and 30 km). We conclude that MN-SHM handles the change of support problems easily while retaining reasonable predictive accuracy across multiple spatial resolutions in the presence of surface heterogeneity. The MN-SHM can be considered as a complex non-stationary extension of traditional geostatistical prediction methods (such as Kriging) for fusing multi-platform multi-scale datasets.
A Simple Tool for the Design and Analysis of Multiple-Reflector Antennas in a Multi-Disciplinary Environment

NASA Technical Reports Server (NTRS)

Katz, Daniel S.; Cwik, Tom; Fu, Chuigang; Imbriale, William A.; Jamnejad, Vahraz; Springer, Paul L.; Borgioli, Andrea

2000-01-01

The process of designing and analyzing a multiple-reflector system has traditionally been time-intensive, requiring large amounts of both computational and human time. At many frequencies, a discrete approximation of the radiation integral may be used to model the system. The code which implements this physical optics (PO) algorithm was developed at the Jet Propulsion Laboratory. It analyzes systems of antennas in pairs, and for each pair, the analysis can be computationally time-consuming. Additionally, the antennas must be described using a local coordinate system for each antenna, which makes it difficult to integrate the design into a multi-disciplinary framework in which there is traditionally one global coordinate system, even before considering deforming the antenna as prescribed by external structural and/or thermal factors. Finally, setting up the code to correctly analyze all the antenna pairs in the system can take a fair amount of time, and introduces possible human error. The use of parallel computing to reduce the computational time required for the analysis of a given pair of antennas has been previously discussed. This paper focuses on the other problems mentioned above. It will present a methodology and examples of use of an automated tool that performs the analysis of a complete multiple-reflector system in an integrated multi-disciplinary environment (including CAD modeling, and structural and thermal analysis) at the click of a button. This tool, named MOD Tool (Millimeter-wave Optics Design Tool), has been designed and implemented as a distributed tool, with a client that runs almost identically on Unix, Mac, and Windows platforms, and a server that runs primarily on a Unix workstation and can interact with parallel supercomputers with simple instruction from the user interacting with the client.
Identification of crop cultivars with consistently high lignocellulosic sugar release requires the use of appropriate statistical design and modelling

PubMed Central

2013-01-01

Background In this study, a multi-parent population of barley cultivars was grown in the field for two consecutive years and then straw saccharification (sugar release by enzymes) was subsequently analysed in the laboratory to identify the cultivars with the highest consistent sugar yield. This experiment was used to assess the benefit of accounting for both the multi-phase and multi-environment aspects of large-scale phenotyping experiments with field-grown germplasm through sound statistical design and analysis. Results Complementary designs at both the field and laboratory phases of the experiment ensured that non-genetic sources of variation could be separated from the genetic variation of cultivars, which was the main target of the study. The field phase included biological replication and plot randomisation. The laboratory phase employed re-randomisation and technical replication of samples within a batch, with a subset of cultivars chosen as duplicates that were randomly allocated across batches. The resulting data was analysed using a linear mixed model that incorporated field and laboratory variation and a cultivar by trial interaction, and ensured that the cultivar means were more accurately represented than if the non-genetic variation was ignored. The heritability detected was more than doubled in each year of the trial by accounting for the non-genetic variation in the analysis, clearly showing the benefit of this design and approach. Conclusions The importance of accounting for both field and laboratory variation, as well as the cultivar by trial interaction, by fitting a single statistical model (multi-environment trial, MET, model), was evidenced by the changes in list of the top 40 cultivars showing the highest sugar yields. Failure to account for this interaction resulted in only eight cultivars that were consistently in the top 40 in different years. The correspondence between the rankings of cultivars was much higher at 25 in the MET model. This approach is suited to any multi-phase and multi-environment population-based genetic experiment. PMID:24359577
Numerical optimization of a multi-jet cooling system for the blown film extrusion

NASA Astrophysics Data System (ADS)

Janas, M.; Wortberg, J.

2015-05-01

The limiting factor for every extrusion process is the cooling. For the blown film process, this task is usually done by means of a single or dual lip air ring. Prior work has shown that two major effects are responsible for a bad heat transfer. The first one is the interaction between the jet and the ambient air. It reduces the velocity of the jet and enlarges the straight flow. The other one is the formation of a laminar boundary layer on the film surface due to the fast flowing cooling air. In this case, the boundary layer isolates the film and prevents an efficient heat transfer. To improve the heat exchange, a novel cooling approach is developed, called Multi-Jet. The new cooling system uses several slit nozzles over the whole tube formation zone for cooling the film. In contrast to a conventional system, the cooling air is guided vertically on the film surface in different heights to penetrate the boundary sublayer. Simultaneously, a housing of the tube formation zone is practically obtained to reduce the interaction with the ambient air. For the numerical optimization of the Multi-Jet system, a new procedure is developed. First, a prediction model identifies a worth considering cooling configuration. Therefore, the prediction model computes a film curve using the formulation from Zatloukal-Vlcek and the energy balance for the film temperature. Thereafter, the optimized cooling geometry is investigated in detail using a process model for the blown film extrusion that is able to compute a realistic bubble behavior depending on the cooling situation. In this paper, the Multi-Jet cooling system is numerically optimized for several different process states, like mass throughputs and blow-up ratios using one slit nozzle setting. For each process condition, the best cooling result has to be achieved. Therefore, the height of any nozzle over the tube formation zone is adjustable. The other geometrical parameters of the cooling system like the nozzle diameter or the nozzle width are fix.
Shared decision-making at the end of life: A focus group study exploring the perceptions and experiences of multi-disciplinary healthcare professionals working in the home setting.

PubMed

Brogan, Paula; Hasson, Felicity; McIlfatrick, Sonja

2018-01-01

Globally recommended in healthcare policy, Shared Decision-Making is also central to international policy promoting community palliative care. Yet realities of implementation by multi-disciplinary healthcare professionals who provide end-of-life care in the home are unclear. To explore multi-disciplinary healthcare professionals' perceptions and experiences of Shared Decision-Making at end of life in the home. Qualitative design using focus groups, transcribed verbatim and analysed thematically. A total of 43 participants, from multi-disciplinary community-based services in one region of the United Kingdom, were recruited. While the rhetoric of Shared Decision-Making was recognised, its implementation was impacted by several interconnecting factors, including (1) conceptual confusion regarding Shared Decision-Making, (2) uncertainty in the process and (3) organisational factors which impeded Shared Decision-Making. Multiple interacting factors influence implementation of Shared Decision-Making by professionals working in complex community settings at the end of life. Moving from rhetoric to reality requires future work exploring the realities of Shared Decision-Making practice at individual, process and systems levels.
Phase diagrams of vortex matter with multi-scale inter-vortex interactions in layered superconductors.

PubMed

Meng, Qingyou; Varney, Christopher N; Fangohr, Hans; Babaev, Egor

2017-01-25

It was recently proposed to use the stray magnetic fields of superconducting vortex lattices to trap ultracold atoms for building quantum emulators. This calls for new methods for engineering and manipulating of the vortex states. One of the possible routes utilizes type-1.5 superconducting layered systems with multi-scale inter-vortex interactions. In order to explore the possible vortex states that can be engineered, we present two phase diagrams of phenomenological vortex matter models with multi-scale inter-vortex interactions featuring several attractive and repulsive length scales. The phase diagrams exhibit a plethora of phases, including conventional 2D lattice phases, five stripe phases, dimer, trimer, and tetramer phases, void phases, and stable low-temperature disordered phases. The transitions between these states can be controlled by the value of an applied external field.
Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

NASA Astrophysics Data System (ADS)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.
Centennial-scale Holocene climate variations amplified by Antarctic Ice Sheet discharge

NASA Astrophysics Data System (ADS)

Bakker, Pepijn; Clark, Peter U.; Golledge, Nicholas R.; Schmittner, Andreas; Weber, Michael E.

2017-01-01

Proxy-based indicators of past climate change show that current global climate models systematically underestimate Holocene-epoch climate variability on centennial to multi-millennial timescales, with the mismatch increasing for longer periods. Proposed explanations for the discrepancy include ocean-atmosphere coupling that is too weak in models, insufficient energy cascades from smaller to larger spatial and temporal scales, or that global climate models do not consider slow climate feedbacks related to the carbon cycle or interactions between ice sheets and climate. Such interactions, however, are known to have strongly affected centennial- to orbital-scale climate variability during past glaciations, and are likely to be important in future climate change. Here we show that fluctuations in Antarctic Ice Sheet discharge caused by relatively small changes in subsurface ocean temperature can amplify multi-centennial climate variability regionally and globally, suggesting that a dynamic Antarctic Ice Sheet may have driven climate fluctuations during the Holocene. We analysed high-temporal-resolution records of iceberg-rafted debris derived from the Antarctic Ice Sheet, and performed both high-spatial-resolution ice-sheet modelling of the Antarctic Ice Sheet and multi-millennial global climate model simulations. Ice-sheet responses to decadal-scale ocean forcing appear to be less important, possibly indicating that the future response of the Antarctic Ice Sheet will be governed more by long-term anthropogenic warming combined with multi-centennial natural variability than by annual or decadal climate oscillations.
The brain-derived neurotrophic factor pathway, life stress, and chronic multi-site musculoskeletal pain.

PubMed

Generaal, Ellen; Milaneschi, Yuri; Jansen, Rick; Elzinga, Bernet M; Dekker, Joost; Penninx, Brenda W J H

2016-01-01

Brain-derived neurotrophic factor (BDNF) disturbances and life stress, both independently and in interaction, have been hypothesized to induce chronic pain. We examined whether (a) the BDNF pathway (val(66)met genotype, gene expression, and serum levels), (b) early and recent life stress, and (c) their interaction are associated with the presence and severity of chronic multi-site musculoskeletal pain. Cross-sectional data are from 1646 subjects of the Netherlands Study of Depression and Anxiety. The presence and severity of chronic multi-site musculoskeletal pain were determined using the Chronic Pain Grade (CPG) questionnaire. The BDNF val(66)met polymorphism, BDNF gene expression, and BDNF serum levels were measured. Early life stress before the age of 16 was assessed by calculating a childhood trauma index using the Childhood Trauma Interview. Recent life stress was assessed as the number of recent adverse life events using the List of Threatening Events Questionnaire. Compared to val(66)val, BDNF met carriers more often had chronic pain, whereas no differences were found for BDNF gene expression and serum levels. Higher levels of early and recent stress were both associated with the presence and severity of chronic pain (p < 0.001). No interaction effect was found for the BDNF pathway with life stress in the associations with chronic pain presence and severity. This study suggests that the BDNF gene marks vulnerability for chronic pain. Although life stress did not alter the impact of BDNF on chronic pain, it seems an independent factor in the onset and persistence of chronic pain. © The Author(s) 2016.
Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironment

NASA Astrophysics Data System (ADS)

Jackson, Pamela R.; Hawkins-Daarud, Andrea; Partridge, Savannah C.; Kinahan, Paul E.; Swanson, Kristin R.

2018-03-01

Glioblastoma (GBM), the most aggressive primary brain tumor, is primarily diagnosed and monitored using gadoliniumenhanced T1-weighted and T2-weighted (T2W) magnetic resonance imaging (MRI). Hyperintensity on T2W images is understood to correspond with vasogenic edema and infiltrating tumor cells. GBM's inherent heterogeneity and resulting non-specific MRI image features complicate assessing treatment response. To better understand treatment response, we propose creating a patient-specific untreated virtual imaging control (UVIC), which represents an individual tumor's growth if it had not been treated, for comparison with actual post-treatment images. We generated a T2W MRI UVIC by combining a patient-specific mathematical model of tumor growth with a multi-compartmental MRI signal equation. GBM growth was mathematically modeled using the previously developed Proliferation-Invasion-Hypoxia-Necrosis- Angiogenesis-Edema (PIHNA-E) model, which simulated tumor as being comprised of three cellular phenotypes: normoxic, hypoxic and necrotic cells interacting with a vasculature species, angiogenic factors and extracellular fluid. Within the PIHNA-E model, both hypoxic and normoxic cells emitted angiogenic factors, which recruited additional vessels and caused the vessels to leak, allowing fluid, or edema, to escape into the extracellular space. The model's output was spatial volume fraction maps for each glioma cell type and edema/extracellular space. Volume fraction maps and corresponding T2 values were then incorporated into a multi-compartmental Bloch signal equation to create simulated T2W images. T2 values for individual compartments were estimated from the literature and a normal volunteer. T2 maps calculated from simulated images had normal white matter, normal gray matter, and tumor tissue T2 values within range of literature values.
Can poly-parameter linear-free energy relationships (pp-LFERs) improve modelling bioaccumulation in fish?

PubMed

Zhao, Shizhen; Jones, Kevin C; Sweetman, Andrew J

2018-01-01

A wide range of studies have characterized different types of biosorbent, with regard to their interactions with chemicals. This has resulted in the development of poly-parameter linear free energy relationships (pp-LFERs) for the estimation of partitioning of neutral organic compounds to biological phases (e.g., storage lipids, phospholipids and serum albumins). The aims of this study were to explore and evaluate the influence of implementing pp-LFERs both into a one-compartment fish model and a multi-compartment physiologically based toxicokinetic (PBTK) fish model and the associated implications for chemical risk assessment. For this purpose, fish was used as reference biota, due to their important role in aquatic food chains and dietary exposure to humans. The bioconcentration factor (BCF) was utilized as the evaluation metric. Overall, our results indicated that models incorporating pp-LFERs (R 2 = 0.75) slightly outperformed the single parameter (sp) LFERs approach in the one-compartmental fish model (R 2 = 0.72). A pronounced enhancement was achieved for compounds with log K OW between 4 and 5 with increased R 2 from 0.52 to 0.71. The minimal improvement was caused by the overestimation of lipid contribution and underestimation of protein contribution by the sp-approach, which cancelled each other out. Meanwhile, a greater improvement was observed for multi-compartmental PBTK models with consideration of metabolism, making all predictions fall within a factor of 10 compared with measured data. For screening purposes, the K OW -based (sp-LFERs) approach should be sufficient to quantify the main partitioning characteristics. Further developments are required for the consideration of ionization and more accurate quantification of biotransformation in biota. Copyright © 2017 Elsevier Ltd. All rights reserved.
Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.

PubMed

Li, Yuanning; Richardson, Robert Mark; Ghuman, Avniel Singh

2017-11-15

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions. Copyright © 2017 Elsevier Inc. All rights reserved.
Flame-Generated Vorticity Production in Premixed Flame-Vortex Interactions

NASA Technical Reports Server (NTRS)

Patnaik, G.; Kailasanath, K.

2003-01-01

In this study, we use detailed time-dependent, multi-dimensional numerical simulations to investigate the relative importance of the processes leading to FGV in flame-vortex interactions in normal gravity and microgravity and to determine if the production of vorticity in flames in gravity is the same as that in zero gravity except for the contribution of the gravity term. The numerical simulations will be performed using the computational model developed at NRL, FLAME3D. FLAME3D is a parallel, multi-dimensional (either two- or three-dimensional) flame model based on FLIC2D, which has been used extensively to study the structure and stability of premixed hydrogen and methane flames.
Multi-issue Agent Negotiation Based on Fairness

NASA Astrophysics Data System (ADS)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.
Refined views of multi-protein complexes in the erythrocyte membrane

PubMed Central

Mankelow, TJ; Satchwell, TJ; Burton, NM

2015-01-01

The erythrocyte membrane has been extensively studied, both as a model membrane system and to investigate its role in gas exchange and transport. Much is now known about the protein components of the membrane, how they are organised into large multi-protein complexes and how they interact with each other within these complexes. Many links between the membrane and the cytoskeleton have also been delineated and have been demonstrated to be crucial for maintaining the deformability and integrity of the erythrocyte. In this study we have refined previous, highly speculative molecular models of these complexes by including the available data pertaining to known protein-protein interactions. While the refined models remain highly speculative, they provide an evolving framework for visualisation of these important cellular structures at the atomic level. PMID:22465511
Novel Method of Production Decline Analysis

NASA Astrophysics Data System (ADS)

Xie, Shan; Lan, Yifei; He, Lei; Jiao, Yang; Wu, Yong

2018-02-01

ARPS decline curves is the most commonly used in oil and gas field due to its minimal data requirements and ease application. And prediction of production decline which is based on ARPS analysis rely on known decline type. However, when coefficient index are very approximate under different decline type, it is difficult to directly recognize decline trend of matched curves. Due to difficulties above, based on simulation results of multi-factor response experiments, a new dynamic decline prediction model is introduced with using multiple linear regression of influence factors. First of all, according to study of effect factors of production decline, interaction experimental schemes are designed. Based on simulated results, annual decline rate is predicted by decline model. Moreover, the new method is applied in A gas filed of Ordos Basin as example to illustrate reliability. The result commit that the new model can directly predict decline tendency without needing recognize decline style. From arithmetic aspect, it also take advantage of high veracity. Finally, the new method improves the evaluation method of gas well production decline in low permeability gas reservoir, which also provides technical support for further understanding of tight gas field development laws.
Measurements of Kepler Planet Masses and Eccentricities from Transit Timing Variations: Analytic and N-body Results

NASA Astrophysics Data System (ADS)

Hadden, Sam; Lithwick, Yoram

2015-12-01

Several Kepler planets reside in multi-planet systems where gravitational interactions result in transit timing variations (TTVs) that provide exquisitely sensitive probes of their masses of and orbits. Measuring these planets' masses and orbits constrains their bulk compositions and can provide clues about their formation. However, inverting TTV measurements in order to infer planet properties can be challenging: it involves fitting a nonlinear model with a large number of parameters to noisy data, often with significant degeneracies between parameters. I present results from two complementary approaches to TTV inversion: Markov chain Monte Carlo simulations that use N-body integrations to compute transit times and a simplified analytic model for computing the TTVs of planets near mean motion resonances. The analytic model allows for straightforward interpretations of N-body results and provides an independent estimate of parameter uncertainties that can be compared to MCMC results which may be sensitive to factors such as priors. We have conducted extensive MCMC simulations along with analytic fits to model the TTVs of dozens of Kepler multi-planet systems. We find that the bulk of these sub-Jovian planets have low densities that necessitate significant gaseous envelopes. We also find that the planets' eccentricities are generally small but often definitively non-zero.
Blast and the Consequences on Traumatic Brain Injury-Multiscale Mechanical Modeling of Brain

DTIC Science & Technology

2011-02-17

blast simulation. LS-DYNA as an explicit FE code has been employed to simulate this multi- material fluid –structure interaction problem. The 3-D head...formulation is implemented to model the air-blast simulation. LS-DYNA as an explicit FE code has been employed to simulate this multi-material fluid ...Biomechanics Study of Influencing Parameters for brain under Impact ............................... 12 5.1 The Impact of Cerebrospinal Fluid
Biomass and fire dynamics in a temperate forest-grassland mosaic: Integrating multi-species herbivory, climate, and fire with the FireBGCv2/GrazeBGC system

Treesearch

Robert A. Riggs; Robert E. Keane; Norm Cimon; Rachel Cook; Lisa Holsinger; John Cook; Timothy DelCurto; L.Scott Baggett; Donald Justice; David Powell; Martin Vavra; Bridgett Naylor

2015-01-01

Landscape fire succession models (LFSMs) predict spatially-explicit interactions between vegetation succession and disturbance, but these models have yet to fully integrate ungulate herbivory as a driver of their processes. We modified a complex LFSM, FireBGCv2, to include a multi-species herbivory module, GrazeBGC. The system is novel in that it explicitly...

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.
A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003

PubMed Central

van Witteloostuijn, Arjen

2018-01-01

In this paper, we develop an ecological, multi-level model that can be used to study the evolution of emerging technology. More specifically, by defining technology as a system composed of a set of interacting components, we can build upon the argument of multi-level density dependence from organizational ecology to develop a distribution-independent model of technological evolution. This allows us to distinguish between different stages of component development, which provides more insight into the emergence of stable component configurations, or dominant designs. We validate our hypotheses in the biotechnology industry by using patent data from the USPTO from 1976 to 2003. PMID:29795575
Astroblaster--A Fascinating Game of Multi-Ball Collisions

ERIC Educational Resources Information Center

Kires, Marian

2009-01-01

Multi-ball collisions inside the Astroblaster toy are explained from the conservation of momentum point of view. The important role of the coefficient of restitution is demonstrated in ideal and real cases. Real experimental results with the simple toy can be compared with a computer model represented by an interactive Java applet. (Contains 1…
Applications of Multi-Agent Technology to Power Systems

NASA Astrophysics Data System (ADS)

Nagata, Takeshi

Currently, agents are focus of intense on many sub-fields of computer science and artificial intelligence. Agents are being used in an increasingly wide variety of applications. Many important computing applications such as planning, process control, communication networks and concurrent systems will benefit from using multi-agent system approach. A multi-agent system is a structure given by an environment together with a set of artificial agents capable to act on this environment. Multi-agent models are oriented towards interactions, collaborative phenomena, and autonomy. This article presents the applications of multi-agent technology to the power systems.
Static and dynamic factors in an information-based multi-asset artificial stock market

NASA Astrophysics Data System (ADS)

Ponta, Linda; Pastore, Stefano; Cincotti, Silvano

2018-02-01

An information-based multi-asset artificial stock market characterized by different types of stocks and populated by heterogeneous agents is presented. In the market, agents trade risky assets in exchange for cash. Beside the amount of cash and of stocks owned, each agent is characterized by sentiments and agents share their sentiments by means of interactions that are determined by sparsely connected networks. A central market maker (clearing house mechanism) determines the price processes for each stock at the intersection of the demand and the supply curves. Single stock price processes exhibit volatility clustering and fat-tailed distribution of returns whereas multivariate price process exhibits both static and dynamic stylized facts, i.e., the presence of static factors and common trends. Static factors are studied making reference to the cross-correlation of returns of different stocks. The common trends are investigated considering the variance-covariance matrix of prices. Results point out that the probability distribution of eigenvalues of the cross-correlation matrix of returns shows the presence of sectors, similar to those observed on real empirical data. As regarding the dynamic factors, the variance-covariance matrix of prices point out a limited number of assets prices series that are independent integrated processes, in close agreement with the empirical evidence of asset price time series of real stock markets. These results remarks the crucial dependence of statistical properties of multi-assets stock market on the agents' interaction structure.
Mobile spin impurity in an optical lattice

NASA Astrophysics Data System (ADS)

Duncan, C. W.; Bellotti, F. F.; Öhberg, P.; Zinner, N. T.; Valiente, M.

2017-07-01

We investigate the Fermi polaron problem in a spin-1/2 Fermi gas in an optical lattice for the limit of both strong repulsive contact interactions and one dimension. In this limit, a polaronic-like behaviour is not expected, and the physics is that of a magnon or impurity. While the charge degrees of freedom of the system are frozen, the resulting tight-binding Hamiltonian for the impurity’s spin exhibits an intriguing structure that strongly depends on the filling factor of the lattice potential. This filling dependency also transfers to the nature of the interactions for the case of two magnons and the important spin balanced case. At low filling, and up until near unit filling, the single impurity Hamiltonian faithfully reproduces a single-band, quasi-homogeneous tight-binding problem. As the filling is increased and the second band of the single particle spectrum of the periodic potential is progressively filled, the impurity Hamiltonian, at low energies, describes a single particle trapped in a multi-well potential. Interestingly, once the first two bands are fully filled, the impurity Hamiltonian is a near-perfect realisation of the Su-Schrieffer-Heeger model. Our studies, which go well beyond the single-band approximation, that is, the Hubbard model, pave the way for the realisation of interacting one-dimensional models of condensed matter physics.
Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1991-01-01

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.
Theory and applications of a novel ion exchange chromatographic technology using controlled pH gradients for separating proteins on anionic and cationic stationary phases.

PubMed

Tsonev, Latchezar I; Hirsh, Allen G

2008-07-25

pISep is a major new advance in low ionic strength ion exchange chromatography. It enables the formation of externally controlled pH gradients over the very broad pH range from 2 to 12. The gradients can be generated on either cationic or anionic exchangers over arbitrary pH ranges wherein the stationary phases remain totally charged. Associated pISep software makes possible the calculation of either linear, nonlinear or combined, multi-step, multi-slope pH gradients. These highly reproducible pH gradients, while separating proteins and glycoproteins in the order of their electrophoretic pIs, provide superior chromatographic resolution compared to salt. This paper also presents a statistical mechanical model for protein binding to ion exchange stationary phases enhancing the electrostatic interaction theory for the general dependence of retention factor k, on both salt and pH simultaneously. It is shown that the retention factors computed from short time isocratic salt elution data of a model protein can be used to accurately predict its salt elution concentration in varying slope salt elution gradients formed at varying isocratic pH as well as the pH at which it will be eluted from an anionic exchange column by a pISep pH gradient in the absence of salt.
Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model.

PubMed

Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo

2017-01-31

Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.
Species interactions may help explain the erratic periodicity of whooping cough dynamics.

PubMed

Bhattacharyya, Samit; Ferrari, Matthew J; Bjørnstad, Ottar N

2017-12-14

Incidence of whooping cough exhibits variable dynamics across time and space. The periodicity of this disease varies from annual to five years in different geographic regions in both developing and developed countries. Many hypotheses have been put forward to explain this variability such as nonlinearity and seasonality, stochasticity, variable recruitment of susceptible individuals via birth, immunization, and immune boosting. We propose an alternative hypothesis to describe the variability in periodicity - the intricate dynamical variability of whooping cough may arise from interactions between its dominant etiological agents of Bordetella pertussis and Bordetella parapertussis. We develop a two-species age-structured model, where two pathogens are allowed to interact by age-dependent convalescence of individuals with severe illness from infections. With moderate strength of interactions, the model exhibits multi-annual coexisting attractors that depend on the R 0 of the two pathogens. We also examine how perturbation from case importation and noise in transmission may push the system from one dynamical regime to another. The coexistence of multi-annual cycles and the behavior of switching between attractors suggest that variable dynamics of whopping cough could be an emergent property of its multi-agent etiology. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

PubMed Central

Li, Feng

2017-01-01

The use of RFID technology in complex and distributed environments often leads to a multi-domain RFID system, in which trust establishment among entities from heterogeneous domains without past interaction or prior agreed policy, is a challenge. The current trust management mechanisms in the literature do not meet the specific requirements in multi-domain RFID systems. Therefore, this paper analyzes the special challenges on trust management in multi-domain RFID systems, and identifies the implications and the requirements of the challenges on the solutions to the trust management of multi-domain RFID systems. A multi-domain trust management model is proposed, which provides a hierarchical trust management framework include a diversity of trust evaluation and establishment approaches. The simulation results and analysis show that the proposed method has excellent ability to deal with the trust relationships, better security, and higher accuracy rate. PMID:28708855
A multi-domain trust management model for supporting RFID applications of IoT.

PubMed

Wu, Xu; Li, Feng

2017-01-01

The use of RFID technology in complex and distributed environments often leads to a multi-domain RFID system, in which trust establishment among entities from heterogeneous domains without past interaction or prior agreed policy, is a challenge. The current trust management mechanisms in the literature do not meet the specific requirements in multi-domain RFID systems. Therefore, this paper analyzes the special challenges on trust management in multi-domain RFID systems, and identifies the implications and the requirements of the challenges on the solutions to the trust management of multi-domain RFID systems. A multi-domain trust management model is proposed, which provides a hierarchical trust management framework include a diversity of trust evaluation and establishment approaches. The simulation results and analysis show that the proposed method has excellent ability to deal with the trust relationships, better security, and higher accuracy rate.
Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties

PubMed Central

Zapata-Fonseca, Leonardo; Dotov, Dobromir; Fossion, Ruben; Froese, Tom

2016-01-01

There is a growing consensus that a fuller understanding of social cognition depends on more systematic studies of real-time social interaction. Such studies require methods that can deal with the complex dynamics taking place at multiple interdependent temporal and spatial scales, spanning sub-personal, personal, and dyadic levels of analysis. We demonstrate the value of adopting an extended multi-scale approach by re-analyzing movement time-series generated in a study of embodied dyadic interaction in a minimal virtual reality environment (a perceptual crossing experiment). Reduced movement variability revealed an interdependence between social awareness and social coordination that cannot be accounted for by either subjective or objective factors alone: it picks out interactions in which subjective and objective conditions are convergent (i.e., elevated coordination is perceived as clearly social, and impaired coordination is perceived as socially ambiguous). This finding is consistent with the claim that interpersonal interaction can be partially constitutive of direct social perception. Clustering statistics (Allan Factor) of salient events revealed fractal scaling. Complexity matching defined as the similarity between these scaling laws was significantly more pronounced in pairs of participants as compared to surrogate dyads. This further highlights the multi-scale and distributed character of social interaction and extends previous complexity matching results from dyadic conversation to non-verbal social interaction dynamics. Trials with successful joint interaction were also associated with an increase in local coordination. Consequently, a local coordination pattern emerges on the background of complex dyadic interactions in the PCE task and makes joint successful performance possible. PMID:28018274
In vitro Multi-Species Biofilms of Methicillin-Resistant Staphylococcus aureus and Pseudomonas aeruginosa and Their Host Interaction during In vivo Colonization of an Otitis Media Rat Model

PubMed Central

Yadav, Mukesh K.; Chae, Sung-Won; Go, Yoon Young; Im, Gi Jung; Song, Jae-Jun

2017-01-01

Staphylococcus aureus (SA) and Pseudomonas aeruginosa (PA) are known to cause biofilm-related infections. MRSA and PA have been frequently isolated from chronically infected wounds, cystic fibrosis, chronic suppurative otitis media (CSOM), and from indwelling medical devices, and these bacteria co-exist; however, their interaction with each-other or with the host is not well known. In this study, we investigated MRSA and PA multi-species biofilm communities in vitro and their interaction with the host during in vivo colonization using an OM rat-model. In-vitro biofilm formation and in-vivo colonization were studied using CV-microtiter plate assay and OM rat-model respectively. The biofilms were viewed under scanning electron microscope and bacteria were enumerated using cfu counts. The differential gene expressions of rat mucosa colonized with single or multi-species of MRSA or PA were studied using RNA-sequencing of total transcriptome. In multi-species in-vitro biofilms PA partially inhibited SA growth. However, no significant inhibition of MRSA was detected during in-vivo colonization of multi-species in rat bullae. A total of 1,797 genes were significantly (p < 0.05) differentially expressed in MRSA or PA or MRSA + PA colonized rat middle ear mucosa with respect to the control. The poly-microbial colonization of MRSA and PA induced the differential expression of a significant number of genes that are involved in immune response, inflammation, signaling, development, and defense; these were not expressed with single species colonization by either MRSA or PA. Genes involved in defense, immune response, inflammatory response, and developmental process were exclusively up-regulated, and genes that are involved in nervous system signaling, development and transmission, regulation of cell growth and development, anatomical and system development, and cell differentiation were down-regulated after multi-species inoculation. These results indicate that poly-microbial colonization induces a host response that is different from that induced by single species infection. PMID:28459043
Investigation of the binding properties of a multi-modular GH45 cellulase using bioinspired model assemblies.

PubMed

Fong, Monica; Berrin, Jean-Guy; Paës, Gabriel

2016-01-01

Enzymes degrading plant biomass polymers are widely used in biotechnological applications. Their efficiency can be limited by non-specific interactions occurring with some chemical motifs. In particular, the lignin component is known to bind enzymes irreversibly. In order to determine interactions of enzymes with their substrates, experiments are usually performed on isolated simple polymers which are not representative of plant cell wall complexity. But when using natural plant substrates, the role of individual chemical and structural features affecting enzyme-binding properties is also difficult to decipher. We have designed and used lignified model assemblies of plant cell walls as templates to characterize binding properties of multi-modular cellulases. These three-dimensional assemblies are modulated in their composition using the three principal polymers found in secondary plant cell walls (cellulose, hemicellulose, and lignin). Binding properties of enzymes are obtained from the measurement of their mobility that depends on their interactions with the polymers and chemical motifs of the assemblies. The affinity of the multi-modular GH45 cellulase was characterized using a statistical analysis to determine the role played by each assembly polymer. Presence of hemicellulose had much less impact on affinity than cellulose and model lignin. Depending on the number of CBMs appended to the cellulase catalytic core, binding properties toward cellulose and lignin were highly contrasted. Model assemblies bring new insights into the molecular determinants that are responsible for interactions between enzymes and substrate without the need of complex analysis. Consequently, we believe that model bioinspired assemblies will provide relevant information for the design and optimization of enzyme cocktails in the context of biorefineries.
Learning Analytics for Networked Learning Models

ERIC Educational Resources Information Center

Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

2014-01-01

Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…
Wave-Particle Interactions in the Earth's Radiation Belts: Recent Advances and Unprecedented Future Opportunities

NASA Astrophysics Data System (ADS)

Li, W.

2017-12-01

In the collisionless heliospheric plasmas, wave-particle interaction is a fundamental physical process in transferring energy and momentum between particles with different species and energies. This presentation focuses on one of the important wave-particle interaction processes: interaction between whistler-mode waves and electrons. Whistler-mode waves have frequencies between proton and electron cyclotron frequency and are ubiquitously present in the heliospheric plasmas including solar wind and planetary magnetospheres. I use Earth's Van Allen radiation belt as "local space laboratory" to discuss the role of whistler-mode waves in energetic electron dynamics using multi-satellite observations, theory and modeling. I further discuss solar wind drivers leading to energetic electron dynamics in the Earth's radiation belts, which is critical in predicting space weather that has broad impacts on our technological systems and society. At last, I discuss the unprecedented future opportunities of exploring space science using multi-satellite observations and state-of-the-art theory and modeling.
Computational Simulation of the Formation and Material Behavior of Ice

NASA Technical Reports Server (NTRS)

Tong, Michael T.; Singhal, Surendra N.; Chamis, Christos C.

1994-01-01

Computational methods are described for simulating the formation and the material behavior of ice in prevailing transient environments. The methodology developed at the NASA Lewis Research Center was adopted. A three dimensional finite-element heat transfer analyzer was used to predict the thickness of ice formed under prevailing environmental conditions. A multi-factor interaction model for simulating the material behavior of time-variant ice layers is presented. The model, used in conjunction with laminated composite mechanics, updates the material properties of an ice block as its thickness increases with time. A sample case of ice formation in a body of water was used to demonstrate the methodology. The results showed that the formation and the material behavior of ice can be computationally simulated using the available composites technology.
Recollimation shocks in the relativistic outflows of active galactic nuclei. Doctoral Thesis Award Lecture 2014

NASA Astrophysics Data System (ADS)

Fromm, C. M.

2015-06-01

We analysed the single-dish radio light curves of the blazar CTA 102 during its major flare around April 2006. The modelling of these data revealed a possible travelling shock-recollimation shock interaction during the flare. To verify this hypothesis, we used multi-epoch and multi-frequency very-long baseline interferometry (VLBI) observations and performed a detailed kinematic and spectral analysis. The results confirmed the hypothesis of a shock-shock interaction causing the 2006 radio flare and provided indications for additional recollimation shocks farther downstream.

A Robotic Coach Architecture for Elder Care (ROCARE) Based on Multi-user Engagement Models

PubMed Central

Fan, Jing; Bian, Dayi; Zheng, Zhi; Beuscher, Linda; Newhouse, Paul A.; Mion, Lorraine C.; Sarkar, Nilanjan

2017-01-01

The aging population with its concomitant medical conditions, physical and cognitive impairments, at a time of strained resources, establishes the urgent need to explore advanced technologies that may enhance function and quality of life. Recently, robotic technology, especially socially assistive robotics has been investigated to address the physical, cognitive, and social needs of older adults. Most system to date have predominantly focused on one-on-one human robot interaction (HRI). In this paper, we present a multi-user engagement-based robotic coach system architecture (ROCARE). ROCARE is capable of administering both one-on-one and multi-user HRI, providing implicit and explicit channels of communication, and individualized activity management for long-term engagement. Two preliminary feasibility studies, a one-on-one interaction and a triadic interaction with two humans and a robot, were conducted and the results indicated potential usefulness and acceptance by older adults, with and without cognitive impairment. PMID:28113672
A Robotic Coach Architecture for Elder Care (ROCARE) Based on Multi-User Engagement Models.

PubMed

Fan, Jing; Bian, Dayi; Zheng, Zhi; Beuscher, Linda; Newhouse, Paul A; Mion, Lorraine C; Sarkar, Nilanjan

2017-08-01

The aging population with its concomitant medical conditions, physical and cognitive impairments, at a time of strained resources, establishes the urgent need to explore advanced technologies that may enhance function and quality of life. Recently, robotic technology, especially socially assistive robotics has been investigated to address the physical, cognitive, and social needs of older adults. Most system to date have predominantly focused on one-on-one human robot interaction (HRI). In this paper, we present a multi-user engagement-based robotic coach system architecture (ROCARE). ROCARE is capable of administering both one-on-one and multi-user HRI, providing implicit and explicit channels of communication, and individualized activity management for long-term engagement. Two preliminary feasibility studies, a one-on-one interaction and a triadic interaction with two humans and a robot, were conducted and the results indicated potential usefulness and acceptance by older adults, with and without cognitive impairment.
NGA West 2 | Pacific Earthquake Engineering Research Center

Science.gov Websites

, multi-year research program to improve Next Generation Attenuation models for active tectonic regions earthquake engineering, including modeling of directivity and directionality; verification of NGA-West models epistemic uncertainty; and evaluation of soil amplification factors in NGA models versus NEHRP site factors
A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context.

PubMed

Valavanis, Ioannis K; Mougiakakou, Stavroula G; Grimaldi, Keith A; Nikita, Konstantina S

2010-09-08

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm. PDM-ANN and GA-ANN were comparatively assessed in terms of their ability to identify the most important factors among the initial 63 variables describing genetic variations, nutrition and gender, able to classify a subject into one of the BMI related classes: normal and overweight. The methods were designed and evaluated using appropriate training and testing sets provided by 3-fold Cross Validation (3-CV) resampling. Classification accuracy, sensitivity, specificity and area under receiver operating characteristics curve were utilized to evaluate the resulted predictive ANN models. The most parsimonious set of factors was obtained by the GA-ANN method and included gender, six genetic variations and 18 nutrition-related variables. The corresponding predictive model was characterized by a mean accuracy equal of 61.46% in the 3-CV testing sets. The ANN based methods revealed factors that interactively contribute to obesity trait and provided predictive models with a promising generalization ability. In general, results showed that ANNs and their hybrids can provide useful tools for the study of complex traits in the context of nutrigenetics.
Multifunctional Collaborative Modeling and Analysis Methods in Engineering Science

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.; Broduer, Steve (Technical Monitor)

2001-01-01

Engineers are challenged to produce better designs in less time and for less cost. Hence, to investigate novel and revolutionary design concepts, accurate, high-fidelity results must be assimilated rapidly into the design, analysis, and simulation process. This assimilation should consider diverse mathematical modeling and multi-discipline interactions necessitated by concepts exploiting advanced materials and structures. Integrated high-fidelity methods with diverse engineering applications provide the enabling technologies to assimilate these high-fidelity, multi-disciplinary results rapidly at an early stage in the design. These integrated methods must be multifunctional, collaborative, and applicable to the general field of engineering science and mechanics. Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple-method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized. The multifunctional methodology presented provides an effective mechanism by which domains with diverse idealizations are interfaced. This capability rapidly provides the high-fidelity results needed in the early design phase. Moreover, the capability is applicable to the general field of engineering science and mechanics. Hence, it provides a collaborative capability that accounts for interactions among engineering analysis methods.
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.
A multi-level approach for investigating socio-economic and agricultural risk factors associated with rates of reported cases of Escherichia coli O157 in humans in Alberta, Canada.

PubMed

Pearl, D L; Louie, M; Chui, L; Doré, K; Grimsrud, K M; Martin, S W; Michel, P; Svenson, L W; McEwen, S A

2009-10-01

Using negative binomial and multi-level Poisson models, the authors determined the statistical significance of agricultural and socio-economic risk factors for rates of reported disease associated with Escherichia coli O157 in census subdivisions (CSDs) in Alberta, Canada, 2000-2002. Variables relating to population stability, aboriginal composition of the CSDs, and the economic relationship between CSDs and urban centres were significant risk factors. The percentage of individuals living in low-income households was not a statistically significant risk factor for rates of disease. The statistical significance of cattle density, recorded at a higher geographical level, depended on the method used to correct for overdispersion, the number of levels included in the multi-level models, and the choice of using all reported cases or only sporadic cases. Our results highlight the importance of local socio-economic risk factors in determining rates of disease associated with E. coli O157, but their relationship with individual risk factors requires further evaluation.
Phase coupling in the cardiorespiratory interaction.

PubMed

Bahraminasab, A; Kenwright, D; Stefanovska, A; Ghasemi, F; McClintock, P V E

2008-01-01

Markovian analysis is applied to derive nonlinear stochastic equations for the reconstruction of heart rate and respiration rate variability data. A model of their 'phase' interactions is obtained for the first time, thereby gaining new insights into the strength and direction of the cardiorespiratory phase coupling. The reconstructed model can reproduce synchronisation phenomena between the cardiac and the respiratory systems, including switches in synchronisation ratio. The technique is equally applicable to the extraction of the multi-dimensional couplings between many interacting subsystems.
Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

NASA Astrophysics Data System (ADS)

Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

2016-12-01

Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.
Exploring an Ecological Model of Perceived Usability within a Multi-Tiered Vocabulary Intervention

ERIC Educational Resources Information Center

Neugebauer, Sabina R.; Chafouleas, Sandra M.; Coyne, Michael D.; McCoach, D. Betsy; Briesch, Amy M.

2016-01-01

The present study examines an ecological model for intervention use to explain student vocabulary performance in a multi-tiered intervention setting. A teacher self-report measure composed of factors hypothesized to influence intervention use at multiple levels (i.e., individual, intervention, and system level) was administered to 54 teachers and…
Investigation of Alien Wavelength Quality in Live Multi-Domain, Multi-Vendor Link Using Advanced Simulation Tool

NASA Astrophysics Data System (ADS)

Nordal Petersen, Martin; Nuijts, Roeland; Lange Bjørn, Lars

2014-05-01

This article presents an advanced optical model for simulation of alien wavelengths in multi-domain and multi-vendor dense wavelength-division multiplexing networks. The model aids optical network planners with a better understanding of the non-linear effects present in dense wavelength-division multiplexing systems and better utilization of alien wavelengths in future applications. The limiting physical effects for alien wavelengths are investigated in relation to power levels, channel spacing, and other factors. The simulation results are verified through experimental setup in live multi-domain dense wavelength-division multiplexing systems between two national research networks: SURFnet in Holland and NORDUnet in Denmark.
A New Global Multi-fluid MHD Model of the Solar Corona

NASA Astrophysics Data System (ADS)

van der Holst, B.; Chandran, B. D. G.; Alterman, B. L.; Kasper, J. C.; Toth, G.

2017-12-01

We present a multi-fluid generalization of the AWSoM model, a global magnetohydrodynamic (MHD) solar corona model with low-frequency Alfven wave turbulence (van der Holst et al., 2014). This new extended model includes electron and multi-ion temperatures and velocities (protons and alpha particles). The coronal heating and acceleration is addressed via outward propagating low-frequency Alfven waves that are partially reflected by Alfven speed gradients. The nonlinear interaction of these counter-propagating waves results in turbulent energy cascade. To apportion the wave dissipation to the electron and ion temperatures, we employ the results of the theories of linear wave damping and nonlinear stochastic heating as described by Chandran et al. (2011, 2013). This heat partitioning results in a more than mass proportional heating among ions.
Description of bioremediation of soils using the model of a multistep system of microorganisms

NASA Astrophysics Data System (ADS)

Lubysheva, A. I.; Potashev, K. A.; Sofinskaya, O. A.

2018-01-01

The paper deals with the development of a mathematical model describing the interaction of a multi-step system of microorganisms in soil polluted with oil products. Each step in this system uses products of vital activity of the previous step to feed. Six different models of the multi-step system are considered. The equipping of the models with coefficients was carried out from the condition of minimizing the residual of the calculated and experimental data using an original algorithm based on the Levenberg-Marquardt method in combination with the Monte Carlo method for the initial approximation finding.
A multiscale approach to simulating the conformational properties of unbound multi-C₂H₂ zinc finger proteins.

PubMed

Liu, Lei; Wade, Rebecca C; Heermann, Dieter W

2015-09-01

The conformational properties of unbound multi-Cys2 His2 (mC2H2) zinc finger proteins, in which zinc finger domains are connected by flexible linkers, are studied by a multiscale approach. Three methods on different length scales are utilized. First, atomic detail molecular dynamics simulations of one zinc finger and its adjacent flexible linker confirmed that the zinc finger is more rigid than the flexible linker. Second, the end-to-end distance distributions of mC2H2 zinc finger proteins are computed using an efficient atomistic pivoting algorithm, which only takes excluded volume interactions into consideration. The end-to-end distance distribution gradually changes its profile, from left-tailed to right-tailed, as the number of zinc fingers increases. This is explained by using a worm-like chain model. For proteins of a few zinc fingers, an effective bending constraint favors an extended conformation. Only for proteins containing more than nine zinc fingers, is a somewhat compacted conformation preferred. Third, a mesoscale model is modified to study both the local and the global conformational properties of multi-C2H2 zinc finger proteins. Simulations of the CCCTC-binding factor (CTCF), an important mC2H2 zinc finger protein for genome spatial organization, are presented. © 2015 Wiley Periodicals, Inc.
Multi-fluid MHD simulations of Europa's interaction with Jupiter's magnetosphere

NASA Astrophysics Data System (ADS)

Harris, C. D. K.; Jia, X.; Slavin, J. A.; Rubin, M.; Toth, G.

2017-12-01

Several distinct physical processes generate the interaction between Europa, the smallest of Jupiter's Galilean moons, and Jupiter's magnetosphere. The 10˚ tilt of Jupiter's dipole causes time varying magnetic fields at Europa's orbit which interact with Europa's subsurface conducting ocean to induce magnetic perturbations around the moon. Jovian plasma interacts with Europa's icy surface to sputter off neutral particles, forming a tenuous exosphere which is then ionized by impact and photo-ionization to form an ionosphere. As jovian plasma flows towards the moon, mass-loading and interaction with the ionosphere slow the flow, producing magnetic perturbations that propagate along the field lines to form an Alfvén wing current system, which connects Europa to its bright footprint in Jupiter's ionosphere. The Galileo mission has shown that the plasma interaction generates significant magnetic perturbations that obscure signatures of the induced field from the subsurface ocean. Modeling the plasma-related perturbations is critical to interpreting the magnetic signatures of Europa's induction field, and therefore to magnetic sounding of its interior, a central goal of the upcoming Europa Clipper mission. Here we model the Europa-Jupiter interaction with multi-fluid magnetohydrodynamic simulations to understand quantitatively how these physical processes affect the plasma and magnetic environment around the moon. Our model separately tracks the bulk motion of three different ion fluids (exospheric O2+, O+, and magnetospheric O+), and includes sources and losses of mass, momentum and energy to each of the ion fluids due to ionization, charge-exchange and recombination. We include calculations of the electron temperature allowing for field-aligned electron heat conduction, and Hall effects due to differential ion-electron motion. Compared to previous simulations, this multi-fluid model allows us to more accurately determine the precipitation flux of jovian plasma to Europa's surface, which has significant implications for space weathering at the moon. Including the Hall effect in our simulations enables us to determine the effects of separate ion-electron bulk motion throughout the interaction, and our simulations reveal noticeable asymmetries and small-scale features in the Alfvén wings.
Multi-Level Risk Factors for Suicidal Ideation Among at-Risk Adolescent Females: The Role of Hypothalamic-Pituitary-Adrenal Axis Responses to Stress

PubMed Central

Calhoun, Casey D.; Hastings, Paul D.; Rudolph, Karen D.; Nock, Matthew K.; Prinstein, Mitchell J.

2014-01-01

Adopting a multi-level approach, this study examined risk factors for adolescent suicidal ideation, with specific attention to (a) hypothalamic-pituitary-adrenal (HPA) axis stress responses and (b) the interplay between HPA-axis and other risk factors from multiple domains (i.e., psychological, interpersonal and biological). Participants were 138 adolescent females (Mage=14.13 years, SD=1.40) at risk for suicidal behaviors. At baseline, lifetime suicidal ideation and a number of risk factors were assessed (i.e., depressive symptoms, impulsiveness, pubertal status and peer stress). Participants were exposed to a psychosocial stress task and HPA-axis responses were assessed by measuring cortisol levels pre- and post-stressor. At 3 months post-baseline, suicidal ideation again was assessed. Using group-based trajectory modeling, three groups of cortisol stress-response patterns were identified (i.e., hyporesponsive, normative, and hyperresponsive). As compared to females in the normative and hyporesponsive group, females in the hyperresponsive group were more likely to report a lifetime history of suicidal ideation at baseline, above and beyond the effects of the other predictors. Moreover, as compared to females in the normative group, females in the hyperresponsive group were at increased risk for reporting suicidal ideation 3 months later, after controlling for prior ideation. No interactions between cortisol group and the other risk factors were significant, with the exception of a non-significant trend between impulsiveness and cortisol group on lifetime suicidal ideation. Findings highlight the importance of HPA-axis responses to acute stressors as a risk factor for suicidal ideation among adolescents. PMID:24958308
3-D Wave-Structure Interaction with Coastal Sediments - A Multi-Physics/Multi-Solution Techniques Approach

DTIC Science & Technology

2007-01-01

Stokes (RANS) and the particle finite element method ( PFEM ) will be used in the water/mine/sand domain. Sand and the geomaterials around the sand will...wave propagation over a bottom mine at various time steps (Soil and Foam model) 8 SOLID/FEM SAND/SPH GEOMATERIALS FNPF/BEM FNPF/BEM RANS/ PFEM
Numerical Investigations of Two Typical Unsteady Flows in Turbomachinery Using the Multi-Passage Model

NASA Astrophysics Data System (ADS)

Zhou, Di; Lu, Zhiliang; Guo, Tongqing; Shen, Ennan

2016-06-01

In this paper, the research on two types of unsteady flow problems in turbomachinery including blade flutter and rotor-stator interaction is made by means of numerical simulation. For the former, the energy method is often used to predict the aeroelastic stability by calculating the aerodynamic work per vibration cycle. The inter-blade phase angle (IBPA) is an important parameter in computation and may have significant effects on aeroelastic behavior. For the latter, the numbers of blades in each row are usually not equal and the unsteady rotor-stator interactions could be strong. An effective way to perform multi-row calculations is the domain scaling method (DSM). These two cases share a common point that the computational domain has to be extended to multi passages (MP) considering their respective features. The present work is aimed at modeling these two issues with the developed MP model. Computational fluid dynamics (CFD) technique is applied to resolve the unsteady Reynolds-averaged Navier-Stokes (RANS) equations and simulate the flow fields. With the parallel technique, the additional time cost due to modeling more passages can be largely decreased. Results are presented on two test cases including a vibrating rotor blade and a turbine stage.
Agent-based model with multi-level herding for complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.
Agent-based model with multi-level herding for complex financial systems

PubMed Central

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-01-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

Multi-scale computational modeling of developmental biology.

PubMed

Setty, Yaki

2012-08-01

Normal development of multicellular organisms is regulated by a highly complex process in which a set of precursor cells proliferate, differentiate and move, forming over time a functioning tissue. To handle their complexity, developmental systems can be studied over distinct scales. The dynamics of each scale is determined by the collective activity of entities at the scale below it. I describe a multi-scale computational approach for modeling developmental systems and detail the methodology through a synthetic example of a developmental system that retains key features of real developmental systems. I discuss the simulation of the system as it emerges from cross-scale and intra-scale interactions and describe how an in silico study can be carried out by modifying these interactions in a way that mimics in vivo experiments. I highlight biological features of the results through a comparison with findings in Caenorhabditis elegans germline development and finally discuss about the applications of the approach in real developmental systems and propose future extensions. The source code of the model of the synthetic developmental system can be found in www.wisdom.weizmann.ac.il/~yaki/MultiScaleModel. yaki.setty@gmail.com Supplementary data are available at Bioinformatics online.
Chlorophenol sorption on multi-walled carbon nanotubes: DFT modeling and structure-property relationship analysis.

PubMed

Watkins, Marquita; Sizochenko, Natalia; Moore, Quentarius; Golebiowski, Marek; Leszczynska, Danuta; Leszczynski, Jerzy

2017-02-01

The presence of chlorophenols in drinking water can be hazardous to human health. Understanding the mechanisms of adsorption under specific experimental conditions would be beneficial when developing methods to remove toxic substances from drinking water during water treatment in order to limit human exposure to these contaminants. In this study, we investigated the sorption of chlorophenols on multi-walled carbon nanotubes using a density functional theory (DFT) approach. This was applied to study selected interactions between six solvents, five types of nanotubes, and six chlorophenols. Experimental data were used to construct structure-adsorption relationship (SAR) models that describe the recovery process. Specific interactions between solvents and chlorophenols were taken into account in the calculations by using novel specific mixture descriptors.
Detection of gene communities in multi-networks reveals cancer drivers

NASA Astrophysics Data System (ADS)

Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

2015-12-01

We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.
A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

NASA Astrophysics Data System (ADS)

Tao, W. K.

2017-12-01

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

Zhao, Jiao; Scheibe, Timothy D.; Mahadevan, Radhakrishnan

2011-01-24

Uranium contamination is a serious concern at several sites motivating the development of novel treatment strategies such as the Geobacter-mediated reductive immobilization of uranium. However, this bioremediation strategy has not yet been optimized for the sustained uranium removal. While several reactive-transport models have been developed to represent Geobacter-mediated bioremediation of uranium, these models often lack the detailed quantitative description of the microbial process (e.g., biomass build-up in both groundwater and sediments, electron transport system, etc.) and the interaction between biogeochemical and hydrological process. In this study, a novel multi-scale model was developed by integrating our recent model on electron capacitancemore » of Geobacter (Zhao et al., 2010) with a comprehensive simulator of coupled fluid flow, hydrologic transport, heat transfer, and biogeochemical reactions. This mechanistic reactive-transport model accurately reproduces the experimental data for the bioremediation of uranium with acetate amendment. We subsequently performed global sensitivity analysis with the reactive-transport model in order to identify the main sources of prediction uncertainty caused by synergistic effects of biological, geochemical, and hydrological processes. The proposed approach successfully captured significant contributing factors across time and space, thereby improving the structure and parameterization of the comprehensive reactive-transport model. The global sensitivity analysis also provides a potentially useful tool to evaluate uranium bioremediation strategy. The simulations suggest that under difficult environments (e.g., highly contaminated with U(VI) at a high migration rate of solutes), the efficiency of uranium removal can be improved by adding Geobacter species to the contaminated site (bioaugmentation) in conjunction with the addition of electron donor (biostimulation). The simulations also highlight the interactive effect of initial cell concentration and flow rate on U(VI) reduction.« less
Accuracies of univariate and multivariate genomic prediction models in African cassava.

PubMed

Okeke, Uche Godfrey; Akdemir, Deniz; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2017-12-04

Genomic selection (GS) promises to accelerate genetic gain in plant breeding programs especially for crop species such as cassava that have long breeding cycles. Practically, to implement GS in cassava breeding, it is necessary to evaluate different GS models and to develop suitable models for an optimized breeding pipeline. In this paper, we compared (1) prediction accuracies from a single-trait (uT) and a multi-trait (MT) mixed model for a single-environment genetic evaluation (Scenario 1), and (2) accuracies from a compound symmetric multi-environment model (uE) parameterized as a univariate multi-kernel model to a multivariate (ME) multi-environment mixed model that accounts for genotype-by-environment interaction for multi-environment genetic evaluation (Scenario 2). For these analyses, we used 16 years of public cassava breeding data for six target cassava traits and a fivefold cross-validation scheme with 10-repeat cycles to assess model prediction accuracies. In Scenario 1, the MT models had higher prediction accuracies than the uT models for all traits and locations analyzed, which amounted to on average a 40% improved prediction accuracy. For Scenario 2, we observed that the ME model had on average (across all locations and traits) a 12% improved prediction accuracy compared to the uE model. We recommend the use of multivariate mixed models (MT and ME) for cassava genetic evaluation. These models may be useful for other plant species.
Truck crash severity in New York city: An investigation of the spatial and the time of day effects.

PubMed

Zou, Wei; Wang, Xiaokun; Zhang, Dapeng

2017-02-01

This paper investigates the differences between single-vehicle and multi-vehicle truck crashes in New York City. The random parameter models take into account the time of day effect, the heterogeneous truck weight effect and other influencing factors such as crash characteristics, driver and vehicle characteristics, built environment factors and traffic volume attributes. Based on the results from the co-location quotient analysis, a spatial generalized ordered probit model is further developed to investigate the potential spatial dependency among single-vehicle truck crashes. The sample is drawn from the state maintained incident data, the publicly available Smart Location Data, and the BEST Practices Model (BPM) data from 2008 to 2012. The result shows that there exists a substantial difference between factors influencing single-vehicle and multi-vehicle truck crash severity. It also suggests that heterogeneity does exist in the truck weight, and it behaves differently in single-vehicle and multi-vehicle truck crashes. Furthermore, individual truck crashes are proved to be spatially dependent events for both single and multi-vehicle crashes. Last but not least, significant time of day effects were found for PM and night time slots, crashes that occurred in the afternoons and at nights were less severe in single-vehicle crashes, but more severe in multi-vehicle crashes. Copyright © 2016. Published by Elsevier Ltd.
Propagation factors of multi-sinc Schell-model beams in non-Kolmogorov turbulence.

PubMed

Song, Zhenzhen; Liu, Zhengjun; Zhou, Keya; Sun, Qiongge; Liu, Shutian

2016-01-25

We derive several analytical expressions for the root-mean-square (rms) angular width and the M(2)-factor of the multi-sinc Schell-model (MSSM) beams propagating in non-Kolmogorov turbulence with the extended Huygens-Fresnel principle and the second-order moments of the Wigner distribution function. Numerical results show that a MSSM beam with dark-hollow far fields in free space has advantage over the one with flat-topped or multi-rings far fields for reducing the turbulence-induced degradation, which will become more obvious with larger dark-hollow size. Beam quality of MSSM beams can be further improved with longer wavelength and larger beam width, or under the condition of weaker turbulence. We also demonstrate that the non-Kolmogorov turbulence has significantly less effect on the MSSM beams than the Gaussian Schell-model beam.
Brief Report: Learning via the Electronic Interactive Whiteboard for Two Students with Autism and a Student with Moderate Intellectual Disability

ERIC Educational Resources Information Center

Yakubova, Gulnoza; Taber-Doughty, Teresa

2013-01-01

The effects of a multicomponent intervention (a self-operated video modeling and self-monitoring delivered via an electronic interactive whiteboard (IWB) and a system of least prompts) on skill acquisition and interaction behavior of two students with autism and one student with moderate intellectual disability were examined using a multi-probe…
Potential barriers to the application of multi-factor portfolio analysis in public hospitals: evidence from a pilot study in the Netherlands.

PubMed

Pavlova, Milena; Tsiachristas, Apostolos; Vermaeten, Gerhard; Groot, Wim

2009-01-01

Portfolio analysis is a business management tool that can assist health care managers to develop new organizational strategies. The application of portfolio analysis to US hospital settings has been frequently reported. In Europe however, the application of this technique has received little attention, especially concerning public hospitals. Therefore, this paper examines the peculiarities of portfolio analysis and its applicability to the strategic management of European public hospitals. The analysis is based on a pilot application of a multi-factor portfolio analysis in a Dutch university hospital. The nature of portfolio analysis and the steps in a multi-factor portfolio analysis are reviewed along with the characteristics of the research setting. Based on these data, a multi-factor portfolio model is developed and operationalized. The portfolio model is applied in a pilot investigation to analyze the market attractiveness and hospital strengths with regard to the provision of three orthopedic services: knee surgery, hip surgery, and arthroscopy. The pilot portfolio analysis is discussed to draw conclusions about potential barriers to the overall adoption of portfolio analysis in the management of a public hospital. Copyright (c) 2008 John Wiley & Sons, Ltd.
Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2

NASA Technical Reports Server (NTRS)

1991-01-01

The technical effort and computer code enhancements performed during the sixth year of the Probabilistic Structural Analysis Methods program are summarized. Various capabilities are described to probabilistically combine structural response and structural resistance to compute component reliability. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. In addition, a user interface was developed for user-defined resistance models. An accurate and efficient reliability method was developed and was successfully implemented in the NESSUS code to compute component reliability based on user-selected response and resistance models. A risk module was developed to compute component risk with respect to cost, performance, or user-defined criteria. The new component risk assessment capabilities were validated and demonstrated using several examples. Various supporting methodologies were also developed in support of component risk assessment.
Multi-phase-field modeling of anisotropic crack propagation for polycrystalline materials

NASA Astrophysics Data System (ADS)

Nguyen, Thanh-Tung; Réthoré, Julien; Yvonnet, Julien; Baietto, Marie-Christine

2017-08-01

A new multi-phase-field method is developed for modeling the fracture of polycrystals at the microstructural level. Inter and transgranular cracking, as well as anisotropic effects of both elasticity and preferential cleavage directions within each randomly oriented crystal are taken into account. For this purpose, the proposed phase field formulation includes: (a) a smeared description of grain boundaries as cohesive zones avoiding defining an additional phase for grains; (b) an anisotropic phase field model; (c) a multi-phase field formulation where each preferential cleavage direction is associated with a damage (phase field) variable. The obtained framework allows modeling interactions and competition between grains and grain boundary cracks, as well as their effects on the effective response of the material. The proposed model is illustrated through several numerical examples involving a full description of complex crack initiation and propagation within 2D and 3D models of polycrystals.
A Multi-Domain Model of Risk Factors for ODD Symptoms in a Community Sample of 4-Year-Olds

ERIC Educational Resources Information Center

Lavigne, John V.; Gouze, Karen R.; Hopkins, Joyce; Bryant, Fred B.; LeBailly, Susan A.

2012-01-01

Few studies have been designed to assess the pathways by which risk factors are associated with symptoms of psychopathology across multiple domains, including contextual factors, parental depression, parenting, and child characteristics. The present study examines a cross-sectional model of risk factors for symptoms of Oppositional Defiant…
Development of a Thermodynamic Model for the Hanford Tank Waste Operations Simulator - 12193

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

Carter, Robert; Seniow, Kendra

The Hanford Tank Waste Operations Simulator (HTWOS) is the current tool used by the Hanford Tank Operations Contractor for system planning and assessment of different operational strategies. Activities such as waste retrievals in the Hanford tank farms and washing and leaching of waste in the Waste Treatment and Immobilization Plant (WTP) are currently modeled in HTWOS. To predict phase compositions during these activities, HTWOS currently uses simple wash and leach factors that were developed many years ago. To improve these predictions, a rigorous thermodynamic framework has been developed based on the multi-component Pitzer ion interaction model for use with severalmore » important chemical species in Hanford tank waste. These chemical species are those with the greatest impact on high-level waste glass production in the WTP and whose solubility depends on the processing conditions. Starting with Pitzer parameter coefficients and species chemical potential coefficients collated from open literature sources, reconciliation with published experimental data led to a self-consistent set of coefficients known as the HTWOS Pitzer database. Using Gibbs energy minimization with the Pitzer ion interaction equations in Microsoft Excel,1 a number of successful predictions were made for the solubility of simple mixtures of the chosen species. Currently, this thermodynamic framework is being programmed into HTWOS as the mechanism for determining the solid-liquid phase distributions for the chosen species, replacing their simple wash and leach factors. Starting from a variety of open literature sources, a collection of Pitzer parameters and species chemical potentials, as functions of temperature, was tested for consistency and accuracy by comparison with available experimental thermodynamic data (e.g., osmotic coefficients and solubility). Reconciliation of the initial set of parameter coefficients with the experimental data led to the development of the self-consistent set known as the HTWOS Pitzer database. Using Microsoft Excel to formulate the Gibbs energy minimization method and the multi-component Pitzer ion interaction equations, several predictions of the solubility of solute mixtures at various temperatures were made using the HTWOS Pitzer database coefficients. Examples of these predictions are shown in Figure 3 and Figure 4. A listing of the entire HTWOS Pitzer database can be found in RPP-RPT-50703. Currently, work is underway to install the Pitzer ion interaction model in HTWOS as the mechanism for determining the solid-liquid phase distributions of select waste constituents during tank retrievals and subsequent washing and leaching of the waste. Validation of the Pitzer ion interaction model in HTWOS will be performed with analytical laboratory data of actual tank waste. This change in HTWOS is expected to elicit shifts in mission criteria, such as mission end date and quantity of high-level waste glass produced by WTP, as predicted by HTWOS. These improvements to the speciation calculations in HTWOS, however, will establish a better planning basis and facilitate more effective and efficient future operations of the WTP. (authors)« less
Early Intervention for Reading Difficulties: The Interactive Strategies Approach

ERIC Educational Resources Information Center

Scanlon, Donna M.; Anderson, Kimberly L.; Sweeney, Joan M.

2010-01-01

This book presents a research-supported framework for early literacy instruction that aligns with multi-tiered response-to-intervention (RTI) models. The book focuses on giving teachers a better understanding of literacy development and how to effectively support children as they begin to read and write. The authors' interactive strategies…
Emerging functions of multi-protein complex Mediator with special emphasis on plants.

PubMed

Malik, Naveen; Agarwal, Pinky; Tyagi, Akhilesh

2017-10-01

Mediator is a multi-subunit protein complex which is involved in transcriptional regulation in yeast and other eukaryotes. As a co-activator, it connects information from transcriptional activators/repressors to transcriptional machinery including RNA polymerase II and general transcription factors. It is not only involved in transcription initiation but also has important roles to play in transcription elongation and termination. Functional attributes of different Mediator subunits have been largely defined in yeast and mammalian systems earlier, while such studies in plants have gained momentum recently. Mediator regulates various processes related to plant development and is also involved in biotic and abiotic stress response. Thus, plant Mediator, like yeast and mammalian Mediator complex, is indispensable for plant growth and survival. Interaction of its multiple subunits with other regulatory proteins and their ectopic expression or knockdown in model plant like Arabidopsis and certain crop plants are paving the way to biochemical analysis and unravel molecular mechanisms of action of Mediator in plants.
Modulational instability, beak-shaped rogue waves, multi-dark-dark solitons and dynamics in pair-transition-coupled nonlinear Schrödinger equations.

PubMed

Zhang, Guoqiang; Yan, Zhenya; Wen, Xiao-Yong

2017-07-01

The integrable coupled nonlinear Schrödinger equations with four-wave mixing are investigated. We first explore the conditions for modulational instability of continuous waves of this system. Secondly, based on the generalized N -fold Darboux transformation (DT), beak-shaped higher-order rogue waves (RWs) and beak-shaped higher-order rogue wave pairs are derived for the coupled model with attractive interaction in terms of simple determinants. Moreover, we derive the simple multi-dark-dark and kink-shaped multi-dark-dark solitons for the coupled model with repulsive interaction through the generalizing DT. We explore their dynamics and classifications by different kinds of spatial-temporal distribution structures including triangular, pentagonal, 'claw-like' and heptagonal patterns. Finally, we perform the numerical simulations to predict that some dark solitons and RWs are stable enough to develop within a short time. The results would enrich our understanding on nonlinear excitations in many coupled nonlinear wave systems with transition coupling effects.
Emergent of Burden Sharing of Robots with Emotion Model

NASA Astrophysics Data System (ADS)

Kusano, Takuya; Nozawa, Akio; Ide, Hideto

Cooperated multi robots system has much dominance in comparison with single robot system. Multi robots system is able to adapt to various circumstances and has a flexibility for variation of tasks. Robots are necessary that build a cooperative relations and acts as an organization to attain a purpose in multi robots system. Then, group behavior of insects which doesn't have advanced ability is observed. For example, ants called a sociality insect emerge systematic activities by the interaction with using a very simple way. Though ants make a communication with chemical matter, a human plans a communication by words and gestures. In this paper, we paid attention to the interaction based on psychological viewpoint. And a human's emotion model was used for the parameter which became a base of the motion planning of robots. These robots were made to do both-way action in test field with obstacle. As a result, a burden sharing like guide or carrier was seen even though those had a simple setup.
The importance of multi-level Rydberg interaction in electric field tuned Förster resonances

NASA Astrophysics Data System (ADS)

Kondo, Jorge; Booth, Donald; Gonçalves, Luis; Shaffer, James; Marcassa, Luis

2016-05-01

Many-body physics has been investigated in ultracold Rydberg atom systems, mainly because important parameters, such as density and interaction strength, can be controlled. Several puzzling experimental observations on Förster resonances have been associated to many-body effects, usually by comparison to complex theoretical models. In this work, we investigate the dc electric field dependence of 2 Förster resonant processes in ultracold 85 Rb, 37D5 / 2 + 37D5 / 2 --> 35 L(L = O , Q) + 39P3 / 2 , as a function of the atomic density in an optical dipole trap. At low densities, the 39 P yield as a function of electric field exhibits resonances. With increasing density, the linewidths increase until the peaks merge. Even under these extreme conditions, where many-body effects were expected to play a role, the 39 P population depends quadratically on the total Rydberg atom population. In order to explain our results, we implement a theoretical model which takes into account the multi-level character of the interactions and Rydberg atom blockade process using only atom pair interactions. The comparison between the experimental data and the model is very good, suggesting that the Förster resonant processes are dominated by 2-body interactions. This work is supported by FAPESP, AFOSR, NSF, INCT-IQ and CNPq.

MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS*

PubMed Central

CHAHINE, Georges L.; HSIAO, Chao-Tsung

2012-01-01

Controlling microbubble dynamics to produce desirable biomedical outcomes when and where necessary and avoid deleterious effects requires advanced knowledge, which can be achieved only through a combination of experimental and numerical/analytical techniques. The present communication presents a multi-physics approach to study the dynamics combining viscous- in-viscid effects, liquid and structure dynamics, and multi bubble interaction. While complex numerical tools are developed and used, the study aims at identifying the key parameters influencing the dynamics, which need to be included in simpler models. PMID:22833696
SpecViz: Interactive Spectral Data Analysis

NASA Astrophysics Data System (ADS)

Earl, Nicholas Michael; STScI

2016-06-01

The astronomical community is about to enter a new generation of scientific enterprise. With next-generation instrumentation and advanced capabilities, the need has arisen to equip astronomers with the necessary tools to deal with large, multi-faceted data. The Space Telescope Science Institute has initiated a data analysis forum for the creation, development, and maintenance of software tools for the interpretation of these new data sets. SpecViz is a spectral 1-D interactive visualization and analysis application built with Python in an open source development environment. A user-friendly GUI allows for a fast, interactive approach to spectral analysis. SpecViz supports handling of unique and instrument-specific data, incorporation of advanced spectral unit handling and conversions in a flexible, high-performance interactive plotting environment. Active spectral feature analysis is possible through interactive measurement and statistical tools. It can be used to build wide-band SEDs, with the capability of combining or overplotting data products from various instruments. SpecViz sports advanced toolsets for filtering and detrending spectral lines; identifying, isolating, and manipulating spectral features; as well as utilizing spectral templates for renormalizing data in an interactive way. SpecViz also includes a flexible model fitting toolset that allows for multi-component models, as well as custom models, to be used with various fitting and decomposition routines. SpecViz also features robust extension via custom data loaders and connection to the central communication system underneath the interface for more advanced control. Incorporation with Jupyter notebooks via connection with the active iPython kernel allows for SpecViz to be used in addition to a user’s normal workflow without demanding the user drastically alter their method of data analysis. In addition, SpecViz allows the interactive analysis of multi-object spectroscopy in the same straight-forward, consistent way. Through the development of such tools, STScI hopes to unify astronomical data analysis software for JWST and other instruments, allowing for efficient, reliable, and consistent scientific results.
Multi-Group Covariance and Mean Structure Modeling of the Relationship between the WAIS-III Common Factors and Sex and Educational Attainment in Spain

ERIC Educational Resources Information Center

Dolan, Conor V.; Colom, Roberto; Abad, Francisco J.; Wicherts, Jelte M.; Hessen, David J.; van de Sluis, Sophie

2006-01-01

We investigated sex effects and the effects of educational attainment (EA) on the covariance structure of the WAIS-III in a subsample of the Spanish standardization data. We fitted both first order common factor models and second order common factor models. The latter include general intelligence ("g") as a second order common factor.…
Screening large-scale association study data: exploiting interactions using random forests.

PubMed

Lunetta, Kathryn L; Hayward, L Brooke; Segal, Jonathan; Van Eerdewegh, Paul

2004-12-10

Genome-wide association studies for complex diseases will produce genotypes on hundreds of thousands of single nucleotide polymorphisms (SNPs). A logical first approach to dealing with massive numbers of SNPs is to use some test to screen the SNPs, retaining only those that meet some criterion for further study. For example, SNPs can be ranked by p-value, and those with the lowest p-values retained. When SNPs have large interaction effects but small marginal effects in a population, they are unlikely to be retained when univariate tests are used for screening. However, model-based screens that pre-specify interactions are impractical for data sets with thousands of SNPs. Random forest analysis is an alternative method that produces a single measure of importance for each predictor variable that takes into account interactions among variables without requiring model specification. Interactions increase the importance for the individual interacting variables, making them more likely to be given high importance relative to other variables. We test the performance of random forests as a screening procedure to identify small numbers of risk-associated SNPs from among large numbers of unassociated SNPs using complex disease models with up to 32 loci, incorporating both genetic heterogeneity and multi-locus interaction. Keeping other factors constant, if risk SNPs interact, the random forest importance measure significantly outperforms the Fisher Exact test as a screening tool. As the number of interacting SNPs increases, the improvement in performance of random forest analysis relative to Fisher Exact test for screening also increases. Random forests perform similarly to the univariate Fisher Exact test as a screening tool when SNPs in the analysis do not interact. In the context of large-scale genetic association studies where unknown interactions exist among true risk-associated SNPs or SNPs and environmental covariates, screening SNPs using random forest analyses can significantly reduce the number of SNPs that need to be retained for further study compared to standard univariate screening methods.
A Lagrangian stochastic model to demonstrate multi-scale interactions between convection and land surface heterogeneity in the atmospheric boundary layer

NASA Astrophysics Data System (ADS)

Parsakhoo, Zahra; Shao, Yaping

2017-04-01

Near-surface turbulent mixing has considerable effect on surface fluxes, cloud formation and convection in the atmospheric boundary layer (ABL). Its quantifications is however a modeling and computational challenge since the small eddies are not fully resolved in Eulerian models directly. We have developed a Lagrangian stochastic model to demonstrate multi-scale interactions between convection and land surface heterogeneity in the atmospheric boundary layer based on the Ito Stochastic Differential Equation (SDE) for air parcels (particles). Due to the complexity of the mixing in the ABL, we find that linear Ito SDE cannot represent convections properly. Three strategies have been tested to solve the problem: 1) to make the deterministic term in the Ito equation non-linear; 2) to change the random term in the Ito equation fractional, and 3) to modify the Ito equation by including Levy flights. We focus on the third strategy and interpret mixing as interaction between at least two stochastic processes with different Lagrangian time scales. The model is in progress to include the collisions among the particles with different characteristic and to apply the 3D model for real cases. One application of the model is emphasized: some land surface patterns are generated and then coupled with the Large Eddy Simulation (LES).
Predicting Trophic Interactions and Habitat Utilization in the California Current Ecosystem

DTIC Science & Technology

2014-09-30

on trophic interactions affecting habitat utilization and foraging patterns of California sea lions (CSL) in the California Current Large Marine...middle (sardine and anchovy) and higher (sea lions ) trophic level species. To this end, our numerical experiments are designed to isolate patterns of...NEMURO) embedded in a regional ocean circulation model (ROMS), and both coupled with a multi- species individual-based model (IBM) for forage fish
Look and Feel: Haptic Interaction for Biomedicine

DTIC Science & Technology

1995-10-01

algorithm that is evaluated within the topology of the model. During each time step, forces are summed for each mobile atom based on external forces...volumetric properties; (b) conserving computation power by rendering media local to the interaction point; and (c) evaluating the simulation within...alteration of the model topology. Simulation of the DSM state is accomplished by a multi-step algorithm that is evaluated within the topology of the
Framing Ethnic Variations in Alcohol Outcomes from Biological Pathways to Neighborhood Context

PubMed Central

Chartier, Karen G.; Scott, Denise M.; Wall, Tamara L.; Covault, Jonathan; Karriker-Jaffe, Katherine J.; Mills, Britain A.; Luczak, Susan E.; Caetano, Raul; Arroyo, Judith A.

2013-01-01

Health disparities research seeks to eliminate disproportionate negative health outcomes experienced in some racial/ethnic minority groups. This brief review presents findings on factors associated with drinking and alcohol-related problems in racial/ethnic groups. Those discussed are: 1) biological pathways to alcohol problems, 2) gene by stress interactions, 3) neighborhood disadvantage, stress, and access to alcohol, and 4) drinking cultures and contexts. These factors and their interrelationships are complex, requiring a multi-level perspective. The use of interdisciplinary teams and an epigenetic focus are suggested to move the research forward. The application of multi-level research to policy, prevention, and intervention programs may help prioritize combinations of the most promising intervention targets. PMID:24483624
Continuity of care in mental health: understanding and measuring a complex phenomenon.

PubMed

Burns, T; Catty, J; White, S; Clement, S; Ellis, G; Jones, I R; Lissouba, P; McLaren, S; Rose, D; Wykes, T

2009-02-01

Continuity of care is considered by patients and clinicians an essential feature of good quality care in long-term disorders, yet there is general agreement that it is a complex concept. Most policies emphasize it and encourage systems to promote it. Despite this, there is no accepted definition or measure against which to test policies or interventions designed to improve continuity. We aimed to operationalize a multi-axial model of continuity of care and to use factor analysis to determine its validity for severe mental illness. A multi-axial model of continuity of care comprising eight facets was operationalized for quantitative data collection from mental health service users using 32 variables. Of these variables, 22 were subsequently entered into a factor analysis as independent components, using data from a clinical population considered to require long-term consistent care. Factor analysis produced seven independent continuity factors accounting for 62.5% of the total variance. These factors, Experience and Relationship, Regularity, Meeting Needs, Consolidation, Managed Transitions, Care Coordination and Supported Living, were close but not identical to the original theoretical model. We confirmed that continuity of care is multi-factorial. Our seven factors are intuitively meaningful and appear to work in mental health. These factors should be used as a starting-point in research into the determinants and outcomes of continuity of care in long-term disorders.
Gender and racial differences in risk factors for sexually transmitted diseases among justice-involved youth

PubMed Central

Dembo, Richard; Childs, Kristina; Belenko, Steven; Schmeidler, James; Wareham, Jennifer

2010-01-01

Gender and racial differences in infection rates for chlamydia and gonorrhea have been reported within community-based populations, but little is known of such differences within juvenile offending populations. Moreover, while research has demonstrated that certain individual-level and community-level factors affect risky behaviors associated with sexually transmitted disease (STD), less is known about how multi-level factors affect STD infection, particularly among delinquent populations. The present study investigated gender and racial differences in STD infection among a sample of 924 juvenile offenders. Generalized linear model regression analyses were conducted to examine the influence of individual-level factors such as age, offense history, and substance use and community-level factors such as concentrated disadvantage, ethnic heterogeneity, and family disruption on STD status. Results revealed significant racial and STD status differences across gender, as well as interaction effects for race and STD status for males only. Gender differences in individual-level and community-level predictors were also found. Implications of these findings for future research and public health policy are discussed. PMID:20700475
Associations between homocysteine metabolism related SNPs and carotid intima-media thickness: a Chinese sib pair study.

PubMed

Sun, Kexin; Song, Jing; Liu, Kuo; Fang, Kai; Wang, Ling; Wang, Xueyin; Li, Jing; Tang, Xun; Wu, Yiqun; Qin, Xueying; Wu, Tao; Gao, Pei; Chen, Dafang; Hu, Yonghua

2017-04-01

Carotid intima-media thickness (CIMT) is a good surrogate for atherosclerosis. Hyperhomocysteinemia is an independent risk factor for cardiovascular diseases. We aim to investigate the relationships between homocysteine (Hcy) related biochemical indexes and CIMT, the associations between Hcy related SNPs and CIMT, as well as the potential gene-gene interactions. The present study recruited full siblings (186 eligible families with 424 individuals) with no history of cardiovascular events from a rural area of Beijing. We examined CIMT, intima-media thickness for common carotid artery (CCA-IMT) and carotid bifurcation, tested plasma levels for Hcy, vitamin B6 (VB6), vitamin B12 (VB12) and folic acid (FA), and genotyped 9 SNPs on MTHFR, MTR, MTRR, BHMT, SHMT1, CBS genes. Associations between SNPs and biochemical indexes and CIMT indexes were analyzed using family-based association test analysis. We used multi-level mixed-effects regression model to verify SNP-CIMT associations and to explore the potential gene-gene interactions. VB6, VB12 and FA were negatively correlated with CIMT indexes (p < 0.05). rs2851391 T allele was associated with decreased plasma VB12 levels (p = 0.036). In FABT, CBS rs2851391 was significantly associated with CCA-IMT (p = 0.021) and CIMT (p = 0.019). In multi-level mixed-effects regression model, CBS rs2851391 was positively significantly associated with CCA-IMT (Coef = 0.032, se = 0.009, raw p < 0.001) after Bonferoni correction (corrected α = 0.0056). Gene-gene interactions were found between CBS rs2851391 and BHMT rs10037045 for CCA-IMT (p = 0.011), as well as between CBS rs2851391 and MTR rs1805087 for CCA-IMT (p = 0.007) and CIMT (p = 0.022). Significant associations are found between Hcy metabolism related genetic polymorphisms, biochemical indexes and CIMT indexes. There are complex interactions between genetic polymorphisms for CCA-IMT and CIMT.
Modelling End-User of Electronic-Government Service: The Role of Information quality, System Quality and Trust

NASA Astrophysics Data System (ADS)

Witarsyah Jacob, Deden; Fudzee, Mohd Farhan Md; Aizi Salamat, Mohamad; Kasim, Shahreen; Mahdin, Hairulnizam; Azhar Ramli, Azizul

2017-08-01

Many governments around the world increasingly use internet technologies such as electronic government to provide public services. These services range from providing the most basic informational website to deploying sophisticated tools for managing interactions between government agencies and beyond government. Electronic government (e-government) aims to provide a more accurate, easily accessible, cost-effective and time saving for the community. In this study, we develop a new model of e-government adoption service by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) through the incorporation of some variables such as System Quality, Information Quality and Trust. The model is then tested using a large-scale, multi-site survey research of 237 Indonesian citizens. This model will be validated by using Structural Equation Modeling (SEM). The result indicates that System Quality, Information Quality and Trust variables proven to effect user behavior. This study extends the current understanding on the influence of System Quality, Information Quality and Trust factors to researchers, practitioners, and policy makers.
Entropy measure of credit risk in highly correlated markets

NASA Astrophysics Data System (ADS)

Gottschalk, Sylvia

2017-07-01

We compare the single and multi-factor structural models of corporate default by calculating the Jeffreys-Kullback-Leibler divergence between their predicted default probabilities when asset correlations are either high or low. Single-factor structural models assume that the stochastic process driving the value of a firm is independent of that of other companies. A multi-factor structural model, on the contrary, is built on the assumption that a single firm's value follows a stochastic process correlated with that of other companies. Our main results show that the divergence between the two models increases in highly correlated, volatile, and large markets, but that it is closer to zero in small markets, when asset correlations are low and firms are highly leveraged. These findings suggest that during periods of financial instability, when asset volatility and correlations increase, one of the models misreports actual default risk.
Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials.

PubMed

Dias, Kaio Olímpio Das Graças; Gezan, Salvador Alejandro; Guimarães, Claudia Teixeira; Nazarian, Alireza; da Costa E Silva, Luciano; Parentoni, Sidney Netto; de Oliveira Guimarães, Paulo Evaristo; de Oliveira Anoni, Carina; Pádua, José Maria Villela; de Oliveira Pinto, Marcos; Noda, Roberto Willians; Ribeiro, Carlos Alexandre Gomes; de Magalhães, Jurandir Vieira; Garcia, Antonio Augusto Franco; de Souza, João Cândido; Guimarães, Lauro José Moreira; Pastina, Maria Marta

2018-07-01

Breeding for drought tolerance is a challenging task that requires costly, extensive, and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here, we evaluated the accuracy of genomic selection (GS) using additive (A) and additive + dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multi-environment trials. Phenotypic data of five drought tolerance traits were measured in 308 hybrids along eight trials under water-stressed (WS) and well-watered (WW) conditions over two years and two locations in Brazil. Hybrids' genotypes were inferred based on their parents' genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GS analyses were performed using genomic best linear unbiased prediction by fitting a factor analytic (FA) multiplicative mixed model. Two cross-validation (CV) schemes were tested: CV1 and CV2. The FA framework allowed for investigating the stability of additive and dominance effects across environments, as well as the additive-by-environment and the dominance-by-environment interactions, with interesting applications for parental and hybrid selection. Results showed differences in the predictive accuracy between A and AD models, using both CV1 and CV2, for the five traits in both water conditions. For grain yield (GY) under WS and using CV1, the AD model doubled the predictive accuracy in comparison to the A model. Through CV2, GS models benefit from borrowing information of correlated trials, resulting in an increase of 40% and 9% in the predictive accuracy of GY under WS for A and AD models, respectively. These results highlight the importance of multi-environment trial analyses using GS models that incorporate additive and dominance effects for genomic predictions of GY under drought in maize single-cross hybrids.
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.
Considerations in representing human individuals in social ecological models

USGS Publications Warehouse

Manfredo, Michael J.; Teel, Tara L.; Gavin, Michael C.; Fulton, David C.

2017-01-01

In this chapter we focus on how to integrate the human individual into social-ecological systems analysis, and how to improve research on individual thought and action regarding the environment by locating it within the broader social-ecological context. We discuss three key questions as considerations for future research: (1) is human thought conceptualized as a dynamic and adaptive process, (2) is the individual placed in a multi-level context (including within-person levels, person-group interactions, and institutional and structural factors), and (3) is human thought seen as mutually constructed with the social and natural environment. Increased emphasis on the individual will be essential if we are to understand agency, innovation, and adaptation in social-ecological systems.
Understanding Cortisol Reactivity across the Day at Child Care: The Potential Buffering Role of Secure Attachments to Caregivers

PubMed Central

Badanes, Lisa S.; Dmitrieva, Julia; Watamura, Sarah Enos

2011-01-01

Full-day center-based child care has been repeatedly associated with rising cortisol across the child care day. This study addressed the potential buffering role of attachment to mothers and lead teachers in 110 preschoolers while at child care. Using multi-level modeling and controlling for a number of child, family, and child care factors, children with more secure attachments to teachers were more likely to show falling cortisol across the child care day. Attachment to mothers interacted with child care quality, with buffering effects found for children with secure attachments attending higher quality child care. Implications for early childhood educators are discussed. PMID:22408288
Biomaterial science meets computational biology.

PubMed

Hutmacher, Dietmar W; Little, J Paige; Pettet, Graeme J; Loessner, Daniela

2015-05-01

There is a pressing need for a predictive tool capable of revealing a holistic understanding of fundamental elements in the normal and pathological cell physiology of organoids in order to decipher the mechanoresponse of cells. Therefore, the integration of a systems bioengineering approach into a validated mathematical model is necessary to develop a new simulation tool. This tool can only be innovative by combining biomaterials science with computational biology. Systems-level and multi-scale experimental data are incorporated into a single framework, thus representing both single cells and collective cell behaviour. Such a computational platform needs to be validated in order to discover key mechano-biological factors associated with cell-cell and cell-niche interactions.
A brief review of salient factors influencing adult eating behaviour.

PubMed

Emilien, Christine; Hollis, James H

2017-12-01

A better understanding of the factors that influence eating behaviour is of importance as our food choices are associated with the risk of developing chronic diseases such as obesity, CVD, type 2 diabetes or some forms of cancer. In addition, accumulating evidence suggests that the industrial food production system is a major contributor to greenhouse gas emission and may be unsustainable. Therefore, our food choices may also contribute to climate change. By identifying the factors that influence eating behaviour new interventions may be developed, at the individual or population level, to modify eating behaviour and contribute to society's health and environmental goals. Research indicates that eating behaviour is dictated by a complex interaction between physiology, environment, psychology, culture, socio-economics and genetics that is not fully understood. While a growing body of research has identified how several single factors influence eating behaviour, a better understanding of how these factors interact is required to facilitate the developing new models of eating behaviour. Due to the diversity of influences on eating behaviour this would probably necessitate a greater focus on multi-disciplinary research. In the present review, the influence of several salient physiological and environmental factors (largely related to food characteristics) on meal initiation, satiation (meal size) and satiety (inter-meal interval) are briefly discussed. Due to the large literature this review is not exhaustive but illustrates the complexity of eating behaviour. The present review will also highlight several limitations that apply to eating behaviour research.
Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism

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

Ucciferri, Nadia; Interdepartmental Research Center “E. Piaggio”, University of Pisa, Pisa; Sbrana, Tommaso

2014-12-17

Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell–cell or cell–tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting differentmore » cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.« less

Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism.

PubMed

Ucciferri, Nadia; Sbrana, Tommaso; Ahluwalia, Arti

2014-01-01

Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell-cell or cell-tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.
A Discontinuous Potential Model for Protein-Protein Interactions.

PubMed

Shao, Qing; Hall, Carol K

2016-01-01

Protein-protein interactions play an important role in many biologic and industrial processes. In this work, we develop a two-bead-per-residue model that enables us to account for protein-protein interactions in a multi-protein system using discontinuous molecular dynamics simulations. This model deploys discontinuous potentials to describe the non-bonded interactions and virtual bonds to keep proteins in their native state. The geometric and energetic parameters are derived from the potentials of mean force between sidechain-sidechain, sidechain-backbone, and backbone-backbone pairs. The energetic parameters are scaled with the aim of matching the second virial coefficient of lysozyme reported in experiment. We also investigate the performance of several bond-building strategies.
Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models.

PubMed

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

2014-02-26

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

PubMed Central

2014-01-01

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

ERIC Educational Resources Information Center

Vidotto, G.; Massidda, D.; Noventa, S.

2010-01-01

The Functional Measurement approach, proposed within the theoretical framework of Information Integration Theory (Anderson, 1981, 1982), can be a useful multi-attribute analysis tool. Compared to the majority of statistical models, the averaging model can account for interaction effects without adding complexity. The R-Average method (Vidotto &…
Primary Cosmic-Ray Spectra in the Knee Region

NASA Astrophysics Data System (ADS)

Ter-Antonyan, Samvel V.; Biermann, P. L.

2003-07-01

Using EAS inverse approach and KASCADE EAS data the primary energy spectra for different primary nuclei at energies 1015 - 1017 eV are obtained in the framework of multi-comp onent model of primary cosmic ray origin and QGSJET and SIBYLL interaction models. The rigidity-dep endent behavior of spectra is the same for two interaction models. The extrap olation of the obtained primary spectra in a 1017 - 1018 eV energy range displays a presence of the extragalactic component of primary cosmic rays.
Multishaker modal testing

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.

1987-01-01

The major accomplishments of this research are: (1) the refinement and documentation of a multi-input, multi-output modal parameter estimation algorithm which is applicable to general linear, time-invariant dynamic systems; (2) the development and testing of an unsymmetric block-Lanzcos algorithm for reduced-order modeling of linear systems with arbitrary damping; and (3) the development of a control-structure-interaction (CSI) test facility.
Systems Biology Approaches for Host–Fungal Interactions: An Expanding Multi-Omics Frontier

PubMed Central

Culibrk, Luka; Croft, Carys A.

2016-01-01

Abstract Opportunistic fungal infections are an increasing threat for global health, and for immunocompromised patients in particular. These infections are characterized by interaction between fungal pathogen and host cells. The exact mechanisms and the attendant variability in host and fungal pathogen interaction remain to be fully elucidated. The field of systems biology aims to characterize a biological system, and utilize this knowledge to predict the system's response to stimuli such as fungal exposures. A multi-omics approach, for example, combining data from genomics, proteomics, metabolomics, would allow a more comprehensive and pan-optic “two systems” biology of both the host and the fungal pathogen. In this review and literature analysis, we present highly specialized and nascent methods for analysis of multiple -omes of biological systems, in addition to emerging single-molecule visualization techniques that may assist in determining biological relevance of multi-omics data. We provide an overview of computational methods for modeling of gene regulatory networks, including some that have been applied towards the study of an interacting host and pathogen. In sum, comprehensive characterizations of host–fungal pathogen systems are now possible, and utilization of these cutting-edge multi-omics strategies may yield advances in better understanding of both host biology and fungal pathogens at a systems scale. PMID:26885725
Visualization of Spatio-Temporal Relations in Movement Event Using Multi-View

NASA Astrophysics Data System (ADS)

Zheng, K.; Gu, D.; Fang, F.; Wang, Y.; Liu, H.; Zhao, W.; Zhang, M.; Li, Q.

2017-09-01

Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.
Chandra Interactive Analysis of Observations (CIAO)

NASA Technical Reports Server (NTRS)

Dobrzycki, Adam

2000-01-01

The Chandra (formerly AXAF) telescope, launched on July 23, 1999, provides X-rays data with unprecedented spatial and spectral resolution. As part of the Chandra scientific support, the Chandra X-ray Observatory Center provides a new data analysis system, CIAO ("Chandra Interactive Analysis of Observations"). We will present the main components of the system: "First Look" analysis; SHERPA: a multi-dimensional, multi-mission modeling and fitting application; Chandra Imaging and Plotting System; Detect package-source detection algorithms; and DM package generic data manipulation tools, We will set up a demonstration of the portable version of the system and show examples of Chandra Data Analysis.
Study of CFB Simulation Model with Coincidence at Multi-Working Condition

NASA Astrophysics Data System (ADS)

Wang, Z.; He, F.; Yang, Z. W.; Li, Z.; Ni, W. D.

A circulating fluidized bed (CFB) two-stage simulation model was developed. To realize the model results coincident with the design value or real operation value at specified multi-working conditions and with capability of real-time calculation, only the main key processes were taken into account and the dominant factors were further abstracted out of these key processes. The simulation results showed a sound accordance at multi-working conditions, and confirmed the advantage of the two-stage model over the original single-stage simulation model. The combustion-support effect of secondary air was investigated using the two-stage model. This model provides a solid platform for investigating the pant-leg structured CFB furnace, which is now under design for a supercritical power plant.
Multi-physics 3D computational study of leaflet thrombus formation following surgical and transcatheter aortic valve replacement

NASA Astrophysics Data System (ADS)

Vahidkhah, Koohyar; Abbasi, Mostafa; Barakat, Mohammed; Dvir, Danny; Azadani, Ali

2017-11-01

An increasingly recognized complication following surgical/transcatheter aortic valve replacement is thrombosis or blood clot formation on replacement valve leaflets. A predisposing factor in thrombus formation on biomaterial surfaces of a bioprosthetic heart valve is blood stasis. Longer residence time of blood provides an opportunity for platelets and agonists to accumulate to critical concentrations that leads to platelet activation and then thrombosis. In this study, we have developed a fluid-solid interaction (FSI) modeling approach, to quantify blood stasis on the leaflets of bioprosthetic aortic valves with different design operating in a patient-specific geometry. We have validated our FSI model against experimental measurements of valve opening/closing as well as in-vitro particle image velocimetry. We have also embedded in our method a model for transport of platelets and agonists (ADP, TxA2, and thrombin) and their interactions that result in platelets activation and adhesion to biomaterial bioprosthetic surfaces. We have provided quantitative evidence for the correlation between long residence of blood on bioprosthetic aortic valve leaflets and formation of high thrombogenicity risk regions on the leaflets that are characterized by accumulation of activated platelet.
Latent Constructs in Psychosocial Factors Associated with Cardiovascular Disease: An Examination by Race and Sex

PubMed Central

Clark, Cari Jo; Henderson, Kimberly M.; de Leon, Carlos F. Mendes; Guo, Hongfei; Lunos, Scott; Evans, Denis A.; Everson-Rose, Susan A.

2012-01-01

This study examines race and sex differences in the latent structure of 10 psychosocial measures and the association of identified factors with self-reported history of coronary heart disease (CHD). Participants were 4,128 older adults from the Chicago Health and Aging Project. Exploratory factor analysis (EFA) with oblique geomin rotation was used to identify latent factors among the psychosocial measures. Multi-group comparisons of the EFA model were conducted using exploratory structural equation modeling to test for measurement invariance across race and sex subgroups. A factor-based scale score was created for invariant factor(s). Logistic regression was used to test the relationship between the factor score(s) and CHD adjusting for relevant confounders. Effect modification of the relationship by race–sex subgroup was tested. A two-factor model fit the data well (comparative fit index = 0.986; Tucker–Lewis index = 0.969; root mean square error of approximation = 0.039). Depressive symptoms, neuroticism, perceived stress, and low life satisfaction loaded on Factor I. Social engagement, spirituality, social networks, and extraversion loaded on Factor II. Only Factor I, re-named distress, showed measurement invariance across subgroups. Distress was associated with a 37% increased odds of self-reported CHD (odds ratio: 1.37; 95% confidence intervals: 1.25, 1.50; p-value < 0.0001). This effect did not differ by race or sex (interaction p-value = 0.43). This study identified two underlying latent constructs among a large range of psychosocial variables; only one, distress, was validly measured across race–sex subgroups. This construct was robustly related to prevalent CHD, highlighting the potential importance of latent constructs as predictors of cardiovascular disease. PMID:22347196
Population-based health promotion perspective for older driver safety: Conceptual framework to intervention plan

PubMed Central

Classen, Sherrilene; Lopez, Ellen DS; Winter, Sandra; Awadzi, Kezia D; Ferree, Nita; Garvan, Cynthia W

2007-01-01

The topic of motor vehicle crashes among the elderly is dynamic and multi-faceted requiring a comprehensive and synergistic approach to intervention planning. This approach must be based on the values of a given population as well as health statistics and asserted through community, organizational and policy strategies. An integrated summary of the predictors (quantitative research), and views (qualitative research) of the older drivers and their stakeholders, does not currently exist. This study provided an explicit socio-ecological view explaining the interrelation of possible causative factors, an integrated summary of these causative factors, and empirical guidelines for developing public health interventions to promote older driver safety. Using a mixed methods approach, we were able to compare and integrate main findings from a national crash dataset with perspectives of stakeholders. We identified: 11 multi-causal factors for safe elderly driving; the importance of the environmental factors - previously underrated in the literature- interacting with behavioral and health factors; and the interrelatedness among many socio-ecological factors. For the first time, to our knowledge, we conceptualized the fundamental elements of a multi-causal health promotion plan, with measurable intermediate and long-term outcomes. After completing the detailed plan we will test the effectiveness of this intervention on multiple levels. PMID:18225470
Microscopic modeling of multi-lane highway traffic flow

NASA Astrophysics Data System (ADS)

Hodas, Nathan O.; Jagota, Anand

2003-12-01

We discuss a microscopic model for the study of multi-lane highway traffic flow dynamics. Each car experiences a force resulting from a combination of the desire of the driver to attain a certain velocity, aerodynamic drag, and change of the force due to car-car interactions. The model also includes multi-lane simulation capability and the ability to add and remove obstructions. We implement the model via a Java applet, which is used to simulate traffic jam formation, the effect of bottlenecks on traffic flow, and the existence of light, medium, and heavy traffic flow. The simulations also provide insight into how the properties of individual cars result in macroscopic behavior. Because the investigation of emergent characteristics is so common in physics, the study of traffic in this manner sheds new light on how the micro-to-macro transition works in general.
Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty.

PubMed

Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning

2018-03-05

This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.
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.
Ethno-Pedagogical Factor of Polycultural Training

ERIC Educational Resources Information Center

Fahrutdinova, Guzaliya Zh.

2016-01-01

With the increased tension in human relations, in a burst of misunderstanding, ethnic conflicts, which have proliferated in a new socio-cultural environment, the study of processes of interaction in multi-ethnic educational environment and upbringing, the emerging national identity for centuries, actualizes the importance of contemporary problems…
Community-level cohesion without cooperation.

PubMed

Tikhonov, Mikhail

2016-06-16

Recent work draws attention to community-community encounters ('coalescence') as likely an important factor shaping natural ecosystems. This work builds on MacArthur's classic model of competitive coexistence to investigate such community-level competition in a minimal theoretical setting. It is shown that the ability of a species to survive a coalescence event is best predicted by a community-level 'fitness' of its native community rather than the intrinsic performance of the species itself. The model presented here allows formalizing a macroscopic perspective whereby a community harboring organisms at varying abundances becomes equivalent to a single organism expressing genes at different levels. While most natural communities do not satisfy the strict criteria of multicellularity developed by multi-level selection theory, the effective cohesion described here is a generic consequence of resource partitioning, requires no cooperative interactions, and can be expected to be widespread in microbial ecosystems.
Reduced-Order Biogeochemical Flux Model for High-Resolution Multi-Scale Biophysical Simulations

NASA Astrophysics Data System (ADS)

Smith, Katherine; Hamlington, Peter; Pinardi, Nadia; Zavatarelli, Marco

2017-04-01

Biogeochemical tracers and their interactions with upper ocean physical processes such as submesoscale circulations and small-scale turbulence are critical for understanding the role of the ocean in the global carbon cycle. These interactions can cause small-scale spatial and temporal heterogeneity in tracer distributions that can, in turn, greatly affect carbon exchange rates between the atmosphere and interior ocean. For this reason, it is important to take into account small-scale biophysical interactions when modeling the global carbon cycle. However, explicitly resolving these interactions in an earth system model (ESM) is currently infeasible due to the enormous associated computational cost. As a result, understanding and subsequently parameterizing how these small-scale heterogeneous distributions develop and how they relate to larger resolved scales is critical for obtaining improved predictions of carbon exchange rates in ESMs. In order to address this need, we have developed the reduced-order, 17 state variable Biogeochemical Flux Model (BFM-17) that follows the chemical functional group approach, which allows for non-Redfield stoichiometric ratios and the exchange of matter through units of carbon, nitrate, and phosphate. This model captures the behavior of open-ocean biogeochemical systems without substantially increasing computational cost, thus allowing the model to be combined with computationally-intensive, fully three-dimensional, non-hydrostatic large eddy simulations (LES). In this talk, we couple BFM-17 with the Princeton Ocean Model and show good agreement between predicted monthly-averaged results and Bermuda testbed area field data (including the Bermuda-Atlantic Time-series Study and Bermuda Testbed Mooring). Through these tests, we demonstrate the capability of BFM-17 to accurately model open-ocean biochemistry. Additionally, we discuss the use of BFM-17 within a multi-scale LES framework and outline how this will further our understanding of turbulent biophysical interactions in the upper ocean.

Reduced-Order Biogeochemical Flux Model for High-Resolution Multi-Scale Biophysical Simulations

NASA Astrophysics Data System (ADS)

Smith, K.; Hamlington, P.; Pinardi, N.; Zavatarelli, M.; Milliff, R. F.

2016-12-01

Biogeochemical tracers and their interactions with upper ocean physical processes such as submesoscale circulations and small-scale turbulence are critical for understanding the role of the ocean in the global carbon cycle. These interactions can cause small-scale spatial and temporal heterogeneity in tracer distributions which can, in turn, greatly affect carbon exchange rates between the atmosphere and interior ocean. For this reason, it is important to take into account small-scale biophysical interactions when modeling the global carbon cycle. However, explicitly resolving these interactions in an earth system model (ESM) is currently infeasible due to the enormous associated computational cost. As a result, understanding and subsequently parametrizing how these small-scale heterogeneous distributions develop and how they relate to larger resolved scales is critical for obtaining improved predictions of carbon exchange rates in ESMs. In order to address this need, we have developed the reduced-order, 17 state variable Biogeochemical Flux Model (BFM-17). This model captures the behavior of open-ocean biogeochemical systems without substantially increasing computational cost, thus allowing the model to be combined with computationally-intensive, fully three-dimensional, non-hydrostatic large eddy simulations (LES). In this talk, we couple BFM-17 with the Princeton Ocean Model and show good agreement between predicted monthly-averaged results and Bermuda testbed area field data (including the Bermuda-Atlantic Time Series and Bermuda Testbed Mooring). Through these tests, we demonstrate the capability of BFM-17 to accurately model open-ocean biochemistry. Additionally, we discuss the use of BFM-17 within a multi-scale LES framework and outline how this will further our understanding of turbulent biophysical interactions in the upper ocean.
Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering

PubMed Central

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time. PMID:26270539
Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering.

PubMed

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time.
Generalized information fusion and visualization using spatial voting and data modeling

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.

2013-05-01

We present a novel and innovative information fusion and visualization framework for multi-source intelligence (multiINT) data using Spatial Voting (SV) and Data Modeling. We describe how different sources of information can be converted into numerical form for further processing downstream, followed by a short description of how this information can be fused using the SV grid. As an illustrative example, we show the modeling of cyberspace as cyber layers for the purpose of tracking cyber personas. Finally we describe a path ahead for creating interactive agile networks through defender customized Cyber-cubes for network configuration and attack visualization.
NASA Jet Noise Research

NASA Technical Reports Server (NTRS)

Henderson, Brenda

2016-01-01

The presentation highlights NASA's jet noise research for 2016. Jet-noise modeling efforts, jet-surface interactions results, acoustic characteristics of multi-stream jets, and N+2 Supersonic Aircraft system studies are presented.
Prosocial behavior as a protective factor for children's peer victimization.

PubMed

Griese, Emily R; Buhs, Eric S

2014-07-01

A majority of peer victimization research focuses on its associations with negative outcomes, yet efforts to understand possible protective factors that may mitigate these negative outcomes also require attention. The present study was an investigation of the potential moderating effect of prosocial behaviors on loneliness for youth who are peer victimized. Participants were fourth and fifth grade students (511 total; 49 % boys) who were primarily European American (43.4 %) and Hispanic (48.2 %). Structural Equation Modeling was used to test the interaction of prosocial behavior and peer victimization (relational and overt forms) on loneliness 1 year later. The results indicated that prosocial behavior significantly moderated the relationship between peer victimization (for the relational form only) and loneliness while controlling for levels of perceived peer support. A multi-group comparison by gender further indicated the moderation was significant for boys only. Potential implications for intervention/prevention efforts focused on developing children's prosocial skills as a possible protective factor for relationally victimized youth are discussed.
Geometry modeling and multi-block grid generation for turbomachinery configurations

NASA Technical Reports Server (NTRS)

Shih, Ming H.; Soni, Bharat K.

1992-01-01

An interactive 3D grid generation code, Turbomachinery Interactive Grid genERation (TIGER), was developed for general turbomachinery configurations. TIGER features the automatic generation of multi-block structured grids around multiple blade rows for either internal, external, or internal-external turbomachinery flow fields. Utilization of the Bezier's curves achieves a smooth grid and better orthogonality. TIGER generates the algebraic grid automatically based on geometric information provided by its built-in pseudo-AI algorithm. However, due to the large variation of turbomachinery configurations, this initial grid may not always be as good as desired. TIGER therefore provides graphical user interactions during the process which allow the user to design, modify, as well as manipulate the grid, including the capability of elliptic surface grid generation.
No Association Between Variant N-acetyltransferase Genes, Cigarette Smoking and Prostate Cancer Susceptibility Among Men of African Descent

PubMed Central

Kidd, La Creis Renee; VanCleave, Tiva T.; Doll, Mark A.; Srivastava, Daya S.; Thacker, Brandon; Komolafe, Oyeyemi; Pihur, Vasyl; Brock, Guy N.; Hein, David W.

2011-01-01

Objective We evaluated the individual and combination effects of NAT1, NAT2 and tobacco smoking in a case-control study of 219 incident prostate cancer (PCa) cases and 555 disease-free men. Methods Allelic discriminations for 15 NAT1 and NAT2 loci were detected in germ-line DNA samples using Taqman polymerase chain reaction (PCR) assays. Single gene, gene-gene and gene-smoking interactions were analyzed using logistic regression models and multi-factor dimensionality reduction (MDR) adjusted for age and subpopulation stratification. MDR involves a rigorous algorithm that has ample statistical power to assess and visualize gene-gene and gene-environment interactions using relatively small samples sizes (i.e., 200 cases and 200 controls). Results Despite the relatively high prevalence of NAT1*10/*10 (40.1%), NAT2 slow (30.6%), and NAT2 very slow acetylator genotypes (10.1%) among our study participants, these putative risk factors did not individually or jointly increase PCa risk among all subjects or a subset analysis restricted to tobacco smokers. Conclusion Our data do not support the use of N-acetyltransferase genetic susceptibilities as PCa risk factors among men of African descent; however, subsequent studies in larger sample populations are needed to confirm this finding. PMID:21709725
Psychological and social factors affecting Internet searches on suicide in Korea: a big data analysis of Google search trends.

PubMed

Song, Tae Min; Song, Juyoung; An, Ji-Young; Hayman, Laura L; Woo, Jong-Min

2014-01-01

The average mortality rate for death by suicide among OECD countries is 12.8 per 100000, and 33.5 for Korea. The present study analyzed big data extracted from Google to identify factors related to searches on suicide in Korea. Google search trends for the search words of suicide, stress, exercise, and drinking were obtained for 2004-2010. Analyzing data by month, the relationship between the actual number of suicides and search words per year was examined using multi-level models. Both suicide rates and Google searches on suicide in Korea increased since 2007. An unconditional slope model indicated stress and suicide-related searches were positively related. A conditional model showed that factors associated with suicide by year directly affected suicide-related searches. The interaction between stress-related searches and the actual number of suicides was significant. A positive relationship between stress- and suicide-related searches further confirmed that stress affects suicide. Taken together and viewed in context of the big data analysis, our results point to the need for a tailored prevention program. Real-time big data can be of use in indicating increases in suicidality when search words such as stress and suicide generate greater numbers of hits on portals and social network sites.
Disability and health-related quality-of-life 4 years after a severe traumatic brain injury: A structural equation modelling analysis.

PubMed

Azouvi, Philippe; Ghout, Idir; Bayen, Eleonore; Darnoux, Emmanuelle; Azerad, Sylvie; Ruet, Alexis; Vallat-Azouvi, Claire; Pradat-Diehl, Pascale; Aegerter, Philippe; Charanton, James; Jourdan, Claire

2016-01-01

To assess predictors and indicators of disability and quality-of-life 4 years after severe traumatic brain injury (TBI), using structural equation modelling (SEM). The PariS-TBI study is a longitudinal multi-centre inception cohort study of 504 patients with severe TBI. Among 245 survivors, 147 patients were evaluated upon 4-year follow-up, and 85 completed the full assessment. Two outcome measures were analysed separately using SEM: the Glasgow Outcome Scale-extended (GOS-E), to measure disability, and the QOLIBRI, to assess quality-of-life. Four groups of variables were entered in the model: demographics; injury severity; mood and cognitive impairments; somatic impairments. The GOS-E was directly significantly related to mood and cognition, injury severity, and somatic impairments. Age and education had an indirect effect, mediated by mood/cognition or somatic deficiencies. In contrast, the only direct predictor of QOLIBRI was mood and cognition. Age and somatic impairments had an indirect influence on the QOLIBRI. Although this study should be considered as explorative, it suggests that disability and quality-of-life were directly influenced by different factors. While disability appeared to result from an interaction of a wide range of factors, quality-of-life was solely directly related to psycho-cognitive factors.
Fully Coupled 3D Finite Element Model of Hydraulic Fracturing in a Permeable Rock Formation

NASA Astrophysics Data System (ADS)

Salimzadeh, S.; Paluszny, A.; Zimmerman, R. W.

2015-12-01

Hydraulic fracturing in permeable rock formations is a complex three-dimensional multi-physics phenomenon. Numerous analytical models of hydraulic fracturing processes have been proposed that typically simplify the physical processes, or somehow reduce the problem from three dimensions to two dimensions. Moreover, although such simplified models are able to model the growth of a single hydraulic fracture into an initially intact, homogeneous rock mass, they are generally not able to model fracturing of heterogeneous rock formations, or to account for interactions between multiple induced fractures, or between an induced fracture and pre-existing natural fractures. We have developed a numerical finite-element model for hydraulic fracturing that does not suffer from any of the limitations mentioned above. The model accounts for fluid flow within a fracture, the propagation of the fracture, and the leak-off of fluid from the fracture into the host rock. Fluid flow through the permeable rock matrix is modelled using Darcy's law, and is coupled with the laminar flow within the fracture. Fractures are discretely modelled in the three-dimensional mesh. Growth of a fracture is modelled using the concepts of linear elastic fracture mechanics (LEFM), with the onset and direction of growth based on stress intensity factors that are computed for arbitrary tetrahedral meshes. The model has been verified against several analytical solutions available in the literature for plane-strain (2D) and penny-shaped (3D) fractures, for various regimes of domination: viscosity, toughness, storage and leak-off. The interaction of the hydraulically driven fracture with pre-existing fractures and other fluid-driven fractures in terms of fluid leak-off, stress interaction and fracture arrest is investigated and the results are presented. Finally, some preliminary results are presented regarding the interaction of a hydraulically-induced fracture with a set of pre-existing natural fractures.
Distributed MPC based consensus for single-integrator multi-agent systems.

PubMed

Cheng, Zhaomeng; Fan, Ming-Can; Zhang, Hai-Tao

2015-09-01

This paper addresses model predictive control schemes for consensus in multi-agent systems (MASs) with discrete-time single-integrator dynamics under switching directed interaction graphs. The control horizon is extended to be greater than one which endows the closed-loop system with extra degree of freedom. We derive sufficient conditions on the sampling period and the interaction graph to achieve consensus by using the property of infinite products of stochastic matrices. Consensus can be achieved asymptotically if the sampling period is selected such that the interaction graph among agents has a directed spanning tree jointly. Significantly, if the interaction graph always has a spanning tree, one can select an arbitrary large sampling period to guarantee consensus. Finally, several simulations are conducted to illustrate the effectiveness of the theoretical results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling

PubMed Central

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By “multi-level” we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization. PMID:29868515
Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling.

PubMed

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By "multi-level" we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization.
Genomic Prediction Accounting for Genotype by Environment Interaction Offers an Effective Framework for Breeding Simultaneously for Adaptation to an Abiotic Stress and Performance Under Normal Cropping Conditions in Rice.

PubMed

Ben Hassen, Manel; Bartholomé, Jérôme; Valè, Giampiero; Cao, Tuong-Vi; Ahmadi, Nourollah

2018-05-09

Developing rice varieties adapted to alternate wetting and drying water management is crucial for the sustainability of irrigated rice cropping systems. Here we report the first study exploring the feasibility of breeding rice for adaptation to alternate wetting and drying using genomic prediction methods that account for genotype by environment interactions. Two breeding populations (a reference panel of 284 accessions and a progeny population of 97 advanced lines) were evaluated under alternate wetting and drying and continuous flooding management systems. The predictive ability of genomic prediction for response variables (index of relative performance and the slope of the joint regression) and for multi-environment genomic prediction models were compared. For the three traits considered (days to flowering, panicle weight and nitrogen-balance index), significant genotype by environment interactions were observed in both populations. In cross validation, predictive ability for the index was on average lower (0.31) than that of the slope of the joint regression (0.64) whatever the trait considered. Similar results were found for progeny validation. Both cross-validation and progeny validation experiments showed that the performance of multi-environment models predicting unobserved phenotypes of untested entrees was similar to the performance of single environment models with differences in predictive ability ranging from -6% to 4% depending on the trait and on the statistical model concerned. The predictive ability of multi-environment models predicting unobserved phenotypes of entrees evaluated under both water management systems outperformed single environment models by an average of 30%. Practical implications for breeding rice for adaptation to alternate wetting and drying system are discussed. Copyright © 2018, G3: Genes, Genomes, Genetics.
Hybrid integral-differential simulator of EM force interactions/scenario-assessment tool with pre-computed influence matrix in applications to ITER

NASA Astrophysics Data System (ADS)

Rozov, V.; Alekseev, A.

2015-08-01

A necessity to address a wide spectrum of engineering problems in ITER determined the need for efficient tools for modeling of the magnetic environment and force interactions between the main components of the magnet system. The assessment of the operating window for the machine, determined by the electro-magnetic (EM) forces, and the check of feasibility of particular scenarios play an important role for ensuring the safety of exploitation. Such analysis-powered prevention of damages forms an element of the Machine Operations and Investment Protection strategy. The corresponding analysis is a necessary step in preparation of the commissioning, which finalizes the construction phase. It shall be supported by the development of the efficient and robust simulators and multi-physics/multi-system integration of models. The developed numerical model of interactions in the ITER magnetic system, based on the use of pre-computed influence matrices, facilitated immediate and complete assessment and systematic specification of EM loads on magnets in all foreseen operating regimes, their maximum values, envelopes and the most critical scenarios. The common principles of interaction in typical bilateral configurations have been generalized for asymmetry conditions, inspired by the plasma and by the hardware, including asymmetric plasma event and magnetic system fault cases. The specification of loads is supported by the technology of functional approximation of nodal and distributed data by continuous patterns/analytical interpolants. The global model of interactions together with the mesh-independent analytical format of output provides the source of self-consistent and transferable data on the spatial distribution of the system of forces for assessments of structural performance of the components, assemblies and supporting structures. The numerical model used is fully parametrized, which makes it very suitable for multi-variant and sensitivity studies (positioning, off-normal events, asymmetry, etc). The obtained results and matrices form a basis for a relatively simple and robust force processor as a specialized module of a global simulator for diagnostic, operational instrumentation, monitoring and control, as well as a scenario assessment tool. This paper gives an overview of the model, applied technique, assessed problems and obtained qualitative and quantitative results.
Using Bayes factors for multi-factor, biometric authentication

NASA Astrophysics Data System (ADS)

Giffin, A.; Skufca, J. D.; Lao, P. A.

2015-01-01

Multi-factor/multi-modal authentication systems are becoming the de facto industry standard. Traditional methods typically use rates that are point estimates and lack a good measure of uncertainty. Additionally, multiple factors are typically fused together in an ad hoc manner. To be consistent, as well as to establish and make proper use of uncertainties, we use a Bayesian method that will update our estimates and uncertainties as new information presents itself. Our algorithm compares competing classes (such as genuine vs. imposter) using Bayes Factors (BF). The importance of this approach is that we not only accept or reject one model (class), but compare it to others to make a decision. We show using a Receiver Operating Characteristic (ROC) curve that using BF for determining class will always perform at least as well as the traditional combining of factors, such as a voting algorithm. As the uncertainty decreases, the BF result continues to exceed the traditional methods result.
Simulating the conversion of rural settlements to town land based on multi-agent systems and cellular automata.

PubMed

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.
Defining how aging Pseudotsuga and Abies compensate for multiple stresses through multi-criteria assessment of a functional-structural model

Treesearch

Maureen C. Kennedy; E. David Ford; Thomas M. Hinckley

2009-01-01

Many hypotheses have been advanced about factors that control tree longevity. We use a simulation model with multi-criteria optimization and Pareto optimality to determine branch morphologies in the Pinaceae that minimize the effect of growth limitations due to water stress while simultaneously maximizing carbohydrate gain. Two distinct branch morphologies in the...
Ecodevelopmental contexts for preventing type 2 diabetes in Latino and other racial/ethnic minority populations

PubMed Central

Shaibi, Gabriel Q.; Boehm-Smith, Edna

2009-01-01

Diabetes is the sixth leading cause of death in the United States and it is now cited along with obesity as a global epidemic. Significant racial/ethnic disparities exist in the prevalence of diabetes within the US, with racial and ethnic minorities disproportionately affected by type 2 diabetes and its complications. Racial/ethnic and socioeconomic factors influence the development and course of diabetes at multiple levels, including genetic, individual, familial, community and national. From an ecodevelopmental perspective, cultural variables assessed at one level (e.g., family level dietary practices) may interact with other types of variables examined at other levels (e.g., the availability of healthy foods within a low-income neighborhood), thus prompting the need for a clear analysis of these systemic relationships as they may increase risks for disease. Therefore, the need exists for models that aid in “mapping out” these relationships. A more explicit conceptualization of such multi-level relationships would aid in the design of culturally relevant interventions that aim to maximize effectiveness when applied with Latinos and other racial/ethnic minority groups. This paper presents an expanded ecodevelopmental model intended to serve as a tool to aid in the design of multi-level diabetes prevention interventions for application with racial/ethnic minority populations. This discussion focuses primarily on risk factors and prevention intervention in Latino populations, although with implications for other racial/ethnic minority populations that are also at high risk for type 2 diabetes. PMID:19101788

Symplectic multi-particle tracking on GPUs

NASA Astrophysics Data System (ADS)

Liu, Zhicong; Qiang, Ji

2018-05-01

A symplectic multi-particle tracking model is implemented on the Graphic Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) language. The symplectic tracking model can preserve phase space structure and reduce non-physical effects in long term simulation, which is important for beam property evaluation in particle accelerators. Though this model is computationally expensive, it is very suitable for parallelization and can be accelerated significantly by using GPUs. In this paper, we optimized the implementation of the symplectic tracking model on both single GPU and multiple GPUs. Using a single GPU processor, the code achieves a factor of 2-10 speedup for a range of problem sizes compared with the time on a single state-of-the-art Central Processing Unit (CPU) node with similar power consumption and semiconductor technology. It also shows good scalability on a multi-GPU cluster at Oak Ridge Leadership Computing Facility. In an application to beam dynamics simulation, the GPU implementation helps save more than a factor of two total computing time in comparison to the CPU implementation.
Standardized residual as response function for order identification of multi input intervention analysis

NASA Astrophysics Data System (ADS)

Suhartono, Lee, Muhammad Hisyam; Rezeki, Sri

2017-05-01

Intervention analysis is a statistical model in the group of time series analysis which is widely used to describe the effect of an intervention caused by external or internal factors. An example of external factors that often occurs in Indonesia is a disaster, both natural or man-made disaster. The main purpose of this paper is to provide the results of theoretical studies on identification step for determining the order of multi inputs intervention analysis for evaluating the magnitude and duration of the impact of interventions on time series data. The theoretical result showed that the standardized residuals could be used properly as response function for determining the order of multi inputs intervention model. Then, these results are applied for evaluating the impact of a disaster on a real case in Indonesia, i.e. the magnitude and duration of the impact of the Lapindo mud on the volume of vehicles on the highway. Moreover, the empirical results showed that the multi inputs intervention model can describe and explain accurately the magnitude and duration of the impact of disasters on a time series data.
Trajectories of Children's Social Interactions with their Infant Sibling in the First Year: A Multi-Dimensional Approach

PubMed Central

Oh, Wonjung; Volling, Brenda L.; Gonzalez, Richard

2015-01-01

Individual differences in longitudinal trajectories of children's social behaviors toward their infant sibling were examined simultaneously across multiple social dimensions: Positive engagement (moving toward), Antagonism (moving against), and Avoidance (moving away). Three distinct social patterns were identified: (C1) Positively-Engaged (n=107, 50%); (C2) Escalating-Antagonism (n=90, 42%); and (C3) Early-Onset Antagonism (n=16, 8%). Children in the positively-engaged class had high levels of positive engagement with their infant siblings, coupled with low levels of antagonism and avoidance. The escalating-antagonism class was positively engaged in sibling interaction with a steep escalation in antagonistic behavior and avoidance from 4 to 12 months. Children in the early-onset antagonism class displayed the highest level of antagonistic behavior starting as early as 4 months, and became increasingly avoidant over time. A path model, guided by a process × person × context × time model, revealed that low parental self-efficacy heightened by parenting stress and children's dysregulated temperament was directly related to the escalating-antagonism pattern. Punitive parenting in response to children's antagonistic behavior increased the likelihood of being in the early-onset antagonism class. Together, the results highlighted heterogeneity in the earliest emergence of sibling interaction patterns and the interplay of child and parent factors in predicting distinct sibling interaction trajectory patterns. PMID:25664367
A tool for multi-scale modelling of the renal nephron

PubMed Central

Nickerson, David P.; Terkildsen, Jonna R.; Hamilton, Kirk L.; Hunter, Peter J.

2011-01-01

We present the development of a tool, which provides users with the ability to visualize and interact with a comprehensive description of a multi-scale model of the renal nephron. A one-dimensional anatomical model of the nephron has been created and is used for visualization and modelling of tubule transport in various nephron anatomical segments. Mathematical models of nephron segments are embedded in the one-dimensional model. At the cellular level, these segment models use models encoded in CellML to describe cellular and subcellular transport kinetics. A web-based presentation environment has been developed that allows the user to visualize and navigate through the multi-scale nephron model, including simulation results, at the different spatial scales encompassed by the model description. The Zinc extension to Firefox is used to provide an interactive three-dimensional view of the tubule model and the native Firefox rendering of scalable vector graphics is used to present schematic diagrams for cellular and subcellular scale models. The model viewer is embedded in a web page that dynamically presents content based on user input. For example, when viewing the whole nephron model, the user might be presented with information on the various embedded segment models as they select them in the three-dimensional model view. Alternatively, the user chooses to focus the model viewer on a cellular model located in a particular nephron segment in order to view the various membrane transport proteins. Selecting a specific protein may then present the user with a description of the mathematical model governing the behaviour of that protein—including the mathematical model itself and various simulation experiments used to validate the model against the literature. PMID:22670210
TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

PubMed

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .
TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

NASA Astrophysics Data System (ADS)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.
A practical approach for comparing management strategies in complex forest ecosystems using meta-modelling toolkits

Treesearch

Andrew Fall; B. Sturtevant; M.-J. Fortin; M. Papaik; F. Doyon; D. Morgan; K. Berninger; C. Messier

2010-01-01

The complexity and multi-scaled nature of forests poses significant challenges to understanding and management. Models can provide useful insights into process and their interactions, and implications of alternative management options. Most models, particularly scientific models, focus on a relatively small set of processes and are designed to operate within a...
A study of the dynamics of multi-player games on small networks using territorial interactions.

PubMed

Broom, Mark; Lafaye, Charlotte; Pattni, Karan; Rychtář, Jan

2015-12-01

Recently, the study of structured populations using models of evolutionary processes on graphs has begun to incorporate a more general type of interaction between individuals, allowing multi-player games to be played among the population. In this paper, we develop a birth-death dynamics for use in such models and consider the evolution of populations for special cases of very small graphs where we can easily identify all of the population states and carry out exact analyses. To do so, we study two multi-player games, a Hawk-Dove game and a public goods game. Our focus is on finding the fixation probability of an individual from one type, cooperator or defector in the case of the public goods game, within a population of the other type. We compare this value for both games on several graphs under different parameter values and assumptions, and identify some interesting general features of our model. In particular there is a very close relationship between the fixation probability and the mean temperature, with high temperatures helping fitter individuals and punishing unfit ones and so enhancing selection, whereas low temperatures give a levelling effect which suppresses selection.
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.
Vector-borne diseases models with residence times - A Lagrangian perspective.

PubMed

Bichara, Derdei; Castillo-Chavez, Carlos

2016-11-01

A multi-patch and multi-group modeling framework describing the dynamics of a class of diseases driven by the interactions between vectors and hosts structured by groups is formulated. Hosts' dispersal is modeled in terms of patch-residence times with the nonlinear dynamics taking into account the effective patch-host size. The residence times basic reproduction number R 0 is computed and shown to depend on the relative environmental risk of infection. The model is robust, that is, the disease free equilibrium is globally asymptotically stable (GAS) if R 0 ≤1 and a unique interior endemic equilibrium is shown to exist that is GAS whenever R 0 >1 whenever the configuration of host-vector interactions is irreducible. The effects of patchiness and groupness, a measure of host-vector heterogeneous structure, on the basic reproduction number R 0 , are explored. Numerical simulations are carried out to highlight the effects of residence times on disease prevalence. Copyright © 2016 Elsevier Inc. All rights reserved.
Simulated tri-trophic networks reveal complex relationships between species diversity and interaction diversity

PubMed Central

Lumpkin, Will; Hurtado, Paul J.; Dyer, Lee A.

2018-01-01

Most of earth’s biodiversity is comprised of interactions among species, yet it is unclear what causes variation in interaction diversity across space and time. We define interaction diversity as the richness and relative abundance of interactions linking species together at scales from localized, measurable webs to entire ecosystems. Large-scale patterns suggest that two basic components of interaction diversity differ substantially and predictably between different ecosystems: overall taxonomic diversity and host specificity of consumers. Understanding how these factors influence interaction diversity, and quantifying the causes and effects of variation in interaction diversity are important goals for community ecology. While previous studies have examined the effects of sampling bias and consumer specialization on determining patterns of ecological networks, these studies were restricted to two trophic levels and did not incorporate realistic variation in species diversity and consumer diet breadth. Here, we developed a food web model to generate tri-trophic ecological networks, and evaluated specific hypotheses about how the diversity of trophic interactions and species diversity are related under different scenarios of species richness, taxonomic abundance, and consumer diet breadth. We investigated the accumulation of species and interactions and found that interactions accumulate more quickly; thus, the accumulation of novel interactions may require less sampling effort than sampling species in order to get reliable estimates of either type of diversity. Mean consumer diet breadth influenced the correlation between species and interaction diversity significantly more than variation in both species richness and taxonomic abundance. However, this effect of diet breadth on interaction diversity is conditional on the number of observed interactions included in the models. The results presented here will help develop realistic predictions of the relationships between consumer diet breadth, interaction diversity, and species diversity within multi-trophic communities, which is critical for the conservation of biodiversity in this period of accelerated global change. PMID:29579077
Simulated tri-trophic networks reveal complex relationships between species diversity and interaction diversity.

PubMed

Pardikes, Nicholas A; Lumpkin, Will; Hurtado, Paul J; Dyer, Lee A

2018-01-01

Most of earth's biodiversity is comprised of interactions among species, yet it is unclear what causes variation in interaction diversity across space and time. We define interaction diversity as the richness and relative abundance of interactions linking species together at scales from localized, measurable webs to entire ecosystems. Large-scale patterns suggest that two basic components of interaction diversity differ substantially and predictably between different ecosystems: overall taxonomic diversity and host specificity of consumers. Understanding how these factors influence interaction diversity, and quantifying the causes and effects of variation in interaction diversity are important goals for community ecology. While previous studies have examined the effects of sampling bias and consumer specialization on determining patterns of ecological networks, these studies were restricted to two trophic levels and did not incorporate realistic variation in species diversity and consumer diet breadth. Here, we developed a food web model to generate tri-trophic ecological networks, and evaluated specific hypotheses about how the diversity of trophic interactions and species diversity are related under different scenarios of species richness, taxonomic abundance, and consumer diet breadth. We investigated the accumulation of species and interactions and found that interactions accumulate more quickly; thus, the accumulation of novel interactions may require less sampling effort than sampling species in order to get reliable estimates of either type of diversity. Mean consumer diet breadth influenced the correlation between species and interaction diversity significantly more than variation in both species richness and taxonomic abundance. However, this effect of diet breadth on interaction diversity is conditional on the number of observed interactions included in the models. The results presented here will help develop realistic predictions of the relationships between consumer diet breadth, interaction diversity, and species diversity within multi-trophic communities, which is critical for the conservation of biodiversity in this period of accelerated global change.
A Bayesian Framework of Uncertainties Integration in 3D Geological Model

NASA Astrophysics Data System (ADS)

Liang, D.; Liu, X.

2017-12-01

3D geological model can describe complicated geological phenomena in an intuitive way while its application may be limited by uncertain factors. Great progress has been made over the years, lots of studies decompose the uncertainties of geological model to analyze separately, while ignored the comprehensive impacts of multi-source uncertainties. Great progress has been made over the years, while lots of studies ignored the comprehensive impacts of multi-source uncertainties when analyzed them item by item from each source. To evaluate the synthetical uncertainty, we choose probability distribution to quantify uncertainty, and propose a bayesian framework of uncertainties integration. With this framework, we integrated data errors, spatial randomness, and cognitive information into posterior distribution to evaluate synthetical uncertainty of geological model. Uncertainties propagate and cumulate in modeling process, the gradual integration of multi-source uncertainty is a kind of simulation of the uncertainty propagation. Bayesian inference accomplishes uncertainty updating in modeling process. Maximum entropy principle makes a good effect on estimating prior probability distribution, which ensures the prior probability distribution subjecting to constraints supplied by the given information with minimum prejudice. In the end, we obtained a posterior distribution to evaluate synthetical uncertainty of geological model. This posterior distribution represents the synthetical impact of all the uncertain factors on the spatial structure of geological model. The framework provides a solution to evaluate synthetical impact on geological model of multi-source uncertainties and a thought to study uncertainty propagation mechanism in geological modeling.
Mortality and Population Dynamics of Bemisia tabaci within a Multi-Crop System

USDA-ARS?s Scientific Manuscript database

The population dynamics of mobile polyphagous pests is governed by a complex set of interacting factors that involve multiple host-plants, seasonality, movement and demography. Bemisia tabaci is a multivoltine insect with no diapause that maintains population continuity by moving from one host to a...
Multi-site pain and working conditions as predictors of work ability in a 4-year follow-up among food industry employees.

PubMed

Neupane, S; Virtanen, P; Leino-Arjas, P; Miranda, H; Siukola, A; Nygård, C-H

2013-03-01

We investigated the separate and joint effects of multi-site musculoskeletal pain and physical and psychosocial exposures at work on future work ability. A survey was conducted among employees of a Finnish food industry company in 2005 (n = 1201) and a follow-up survey in 2009 (n = 734). Information on self-assessed work ability (current work ability on a scale from 0 to 10; 7 = poor work ability), multi-site musculoskeletal pain (pain in at least two anatomical areas of four), leisure-time physical activity, body mass index and physical and psychosocial exposures was obtained by questionnaire. The separate and joint effects of multi-site pain and work exposures on work ability at follow-up, among subjects with good work ability at baseline, were assessed by logistic regression, and p-values for the interaction derived. Compared with subjects with neither multi-site pain nor adverse work exposure, multi-site pain at baseline increased the risk of poor work ability at follow-up, allowing for age, gender, occupational class, body mass index and leisure-time physical activity. The separate effects of the work exposures on work ability were somewhat smaller than those of multi-site pain. Multi-site pain had an interactive effect with work environment and awkward postures, such that no association of multi-site pain with poor work ability was seen when work environment was poor or awkward postures present. The decline in work ability connected with multi-site pain was not increased by exposure to adverse physical or psychosocial factors at work. © 2012 European Federation of International Association for the Study of Pain Chapters.
Multi-Population Invariance with Dichotomous Measures: Combining Multi-Group and MIMIC Methodologies in Evaluating the General Aptitude Test in the Arabic Language

ERIC Educational Resources Information Center

Sideridis, Georgios D.; Tsaousis, Ioannis; Al-harbi, Khaleel A.

2015-01-01

The purpose of the present study was to extend the model of measurement invariance by simultaneously estimating invariance across multiple populations in the dichotomous instrument case using multi-group confirmatory factor analytic and multiple indicator multiple causes (MIMIC) methodologies. Using the Arabic version of the General Aptitude Test…
Aquatic community structure in Mediterranean edge-of-field waterbodies as explained by environmental factors and the presence of pesticide mixtures.

PubMed

Pereira, Ana Santos; Dâmaso-Rodrigues, Maria Luísa; Amorim, Ana; Daam, Michiel A; Cerejeira, Maria José

2018-06-16

Studies addressing the predicted effects of pesticides in combination with abiotic and biotic factors on aquatic biota in ditches associated with typical Mediterranean agroecosystems are scarce. The current study aimed to evaluate the predicted effects of pesticides along with environmental factors and biota interactions on macroinvertebrate, zooplankton and phytoplankton community compositions in ditches adjacent to Portuguese maize and tomato crop areas. Data was analysed with the variance partitioning procedure based on redundancy analysis (RDA). The total variance in biological community composition was divided into the variance explained by the multi-substance potentially affected fraction [(msPAF) arthropods and primary producers], environmental factors (water chemistry parameters), biotic interactions, shared variance, and unexplained variance. The total explained variance reached 39.4% and the largest proportion of this explained variance was attributed to msPAF (23.7%). When each group (phytoplankton, zooplankton and macroinvertebrates) was analysed separately, biota interactions and environmental factors explained the largest proportion of variance. Results of this study indicate that besides the presence of pesticide mixtures, environmental factors and biotic interactions also considerably influence field freshwater communities. Subsequently, to increase our understanding of the risk of pesticide mixtures on ecosystem communities in edge-of-field water bodies, variations in environmental and biological factors should also be considered.
The Research of Regression Method for Forecasting Monthly Electricity Sales Considering Coupled Multi-factor

NASA Astrophysics Data System (ADS)

Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui

2018-01-01

The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.
Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

NASA Astrophysics Data System (ADS)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-06-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection—species differentiation and population change—through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test.
Multi-Cellular Logistics of Collective Cell Migration

PubMed Central

Yamao, Masataka; Naoki, Honda; Ishii, Shin

2011-01-01

During development, the formation of biological networks (such as organs and neuronal networks) is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic) blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes “collective migration,” whereas strong noise from non-migratory cells causes “dispersive migration.” Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems. PMID:22205934

Does Multi-morbidity Mediate the Effect of Socioeconomics on Self-rated Health? Cross-country Differences

PubMed Central

Assari, Shervin; Lankarani, Maryam Moghani

2015-01-01

Background: This study explored cross-country differences in how multi-morbidity explains the effects of socioeconomic characteristics on self-rated health. Methods: The study borrowed data from the Research on Early Life and Aging Trends and Effects. Participants were 44,530 individuals (age > 65 years) who were sampled from 15 countries (i.e. United States, China, India, Russia, Costa Rica, Puerto Rico, Mexico, Argentina, Barbados, Brazil, Chile, Cuba, Uruguay, Ghana and South Africa). Multi-morbidity was measured as number of chronic medical conditions. In Model I, main effects of socioeconomic factors on self-rated health were calculated using country-specific logistic regressions. In Model II, number of chronic conditions were also added to the models to find changes in coefficients for demographic and socioeconomic factors. Results: In the United States, number of chronic medical conditions explained the effect of income on subjective health. In Puerto Rico, number of chronic medical conditions explained the effect of marital status on subjective health. In Costa Rica, Argentina, Barbados, Cuba, and Uruguay, number of chronic medical conditions explained gender disparities in subjective health. In China, Mexico, Brazil, Russia, Chile, India, Ghana and South Africa, number of chronic medical conditions did not explain the effect of demographic or socioeconomic factors on subjective health. Conclusions: Multi-morbidity explains the effect of demographic and socioeconomic factors on subjective health in some but not other countries. Further research is needed. PMID:26445632
Stability and structural properties of gene regulation networks with coregulation rules.

PubMed

Warrell, Jonathan; Mhlanga, Musa

2017-05-07

Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated expression of modules (and module groups) of functionally related genes across the genome. Coregulation can also arise through the physical association of multi-gene complexes through chromosomal looping, which are then transcribed together. We present a general formalism for modeling coregulation rules in the framework of Random Boolean Networks (RBN), and develop specific models for transcription factor networks with modular structure (including module groups, and multi-input modules (MIM) with autoregulation) and multi-gene complexes (including hierarchical differentiation between multi-gene complex members). We develop a mean-field approach to analyse the dynamical stability of large networks incorporating coregulation, and show that autoregulated MIM and hierarchical gene-complex models can achieve greater stability than networks without coregulation whose rules have matching activation frequency. We provide further analysis of the stability of small networks of both kinds through simulations. We also characterize several general properties of the transients and attractors in the hierarchical coregulation model, and show using simulations that the steady-state distribution factorizes hierarchically as a Bayesian network in a Markov Jump Process analogue of the RBN model. Copyright © 2017. Published by Elsevier Ltd.
A theoretical framework for negotiating the path of emergency management multi-agency coordination.

PubMed

Curnin, Steven; Owen, Christine; Paton, Douglas; Brooks, Benjamin

2015-03-01

Multi-agency coordination represents a significant challenge in emergency management. The need for liaison officers working in strategic level emergency operations centres to play organizational boundary spanning roles within multi-agency coordination arrangements that are enacted in complex and dynamic emergency response scenarios creates significant research and practical challenges. The aim of the paper is to address a gap in the literature regarding the concept of multi-agency coordination from a human-environment interaction perspective. We present a theoretical framework for facilitating multi-agency coordination in emergency management that is grounded in human factors and ergonomics using the methodology of core-task analysis. As a result we believe the framework will enable liaison officers to cope more efficiently within the work domain. In addition, we provide suggestions for extending the theory of core-task analysis to an alternate high reliability environment. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.
Hybrid multi-grids simulations of Ganymede's magnetosphere : comparison with Galileo observations.

NASA Astrophysics Data System (ADS)

Leclercq, L.; Modolo, R.; Leblanc, F.

2015-12-01

The Jovian satellite Ganymede is the biggest moon of our solar system. One of the main motivation of our interest for this moon is its own intrinsic magnetic field, which has been discovered during the Galileo mission (Kivelson et al. 1996). The magnetic field of Ganymede directly interacts with the corotating jovian plasma, leading to the formation of a mini-magnetosphere which is embedded in the giant magnetosphere of Jupiter. This is the only known case of interaction between two planetary magnetospheres.In the frame of the European space mission JUICE (Jupiter Icy moon Exploration), we investigate this unique interaction with a 3D parallel multi-species hybrid model. This model is based on the CAM-CL algorithm (Matthews 1994) and has been used to study the ionized environments of Titan, Mars and Mercury. In the hybrid formalism, ions are kinetically treated whereas electrons are considered as a zero-inertial fluid to ensure the quasi-neutrality of the plasma. The temporal evolution of the electromagnetic fields is calculated solving Maxwell's equations. The jovian magnetospheric plasma is described as being composed of oxygen and proton ions. The magnetic field of Ganymede, which includes dipolar and induced components (Kivelson et al, 2002), is distorted by its interaction with the Jovian plasma and formed the Alfvén wings. The planetary plasma is described as being composed of O+, with a scale height equal to 125 km. The description of the exosphere is provided by the 3D multi-species collisional exospheric/atmospheric model of Leblanc et al, (2015) and Turc et al. (2014). The ionization of this neutral exosphere by charge exchanges, by electronic impacts, and by reaction with solar photons contributes to the production of planetary plasma. In this model, calculations are performed on a cartesian simulation grid which is refined (down to ~120 km of spatial resolution) at Ganymede, using a multi-grids approach (Leclercq et al., submitted, 2015). Results are compared with Galileo observations obtained during the G1, G2 and G8 flybys.
Using multi-resolution proxies to assess ENSO impacts on the mean state of the tropical Pacific.

NASA Astrophysics Data System (ADS)

Karamperidou, C.; Conroy, J. L.

2016-12-01

Observations and model simulations indicate that the relationship between ENSO and the mean state of the tropical Pacific is a two-way interaction. On one hand, a strong zonal SST gradient (dSST) in the Pacific (colder cold tongue) increases the potential intensity of upcoming ENSO events and may lead to increased ENSO variance. On the other hand, in a period of increased ENSO activity, large events can warm the cold tongue at decadal scales via residual heating, and thus lead to reduced zonal SST gradient (ENSO rectification mechanism). The short length of the observational record hinders our ability to confidently evaluate which mechanism dominates in each period, and whether it is sensitive to external climate forcing. This question is effectively a question of interaction between two timescales: interannual and decadal. Paleoclimate proxies of different resolutions can help elucidate this question, since they can be independent records of variability in these separate timescales. Here, we use coral proxies of ENSO variability from across the Pacific and multi-proxy records of dSST at longer timescales. Proxies, models, and observations indicate that in periods of increased ENSO activity, dSST is negatively correlated with ENSO variance at decadal timescales, indicating that strong ENSO events may affect the decadal mean state via warming the cold tongue. Using climate model simulations we attribute this effect to residual nonlinear dynamical heating, thus supporting the ENSO rectification mechanism. On the contrary, in periods without strong events, ENSO variance and dSST are positively correlated, which indicates that the primary mechanism at work is the effect of the mean state on ENSO. Our analysis also quantitatively identifies the regions where paleoclimate proxies are needed in order to reduce the existing uncertainties in ENSO-mean state interactions. Hence, this study is a synthesis of observations, model simulations and paleoclimate proxy evidence guided by the fundamental and open question of multi-scale interactions in the tropical Pacific, and illustrates the need for multi-resolution paleoclimate proxies and their potential uses.
Binding Affinity Effects on Physical Characteristics of a Model Phase-Separated Protein Droplet

NASA Astrophysics Data System (ADS)

Chuang, Sara; Banani, Salman; Rosen, Michael; Brangwynne, Clifford

2015-03-01

Non-membrane bound organelles are associated with a range of biological functions. Several of these structures exhibit liquid-like properties, and may represent droplets of phase-separated RNA and/or proteins. These structures are often enriched in multi-valent molecules, however little is known about the interactions driving the assembly, properties, and function. Here, we address this question using a model multi-valent protein system consisting of repeats of Small Ubiquitin-like Modifier (SUMO) protein and a SUMO-interacting motif (SIM). These proteins undergo phase separation into liquid-like droplets. We combine microrheology and quantitative microscopy to determine affect of binding affinity on the viscosity, density and surface tension of these droplets. We also use fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS) and partitioning experiments to probe the structure and dynamics within these droplets. Our results shed light on how inter-molecular interactions manifests in droplet properties, and lay the groundwork for a comprehensive biophysical picture of intracellular RNA/protein organelles.
A Computational Chemo-Fluidic Modeling for the Investigation of Patient-Specific Left Ventricle Thrombogenesis

NASA Astrophysics Data System (ADS)

Mittal, Rajat; Seo, Jung Hee; Abd, Thura; George, Richard T.

2015-11-01

Patients recovering from myocardial infarction (MI) are considered at high-risk for cardioembolic stroke due to the formation of left ventricle thrombus (LVT). The formation of LVT is the result of a complex interplay between the fluid dynamics inside the ventricle and the chemistry of coagulation, and the role of LV flow pattern on the thrombogenesis was not well understood. The previous computational study performed with the model ventricles suggested that the local flow residence time is the key variable governing the accumulation of coagulation factors. In the present study, a coupled, chemo-fluidic computational modeling is applied to the patient-specific cases of infracted ventricles to investigate the interaction between the LV hemodynamics and thrombogensis. In collaboration with the Johns Hopkins hospital, patient-specific LV models are constructed using the multi-modality medical imaging data. Blood flow in the left ventricle is simulated by solving the incompressible Navier-Stokes equations and the biochemical reactions for the thrombus formation are modeled with convection-diffusion-reaction equations. The formation and deposition of key coagulation chemical factors are then correlated with the hemodynamic flow metrics to explore the biophysics underlying LVT risk. Supported by the Johns Hopkins Medicine Discovery Fund and NSF Grant: CBET-1511200, Computational resource by XSEDE NSF grant TG-CTS100002.
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.
Solving multi-objective optimization problems in conservation with the reference point method

PubMed Central

Dujardin, Yann; Chadès, Iadine

2018-01-01

Managing the biodiversity extinction crisis requires wise decision-making processes able to account for the limited resources available. In most decision problems in conservation biology, several conflicting objectives have to be taken into account. Most methods used in conservation either provide suboptimal solutions or use strong assumptions about the decision-maker’s preferences. Our paper reviews some of the existing approaches to solve multi-objective decision problems and presents new multi-objective linear programming formulations of two multi-objective optimization problems in conservation, allowing the use of a reference point approach. Reference point approaches solve multi-objective optimization problems by interactively representing the preferences of the decision-maker with a point in the criteria (objectives) space, called the reference point. We modelled and solved the following two problems in conservation: a dynamic multi-species management problem under uncertainty and a spatial allocation resource management problem. Results show that the reference point method outperforms classic methods while illustrating the use of an interactive methodology for solving combinatorial problems with multiple objectives. The method is general and can be adapted to a wide range of ecological combinatorial problems. PMID:29293650
Multi-scale modelling of the dynamics of cell colonies: insights into cell-adhesion forces and cancer invasion from in silico simulations.

PubMed

Schlüter, Daniela K; Ramis-Conde, Ignacio; Chaplain, Mark A J

2015-02-06

Studying the biophysical interactions between cells is crucial to understanding how normal tissue develops, how it is structured and also when malfunctions occur. Traditional experiments try to infer events at the tissue level after observing the behaviour of and interactions between individual cells. This approach assumes that cells behave in the same biophysical manner in isolated experiments as they do within colonies and tissues. In this paper, we develop a multi-scale multi-compartment mathematical model that accounts for the principal biophysical interactions and adhesion pathways not only at a cell-cell level but also at the level of cell colonies (in contrast to the traditional approach). Our results suggest that adhesion/separation forces between cells may be lower in cell colonies than traditional isolated single-cell experiments infer. As a consequence, isolated single-cell experiments may be insufficient to deduce important biological processes such as single-cell invasion after detachment from a solid tumour. The simulations further show that kinetic rates and cell biophysical characteristics such as pressure-related cell-cycle arrest have a major influence on cell colony patterns and can allow for the development of protrusive cellular structures as seen in invasive cancer cell lines independent of expression levels of pro-invasion molecules.
Multi-scale modelling of the dynamics of cell colonies: insights into cell-adhesion forces and cancer invasion from in silico simulations

PubMed Central

Schlüter, Daniela K.; Ramis-Conde, Ignacio; Chaplain, Mark A. J.

2015-01-01

Studying the biophysical interactions between cells is crucial to understanding how normal tissue develops, how it is structured and also when malfunctions occur. Traditional experiments try to infer events at the tissue level after observing the behaviour of and interactions between individual cells. This approach assumes that cells behave in the same biophysical manner in isolated experiments as they do within colonies and tissues. In this paper, we develop a multi-scale multi-compartment mathematical model that accounts for the principal biophysical interactions and adhesion pathways not only at a cell–cell level but also at the level of cell colonies (in contrast to the traditional approach). Our results suggest that adhesion/separation forces between cells may be lower in cell colonies than traditional isolated single-cell experiments infer. As a consequence, isolated single-cell experiments may be insufficient to deduce important biological processes such as single-cell invasion after detachment from a solid tumour. The simulations further show that kinetic rates and cell biophysical characteristics such as pressure-related cell-cycle arrest have a major influence on cell colony patterns and can allow for the development of protrusive cellular structures as seen in invasive cancer cell lines independent of expression levels of pro-invasion molecules. PMID:25519994
Robust multi-model control of an autonomous wind power system

NASA Astrophysics Data System (ADS)

Cutululis, Nicolas Antonio; Ceanga, Emil; Hansen, Anca Daniela; Sørensen, Poul

2006-09-01

This article presents a robust multi-model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT-PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi-model control structure is designed. The simulation results prove the viability of the proposed control structure. Copyright
Knowledge-Driven Analysis Identifies a Gene–Gene Interaction Affecting High-Density Lipoprotein Cholesterol Levels in Multi-Ethnic Populations

PubMed Central

Ma, Li; Brautbar, Ariel; Boerwinkle, Eric; Sing, Charles F.

2012-01-01

Total cholesterol, low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol (HDL-C) levels are among the most important risk factors for coronary artery disease. We tested for gene–gene interactions affecting the level of these four lipids based on prior knowledge of established genome-wide association study (GWAS) hits, protein–protein interactions, and pathway information. Using genotype data from 9,713 European Americans from the Atherosclerosis Risk in Communities (ARIC) study, we identified an interaction between HMGCR and a locus near LIPC in their effect on HDL-C levels (Bonferroni corrected P c = 0.002). Using an adaptive locus-based validation procedure, we successfully validated this gene–gene interaction in the European American cohorts from the Framingham Heart Study (P c = 0.002) and the Multi-Ethnic Study of Atherosclerosis (MESA; P c = 0.006). The interaction between these two loci is also significant in the African American sample from ARIC (P c = 0.004) and in the Hispanic American sample from MESA (P c = 0.04). Both HMGCR and LIPC are involved in the metabolism of lipids, and genome-wide association studies have previously identified LIPC as associated with levels of HDL-C. However, the effect on HDL-C of the novel gene–gene interaction reported here is twice as pronounced as that predicted by the sum of the marginal effects of the two loci. In conclusion, based on a knowledge-driven analysis of epistasis, together with a new locus-based validation method, we successfully identified and validated an interaction affecting a complex trait in multi-ethnic populations. PMID:22654671
Studying physician effects on patient outcomes: physician interactional style and performance on quality of care indicators.

PubMed

Franks, Peter; Jerant, Anthony F; Fiscella, Kevin; Shields, Cleveland G; Tancredi, Daniel J; Epstein, Ronald M

2006-01-01

Many prior studies which suggest a relationship between physician interactional style and patient outcomes may have been confounded by relying solely on patient reports, examining very few patients per physician, or not demonstrating evidence of a physician effect on the outcomes. We examined whether physician interactional style, measured both by patient report and objective encounter ratings, is related to performance on quality of care indicators. We also tested for the presence of physician effects on the performance indicators. Using data on 100 US primary care physician (PCP) claims data on 1,21,606 of their managed care patients, survey data on 4746 of their visiting patients, and audiotaped encounters of 2 standardized patients with each physician, we examined the relationships between claims-based quality of care indicators and both survey-derived patient perceptions of their physicians and objective ratings of interactional style in the audiotaped standardized patient encounters. Multi-level models examined whether physician effects (variance components) on care indicators were mediated by patient perceptions or objective ratings of interactional style. We found significant physician effects associated with glycohemoglobin and cholesterol testing. There was also a clinically significant association between better patient perceptions of their physicians and more glycohemoglobin testing. Multi-level analyses revealed, however, that the physician effect on glycohemoglobin testing was not mediated by patient perceived physician interaction style. In conclusion, similar to prior studies, we found evidence of an apparent relationship between patient perceptions of their physician and patient outcomes. However, the apparent relationships found in this study between patient perceptions of their physicians and patient care processes do not reflect physician style, but presumably reflect unmeasured patient confounding. Multi-level modeling may contribute to better understanding of the relationships between physician style and patient outcomes.
Complex carbon cycle responses to multi-level warming and supplemental summer rain in the high Arctic.

PubMed

Sharp, Elizabeth D; Sullivan, Patrick F; Steltzer, Heidi; Csank, Adam Z; Welker, Jeffrey M

2013-06-01

The Arctic has experienced rapid warming and, although there are uncertainties, increases in precipitation are projected to accompany future warming. Climate changes are expected to affect magnitudes of gross ecosystem photosynthesis (GEP), ecosystem respiration (ER) and the net ecosystem exchange of CO2 (NEE). Furthermore, ecosystem responses to climate change are likely to be characterized by nonlinearities, thresholds and interactions among system components and the driving variables. These complex interactions increase the difficulty of predicting responses to climate change and necessitate the use of manipulative experiments. In 2003, we established a long-term, multi-level and multi-factor climate change experiment in a polar semidesert in northwest Greenland. Two levels of heating (30 and 60 W m(-2) ) were applied and the higher level was combined with supplemental summer rain. We made plot-level measurements of CO2 exchange, plant community composition, foliar nitrogen concentrations, leaf δ(13) C and NDVI to examine responses to our treatments at ecosystem- and leaf-levels. We confronted simple models of GEP and ER with our data to test hypotheses regarding key drivers of CO2 exchange and to estimate growing season CO2 -C budgets. Low-level warming increased the magnitude of the ecosystem C sink. Meanwhile, high-level warming made the ecosystem a source of C to the atmosphere. When high-level warming was combined with increased summer rain, the ecosystem became a C sink of magnitude similar to that observed under low-level warming. Competition among our ER models revealed the importance of soil moisture as a driving variable, likely through its effects on microbial activity and nutrient cycling. Measurements of community composition and proxies for leaf-level physiology suggest GEP responses largely reflect changes in leaf area of Salix arctica, rather than changes in leaf-level physiology. Our findings indicate that the sign and magnitude of the future High Arctic C budget may depend upon changes in summer rain. © 2013 Blackwell Publishing Ltd.
Aerosol-cloud interactions in a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Lin, G.; Ghan, S. J.

2017-12-01

Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations.
Design and implementation of space physics multi-model application integration based on web

NASA Astrophysics Data System (ADS)

Jiang, Wenping; Zou, Ziming

With the development of research on space environment and space science, how to develop network online computing environment of space weather, space environment and space physics models for Chinese scientific community is becoming more and more important in recent years. Currently, There are two software modes on space physics multi-model application integrated system (SPMAIS) such as C/S and B/S. the C/S mode which is traditional and stand-alone, demands a team or workshop from many disciplines and specialties to build their own multi-model application integrated system, that requires the client must be deployed in different physical regions when user visits the integrated system. Thus, this requirement brings two shortcomings: reducing the efficiency of researchers who use the models to compute; inconvenience of accessing the data. Therefore, it is necessary to create a shared network resource access environment which could help users to visit the computing resources of space physics models through the terminal quickly for conducting space science research and forecasting spatial environment. The SPMAIS develops high-performance, first-principles in B/S mode based on computational models of the space environment and uses these models to predict "Space Weather", to understand space mission data and to further our understanding of the solar system. the main goal of space physics multi-model application integration system (SPMAIS) is to provide an easily and convenient user-driven online models operating environment. up to now, the SPMAIS have contained dozens of space environment models , including international AP8/AE8 IGRF T96 models and solar proton prediction model geomagnetic transmission model etc. which are developed by Chinese scientists. another function of SPMAIS is to integrate space observation data sets which offers input data for models online high-speed computing. In this paper, service-oriented architecture (SOA) concept that divides system into independent modules according to different business needs is applied to solve the problem of the independence of the physical space between multiple models. The classic MVC(Model View Controller) software design pattern is concerned to build the architecture of space physics multi-model application integrated system. The JSP+servlet+javabean technology is used to integrate the web application programs of space physics multi-model. It solves the problem of multi-user requesting the same job of model computing and effectively balances each server computing tasks. In addition, we also complete follow tasks: establishing standard graphical user interface based on Java Applet application program; Designing the interface between model computing and model computing results visualization; Realizing three-dimensional network visualization without plug-ins; Using Java3D technology to achieve a three-dimensional network scene interaction; Improved ability to interact with web pages and dynamic execution capabilities, including rendering three-dimensional graphics, fonts and color control. Through the design and implementation of the SPMAIS based on Web, we provide an online computing and application runtime environment of space physics multi-model. The practical application improves that researchers could be benefit from our system in space physics research and engineering applications.
Modeling the spectral energy distribution of the radio galaxy IC310

NASA Astrophysics Data System (ADS)

Fraija, N.; Marinelli, A.; Galván-Gámez, A.; Aguilar-Ruiz, E.

2017-03-01

The radio galaxy IC310 located in the Perseus Cluster is one of the brightest objects in the radio and X-ray bands, and one of the closest active galactic nuclei observed in very-high energies. In GeV - TeV γ-rays, IC310 was detected in low and high flux states by the MAGIC telescopes from October 2009 to February 2010. Taking into account that the spectral energy distribution (SED) up to a few GeV seems to exhibit a double-peak feature and that a single-zone synchrotron self-Compton (SSC) model can explain all of the multiwavelength emission except for the non-simultaneous MAGIC emission, we interpret, in this work, the multifrequency data set of the radio galaxy IC310 in the context of homogeneous hadronic and leptonic models. In the leptonic framework, we present a multi-zone SSC model with two electron populations to explain the whole SED whereas for the hadronic model, we propose that a single-zone SSC model describes the SED up to a few GeVs and neutral pion decay products resulting from pγ interactions could describe the TeV - GeV γ-ray spectra. These interactions occur when Fermi-accelerated protons interact with the seed photons around the SSC peaks. We show that, in the leptonic model the minimum Lorentz factor of second electron population is exceedingly high γe ∼ 105 disfavoring this model, and in the hadronic model the required proton luminosity is not extremely high ∼1044 erg/s, provided that charge neutrality between the number of electrons and protons is given. Correlating the TeV γ-ray and neutrino spectra through photo-hadronic interactions, we find that the contribution of the emitting region of IC310 to the observed neutrino and ultra-high-energy cosmic ray fluxes are negligible.
The Work Role Functioning Questionnaire v2.0 Showed Consistent Factor Structure Across Six Working Samples.

PubMed

Abma, Femke I; Bültmann, Ute; Amick Iii, Benjamin C; Arends, Iris; Dorland, Heleen F; Flach, Peter A; van der Klink, Jac J L; van de Ven, Hardy A; Bjørner, Jakob Bue

2017-09-09

Objective The Work Role Functioning Questionnaire v2.0 (WRFQ) is an outcome measure linking a persons' health to the ability to meet work demands in the twenty-first century. We aimed to examine the construct validity of the WRFQ in a heterogeneous set of working samples in the Netherlands with mixed clinical conditions and job types to evaluate the comparability of the scale structure. Methods Confirmatory factor and multi-group analyses were conducted in six cross-sectional working samples (total N = 2433) to evaluate and compare a five-factor model structure of the WRFQ (work scheduling demands, output demands, physical demands, mental and social demands, and flexibility demands). Model fit indices were calculated based on RMSEA ≤ 0.08 and CFI ≥ 0.95. After fitting the five-factor model, the multidimensional structure of the instrument was evaluated across samples using a second order factor model. Results The factor structure was robust across samples and a multi-group model had adequate fit (RMSEA = 0.63, CFI = 0.972). In sample specific analyses, minor modifications were necessary in three samples (final RMSEA 0.055-0.080, final CFI between 0.955 and 0.989). Applying the previous first order specifications, a second order factor model had adequate fit in all samples. Conclusion A five-factor model of the WRFQ showed consistent structural validity across samples. A second order factor model showed adequate fit, but the second order factor loadings varied across samples. Therefore subscale scores are recommended to compare across different clinical and working samples.

Time-dependent spectral analysis of interactions within groups of walking pedestrians and vertical structural motion using wavelets

NASA Astrophysics Data System (ADS)

Bocian, M.; Brownjohn, J. M. W.; Racic, V.; Hester, D.; Quattrone, A.; Gilbert, L.; Beasley, R.

2018-05-01

A multi-scale and multi-object interaction phenomena can arise when a group of walking pedestrians crosses a structure capable of exhibiting dynamic response. This is because each pedestrian is an autonomous dynamic system capable of displaying intricate behaviour affected by social, psychological, biomechanical and environmental factors, including adaptations to the structural motion. Despite a wealth of mathematical models attempting to describe and simulate coupled crowd-structure system, their applicability can generally be considered uncertain. This can be assigned to a number of assumptions made in their development and the scarcity or unavailability of data suitable for their validation, in particular those associated with pedestrian-pedestrian and pedestrian-structure interaction. To alleviate this problem, data on behaviour of individual pedestrians within groups of six walkers with different spatial arrangements are gathered simultaneously with data on dynamic structural response of a footbridge, from a series of measurements utilising wireless motion monitors. Unlike in previous studies on coordination of pedestrian behaviour, the collected data can serve as a proxy for pedestrian vertical force, which is of critical importance from the point of view of structural stability. A bivariate analysis framework is proposed and applied to these data, encompassing wavelet transform, synchronisation measures based on Shannon entropy and circular statistics. A topological pedestrian map is contrived showing the strength and directionality of between-subjects interactions. It is found that the coordination in pedestrians' vertical force depends on the spatial collocation within a group, but it is generally weak. The relationship between the bridge and pedestrian behaviour is also analysed, revealing stronger propensity for pedestrians to coordinate their force with the structural motion rather than with each other.
Is the thumb a fifth finger? A study of digit interaction during force production tasks

PubMed Central

Olafsdottir, Halla; Zatsiorsky, Vladimir M.; Latash, Mark L.

2010-01-01

We studied indices of digit interaction in single- and multi-digit maximal voluntary contraction (MVC) tests when the thumb acted either in parallel or in opposition to the fingers. The peak force produced by the thumb was much higher when the thumb acted in opposition to the fingers and its share of the total force in the five-digit MVC test increased dramatically. The fingers showed relatively similar peak forces and unchanged sharing patterns in the four-finger MVC task when the thumb acted in parallel and in opposition to the fingers. Enslaving during one-digit tasks showed relatively mild differences between the two conditions, while the differences became large when enslaving was quantified for multi-digit tasks. Force deficit was pronounced when the thumb acted in parallel to the fingers; it showed a monotonic increase with the number of explicitly involved digits up to four digits and then a drop when all five digits were involved. Force deficit all but disappeared when the thumb acted in opposition to the fingers. However, for both thumb positions, indices of digit interaction were similar for groups of digits that did or did not include the thumb. These results suggest that, given a certain hand configuration, the central nervous system treats the thumb as a fifth finger. They provide strong support for the hypothesis that indices of digit interaction reflect neural factors, not the peripheral design of the hand. An earlier formal model was able to account for the data when the thumb acted in parallel to the fingers. However, it failed for the data with the thumb acting in opposition to the fingers. PMID:15322785
Biointerface dynamics--Multi scale modeling considerations.

PubMed

Pajic-Lijakovic, Ivana; Levic, Steva; Nedovic, Viktor; Bugarski, Branko

2015-08-01

Irreversible nature of matrix structural changes around the immobilized cell aggregates caused by cell expansion is considered within the Ca-alginate microbeads. It is related to various effects: (1) cell-bulk surface effects (cell-polymer mechanical interactions) and cell surface-polymer surface effects (cell-polymer electrostatic interactions) at the bio-interface, (2) polymer-bulk volume effects (polymer-polymer mechanical and electrostatic interactions) within the perturbed boundary layers around the cell aggregates, (3) cumulative surface and volume effects within the parts of the microbead, and (4) macroscopic effects within the microbead as a whole based on multi scale modeling approaches. All modeling levels are discussed at two time scales i.e. long time scale (cell growth time) and short time scale (cell rearrangement time). Matrix structural changes results in the resistance stress generation which have the feedback impact on: (1) single and collective cell migrations, (2) cell deformation and orientation, (3) decrease of cell-to-cell separation distances, and (4) cell growth. Herein, an attempt is made to discuss and connect various multi scale modeling approaches on a range of time and space scales which have been proposed in the literature in order to shed further light to this complex course-consequence phenomenon which induces the anomalous nature of energy dissipation during the structural changes of cell aggregates and matrix quantified by the damping coefficients (the orders of the fractional derivatives). Deeper insight into the matrix partial disintegration within the boundary layers is useful for understanding and minimizing the polymer matrix resistance stress generation within the interface and on that base optimizing cell growth. Copyright © 2015 Elsevier B.V. All rights reserved.
An improved lattice Boltzmann scheme for multiphase fluid with multi-range interactions

NASA Astrophysics Data System (ADS)

Maquignon, Nicolas; Duchateau, Julien; Roussel, Gilles; Rousselle, François; Renaud, Christophe

2014-10-01

Modeling of fluids with liquid to gas phase transition has become important for understanding many environmental or industrial processes. Such simulations need new techniques, because traditional solvers are often limited. The Lattice Boltzmann Model (LBM) allows simulate complex fluids, because its mesoscopic nature gives possibility to incorporate additional physics in comparison to usual methods. In this work, an improved lattice Boltzmann model for phase transition flow will be introduced. First, the state of art for Shan & Chen [1] [2] (SC) type of LBM will be reminded. Then, link to real thermodynamics will be established with Maxwell equal areas construction. Convergence to isothermal liquid vapor equilibrium will be shown and discussed. Inclusion of an equation of state for real fluid and better incorporation of force term is presented [4] [5]. Multi-range interactions have been used for SC model [8], but it hasn't been yet applied to real fluid with non-ideal equation of state. In this work, we evaluate this model when it is applied to real liquid-vapor equilibrium. We show that important differences are found for evaluation of gas density. In order to recover thermodynamic consistency, we use a new scheme for calculation of force term, which is a combination of multi range model and numerical weighting used by Gong & Cheng [6] [7]. We show the superiority of our new model by studying convergence to equilibrium values over a large temperature range. We prove that spurious velocities remaining at equilibrium are decreased.
An improved lattice Boltzmann scheme for multiphase fluid with multi-range interactions

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

Maquignon, Nicolas; Duchateau, Julien; Roussel, Gilles

2014-10-06

Modeling of fluids with liquid to gas phase transition has become important for understanding many environmental or industrial processes. Such simulations need new techniques, because traditional solvers are often limited. The Lattice Boltzmann Model (LBM) allows simulate complex fluids, because its mesoscopic nature gives possibility to incorporate additional physics in comparison to usual methods. In this work, an improved lattice Boltzmann model for phase transition flow will be introduced. First, the state of art for Shan and Chen (SC) type of LBM will be reminded. Then, link to real thermodynamics will be established with Maxwell equal areas construction. Convergence tomore » isothermal liquid vapor equilibrium will be shown and discussed. Inclusion of an equation of state for real fluid and better incorporation of force term is presented. Multi-range interactions have been used for SC model, but it hasn't been yet applied to real fluid with non-ideal equation of state. In this work, we evaluate this model when it is applied to real liquid-vapor equilibrium. We show that important differences are found for evaluation of gas density. In order to recover thermodynamic consistency, we use a new scheme for calculation of force term, which is a combination of multi range model and numerical weighting used by Gong and Cheng. We show the superiority of our new model by studying convergence to equilibrium values over a large temperature range. We prove that spurious velocities remaining at equilibrium are decreased.« less
Evaluating the Effects of Climate Change on Summertime Ozone using a Relative Response Factor approach for Policy Makers

EPA Science Inventory

The impact of climate change on surface level ozone is examined through a multi-scale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the Relative Response Factor (RRF_E), which es...
Epidemiología genética sobre las teorías causales y la patogénesis de la diabetes mellitus tipo 2.

PubMed

Castro-Juárez, Carlos Jonnathan; Ramírez-García, Sergio Alberto; Villa-Ruano, Nemesio; García-Cruz, Diana

2017-01-01

Diabetes mellitus type 2 (DM2) is a worldwide public health problem. The etiology of the disease is multifactorial and is characterized by great heterogeneity of metabolic disorders. The most common are the insufficient production of insulin, insulin resistance and impaired incretin system. The specialist must understand the multi-causal nature of DM2 in the post-genomic era. This nature is determined by the additive effect of genes and environment, so there is no simple genetic epidemiological model to explain the inheritance pattern. Hence the need to establish the proportion of disease that is determined by genes and the contribution of environmental factors, the combination of which regulates the threshold or tolerance level for diabetes development. Given this complexity in DM2 in this work are discussed the various existing theories of causality of this disease, which will permit us to understand the interaction between the environment and the human genome, and also to know how risk factors or predisposition to this disease influence, laying the grounds that delimit environment interaction with the genome. Copyright: © 2017 SecretarÍa de Salud.
Racial/ethnic differences in the associations between obesity measures and severity of sleep-disordered breathing: the Multi-Ethnic Study of Atherosclerosis.

PubMed

Chen, Xiaoli; Wang, Rui; Lutsey, Pamela L; Zee, Phyllis C; Javaheri, Sogol; Alcántara, Carmela; Jackson, Chandra L; Szklo, Moyses; Punjabi, Naresh; Redline, Susan; Williams, Michelle A

2016-10-01

The objective of this study was to evaluate associations between obesity measures and sleep-disordered breathing severity among White, Black, Hispanic, and Chinese Americans. The method used in this study was a community-based cross-sectional study of 2053 racially/ethnically diverse adults in the Multi-Ethnic Study of Atherosclerosis. Anthropometry and polysomnography were used to measure obesity and apnea-hypopnea index (AHI). Linear regression models were fitted to investigate associations of body mass index (BMI) and waist circumference with AHI (log transformed) with adjustment for sociodemographics, lifestyle factors, and comorbidities. The mean participant age was 68.4 (range: 54-93) years; 53.6% of participants were women. The median AHI was 9.1 events/h. There were significant associations of BMI and waist circumference with AHI in the overall cohort and within each racial/ethnic group. A significant interaction was observed between race/ethnicity and BMI (P interaction = 0.017). Models predicted that for each unit increase in BMI (kg/m 2 ), the mean AHI increased by 19.7% for Chinese, 11.6% for Whites and Blacks, and 10.5% for Hispanics. Similarly, incremental changes in waist circumference were associated with larger increases in AHI among Chinese than among other groups. Associations of BMI and waist circumference with AHI were stronger among Chinese than among other racial/ethnic groups. These findings highlight a potential emergence of elevated sleep-disordered breathing prevalence occurring in association with increasing obesity in Asian populations. Copyright © 2015 Elsevier B.V. All rights reserved.
Network inference reveals novel connections in pathways regulating growth and defense in the yeast salt response.

PubMed

MacGilvray, Matthew E; Shishkova, Evgenia; Chasman, Deborah; Place, Michael; Gitter, Anthony; Coon, Joshua J; Gasch, Audrey P

2018-05-01

Cells respond to stressful conditions by coordinating a complex, multi-faceted response that spans many levels of physiology. Much of the response is coordinated by changes in protein phosphorylation. Although the regulators of transcriptome changes during stress are well characterized in Saccharomyces cerevisiae, the upstream regulatory network controlling protein phosphorylation is less well dissected. Here, we developed a computational approach to infer the signaling network that regulates phosphorylation changes in response to salt stress. We developed an approach to link predicted regulators to groups of likely co-regulated phospho-peptides responding to stress, thereby creating new edges in a background protein interaction network. We then use integer linear programming (ILP) to integrate wild type and mutant phospho-proteomic data and predict the network controlling stress-activated phospho-proteomic changes. The network we inferred predicted new regulatory connections between stress-activated and growth-regulating pathways and suggested mechanisms coordinating metabolism, cell-cycle progression, and growth during stress. We confirmed several network predictions with co-immunoprecipitations coupled with mass-spectrometry protein identification and mutant phospho-proteomic analysis. Results show that the cAMP-phosphodiesterase Pde2 physically interacts with many stress-regulated transcription factors targeted by PKA, and that reduced phosphorylation of those factors during stress requires the Rck2 kinase that we show physically interacts with Pde2. Together, our work shows how a high-quality computational network model can facilitate discovery of new pathway interactions during osmotic stress.
Consensus for linear multi-agent system with intermittent information transmissions using the time-scale theory

NASA Astrophysics Data System (ADS)

Taousser, Fatima; Defoort, Michael; Djemai, Mohamed

2016-01-01

This paper investigates the consensus problem for linear multi-agent system with fixed communication topology in the presence of intermittent communication using the time-scale theory. Since each agent can only obtain relative local information intermittently, the proposed consensus algorithm is based on a discontinuous local interaction rule. The interaction among agents happens at a disjoint set of continuous-time intervals. The closed-loop multi-agent system can be represented using mixed linear continuous-time and linear discrete-time models due to intermittent information transmissions. The time-scale theory provides a powerful tool to combine continuous-time and discrete-time cases and study the consensus protocol under a unified framework. Using this theory, some conditions are derived to achieve exponential consensus under intermittent information transmissions. Simulations are performed to validate the theoretical results.
From single cells to tissue architecture-a bottom-up approach to modelling the spatio-temporal organisation of complex multi-cellular systems.

PubMed

Galle, J; Hoffmann, M; Aust, G

2009-01-01

Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.
A Model for Generating Multi-hazard Scenarios

NASA Astrophysics Data System (ADS)

Lo Jacomo, A.; Han, D.; Champneys, A.

2017-12-01

Communities in mountain areas are often subject to risk from multiple hazards, such as earthquakes, landslides, and floods. Each hazard has its own different rate of onset, duration, and return period. Multiple hazards tend to complicate the combined risk due to their interactions. Prioritising interventions for minimising risk in this context is challenging. We developed a probabilistic multi-hazard model to help inform decision making in multi-hazard areas. The model is applied to a case study region in the Sichuan province in China, using information from satellite imagery and in-situ data. The model is not intended as a predictive model, but rather as a tool which takes stakeholder input and can be used to explore plausible hazard scenarios over time. By using a Monte Carlo framework and varrying uncertain parameters for each of the hazards, the model can be used to explore the effect of different mitigation interventions aimed at reducing the disaster risk within an uncertain hazard context.
Multiplicity distributions of shower particles and target fragments in 84 Kr 36-emulsion interactions at 1 GeV per nucleon

NASA Astrophysics Data System (ADS)

Singh, M. K.; Soma, A. K.; Pathak, Ramji; Singh, V.

2014-03-01

This article focuses on multiplicity distributions of shower particles and target fragments for interaction of 84 Kr 36 with NIKFI BR-2 nuclear emulsion target at kinetic energy of 1 GeV per nucleon. Experimental multiplicity distributions of shower particles, grey particles, black particles and heavily ionization particles are well described by multi-component Erlang distribution of multi-source thermal model. We have observed a linear correlation in multiplicities for the above mentioned particles or fragments. Further experimental studies have shown a saturation phenomenon in shower particle multiplicity with the increase of target fragment multiplicity.
An Integrated Socio-Environmental Model of Health and Well-Being: a Conceptual Framework Exploring the Joint Contribution of Environmental and Social Exposures to Health and Disease Over the Life Span.

PubMed

Olvera Alvarez, Hector A; Appleton, Allison A; Fuller, Christina H; Belcourt, Annie; Kubzansky, Laura D

2018-06-01

Environmental and social determinants of health often co-occur, particularly among socially disadvantaged populations, yet because they are usually studied separately, their joint effects on health are likely underestimated. Building on converging bodies of literature, we delineate a conceptual framework to address these issues. Previous models provided a foundation for study in this area, and generated research pointing to additional important issues. These include a stronger focus on biobehavioral pathways, both positive and adverse health outcomes, and intergenerational effects. To accommodate the expanded set of issues, we put forward the Integrated Socio-Environmental Model of Health and Well-Being (ISEM), which examines how social and environmental factors combine and potentially interact, via multi-factorial pathways, to affect health and well-being over the life span. We then provide applied examples including the study of how food environments affect dietary behavior. The ISEM provides a comprehensive, theoretically informed framework to guide future research on the joint contribution of social and environmental factors to health and well-being across the life span.
Genotype x prenatal and post-weaning nutritional environment interaction in a composite beef cattle breed using reaction norms and multi-trait model

USDA-ARS?s Scientific Manuscript database

Environmental effects have been shown to influence several economically important traits in beef cattle. In this study, genetic x nutritional environment interaction has been evaluated in a composite beef cattle breed (50% Red Angus, 25% Charolais, 25% Tarentaise). Four nutritional environments (MAR...
Analytical study of the acoustic field in a spherical resonator for single bubble sonoluminescence.

PubMed

Dellavale, Damián; Urteaga, Raúl; Bonetto, Fabián J

2010-01-01

The acoustic field in the liquid within a spherical solid shell is calculated. The proposed model takes into account Stoke's wave equation in the viscous fluid, the membrane theory to describe the solid shell motion and the energy loss through the external couplings of the system. A point source at the resonator center is included to reproduce the acoustic emission of a sonoluminescence bubble. Particular calculations of the resulting acoustic field are performed for viscous liquids of interest in single bubble sonoluminescence. The model reveals that in case of radially symmetric modes of low frequency, the quality factor is mainly determined by the acoustic energy flowing through the mechanical coupling of the resonator. Alternatively, for high frequency modes the quality factor is mainly determined by the viscous dissipation in the liquid. Furthermore, the interaction between the bubble acoustic emission and the resonator modes is analyzed. It was found that the bubble acoustic emission produces local maxima in the resonator response. The calculated amplitudes and relative phases of the harmonics constituting the bubble acoustic environment can be used to improve multi-frequency driving in sonoluminescence.
A Conditional Curie-Weiss Model for Stylized Multi-group Binary Choice with Social Interaction

NASA Astrophysics Data System (ADS)

Opoku, Alex Akwasi; Edusei, Kwame Owusu; Ansah, Richard Kwame

2018-04-01

This paper proposes a conditional Curie-Weiss model as a model for decision making in a stylized society made up of binary decision makers that face a particular dichotomous choice between two options. Following Brock and Durlauf (Discrete choice with social interaction I: theory, 1955), we set-up both socio-economic and statistical mechanical models for the choice problem. We point out when both the socio-economic and statistical mechanical models give rise to the same self-consistent equilibrium mean choice level(s). Phase diagram of the associated statistical mechanical model and its socio-economic implications are discussed.
Brief analysis of Jiangsu grid security and stability based on multi-infeed DC index in power system

NASA Astrophysics Data System (ADS)

Zhang, Wenjia; Wang, Quanquan; Ge, Yi; Huang, Junhui; Chen, Zhengfang

2018-02-01

The impact of Multi-infeed HVDC has gradually increased to security and stability operating in Jiangsu power grid. In this paper, an appraisal method of Multi-infeed HVDC power grid security and stability is raised with Multi-Infeed Effective Short Circuit Ratio, Multi-Infeed Interaction Factor and Commutation Failure Immunity Index. These indices are adopted in security and stability simulating calculation of Jiangsu Multi-infeed HVDC system. The simulation results indicate that Jiangsu power grid is operating with a strong DC system. It has high level of power grid security and stability, and meet the safety running requirements. Jinpin-Suzhou DC system is located in the receiving end with huge capacity, which is easily leading to commutation failure of the transmission line. In order to resolve this problem, dynamic reactive power compensation can be applied in power grid near Jinpin-Suzhou DC system. Simulation result shows this method is feasible to commutation failure.
Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.
Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234

Associations between Ectomycorrhizal Fungi and Bacterial Needle Endophytes in Pinus radiata: Implications for Biotic Selection of Microbial Communities

PubMed Central

Rúa, Megan A.; Wilson, Emily C.; Steele, Sarah; Munters, Arielle R.; Hoeksema, Jason D.; Frank, Anna C.

2016-01-01

Studies of the ecological and evolutionary relationships between plants and their associated microbes have long been focused on single microbes, or single microbial guilds, but in reality, plants associate with a diverse array of microbes from a varied set of guilds. As such, multitrophic interactions among plant-associated microbes from multiple guilds represent an area of developing research, and can reveal how complex microbial communities are structured around plants. Interactions between coniferous plants and their associated microbes provide a good model system for such studies, as conifers host a suite of microorganisms including mutualistic ectomycorrhizal (ECM) fungi and foliar bacterial endophytes. To investigate the potential role ECM fungi play in structuring foliar bacterial endophyte communities, we sampled three isolated, native populations of Monterey pine (Pinus radiata), and used constrained analysis of principal coordinates to relate the community matrices of the ECM fungi and bacterial endophytes. Our results suggest that ECM fungi may be important factors for explaining variation in bacterial endophyte communities but this effect is influenced by population and environmental characteristics, emphasizing the potential importance of other factors — biotic or abiotic — in determining the composition of bacterial communities. We also classified ECM fungi into categories based on known fungal traits associated with substrate exploration and nutrient mobilization strategies since variation in these traits allows the fungi to acquire nutrients across a wide range of abiotic conditions and may influence the outcome of multi-species interactions. Across populations and environmental factors, none of the traits associated with fungal foraging strategy types significantly structured bacterial assemblages, suggesting these ECM fungal traits are not important for understanding endophyte-ECM interactions. Overall, our results suggest that both biotic species interactions and environmental filtering are important for structuring microbial communities but emphasize the need for more research into these interactions. PMID:27065966
Effects of land use on lake nutrients: The importance of scale, hydrologic connectivity, and region

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales.
Effects of Land Use on Lake Nutrients: The Importance of Scale, Hydrologic Connectivity, and Region

PubMed Central

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales. PMID:26267813
Comparison of Two Stochastic Daily Rainfall Models and their Ability to Preserve Multi-year Rainfall Variability

NASA Astrophysics Data System (ADS)

Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony; Parana Manage, Nadeeka

2016-04-01

Stochastic simulation of rainfall is often required in the simulation of streamflow and reservoir levels for water security assessment. As reservoir water levels generally vary on monthly to multi-year timescales, it is important that these rainfall series accurately simulate the multi-year variability. However, the underestimation of multi-year variability is a well-known issue in daily rainfall simulation. Focusing on this issue, we developed a hierarchical Markov Chain (MC) model in a traditional two-part MC-Gamma Distribution modelling structure, but with a new parameterization technique. We used two parameters of first-order MC process (transition probabilities of wet-to-wet and dry-to-dry days) to simulate the wet and dry days, and two parameters of Gamma distribution (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. We found that use of deterministic Gamma parameter values results in underestimation of multi-year variability of rainfall depths. Therefore, we calculated the Gamma parameters for each month of each year from the observed data. Then, for each month, we fitted a multi-variate normal distribution to the calculated Gamma parameter values. In the model, we stochastically sampled these two Gamma parameters from the multi-variate normal distribution for each month of each year and used them to generate rainfall depth in wet days using the Gamma distribution. In another study, Mehrotra and Sharma (2007) proposed a semi-parametric Markov model. They also used a first-order MC process for rainfall occurrence simulation. But, the MC parameters were modified by using an additional factor to incorporate the multi-year variability. Generally, the additional factor is analytically derived from the rainfall over a pre-specified past periods (e.g. last 30, 180, or 360 days). They used a non-parametric kernel density process to simulate the wet day rainfall depths. In this study, we have compared the performance of our hierarchical MC model with the semi-parametric model in preserving rainfall variability in daily, monthly, and multi-year scales. To calibrate the parameters of both models and assess their ability to preserve observed statistics, we have used ground based data from 15 raingauge stations around Australia, which consist a wide range of climate zones including coastal, monsoonal, and arid climate characteristics. In preliminary results, both models show comparative performances in preserving the multi-year variability of rainfall depth and occurrence. However, the semi-parametric model shows a tendency of overestimating the mean rainfall depth, while our model shows a tendency of overestimating the number of wet days. We will discuss further the relative merits of the both models for hydrology simulation in the presentation.
Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

PubMed

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.
Domain modeling and grid generation for multi-block structured grids with application to aerodynamic and hydrodynamic configurations

NASA Technical Reports Server (NTRS)

Spekreijse, S. P.; Boerstoel, J. W.; Vitagliano, P. L.; Kuyvenhoven, J. L.

1992-01-01

About five years ago, a joint development was started of a flow simulation system for engine-airframe integration studies on propeller as well as jet aircraft. The initial system was based on the Euler equations and made operational for industrial aerodynamic design work. The system consists of three major components: a domain modeller, for the graphical interactive subdivision of flow domains into an unstructured collection of blocks; a grid generator, for the graphical interactive computation of structured grids in blocks; and a flow solver, for the computation of flows on multi-block grids. The industrial partners of the collaboration and NLR have demonstrated that the domain modeller, grid generator and flow solver can be applied to simulate Euler flows around complete aircraft, including propulsion system simulation. Extension to Navier-Stokes flows is in progress. Delft Hydraulics has shown that both the domain modeller and grid generator can also be applied successfully for hydrodynamic configurations. An overview is given about the main aspects of both domain modelling and grid generation.
A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context

PubMed Central

2010-01-01

Background Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm. Results PDM-ANN and GA-ANN were comparatively assessed in terms of their ability to identify the most important factors among the initial 63 variables describing genetic variations, nutrition and gender, able to classify a subject into one of the BMI related classes: normal and overweight. The methods were designed and evaluated using appropriate training and testing sets provided by 3-fold Cross Validation (3-CV) resampling. Classification accuracy, sensitivity, specificity and area under receiver operating characteristics curve were utilized to evaluate the resulted predictive ANN models. The most parsimonious set of factors was obtained by the GA-ANN method and included gender, six genetic variations and 18 nutrition-related variables. The corresponding predictive model was characterized by a mean accuracy equal of 61.46% in the 3-CV testing sets. Conclusions The ANN based methods revealed factors that interactively contribute to obesity trait and provided predictive models with a promising generalization ability. In general, results showed that ANNs and their hybrids can provide useful tools for the study of complex traits in the context of nutrigenetics. PMID:20825661
Incorporation of the statistical multi-fragmentation model in PHITS and its application for simulation of fragmentation by heavy ions and protons

NASA Astrophysics Data System (ADS)

Ogawa, Tatsuhiko; Sato, Tatsuhiko; Hashimoto, Shintaro; Niita, Koji

2014-06-01

The fragmentation reactions of relativistic-energy nucleus-nucleus and proton-nucleus collisions were simulated using the Statistical Multi-fragmentation Model (SMM) incorporated with the Particle and Heavy Ion Transport code System (PHITS). The comparisons of calculated cross-sections with literature data showed that PHITS-SMM predicts the fragmentation cross-sections of heavy nuclei up to two orders of magnitude more accurately than PHITS for heavy-ion-induced reactions. For proton-induced reactions, noticeable improvements are observed for interactions of the heavy target with protons at an energy greater than 1 GeV. Therefore, consideration for multi-fragmentation reactions is necessary for the accurate simulation of energetic fragmentation reactions of heavy nuclei.
The Rényi entropy H2 as a rigorous, measurable lower bound for the entropy of the interaction region in multi-particle production processes

NASA Astrophysics Data System (ADS)

Bialas, A.; Czyz, W.; Zalewski, K.

2006-10-01

A model-independent lower bound on the entropy S of the multi-particle system produced in high energy collisions, provided by the measurable Rényi entropy H2, is shown to be very effective. Estimates show that the ratio H2/S remains close to one half for all realistic values of the parameters.
Electron density determination and bonding in tetragonal binary intermetallics by convergent beam electron diffraction

NASA Astrophysics Data System (ADS)

Sang, Xiahan

Intermetallics offer unique property combinations often superior to those of more conventional solid solution alloys of identical composition. Understanding of bonding in intermetallics would greatly accelerate development of intermetallics for advanced and high performance engineering applications. Tetragonal intermetallics L10 ordered TiAl, FePd and FePt are used as model systems to experimentally measure their electron densities using quantitative convergent beam electron diffraction (QCBED) method and then compare details of the 3d-4d (FePd) and 3d-5d (FePt) electron interactions to elucidate their role on properties of the respective ferromagnetic L10-ordered intermetallics FePd and FePt. A new multi-beam off-zone axis condition QCBED method has been developed to increase sensitivity of CBED patterns to change of structure factors and the anisotropic Debye-Waller (DW) factors. Unprecedented accuracy and precision in structure and DW factor measurements has been achieved by acquiring CBED patterns using beam-sample geometry that ensures strong dynamical interaction between the fast electrons and the periodic potential in the crystalline samples. This experimental method has been successfully applied to diamond cubic Si, and chemically ordered B2 cubic NiAl, tetragonal L10 ordered TiAl and FePd. The accurate and precise experimental DW and structure factors for L10 TiAl and FePd allow direct evaluation of computer calculations using the current state of the art density functional theory (DFT) based electron structure modeling. The experimental electron density difference map of L1 0 TiAl shows that the DFT calculations describe bonding to a sufficient accuracy for s- and p- electrons interaction, e. g., the Al-layer. However, it indicate significant quantitative differences to the experimental measurements for the 3d-3d interactions of the Ti atoms, e.g. in the Ti layers. The DFT calculations for L10 FePd also show that the current DFT approximations insufficiently describe the interaction between Fe-Fe (3d-3d), Fe-Pd (3d-4d) and Pd-Pd (4d-4d) electrons, which indicates the necessity to evaluate applicability of different DFT approximations, and also provides experimental data for the development of new DFT approximation that better describes transition metal based intermetallic systems.
Testing of two source energy balance model under irrigated and dryland conditions using high resolution airborne imagery

USDA-ARS?s Scientific Manuscript database

Two Source Model (TSM) calculates the heat and water exchange and interaction between soil-atmosphere and vegetation-atmosphere separately. This is achieved through decomposition of radiometric surface temperature to soil and vegetation component temperatures either from multi-angular remotely sense...
Multi-criteria comparative evaluation of spallation reaction models

NASA Astrophysics Data System (ADS)

Andrianov, Andrey; Andrianova, Olga; Konobeev, Alexandr; Korovin, Yury; Kuptsov, Ilya

2017-09-01

This paper presents an approach to a comparative evaluation of the predictive ability of spallation reaction models based on widely used, well-proven multiple-criteria decision analysis methods (MAVT/MAUT, AHP, TOPSIS, PROMETHEE) and the results of such a comparison for 17 spallation reaction models in the presence of the interaction of high-energy protons with natPb.
The Role of Scientific Modeling Criteria in Advancing Students' Explanatory Ideas of Magnetism

ERIC Educational Resources Information Center

Cheng, Meng-Fei; Brown, David E.

2015-01-01

Student construction of models is a strong focus of current research and practice in science education. In order to study in detail the interactions between students' model generation and evaluation and their development of explanatory ideas to account for magnetic phenomena, a multi-session teaching experiment was conducted with a small number of…
A Model Supported Interactive Virtual Environment for Natural Resource Sharing in Environmental Education

ERIC Educational Resources Information Center

Barbalios, N.; Ioannidou, I.; Tzionas, P.; Paraskeuopoulos, S.

2013-01-01

This paper introduces a realistic 3D model supported virtual environment for environmental education, that highlights the importance of water resource sharing by focusing on the tragedy of the commons dilemma. The proposed virtual environment entails simulations that are controlled by a multi-agent simulation model of a real ecosystem consisting…
Network formation in a multi-asset artificial stock market

NASA Astrophysics Data System (ADS)

Wu, Songtao; He, Jianmin; Li, Shouwei; Wang, Chao

2018-04-01

A multi-asset artificial stock market is developed. In the market, stocks are assigned to a number of sectors and traded by heterogeneous investors. The mechanism of continuous double auction is employed to clear order book and form daily closed prices. Simulation results of prices at the sector level show an intra-sector similarity and inter-sector distinctiveness, and returns of individual stocks have stylized facts that are ubiquitous in the real-world stock market. We find that the market risk factor has critical impact on both network topology transition and connection formation, and that sector risk factors account for the formation of intra-sector links and sector-based local interaction. In addition, the number of community in threshold-based networks is correlated negatively and positively with the value of correlation coefficients and the ratio of intra-sector links, which are respectively determined by intensity of sector risk factors and the number of sectors.
Measuring Social Relationships in Different Social Systems: The Construction and Validation of the Evaluation of Social Systems (EVOS) Scale

PubMed Central

Aguilar-Raab, Corina; Grevenstein, Dennis; Schweitzer, Jochen

2015-01-01

Social interactions have gained increasing importance, both as an outcome and as a possible mediator in psychotherapy research. Still, there is a lack of adequate measures capturing relational aspects in multi-person settings. We present a new measure to assess relevant dimensions of quality of relationships and collective efficacy regarding interpersonal interactions in diverse personal and professional social systems including couple partnerships, families, and working teams: the EVOS. Theoretical dimensions were derived from theories of systemic family therapy and organizational psychology. The study was divided in three parts: In Study 1 (N = 537), a short 9-item scale with two interrelated factors was constructed on the basis of exploratory factor analysis. Quality of relationship and collective efficacy emerged as the most relevant dimensions for the quality of social systems. Study 2 (N = 558) confirmed the measurement model using confirmatory factor analysis and established validity with measures of family functioning, life satisfaction, and working team efficacy. Measurement invariance was assessed to ensure that EVOS captures the same latent construct in all social contexts. In Study 3 (N = 317), an English language adaptation was developed, which again confirmed the original measurement model. The EVOS is a theory-based, economic, reliable, and valid measure that covers important aspects of social relationships, applicable for different social systems. It is the first instrument of its kind and an important addition to existing measures of social relationships and related outcome measures in therapeutic and other counseling settings involving multiple persons. PMID:26200357
Learning with Interactive Whiteboards: Determining the Factors on Promoting Interactive Whiteboards to Students by Technology Acceptance Model

ERIC Educational Resources Information Center

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

2015-01-01

Purpose: The purpose of this study is to investigate the factors which might affect the intention to use interactive whiteboards (IWBs) by university students, using Technology Acceptance Model by the structural equation modeling approach. The following hypothesis guided the current study: H1. There is a positive relationship between IWB…
Building and verifying a severity prediction model of acute pancreatitis (AP) based on BISAP, MEWS and routine test indexes.

PubMed

Ye, Jiang-Feng; Zhao, Yu-Xin; Ju, Jian; Wang, Wei

2017-10-01

To discuss the value of the Bedside Index for Severity in Acute Pancreatitis (BISAP), Modified Early Warning Score (MEWS), serum Ca2+, similarly hereinafter, and red cell distribution width (RDW) for predicting the severity grade of acute pancreatitis and to develop and verify a more accurate scoring system to predict the severity of AP. In 302 patients with AP, we calculated BISAP and MEWS scores and conducted regression analyses on the relationships of BISAP scoring, RDW, MEWS, and serum Ca2+ with the severity of AP using single-factor logistics. The variables with statistical significance in the single-factor logistic regression were used in a multi-factor logistic regression model; forward stepwise regression was used to screen variables and build a multi-factor prediction model. A receiver operating characteristic curve (ROC curve) was constructed, and the significance of multi- and single-factor prediction models in predicting the severity of AP using the area under the ROC curve (AUC) was evaluated. The internal validity of the model was verified through bootstrapping. Among 302 patients with AP, 209 had mild acute pancreatitis (MAP) and 93 had severe acute pancreatitis (SAP). According to single-factor logistic regression analysis, we found that BISAP, MEWS and serum Ca2+ are prediction indexes of the severity of AP (P-value<0.001), whereas RDW is not a prediction index of AP severity (P-value>0.05). The multi-factor logistic regression analysis showed that BISAP and serum Ca2+ are independent prediction indexes of AP severity (P-value<0.001), and MEWS is not an independent prediction index of AP severity (P-value>0.05); BISAP is negatively related to serum Ca2+ (r=-0.330, P-value<0.001). The constructed model is as follows: ln()=7.306+1.151*BISAP-4.516*serum Ca2+. The predictive ability of each model for SAP follows the order of the combined BISAP and serum Ca2+ prediction model>Ca2+>BISAP. There is no statistical significance for the predictive ability of BISAP and serum Ca2+ (P-value>0.05); however, there is remarkable statistical significance for the predictive ability using the newly built prediction model as well as BISAP and serum Ca2+ individually (P-value<0.01). Verification of the internal validity of the models by bootstrapping is favorable. BISAP and serum Ca2+ have high predictive value for the severity of AP. However, the model built by combining BISAP and serum Ca2+ is remarkably superior to those of BISAP and serum Ca2+ individually. Furthermore, this model is simple, practical and appropriate for clinical use. Copyright © 2016. Published by Elsevier Masson SAS.
Multi-pathway Kinase Signatures of Multipotent Stromal Cells are Predictive for Osteogenic Differentiation

PubMed Central

Platt, Manu O.; Wilder, Catera L.; Wells, Alan; Griffith, Linda G.; Lauffenburger, Douglas A.

2010-01-01

Bone marrow-derived multi-potent stromal cells (MSCs) offer great promise for regenerating tissue. While certain transcription factors have been identified in association with tendency toward particular MSC differentiation phenotypes, the regulatory network of key receptor-mediated signaling pathways activated by extracellular ligands that induce various differentiation responses remain poorly understood. Attempts to predict differentiation fate tendencies from individual pathways in isolation are problematic due to the complex pathway interactions inherent in signaling networks. Accordingly, we have undertaken a multi-variate systems approach integrating experimental measurement of multiple kinase pathway activities and osteogenic differentiation in MSCs, together with computational analysis to elucidate quantitative combinations of kinase signals predictive of cell behavior across diverse contexts. In particular, for culture on polymeric biomaterials surfaces presenting tethered epidermal growth factor (tEGF), type-I collagen, neither, or both, we have found that a partial least-squares regression model yields successful prediction of phenotypic behavior on the basis of two principal components comprising the weighted sums of 8 intracellular phosphoproteins: p-EGFR, p-Akt, p-ERK1/2, p-Hsp27, p-c-jun, p-GSK3α/β, p-p38, and p-STAT3. This combination provides strongest predictive capability for 21-day differentiated phenotype status when calculated from day-7 signal measurements (99%); day-4 (88%) and day-14 (89%) signal measurements are also significantly predictive, indicating a broad time-frame during MSC osteogenesis wherein multiple pathways and states of the kinase signaling network are quantitatively integrated to regulate gene expression, cell processes, and ultimately, cell fate. PMID:19750537
Methodology to improve design of accelerated life tests in civil engineering projects.

PubMed

Lin, Jing; Yuan, Yongbo; Zhou, Jilai; Gao, Jie

2014-01-01

For reliability testing an Energy Expansion Tree (EET) and a companion Energy Function Model (EFM) are proposed and described in this paper. Different from conventional approaches, the EET provides a more comprehensive and objective way to systematically identify external energy factors affecting reliability. The EFM introduces energy loss into a traditional Function Model to identify internal energy sources affecting reliability. The combination creates a sound way to enumerate the energies to which a system may be exposed during its lifetime. We input these energies into planning an accelerated life test, a Multi Environment Over Stress Test. The test objective is to discover weak links and interactions among the system and the energies to which it is exposed, and design them out. As an example, the methods are applied to the pipe in subsea pipeline. However, they can be widely used in other civil engineering industries as well. The proposed method is compared with current methods.

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

PubMed Central

Moss, Robert; Grosse, Thibault; Marchant, Ivanny; Lassau, Nathalie; Gueyffier, François; Thomas, S. Randall

2012-01-01

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models. PMID:22761561
Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.
Dynamic Museum Place: Exploring the Multi-Dimensional Museum Environment

ERIC Educational Resources Information Center

Leach, Denise Blair

2007-01-01

Place is an important factor in museum education, yet describing what the museum is as place is often difficult. This article introduces the idea that museums consist of multiple physical and virtual place "domains" where interactions between people and objects occur: the origin domain, creation domain, display domain, and the experiencer-object…
Determinants of Academic Achievement of Middle Schoolers in Turkey

ERIC Educational Resources Information Center

Börkan, Bengü; Bakis, Ozan

2016-01-01

The purpose of this study is to discuss student and school factors, including cross level interaction, that cause inequalities in seven and eighth grade students' achievement in Turkish context by using national achievement test scores with a multi-level statistical approach. Our results are in line with most other studies with similar purpose.…
Optimization of multi-environment trials for genomic selection based on crop models.

PubMed

Rincent, R; Kuhn, E; Monod, H; Oury, F-X; Rousset, M; Allard, V; Le Gouis, J

2017-08-01

We propose a statistical criterion to optimize multi-environment trials to predict genotype × environment interactions more efficiently, by combining crop growth models and genomic selection models. Genotype × environment interactions (GEI) are common in plant multi-environment trials (METs). In this context, models developed for genomic selection (GS) that refers to the use of genome-wide information for predicting breeding values of selection candidates need to be adapted. One promising way to increase prediction accuracy in various environments is to combine ecophysiological and genetic modelling thanks to crop growth models (CGM) incorporating genetic parameters. The efficiency of this approach relies on the quality of the parameter estimates, which depends on the environments composing this MET used for calibration. The objective of this study was to determine a method to optimize the set of environments composing the MET for estimating genetic parameters in this context. A criterion called OptiMET was defined to this aim, and was evaluated on simulated and real data, with the example of wheat phenology. The MET defined with OptiMET allowed estimating the genetic parameters with lower error, leading to higher QTL detection power and higher prediction accuracies. MET defined with OptiMET was on average more efficient than random MET composed of twice as many environments, in terms of quality of the parameter estimates. OptiMET is thus a valuable tool to determine optimal experimental conditions to best exploit MET and the phenotyping tools that are currently developed.
Causal functional contributions and interactions in the attention network of the brain: an objective multi-perturbation analysis.

PubMed

Zavaglia, Melissa; Hilgetag, Claus C

2016-06-01

Spatial attention is a prime example for the distributed network functions of the brain. Lesion studies in animal models have been used to investigate intact attentional mechanisms as well as perspectives for rehabilitation in the injured brain. Here, we systematically analyzed behavioral data from cooling deactivation and permanent lesion experiments in the cat, where unilateral deactivation of the posterior parietal cortex (in the vicinity of the posterior middle suprasylvian cortex, pMS) or the superior colliculus (SC) cause a severe neglect in the contralateral hemifield. Counterintuitively, additional deactivation of structures in the opposite hemisphere reverses the deficit. Using such lesion data, we employed a game-theoretical approach, multi-perturbation Shapley value analysis (MSA), for inferring functional contributions and network interactions of bilateral pMS and SC from behavioral performance in visual attention studies. The approach provides an objective theoretical strategy for lesion inferences and allows a unique quantitative characterization of regional functional contributions and interactions on the basis of multi-perturbations. The quantitative analysis demonstrated that right posterior parietal cortex and superior colliculus made the strongest positive contributions to left-field orienting, while left brain regions had negative contributions, implying that their perturbation may reverse the effects of contralateral lesions or improve normal function. An analysis of functional modulations and interactions among the regions revealed redundant interactions (implying functional overlap) between regions within each hemisphere, and synergistic interactions between bilateral regions. To assess the reliability of the MSA method in the face of variable and incomplete input data, we performed a sensitivity analysis, investigating how much the contribution values of the four regions depended on the performance of specific configurations and on the prediction of unknown performances. The results suggest that the MSA approach is sensitive to categorical, but insensitive to gradual changes in the input data. Finally, we created a basic network model that was based on the known anatomical interactions among cortical-tectal regions and reproduced the experimentally observed behavior in visual orienting. We discuss the structural organization of the network model relative to the causal modulations identified by MSA, to aid a mechanistic understanding of the attention network of the brain.
Multi-objective game-theory models for conflict analysis in reservoir watershed management.

PubMed

Lee, Chih-Sheng

2012-05-01

This study focuses on the development of a multi-objective game-theory model (MOGM) for balancing economic and environmental concerns in reservoir watershed management and for assistance in decision. Game theory is used as an alternative tool for analyzing strategic interaction between economic development (land use and development) and environmental protection (water-quality protection and eutrophication control). Geographic information system is used to concisely illustrate and calculate the areas of various land use types. The MOGM methodology is illustrated in a case study of multi-objective watershed management in the Tseng-Wen reservoir, Taiwan. The innovation and advantages of MOGM can be seen in the results, which balance economic and environmental concerns in watershed management and which can be interpreted easily by decision makers. For comparison, the decision-making process using conventional multi-objective method to produce many alternatives was found to be more difficult. Copyright Â© 2012 Elsevier Ltd. All rights reserved.
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.
Multi-Unit Considerations for Human Reliability Analysis

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

St. Germain, S.; Boring, R.; Banaseanu, G.

This paper uses the insights from the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) methodology to help identify human actions currently modeled in the single unit PSA that may need to be modified to account for additional challenges imposed by a multi-unit accident as well as identify possible new human actions that might be modeled to more accurately characterize multi-unit risk. In identifying these potential human action impacts, the use of the SPAR-H strategy to include both errors in diagnosis and errors in action is considered as well as identifying characteristics of a multi-unit accident scenario that may impact themore » selection of the performance shaping factors (PSFs) used in SPAR-H. The lessons learned from the Fukushima Daiichi reactor accident will be addressed to further help identify areas where improved modeling may be required. While these multi-unit impacts may require modifications to a Level 1 PSA model, it is expected to have much more importance for Level 2 modeling. There is little currently written specifically about multi-unit HRA issues. A review of related published research will be presented. While this paper cannot answer all issues related to multi-unit HRA, it will hopefully serve as a starting point to generate discussion and spark additional ideas towards the proper treatment of HRA in a multi-unit PSA.« less
Global water cycle

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Christy, John R.; Goodman, Steven J.; Miller, Tim L.; Fitzjarrald, Dan; Lapenta, Bill; Wang, Shouping

1991-01-01

The primary objective is to determine the scope and interactions of the global water cycle with all components of the Earth system and to understand how it stimulates and regulates changes on both global and regional scales. The following subject areas are covered: (1) water vapor variability; (2) multi-phase water analysis; (3) diabatic heating; (4) MSU (Microwave Sounding Unit) temperature analysis; (5) Optimal precipitation and streamflow analysis; (6) CCM (Community Climate Model) hydrological cycle; (7) CCM1 climate sensitivity to lower boundary forcing; and (8) mesoscale modeling of atmosphere/surface interaction.
Multi-Conformation Monte Carlo: A Method for Introducing Flexibility in Efficient Simulations of Many-Protein Systems.

PubMed

Prytkova, Vera; Heyden, Matthias; Khago, Domarin; Freites, J Alfredo; Butts, Carter T; Martin, Rachel W; Tobias, Douglas J

2016-08-25

We present a novel multi-conformation Monte Carlo simulation method that enables the modeling of protein-protein interactions and aggregation in crowded protein solutions. This approach is relevant to a molecular-scale description of realistic biological environments, including the cytoplasm and the extracellular matrix, which are characterized by high concentrations of biomolecular solutes (e.g., 300-400 mg/mL for proteins and nucleic acids in the cytoplasm of Escherichia coli). Simulation of such environments necessitates the inclusion of a large number of protein molecules. Therefore, computationally inexpensive methods, such as rigid-body Brownian dynamics (BD) or Monte Carlo simulations, can be particularly useful. However, as we demonstrate herein, the rigid-body representation typically employed in simulations of many-protein systems gives rise to certain artifacts in protein-protein interactions. Our approach allows us to incorporate molecular flexibility in Monte Carlo simulations at low computational cost, thereby eliminating ambiguities arising from structure selection in rigid-body simulations. We benchmark and validate the methodology using simulations of hen egg white lysozyme in solution, a well-studied system for which extensive experimental data, including osmotic second virial coefficients, small-angle scattering structure factors, and multiple structures determined by X-ray and neutron crystallography and solution NMR, as well as rigid-body BD simulation results, are available for comparison.
Interaction of phenylbutazone and colchicine in binding to serum albumin in rheumatoid therapy: 1H NMR study

NASA Astrophysics Data System (ADS)

Maciążek-Jurczyk, M.; Sułkowska, A.; Bojko, B.; Równicka-Zubik, J.; Sułkowski, W. W.

2009-09-01

The monitoring of drug concentration in blood serum is necessary in multi-drug therapy. Mechanism of drug binding with serum albumin (SA) is one of the most important factors which determine drug concentration and its transport to the destination tissues. In rheumatoid diseases drugs which can induce various adverse effects are commonly used in combination therapy. Such proceeding may result in the enhancement of those side effects due to drug interaction. Interaction of phenylbutazone and colchicine in binding to serum albumin and competition between them in gout has been studied by proton nuclear magnetic resonance ( 1H NMR) technique. The aim of the study was to determine the low affinity binding sites, the strength and kind of interaction between serum albumin and drugs used in combination therapy. The study of competition between phenylbutazone and colchicine in binding to serum albumin points to the change of their affinity to serum albumin in the ternary systems. This should be taken into account in multi-drug therapy. This work is a subsequent part of the spectroscopic study on Phe-COL-SA interactions [A. Sułkowska, et al., J. Mol. Struct. 881 (2008) 97-106].
PAM: Particle automata model in simulation of Fusarium graminearum pathogen expansion.

PubMed

Wcisło, Rafał; Miller, S Shea; Dzwinel, Witold

2016-01-21

The multi-scale nature and inherent complexity of biological systems are a great challenge for computer modeling and classical modeling paradigms. We present a novel particle automata modeling metaphor in the context of developing a 3D model of Fusarium graminearum infection in wheat. The system consisting of the host plant and Fusarium pathogen cells can be represented by an ensemble of discrete particles defined by a set of attributes. The cells-particles can interact with each other mimicking mechanical resistance of the cell walls and cell coalescence. The particles can move, while some of their attributes can be changed according to prescribed rules. The rules can represent cellular scales of a complex system, while the integrated particle automata model (PAM) simulates its overall multi-scale behavior. We show that due to the ability of mimicking mechanical interactions of Fusarium tip cells with the host tissue, the model is able to simulate realistic penetration properties of the colonization process reproducing both vertical and lateral Fusarium invasion scenarios. The comparison of simulation results with micrographs from laboratory experiments shows encouraging qualitative agreement between the two. Copyright © 2015 Elsevier Ltd. All rights reserved.
Modelling and simulating a crisis management system: an organisational perspective

NASA Astrophysics Data System (ADS)

Chaawa, Mohamed; Thabet, Inès; Hanachi, Chihab; Ben Said, Lamjed

2017-04-01

Crises are complex situations due to the dynamism of the environment, its unpredictability and the complexity of the interactions among several different and autonomous involved organisations. In such a context, establishing an organisational view as well as structuring organisations' communications and their functioning is a crucial requirement. In this article, we propose a multi-agent organisational model (OM) to abstract, simulate and analyse a crisis management system (CMS). The objective is to evaluate the CMS from an organisational view, to assess its strength as well as its weakness and to provide deciders with some recommendations for a more flexible and reactive CMS. The proposed OM is illustrated through a real case study: a snowstorm in a Tunisian region. More precisely, we made the following contribution: firstly, we provide an environmental model that identifies the concepts involved in the crisis. Then, we define a role model that copes with the involved actors. In addition, we specify the organisational structure and the interaction model that rule communications and structure actors' functioning. Those models, built following the GAIA methodology, abstract the CMS from an organisational perspective. Finally, we implemented a customisable multi-agent simulator based on the Janus platform to analyse, through several performed simulations, the organisational model.
Game Design to Measure Reflexes and Attention Based on Biofeedback Multi-Sensor Interaction

PubMed Central

Ortiz-Vigon Uriarte, Inigo de Loyola; Garcia-Zapirain, Begonya; Garcia-Chimeno, Yolanda

2015-01-01

This paper presents a multi-sensor system for implementing biofeedback as a human-computer interaction technique in a game involving driving cars in risky situations. The sensors used are: Eye Tracker, Kinect, pulsometer, respirometer, electromiography (EMG) and galvanic skin resistance (GSR). An algorithm has been designed which gives rise to an interaction logic with the game according to the set of physiological constants obtained from the sensors. The results reflect a 72.333 response to the System Usability Scale (SUS), a significant difference of p = 0.026 in GSR values in terms of the difference between the start and end of the game, and an r = 0.659 and p = 0.008 correlation while playing with the Kinect between the breathing level and the energy and joy factor. All the sensors used had an impact on the end results, whereby none of them should be disregarded in future lines of research, even though it would be interesting to obtain separate breathing values from that of the cardio. PMID:25789493
Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.
Grounding a new information technology implementation framework in behavioral science: a systematic analysis of the literature on IT use.

PubMed

Kukafka, Rita; Johnson, Stephen B; Linfante, Allison; Allegrante, John P

2003-06-01

Many interventions to improve the success of information technology (IT) implementations are grounded in behavioral science, using theories, and models to identify conditions and determinants of successful use. However, each model in the IT literature has evolved to address specific theoretical problems of particular disciplinary concerns, and each model has been tested and has evolved using, in most cases, a more or less restricted set of IT implementation procedures. Functionally, this limits the perspective for taking into account the multiple factors at the individual, group, and organizational levels that influence use behavior. While a rich body of literature has emerged, employing prominent models such as the Technology Adoption Model, Social-Cognitive Theory, and Diffusion of Innovation Theory, the complexity of defining a suitable multi-level intervention has largely been overlooked. A gap exists between the implementation of IT and the integration of theories and models that can be utilized to develop multi-level approaches to identify factors that impede usage behavior. We present a novel framework that is intended to guide synthesis of more than one theoretical perspective for the purpose of planning multi-level interventions to enhance IT use. This integrative framework is adapted from PRECEDE/PROCEDE, a conceptual framework used by health planners in hundreds of published studies to direct interventions that account for the multiple determinants of behavior. Since we claim that the literature on IT use behavior does not now include a multi-level approach, we undertook a systematic literature analysis to confirm this assertion. Our framework facilitated organizing this literature synthesis and our analysis was aimed at determining if the IT implementation approaches in the published literature were characterized by an approach that considered at least two levels of IT usage determinants. We found that while 61% of studies mentioned or referred to theory, none considered two or more levels. In other words, although the researchers employ behavioral theory, they omit two fundamental propositions: (1) IT usage is influenced by multiple factors and (2) interventions must be multi-dimensional. Our literature synthesis may provide additional insight into the reason for high failure rates associated with underutilized systems, and underscores the need to move beyond the current dominant approach that employs a single model to guide IT implementation plans that aim to address factors associated with IT acceptance and subsequent positive use behavior.
Empirical potential for molecular simulation of graphene nanoplatelets

NASA Astrophysics Data System (ADS)

Bourque, Alexander J.; Rutledge, Gregory C.

2018-04-01

A new empirical potential for layered graphitic materials is reported. Interatomic interactions within a single graphene sheet are modeled using a Stillinger-Weber potential. Interatomic interactions between atoms in different sheets of graphene in the nanoplatelet are modeled using a Lennard-Jones interaction potential. The potential is validated by comparing molecular dynamics simulations of tensile deformation with the reported elastic constants for graphite. The graphite is found to fracture into graphene nanoplatelets when subjected to ˜15% tensile strain normal to the basal surface of the graphene stack, with an ultimate stress of 2.0 GPa and toughness of 0.33 GPa. This force field is useful to model molecular interactions in an important class of composite systems comprising 2D materials like graphene and multi-layer graphene nanoplatelets.
High Fidelity Modeling of Turbulent Mixing and Chemical Kinetics Interactions in a Post-Detonation Flow Field

NASA Astrophysics Data System (ADS)

Sinha, Neeraj; Zambon, Andrea; Ott, James; Demagistris, Michael

2015-06-01

Driven by the continuing rapid advances in high-performance computing, multi-dimensional high-fidelity modeling is an increasingly reliable predictive tool capable of providing valuable physical insight into complex post-detonation reacting flow fields. Utilizing a series of test cases featuring blast waves interacting with combustible dispersed clouds in a small-scale test setup under well-controlled conditions, the predictive capabilities of a state-of-the-art code are demonstrated and validated. Leveraging physics-based, first principle models and solving large system of equations on highly-resolved grids, the combined effects of finite-rate/multi-phase chemical processes (including thermal ignition), turbulent mixing and shock interactions are captured across the spectrum of relevant time-scales and length scales. Since many scales of motion are generated in a post-detonation environment, even if the initial ambient conditions are quiescent, turbulent mixing plays a major role in the fireball afterburning as well as in dispersion, mixing, ignition and burn-out of combustible clouds in its vicinity. Validating these capabilities at the small scale is critical to establish a reliable predictive tool applicable to more complex and large-scale geometries of practical interest.
A multi-level analysis of the impact of neighborhood structural and social factors on adolescent substance use.

PubMed

Fagan, Abigail A; Wright, Emily M; Pinchevsky, Gillian M

2015-08-01

This paper examined the effects of neighborhood structural (i.e., economic disadvantage, immigrant concentration, residential stability) and social (e.g., collective efficacy, social network interactions, intolerance of drug use, legal cynicism) factors on the likelihood of any adolescent tobacco, alcohol, and marijuana use. Analyses drew upon information from the Project on Human Development in Chicago Neighborhoods (PHDCN). Data were obtained from a survey of adult residents of 79 Chicago neighborhoods, two waves of interviews with 1657 to 1664 care-givers and youth aged 8 to 16 years, and information from the 1990 U.S. Census Bureau. Hierarchical Bernoulli regression models estimated the impact of neighborhood factors on substance use controlling for individual-level demographic characteristics and psycho-social risk factors. Few neighborhood factors had statistically significant direct effects on adolescent tobacco, alcohol or marijuana use, although youth living in neighborhoods with greater levels of immigrant concentration were less likely to report any drinking. Additional theorizing and more empirical research are needed to better understand the ways in which contextual influences affect adolescent substance use and delinquency. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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