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Sample records for identify multiscale integration

  1. Integrated multi-scale modelling and simulation of nuclear fuels

    International Nuclear Information System (INIS)

    Valot, C.; Bertolus, M.; Masson, R.; Malerba, L.; Rachid, J.; Besmann, T.; Phillpot, S.; Stan, M.

    2015-01-01

    This chapter aims at discussing the objectives, implementation and integration of multi-scale modelling approaches applied to nuclear fuel materials. We will first show why the multi-scale modelling approach is required, due to the nature of the materials and by the phenomena involved under irradiation. We will then present the multiple facets of multi-scale modelling approach, while giving some recommendations with regard to its application. We will also show that multi-scale modelling must be coupled with appropriate multi-scale experiments and characterisation. Finally, we will demonstrate how multi-scale modelling can contribute to solving technology issues. (authors)

  2. Multiscale sampling model for motion integration.

    Science.gov (United States)

    Sherbakov, Lena; Yazdanbakhsh, Arash

    2013-09-30

    Biologically plausible strategies for visual scene integration across spatial and temporal domains continues to be a challenging topic. The fundamental question we address is whether classical problems in motion integration, such as the aperture problem, can be solved in a model that samples the visual scene at multiple spatial and temporal scales in parallel. We hypothesize that fast interareal connections that allow feedback of information between cortical layers are the key processes that disambiguate motion direction. We developed a neural model showing how the aperture problem can be solved using different spatial sampling scales between LGN, V1 layer 4, V1 layer 6, and area MT. Our results suggest that multiscale sampling, rather than feedback explicitly, is the key process that gives rise to end-stopped cells in V1 and enables area MT to solve the aperture problem without the need for calculating intersecting constraints or crafting intricate patterns of spatiotemporal receptive fields. Furthermore, the model explains why end-stopped cells no longer emerge in the absence of V1 layer 6 activity (Bolz & Gilbert, 1986), why V1 layer 4 cells are significantly more end-stopped than V1 layer 6 cells (Pack, Livingstone, Duffy, & Born, 2003), and how it is possible to have a solution to the aperture problem in area MT with no solution in V1 in the presence of driving feedback. In summary, while much research in the field focuses on how a laminar architecture can give rise to complicated spatiotemporal receptive fields to solve problems in the motion domain, we show that one can reframe motion integration as an emergent property of multiscale sampling achieved concurrently within lamina and across multiple visual areas.

  3. Integrated multiscale modeling of molecular computing devices

    International Nuclear Information System (INIS)

    Cummings, Peter T; Leng Yongsheng

    2005-01-01

    Molecular electronics, in which single organic molecules are designed to perform the functions of transistors, diodes, switches and other circuit elements used in current siliconbased microelecronics, is drawing wide interest as a potential replacement technology for conventional silicon-based lithographically etched microelectronic devices. In addition to their nanoscopic scale, the additional advantage of molecular electronics devices compared to silicon-based lithographically etched devices is the promise of being able to produce them cheaply on an industrial scale using wet chemistry methods (i.e., self-assembly from solution). The design of molecular electronics devices, and the processes to make them on an industrial scale, will require a thorough theoretical understanding of the molecular and higher level processes involved. Hence, the development of modeling techniques for molecular electronics devices is a high priority from both a basic science point of view (to understand the experimental studies in this field) and from an applied nanotechnology (manufacturing) point of view. Modeling molecular electronics devices requires computational methods at all length scales - electronic structure methods for calculating electron transport through organic molecules bonded to inorganic surfaces, molecular simulation methods for determining the structure of self-assembled films of organic molecules on inorganic surfaces, mesoscale methods to understand and predict the formation of mesoscale patterns on surfaces (including interconnect architecture), and macroscopic scale methods (including finite element methods) for simulating the behavior of molecular electronic circuit elements in a larger integrated device. Here we describe a large Department of Energy project involving six universities and one national laboratory aimed at developing integrated multiscale methods for modeling molecular electronics devices. The project is funded equally by the Office of Basic

  4. Multiscale integration schemes for jump-diffusion systems

    Energy Technology Data Exchange (ETDEWEB)

    Givon, D.; Kevrekidis, I.G.

    2008-12-09

    We study a two-time-scale system of jump-diffusion stochastic differential equations. We analyze a class of multiscale integration methods for these systems, which, in the spirit of [1], consist of a hybridization between a standard solver for the slow components and short runs for the fast dynamics, which are used to estimate the effect that the fast components have on the slow ones. We obtain explicit bounds for the discrepancy between the results of the multiscale integration method and the slow components of the original system.

  5. Integrated multiscale biomaterials experiment and modelling: a perspective

    Science.gov (United States)

    Buehler, Markus J.; Genin, Guy M.

    2016-01-01

    Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126

  6. Simplifying Differential Equations for Multiscale Feynman Integrals beyond Multiple Polylogarithms.

    Science.gov (United States)

    Adams, Luise; Chaubey, Ekta; Weinzierl, Stefan

    2017-04-07

    In this Letter we exploit factorization properties of Picard-Fuchs operators to decouple differential equations for multiscale Feynman integrals. The algorithm reduces the differential equations to blocks of the size of the order of the irreducible factors of the Picard-Fuchs operator. As a side product, our method can be used to easily convert the differential equations for Feynman integrals which evaluate to multiple polylogarithms to an ϵ form.

  7. Integrated Multiscale Latent Variable Regression and Application to Distillation Columns

    Directory of Open Access Journals (Sweden)

    Muddu Madakyaru

    2013-01-01

    Full Text Available Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions, which are usually estimated using inferential models. Commonly used inferential models include latent variable regression (LVR techniques, such as principal component regression (PCR, partial least squares (PLS, and regularized canonical correlation analysis (RCCA. Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. Multiscale filtering has been shown to be a powerful feature extraction tool. In this work, the advantages of multiscale filtering are utilized to enhance the prediction accuracy of LVR models by developing an integrated multiscale LVR (IMSLVR modeling algorithm that integrates modeling and feature extraction. The idea behind the IMSLVR modeling algorithm is to filter the process data at different decomposition levels, model the filtered data from each level, and then select the LVR model that optimizes a model selection criterion. The performance of the developed IMSLVR algorithm is illustrated using three examples, one using synthetic data, one using simulated distillation column data, and one using experimental packed bed distillation column data. All examples clearly demonstrate the effectiveness of the IMSLVR algorithm over the conventional methods.

  8. Integrating cellular metabolism into a multiscale whole-body model.

    Directory of Open Access Journals (Sweden)

    Markus Krauss

    Full Text Available Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development.

  9. Integrating Cellular Metabolism into a Multiscale Whole-Body Model

    Science.gov (United States)

    Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars

    2012-01-01

    Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351

  10. Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.

    Science.gov (United States)

    Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei

    2012-01-01

    This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.

  11. On the mass-coupling relation of multi-scale quantum integrable models

    Energy Technology Data Exchange (ETDEWEB)

    Bajnok, Zoltán; Balog, János [MTA Lendület Holographic QFT Group, Wigner Research Centre,H-1525 Budapest 114, P.O.B. 49 (Hungary); Ito, Katsushi [Department of Physics, Tokyo Institute of Technology,2-12-1 Ookayama, Meguro-ku, Tokyo 152-8551 (Japan); Satoh, Yuji [Institute of Physics, University of Tsukuba,1-1-1 Tennodai, Tsukuba, Ibaraki 305-8571 (Japan); Tóth, Gábor Zsolt [MTA Lendület Holographic QFT Group, Wigner Research Centre,H-1525 Budapest 114, P.O.B. 49 (Hungary)

    2016-06-13

    We determine exactly the mass-coupling relation for the simplest multi-scale quantum integrable model, the homogenous sine-Gordon model with two independent mass-scales. We first reformulate its perturbed coset CFT description in terms of the perturbation of a projected product of minimal models. This representation enables us to identify conserved tensor currents on the UV side. These UV operators are then mapped via form factor perturbation theory to operators on the IR side, which are characterized by their form factors. The relation between the UV and IR operators is given in terms of the sought-for mass-coupling relation. By generalizing the Θ sum rule Ward identity we are able to derive differential equations for the mass-coupling relation, which we solve in terms of hypergeometric functions. We check these results against the data obtained by numerically solving the thermodynamic Bethe Ansatz equations, and find a complete agreement.

  12. Modelling future impacts of air pollution using the multi-scale UK Integrated Assessment Model (UKIAM).

    Science.gov (United States)

    Oxley, Tim; Dore, Anthony J; ApSimon, Helen; Hall, Jane; Kryza, Maciej

    2013-11-01

    Integrated assessment modelling has evolved to support policy development in relation to air pollutants and greenhouse gases by providing integrated simulation tools able to produce quick and realistic representations of emission scenarios and their environmental impacts without the need to re-run complex atmospheric dispersion models. The UK Integrated Assessment Model (UKIAM) has been developed to investigate strategies for reducing UK emissions by bringing together information on projected UK emissions of SO2, NOx, NH3, PM10 and PM2.5, atmospheric dispersion, criteria for protection of ecosystems, urban air quality and human health, and data on potential abatement measures to reduce emissions, which may subsequently be linked to associated analyses of costs and benefits. We describe the multi-scale model structure ranging from continental to roadside, UK emission sources, atmospheric dispersion of emissions, implementation of abatement measures, integration with European-scale modelling, and environmental impacts. The model generates outputs from a national perspective which are used to evaluate alternative strategies in relation to emissions, deposition patterns, air quality metrics and ecosystem critical load exceedance. We present a selection of scenarios in relation to the 2020 Business-As-Usual projections and identify potential further reductions beyond those currently being planned. © 2013.

  13. Vision 2040: A Roadmap for Integrated, Multiscale Modeling and Simulation of Materials and Systems

    Science.gov (United States)

    Liu, Xuan; Furrer, David; Kosters, Jared; Holmes, Jack

    2018-01-01

    Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a diverse team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This report describes the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); identified gaps and actions to close those gaps; and major recommendations) which constitutes a community consensus document as it is a result of over 450 professionals input obtain via: 1) four society workshops (AIAA, NAFEMS, and two TMS), 2) community-wide survey, and 3) the establishment of 9 expert panels (one per KE) consisting on average of 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. The study envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost

  14. Efficient Integration of Coupled Electrical-chemical Systems in Multiscale Neuronal Simulations

    Directory of Open Access Journals (Sweden)

    Ekaterina Brocke

    2016-09-01

    Full Text Available Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. One of them is that the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components of a multiscale test system. We introduce an efficient coupling method based on the second-order backward differentiation formula numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000. The method shows a significant advantage over conventional fixed step size solvers used for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the

  15. “HABITAT MAPPING” GEODATABASE, AN INTEGRATED INTERDISCIPLINARY AND MULTI-SCALE APPROACH FOR DATA MANAGEMENT

    OpenAIRE

    Grande, Valentina; Angeletti, Lorenzo; Campiani, Elisabetta; Conese, Ilaria; Foglini, Federica; Leidi, Elisa; Mercorella, Alessandra; Taviani, Marco

    2016-01-01

    Abstract Historically, a number of different key concepts and methods dealing with marine habitat classifications and mapping have been developed to date. The EU CoCoNET project provides a new attempt in establishing an integrated approach on the definition of habitats. This scheme combines multi-scale geological and biological data, in fact it consists of three levels (Geomorphological level, Substrate level and Biological level) which in turn are divided into several h...

  16. Systematic approximation of multi-scale Feynman integrals arXiv

    CERN Document Server

    Borowka, Sophia; Hulme, Daniel

    An algorithm for the systematic analytical approximation of multi-scale Feynman integrals is presented. The algorithm produces algebraic expressions as functions of the kinematical parameters and mass scales appearing in the Feynman integrals, allowing for fast numerical evaluation. The results are valid in all kinematical regions, both above and below thresholds, up to in principle arbitrary orders in the dimensional regulator. The scope of the algorithm is demonstrated by presenting results for selected two-loop three-point and four-point integrals with an internal mass scale that appear in the two-loop amplitudes for Higgs+jet production.

  17. Porosity characterization for heterogeneous shales using integrated multiscale microscopy

    Science.gov (United States)

    Rassouli, F.; Andrew, M.; Zoback, M. D.

    2016-12-01

    from all different imaging techniques. These multi-scale characterization techniques are then compared with traditional analytical techniques such as Mercury Porosimetry.

  18. MULTI-SCALE SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING IMAGES BY INTEGRATING MULTIPLE FEATURES

    Directory of Open Access Journals (Sweden)

    Y. Di

    2017-05-01

    Full Text Available Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers’ information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford–Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA on the accuracy and slightly inferior to FNEA on the efficiency.

  19. Multiscale mechanical integrity of human supraspinatus tendon in shear after elastin depletion.

    Science.gov (United States)

    Fang, Fei; Lake, Spencer P

    2016-10-01

    Human supraspinatus tendon (SST) exhibits region-specific nonlinear mechanical properties under tension, which have been attributed to its complex multiaxial physiological loading environment. However, the mechanical response and underlying multiscale mechanism regulating SST behavior under other loading scenarios are poorly understood. Furthermore, little is known about the contribution of elastin to tendon mechanics. We hypothesized that (1) SST exhibits region-specific shear mechanical properties, (2) fiber sliding is the predominant mode of local matrix deformation in SST in shear, and (3) elastin helps maintain SST mechanical integrity by facilitating force transfer among collagen fibers. Through the use of biomechanical testing and multiphoton microscopy, we measured the multiscale mechanical behavior of human SST in shear before and after elastase treatment. Three distinct SST regions showed similar stresses and microscale deformation. Collagen fiber reorganization and sliding were physical mechanisms observed as the SST response to shear loading. Measures of microscale deformation were highly variable, likely due to a high degree of extracellular matrix heterogeneity. After elastase treatment, tendon exhibited significantly decreased stresses under shear loading, particularly at low strains. These results show that elastin contributes to tendon mechanics in shear, further complementing our understanding of multiscale tendon structure-function relationships. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. A unified double-loop multi-scale control strategy for NMP integrating-unstable systems

    International Nuclear Information System (INIS)

    Seer, Qiu Han; Nandong, Jobrun

    2016-01-01

    This paper presents a new control strategy which unifies the direct and indirect multi-scale control schemes via a double-loop control structure. This unified control strategy is proposed for controlling a class of highly nonminimum-phase processes having both integrating and unstable modes. This type of systems is often encountered in fed-batch fermentation processes which are very difficult to stabilize via most of the existing well-established control strategies. A systematic design procedure is provided where its applicability is demonstrated via a numerical example. (paper)

  1. Prediction of irradiation damage effects by multi-scale modelling: EURATOM 3 Framework integrated project perfect

    International Nuclear Information System (INIS)

    Massoud, J.P.; Bugat, St.; Marini, B.; Lidbury, D.; Van Dyck, St.; Debarberis, L.

    2008-01-01

    Full text of publication follows. In nuclear PWRs, materials undergo degradation due to severe irradiation conditions that may limit their operational life. Utilities operating these reactors must quantify the aging and the potential degradations of reactor pressure vessels and also of internal structures to ensure safe and reliable plant operation. The EURATOM 6. Framework Integrated Project PERFECT (Prediction of Irradiation Damage Effects in Reactor Components) addresses irradiation damage in RPV materials and components by multi-scale modelling. This state-of-the-art approach offers potential advantages over the conventional empirical methods used in current practice of nuclear plant lifetime management. Launched in January 2004, this 48-month project is focusing on two main components of nuclear power plants which are subject to irradiation damage: the ferritic steel reactor pressure vessel and the austenitic steel internals. This project is also an opportunity to integrate the fragmented research and experience that currently exists within Europe in the field of numerical simulation of radiation damage and creates the links with international organisations involved in similar projects throughout the world. Continuous progress in the physical understanding of the phenomena involved in irradiation damage and continuous progress in computer sciences make possible the development of multi-scale numerical tools able to simulate the effects of irradiation on materials microstructure. The consequences of irradiation on mechanical and corrosion properties of materials are also tentatively modelled using such multi-scale modelling. But it requires to develop different mechanistic models at different levels of physics and engineering and to extend the state of knowledge in several scientific fields. And the links between these different kinds of models are particularly delicate to deal with and need specific works. Practically the main objective of PERFECT is to build

  2. The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

    Science.gov (United States)

    Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

    2018-04-01

    Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

  3. Integrating intracellular dynamics using CompuCell3D and Bionetsolver: applications to multiscale modelling of cancer cell growth and invasion.

    Directory of Open Access Journals (Sweden)

    Vivi Andasari

    Full Text Available In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008 where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and β-catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach.

  4. A multi-scale integrated analysis of the energy use in Romania, Bulgaria, Poland and Hungary

    International Nuclear Information System (INIS)

    Iorgulescu, Raluca I.; Polimeni, John M.

    2009-01-01

    This paper discusses energy use in the case of four countries, Bulgaria, Poland, Hungary, and Romania, which changed the economic system from command economy to open-market. The analysis provided uses the multi-scale integrated analysis of societal metabolism (MSIASM) approach and contrasts it with the use of the traditional indicators approach (GDP growth rates and energy intensity). These traditional indicators have been widely criticized for being inadequate reflections of how energy policies work. Furthermore, the one-size-fits-all policies that result from analyzing these indicators are inaccurate, particularly for transitional economies. The alternative indicators, economic labor productivity, saturation index of human activity, and exosomatic metabolic rates are used to investigate the four case studies considering the complexity of the transition process

  5. Multiscale Modeling of Carbon Fiber Reinforced Polymer (CFRP) for Integrated Computational Materials Engineering Process

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Jiaying; Liang, Biao; Zhang, Weizhao; Liu, Zeliang; Cheng, Puikei; Bostanabad, Ramin; Cao, Jian; Chen, Wei; Liu, Wing Kam; Su, Xuming; Zeng, Danielle; Zhao, John

    2017-10-23

    In this work, a multiscale modeling framework for CFRP is introduced to study hierarchical structure of CFRP. Four distinct scales are defined: nanoscale, microscale, mesoscale, and macroscale. Information at lower scales can be passed to higher scale, which is beneficial for studying effect of constituents on macroscale part’s mechanical property. This bottom-up modeling approach enables better understanding of CFRP from finest details. Current study focuses on microscale and mesoscale. Representative volume element is used at microscale and mesoscale to model material’s properties. At microscale, unidirection CFRP (UD) RVE is used to study properties of UD. The UD RVE can be modeled with different volumetric fraction to encounter non-uniform fiber distribution in CFRP part. Such consideration is important in modeling uncertainties at microscale level. Currently, we identified volumetric fraction as the only uncertainty parameters in UD RVE. To measure effective material properties of UD RVE, periodic boundary conditions (PBC) are applied to UD RVE to ensure convergence of obtained properties. Properties of UD is directly used at mesoscale woven RVE modeling, where each yarn is assumed to have same properties as UD. Within woven RVE, there can be many potential uncertainties parameters to consider for a physical modeling of CFRP. Currently, we will consider fiber misalignment within yarn and angle between wrap and weft yarns. PBC is applied to woven RVE to calculate its effective material properties. The effect of uncertainties are investigated quantitatively by Gaussian process. Preliminary results of UD and Woven study are analyzed for efficacy of the RVE modeling. This work is considered as the foundation for future multiscale modeling framework development for ICME project.

  6. The multiscale expansions of difference equations in the small lattice spacing regime, and a vicinity and integrability test: I

    Science.gov (United States)

    Santini, Paolo Maria

    2010-01-01

    We propose an algorithmic procedure (i) to study the 'distance' between an integrable PDE and any discretization of it, in the small lattice spacing epsilon regime, and, at the same time, (ii) to test the (asymptotic) integrability properties of such discretization. This method should provide, in particular, useful and concrete information on how good is any numerical scheme used to integrate a given integrable PDE. The procedure, illustrated on a fairly general ten-parameter family of discretizations of the nonlinear Schrödinger equation, consists of the following three steps: (i) the construction of the continuous multiscale expansion of a generic solution of the discrete system at all orders in epsilon, following Degasperis et al (1997 Physica D 100 187-211) (ii) the application, to such an expansion, of the Degasperis-Procesi (DP) integrability test (Degasperis A and Procesi M 1999 Asymptotic integrability Symmetry and Perturbation Theory, SPT98, ed A Degasperis and G Gaeta (Singapore: World Scientific) pp 23-37 Degasperis A 2001 Multiscale expansion and integrability of dispersive wave equations Lectures given at the Euro Summer School: 'What is integrability?' (Isaac Newton Institute, Cambridge, UK, 13-24 August); Integrability (Lecture Notes in Physics vol 767) ed A Mikhailov (Berlin: Springer)), to test the asymptotic integrability properties of the discrete system and its 'distance' from its continuous limit; (iii) the use of the main output of the DP test to construct infinitely many approximate symmetries and constants of motion of the discrete system, through novel and simple formulas.

  7. The multiscale expansions of difference equations in the small lattice spacing regime, and a vicinity and integrability test: I

    International Nuclear Information System (INIS)

    Santini, Paolo Maria

    2010-01-01

    We propose an algorithmic procedure (i) to study the 'distance' between an integrable PDE and any discretization of it, in the small lattice spacing ε regime, and, at the same time, (ii) to test the (asymptotic) integrability properties of such discretization. This method should provide, in particular, useful and concrete information on how good is any numerical scheme used to integrate a given integrable PDE. The procedure, illustrated on a fairly general ten-parameter family of discretizations of the nonlinear Schroedinger equation, consists of the following three steps: (i) the construction of the continuous multiscale expansion of a generic solution of the discrete system at all orders in ε, following Degasperis et al (1997 Physica D 100 187-211); (ii) the application, to such an expansion, of the Degasperis-Procesi (DP) integrability test (Degasperis A and Procesi M 1999 Asymptotic integrability Symmetry and Perturbation Theory, SPT98, ed A Degasperis and G Gaeta (Singapore: World Scientific) pp 23-37; Degasperis A 2001 Multiscale expansion and integrability of dispersive wave equations Lectures given at the Euro Summer School: 'What is integrability?' (Isaac Newton Institute, Cambridge, UK, 13-24 August); Integrability (Lecture Notes in Physics vol 767) ed A Mikhailov (Berlin: Springer)), to test the asymptotic integrability properties of the discrete system and its 'distance' from its continuous limit; (iii) the use of the main output of the DP test to construct infinitely many approximate symmetries and constants of motion of the discrete system, through novel and simple formulas.

  8. Towards an integrated multiscale simulation of turbulent clouds on PetaScale computers

    International Nuclear Information System (INIS)

    Wang Lianping; Ayala, Orlando; Parishani, Hossein; Gao, Guang R; Kambhamettu, Chandra; Li Xiaoming; Rossi, Louis; Orozco, Daniel; Torres, Claudio; Grabowski, Wojciech W; Wyszogrodzki, Andrzej A; Piotrowski, Zbigniew

    2011-01-01

    The development of precipitating warm clouds is affected by several effects of small-scale air turbulence including enhancement of droplet-droplet collision rate by turbulence, entrainment and mixing at the cloud edges, and coupling of mechanical and thermal energies at various scales. Large-scale computation is a viable research tool for quantifying these multiscale processes. Specifically, top-down large-eddy simulations (LES) of shallow convective clouds typically resolve scales of turbulent energy-containing eddies while the effects of turbulent cascade toward viscous dissipation are parameterized. Bottom-up hybrid direct numerical simulations (HDNS) of cloud microphysical processes resolve fully the dissipation-range flow scales but only partially the inertial subrange scales. it is desirable to systematically decrease the grid length in LES and increase the domain size in HDNS so that they can be better integrated to address the full range of scales and their coupling. In this paper, we discuss computational issues and physical modeling questions in expanding the ranges of scales realizable in LES and HDNS, and in bridging LES and HDNS. We review our on-going efforts in transforming our simulation codes towards PetaScale computing, in improving physical representations in LES and HDNS, and in developing better methods to analyze and interpret the simulation results.

  9. Numerical Simulation of Early Age Cracking of Reinforced Concrete Bridge Decks with a Full-3D Multiscale and Multi-Chemo-Physical Integrated Analysis

    Directory of Open Access Journals (Sweden)

    Tetsuya Ishida

    2018-03-01

    Full Text Available In November 2011, the Japanese government resolved to build “Revival Roads” in the Tohoku region to accelerate the recovery from the Great East Japan Earthquake of March 2011. Because the Tohoku region experiences such cold and snowy weather in winter, complex degradation from a combination of frost damage, chloride attack from de-icing agents, alkali–silica reaction, cracking and fatigue is anticipated. Thus, to enhance the durability performance of road structures, particularly reinforced concrete (RC bridge decks, multiple countermeasures are proposed: a low water-to-cement ratio in the mix, mineral admixtures such as ground granulated blast furnace slag and/or fly ash to mitigate the risks of chloride attack and alkali–silica reaction, anticorrosion rebar and 6% entrained air for frost damage. It should be noted here that such high durability specifications may conversely increase the risk of early age cracking caused by temperature and shrinkage due to the large amounts of cement and the use of mineral admixtures. Against this background, this paper presents a numerical simulation of early age deformation and cracking of RC bridge decks with full 3D multiscale and multi-chemo-physical integrated analysis. First, a multiscale constitutive model of solidifying cementitious materials is briefly introduced based on systematic knowledge coupling microscopic thermodynamic phenomena and microscopic structural mechanics. With the aim to assess the early age thermal and shrinkage-induced cracks on real bridge deck, the study began with extensive model validations by applying the multiscale and multi-physical integrated analysis system to small specimens and mock-up RC bridge deck specimens. Then, through the application of the current computational system, factors that affect the generation and propagation of early age thermal and shrinkage-induced cracks are identified via experimental validation and full-scale numerical simulation on real

  10. Multiscale modelling in immunology: a review.

    Science.gov (United States)

    Cappuccio, Antonio; Tieri, Paolo; Castiglione, Filippo

    2016-05-01

    One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  11. Integrated multiscale simulation of combined heat and power based district heating system

    International Nuclear Information System (INIS)

    Li, Peifeng; Nord, Natasa; Ertesvåg, Ivar Ståle; Ge, Zhihua; Yang, Zhiping; Yang, Yongping

    2015-01-01

    Highlights: • Simulation of power plant, district heating network and heat users in detail and integrated. • Coupled calculation and analysis of the heat and pressure losses of the district heating network. • District heating is not preferable for very low heat load due to relatively high heat loss. • Lower design supply temperatures of the district heating network give higher system efficiency. - Abstract: Many studies have been carried out separately on combined heat and power and district heating. However, little work has been done considering the heat source, the district heating network and the heat users simultaneously, especially when it comes to the heating system with large-scale combined heat and power plant. For the purpose of energy conservation, it is very important to know well the system performance of the integrated heating system from the very primary fuel input to the terminal heat users. This paper set up a model of 300 MW electric power rated air-cooled combined heat and power plant using Ebsilon software, which was validated according to the design data from the turbine manufacturer. Then, the model of heating network and heat users were developed based on the fundamental theories of fluid mechanics and heat transfer. Finally the combined heat and power based district heating system was obtained and the system performances within multiscale scope of the system were analyzed using the developed Ebsilon model. Topics with regard to the heat loss, the pressure drop, the pump power consumption and the supply temperatures of the district heating network were discussed. Besides, the operational issues of the integrated system were also researched. Several useful conclusions were drawn. It was found that a lower design primary supply temperature of the district heating network would give a higher seasonal energy efficiency of the integrated system throughout the whole heating season. Moreover, it was not always right to relate low design

  12. A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Bangzhu Zhu

    2012-02-01

    Full Text Available Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble forecasting model integrating empirical mode decomposition (EMD, genetic algorithm (GA and artificial neural network (ANN is proposed to forecast carbon price. Firstly, the proposed model uses EMD to decompose carbon price data into several intrinsic mode functions (IMFs and one residue. Then, the IMFs and residue are composed into a high frequency component, a low frequency component and a trend component which have similar frequency characteristics, simple components and strong regularity using the fine-to-coarse reconstruction algorithm. Finally, those three components are predicted using an ANN trained by GA, i.e., a GAANN model, and the final forecasting results can be obtained by the sum of these three forecasting results. For verification and testing, two main carbon future prices with different maturity in the European Climate Exchange (ECX are used to test the effectiveness of the proposed multiscale ensemble forecasting model. Empirical results obtained demonstrate that the proposed multiscale ensemble forecasting model can outperform the single random walk (RW, ARIMA, ANN and GAANN models without EMD preprocessing and the ensemble ARIMA model with EMD preprocessing.

  13. Developing Flexible, Integrated Hydrologic Modeling Systems for Multiscale Analysis in the Midwest and Great Lakes Region

    Science.gov (United States)

    Hamlet, A. F.; Chiu, C. M.; Sharma, A.; Byun, K.; Hanson, Z.

    2016-12-01

    Physically based hydrologic modeling of surface and groundwater resources that can be flexibly and efficiently applied to support water resources policy/planning/management decisions at a wide range of spatial and temporal scales are greatly needed in the Midwest, where stakeholder access to such tools is currently a fundamental barrier to basic climate change assessment and adaptation efforts, and also the co-production of useful products to support detailed decision making. Based on earlier pilot studies in the Pacific Northwest Region, we are currently assembling a suite of end-to-end tools and resources to support various kinds of water resources planning and management applications across the region. One of the key aspects of these integrated tools is that the user community can access gridded products at any point along the end-to-end chain of models, looking backwards in time about 100 years (1915-2015), and forwards in time about 85 years using CMIP5 climate model projections. The integrated model is composed of historical and projected future meteorological data based on station observations and statistical and dynamically downscaled climate model output respectively. These gridded meteorological data sets serve as forcing data for the macro-scale VIC hydrologic model implemented over the Midwest at 1/16 degree resolution. High-resolution climate model (4km WRF) output provides inputs for the analyses of urban impacts, hydrologic extremes, agricultural impacts, and impacts to the Great Lakes. Groundwater recharge estimated by the surface water model provides input data for fine-scale and macro-scale groundwater models needed for specific applications. To highlight the multi-scale use of the integrated models in support of co-production of scientific information for decision making, we briefly describe three current case studies addressing different spatial scales of analysis: 1) Effects of climate change on the water balance of the Great Lakes, 2) Future

  14. Multiscale paradigms in integrated computational materials science and engineering materials theory, modeling, and simulation for predictive design

    CERN Document Server

    Runge, Keith; Muralidharan, Krishna

    2016-01-01

    This book presents cutting-edge concepts, paradigms, and research highlights in the field of computational materials science and engineering, and provides a fresh, up-to-date perspective on solving present and future materials challenges. The chapters are written by not only pioneers in the fields of computational materials chemistry and materials science, but also experts in multi-scale modeling and simulation as applied to materials engineering. Pedagogical introductions to the different topics and continuity between the chapters are provided to ensure the appeal to a broad audience and to address the applicability of integrated computational materials science and engineering for solving real-world problems.

  15. ADVANCED INTEGRATION OF MULTI-SCALE MECHANICS AND WELDING PROCESS SIMULATION IN WELD INTEGRITY ASSESSMENT

    Energy Technology Data Exchange (ETDEWEB)

    Wilkowski, Gery M.; Rudland, David L.; Shim, Do-Jun; Brust, Frederick W.; Babu, Sundarsanam

    2008-06-30

    -driving force by a factor of 2 depending on strain-hardening, pressure level as a % of SMYS, and flaw size. • From years of experience in circumferential fracture analyses and experimentation, there has not been sufficient integration of work performed for other industries into analogous problems facing the oil and gas pipeline markets. Some very basic concepts and problems solved previously in these fields could have circumvented inconsistencies seen in the stress-based and strain-based analysis efforts. For example, in nuclear utility piping work, more detailed elastic-plastic fracture analyses were always validated in their ability to predict loads and displacements (stresses and strains). The eventual implementation of these methodologies will result in acceleration of the industry adoption of higher-strength line-pipe steels.

  16. Multiscale, multispectral and multitemporal satellite data to identify archaeological remains in the archaeological area of Tiwanaku (Bolivia)

    Science.gov (United States)

    Masini, Nicola; Lasaponara, Rosa

    2015-04-01

    The aim of this paper is to investigate the cultural landscape of the archaeological area of Tiwanaku (Bolivia) using multiscale, multispectral and multitemporal satellite data. Geospatial analysis techniques were applied to the satellite data sets in order to enhance and map traces of past human activities and perform a spatial characterization of environmental and cultural patterns. In particular, in the Tiwanaku area, the approach based on local indicators of spatial autocorrelation (LISA) applied to ASTER data allowed us to identify traces of a possible ancient hydrographic network with a clear spatial relation with the well-known moat surrounding the core of the monumental area. The same approach applied to QuickBird data, allowed us to identify numerous traces of archaeological interest, in Mollo Kontu mound, less investigated than the monumental area. Some of these traces were in perfect accordance with the results of independent studies, other were completely unknown. As a whole, the detected features, composing a geometric pattern with roughly North-South orientation, closely match those of the other residential contexts at Tiwanaku. These new insights, captured from multitemporal ASTER and QuickBird data processing, suggested new questions on the ancient landscape and provided important information for planning future field surveys and archaeogeophyical investigations. Reference [1] Lasaponara R., Masini N. 2014. Beyond modern landscape features: New insights in thearchaeological area of Tiwanaku in Bolivia from satellite data. International Journal of Applied Earth Observation and Geoinformation, 26, 464-471, http://dx.doi.org/10.1016/j.jag.2013.09.00. [2] Tapete D., Cigna F., Masini N., Lasaponara R. 2013. Prospection and monitoring of the archaeological heritage of Nasca, Peru, with ENVISAT ASAR, Archaeological Prospection, 20, 133-147, doi: 10.1002/arp.1449. [3] Lasaponara R, N Masini, 2012 Satellite Remote Sensing, A New Tool for Archaeology (Series

  17. Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

    Science.gov (United States)

    Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

    2017-10-01

    A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

  18. Integration of multiscale dendritic spine structure and function data into systems biology models

    Directory of Open Access Journals (Sweden)

    James J Mancuso

    2014-11-01

    Full Text Available Comprising 1011 neurons with 1014 synaptic connections the human brain is the ultimate systems biology puzzle. An increasing body of evidence highlights the observation that changes in brain function, both normal and pathological, consistently correlate with dynamic changes in neuronal anatomy. Anatomical changes occur on a full range of scales from the trafficking of individual proteins, to alterations in synaptic morphology both individually and on a systems level, to reductions in long distance connectivity and brain volume. The major sites of contact for synapsing neurons are dendritic spines, which provide an excellent metric for the number and strength of signaling connections between elements of functional neuronal circuits. A comprehensive model of anatomical changes and their functional consequences would be a holy grail for the field of systems neuroscience but its realization appears far on the horizon. Various imaging technologies have advanced to allow for multi-scale visualization of brain plasticity and pathology, but computational analysis of the massive big data sets involved forms the bottleneck toward the creation of multiscale models of brain structure and function. While a full accounting of techniques and progress toward a comprehensive model of brain anatomy and function is beyond the scope of this or any other single paper, this review serves to highlight the opportunities for analysis of neuronal spine anatomy and function provided by new imaging technologies and the high-throughput application of older technologies while surveying the strengths and weaknesses of currently available computational analytical tools and room for future improvement.

  19. A method for identifying gas-liquid two-phase flow patterns on the basis of wavelet packet multi-scale information entropy and HMM

    International Nuclear Information System (INIS)

    Zhou Yunlong; Zhang Xueqing; Gao Yunpeng; Cheng Yue

    2009-01-01

    For studying flow regimes of gas/liquid two-phase in a vertical upward pipe, the conductance fluctuation information of four typical flow regimes was collected by a measuring the system with self-made multiple conductivity probes. Owing to the non-stationarity of conductance fluctuation signals of gas-liquid two-phase flow, a kind of' flow regime identification method based on wavelet packet Multi-scale Information Entropy and Hidden Markov Model (HMM) was put forward. First of all, the collected conductance fluctuation signals were decomposed into eight different frequency bands signals. Secondly, the wavelet packet multi-scale information entropy of different frequency bands signals were regarded as the input characteristic vectors of all states HMM which had been trained. In the end the regime identification of' the gas-liquid two-phase flow could be performed. The study showed that the method that HMM was applied to identify the flow regime was superior to the one that BP neural network was used, and the results proved that the method was efficient and feasible. (authors)

  20. A Comprehensive Database and Analysis Framework To Incorporate Multiscale Data Types and Enable Integrated Analysis of Bioactive Polyphenols.

    Science.gov (United States)

    Ho, Lap; Cheng, Haoxiang; Wang, Jun; Simon, James E; Wu, Qingli; Zhao, Danyue; Carry, Eileen; Ferruzzi, Mario G; Faith, Jeremiah; Valcarcel, Breanna; Hao, Ke; Pasinetti, Giulio M

    2018-03-05

    The development of a given botanical preparation for eventual clinical application requires extensive, detailed characterizations of the chemical composition, as well as the biological availability, biological activity, and safety profiles of the botanical. These issues are typically addressed using diverse experimental protocols and model systems. Based on this consideration, in this study we established a comprehensive database and analysis framework for the collection, collation, and integrative analysis of diverse, multiscale data sets. Using this framework, we conducted an integrative analysis of heterogeneous data from in vivo and in vitro investigation of a complex bioactive dietary polyphenol-rich preparation (BDPP) and built an integrated network linking data sets generated from this multitude of diverse experimental paradigms. We established a comprehensive database and analysis framework as well as a systematic and logical means to catalogue and collate the diverse array of information gathered, which is securely stored and added to in a standardized manner to enable fast query. We demonstrated the utility of the database in (1) a statistical ranking scheme to prioritize response to treatments and (2) in depth reconstruction of functionality studies. By examination of these data sets, the system allows analytical querying of heterogeneous data and the access of information related to interactions, mechanism of actions, functions, etc., which ultimately provide a global overview of complex biological responses. Collectively, we present an integrative analysis framework that leads to novel insights on the biological activities of a complex botanical such as BDPP that is based on data-driven characterizations of interactions between BDPP-derived phenolic metabolites and their mechanisms of action, as well as synergism and/or potential cancellation of biological functions. Out integrative analytical approach provides novel means for a systematic integrative

  1. A service-oriented distributed semantic mediator: integrating multiscale biomedical information.

    Science.gov (United States)

    Mora, Oscar; Engelbrecht, Gerhard; Bisbal, Jesus

    2012-11-01

    Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.

  2. Integrating multiscale polar active contours and region growing for microcalcifications segmentation in mammography

    International Nuclear Information System (INIS)

    Arikidis, N S; Karahaliou, A; Skiadopoulos, S; Panagiotakis, G; Costaridou, L; Likaki, E

    2009-01-01

    Morphology of individual microcalcifications is an important clinical factor in microcalcification clusters diagnosis. Accurate segmentation remains a difficult task due to microcalcifications small size, low contrast, fuzzy nature and low distinguishability from surrounding tissue. A novel application of active rays (polar transformed active contours) on B-spline wavelet representation is employed, to provide initial estimates of microcalcification boundary. Then, a region growing method is used with pixel aggregation constrained by the microcalcification boundary estimates, to obtain the final microcalcification boundary. The method was tested on dataset of 49 microcalcification clusters (30 benign, 19 malignant), originating from the DDSM database. An observer study was conducted to evaluate segmentation accuracy of the proposed method, on a 5-point rating scale (from 5:excellent to 1:very poor). The average accuracy rating was 3.98±0.81 when multiscale active rays were combined to region growing and 2.93±0.92 when combined to linear polynomial fitting, while the difference in rating of segmentation accuracy was statistically significant (p < 0.05).

  3. Integrating multi-scale data to create a virtual physiological mouse heart.

    Science.gov (United States)

    Land, Sander; Niederer, Steven A; Louch, William E; Sejersted, Ole M; Smith, Nicolas P

    2013-04-06

    While the virtual physiological human (VPH) project has made great advances in human modelling, many of the tools and insights developed as part of this initiative are also applicable for facilitating mechanistic understanding of the physiology of a range of other species. This process, in turn, has the potential to provide human relevant insights via a different scientific path. Specifically, the increasing use of mice in experimental research, not yet fully complemented by a similar increase in computational modelling, is currently missing an important opportunity for using and interpreting this growing body of experimental data to improve our understanding of cardiac function. This overview describes our work to address this issue by creating a virtual physiological mouse model of the heart. We describe the similarities between human- and mouse-focused modelling, including the reuse of VPH tools, and the development of methods for investigating parameter sensitivity that are applicable across species. We show how previous results using this approach have already provided important biological insights, and how these can also be used to advance VPH heart models. Finally, we show an example application of this approach to test competing multi-scale hypotheses by investigating variations in length-dependent properties of cardiac muscle.

  4. Identifying influential factors on integrated marketing planning using information technology

    Directory of Open Access Journals (Sweden)

    Karim Hamdi

    2014-07-01

    Full Text Available This paper presents an empirical investigation to identify important factors influencing integrated marketing planning using information technology. The proposed study designs a questionnaire for measuring integrated marketing planning, which consists of three categories of structural factors, behavioral factors and background factors. There are 40 questions associated with the proposed study in Likert scale. Cronbach alphas have been calculated for structural factors, behavioral factors and background factors as 0.89, 0.86 and 0.83, respectively. Using some statistical test, the study has confirmed the effects of three factors on integrated marketing. In addition, the implementation of Freedman test has revealed that structural factors were the most important factor followed by background factors and behavioral factors.

  5. Integrative biology approach identifies cytokine targeting strategies for psoriasis.

    Science.gov (United States)

    Perera, Gayathri K; Ainali, Chrysanthi; Semenova, Ekaterina; Hundhausen, Christian; Barinaga, Guillermo; Kassen, Deepika; Williams, Andrew E; Mirza, Muddassar M; Balazs, Mercedesz; Wang, Xiaoting; Rodriguez, Robert Sanchez; Alendar, Andrej; Barker, Jonathan; Tsoka, Sophia; Ouyang, Wenjun; Nestle, Frank O

    2014-02-12

    Cytokines are critical checkpoints of inflammation. The treatment of human autoimmune disease has been revolutionized by targeting inflammatory cytokines as key drivers of disease pathogenesis. Despite this, there exist numerous pitfalls when translating preclinical data into the clinic. We developed an integrative biology approach combining human disease transcriptome data sets with clinically relevant in vivo models in an attempt to bridge this translational gap. We chose interleukin-22 (IL-22) as a model cytokine because of its potentially important proinflammatory role in epithelial tissues. Injection of IL-22 into normal human skin grafts produced marked inflammatory skin changes resembling human psoriasis. Injection of anti-IL-22 monoclonal antibody in a human xenotransplant model of psoriasis, developed specifically to test potential therapeutic candidates, efficiently blocked skin inflammation. Bioinformatic analysis integrating both the IL-22 and anti-IL-22 cytokine transcriptomes and mapping them onto a psoriasis disease gene coexpression network identified key cytokine-dependent hub genes. Using knockout mice and small-molecule blockade, we show that one of these hub genes, the so far unexplored serine/threonine kinase PIM1, is a critical checkpoint for human skin inflammation and potential future therapeutic target in psoriasis. Using in silico integration of human data sets and biological models, we were able to identify a new target in the treatment of psoriasis.

  6. Revisiting drought impact on tropical forest photosynthesis: a novel multi-scale integrated approach reveals new insights

    Science.gov (United States)

    Detto, M.; Wu, J.; Xu, X.; Serbin, S.; Rogers, A.

    2017-12-01

    A fundamental unanswered question for global change ecology is to determine the vulnerability of tropical forests to climate change, particularly with increasing intensity and frequency of drought events. This question, despite its apparent simplicity, remains difficult for earth system models to answer, and is controversial in remote sensing literature. Here, we leverage unique multi-scale remote sensing measurements (from leaf to crown) in conjunction with four-continuous-year (2013-2017) eddy covariance measurements of ecosystem carbon fluxes in a tropical forest in Panama to revisit this question. We hypothesize that drought impacts tropical forest photosynthesis through variation in abiotic drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with physiological traits that govern photosynthesis, and biotic variation in ecosystem photosynthetic capacity associated with changes in the traits themselves. Our study site, located in a seasonal tropical forest on Barro Colorado Island (BCI), Panama, experienced a significant drought in 2015. Local eddy covariance derived photosynthesis shows an abrupt increase during the drought year. Our specific goal here is to assess the relative impact of abiotic and biotic drivers of such photosynthesis response to interannual drought. To this goal, we derived abiotic drivers from eddy tower-based meteorological measurements. We will derive the biotic drivers using a recently developed leaf demography-ontogeny model, where ecosystem photosynthetic capacity can be described as the product of field measured, age-dependent leaf photosynthetic capacity and local tower-camera derived ecosystem-scale inter-annual variability in leaf age demography of the same time period (2013-2017). Lastly, we will use a process-based model to assess the separate and joint effects of abiotic and biotic drivers on eddy covariance derive photosynthetic interannual variability. Collectively, this novel multi-scale

  7. A computational systems biology software platform for multiscale modeling and simulation: Integrating whole-body physiology, disease biology, and molecular reaction networks

    Directory of Open Access Journals (Sweden)

    Thomas eEissing

    2011-02-01

    Full Text Available Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multi-scale by nature, project work and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug-drug or drug-metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach.

  8. Distributed multiscale computing

    NARCIS (Netherlands)

    Borgdorff, J.

    2014-01-01

    Multiscale models combine knowledge, data, and hypotheses from different scales. Simulating a multiscale model often requires extensive computation. This thesis evaluates distributing these computations, an approach termed distributed multiscale computing (DMC). First, the process of multiscale

  9. pySecDec: A toolbox for the numerical evaluation of multi-scale integrals

    Science.gov (United States)

    Borowka, S.; Heinrich, G.; Jahn, S.; Jones, S. P.; Kerner, M.; Schlenk, J.; Zirke, T.

    2018-01-01

    We present pySECDEC, a new version of the program SECDEC, which performs the factorization of dimensionally regulated poles in parametric integrals, and the subsequent numerical evaluation of the finite coefficients. The algebraic part of the program is now written in the form of python modules, which allow a very flexible usage. The optimization of the C++ code, generated using FORM, is improved, leading to a faster numerical convergence. The new version also creates a library of the integrand functions, such that it can be linked to user-specific codes for the evaluation of matrix elements in a way similar to analytic integral libraries.

  10. Multiscale N=2 SUSY field theories, integrable systems and their stringy/brane origin

    International Nuclear Information System (INIS)

    Gorsky, A.; Gukov, S.; Mironov, A.

    1998-01-01

    We discuss supersymmetric Yang-Mills theories with multiple scales in the brane language. The issue concerns N=2 SUSY gauge theories with massive fundamental matter including the UV finite case of n f =2n c , theories involving products of SU(n) gauge groups with bifundamental matter, and systems with several parameters similar to Λ QCD . We argue that the proper integrable systems are, accordingly, twisted XXX SL(2) spin chain, SL(p) magnets and degenerations of the spin Calogero system. The issue of symmetries underlying integrable systems is addressed. Relations with the monopole systems are specially discussed. Brane pictures behind all these integrable structures in the IIB and M-theory are suggested. We argue that degrees of freedom in integrable systems are related to KK excitations in M-theory or D-particles in the IIA string theory, which substitute the infinite number of instantons in the field theory. This implies the presence of more BPS states in the low-energy sector. (orig.)

  11. INTEGRATED IMAGING APPROACHES SUPPORTING THE EXCAVATION ACTIVITIES. MULTI-SCALE GEOSPATIAL DOCUMENTATION IN HIERAPOLIS (TK

    Directory of Open Access Journals (Sweden)

    A. Spanò

    2018-05-01

    Full Text Available The paper focuses on the exploration of the suitability and the discretization of applicability issues about advanced surveying integrated techniques, mainly based on image-based approaches compared and integrated to range-based ones that have been developed with the use of the cutting-edge solutions tested on field. The investigated techniques integrate both technological devices for 3D data acquisition and thus editing and management systems to handle metric models and multi-dimensional data in a geospatial perspective, in order to innovate and speed up the extraction of information during the archaeological excavation activities. These factors, have been experienced in the outstanding site of the Hierapolis of Phrygia ancient city (Turkey, downstream the 2017 surveying missions, in order to produce high-scale metric deliverables in terms of high-detailed Digital Surface Models (DSM, 3D continuous surface models and high-resolution orthoimages products. In particular, the potentialities in the use of UAV platforms for low altitude acquisitions in aerial photogrammetric approach, together with terrestrial panoramic acquisitions (Trimble V10 imaging rover, have been investigated with a comparison toward consolidated Terrestrial Laser Scanning (TLS measurements. One of the main purposes of the paper is to evaluate the results offered by the technologies used independently and using integrated approaches. A section of the study in fact, is specifically dedicated to experimenting the union of different sensor dense clouds: both dense clouds derived from UAV have been integrated with terrestrial Lidar clouds, to evaluate their fusion. Different test cases have been considered, representing typical situations that can be encountered in archaeological sites.

  12. Understanding Greenland ice sheet hydrology using an integrated multi-scale approach

    International Nuclear Information System (INIS)

    Rennermalm, A K; Moustafa, S E; Mioduszewski, J; Robinson, D A; Chu, V W; Smith, L C; Forster, R R; Hagedorn, B; Harper, J T; Mote, T L; Shuman, C A; Tedesco, M

    2013-01-01

    Improved understanding of Greenland ice sheet hydrology is critically important for assessing its impact on current and future ice sheet dynamics and global sea level rise. This has motivated the collection and integration of in situ observations, model development, and remote sensing efforts to quantify meltwater production, as well as its phase changes, transport, and export. Particularly urgent is a better understanding of albedo feedbacks leading to enhanced surface melt, potential positive feedbacks between ice sheet hydrology and dynamics, and meltwater retention in firn. These processes are not isolated, but must be understood as part of a continuum of processes within an integrated system. This letter describes a systems approach to the study of Greenland ice sheet hydrology, emphasizing component interconnections and feedbacks, and highlighting research and observational needs. (letter)

  13. Identifying candidate driver genes by integrative ovarian cancer genomics data

    Science.gov (United States)

    Lu, Xinguo; Lu, Jibo

    2017-08-01

    Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

  14. Integrating mean and variance heterogeneities to identify differentially expressed genes.

    Science.gov (United States)

    Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

    2016-12-06

    In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

  15. Mechanical integrity of a carbon nanotube/copper-based through-silicon via for 3D integrated circuits: a multi-scale modeling approach.

    Science.gov (United States)

    Awad, Ibrahim; Ladani, Leila

    2015-12-04

    Carbon nanotube (CNT)/copper (Cu) composite material is proposed to replace Cu-based through-silicon vias (TSVs) in micro-electronic packages. The proposed material is believed to offer extraordinary mechanical and electrical properties and the presence of CNTs in Cu is believed to overcome issues associated with miniaturization of Cu interconnects, such as electromigration. This study introduces a multi-scale modeling of the proposed TSV in order to evaluate its mechanical integrity under mechanical and thermo-mechanical loading conditions. Molecular dynamics (MD) simulation was used to determine CNT/Cu interface adhesion properties. A cohesive zone model (CZM) was found to be most appropriate to model the interface adhesion, and CZM parameters at the nanoscale were determined using MD simulation. CZM parameters were then used in the finite element analysis in order to understand the mechanical and thermo-mechanical behavior of composite TSV at micro-scale. From the results, CNT/Cu separation does not take place prior to plastic deformation of Cu in bending, and separation does not take place when standard thermal cycling is applied. Further investigation is recommended in order to alleviate the increased plastic deformation in Cu at the CNT/Cu interface in both loading conditions.

  16. Using a multi-scale approach to identify and quantify oil and gas emissions: a case study for GHG emissions verification

    Science.gov (United States)

    Sweeney, C.; Kort, E. A.; Rella, C.; Conley, S. A.; Karion, A.; Lauvaux, T.; Frankenberg, C.

    2015-12-01

    Along with a boom in oil and natural gas production in the US, there has been a substantial effort to understand the true environmental impact of these operations on air and water quality, as well asnet radiation balance. This multi-institution effort funded by both governmental and non-governmental agencies has provided a case study for identification and verification of emissions using a multi-scale, top-down approach. This approach leverages a combination of remote sensing to identify areas that need specific focus and airborne in-situ measurements to quantify both regional and large- to mid-size single-point emitters. Ground-based networks of mobile and stationary measurements provide the bottom tier of measurements from which process-level information can be gathered to better understand the specific sources and temporal distribution of the emitters. The motivation for this type of approach is largely driven by recent work in the Barnett Shale region in Texas as well as the San Juan Basin in New Mexico and Colorado; these studies suggest that relatively few single-point emitters dominate the regional emissions of CH4.

  17. Integrating landscape analysis and planning: a multi-scale approach for oriented management of tourist recreation.

    Science.gov (United States)

    de Aranzabal, Itziar; Schmitz, María F; Pineda, Francisco D

    2009-11-01

    Tourism and landscape are interdependent concepts. Nature- and culture-based tourism are now quite well developed activities and can constitute an excellent way of exploiting the natural resources of certain areas, and should therefore be considered as key objectives in landscape planning and management in a growing number of countries. All of this calls for careful evaluation of the effects of tourism on the territory. This article focuses on an integrated spatial method for landscape analysis aimed at quantifying the relationship between preferences of visitors and landscape features. The spatial expression of the model relating types of leisure and recreational preferences to the potential capacity of the landscape to meet them involves a set of maps showing degrees of potential visitor satisfaction. The method constitutes a useful tool for the design of tourism planning and management strategies, with landscape conservation as a reference.

  18. The integration of novel diagnostics techniques for multi-scale monitoring of large civil infrastructures

    Directory of Open Access Journals (Sweden)

    F. Soldovieri

    2008-11-01

    Full Text Available In the recent years, structural monitoring of large infrastructures (buildings, dams, bridges or more generally man-made structures has raised an increased attention due to the growing interest about safety and security issues and risk assessment through early detection. In this framework, aim of the paper is to introduce a new integrated approach which combines two sensing techniques acting on different spatial and temporal scales. The first one is a distributed optic fiber sensor based on the Brillouin scattering phenomenon, which allows a spatially and temporally continuous monitoring of the structure with a "low" spatial resolution (meter. The second technique is based on the use of Ground Penetrating Radar (GPR, which can provide detailed images of the inner status of the structure (with a spatial resolution less then tens centimetres, but does not allow a temporal continuous monitoring. The paper describes the features of these two techniques and provides experimental results concerning preliminary test cases.

  19. Integrating Landscape Analysis and Planning: A Multi-Scale Approach for Oriented Management of Tourist Recreation

    Science.gov (United States)

    de Aranzabal, Itziar; Schmitz, María F.; Pineda, Francisco D.

    2009-11-01

    Tourism and landscape are interdependent concepts. Nature- and culture-based tourism are now quite well developed activities and can constitute an excellent way of exploiting the natural resources of certain areas, and should therefore be considered as key objectives in landscape planning and management in a growing number of countries. All of this calls for careful evaluation of the effects of tourism on the territory. This article focuses on an integrated spatial method for landscape analysis aimed at quantifying the relationship between preferences of visitors and landscape features. The spatial expression of the model relating types of leisure and recreational preferences to the potential capacity of the landscape to meet them involves a set of maps showing degrees of potential visitor satisfaction. The method constitutes a useful tool for the design of tourism planning and management strategies, with landscape conservation as a reference.

  20. Impact of model complexity and multi-scale data integration on the estimation of hydrogeological parameters in a dual-porosity aquifer

    Science.gov (United States)

    Tamayo-Mas, Elena; Bianchi, Marco; Mansour, Majdi

    2018-03-01

    This study investigates the impact of model complexity and multi-scale prior hydrogeological data on the interpretation of pumping test data in a dual-porosity aquifer (the Chalk aquifer in England, UK). In order to characterize the hydrogeological properties, different approaches ranging from a traditional analytical solution (Theis approach) to more sophisticated numerical models with automatically calibrated input parameters are applied. Comparisons of results from the different approaches show that neither traditional analytical solutions nor a numerical model assuming a homogenous and isotropic aquifer can adequately explain the observed drawdowns. A better reproduction of the observed drawdowns in all seven monitoring locations is instead achieved when medium and local-scale prior information about the vertical hydraulic conductivity (K) distribution is used to constrain the model calibration process. In particular, the integration of medium-scale vertical K variations based on flowmeter measurements lead to an improvement in the goodness-of-fit of the simulated drawdowns of about 30%. Further improvements (up to 70%) were observed when a simple upscaling approach was used to integrate small-scale K data to constrain the automatic calibration process of the numerical model. Although the analysis focuses on a specific case study, these results provide insights about the representativeness of the estimates of hydrogeological properties based on different interpretations of pumping test data, and promote the integration of multi-scale data for the characterization of heterogeneous aquifers in complex hydrogeological settings.

  1. Emerging Technologies for Integrating Multi-Scale Observations of the Hydrologic Cycle

    Science.gov (United States)

    Logan, W. S.; Potter, K. W.; Wood, E. F.

    2007-12-01

    The results are presented of a recent National Research Council study on examining the potential for integrating spaceborne observations with complementary airborne and ground-based observations to gain holistic understanding of hydrologic and related biogeochemical and ecological processes and to help support water and related land-resource management. The study was motivated by the interrelated challenges of population growth, global climate change, and regional changes in land use and land management that will increasingly stress water resources around the world. Meeting these challenges will require significant improvement in our management of water resources, which in turn will require improvements in our capacity to understand and quantify the hydrologic cycle and its interactions with the natural and built environment. Recent and potential future technological innovations in sensors (in-situ, airborne, and space-borne) and sensor networks, cyber-infrastructure, data assimilation, modeling, and decision-support tools offer unprecedented opportunities to improve our capacity to observe, understand, and manage hydrologic systems. The committee investigated a number of aspects to turning this potential into a reality. These included development and field deployment of land-based chemical and biological sensors; the role of airborne remote sensing; interagency gaps between the steps of sensor development, demonstration, and operational deployment; the coordination of federal responsibilities for measurement, monitoring and modeling; and getting the new information to those who can use it. A variety of case studies were used to illustrate the needs and opportunities for new measurement capacity, including hydrologic monitoring in the Everglades, water quantity and quality in the Southern High Plains, malaria in Sub-Saharan Africa, hydroclimatic research in the Arctic, hydrologic extremes and water quality in the Neuse River watershed, and mountain hydrology in the

  2. Multiscale Retinex

    Directory of Open Access Journals (Sweden)

    Ana Belén Petro

    2014-04-01

    Full Text Available While the retinex theory aimed at explaining human color perception, its derivations have led to efficient algorithms enhancing local image contrast, thus permitting among other features, to "see in the shadows". Among these derived algorithms, Multiscale Retinex is probably the most successful center-surround image filter. In this paper, we offer an analysis and implementation of Multiscale Retinex. We point out and resolve some ambiguities of the method. In particular, we show that the important color correction final step of the method can be seriously improved. This analysis permits to come up with an automatic implementation of Multiscale Retinex which is as faithful as possible to the one described in the original paper. Overall, this implementation delivers excellent results and confirms the validity of Multiscale Retinex for image color restoration and contrast enhancement. Nevertheless, while the method parameters can be fixed, we show that a crucial choice must be left to the user, depending on the lightning condition of the image: the method must either be applied to each color independently if a color balance is required, or to the luminance only if the goal is to achieve local contrast enhancement. Thus, we propose two slightly different algorithms to deal with both cases.

  3. New integrated and multiscale decision-aiding framework in a context of imperfect information: application to the assessment of torrent checkdams' effectiveness.

    Science.gov (United States)

    Tacnet, Jean-Marc; Carladous, Simon; Dezert, Jean; Batton-Hubert, Mireille

    2017-04-01

    Mountain natural phenomena (e.g. torrential floods) put people and buildings at risk. Civil engineering protection works such as torrent check-dams are designed to mitigate those natural risks. Protection works act on both causes and effects of phenomena to reduce consequences and therefore risks. For instance, check-dams control sediment production and liquid/solid flow of torrential floods: several series of dams are located in the headwaters of a watershed, each having specific functions. All those works are damaged by time passing and flood impacts. Effectiveness assessment is needed to define, compare or choose strategies for investment and maintenance which are essential issues in risk management process. Decision support tools are expected to analyze at different scales both their technical effectiveness (related to their structural state and functional effects on phenomena such as stopping, braking, guiding, etc.) and their economic efficiency through comparison between benefits and costs. Several methods, often based on expert knowledge, have already been developed to care about decision under risk. But uncertainty has also to be considered, since decisions are indeed often taken in a context of lack of information and knowledge on natural phenomena, heterogeneity of available information and, finally, reliability of sources. First methods derived from classical industrial contexts, such as dependability analysis, are used to formalize expert knowledge used for decision-making. After having defined the concept of effectiveness, dependability analysis are used to identify decision contexts and problems: criteria and indicators are identified in relation with structural or functional features. Then, innovative and multi-scales multi-criteria decision-making methods (MCDMs) and frameworks are proposed to help assessing protection works effectiveness. They combine classical MCDM approaches, belief function, fuzzy sets and possibility theories. Those methods

  4. Identifying Opportunities for Vertical Integration of Biochemistry and Clinical Medicine.

    Science.gov (United States)

    Wendelberger, Karen J.; Burke, Rebecca; Haas, Arthur L.; Harenwattananon, Marisa; Simpson, Deborah

    1998-01-01

    Objectives: Retention of basic science knowledge, as judged by National Board of Medical Examiners' (NBME) data, suffers due to lack of apparent relevance and isolation of instruction from clinical application, especially in biochemistry. However, the literature reveals no systematic process for identifying key biochemical concepts and associated clinical conditions. This study systematically identified difficult biochemical concepts and their common clinical conditions as a critical step towards enhancing relevance and retention of biochemistry.Methods: A multi-step/ multiple stakeholder process was used to: (1) identify important biochemistry concepts; (2) determine students' perceptions of concept difficulty; (3) assess biochemistry faculty, student, and clinical teaching scholars' perceived relevance of identified concepts; and (4) identify associated common clinical conditions for relevant and difficult concepts. Surveys and a modified Delphi process were used to gather data, subsequently analyzed using SPSS for Windows.Results: Sixteen key biochemical concepts were identified. Second year medical students rated 14/16 concepts as extremely difficult while fourth year students rated nine concepts as moderately to extremely difficult. On average, each teaching scholar generated common clinical conditions for 6.2 of the 16 concepts, yielding a set of seven critical concepts and associated clinical conditions.Conclusions: Key stakeholders in the instructional process struggle to identify biochemistry concepts that are critical, difficult to learn and associated with common clinical conditions. However, through a systematic process beginning with identification of concepts and associated clinical conditions, relevance of basic science instruction can be enhanced.

  5. Integrating bioenergy into a green economy: identifying opportunities and constraints

    CSIR Research Space (South Africa)

    Von Maltitz, Graham P

    2012-10-01

    Full Text Available .kashan.co.za] BACKGROUND Bioenergy is a renewable energy option that has the potential to contribute to a low-carbon development path and stimulate a green economy. However, since bioenergy uses land and natural resources, it is in competition with the valuable bio... an analytical framework and decision-support tools to assist in assessing, managing and monitoring the sustainability of bioenergy. IMPROVING THE SUSTAINABILITY OF BIOENERGY THROUGH INTEGRATION WITH OTHER BIO-BASED PRODUCTS Since bioenergy production...

  6. Integration of curated databases to identify genotype-phenotype associations

    Directory of Open Access Journals (Sweden)

    Li Jianrong

    2006-10-01

    Full Text Available Abstract Background The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism's phenotype based on the molecules encoded by its genome. However, the link between molecular composition (i.e. genotype and phenotype for microbes is not obvious. While there have been several studies that address this challenge, none have yet proposed a large-scale method integrating curated biological information. Here we utilize a systematic approach to discover genotype-phenotype associations that combines phenotypic information from a biomedical informatics database, GIDEON, with the molecular information contained in National Center for Biotechnology Information's Clusters of Orthologous Groups database (NCBI COGs. Results Integrating the information in the two databases, we are able to correlate the presence or absence of a given protein in a microbe with its phenotype as measured by certain morphological characteristics or survival in a particular growth media. With a 0.8 correlation score threshold, 66% of the associations found were confirmed by the literature and at a 0.9 correlation threshold, 86% were positively verified. Conclusion Our results suggest possible phenotypic manifestations for proteins biochemically associated with sugar metabolism and electron transport. Moreover, we believe our approach can be extended to linking pathogenic phenotypes with functionally related proteins.

  7. Identifying multiple submissions in Internet research: preserving data integrity.

    Science.gov (United States)

    Bowen, Anne M; Daniel, Candice M; Williams, Mark L; Baird, Grayson L

    2008-11-01

    Internet-based sexuality research with hidden populations has become increasingly popular. Respondent anonymity may encourage participation and lower social desirability, but associated disinhibition may promote multiple submissions, especially when incentives are offered. The goal of this study was to identify the usefulness of different variables for detecting multiple submissions from repeat responders and to explore incentive effects. The data included 1,900 submissions from a three-session Internet intervention with a pretest and three post-test questionnaires. Participants were men who have sex with men and incentives were offered to rural participants for completing each questionnaire. The final number of submissions included 1,273 "unique", 132 first submissions by "repeat responders" and 495 additional submissions by the "repeat responders" (N = 1,900). Four categories of repeat responders were identified: "infrequent" (2-5 submissions), "persistent" (6-10 submissions), "very persistent" (11-30 submissions), and "hackers" (more than 30 submissions). Internet Provider (IP) addresses, user names, and passwords were the most useful for identifying "infrequent" repeat responders. "Hackers" often varied their IP address and identifying information to prevent easy identification, but investigating the data for small variations in IP, using reverse telephone look up, and patterns across usernames and passwords were helpful. Incentives appeared to play a role in stimulating multiple submissions, especially from the more sophisticated "hackers". Finally, the web is ever evolving and it will be necessary to have good programmers and staff who evolve as fast as "hackers".

  8. An Integrative, Multi-Scale Computational Model of a Swimming Lamprey Fully Coupled to Its Fluid Environment and Incorporating Proprioceptive Feedback

    Science.gov (United States)

    Hamlet, C. L.; Hoffman, K.; Fauci, L.; Tytell, E.

    2016-02-01

    The lamprey is a model organism for both neurophysiology and locomotion studies. To study the role of sensory feedback as an organism moves through its environment, a 2D, integrative, multi-scale model of an anguilliform swimmer driven by neural activation from a central pattern generator (CPG) is constructed. The CPG in turn drives muscle kinematics and is fully coupled to the surrounding fluid. The system is numerically evolved in time using an immersed boundary framework producing an emergent swimming mode. Proprioceptive feedback to the CPG based on experimental observations adjust the activation signal as the organism interacts with its environment. Effects on the speed, stability and cost (metabolic work) of swimming due to nonlinear dependencies associated with muscle force development combined with proprioceptive feedback to neural activation are estimated and examined.

  9. Collaborating for Multi-Scale Chemical Science

    Energy Technology Data Exchange (ETDEWEB)

    William H. Green

    2006-07-14

    Advanced model reduction methods were developed and integrated into the CMCS multiscale chemical science simulation software. The new technologies were used to simulate HCCI engines and burner flames with exceptional fidelity.

  10. The Adaptive Multi-scale Simulation Infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Tobin, William R. [Rensselaer Polytechnic Inst., Troy, NY (United States)

    2015-09-01

    The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.

  11. Development of an integrated generic model for multi-scale assessment of the impacts of agro-ecosystems on major ecosystem services in West Africa.

    Science.gov (United States)

    Belem, Mahamadou; Saqalli, Mehdi

    2017-11-01

    This paper presents an integrated model assessing the impacts of climate change, agro-ecosystem and demographic transition patterns on major ecosystem services in West-Africa along a partial overview of economic aspects (poverty reduction, food self-sufficiency and income generation). The model is based on an agent-based model associated with a soil model and multi-scale spatial model. The resulting Model for West-Africa Agro-Ecosystem Integrated Assessment (MOWASIA) is ecologically generic, meaning it is designed for all sudano-sahelian environments but may then be used as an experimentation facility for testing different scenarios combining ecological and socioeconomic dimensions. A case study in Burkina Faso is examined to assess the environmental and economic performances of semi-continuous and continuous farming systems. Results show that the semi-continuous system using organic fertilizer and fallowing practices contribute better to environment preservation and food security than the more economically performant continuous system. In addition, this study showed that farmers heterogeneity could play an important role in agricultural policies planning and assessment. In addition, the results showed that MOWASIA is an effective tool for designing, analysing the impacts of agro-ecosystems. Copyright © 2017. Published by Elsevier Ltd.

  12. Multiscale Modeling of the Early CD8 T-Cell Immune Response in Lymph Nodes: An Integrative Study

    Directory of Open Access Journals (Sweden)

    Sotiris A. Prokopiou

    2014-09-01

    Full Text Available CD8 T-cells are critical  in controlling infection by intracellular  pathogens. Upon encountering antigen presenting cells, T-cell receptor activation promotes the differentiation of naïve CD8 T-cells into strongly proliferating  activated and effector stages. We propose a 2D-multiscale computational model to study the maturation of CD8 T-cells in a lymph node controlled by their molecular profile. A novel molecular pathway is presented and converted into an ordinary differential  equation model, coupled with a cellular Potts model to describe cell-cell interactions. Key molecular  players such as activated IL2 receptor and Tbet levels  control the differentiation  from naïve into activated and effector stages, respectively,  while caspases and Fas-Fas ligand interactions control cell apoptosis.  Coupling  this molecular model to the cellular scale successfully  reproduces  qualitatively the evolution of total CD8 T-cell counts observed in mice lymph node, between Day 3 and 5.5 post-infection. Furthermore, this model allows us to make testable predictions  of the evolution of the different CD8 T-cell stages.

  13. A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

    Science.gov (United States)

    Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

    2014-01-01

    Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

  14. Classification of Urban Feature from Unmanned Aerial Vehicle Images Using Gasvm Integration and Multi-Scale Segmentation

    Science.gov (United States)

    Modiri, M.; Salehabadi, A.; Mohebbi, M.; Hashemi, A. M.; Masumi, M.

    2015-12-01

    The use of UAV in the application of photogrammetry to obtain cover images and achieve the main objectives of the photogrammetric mapping has been a boom in the region. The images taken from REGGIOLO region in the province of, Italy Reggio -Emilia by UAV with non-metric camera Canon Ixus and with an average height of 139.42 meters were used to classify urban feature. Using the software provided SURE and cover images of the study area, to produce dense point cloud, DSM and Artvqvtv spatial resolution of 10 cm was prepared. DTM area using Adaptive TIN filtering algorithm was developed. NDSM area was prepared with using the difference between DSM and DTM and a separate features in the image stack. In order to extract features, using simultaneous occurrence matrix features mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation for each of the RGB band image was used Orthophoto area. Classes used to classify urban problems, including buildings, trees and tall vegetation, grass and vegetation short, paved road and is impervious surfaces. Class consists of impervious surfaces such as pavement conditions, the cement, the car, the roof is stored. In order to pixel-based classification and selection of optimal features of classification was GASVM pixel basis. In order to achieve the classification results with higher accuracy and spectral composition informations, texture, and shape conceptual image featureOrthophoto area was fencing. The segmentation of multi-scale segmentation method was used.it belonged class. Search results using the proposed classification of urban feature, suggests the suitability of this method of classification complications UAV is a city using images. The overall accuracy and kappa coefficient method proposed in this study, respectively, 47/93% and 84/91% was.

  15. f-divergence cutoff index to simultaneously identify differential expression in the integrated transcriptome and proteome

    OpenAIRE

    Tang, Shaojun; Hemberg, Martin; Cansizoglu, Ertugrul; Belin, Stephane; Kosik, Kenneth; Kreiman, Gabriel; Steen, Hanno; Steen, Judith

    2016-01-01

    The ability to integrate 'omics' (i.e., transcriptomics and proteomics) is becoming increasingly important to the understanding of regulatory mechanisms. There are currently no tools available to identify differentially expressed genes (DEGs)across different 'omics'data types or multi-dimensional data including time courses. We present a model capable of simultaneously identifying DEGs from continuous and discrete transcriptomic, proteomic and integrated proteogenomic data. We show that...

  16. Multifunctional multiscale composites: Processing, modeling and characterization

    Science.gov (United States)

    Qiu, Jingjing

    Carbon nanotubes (CNTs) demonstrate extraordinary properties and show great promise in enhancing out-of-plane properties of traditional polymer/fiber composites and enabling functionality. However, current manufacturing challenges hinder the realization of their potential. In the dissertation research, both experimental and computational efforts have been conducted to investigate effective manufacturing techniques of CNT integrated multiscale composites. The fabricated composites demonstrated significant improvements in physical properties, such as tensile strength, tensile modulus, inter-laminar shear strength, thermal dimension stability and electrical conductivity. Such multiscale composites were truly multifunctional with the addition of CNTs. Furthermore, a novel hierarchical multiscale modeling method was developed in this research. Molecular dynamic (MD) simulation offered reasonable explanation of CNTs dispersion and their motion in polymer solution. Bi-mode finite-extensible-nonlinear-elastic (FENE) dumbbell simulation was used to analyze the influence of CNT length distribution on the stress tensor and shear-rate-dependent viscosity. Based on the simulated viscosity profile and empirical equations from experiments, a macroscale flow simulation model on the finite element method (FEM) method was developed and validated to predict resin flow behavior in the processing of CNT-enhanced multiscale composites. The proposed multiscale modeling method provided a comprehensive understanding of micro/nano flow in both atomistic details and mesoscale. The simulation model can be used to optimize process design and control of the mold-filling process in multiscale composite manufacturing. This research provided systematic investigations into the CNT-based multiscale composites. The results from this study may be used to leverage the benefits of CNTs and open up new application opportunities for high-performance multifunctional multiscale composites. Keywords. Carbon

  17. Multiscale phase inversion of seismic marine data

    KAUST Repository

    Fu, Lei

    2017-08-17

    We test the feasibility of applying multiscale phase inversion (MPI) to seismic marine data. To avoid cycle-skipping, the multiscale strategy temporally integrates the traces several times, i.e. high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, higher frequencies in the data are boosted by using integrated traces of lower order as the input data. Results with synthetic data and field data from the Gulf of Mexico produce robust and accurate results if the model does not contain strong velocity contrasts such as salt-sediment interfaces.

  18. Integrated Healthcare Delivery: A Qualitative Research Approach to Identifying and Harmonizing Perspectives of Integrated Neglected Tropical Disease Programs.

    Directory of Open Access Journals (Sweden)

    Arianna Rubin Means

    2016-10-01

    Full Text Available While some evidence supports the beneficial effects of integrating neglected tropical disease (NTD programs to optimize coverage and reduce costs, there is minimal information regarding when or how to effectively operationalize program integration. The lack of systematic analyses of integration experiences and of integration processes may act as an impediment to achieving more effective NTD programming. We aimed to learn about the experiences of NTD stakeholders and their perceptions of integration.We evaluated differences in the definitions, roles, perceived effectiveness, and implementation experiences of integrated NTD programs among a variety of NTD stakeholder groups, including multilateral organizations, funding partners, implementation partners, national Ministry of Health (MOH teams, district MOH teams, volunteer rural health workers, and community members participating in NTD campaigns. Semi-structured key informant interviews were conducted. Coding of themes involved a mix of applying in-vivo open coding and a priori thematic coding from a start list.In total, 41 interviews were conducted. Salient themes varied by stakeholder, however dominant themes on integration included: significant variations in definitions, differential effectiveness of specific integrated NTD activities, community member perceptions of NTD programs, the influence of funders, perceived facilitators, perceived barriers, and the effects of integration on health system strength. In general, stakeholder groups provided unique perspectives, rather than contrarian points of view, on the same topics. The stakeholders identified more advantages to integration than disadvantages, however there are a number of both unique facilitators and challenges to integration from the perspective of each stakeholder group.Qualitative data suggest several structural, process, and technical opportunities that could be addressed to promote more effective and efficient integrated NTD

  19. Multiscale Phase Inversion of Seismic Data

    KAUST Repository

    Fu, Lei; Guo, Bowen; Sun, Yonghe; Schuster, Gerard T.

    2017-01-01

    -skipping, the multiscale strategy temporally integrates the traces several times, i.e. high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, higher frequencies in the data

  20. Integrated, multi-scale, spatial-temporal cell biology--A next step in the post genomic era.

    Science.gov (United States)

    Horwitz, Rick

    2016-03-01

    New microscopic approaches, high-throughput imaging, and gene editing promise major new insights into cellular behaviors. When coupled with genomic and other 'omic information and "mined" for correlations and associations, a new breed of powerful and useful cellular models should emerge. These top down, coarse-grained, and statistical models, in turn, can be used to form hypotheses merging with fine-grained, bottom up mechanistic studies and models that are the back bone of cell biology. The goal of the Allen Institute for Cell Science is to develop the top down approach by developing a high throughput microscopy pipeline that is integrated with modeling, using gene edited hiPS cell lines in various physiological and pathological contexts. The output of these experiments and models will be an "animated" cell, capable of integrating and analyzing image data generated from experiments and models. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Integrating the nursing management minimum data set into the logical observation identifier names and codes system.

    Science.gov (United States)

    Subramanian, Amarnath; Westra, Bonnie; Matney, Susan; Wilson, Patricia S; Delaney, Connie W; Huff, Stan; Huff, Stanley M; Huber, Diane

    2008-11-06

    This poster describes the process used to integrate the Nursing Management Minimum Data Set (NMMDS), an instrument to measure the nursing context of care, into the Logical Observation Identifier Names and Codes (LOINC) system to facilitate contextualization of quality measures. Integration of the first three of 18 elements resulted in 48 new codes including five panels. The LOINC Clinical Committee has approved the presented mapping for their next release.

  2. A multi-scale PDMS fabrication strategy to bridge the size mismatch between integrated circuits and microfluidics.

    Science.gov (United States)

    Muluneh, Melaku; Issadore, David

    2014-12-07

    In recent years there has been great progress harnessing the small-feature size and programmability of integrated circuits (ICs) for biological applications, by building microfluidics directly on top of ICs. However, a major hurdle to the further development of this technology is the inherent size-mismatch between ICs (~mm) and microfluidic chips (~cm). Increasing the area of the ICs to match the size of the microfluidic chip, as has often been done in previous studies, leads to a waste of valuable space on the IC and an increase in fabrication cost (>100×). To address this challenge, we have developed a three dimensional PDMS chip that can straddle multiple length scales of hybrid IC/microfluidic chips. This approach allows millimeter-scale ICs, with no post-processing, to be integrated into a centimeter-sized PDMS chip. To fabricate this PDMS chip we use a combination of soft-lithography and laser micromachining. Soft lithography was used to define micrometer-scale fluid channels directly on the surface of the IC, allowing fluid to be controlled with high accuracy and brought into close proximity to sensors for highly sensitive measurements. Laser micromachining was used to create ~50 μm vias to connect these molded PDMS channels to a larger PDMS chip, which can connect multiple ICs and house fluid connections to the outside world. To demonstrate the utility of this approach, we built and demonstrated an in-flow magnetic cytometer that consisted of a 5 × 5 cm(2) microfluidic chip that incorporated a commercial 565 × 1145 μm(2) IC with a GMR sensing circuit. We additionally demonstrated the modularity of this approach by building a chip that incorporated two of these GMR chips connected in series.

  3. RegRNA: an integrated web server for identifying regulatory RNA motifs and elements

    OpenAIRE

    Huang, Hsi-Yuan; Chien, Chia-Hung; Jen, Kuan-Hua; Huang, Hsien-Da

    2006-01-01

    Numerous regulatory structural motifs have been identified as playing essential roles in transcriptional and post-transcriptional regulation of gene expression. RegRNA is an integrated web server for identifying the homologs of regulatory RNA motifs and elements against an input mRNA sequence. Both sequence homologs and structural homologs of regulatory RNA motifs can be recognized. The regulatory RNA motifs supported in RegRNA are categorized into several classes: (i) motifs in mRNA 5′-untra...

  4. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes

    Directory of Open Access Journals (Sweden)

    Xinguo Lu

    2018-01-01

    Full Text Available With advances in next-generation sequencing(NGS technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profiles and copy number variation (CNV data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.

  5. Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation.

    Science.gov (United States)

    Brosch, Tom; Tang, Lisa Y W; Youngjin Yoo; Li, David K B; Traboulsee, Anthony; Tam, Roger

    2016-05-01

    We propose a novel segmentation approach based on deep 3D convolutional encoder networks with shortcut connections and apply it to the segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. Our model is a neural network that consists of two interconnected pathways, a convolutional pathway, which learns increasingly more abstract and higher-level image features, and a deconvolutional pathway, which predicts the final segmentation at the voxel level. The joint training of the feature extraction and prediction pathways allows for the automatic learning of features at different scales that are optimized for accuracy for any given combination of image types and segmentation task. In addition, shortcut connections between the two pathways allow high- and low-level features to be integrated, which enables the segmentation of lesions across a wide range of sizes. We have evaluated our method on two publicly available data sets (MICCAI 2008 and ISBI 2015 challenges) with the results showing that our method performs comparably to the top-ranked state-of-the-art methods, even when only relatively small data sets are available for training. In addition, we have compared our method with five freely available and widely used MS lesion segmentation methods (EMS, LST-LPA, LST-LGA, Lesion-TOADS, and SLS) on a large data set from an MS clinical trial. The results show that our method consistently outperforms these other methods across a wide range of lesion sizes.

  6. Identifying Core Mobile Learning Faculty Competencies Based Integrated Approach: A Delphi Study

    Science.gov (United States)

    Elbarbary, Rafik Said

    2015-01-01

    This study is based on the integrated approach as a concept framework to identify, categorize, and rank a key component of mobile learning core competencies for Egyptian faculty members in higher education. The field investigation framework used four rounds Delphi technique to determine the importance rate of each component of core competencies…

  7. Process framework for identifying sustainability aspects in university curricula and integrating education for sustainable development

    DEFF Research Database (Denmark)

    Holm, Tove; Sammalisto, Kaisu; Grindsted, Thomas Skou

    2015-01-01

    Sustainability aspects in higher education must be enhanced with more concrete actions. Universities are globally required to have quality assurance to secure and improve teaching and learning, and they use management systems to this aim. Integrating education for sustainable development...... and management systems are alike in that they are based on continuous improvement and systematic thinking; for both processes all stakeholders need to be involved. Although quality assurance is compulsory for higher education, education for sustainable development has barely been examined or integrated...... in this context. This article examines how voluntary integration of education for sustainable development into management systems at universities could facilitate a scheme to overcome the challenges to integrating education for sustainable development that were identified in previous research. For this, a process...

  8. Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

    Science.gov (United States)

    Zanin, Massimiliano; Chorbev, Ivan; Stres, Blaz; Stalidzans, Egils; Vera, Julio; Tieri, Paolo; Castiglione, Filippo; Groen, Derek; Zheng, Huiru; Baumbach, Jan; Schmid, Johannes A; Basilio, José; Klimek, Peter; Debeljak, Nataša; Rozman, Damjana; Schmidt, Harald H H W

    2017-12-05

    Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine. © The Author 2017. Published by Oxford University Press.

  9. Common integration sites of published datasets identified using a graph-based framework

    Directory of Open Access Journals (Sweden)

    Alessandro Vasciaveo

    2016-01-01

    Full Text Available With next-generation sequencing, the genomic data available for the characterization of integration sites (IS has dramatically increased. At present, in a single experiment, several thousand viral integration genome targets can be investigated to define genomic hot spots. In a previous article, we renovated a formal CIS analysis based on a rigid fixed window demarcation into a more stretchy definition grounded on graphs. Here, we present a selection of supporting data related to the graph-based framework (GBF from our previous article, in which a collection of common integration sites (CIS was identified on six published datasets. In this work, we will focus on two datasets, ISRTCGD and ISHIV, which have been previously discussed. Moreover, we show in more detail the workflow design that originates the datasets.

  10. Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Bing Jiang

    2017-01-01

    Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

  11. A complete categorization of multiscale models of infectious disease systems.

    Science.gov (United States)

    Garira, Winston

    2017-12-01

    Modelling of infectious disease systems has entered a new era in which disease modellers are increasingly turning to multiscale modelling to extend traditional modelling frameworks into new application areas and to achieve higher levels of detail and accuracy in characterizing infectious disease systems. In this paper we present a categorization framework for categorizing multiscale models of infectious disease systems. The categorization framework consists of five integration frameworks and five criteria. We use the categorization framework to give a complete categorization of host-level immuno-epidemiological models (HL-IEMs). This categorization framework is also shown to be applicable in categorizing other types of multiscale models of infectious diseases beyond HL-IEMs through modifying the initial categorization framework presented in this study. Categorization of multiscale models of infectious disease systems in this way is useful in bringing some order to the discussion on the structure of these multiscale models.

  12. Integrated corridor management : phase I, concept development and foundational research. Task 3.4, identify integrated corridor management institutional strategies and administration

    Science.gov (United States)

    2006-04-12

    Task 3 involves overall foundational research to further the understanding of various aspects of Integrated Corridor Management (ICM) and to identify integration issues needed to evaluate the feasibility of the ICM initiative. The focus of Task 3.4 a...

  13. ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

    Science.gov (United States)

    Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

    2015-01-01

    Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

  14. Multiscale information modelling for heart morphogenesis

    Energy Technology Data Exchange (ETDEWEB)

    Abdulla, T; Imms, R; Summers, R [Department of Electronic and Electrical Engineering, Loughborough University, Loughborough (United Kingdom); Schleich, J M, E-mail: T.Abdulla@lboro.ac.u [LTSI Signal and Image Processing Laboratory, University of Rennes 1, Rennes (France)

    2010-07-01

    Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.

  15. Multiscale information modelling for heart morphogenesis

    International Nuclear Information System (INIS)

    Abdulla, T; Imms, R; Summers, R; Schleich, J M

    2010-01-01

    Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.

  16. Multiscale Cancer Modeling

    Science.gov (United States)

    Macklin, Paul; Cristini, Vittorio

    2013-01-01

    Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insight on the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community. PMID:21529163

  17. Multiscale Representations Phase II

    National Research Council Canada - National Science Library

    Bar-Yam, Yaneer

    2004-01-01

    .... Multiscale analysis provides an analytic tool that can be applied to evaluating force capabilities as well as the relevance of designs for technological innovations to support force structures and their modernization...

  18. Multiscale System Theory

    Science.gov (United States)

    1990-02-21

    LIDS-P-1953 Multiscale System Theory Albert Benveniste IRISA-INRIA, Campus de Beaulieu 35042 RENNES CEDEX, FRANCE Ramine Nikoukhah INRIA...TITLE AND SUBTITLE Multiscale System Theory 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e...the development of a corresponding system theory and a theory of stochastic processes and their estimation. The research presented in this and several

  19. Multiscale Simulations Using Particles

    DEFF Research Database (Denmark)

    Walther, Jens Honore

    vortex methods for problems in continuum fluid dynamics, dissipative particle dynamics for flow at the meso scale, and atomistic molecular dynamics simulations of nanofluidic systems. We employ multiscale techniques to breach the atomistic and continuum scales to study fundamental problems in fluid...... dynamics. Recent work on the thermophoretic motion of water nanodroplets confined inside carbon nanotubes, and multiscale techniques for polar liquids will be discussed in detail at the symposium....

  20. Semantic integration to identify overlapping functional modules in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Ramanathan Murali

    2007-07-01

    Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

  1. Integrated systems approach identifies risk regulatory pathways and key regulators in coronary artery disease.

    Science.gov (United States)

    Zhang, Yan; Liu, Dianming; Wang, Lihong; Wang, Shuyuan; Yu, Xuexin; Dai, Enyu; Liu, Xinyi; Luo, Shanshun; Jiang, Wei

    2015-12-01

    Coronary artery disease (CAD) is the most common type of heart disease. However, the molecular mechanisms of CAD remain elusive. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, inferring risk regulatory pathways is an important step toward elucidating the mechanisms underlying CAD. With advances in high-throughput data, we developed an integrated systems approach to identify CAD risk regulatory pathways and key regulators. Firstly, a CAD-related core subnetwork was identified from a curated transcription factor (TF) and microRNA (miRNA) regulatory network based on a random walk algorithm. Secondly, candidate risk regulatory pathways were extracted from the subnetwork by applying a breadth-first search (BFS) algorithm. Then, risk regulatory pathways were prioritized based on multiple CAD-associated data sources. Finally, we also proposed a new measure to prioritize upstream regulators. We inferred that phosphatase and tensin homolog (PTEN) may be a key regulator in the dysregulation of risk regulatory pathways. This study takes a closer step than the identification of disease subnetworks or modules. From the risk regulatory pathways, we could understand the flow of regulatory information in the initiation and progression of the disease. Our approach helps to uncover its potential etiology. We developed an integrated systems approach to identify risk regulatory pathways. We proposed a new measure to prioritize the key regulators in CAD. PTEN may be a key regulator in dysregulation of the risk regulatory pathways.

  2. Multiscale Computing with the Multiscale Modeling Library and Runtime Environment

    NARCIS (Netherlands)

    Borgdorff, J.; Mamonski, M.; Bosak, B.; Groen, D.; Ben Belgacem, M.; Kurowski, K.; Hoekstra, A.G.

    2013-01-01

    We introduce a software tool to simulate multiscale models: the Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We

  3. Genome-wide profiling of HPV integration in cervical cancer identifies clustered genomic hot spots and a potential microhomology-mediated integration mechanism

    DEFF Research Database (Denmark)

    Hu, Zheng; Zhu, Da; Wang, Wei

    2015-01-01

    Human papillomavirus (HPV) integration is a key genetic event in cervical carcinogenesis1. By conducting whole-genome sequencing and high-throughput viral integration detection, we identified 3,667 HPV integration breakpoints in 26 cervical intraepithelial neoplasias, 104 cervical carcinomas and ...

  4. Identifying Issues in Applying Integrated Project Delivery to Domestic Nuclear Power Plant Construction Projects

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Young Joo [Korean Nuclear Society, Daejeon (Korea, Republic of)

    2016-05-15

    Integrated Project Delivery (IPD) is defined as that people, systems, business structures, and practices of key stakeholders are incorporated into a single-team, with a single process, which executes a project in a way of optimizing the project's outcome, increasing values delivered to the end user, reducing waste, and maximizing efficiency throughout the phases of engineering to construction. The researcher had carried out literature review in terms of IPD to identify major characteristics of IPD which are presented in the following section and had compared such characteristics against peculiarities of nuclear power plant (NPP) construction projects in order to shed light on obstacles in possible application of IPD method to domestic NPP construction projects in the coming days. In this research, three (3) major characteristics of IPD were identified: 1) key stakeholders signing one balanced contract, forming de facto one body, sharing risk and reward 2) an integrated project team being formed in the early stage of a project and providing input to minimize time and cost loss from rework downstream 3) team members co-locating, having open and direct communication, making decisions on time, and pursuing the success of the project itself.

  5. Integrating Diverse Types of Genomic Data to Identify Genes that Underlie Adverse Pregnancy Phenotypes.

    Directory of Open Access Journals (Sweden)

    Jibril Hirbo

    Full Text Available Progress in understanding complex genetic diseases has been bolstered by synthetic approaches that overlay diverse data types and analyses to identify functionally important genes. Pre-term birth (PTB, a major complication of pregnancy, is a leading cause of infant mortality worldwide. A major obstacle in addressing PTB is that the mechanisms controlling parturition and birth timing remain poorly understood. Integrative approaches that overlay datasets derived from comparative genomics with function-derived ones have potential to advance our understanding of the genetics of birth timing, and thus provide insights into the genes that may contribute to PTB. We intersected data from fast evolving coding and non-coding gene regions in the human and primate lineage with data from genes expressed in the placenta, from genes that show enriched expression only in the placenta, as well as from genes that are differentially expressed in four distinct PTB clinical subtypes. A large fraction of genes that are expressed in placenta, and differentially expressed in PTB clinical subtypes (23-34% are fast evolving, and are associated with functions that include adhesion neurodevelopmental and immune processes. Functional categories of genes that express fast evolution in coding regions differ from those linked to fast evolution in non-coding regions. Finally, there is a surprising lack of overlap between fast evolving genes that are differentially expressed in four PTB clinical subtypes. Integrative approaches, especially those that incorporate evolutionary perspectives, can be successful in identifying potential genetic contributions to complex genetic diseases, such as PTB.

  6. Identifying professionals' needs in integrating electronic pain monitoring in community palliative care services: An interview study.

    Science.gov (United States)

    Taylor, Sally; Allsop, Matthew J; Bekker, Hilary L; Bennett, Michael I; Bewick, Bridgette M

    2017-07-01

    Poor pain assessment is a barrier to effective pain control. There is growing interest internationally in the development and implementation of remote monitoring technologies to enhance assessment in cancer and chronic disease contexts. Findings describe the development and testing of pain monitoring systems, but research identifying the needs of health professionals to implement routine monitoring systems within clinical practice is limited. To inform the development and implementation strategy of an electronic pain monitoring system, PainCheck, by understanding palliative care professionals' needs when integrating PainCheck into routine clinical practice. Qualitative study using face-to-face interviews. Data were analysed using framework analysis Setting/participants: Purposive sample of health professionals managing the palliative care of patients living in the community Results: A total of 15 interviews with health professionals took place. Three meta-themes emerged from the data: (1) uncertainties about integration of PainCheck and changes to current practice, (2) appraisal of current practice and (3) pain management is everybody's responsibility Conclusion: Even the most sceptical of health professionals could see the potential benefits of implementing an electronic patient-reported pain monitoring system. Health professionals have reservations about how PainCheck would work in practice. For optimal use, PainCheck needs embedding within existing electronic health records. Electronic pain monitoring systems have the potential to enable professionals to support patients' pain management more effectively but only when barriers to implementation are appropriately identified and addressed.

  7. Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

    Science.gov (United States)

    Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-06

    Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

  8. A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

    Science.gov (United States)

    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.

  9. Identifying the barriers to conducting outcomes research in integrative health care clinic settings - a qualitative study

    Directory of Open Access Journals (Sweden)

    Findlay-Reece Barbara

    2010-01-01

    Full Text Available Abstract Background Integrative health care (IHC is an interdisciplinary blending of conventional medicine and complementary and alternative medicine (CAM with the purpose of enhancing patients' health. In 2006, we designed a study to assess outcomes that are relevant to people using such care. However, we faced major challenges in conducting this study and hypothesized that this might be due to the lack of a research climate in these clinics. To investigate these challenges, we initiated a further study in 2008, to explore the reasons why IHC clinics are not conducting outcomes research and to identify strategies for conducting successful in-house outcomes research programs. The results of the latter study are reported here. Methods A total of 25 qualitative interviews were conducted with key participants from 19 IHC clinics across Canada. Basic content analysis was used to identify key themes from the transcribed interviews. Results Barriers identified by participants fell into four categories: organizational culture, organizational resources, organizational environment and logistical challenges. Cultural challenges relate to the philosophy of IHC, organizational leadership and practitioner attitudes and beliefs. Participants also identified significant issues relating to their organization's lack of resources such as funding, compensation, infrastructure and partnerships/linkages. Environmental challenges such as the nature of a clinic's patient population and logistical issues such as the actual implementation of a research program and the applicability of research data also posed challenges to the conduct of research. Embedded research leadership, integration of personal and professional values about research, alignment of research activities and clinical workflow processes are some of the factors identified by participants that support IHC clinics' ability to conduct outcomes research. Conclusions Assessing and enhancing the broader

  10. Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles

    Directory of Open Access Journals (Sweden)

    Farshad Farshidfar

    2017-03-01

    Full Text Available Cholangiocarcinoma (CCA is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance.

  11. Integrated analysis of the molecular action of Vorinostat identifies epi-sensitised targets for combination therapy.

    Science.gov (United States)

    Hay, Jodie F; Lappin, Katrina; Liberante, Fabio; Kettyle, Laura M; Matchett, Kyle B; Thompson, Alexander; Mills, Ken I

    2017-09-15

    Several histone deacetylase inhibitors including Vorinostat have received FDA approval for the treatment of haematological malignancies. However, data from these trials indicate that Vorinostat has limited efficacy as a monotherapy, prompting the need for rational design of combination therapies. A number of epi-sensitised pathways, including sonic hedgehog (SHH), were identified in AML cells by integration of global patterns of histone H3 lysine 9 (H3K9) acetylation with transcriptomic analysis following Vorinostat-treatment. Direct targeting of the SHH pathway with SANT-1, following Vorinostat induced epi-sensitisation, resulted in synergistic cell death of AML cells. In addition, xenograft studies demonstrated that combination therapy induced a marked reduction in leukemic burden compared to control or single agents. Together, the data supports epi-sensitisation as a potential component of the strategy for the rational development of combination therapies in AML.

  12. Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer.

    Directory of Open Access Journals (Sweden)

    Matthew Ruffalo

    2015-12-01

    Full Text Available Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at different levels of cellular activity. Namely, we hypothesize that genes that play a role in cancer development and progression may be implicated by neither frequent mutation nor differential expression, and that network-based integration of mutation and differential expression data can reveal these "silent players". For this purpose, we utilize network-propagation algorithms to simulate the information flow in the cell at a sample-specific resolution. We then use the propagated mutation and expression signals to identify genes that are not necessarily mutated or differentially expressed genes, but have an essential role in tumor development and patient outcome. We test the proposed method on breast cancer and glioblastoma multiforme data obtained from TCGA. Our results show that the proposed method can identify important proteins that are not readily revealed by molecular data, providing insights beyond what can be gleaned by analyzing different types of molecular data in isolation.

  13. Integrated database for identifying candidate genes for Aspergillus flavus resistance in maize.

    Science.gov (United States)

    Kelley, Rowena Y; Gresham, Cathy; Harper, Jonathan; Bridges, Susan M; Warburton, Marilyn L; Hawkins, Leigh K; Pechanova, Olga; Peethambaran, Bela; Pechan, Tibor; Luthe, Dawn S; Mylroie, J E; Ankala, Arunkanth; Ozkan, Seval; Henry, W B; Williams, W P

    2010-10-07

    Aspergillus flavus Link:Fr, an opportunistic fungus that produces aflatoxin, is pathogenic to maize and other oilseed crops. Aflatoxin is a potent carcinogen, and its presence markedly reduces the value of grain. Understanding and enhancing host resistance to A. flavus infection and/or subsequent aflatoxin accumulation is generally considered an efficient means of reducing grain losses to aflatoxin. Different proteomic, genomic and genetic studies of maize (Zea mays L.) have generated large data sets with the goal of identifying genes responsible for conferring resistance to A. flavus, or aflatoxin. In order to maximize the usage of different data sets in new studies, including association mapping, we have constructed a relational database with web interface integrating the results of gene expression, proteomic (both gel-based and shotgun), Quantitative Trait Loci (QTL) genetic mapping studies, and sequence data from the literature to facilitate selection of candidate genes for continued investigation. The Corn Fungal Resistance Associated Sequences Database (CFRAS-DB) (http://agbase.msstate.edu/) was created with the main goal of identifying genes important to aflatoxin resistance. CFRAS-DB is implemented using MySQL as the relational database management system running on a Linux server, using an Apache web server, and Perl CGI scripts as the web interface. The database and the associated web-based interface allow researchers to examine many lines of evidence (e.g. microarray, proteomics, QTL studies, SNP data) to assess the potential role of a gene or group of genes in the response of different maize lines to A. flavus infection and subsequent production of aflatoxin by the fungus. CFRAS-DB provides the first opportunity to integrate data pertaining to the problem of A. flavus and aflatoxin resistance in maize in one resource and to support queries across different datasets. The web-based interface gives researchers different query options for mining the database

  14. An Integrative Data Science Pipeline to Identify Novel Drug Interactions that Prolong the QT Interval.

    Science.gov (United States)

    Lorberbaum, Tal; Sampson, Kevin J; Woosley, Raymond L; Kass, Robert S; Tatonetti, Nicholas P

    2016-05-01

    Drug-induced prolongation of the QT interval on the electrocardiogram (long QT syndrome, LQTS) can lead to a potentially fatal ventricular arrhythmia known as torsades de pointes (TdP). Over 40 drugs with both cardiac and non-cardiac indications are associated with increased risk of TdP, but drug-drug interactions contributing to LQTS (QT-DDIs) remain poorly characterized. Traditional methods for mining observational healthcare data are poorly equipped to detect QT-DDI signals due to low reporting numbers and lack of direct evidence for LQTS. We hypothesized that LQTS could be identified latently using an adverse event (AE) fingerprint of more commonly reported AEs. We aimed to generate an integrated data science pipeline that addresses current limitations by identifying latent signals for QT-DDIs in the US FDA's Adverse Event Reporting System (FAERS) and retrospectively validating these predictions using electrocardiogram data in electronic health records (EHRs). We trained a model to identify an AE fingerprint for risk of TdP for single drugs and applied this model to drug pair data to predict novel DDIs. In the EHR at Columbia University Medical Center, we compared the QTc intervals of patients prescribed the flagged drug pairs with patients prescribed either drug individually. We created an AE fingerprint consisting of 13 latently detected side effects. This model significantly outperformed a direct evidence control model in the detection of established interactions (p = 1.62E-3) and significantly enriched for validated QT-DDIs in the EHR (p = 0.01). Of 889 pairs flagged in FAERS, eight novel QT-DDIs were significantly associated with prolonged QTc intervals in the EHR and were not due to co-prescribed medications. Latent signal detection in FAERS validated using the EHR presents an automated and data-driven approach for systematically identifying novel QT-DDIs. The high-confidence hypotheses flagged using this method warrant further investigation.

  15. The Integrated Nordic End-User Electricity Market - Feasibility and identified obstacles

    International Nuclear Information System (INIS)

    2006-02-01

    The report identifies the various obstacles that currently exist which prevent the formation of a truly integrated Nordic electricity end-user market. The obstacles have been divided into three categories: technical, regulatory and commercial. NordREG proposes that to further integrate the Nordic end-user electricity markets, a number of differences of technical, legal and market nature ought to be gradually harmonized in order to facilitate market entry and cross-border trade. Technical obstacles: Especially the following problems related to the data and metering systems should be solved: Transferred messages, information and message timing should be harmonised; Message format should be decided; A common data transmission protocol should be specified. New solutions like web-based solutions should be studied; The identification of the final customers' metering point should be harmonised. Regulatory obstacles: The identified regulatory obstacles relate to three areas, namely the division of tasks between monopoly and competitive activities, the operation and duties of distribution network operators including how these are regulated, and the legal framework to provide protection for small end users. On the basis of the review of regulatory obstacles, the following recommendations are made: The principles of neutrality and the way these principles are being supervised by the regulator is a key issue to improve the functioning of the Nordic end-user market. Regulators should seek to harmonise regulation on neutrality and put it high on the agenda in a forthcoming process of market integration; The procedures for switching supplier should be as smooth, easy and quick as possible. It is also important that suppliers, especially the new market entrants, can participate in reliable, transparent and fluent switching practices, since this lowers the threshold for entering other than domestic electricity market. The switching model should be harmonised for the Nordic end

  16. The Integrated Nordic End-User Electricity Market - Feasibility and identified obstacles

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-02-15

    The report identifies the various obstacles that currently exist which prevent the formation of a truly integrated Nordic electricity end-user market. The obstacles have been divided into three categories: technical, regulatory and commercial. NordREG proposes that to further integrate the Nordic end-user electricity markets, a number of differences of technical, legal and market nature ought to be gradually harmonized in order to facilitate market entry and cross-border trade. Technical obstacles: Especially the following problems related to the data and metering systems should be solved: Transferred messages, information and message timing should be harmonised; Message format should be decided; A common data transmission protocol should be specified. New solutions like web-based solutions should be studied; The identification of the final customers' metering point should be harmonised. Regulatory obstacles: The identified regulatory obstacles relate to three areas, namely the division of tasks between monopoly and competitive activities, the operation and duties of distribution network operators including how these are regulated, and the legal framework to provide protection for small end users. On the basis of the review of regulatory obstacles, the following recommendations are made: The principles of neutrality and the way these principles are being supervised by the regulator is a key issue to improve the functioning of the Nordic end-user market. Regulators should seek to harmonise regulation on neutrality and put it high on the agenda in a forthcoming process of market integration; The procedures for switching supplier should be as smooth, easy and quick as possible. It is also important that suppliers, especially the new market entrants, can participate in reliable, transparent and fluent switching practices, since this lowers the threshold for entering other than domestic electricity market. The switching model should be harmonised for the Nordic end

  17. Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

    Directory of Open Access Journals (Sweden)

    Xianjun Shen

    Full Text Available How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment. It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

  18. An integrated system for identifying the hidden assassins in traditional medicines containing aristolochic acids

    Science.gov (United States)

    Wu, Lan; Sun, Wei; Wang, Bo; Zhao, Haiyu; Li, Yaoli; Cai, Shaoqing; Xiang, Li; Zhu, Yingjie; Yao, Hui; Song, Jingyuan; Cheng, Yung-Chi; Chen, Shilin

    2015-08-01

    Traditional herbal medicines adulterated and contaminated with plant materials from the Aristolochiaceae family, which contain aristolochic acids (AAs), cause aristolochic acid nephropathy. Approximately 256 traditional Chinese patent medicines, containing Aristolochiaceous materials, are still being sold in Chinese markets today. In order to protect consumers from health risks due to AAs, the hidden assassins, efficient methods to differentiate Aristolochiaceous herbs from their putative substitutes need to be established. In this study, 158 Aristolochiaceous samples representing 46 species and four genera as well as 131 non-Aristolochiaceous samples representing 33 species, 20 genera and 12 families were analyzed using DNA barcodes based on the ITS2 and psbA-trnH sequences. Aristolochiaceous materials and their non-Aristolochiaceous substitutes were successfully identified using BLAST1, the nearest distance method and the neighbor-joining (NJ) tree. In addition, based on sequence information of ITS2, we developed a Real-Time PCR assay which successfully identified herbal material from the Aristolochiaceae family. Using Ultra High Performance Liquid Chromatography-Mass Spectrometer (UHPLC-HR-MS), we demonstrated that most representatives from the Aristolochiaceae family contain toxic AAs. Therefore, integrated DNA barcodes, Real-Time PCR assays using TaqMan probes and UHPLC-HR-MS system provides an efficient and reliable authentication system to protect consumers from health risks due to the hidden assassins (AAs).

  19. Integrative screening approach identifies regulators of polyploidization and targets for acute megakaryocytic leukemia

    Science.gov (United States)

    Wen, Qiang; Goldenson, Benjamin; Silver, Serena J.; Schenone, Monica; Dancik, Vladimir; Huang, Zan; Wang, Ling-Zhi; Lewis, Timothy; An, W. Frank; Li, Xiaoyu; Bray, Mark-Anthony; Thiollier, Clarisse; Diebold, Lauren; Gilles, Laure; Vokes, Martha S.; Moore, Christopher B.; Bliss-Moreau, Meghan; VerPlank, Lynn; Tolliday, Nicola J.; Mishra, Rama; Vemula, Sasidhar; Shi, Jianjian; Wei, Lei; Kapur, Reuben; Lopez, Cécile K.; Gerby, Bastien; Ballerini, Paola; Pflumio, Francoise; Gilliland, D. Gary; Goldberg, Liat; Birger, Yehudit; Izraeli, Shai; Gamis, Alan S.; Smith, Franklin O.; Woods, William G.; Taub, Jeffrey; Scherer, Christina A.; Bradner, James; Goh, Boon-Cher; Mercher, Thomas; Carpenter, Anne E.; Gould, Robert J.; Clemons, Paul A.; Carr, Steven A.; Root, David E.; Schreiber, Stuart L.; Stern, Andrew M.; Crispino, John D.

    2012-01-01

    Summary The mechanism by which cells decide to skip mitosis to become polyploid is largely undefined. Here we used a high-content image-based screen to identify small-molecule probes that induce polyploidization of megakaryocytic leukemia cells and serve as perturbagens to help understand this process. We found that dimethylfasudil (diMF, H-1152P) selectively increased polyploidization, mature cell-surface marker expression, and apoptosis of malignant megakaryocytes. A broadly applicable, highly integrated target identification approach employing proteomic and shRNA screening revealed that a major target of diMF is Aurora A kinase (AURKA), which has not been studied extensively in megakaryocytes. Moreover, we discovered that MLN8237 (Alisertib), a selective inhibitor of AURKA, induced polyploidization and expression of mature megakaryocyte markers in AMKL blasts and displayed potent anti-AMKL activity in vivo. This research provides the rationale to support clinical trials of MLN8237 and other inducers of polyploidization in AMKL. Finally, we have identified five networks of kinases that regulate the switch to polyploidy. PMID:22863010

  20. Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends.

    Science.gov (United States)

    Jurca, Gabriela; Addam, Omar; Aksac, Alper; Gao, Shang; Özyer, Tansel; Demetrick, Douglas; Alhajj, Reda

    2016-04-26

    Breast cancer is a serious disease which affects many women and may lead to death. It has received considerable attention from the research community. Thus, biomedical researchers aim to find genetic biomarkers indicative of the disease. Novel biomarkers can be elucidated from the existing literature. However, the vast amount of scientific publications on breast cancer make this a daunting task. This paper presents a framework which investigates existing literature data for informative discoveries. It integrates text mining and social network analysis in order to identify new potential biomarkers for breast cancer. We utilized PubMed for the testing. We investigated gene-gene interactions, as well as novel interactions such as gene-year, gene-country, and abstract-country to find out how the discoveries varied over time and how overlapping/diverse are the discoveries and the interest of various research groups in different countries. Interesting trends have been identified and discussed, e.g., different genes are highlighted in relationship to different countries though the various genes were found to share functionality. Some text analysis based results have been validated against results from other tools that predict gene-gene relations and gene functions.

  1. An innovative and integrated approach based on DNA walking to identify unauthorised GMOs.

    Science.gov (United States)

    Fraiture, Marie-Alice; Herman, Philippe; Taverniers, Isabel; De Loose, Marc; Deforce, Dieter; Roosens, Nancy H

    2014-03-15

    In the coming years, the frequency of unauthorised genetically modified organisms (GMOs) being present in the European food and feed chain will increase significantly. Therefore, we have developed a strategy to identify unauthorised GMOs containing a pCAMBIA family vector, frequently present in transgenic plants. This integrated approach is performed in two successive steps on Bt rice grains. First, the potential presence of unauthorised GMOs is assessed by the qPCR SYBR®Green technology targeting the terminator 35S pCAMBIA element. Second, its presence is confirmed via the characterisation of the junction between the transgenic cassette and the rice genome. To this end, a DNA walking strategy is applied using a first reverse primer followed by two semi-nested PCR rounds using primers that are each time nested to the previous reverse primer. This approach allows to rapidly identify the transgene flanking region and can easily be implemented by the enforcement laboratories. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. An Integrative Analysis to Identify Driver Genes in Esophageal Squamous Cell Carcinoma.

    Directory of Open Access Journals (Sweden)

    Genta Sawada

    Full Text Available Few driver genes have been well established in esophageal squamous cell carcinoma (ESCC. Identification of the genomic aberrations that contribute to changes in gene expression profiles can be used to predict driver genes.We searched for driver genes in ESCC by integrative analysis of gene expression microarray profiles and copy number data. To narrow down candidate genes, we performed survival analysis on expression data and tested the genetic vulnerability of each genes using public RNAi screening data. We confirmed the results by performing RNAi experiments and evaluating the clinical relevance of candidate genes in an independent ESCC cohort.We found 10 significantly recurrent copy number alterations accompanying gene expression changes, including loci 11q13.2, 7p11.2, 3q26.33, and 17q12, which harbored CCND1, EGFR, SOX2, and ERBB2, respectively. Analysis of survival data and RNAi screening data suggested that GRB7, located on 17q12, was a driver gene in ESCC. In ESCC cell lines harboring 17q12 amplification, knockdown of GRB7 reduced the proliferation, migration, and invasion capacities of cells. Moreover, siRNA targeting GRB7 had a synergistic inhibitory effect when combined with trastuzumab, an anti-ERBB2 antibody. Survival analysis of the independent cohort also showed that high GRB7 expression was associated with poor prognosis in ESCC.Our integrative analysis provided important insights into ESCC pathogenesis. We identified GRB7 as a novel ESCC driver gene and potential new therapeutic target.

  3. Effects of active conductance distribution over dendrites on the synaptic integration in an identified nonspiking interneuron.

    Directory of Open Access Journals (Sweden)

    Akira Takashima

    Full Text Available The synaptic integration in individual central neuron is critically affected by how active conductances are distributed over dendrites. It has been well known that the dendrites of central neurons are richly endowed with voltage- and ligand-regulated ion conductances. Nonspiking interneurons (NSIs, almost exclusively characteristic to arthropod central nervous systems, do not generate action potentials and hence lack voltage-regulated sodium channels, yet having a variety of voltage-regulated potassium conductances on their dendritic membrane including the one similar to the delayed-rectifier type potassium conductance. It remains unknown, however, how the active conductances are distributed over dendrites and how the synaptic integration is affected by those conductances in NSIs and other invertebrate neurons where the cell body is not included in the signal pathway from input synapses to output sites. In the present study, we quantitatively investigated the functional significance of active conductance distribution pattern in the spatio-temporal spread of synaptic potentials over dendrites of an identified NSI in the crayfish central nervous system by computer simulation. We systematically changed the distribution pattern of active conductances in the neuron's multicompartment model and examined how the synaptic potential waveform was affected by each distribution pattern. It was revealed that specific patterns of nonuniform distribution of potassium conductances were consistent, while other patterns were not, with the waveform of compound synaptic potentials recorded physiologically in the major input-output pathway of the cell, suggesting that the possibility of nonuniform distribution of potassium conductances over the dendrite cannot be excluded as well as the possibility of uniform distribution. Local synaptic circuits involving input and output synapses on the same branch or on the same side were found to be potentially affected under

  4. Improving accuracy for identifying related PubMed queries by an integrated approach.

    Science.gov (United States)

    Lu, Zhiyong; Wilbur, W John

    2009-10-01

    PubMed is the most widely used tool for searching biomedical literature online. As with many other online search tools, a user often types a series of multiple related queries before retrieving satisfactory results to fulfill a single information need. Meanwhile, it is also a common phenomenon to see a user type queries on unrelated topics in a single session. In order to study PubMed users' search strategies, it is necessary to be able to automatically separate unrelated queries and group together related queries. Here, we report a novel approach combining both lexical and contextual analyses for segmenting PubMed query sessions and identifying related queries and compare its performance with the previous approach based solely on concept mapping. We experimented with our integrated approach on sample data consisting of 1539 pairs of consecutive user queries in 351 user sessions. The prediction results of 1396 pairs agreed with the gold-standard annotations, achieving an overall accuracy of 90.7%. This demonstrates that our approach is significantly better than the previously published method. By applying this approach to a one day query log of PubMed, we found that a significant proportion of information needs involved more than one PubMed query, and that most of the consecutive queries for the same information need are lexically related. Finally, the proposed PubMed distance is shown to be an accurate and meaningful measure for determining the contextual similarity between biological terms. The integrated approach can play a critical role in handling real-world PubMed query log data as is demonstrated in our experiments.

  5. Multiscale Biological Materials

    DEFF Research Database (Denmark)

    Frølich, Simon

    of multiscale biological systems have been investigated and new research methods for automated Rietveld refinement and diffraction scattering computed tomography developed. The composite nature of biological materials was investigated at the atomic scale by looking at the consequences of interactions between...

  6. A mathematical framework for multiscale science and engineering: the variational multiscale method and interscale transfer operators

    International Nuclear Information System (INIS)

    Shadid, John Nicolas; Lehoucq, Richard B.; Christon, Mark Allen; Slepoy, Alexander; Bochev, Pavel Blagoveston; Collis, Samuel Scott; Wagner, Gregory John

    2004-01-01

    Existing approaches in multiscale science and engineering have evolved from a range of ideas and solutions that are reflective of their original problem domains. As a result, research in multiscale science has followed widely diverse and disjoint paths, which presents a barrier to cross pollination of ideas and application of methods outside their application domains. The status of the research environment calls for an abstract mathematical framework that can provide a common language to formulate and analyze multiscale problems across a range of scientific and engineering disciplines. In such a framework, critical common issues arising in multiscale problems can be identified, explored and characterized in an abstract setting. This type of overarching approach would allow categorization and clarification of existing models and approximations in a landscape of seemingly disjoint, mutually exclusive and ad hoc methods. More importantly, such an approach can provide context for both the development of new techniques and their critical examination. As with any new mathematical framework, it is necessary to demonstrate its viability on problems of practical importance. At Sandia, lab-centric, prototype application problems in fluid mechanics, reacting flows, magnetohydrodynamics (MHD), shock hydrodynamics and materials science span an important subset of DOE Office of Science applications and form an ideal proving ground for new approaches in multiscale science.

  7. Synergies, Trade-offs, and Losses of Ecosystem Services in Urban Regions: an Integrated Multiscale Framework Applied to the Leipzig-Halle Region, Germany

    Directory of Open Access Journals (Sweden)

    Dagmar Haase

    2012-09-01

    Full Text Available Because we have entered the 'millennium of the cities', urban ecological research needs to account for the provisions ecosystem services provide to urban regions. In urban areas, ecosystem service assessment studies need to account for the complex land use patterns, which change over relatively short periods of time. We discuss an analytical framework for the spatial and temporal integration of different ecosystem services in an urban region to determine synergies, trade-offs and losses, and we employ a case study in Leipzig-Halle, Germany. The following five ecosystem services, which are of special importance for urban areas, were selected: local climate regulation, recreation potential, biodiversity potential, food supply, and above-ground carbon storage. These services were analyzed from 1990 to 2006. Our results identified only slight increases in urbanization (1% or 3 km² and in mining restoration (-11 km². However, the detected land use changes led to synergies with biodiversity and climate regulation of > 50% of the total area, whereas trade-offs of approximately 60% were detected between variables such as climate regulation and recreation. Finally, we address both the opportunities and the challenges that were encountered in the integration study, specifically with respect to the application in land use planning.

  8. Multiscale Phase Inversion of Seismic Data

    KAUST Repository

    Fu, Lei

    2017-12-02

    We present a scheme for multiscale phase inversion (MPI) of seismic data that is less sensitive to the unmodeled physics of wave propagation and a poor starting model than standard full waveform inversion (FWI). To avoid cycle-skipping, the multiscale strategy temporally integrates the traces several times, i.e. high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, higher frequencies in the data are boosted by using integrated traces of lower order as the input data. The input data are also filtered into different narrow frequency bands for the MPI implementation. At low frequencies, we show that MPI with windowed reflections approximates wave equation inversion of the reflection traveltimes, except no traveltime picking is needed. Numerical results with synthetic acoustic data show that MPI is more robust than conventional multiscale FWI when the initial model is far from the true model. Results from synthetic viscoacoustic and elastic data show that MPI is less sensitive than FWI to some of the unmodeled physics. Inversion of marine data shows that MPI is more robust and produces modestly more accurate results than FWI for this data set.

  9. Integrated genomic and gene expression profiling identifies two major genomic circuits in urothelial carcinoma.

    Directory of Open Access Journals (Sweden)

    David Lindgren

    Full Text Available Similar to other malignancies, urothelial carcinoma (UC is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21, and BCL2L1 (20q11. We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.

  10. Integration of experimental and computational methods for identifying geometric, thermal and diffusive properties of biomaterials

    Science.gov (United States)

    Weres, Jerzy; Kujawa, Sebastian; Olek, Wiesław; Czajkowski, Łukasz

    2016-04-01

    Knowledge of physical properties of biomaterials is important in understanding and designing agri-food and wood processing industries. In the study presented in this paper computational methods were developed and combined with experiments to enhance identification of agri-food and forest product properties, and to predict heat and water transport in such products. They were based on the finite element model of heat and water transport and supplemented with experimental data. Algorithms were proposed for image processing, geometry meshing, and inverse/direct finite element modelling. The resulting software system was composed of integrated subsystems for 3D geometry data acquisition and mesh generation, for 3D geometry modelling and visualization, and for inverse/direct problem computations for the heat and water transport processes. Auxiliary packages were developed to assess performance, accuracy and unification of data access. The software was validated by identifying selected properties and using the estimated values to predict the examined processes, and then comparing predictions to experimental data. The geometry, thermal conductivity, specific heat, coefficient of water diffusion, equilibrium water content and convective heat and water transfer coefficients in the boundary layer were analysed. The estimated values, used as an input for simulation of the examined processes, enabled reduction in the uncertainty associated with predictions.

  11. A new method to identify the foot of continental slope based on an integrated profile analysis

    Science.gov (United States)

    Wu, Ziyin; Li, Jiabiao; Li, Shoujun; Shang, Jihong; Jin, Xiaobin

    2017-06-01

    A new method is proposed to identify automatically the foot of the continental slope (FOS) based on the integrated analysis of topographic profiles. Based on the extremum points of the second derivative and the Douglas-Peucker algorithm, it simplifies the topographic profiles, then calculates the second derivative of the original profiles and the D-P profiles. Seven steps are proposed to simplify the original profiles. Meanwhile, multiple identification methods are proposed to determine the FOS points, including gradient, water depth and second derivative values of data points, as well as the concave and convex, continuity and segmentation of the topographic profiles. This method can comprehensively and intelligently analyze the topographic profiles and their derived slopes, second derivatives and D-P profiles, based on which, it is capable to analyze the essential properties of every single data point in the profile. Furthermore, it is proposed to remove the concave points of the curve and in addition, to implement six FOS judgment criteria.

  12. Identifying essential proteins based on sub-network partition and prioritization by integrating subcellular localization information.

    Science.gov (United States)

    Li, Min; Li, Wenkai; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

    2018-06-14

    Essential proteins are important participants in various life activities and play a vital role in the survival and reproduction of living organisms. Identification of essential proteins from protein-protein interaction (PPI) networks has great significance to facilitate the study of human complex diseases, the design of drugs and the development of bioinformatics and computational science. Studies have shown that highly connected proteins in a PPI network tend to be essential. A series of computational methods have been proposed to identify essential proteins by analyzing topological structures of PPI networks. However, the high noise in the PPI data can degrade the accuracy of essential protein prediction. Moreover, proteins must be located in the appropriate subcellular localization to perform their functions, and only when the proteins are located in the same subcellular localization, it is possible that they can interact with each other. In this paper, we propose a new network-based essential protein discovery method based on sub-network partition and prioritization by integrating subcellular localization information, named SPP. The proposed method SPP was tested on two different yeast PPI networks obtained from DIP database and BioGRID database. The experimental results show that SPP can effectively reduce the effect of false positives in PPI networks and predict essential proteins more accurately compared with other existing computational methods DC, BC, CC, SC, EC, IC, NC. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. Integrative genomic analysis identifies isoleucine and CodY as regulators of Listeria monocytogenes virulence.

    Directory of Open Access Journals (Sweden)

    Lior Lobel

    2012-09-01

    Full Text Available Intracellular bacterial pathogens are metabolically adapted to grow within mammalian cells. While these adaptations are fundamental to the ability to cause disease, we know little about the relationship between the pathogen's metabolism and virulence. Here we used an integrative Metabolic Analysis Tool that combines transcriptome data with genome-scale metabolic models to define the metabolic requirements of Listeria monocytogenes during infection. Twelve metabolic pathways were identified as differentially active during L. monocytogenes growth in macrophage cells. Intracellular replication requires de novo synthesis of histidine, arginine, purine, and branch chain amino acids (BCAAs, as well as catabolism of L-rhamnose and glycerol. The importance of each metabolic pathway during infection was confirmed by generation of gene knockout mutants in the respective pathways. Next, we investigated the association of these metabolic requirements in the regulation of L. monocytogenes virulence. Here we show that limiting BCAA concentrations, primarily isoleucine, results in robust induction of the master virulence activator gene, prfA, and the PrfA-regulated genes. This response was specific and required the nutrient responsive regulator CodY, which is known to bind isoleucine. Further analysis demonstrated that CodY is involved in prfA regulation, playing a role in prfA activation under limiting conditions of BCAAs. This study evidences an additional regulatory mechanism underlying L. monocytogenes virulence, placing CodY at the crossroads of metabolism and virulence.

  14. Physical interpretation of the J2 integral by identifying the associated crack translation

    International Nuclear Information System (INIS)

    Liu, Cong Hao; Chu, Seok Jae

    2016-01-01

    The physical interpretation of the J integral (i.e., J 1 integral) is clear. J 1 integral is the energy release rate associated with crack extension(i.e., translation of the crack in the x 1 direction). However, the physical interpretation of the J 2 integral remains unclear. In this study, different crack translations in the x 2 direction were selected and tested by calculating the energy release rates associated with the crack translations and comparing them with the theoretical value of the J 2 integral.

  15. An integrative -omics approach to identify functional sub-networks in human colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Rod K Nibbe

    2010-01-01

    Full Text Available Emerging evidence indicates that gene products implicated in human cancers often cluster together in "hot spots" in protein-protein interaction (PPI networks. Additionally, small sub-networks within PPI networks that demonstrate synergistic differential expression with respect to tumorigenic phenotypes were recently shown to be more accurate classifiers of disease progression when compared to single targets identified by traditional approaches. However, many of these studies rely exclusively on mRNA expression data, a useful but limited measure of cellular activity. Proteomic profiling experiments provide information at the post-translational level, yet they generally screen only a limited fraction of the proteome. Here, we demonstrate that integration of these complementary data sources with a "proteomics-first" approach can enhance the discovery of candidate sub-networks in cancer that are well-suited for mechanistic validation in disease. We propose that small changes in the mRNA expression of multiple genes in the neighborhood of a protein-hub can be synergistically associated with significant changes in the activity of that protein and its network neighbors. Further, we hypothesize that proteomic targets with significant fold change between phenotype and control may be used to "seed" a search for small PPI sub-networks that are functionally associated with these targets. To test this hypothesis, we select proteomic targets having significant expression changes in human colorectal cancer (CRC from two independent 2-D gel-based screens. Then, we use random walk based models of network crosstalk and develop novel reference models to identify sub-networks that are statistically significant in terms of their functional association with these proteomic targets. Subsequently, using an information-theoretic measure, we evaluate synergistic changes in the activity of identified sub-networks based on genome-wide screens of mRNA expression in CRC

  16. Multiscale modeling of mucosal immune responses

    Science.gov (United States)

    2015-01-01

    Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut

  17. Multiscale modeling of mucosal immune responses.

    Science.gov (United States)

    Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep

    2015-01-01

    Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T

  18. Towards distributed multiscale computing for the VPH

    NARCIS (Netherlands)

    Hoekstra, A.G.; Coveney, P.

    2010-01-01

    Multiscale modeling is fundamental to the Virtual Physiological Human (VPH) initiative. Most detailed three-dimensional multiscale models lead to prohibitive computational demands. As a possible solution we present MAPPER, a computational science infrastructure for Distributed Multiscale Computing

  19. A Multi-Scale Settlement Matching Algorithm Based on ARG

    Science.gov (United States)

    Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia

    2016-06-01

    Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.

  20. A Multi-Scale Settlement Matching Algorithm Based on ARG

    Directory of Open Access Journals (Sweden)

    H. Yue

    2016-06-01

    Full Text Available Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.

  1. Identifying and assessing the risk of opioid abuse in patients with cancer: an integrative review

    Directory of Open Access Journals (Sweden)

    Carmichael AN

    2016-06-01

    Full Text Available Ashley-Nicole Carmichael,1 Laura Morgan,1 Egidio Del Fabbro2 1School of Pharmacy, 2Division of Hematology, Oncology, and Palliative Care, Virginia Commonwealth University, Richmond, VA, USA Background: The misuse and abuse of opioid medications in many developed nations is a health crisis, leading to increased health-system utilization, emergency department visits, and overdose deaths. There are also increasing concerns about opioid abuse and diversion in patients with cancer, even at the end of life. Aims: To evaluate the current literature on opioid misuse and abuse, and more specifically the identification and assessment of opioid-abuse risk in patients with cancer. Our secondary aim is to offer the most current evidence of best clinical practice and suggest future directions for research. Materials and methods: Our integrative review included a literature search using the key terms “identification and assessment of opioid abuse in cancer”, “advanced cancer and opioid abuse”, “hospice and opioid abuse”, and “palliative care and opioid abuse”. PubMed, PsycInfo, and Embase were supplemented by a manual search. Results: We found 691 articles and eliminated 657, because they were predominantly noncancer populations or specifically excluded cancer patients. A total of 34 articles met our criteria, including case studies, case series, retrospective observational studies, and narrative reviews. The studies were categorized into screening questionnaires for opioid abuse or alcohol, urine drug screens to identify opioid misuse or abuse, prescription drug-monitoring programs, and the use of universal precautions. Conclusion: Screening questionnaires and urine drug screens indicated at least one in five patients with cancer may be at risk of opioid-use disorder. Several studies demonstrated associations between high-risk patients and clinical outcomes, such as aberrant behavior, prolonged opioid use, higher morphine-equivalent daily dose

  2. Multiscale singularity trees

    DEFF Research Database (Denmark)

    Somchaipeng, Kerawit; Sporring, Jon; Johansen, Peter

    2007-01-01

    We propose MultiScale Singularity Trees (MSSTs) as a structure to represent images, and we propose an algorithm for image comparison based on comparing MSSTs. The algorithm is tested on 3 public image databases and compared to 2 state-of-theart methods. We conclude that the computational complexity...... of our algorithm only allows for the comparison of small trees, and that the results of our method are comparable with state-of-the-art using much fewer parameters for image representation....

  3. Multiscale modelling of nanostructures

    International Nuclear Information System (INIS)

    Vvedensky, Dimitri D

    2004-01-01

    Most materials phenomena are manifestations of processes that are operative over a vast range of length and time scales. A complete understanding of the behaviour of materials thereby requires theoretical and computational tools that span the atomic-scale detail of first-principles methods and the more coarse-grained description provided by continuum equations. Recent efforts have focused on combining traditional methodologies-density functional theory, molecular dynamics, Monte Carlo methods and continuum descriptions-within a unified multiscale framework. This review covers the techniques that have been developed to model various aspects of materials behaviour with the ultimate aim of systematically coupling the atomistic to the continuum descriptions. The approaches described typically have been motivated by particular applications but can often be applied in wider contexts. The self-assembly of quantum dot ensembles will be used as a case study for the issues that arise and the methods used for all nanostructures. Although quantum dots can be obtained with all the standard growth methods and for a variety of material systems, their appearance is a quite selective process, involving the competition between equilibrium and kinetic effects, and the interplay between atomistic and long-range interactions. Most theoretical models have addressed particular aspects of the ordering kinetics of quantum dot ensembles, with far fewer attempts at a comprehensive synthesis of this inherently multiscale phenomenon. We conclude with an assessment of the current status of multiscale modelling strategies and highlight the main outstanding issues. (topical review)

  4. Quantum theory of multiscale coarse-graining.

    Science.gov (United States)

    Han, Yining; Jin, Jaehyeok; Wagner, Jacob W; Voth, Gregory A

    2018-03-14

    Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.

  5. Quantum theory of multiscale coarse-graining

    Science.gov (United States)

    Han, Yining; Jin, Jaehyeok; Wagner, Jacob W.; Voth, Gregory A.

    2018-03-01

    Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.

  6. Integrated Analysis of Genetic and Proteomic Data Identifies Biomarkers Associated with Adverse Events Following Smallpox Vaccination

    Science.gov (United States)

    Complex clinical outcomes, such as adverse reaction to vaccination, arise from the concerted interactions among the myriad components of a biological system. Therefore, comprehensive etiological models can be developed only through the integrated study of multiple types of experi...

  7. An approach to multiscale modelling with graph grammars.

    Science.gov (United States)

    Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried

    2014-09-01

    Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.

  8. Multiscale Signal Analysis and Modeling

    CERN Document Server

    Zayed, Ahmed

    2013-01-01

    Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...

  9. Adaptive multiscale processing for contrast enhancement

    Science.gov (United States)

    Laine, Andrew F.; Song, Shuwu; Fan, Jian; Huda, Walter; Honeyman, Janice C.; Steinbach, Barbara G.

    1993-07-01

    This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

  10. Multiscale computing in the exascale era

    NARCIS (Netherlands)

    Alowayyed, S.; Groen, D.; Coveney, P.V.; Hoekstra, A.G.

    We expect that multiscale simulations will be one of the main high performance computing workloads in the exascale era. We propose multiscale computing patterns as a generic vehicle to realise load balanced, fault tolerant and energy aware high performance multiscale computing. Multiscale computing

  11. Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer

    NARCIS (Netherlands)

    Peifer, Martin; Fernandez-Cuesta, Lynnette; Sos, Martin L.; George, Julie; Seidel, Danila; Kasper, Lawryn H.; Plenker, Dennis; Leenders, Frauke; Sun, Ruping; Zander, Thomas; Menon, Roopika; Koker, Mirjam; Dahmen, Ilona; Mueller, Christian; Di Cerbo, Vincenzo; Schildhaus, Hans-Ulrich; Altmueller, Janine; Baessmann, Ingelore; Becker, Christian; de Wilde, Bram; Vandesompele, Jo; Boehm, Diana; Ansen, Sascha; Gabler, Franziska; Wilkening, Ines; Heynck, Stefanie; Heuckmann, Johannes M.; Lu, Xin; Carter, Scott L.; Cibulskis, Kristian; Banerji, Shantanu; Getz, Gad; Park, Kwon-Sik; Rauh, Daniel; Gruetter, Christian; Fischer, Matthias; Pasqualucci, Laura; Wright, Gavin; Wainer, Zoe; Russell, Prudence; Petersen, Iver; Chen, Yuan; Stoelben, Erich; Ludwig, Corinna; Schnabel, Philipp; Hoffmann, Hans; Muley, Thomas; Brockmann, Michael; Engel-Riedel, Walburga; Muscarella, Lucia A.; Fazio, Vito M.; Groen, Harry; Timens, Wim; Sietsma, Hannie; Thunnissen, Erik; Smit, Egbert; Heideman, Danielle A. M.; Snijders, Peter J. F.; Cappuzzo, Federico; Ligorio, Claudia; Damiani, Stefania; Field, John; Solberg, Steinar; Brustugun, Odd Terje; Lund-Iversen, Marius; Saenger, Joerg; Clement, Joachim H.; Soltermann, Alex; Moch, Holger; Weder, Walter; Solomon, Benjamin; Soria, Jean-Charles; Validire, Pierre; Besse, Benjamin; Brambilla, Elisabeth; Brambilla, Christian; Lantuejoul, Sylvie; Lorimier, Philippe; Schneider, Peter M.; Hallek, Michael; Pao, William; Meyerson, Matthew; Sage, Julien; Shendure, Jay; Schneider, Robert; Buettner, Reinhard; Wolf, Juergen; Nuernberg, Peter; Perner, Sven; Heukamp, Lukas C.; Brindle, Paul K.; Haas, Stefan; Thomas, Roman K.

    2012-01-01

    Small-cell lung cancer (SCLC) is an aggressive lung tumor subtype with poor prognosis(1-3). We sequenced 29 SCLC exomes, 2 genomes and 15 transcriptomes and found an extremely high mutation rate of 7.4 +/- 1 protein-changing mutations per million base pairs. Therefore, we conducted integrated

  12. Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles

    DEFF Research Database (Denmark)

    Farshidfar, Farshad; Zheng, Siyuan; Gingras, Marie-Claude

    2017-01-01

    Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahep...

  13. Issues and Challenges Identified in the Development of a Broad Multidisciplinary Work Integrated Learning Package

    Science.gov (United States)

    Sutherland, Karen; Symmons, Mark

    2013-01-01

    Work integrated learning (WIL) units can be discipline specific and constructed for majors or degrees with a strong vocational orientation. This paper describes an undergraduate unit with its genesis in a public relations internship. The original unit enjoyed strong support from industry partners and was instrumental in many graduates securing…

  14. Integrated Pathway-Based Approach Identifies Association between Genomic Regions at CTCF and CACNB2 and Schizophrenia

    NARCIS (Netherlands)

    Juraeva, Dilafruz; Haenisch, Britta; Zapatka, Marc; Frank, Josef; Witt, Stephanie H.; Mühleisen, Thomas W.; Treutlein, Jens; Strohmaier, Jana; Meier, Sandra; Degenhardt, Franziska; Giegling, Ina; Ripke, Stephan; Leber, Markus; Lange, Christoph; Schulze, Thomas G.; Mössner, Rainald; Nenadic, Igor; Sauer, Heinrich; Rujescu, Dan; Maier, Wolfgang; Børglum, Anders; Ophoff, Roel; Cichon, Sven; Nöthen, Markus M.; Rietschel, Marcella; Mattheisen, Manuel; Brors, Benedikt; Kahn, René S.; Cahn, Wiepke; Linszen, Don H.; de Haan, Lieuwe; van Os, Jim; Krabbendam, Lydia; Myin-Germeys, Inez; Wiersma, Durk; Bruggeman, Richard; Mors, O.; Børglum, A. D.; Mortensen, P. B.; Pedersen, C. B.; Demontis, D.; Grove, J.; Mattheisen, M.; Hougaard, D. M.

    2014-01-01

    In the present study, an integrated hierarchical approach was applied to: (1) identify pathways associated with susceptibility to schizophrenia; (2) detect genes that may be potentially affected in these pathways since they contain an associated polymorphism; and (3) annotate the functional

  15. MULTISCALE THERMOHYDROLOGIC MODEL

    International Nuclear Information System (INIS)

    T. Buscheck

    2005-01-01

    The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting

  16. MULTISCALE THERMOHYDROLOGIC MODEL

    Energy Technology Data Exchange (ETDEWEB)

    T. Buscheck

    2005-07-07

    The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting

  17. Integration and Interoperability: An Analysis to Identify the Attributes for System of Systems

    Science.gov (United States)

    2008-09-01

    divisions of the enterprise. Examples of the current I2 are: • a nightly feed of elearning information is captured through an automated and...standardized process throughout the enterprise and • the LMS has been integrated with SkillSoft, a third party elearning software system, (http...Command (JITC) is responsible to test all programs that utilize standard interfaces to specific global nets or systems. Many times programs that

  18. An Integrated Strategy to Identify Key Genes in Almond Adventitious Shoot Regeneration

    Science.gov (United States)

    Plant genetic transformation usually depends on efficient adventitious regeneration systems. In almond (Prunus dulcis Mill.), regeneration of transgenic adventitious shoots was achieved but with low efficiency. Histological studies identified two main stages of organogenesis in almond explants that ...

  19. An optimization methodology for identifying robust process integration investments under uncertainty

    International Nuclear Information System (INIS)

    Svensson, Elin; Berntsson, Thore; Stroemberg, Ann-Brith; Patriksson, Michael

    2009-01-01

    Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)

  20. An optimization methodology for identifying robust process integration investments under uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden); Patriksson, Michael [Department of Mathematical Sciences, Chalmers University of Technology and Department of Mathematical Sciences, University of Gothenburg, SE-412 96 Goeteborg (Sweden)

    2009-02-15

    Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)

  1. Bridging scales through multiscale modeling: A case study on Protein Kinase A

    Directory of Open Access Journals (Sweden)

    Sophia P Hirakis

    2015-09-01

    Full Text Available The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM, subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.

  2. Multiscale principal component analysis

    International Nuclear Information System (INIS)

    Akinduko, A A; Gorban, A N

    2014-01-01

    Principal component analysis (PCA) is an important tool in exploring data. The conventional approach to PCA leads to a solution which favours the structures with large variances. This is sensitive to outliers and could obfuscate interesting underlying structures. One of the equivalent definitions of PCA is that it seeks the subspaces that maximize the sum of squared pairwise distances between data projections. This definition opens up more flexibility in the analysis of principal components which is useful in enhancing PCA. In this paper we introduce scales into PCA by maximizing only the sum of pairwise distances between projections for pairs of datapoints with distances within a chosen interval of values [l,u]. The resulting principal component decompositions in Multiscale PCA depend on point (l,u) on the plane and for each point we define projectors onto principal components. Cluster analysis of these projectors reveals the structures in the data at various scales. Each structure is described by the eigenvectors at the medoid point of the cluster which represent the structure. We also use the distortion of projections as a criterion for choosing an appropriate scale especially for data with outliers. This method was tested on both artificial distribution of data and real data. For data with multiscale structures, the method was able to reveal the different structures of the data and also to reduce the effect of outliers in the principal component analysis

  3. Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

    Science.gov (United States)

    Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

    2016-09-09

    Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators

  4. Elucidating novel dysfunctional pathways in Alzheimer's disease by integrating loci identified in genetic and epigenetic studies

    Directory of Open Access Journals (Sweden)

    Adam R. Smith

    2016-06-01

    Full Text Available Alzheimer's disease is a complex neurodegenerative disorder. A large number of genome-wide association studies have been performed, which have been supplemented more recently by the first epigenome-wide association studies, leading to the identification of a number of novel loci altered in disease. Twin studies have shown monozygotic twin discordance for Alzheimer's disease (Gatz et al., 2006, leading to the conclusion that a combination of genetic and epigenetic mechanisms is likely to be involved in disease etiology (Lunnon & Mill, 2013. This review focuses on identifying overlapping pathways between published genome-wide association studies and epigenome-wide association studies, highlighting dysfunctional synaptic, lipid metabolism, plasma membrane/cytoskeleton, mitochondrial, and immune cell activation pathways. Identifying common pathways altered in genetic and epigenetic studies will aid our understanding of disease mechanisms and identify potential novel targets for pharmacological intervention.

  5. Multiscale agent-based cancer modeling.

    Science.gov (United States)

    Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

    2009-04-01

    Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

  6. An integrated approach to identify the origin of PM10 exceedances.

    Science.gov (United States)

    Amodio, M; Andriani, E; de Gennaro, G; Demarinis Loiotile, A; Di Gilio, A; Placentino, M C

    2012-09-01

    This study was aimed to the development of an integrated approach for the characterization of particulate matter (PM) pollution events in the South of Italy. PM(10) and PM(2.5) daily samples were collected from June to November 2008 at an urban background site located in Bari (Puglia Region, South of Italy). Meteorological data, particle size distributions and atmospheric dispersion conditions were also monitored in order to provide information concerning the different features of PM sources. The collected data allowed suggesting four indicators to characterize different PM(10) exceedances. PM(2.5)/PM(10) ratio, natural radioactivity, aerosol maps and back-trajectory analysis and particle distributions were considered in order to evaluate the contribution of local anthropogenic sources and to determine the different origins of intrusive air mass coming from long-range transport, such as African dust outbreaks and aerosol particles from Central and Eastern Europe. The obtained results were confirmed by applying principal component analysis to the number particle concentration dataset and by the chemical characterization of the samples (PM(10) and PM(2.5)). The integrated approach for PM study suggested in this paper can be useful to support the air quality managers for the development of cost-effective control strategies and the application of more suitable risk management approaches.

  7. An Integrated Model for Identifying Linkages Between the Management of Fuel Treatments, Fire and Ecosystem Services

    Science.gov (United States)

    Bart, R. R.; Anderson, S.; Moritz, M.; Plantinga, A.; Tague, C.

    2015-12-01

    Vegetation fuel treatments (e.g. thinning, prescribed burning) are a frequent tool for managing fire-prone landscapes. However, predicting how fuel treatments may affect future wildfire risk and associated ecosystem services, such as forest water availability and streamflow, remains a challenge. This challenge is in part due to the large range of conditions under which fuel treatments may be implemented, as response is likely to vary with species type, rates of vegetation regrowth, meteorological conditions and physiographic properties of the treated site. It is also due to insufficient understanding of how social factors such as political pressure, public demands and economic constraints affect fuel management decisions. To examine the feedbacks between ecological and social dimensions of fuel treatments, we present an integrated model that links a biophysical model that simulates vegetation and hydrology (RHESSys), a fire spread model (WMFire) and an empirical fuel treatment model that accounts for agency decision-making. We use this model to investigate how management decisions affect landscape fuel loads, which in turn affect fire severity and ecosystem services, which feedback to management decisions on fuel treatments. We hypothesize that this latter effect will be driven by salience theory, which predicts that fuel treatments are more likely to occur following major wildfire events. The integrated model provides a flexible framework for answering novel questions about fuel treatments that span social and ecological domains, areas that have previously been treated separately.

  8. Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

    Energy Technology Data Exchange (ETDEWEB)

    Stander, Nielen [Livermore Software Technology Corporation, CA (United States); Basudhar, Anirban [Livermore Software Technology Corporation, CA (United States); Basu, Ushnish [Livermore Software Technology Corporation, CA (United States); Gandikota, Imtiaz [Livermore Software Technology Corporation, CA (United States); Savic, Vesna [General Motors, Flint, MI (United States); Sun, Xin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hu, XiaoHua [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pourboghrat, Farhang [The Ohio State Univ., Columbus, OH (United States); Park, Taejoon [The Ohio State Univ., Columbus, OH (United States); Mapar, Aboozar [Michigan State Univ., East Lansing, MI (United States); Kumar, Sharvan [Brown Univ., Providence, RI (United States); Ghassemi-Armaki, Hassan [Brown Univ., Providence, RI (United States); Abu-Farha, Fadi [Clemson Univ., SC (United States)

    2015-06-15

    Ever-tightening regulations on fuel economy and carbon emissions demand continual innovation in finding ways for reducing vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials by adding material diversity, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing thickness while retaining sufficient strength and ductility required for durability and safety. Such a project was proposed and is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the Department of Energy. Under this program, new steel alloys (Third Generation Advanced High Strength Steel or 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. In this project the principal phases identified are (i) material identification, (ii) formability optimization and (iii) multi-disciplinary vehicle optimization. This paper serves as an introduction to the LS-OPT methodology and therefore mainly focuses on the first phase, namely an approach to integrate material identification using material models of different length scales. For this purpose, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a Homogenized State Variable (SV) model, is discussed and demonstrated. The paper concludes with proposals for integrating the multi-scale methodology into the overall vehicle design.

  9. Integrating Stakeholder Preferences and GIS-Based Multicriteria Analysis to Identify Forest Landscape Restoration Priorities

    Directory of Open Access Journals (Sweden)

    David Uribe

    2014-02-01

    Full Text Available A pressing question that arises during the planning of an ecological restoration process is: where to restore first? Answering this question is a complex task; it requires a multidimensional approach to consider economic constrains and the preferences of stakeholders. Being the problem of spatial nature, it may be explored effectively through Multicriteria Decision Analysis (MCDA performed in a Geographical Information System (GIS environment. The proposed approach is based on the definition and weighting of multiple criteria for evaluating land suitability. An MCDA-based methodology was used to identify priority areas for Forest Landscape Restoration in the Upper Mixtec region, Oaxaca (Mexico, one of the most degraded areas of Latin America. Socioeconomic and environmental criteria were selected and evaluated. The opinions of four different stakeholder groups were considered: general public, academic, Non-governmental organizations (NGOs and governmental officers. The preferences of these groups were spatially modeled to identify their priorities. The final result was a map that identifies the most preferable sites for restoration, where resources and efforts should be concentrated. MCDA proved to be a very useful tool in collective planning, when alternative sites have to be identified and prioritized to guide the restoration work.

  10. Integrating genetic, transcriptional, and functional analyses to identify 5 novel genes for atrial fibrillation

    DEFF Research Database (Denmark)

    Sinner, Moritz F; Tucker, Nathan R; Lunetta, Kathryn L

    2014-01-01

    BACKGROUND: Atrial fibrillation (AF) affects >30 million individuals worldwide and is associated with an increased risk of stroke, heart failure, and death. AF is highly heritable, yet the genetic basis for the arrhythmia remains incompletely understood. METHODS AND RESULTS: To identify new AF-re...

  11. Identifying Technical Procedures in Pulmonary Medicine That Should Be Integrated in a Simulation-Based Curriculum

    DEFF Research Database (Denmark)

    Nayahangan, Leizl Joy; Clementsen, Paul Frost; Paltved, Charlotte

    2016-01-01

    of visible lymph node/tumor of the skin, focused ultrasound scanning of the heart, and thoracoscopy. Conclusion: We performed a Delphi study using a needs assessment formula, which identified 11 technical procedures that are highly suitable for simulation-based training. Medical educators can use this list...

  12. Newly identified protein Imi1 affects mitochondrial integrity and glutathione homeostasis in Saccharomyces cerevisiae.

    Science.gov (United States)

    Kowalec, Piotr; Grynberg, Marcin; Pająk, Beata; Socha, Anna; Winiarska, Katarzyna; Fronk, Jan; Kurlandzka, Anna

    2015-09-01

    Glutathione homeostasis is crucial for cell functioning. We describe a novel Imi1 protein of Saccharomyces cerevisiae affecting mitochondrial integrity and involved in controlling glutathione level. Imi1 is cytoplasmic and, except for its N-terminal Flo11 domain, has a distinct solenoid structure. A lack of Imi1 leads to mitochondrial lesions comprising aberrant morphology of cristae and multifarious mtDNA rearrangements and impaired respiration. The mitochondrial malfunctioning is coupled to significantly decrease the level of intracellular reduced glutathione without affecting oxidized glutathione, which decreases the reduced/oxidized glutathione ratio. These defects are accompanied by decreased cadmium sensitivity and increased phytochelatin-2 level. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  13. Identifying Key Issues and Potential Solutions for Integrated Arrival, Departure, Surface Operations by Surveying Stakeholder Preferences

    Science.gov (United States)

    Aponso, Bimal; Coppenbarger, Richard A.; Jung, Yoon; Quon, Leighton; Lohr, Gary; O’Connor, Neil; Engelland, Shawn

    2015-01-01

    NASA's Aeronautics Research Mission Directorate (ARMD) collaborates with the FAA and industry to provide concepts and technologies that enhance the transition to the next-generation air-traffic management system (NextGen). To facilitate this collaboration, ARMD has a series of Airspace Technology Demonstration (ATD) sub-projects that develop, demonstrate, and transitions NASA technologies and concepts for implementation in the National Airspace System (NAS). The second of these sub-projects, ATD-2, is focused on the potential benefits to NAS stakeholders of integrated arrival, departure, surface (IADS) operations. To determine the project objectives and assess the benefits of a potential solution, NASA surveyed NAS stakeholders to understand the existing issues in arrival, departure, and surface operations, and the perceived benefits of better integrating these operations. NASA surveyed a broad cross-section of stakeholders representing the airlines, airports, air-navigation service providers, and industry providers of NAS tools. The survey indicated that improving the predictability of flight times (schedules) could improve efficiency in arrival, departure, and surface operations. Stakeholders also mentioned the need for better strategic and tactical information on traffic constraints as well as better information sharing and a coupled collaborative planning process that allows stakeholders to coordinate IADS operations. To assess the impact of a potential solution, NASA sketched an initial departure scheduling concept and assessed its viability by surveying a select group of stakeholders for a second time. The objective of the departure scheduler was to enable flights to move continuously from gate to cruise with minimal interruption in a busy metroplex airspace environment using strategic and tactical scheduling enhanced by collaborative planning between airlines and service providers. The stakeholders agreed that this departure concept could improve schedule

  14. Multiscale study of metal nanoparticles

    Science.gov (United States)

    Lee, Byeongchan

    Extremely small structures with reduced dimensionality have emerged as a scientific motif for their interesting properties. In particular, metal nanoparticles have been identified as a fundamental material in many catalytic activities; as a consequence, a better understanding of structure-function relationship of nanoparticles has become crucial. The functional analysis of nanoparticles, reactivity for example, requires an accurate method at the electronic structure level, whereas the structural analysis to find energetically stable local minima is beyond the scope of quantum mechanical methods as the computational cost becomes prohibitingly high. The challenge is that the inherent length scale and accuracy associated with any single method hardly covers the broad scale range spanned by both structural and functional analyses. In order to address this, and effectively explore the energetics and reactivity of metal nanoparticles, a hierarchical multiscale modeling is developed, where methodologies of different length scales, i.e. first principles density functional theory, atomistic calculations, and continuum modeling, are utilized in a sequential fashion. This work has focused on identifying the essential information that bridges two different methods so that a successive use of different methods is seamless. The bond characteristics of low coordination systems have been obtained with first principles calculations, and incorporated into the atomistic simulation. This also rectifies the deficiency of conventional interatomic potentials fitted to bulk properties, and improves the accuracy of atomistic calculations for nanoparticles. For the systematic shape selection of nanoparticles, we have improved the Wulff-type construction using a semi-continuum approach, in which atomistic surface energetics and crystallinity of materials are added on to the continuum framework. The developed multiscale modeling scheme is applied to the rational design of platinum

  15. An Integrated Approach to Change the Outcome Part II: Targeted Neuromuscular Training Techniques to Reduce Identified ACL Injury Risk Factors

    Science.gov (United States)

    Myer, Gregory D.; Ford, Kevin R.; Brent, Jensen L.; Hewett, Timothy E.

    2014-01-01

    Prior reports indicate that female athletes who demonstrate high knee abduction moments (KAMs) during landing are more responsive to neuromuscular training designed to reduce KAM. Identification of female athletes who demonstrate high KAM, which accurately identifies those at risk for noncontact anterior cruciate ligament (ACL) injury, may be ideal for targeted neuromuscular training. Specific neuromuscular training targeted to the underlying biomechanical components that increase KAM may provide the most efficient and effective training strategy to reduce noncontact ACL injury risk. The purpose of the current commentary is to provide an integrative approach to identify and target mechanistic underpinnings to increased ACL injury in female athletes. Specific neuromuscular training techniques will be presented that address individual algorithm components related to high knee load landing patterns. If these integrated techniques are employed on a widespread basis, prevention strategies for noncontact ACL injury among young female athletes may prove both more effective and efficient. PMID:22580980

  16. Integrating modelling and phenotyping approaches to identify and screen complex traits - Illustration for transpiration efficiency in cereals.

    Science.gov (United States)

    Chenu, K; van Oosterom, E J; McLean, G; Deifel, K S; Fletcher, A; Geetika, G; Tirfessa, A; Mace, E S; Jordan, D R; Sulman, R; Hammer, G L

    2018-02-21

    Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plants and with their environments, and to target traits of most relevance for the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to identify traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their values in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding program. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programs for improving yield gains in target populations of environments.

  17. An Integrated H-G Scheme Identifying Areas for Soil Remediation and Primary Heavy Metal Contributors: A Risk Perspective

    OpenAIRE

    Bin Zou; Xiaolu Jiang; Xiaoli Duan; Xiuge Zhao; Jing Zhang; Jingwen Tang; Guoqing Sun

    2017-01-01

    Traditional sampling for soil pollution evaluation is cost intensive and has limited representativeness. Therefore, developing methods that can accurately and rapidly identify at-risk areas and the contributing pollutants is imperative for soil remediation. In this study, we propose an innovative integrated H-G scheme combining human health risk assessment and geographical detector methods that was based on geographical information system technology and validated its feasibility in a renewabl...

  18. GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets.

    Directory of Open Access Journals (Sweden)

    John Patrick Mpindi

    Full Text Available BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type ('outlier genes', a hallmark of potential oncogenes. METHODOLOGY: A new statistical method (the gene tissue index, GTI was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29 of these genes, and 17 of these 19 genes (90% showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. CONCLUSIONS/SIGNIFICANCE: Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is

  19. Integrated genomics identifies five medulloblastoma subtypes with distinct genetic profiles, pathway signatures and clinicopathological features.

    Directory of Open Access Journals (Sweden)

    Marcel Kool

    Full Text Available BACKGROUND: Medulloblastoma is the most common malignant brain tumor in children. Despite recent improvements in cure rates, prediction of disease outcome remains a major challenge and survivors suffer from serious therapy-related side-effects. Recent data showed that patients with WNT-activated tumors have a favorable prognosis, suggesting that these patients could be treated less intensively, thereby reducing the side-effects. This illustrates the potential benefits of a robust classification of medulloblastoma patients and a detailed knowledge of associated biological mechanisms. METHODS AND FINDINGS: To get a better insight into the molecular biology of medulloblastoma we established mRNA expression profiles of 62 medulloblastomas and analyzed 52 of them also by comparative genomic hybridization (CGH arrays. Five molecular subtypes were identified, characterized by WNT signaling (A; 9 cases, SHH signaling (B; 15 cases, expression of neuronal differentiation genes (C and D; 16 and 11 cases, respectively or photoreceptor genes (D and E; both 11 cases. Mutations in beta-catenin were identified in all 9 type A tumors, but not in any other tumor. PTCH1 mutations were exclusively identified in type B tumors. CGH analysis identified several fully or partly subtype-specific chromosomal aberrations. Monosomy of chromosome 6 occurred only in type A tumors, loss of 9q mostly occurred in type B tumors, whereas chromosome 17 aberrations, most common in medulloblastoma, were strongly associated with type C or D tumors. Loss of the inactivated X-chromosome was highly specific for female cases of type C, D and E tumors. Gene expression levels faithfully reflected the chromosomal copy number changes. Clinicopathological features significantly different between the 5 subtypes included metastatic disease and age at diagnosis and histology. Metastatic disease at diagnosis was significantly associated with subtypes C and D and most strongly with subtype E

  20. Integration of transcriptome and whole genomic resequencing data to identify key genes affecting swine fat deposition.

    Directory of Open Access Journals (Sweden)

    Kai Xing

    Full Text Available Fat deposition is highly correlated with the growth, meat quality, reproductive performance and immunity of pigs. Fatty acid synthesis takes place mainly in the adipose tissue of pigs; therefore, in this study, a high-throughput massively parallel sequencing approach was used to generate adipose tissue transcriptomes from two groups of Songliao black pigs that had opposite backfat thickness phenotypes. The total number of paired-end reads produced for each sample was in the range of 39.29-49.36 millions. Approximately 188 genes were differentially expressed in adipose tissue and were enriched for metabolic processes, such as fatty acid biosynthesis, lipid synthesis, metabolism of fatty acids, etinol, caffeine and arachidonic acid and immunity. Additionally, many genetic variations were detected between the two groups through pooled whole-genome resequencing. Integration of transcriptome and whole-genome resequencing data revealed important genomic variations among the differentially expressed genes for fat deposition, for example, the lipogenic genes. Further studies are required to investigate the roles of candidate genes in fat deposition to improve pig breeding programs.

  1. An Integrated Bioinformatics and Computational Biology Approach Identifies New BH3-Only Protein Candidates.

    Science.gov (United States)

    Hawley, Robert G; Chen, Yuzhong; Riz, Irene; Zeng, Chen

    2012-05-04

    In this study, we utilized an integrated bioinformatics and computational biology approach in search of new BH3-only proteins belonging to the BCL2 family of apoptotic regulators. The BH3 (BCL2 homology 3) domain mediates specific binding interactions among various BCL2 family members. It is composed of an amphipathic α-helical region of approximately 13 residues that has only a few amino acids that are highly conserved across all members. Using a generalized motif, we performed a genome-wide search for novel BH3-containing proteins in the NCBI Consensus Coding Sequence (CCDS) database. In addition to known pro-apoptotic BH3-only proteins, 197 proteins were recovered that satisfied the search criteria. These were categorized according to α-helical content and predictive binding to BCL-xL (encoded by BCL2L1) and MCL-1, two representative anti-apoptotic BCL2 family members, using position-specific scoring matrix models. Notably, the list is enriched for proteins associated with autophagy as well as a broad spectrum of cellular stress responses such as endoplasmic reticulum stress, oxidative stress, antiviral defense, and the DNA damage response. Several potential novel BH3-containing proteins are highlighted. In particular, the analysis strongly suggests that the apoptosis inhibitor and DNA damage response regulator, AVEN, which was originally isolated as a BCL-xL-interacting protein, is a functional BH3-only protein representing a distinct subclass of BCL2 family members.

  2. Identifying gene-environment interactions in schizophrenia: contemporary challenges for integrated, large-scale investigations.

    Science.gov (United States)

    van Os, Jim; Rutten, Bart P; Myin-Germeys, Inez; Delespaul, Philippe; Viechtbauer, Wolfgang; van Zelst, Catherine; Bruggeman, Richard; Reininghaus, Ulrich; Morgan, Craig; Murray, Robin M; Di Forti, Marta; McGuire, Philip; Valmaggia, Lucia R; Kempton, Matthew J; Gayer-Anderson, Charlotte; Hubbard, Kathryn; Beards, Stephanie; Stilo, Simona A; Onyejiaka, Adanna; Bourque, Francois; Modinos, Gemma; Tognin, Stefania; Calem, Maria; O'Donovan, Michael C; Owen, Michael J; Holmans, Peter; Williams, Nigel; Craddock, Nicholas; Richards, Alexander; Humphreys, Isla; Meyer-Lindenberg, Andreas; Leweke, F Markus; Tost, Heike; Akdeniz, Ceren; Rohleder, Cathrin; Bumb, J Malte; Schwarz, Emanuel; Alptekin, Köksal; Üçok, Alp; Saka, Meram Can; Atbaşoğlu, E Cem; Gülöksüz, Sinan; Gumus-Akay, Guvem; Cihan, Burçin; Karadağ, Hasan; Soygür, Haldan; Cankurtaran, Eylem Şahin; Ulusoy, Semra; Akdede, Berna; Binbay, Tolga; Ayer, Ahmet; Noyan, Handan; Karadayı, Gülşah; Akturan, Elçin; Ulaş, Halis; Arango, Celso; Parellada, Mara; Bernardo, Miguel; Sanjuán, Julio; Bobes, Julio; Arrojo, Manuel; Santos, Jose Luis; Cuadrado, Pedro; Rodríguez Solano, José Juan; Carracedo, Angel; García Bernardo, Enrique; Roldán, Laura; López, Gonzalo; Cabrera, Bibiana; Cruz, Sabrina; Díaz Mesa, Eva Ma; Pouso, María; Jiménez, Estela; Sánchez, Teresa; Rapado, Marta; González, Emiliano; Martínez, Covadonga; Sánchez, Emilio; Olmeda, Ma Soledad; de Haan, Lieuwe; Velthorst, Eva; van der Gaag, Mark; Selten, Jean-Paul; van Dam, Daniella; van der Ven, Elsje; van der Meer, Floor; Messchaert, Elles; Kraan, Tamar; Burger, Nadine; Leboyer, Marion; Szoke, Andrei; Schürhoff, Franck; Llorca, Pierre-Michel; Jamain, Stéphane; Tortelli, Andrea; Frijda, Flora; Vilain, Jeanne; Galliot, Anne-Marie; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Bulzacka, Ewa; Charpeaud, Thomas; Tronche, Anne-Marie; De Hert, Marc; van Winkel, Ruud; Decoster, Jeroen; Derom, Catherine; Thiery, Evert; Stefanis, Nikos C; Sachs, Gabriele; Aschauer, Harald; Lasser, Iris; Winklbaur, Bernadette; Schlögelhofer, Monika; Riecher-Rössler, Anita; Borgwardt, Stefan; Walter, Anna; Harrisberger, Fabienne; Smieskova, Renata; Rapp, Charlotte; Ittig, Sarah; Soguel-dit-Piquard, Fabienne; Studerus, Erich; Klosterkötter, Joachim; Ruhrmann, Stephan; Paruch, Julia; Julkowski, Dominika; Hilboll, Desiree; Sham, Pak C; Cherny, Stacey S; Chen, Eric Y H; Campbell, Desmond D; Li, Miaoxin; Romeo-Casabona, Carlos María; Emaldi Cirión, Aitziber; Urruela Mora, Asier; Jones, Peter; Kirkbride, James; Cannon, Mary; Rujescu, Dan; Tarricone, Ilaria; Berardi, Domenico; Bonora, Elena; Seri, Marco; Marcacci, Thomas; Chiri, Luigi; Chierzi, Federico; Storbini, Viviana; Braca, Mauro; Minenna, Maria Gabriella; Donegani, Ivonne; Fioritti, Angelo; La Barbera, Daniele; La Cascia, Caterina Erika; Mulè, Alice; Sideli, Lucia; Sartorio, Rachele; Ferraro, Laura; Tripoli, Giada; Seminerio, Fabio; Marinaro, Anna Maria; McGorry, Patrick; Nelson, Barnaby; Amminger, G Paul; Pantelis, Christos; Menezes, Paulo R; Del-Ben, Cristina M; Gallo Tenan, Silvia H; Shuhama, Rosana; Ruggeri, Mirella; Tosato, Sarah; Lasalvia, Antonio; Bonetto, Chiara; Ira, Elisa; Nordentoft, Merete; Krebs, Marie-Odile; Barrantes-Vidal, Neus; Cristóbal, Paula; Kwapil, Thomas R; Brietzke, Elisa; Bressan, Rodrigo A; Gadelha, Ary; Maric, Nadja P; Andric, Sanja; Mihaljevic, Marina; Mirjanic, Tijana

    2014-07-01

    Recent years have seen considerable progress in epidemiological and molecular genetic research into environmental and genetic factors in schizophrenia, but methodological uncertainties remain with regard to validating environmental exposures, and the population risk conferred by individual molecular genetic variants is small. There are now also a limited number of studies that have investigated molecular genetic candidate gene-environment interactions (G × E), however, so far, thorough replication of findings is rare and G × E research still faces several conceptual and methodological challenges. In this article, we aim to review these recent developments and illustrate how integrated, large-scale investigations may overcome contemporary challenges in G × E research, drawing on the example of a large, international, multi-center study into the identification and translational application of G × E in schizophrenia. While such investigations are now well underway, new challenges emerge for G × E research from late-breaking evidence that genetic variation and environmental exposures are, to a significant degree, shared across a range of psychiatric disorders, with potential overlap in phenotype. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  3. Integrated expression analysis of muscle hypertrophy identifies Asb2 as a negative regulator of muscle mass

    Science.gov (United States)

    Davey, Jonathan R.; Watt, Kevin I.; Parker, Benjamin L.; Chaudhuri, Rima; Ryall, James G.; Cunningham, Louise; Qian, Hongwei; Sartorelli, Vittorio; Chamberlain, Jeffrey; James, David E.

    2016-01-01

    The transforming growth factor-β (TGF-β) signaling network is a critical regulator of skeletal muscle mass and function and, thus, is an attractive therapeutic target for combating muscle disease, but the underlying mechanisms of action remain undetermined. We report that follistatin-based interventions (which modulate TGF-β network activity) can promote muscle hypertrophy that ameliorates aging-associated muscle wasting. However, the muscles of old sarcopenic mice demonstrate reduced response to follistatin compared with healthy young-adult musculature. Quantitative proteomic and transcriptomic analyses of young-adult muscles identified a transcription/translation signature elicited by follistatin exposure, which included repression of ankyrin repeat and SOCS box protein 2 (Asb2). Increasing expression of ASB2 reduced muscle mass, thereby demonstrating that Asb2 is a TGF-β network–responsive negative regulator of muscle mass. In contrast to young-adult muscles, sarcopenic muscles do not exhibit reduced ASB2 abundance with follistatin exposure. Moreover, preventing repression of ASB2 in young-adult muscles diminished follistatin-induced muscle hypertrophy. These findings provide insight into the program of transcription and translation events governing follistatin-mediated adaptation of skeletal muscle attributes and identify Asb2 as a regulator of muscle mass implicated in the potential mechanistic dysfunction between follistatin-mediated muscle growth in young and old muscles. PMID:27182554

  4. SoftSearch: integration of multiple sequence features to identify breakpoints of structural variations.

    Directory of Open Access Journals (Sweden)

    Steven N Hart

    Full Text Available BACKGROUND: Structural variation (SV represents a significant, yet poorly understood contribution to an individual's genetic makeup. Advanced next-generation sequencing technologies are widely used to discover such variations, but there is no single detection tool that is considered a community standard. In an attempt to fulfil this need, we developed an algorithm, SoftSearch, for discovering structural variant breakpoints in Illumina paired-end next-generation sequencing data. SoftSearch combines multiple strategies for detecting SV including split-read, discordant read-pair, and unmated pairs. Co-localized split-reads and discordant read pairs are used to refine the breakpoints. RESULTS: We developed and validated SoftSearch using real and synthetic datasets. SoftSearch's key features are 1 not requiring secondary (or exhaustive primary alignment, 2 portability into established sequencing workflows, and 3 is applicable to any DNA-sequencing experiment (e.g. whole genome, exome, custom capture, etc.. SoftSearch identifies breakpoints from a small number of soft-clipped bases from split reads and a few discordant read-pairs which on their own would not be sufficient to make an SV call. CONCLUSIONS: We show that SoftSearch can identify more true SVs by combining multiple sequence features. SoftSearch was able to call clinically relevant SVs in the BRCA2 gene not reported by other tools while offering significantly improved overall performance.

  5. Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

    Science.gov (United States)

    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

  6. The Goddard multi-scale modeling system with unified physics

    Directory of Open Access Journals (Sweden)

    W.-K. Tao

    2009-08-01

    Full Text Available Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1 a cloud-resolving model (CRM, (2 a regional-scale model, the NASA unified Weather Research and Forecasting Model (WRF, and (3 a coupled CRM-GCM (general circulation model, known as the Goddard Multi-scale Modeling Framework or MMF. The same cloud-microphysical processes, long- and short-wave radiative transfer and land-surface processes are applied in all of the models to study explicit cloud-radiation and cloud-surface interactive processes in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator for comparison and validation with NASA high-resolution satellite data.

    This paper reviews the development and presents some applications of the multi-scale modeling system, including results from using the multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols. In addition, use of the multi-satellite simulator to identify the strengths and weaknesses of the model-simulated precipitation processes will be discussed as well as future model developments and applications.

  7. Microphysics in Multi-scale Modeling System with Unified Physics

    Science.gov (United States)

    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.

  8. Spectral contaminant identifier for off-axis integrated cavity output spectroscopy measurements of liquid water isotopes

    Energy Technology Data Exchange (ETDEWEB)

    Brian Leen, J.; Berman, Elena S. F.; Gupta, Manish [Los Gatos Research, 67 East Evelyn Avenue, Suite 3, Mountain View, California 94041-1518 (United States); Liebson, Lindsay [Department of Mechanical Engineering, Stanford University, Stanford, California 94305 (United States)

    2012-04-15

    Developments in cavity-enhanced absorption spectrometry have made it possible to measure water isotopes using faster, more cost-effective field-deployable instrumentation. Several groups have attempted to extend this technology to measure water extracted from plants and found that other extracted organics absorb light at frequencies similar to that absorbed by the water isotopomers, leading to {delta}{sup 2}H and {delta}{sup 18}O measurement errors ({Delta}{delta}{sup 2}H and {Delta}{delta}{sup 18}O). In this note, the off-axis integrated cavity output spectroscopy (ICOS) spectra of stable isotopes in liquid water is analyzed to determine the presence of interfering absorbers that lead to erroneous isotope measurements. The baseline offset of the spectra is used to calculate a broadband spectral metric, m{sub BB}, and the mean subtracted fit residuals in two regions of interest are used to determine a narrowband metric, m{sub NB}. These metrics are used to correct for {Delta}{delta}{sup 2}H and {Delta}{delta}{sup 18}O. The method was tested on 14 instruments and {Delta}{delta}{sup 18}O was found to scale linearly with contaminant concentration for both narrowband (e.g., methanol) and broadband (e.g., ethanol) absorbers, while {Delta}{delta}{sup 2}H scaled linearly with narrowband and as a polynomial with broadband absorbers. Additionally, the isotope errors scaled logarithmically with m{sub NB}. Using the isotope error versus m{sub NB} and m{sub BB} curves, {Delta}{delta}{sup 2}H and {Delta}{delta}{sup 18}O resulting from methanol contamination were corrected to a maximum mean absolute error of 0.93 per mille and 0.25 per mille respectively, while {Delta}{delta}{sup 2}H and {Delta}{delta}{sup 18}O from ethanol contamination were corrected to a maximum mean absolute error of 1.22 per mille and 0.22 per mille . Large variation between instruments indicates that the sensitivities must be calibrated for each individual isotope analyzer. These results suggest that the

  9. Integrated sequence analysis pipeline provides one-stop solution for identifying disease-causing mutations.

    Science.gov (United States)

    Hu, Hao; Wienker, Thomas F; Musante, Luciana; Kalscheuer, Vera M; Kahrizi, Kimia; Najmabadi, Hossein; Ropers, H Hilger

    2014-12-01

    Next-generation sequencing has greatly accelerated the search for disease-causing defects, but even for experts the data analysis can be a major challenge. To facilitate the data processing in a clinical setting, we have developed a novel medical resequencing analysis pipeline (MERAP). MERAP assesses the quality of sequencing, and has optimized capacity for calling variants, including single-nucleotide variants, insertions and deletions, copy-number variation, and other structural variants. MERAP identifies polymorphic and known causal variants by filtering against public domain databases, and flags nonsynonymous and splice-site changes. MERAP uses a logistic model to estimate the causal likelihood of a given missense variant. MERAP considers the relevant information such as phenotype and interaction with known disease-causing genes. MERAP compares favorably with GATK, one of the widely used tools, because of its higher sensitivity for detecting indels, its easy installation, and its economical use of computational resources. Upon testing more than 1,200 individuals with mutations in known and novel disease genes, MERAP proved highly reliable, as illustrated here for five families with disease-causing variants. We believe that the clinical implementation of MERAP will expedite the diagnostic process of many disease-causing defects. © 2014 WILEY PERIODICALS, INC.

  10. The Need-Goal Integration Hypothesis: How to Meet Identified Needs

    Directory of Open Access Journals (Sweden)

    Jayeoba F. Ilesanmi

    2016-06-01

    Full Text Available The paper highlights the many needs/goals of stake holders in the organisation and closely examines the well-worn believe that the main role of managers is to motivate their subordinates. Argument was proposed as to why this view is not appropriate in today’s organisations. The driving force for most employees, whose mobility and employability has been enhanced by ICT and globalization, is the extent to which the employing organisations is able to articulate their needs and meet them. To motivate and retain the modern day workers with portable skills, and to whom career is more a lattice than a ladder, is to be able to factor their needs into the goals of the organisation. More so, organisation is not about management and employees alone. There are many other stake holders; less visible though, but very important in the need-goal constellations of the organisation. It is posited that all stake holders in the organisation need to be motivated (by identifying and meeting their needs though in diverse ways, and that the action and inaction of one stake holder provides impetus for adequacy or shortfall in the motivation equation.

  11. A newly identified essential complex, Dre2-Tah18, controls mitochondria integrity and cell death after oxidative stress in yeast.

    Directory of Open Access Journals (Sweden)

    Laurence Vernis

    Full Text Available A mutated allele of the essential gene TAH18 was previously identified in our laboratory in a genetic screen for new proteins interacting with the DNA polymerase delta in yeast [1]. The present work shows that Tah18 plays a role in response to oxidative stress. After exposure to lethal doses of H(2O(2, GFP-Tah18 relocalizes to the mitochondria and controls mitochondria integrity and cell death. Dre2, an essential Fe/S cluster protein and homologue of human anti-apoptotic Ciapin1, was identified as a molecular partner of Tah18 in the absence of stress. Moreover, Ciapin1 is able to replace yeast Dre2 in vivo and physically interacts with Tah18. Our results are in favour of an oxidative stress-induced cell death in yeast that involves mitochondria and is controlled by the newly identified Dre2-Tah18 complex.

  12. Multiscale Drivers of Global Environmental Health

    Science.gov (United States)

    Desai, Manish Anil

    transmission groupings linked to public health intervention strategies; (3) emphasizing the intersection of proximal environmental characteristics and transmission cycles; (4) incorporating a matrix formulation to identify knowledge gaps and facilitate an integration of research; and (5) highlighting hypothesis generation amidst dynamic processes. A systems based approach leverages the reality that studies relevant to environmental change and infectious disease are embedded within a wider web of interactions. As scientific understanding advances, the EnvID framework can help integrate the various factors at play in determining environment-disease relationships and the connections between intrinsically multiscale causal networks. In Chapter 4, the coverage effect model functions primarily as a "proof of concept" analysis to address whether the efficacy of a clean cooking technology may be determined by the extent of not only household level use but also community level coverage. Such coverage dependent efficacy, or a "coverage effect," would transform how interventions are studied and deployed. Ensemble results are consistent with the concept that an appreciable coverage effect from clean cooking interventions can manifest within moderately dense communities. Benefits for users derive largely from direct effects; initially, at low coverage levels, almost exclusively so. Yet, as coverage expands within a user's community, a coverage effect becomes increasingly beneficial. In contrast, non users, despite also experiencing comparable exposure reductions from community-level intervention use, cannot proportionately benefit because their exposures remain overwhelmingly dominated by household-level use of traditional solid fuel cookstoves. The coverage effect model strengthens the rationale for public health programs and policies to encourage clean cooking technologies with an added incentive to realize high coverage within contiguous areas. The implications of the modeling exercise

  13. A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

    Science.gov (United States)

    Bednarcyk, Brett A.; Arnold, Steven M.

    2012-01-01

    A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

  14. An Integrated H-G Scheme Identifying Areas for Soil Remediation and Primary Heavy Metal Contributors: A Risk Perspective.

    Science.gov (United States)

    Zou, Bin; Jiang, Xiaolu; Duan, Xiaoli; Zhao, Xiuge; Zhang, Jing; Tang, Jingwen; Sun, Guoqing

    2017-03-23

    Traditional sampling for soil pollution evaluation is cost intensive and has limited representativeness. Therefore, developing methods that can accurately and rapidly identify at-risk areas and the contributing pollutants is imperative for soil remediation. In this study, we propose an innovative integrated H-G scheme combining human health risk assessment and geographical detector methods that was based on geographical information system technology and validated its feasibility in a renewable resource industrial park in mainland China. With a discrete site investigation of cadmium (Cd), arsenic (As), copper (Cu), mercury (Hg) and zinc (Zn) concentrations, the continuous surfaces of carcinogenic risk and non-carcinogenic risk caused by these heavy metals were estimated and mapped. Source apportionment analysis using geographical detector methods further revealed that these risks were primarily attributed to As, according to the power of the determinant and its associated synergic actions with other heavy metals. Concentrations of critical As and Cd, and the associated exposed CRs are closed to the safe thresholds after remediating the risk areas identified by the integrated H-G scheme. Therefore, the integrated H-G scheme provides an effective approach to support decision-making for regional contaminated soil remediation at fine spatial resolution with limited sampling data over a large geographical extent.

  15. Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote-sensing.

    Science.gov (United States)

    Hakkenberg, C R; Zhu, K; Peet, R K; Song, C

    2018-02-01

    The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species' cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01-900 m 2 . Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15-70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly

  16. Cost reductions on a titanium dioxide plant identified by a process integration study at Tioxide UK Ltd

    Energy Technology Data Exchange (ETDEWEB)

    1985-08-01

    The purpose of a process integration study is to determine the minimum practical amount of energy required to operate a process and to identify the most appropriate investment strategy which will realise the maximum energy cost savings consistent with a particular company's financial and operating criteria. The process integration method involves the rigorous application of thermodynamics and cost accounting, tempered by practical plant engineering and operability considerations. Tioxide UK Ltd is part of Tioxide Group plc and operates two UK sites for the production of titanium dioxide pigment. The site in question, Greatham works near Hartlepool, produces pigment via the chloride route. The energy costs at Greatham works can amount to pound5 - 6 million/year depending on production levels. (author).

  17. Integration of health into urban spatial planning through impact assessment: Identifying governance and policy barriers and facilitators

    International Nuclear Information System (INIS)

    Carmichael, Laurence; Barton, Hugh; Gray, Selena; Lease, Helen; Pilkington, Paul

    2012-01-01

    This article presents the results of a review of literature examining the barriers and facilitators in integrating health in spatial planning at the local, mainly urban level, through appraisals. Our literature review covered the UK and non UK experiences of appraisals used to consider health issues in the planning process. We were able to identify four main categories of obstacles and facilitators including first the different knowledge and conceptual understanding of health by different actors/stakeholders, second the types of governance arrangements, in particular partnerships, in place and the political context, third the way institutions work, the responsibilities they have and their capacity and resources and fourth the timeliness, comprehensiveness and inclusiveness of the appraisal process. The findings allowed us to draw some lessons on the governance and policy framework regarding the integration of health impact into spatial planning, in particular considering the pros and cons of integrating health impact assessment (HIA) into other forms of impact assessment of spatial planning decisions such as environmental impact assessment (EIA) and strategic environment assessment (SEA). In addition, the research uncovered a gap in the literature that tends to focus on the mainly voluntary HIA to assess health outcomes of planning decisions and neglect the analysis of regulatory mechanisms such as EIA and SEA. - Highlights: ► Governance and policy barriers and facilitators to the integration of health into urban planning. ► Review of literature on impact assessment methods used across the world. ► Knowledge, partnerships, management/resources and processes can impede integration. ► HIA evaluations prevail uncovering research opportunities for evaluating other techniques.

  18. Mammographic feature enhancement by multiscale analysis

    International Nuclear Information System (INIS)

    Laine, A.F.; Schuler, S.; Fan, J.; Huda, W.

    1994-01-01

    This paper introduces a novel approach for accomplishing mammographic feature analysis by overcomplete multiresolution representations. The authors show that efficient representations may be identified within a continuum of scale-space and used to enhance features of importance to mammography. Methods of contrast enhancement are described based on three overcomplete multiscale representations: (1) the dyadic wavelet transform (separable), (2) the var-phi-transform (nonseparable, nonorthogonal), and (3) the hexagonal wavelet transform (nonseparable). Multiscale edges identified within distinct levels of transform space provide local support for image enhancement. Mammograms are reconstructed from wavelet coefficients modified at one or more levels by local and global nonlinear operators. In each case, edges and gain parameters are identified adaptively by a measure of energy within each level of scale-space. The authors show quantitatively that transform coefficients, modified by adaptive nonlinear operators, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. The results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. The authors demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology, they can improve chances of early detection while requiring less time to evaluate mammograms for most patients

  19. Covariance, correlation matrix, and the multiscale community structure of networks.

    Science.gov (United States)

    Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing

    2010-07-01

    Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.

  20. The Magnetospheric Multiscale Magnetometers

    Science.gov (United States)

    Russell, C. T.; Anderson, B. J.; Baumjohann, W.; Bromund, K. R.; Dearborn, D.; Fischer, D.; Le, G.; Leinweber, H. K.; Leneman, D.; Magnes, W.; hide

    2014-01-01

    The success of the Magnetospheric Multiscale mission depends on the accurate measurement of the magnetic field on all four spacecraft. To ensure this success, two independently designed and built fluxgate magnetometers were developed, avoiding single-point failures. The magnetometers were dubbed the digital fluxgate (DFG), which uses an ASIC implementation and was supplied by the Space Research Institute of the Austrian Academy of Sciences and the analogue magnetometer (AFG) with a more traditional circuit board design supplied by the University of California, Los Angeles. A stringent magnetic cleanliness program was executed under the supervision of the Johns Hopkins University,s Applied Physics Laboratory. To achieve mission objectives, the calibration determined on the ground will be refined in space to ensure all eight magnetometers are precisely inter-calibrated. Near real-time data plays a key role in the transmission of high-resolution observations stored onboard so rapid processing of the low-resolution data is required. This article describes these instruments, the magnetic cleanliness program, and the instrument pre-launch calibrations, the planned in-flight calibration program, and the information flow that provides the data on the rapid time scale needed for mission success.

  1. Identifying Evolvability for Integration

    National Research Council Canada - National Science Library

    Davis, L; Gamble, Rose

    2002-01-01

    .... Even with successful composite applications, unexpected interoperability conflicts can arise when COTS products are upgraded, new components are needed, and the application requirements change...

  2. Multiscale modeling and simulation of brain blood flow

    Energy Technology Data Exchange (ETDEWEB)

    Perdikaris, Paris, E-mail: parisp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com [IBM T.J Watson Research Center, 1 Rogers St, Cambridge, Massachusetts 02142 (United States); Karniadakis, George Em, E-mail: george-karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912 (United States)

    2016-02-15

    The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.

  3. Elevated intrabolus pressure identifies obstructive processes when integrated relaxation pressure is normal on esophageal high-resolution manometry.

    Science.gov (United States)

    Quader, Farhan; Reddy, Chanakyaram; Patel, Amit; Gyawali, C Prakash

    2017-07-01

    Elevated integrated relaxation pressure (IRP) on esophageal high-resolution manometry (HRM) identifies obstructive processes at the esophagogastric junction (EGJ). Our aim was to determine whether intrabolus pressure (IBP) can identify structural EGJ processes when IRP is normal. In this observational cohort study, adult patients with dysphagia and undergoing HRM were evaluated for endoscopic evidence of structural EGJ processes (strictures, rings, hiatus hernia) in the setting of normal IRP. HRM metrics [IRP, distal contractile integral (DCI), distal latency (DL), IBP, and EGJ contractile integral (EGJ-CI)] were compared among 74 patients with structural EGJ findings (62.8 ± 1.6 yr, 67.6% women), 27 patients with normal EGD (52.9 ± 3.2 yr, 70.3% women), and 21 healthy controls (27.6 ± 0.6 yr, 52.4% women). Findings were validated in 85 consecutive symptomatic patients to address clinical utility. In the primary cohort, mean IBP (18.4 ± 0.9 mmHg) was higher with structural EGJ findings compared with dysphagia with normal EGD (13.5 ± 1.1 mmHg, P = 0.002) and healthy controls (10.9 ± 0.9 mmHg, P 0.05 for each comparison). During multiple rapid swallows, IBP remained higher in the structural findings group compared with controls ( P = 0.02). Similar analysis of the prospective validation cohort confirmed IBP elevation in structural EGJ processes, but correlation with dysphagia could not be demonstrated. We conclude that elevated IBP predicts the presence of structural EGJ processes even when IRP is normal, but correlation with dysphagia is suboptimal. NEW & NOTEWORTHY Integrated relaxation pressure (IRP) above the upper limit of normal defines esophageal outflow obstruction using high-resolution manometry. In patients with normal IRP, elevated intrabolus pressure (IBP) can be a surrogate marker for a structural restrictive or obstructive process at the esophagogastric junction (EGJ). This has the potential to augment the clinical value of

  4. Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses.

    Science.gov (United States)

    Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N; Jones, Byron C; Lu, Lu; Wang, Xusheng

    2018-01-01

    Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

  5. Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

    Directory of Open Access Journals (Sweden)

    Jie Luo

    2018-04-01

    Full Text Available Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1, down-regulation in NOE but rescue in RSE (pattern 2, up-regulation in both restraint stress followed by a saline injection (RSS and NOE, and further amplification in RSE (pattern 3, and up-regulation in RSS but reduction in both NOE and RSE (pattern 4. We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

  6. ICEApl1, an integrative conjugative element related to ICEHin1056, identified in the pig pathogen Actinobacillus pleuropneumoniae

    Directory of Open Access Journals (Sweden)

    Janine T Bosse

    2016-06-01

    Full Text Available ICEApl1 was identified in the whole genome sequence of MIDG2331, a tetracycline-resistant (MIC = 8 mg/L serovar 8 clinical isolate of Actinobacillus pleuropneumoniae, the causative agent of porcine pleuropneumonia. PCR amplification of virB4, one of the core genes involved in conjugation, was used to identify other A. pleuropneumoniae isolates potentially carrying ICEApl1. MICs for tetracycline were determined for virB4 positive isolates, and shotgun whole genome sequence analysis was used to confirm presence of the complete ICEApl1. The sequence of ICEApl1 is 56083 bp long and contains 67 genes including a Tn10 element encoding tetracycline resistance. Comparative sequence analysis was performed with similar integrative conjugative elements (ICEs found in other members of the Pasteurellaceae. ICEApl1 is most similar to the 59393 bp ICEHin1056, from Haemophilus influenzae strain 1056. Although initially identified only in serovar 8 isolates of A. pleuropneumoniae (31 from the UK and 1 from Cyprus, conjugal transfer of ICEApl1 to representative isolates of other serovars was confirmed. All isolates carrying ICEApl1 had a MIC for tetracycline of 8 mg/L. This is, to our knowledge, the first description of an ICE in A. pleuropneumoniae, and the first report of a member of the ICEHin1056 subfamily in a non-human pathogen. ICEApl1 confers resistance to tetracycline, currently one of the more commonly used antibiotics for treatment and control of porcine pleuropneumonia.

  7. Integrative microRNA and proteomic approaches identify novel osteoarthritis genes and their collaborative metabolic and inflammatory networks.

    Directory of Open Access Journals (Sweden)

    Dimitrios Iliopoulos

    Full Text Available BACKGROUND: Osteoarthritis is a multifactorial disease characterized by destruction of the articular cartilage due to genetic, mechanical and environmental components affecting more than 100 million individuals all over the world. Despite the high prevalence of the disease, the absence of large-scale molecular studies limits our ability to understand the molecular pathobiology of osteoathritis and identify targets for drug development. METHODOLOGY/PRINCIPAL FINDINGS: In this study we integrated genetic, bioinformatic and proteomic approaches in order to identify new genes and their collaborative networks involved in osteoarthritis pathogenesis. MicroRNA profiling of patient-derived osteoarthritic cartilage in comparison to normal cartilage, revealed a 16 microRNA osteoarthritis gene signature. Using reverse-phase protein arrays in the same tissues we detected 76 differentially expressed proteins between osteoarthritic and normal chondrocytes. Proteins such as SOX11, FGF23, KLF6, WWOX and GDF15 not implicated previously in the genesis of osteoarthritis were identified. Integration of microRNA and proteomic data with microRNA gene-target prediction algorithms, generated a potential "interactome" network consisting of 11 microRNAs and 58 proteins linked by 414 potential functional associations. Comparison of the molecular and clinical data, revealed specific microRNAs (miR-22, miR-103 and proteins (PPARA, BMP7, IL1B to be highly correlated with Body Mass Index (BMI. Experimental validation revealed that miR-22 regulated PPARA and BMP7 expression and its inhibition blocked inflammatory and catabolic changes in osteoarthritic chondrocytes. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that obesity and inflammation are related to osteoarthritis, a metabolic disease affected by microRNA deregulation. Gene network approaches provide new insights for elucidating the complexity of diseases such as osteoarthritis. The integration of microRNA, proteomic

  8. MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.

    Science.gov (United States)

    Prasath, V B S; Pelapur, R; Glinskii, O V; Glinsky, V V; Huxley, V H; Palaniappan, K

    2015-04-01

    Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary in order to extract accurate vascular morphology information. For this purpose, we propose a multiscale tensor with anisotropic diffusion model which progressively and adaptively updates the amount of smoothing while preserving vessel boundaries accurately. Based on a coherency enhancing flow with planar confidence measure and fused 3D structure information, our method integrates multiple scales for microvasculature preservation and noise removal membrane structures. Experimental results on simulated synthetic images and epifluorescence images show the advantage of our improvement over other related diffusion filters. We further show that the proposed multiscale integration approach improves denoising accuracy of different tensor diffusion methods to obtain better microvasculature segmentation.

  9. Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty-A pulp mill example

    International Nuclear Information System (INIS)

    Svensson, Elin; Berntsson, Thore; Stroemberg, Ann-Brith

    2009-01-01

    This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO 2 emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO 2 emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives

  10. Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty-A pulp mill example

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, Elin [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden)], E-mail: elin.svensson@chalmers.se; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden)

    2009-03-15

    This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives.

  11. Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty. A pulp mill example

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden)

    2009-03-15

    This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, doi:10.1016/j.enpol.2008.10.023] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives. (author)

  12. Cost reductions on a food processing plant identified by a process integration study at Cadbury Typhoo Ltd

    Energy Technology Data Exchange (ETDEWEB)

    Clayton, R.W. (Energy Technology Support Unit, Harwell (UK))

    1986-08-01

    The purpose of a process integration study is to determine the minimum practical amount of energy required to operate a process and to identify the minimum cost schemes to maximise savings consistent with planning and operating criteria. The British-led development of Pinch Technology provides a more systematic approach. This technique involves the rigorous application of thermodynamic principles and cost accounting whilst taking account of practical engineering and operability constraints. Cadbury Typhoo Ltd is part of the Cadbury Schweppes Group. The company produces and markets hot and cold beverage products. A process integration study was carried out at the company's Knighton manufacturing site where 'instant' powder beverage ingredients are made and packaged. The total energy bill at the site is in the region of Pound 0.5 million/year. The process energy bill is around Pound 300-350,000/year. The first significant opportunity involves changing the actual process by a different piping arrangement. For a capital expenditure of around Pound 1,000, savings worth Pound 25,000/year can be achieved with a payback of approximately two weeks. (author).

  13. Multiscale structural study using scanning X-ray microscope

    International Nuclear Information System (INIS)

    Ohsumi, Hiroyuki; Arima, Taka-hisa

    2016-01-01

    Correspondence between structures at the atomic- and meso-scales can be given by scanning X-ray microscopy integrated with polarized X-ray diffractometry. Symmetry is the common structural feature available across multiple hierarchies. This article introduces a symmetry evaluation technique based on polarized X-ray diffractometry and describes two embodiments: chirality domain observation and antiferromagnetic domain observation. Multiscale structural studies would play an important role in uncovering universality of hierarchical structure. (author)

  14. General Approach to Identifying Potential Targets for Cancer Imaging by Integrated Bioinformatics Analysis of Publicly Available Genomic Profiles

    Directory of Open Access Journals (Sweden)

    Yongliang Yang

    2011-03-01

    Full Text Available Molecular imaging has moved to the forefront of drug development and biomedical research. The identification of appropriate imaging targets has become the touchstone for the accurate diagnosis and prognosis of human cancer. Particularly, cell surface- or membrane-bound proteins are attractive imaging targets for their aberrant expression, easily accessible location, and unique biochemical functions in tumor cells. Previously, we published a literature mining of potential targets for our in-house enzyme-mediated cancer imaging and therapy technology. Here we present a simple and integrated bioinformatics analysis approach that assembles a public cancer microarray database with a pathway knowledge base for ascertaining and prioritizing upregulated genes encoding cell surface- or membrane-bound proteins, which could serve imaging targets. As examples, we obtained lists of potential hits for six common and lethal human tumors in the prostate, breast, lung, colon, ovary, and pancreas. As control tests, a number of well-known cancer imaging targets were detected and confirmed by our study. Further, by consulting gene-disease and protein-disease databases, we suggest a number of significantly upregulated genes as promising imaging targets, including cell surface-associated mucin-1, prostate-specific membrane antigen, hepsin, urokinase plasminogen activator receptor, and folate receptors. By integrating pathway analysis, we are able to organize and map “focused” interaction networks derived from significantly dysregulated entity pairs to reflect important cellular functions in disease processes. We provide herein an example of identifying a tumor cell growth and proliferation subnetwork for prostate cancer. This systematic mining approach can be broadly applied to identify imaging or therapeutic targets for other human diseases.

  15. Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function.

    Science.gov (United States)

    Chasman, Daniel I; Fuchsberger, Christian; Pattaro, Cristian; Teumer, Alexander; Böger, Carsten A; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Taliun, Daniel; Li, Man; Gao, Xiaoyi; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C; O'Seaghdha, Conall M; Glazer, Nicole; Isaacs, Aaron; Liu, Ching-Ti; Smith, Albert V; O'Connell, Jeffrey R; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Johnson, Andrew D; Gierman, Hinco J; Feitosa, Mary F; Hwang, Shih-Jen; Atkinson, Elizabeth J; Lohman, Kurt; Cornelis, Marilyn C; Johansson, Asa; Tönjes, Anke; Dehghan, Abbas; Lambert, Jean-Charles; Holliday, Elizabeth G; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y; Murgia, Federico; Trompet, Stella; Imboden, Medea; Coassin, Stefan; Pistis, Giorgio; Harris, Tamara B; Launer, Lenore J; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D; Boerwinkle, Eric; Schmidt, Helena; Cavalieri, Margherita; Rao, Madhumathi; Hu, Frank; Demirkan, Ayse; Oostra, Ben A; de Andrade, Mariza; Turner, Stephen T; Ding, Jingzhong; Andrews, Jeanette S; Freedman, Barry I; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Meisinger, Christa; Gieger, Christian; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H; Wright, Alan F; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G; Rivadeneira, Fernando; Aulchenko, Yurii S; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Ketkar, Shamika; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K; Portas, Laura; Ford, Ian; Buckley, Brendan M; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Kim, Stuart K; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J Wouter; Probst-Hensch, Nicole M; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; Siscovick, David S; van Duijn, Cornelia M; Borecki, Ingrid B; Kardia, Sharon L R; Liu, Yongmei; Curhan, Gary C; Rudan, Igor; Gyllensten, Ulf; Wilson, James F; Franke, Andre; Pramstaller, Peter P; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M; Parsa, Afshin; Bochud, Murielle; Heid, Iris M; Kao, W H Linda; Fox, Caroline S; Köttgen, Anna

    2012-12-15

    In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10(-9)) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10(-4)-2.2 × 10(-7). Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.

  16. Generalized multiscale finite element methods for problems in perforated heterogeneous domains

    KAUST Repository

    Chung, Eric T.

    2015-06-08

    Complex processes in perforated domains occur in many real-world applications. These problems are typically characterized by physical processes in domains with multiple scales. Moreover, these problems are intrinsically multiscale and their discretizations can yield very large linear or nonlinear systems. In this paper, we investigate multiscale approaches that attempt to solve such problems on a coarse grid by constructing multiscale basis functions in each coarse grid, where the coarse grid can contain many perforations. In particular, we are interested in cases when there is no scale separation and the perforations can have different sizes. In this regard, we mention some earlier pioneering works, where the authors develop multiscale finite element methods. In our paper, we follow Generalized Multiscale Finite Element Method (GMsFEM) and develop a multiscale procedure where we identify multiscale basis functions in each coarse block using snapshot space and local spectral problems. We show that with a few basis functions in each coarse block, one can approximate the solution, where each coarse block can contain many small inclusions. We apply our general concept to (1) Laplace equation in perforated domains; (2) elasticity equation in perforated domains; and (3) Stokes equations in perforated domains. Numerical results are presented for these problems using two types of heterogeneous perforated domains. The analysis of the proposed methods will be presented elsewhere. © 2015 Taylor & Francis

  17. Multiscale scenarios for nature futures

    CSIR Research Space (South Africa)

    Rosa, IMD

    2017-09-01

    Full Text Available & Evolution, vol. 1: 1416-1419 Multiscale scenarios for nature futures Rosa IMD Pereira HM Ferrier S Alkemade R Acosta LA Akcakaya HR den Belder E Fazel AM Fujimori S Sitas NE ABSTRACT: Targets for human development are increasingly...

  18. Multiscale mechanics of dynamical metamaterials

    NARCIS (Netherlands)

    Geers, M.G.D.; Kouznetsova, V.; Sridhar, A.; Krushynska, A.; Kleiber, M.; Burczynski, T.; Wilde, K.; Gorski, J.; Winkelmann, K.; Smakosz, L.

    2016-01-01

    This contribution focuses on the computational multi-scale solution of wave propagation phenomena in dynamic metamaterials. Taking the Bloch-Floquet solution for the standard elastic case as a point of departure, an extended scheme is presented to solve for heterogeneous visco-elastic materials. The

  19. Multiscale-Driven approach to detecting change in Synthetic Aperture Radar (SAR) imagery

    Science.gov (United States)

    Gens, R.; Hogenson, K.; Ajadi, O. A.; Meyer, F. J.; Myers, A.; Logan, T. A.; Arnoult, K., Jr.

    2017-12-01

    Detecting changes between Synthetic Aperture Radar (SAR) images can be a useful but challenging exercise. SAR with its all-weather capabilities can be an important resource in identifying and estimating the expanse of events such as flooding, river ice breakup, earthquake damage, oil spills, and forest growth, as it can overcome shortcomings of optical methods related to cloud cover. However, detecting change in SAR imagery can be impeded by many factors including speckle, complex scattering responses, low temporal sampling, and difficulty delineating boundaries. In this presentation we use a change detection method based on a multiscale-driven approach. By using information at different resolution levels, we attempt to obtain more accurate change detection maps in both heterogeneous and homogeneous regions. Integrated within the processing flow are processes that 1) improve classification performance by combining Expectation-Maximization algorithms with mathematical morphology, 2) achieve high accuracy in preserving boundaries using measurement level fusion techniques, and 3) combine modern non-local filtering and 2D-discrete stationary wavelet transform to provide robustness against noise. This multiscale-driven approach to change detection has recently been incorporated into the Alaska Satellite Facility (ASF) Hybrid Pluggable Processing Pipeline (HyP3) using radiometrically terrain corrected SAR images. Examples primarily from natural hazards are presented to illustrate the capabilities and limitations of the change detection method.

  20. Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes.

    Science.gov (United States)

    Ackermann, Amanda M; Wang, Zhiping; Schug, Jonathan; Naji, Ali; Kaestner, Klaus H

    2016-03-01

    Although glucagon-secreting α-cells and insulin-secreting β-cells have opposing functions in regulating plasma glucose levels, the two cell types share a common developmental origin and exhibit overlapping transcriptomes and epigenomes. Notably, destruction of β-cells can stimulate repopulation via transdifferentiation of α-cells, at least in mice, suggesting plasticity between these cell fates. Furthermore, dysfunction of both α- and β-cells contributes to the pathophysiology of type 1 and type 2 diabetes, and β-cell de-differentiation has been proposed to contribute to type 2 diabetes. Our objective was to delineate the molecular properties that maintain islet cell type specification yet allow for cellular plasticity. We hypothesized that correlating cell type-specific transcriptomes with an atlas of open chromatin will identify novel genes and transcriptional regulatory elements such as enhancers involved in α- and β-cell specification and plasticity. We sorted human α- and β-cells and performed the "Assay for Transposase-Accessible Chromatin with high throughput sequencing" (ATAC-seq) and mRNA-seq, followed by integrative analysis to identify cell type-selective gene regulatory regions. We identified numerous transcripts with either α-cell- or β-cell-selective expression and discovered the cell type-selective open chromatin regions that correlate with these gene activation patterns. We confirmed cell type-selective expression on the protein level for two of the top hits from our screen. The "group specific protein" (GC; or vitamin D binding protein) was restricted to α-cells, while CHODL (chondrolectin) immunoreactivity was only present in β-cells. Furthermore, α-cell- and β-cell-selective ATAC-seq peaks were identified to overlap with known binding sites for islet transcription factors, as well as with single nucleotide polymorphisms (SNPs) previously identified as risk loci for type 2 diabetes. We have determined the genetic landscape of

  1. Multiscale Thermohydrologic Model

    Energy Technology Data Exchange (ETDEWEB)

    T. Buscheck

    2004-10-12

    The purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. Thus, the goal is to predict the range of possible thermal-hydrologic conditions across the repository; this is quite different from predicting a single expected thermal-hydrologic response. The MSTHM calculates the following thermal-hydrologic parameters: temperature, relative humidity, liquid-phase saturation, evaporation rate, air-mass fraction, gas-phase pressure, capillary pressure, and liquid- and gas-phase fluxes (Table 1-1). These thermal-hydrologic parameters are required to support ''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504]). The thermal-hydrologic parameters are determined as a function of position along each of the emplacement drifts and as a function of waste package type. These parameters are determined at various reference locations within the emplacement drifts, including the waste package and drip-shield surfaces and in the invert. The parameters are also determined at various defined locations in the adjoining host rock. The MSTHM uses data obtained from the data tracking numbers (DTNs) listed in Table 4.1-1. The majority of those DTNs were generated from the following analyses and model reports: (1) ''UZ Flow Model and Submodels'' (BSC 2004 [DIRS 169861]); (2) ''Development of Numerical Grids for UZ Flow and Transport Modeling'' (BSC 2004); (3) ''Calibrated Properties Model'' (BSC 2004 [DIRS 169857]); (4) ''Thermal Conductivity of the Potential Repository Horizon'' (BSC 2004 [DIRS 169854]); (5) ''Thermal Conductivity of the Non-Repository Lithostratigraphic Layers

  2. Multiscale simulation approach for battery production systems

    CERN Document Server

    Schönemann, Malte

    2017-01-01

    Addressing the challenge of improving battery quality while reducing high costs and environmental impacts of the production, this book presents a multiscale simulation approach for battery production systems along with a software environment and an application procedure. Battery systems are among the most important technologies of the 21st century since they are enablers for the market success of electric vehicles and stationary energy storage solutions. However, the performance of batteries so far has limited possible applications. Addressing this challenge requires an interdisciplinary understanding of dynamic cause-effect relationships between processes, equipment, materials, and environmental conditions. The approach in this book supports the integrated evaluation of improvement measures and is usable for different planning horizons. It is applied to an exemplary battery cell production and module assembly in order to demonstrate the effectiveness and potential benefits of the simulation.

  3. Extended Multiscale Image Segmentation for Castellated Wall Management

    Science.gov (United States)

    Sakamoto, M.; Tsuguchi, M.; Chhatkuli, S.; Satoh, T.

    2018-05-01

    Castellated walls are positioned as tangible cultural heritage, which require regular maintenance to preserve their original state. For the demolition and repair work of the castellated wall, it is necessary to identify the individual stones constituting the wall. However, conventional approaches using laser scanning or integrated circuits (IC) tags were very time-consuming and cumbersome. Therefore, we herein propose an efficient approach for castellated wall management based on an extended multiscale image segmentation technique. In this approach, individual stone polygons are extracted from the castellated wall image and are associated with a stone management database. First, to improve the performance of the extraction of individual stone polygons having a convex shape, we developed a new shape criterion named convex hull fitness in the image segmentation process and confirmed its effectiveness. Next, we discussed the stone management database and its beneficial utilization in the repair work of castellated walls. Subsequently, we proposed irregular-shape indexes that are helpful for evaluating the stone shape and the stability of the stone arrangement state in castellated walls. Finally, we demonstrated an application of the proposed method for a typical castellated wall in Japan. Consequently, we confirmed that the stone polygons can be extracted with an acceptable level. Further, the condition of the shapes and the layout of the stones could be visually judged with the proposed irregular-shape indexes.

  4. Integrated Genomics of Crohn’s Disease Risk Variant Identifies a Role for CLEC12A in Antibacterial Autophagy

    Directory of Open Access Journals (Sweden)

    Jakob Begun

    2015-06-01

    Full Text Available The polymorphism ATG16L1 T300A, associated with increased risk of Crohn’s disease, impairs pathogen defense mechanisms including selective autophagy, but specific pathway interactions altered by the risk allele remain unknown. Here, we use perturbational profiling of human peripheral blood cells to reveal that CLEC12A is regulated in an ATG16L1-T300A-dependent manner. Antibacterial autophagy is impaired in CLEC12A-deficient cells, and this effect is exacerbated in the presence of the ATG16L1∗300A risk allele. Clec12a−/− mice are more susceptible to Salmonella infection, supporting a role for CLEC12A in antibacterial defense pathways in vivo. CLEC12A is recruited to sites of bacterial entry, bacteria-autophagosome complexes, and sites of sterile membrane damage. Integrated genomics identified a functional interaction between CLEC12A and an E3-ubiquitin ligase complex that functions in antibacterial autophagy. These data identify CLEC12A as early adaptor molecule for antibacterial autophagy and highlight perturbational profiling as a method to elucidate defense pathways in complex genetic disease.

  5. Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer.

    Science.gov (United States)

    Michaut, Magali; Chin, Suet-Feung; Majewski, Ian; Severson, Tesa M; Bismeijer, Tycho; de Koning, Leanne; Peeters, Justine K; Schouten, Philip C; Rueda, Oscar M; Bosma, Astrid J; Tarrant, Finbarr; Fan, Yue; He, Beilei; Xue, Zheng; Mittempergher, Lorenza; Kluin, Roelof J C; Heijmans, Jeroen; Snel, Mireille; Pereira, Bernard; Schlicker, Andreas; Provenzano, Elena; Ali, Hamid Raza; Gaber, Alexander; O'Hurley, Gillian; Lehn, Sophie; Muris, Jettie J F; Wesseling, Jelle; Kay, Elaine; Sammut, Stephen John; Bardwell, Helen A; Barbet, Aurélie S; Bard, Floriane; Lecerf, Caroline; O'Connor, Darran P; Vis, Daniël J; Benes, Cyril H; McDermott, Ultan; Garnett, Mathew J; Simon, Iris M; Jirström, Karin; Dubois, Thierry; Linn, Sabine C; Gallagher, William M; Wessels, Lodewyk F A; Caldas, Carlos; Bernards, Rene

    2016-01-05

    Invasive lobular carcinoma (ILC) is the second most frequently occurring histological breast cancer subtype after invasive ductal carcinoma (IDC), accounting for around 10% of all breast cancers. The molecular processes that drive the development of ILC are still largely unknown. We have performed a comprehensive genomic, transcriptomic and proteomic analysis of a large ILC patient cohort and present here an integrated molecular portrait of ILC. Mutations in CDH1 and in the PI3K pathway are the most frequent molecular alterations in ILC. We identified two main subtypes of ILCs: (i) an immune related subtype with mRNA up-regulation of PD-L1, PD-1 and CTLA-4 and greater sensitivity to DNA-damaging agents in representative cell line models; (ii) a hormone related subtype, associated with Epithelial to Mesenchymal Transition (EMT), and gain of chromosomes 1q and 8q and loss of chromosome 11q. Using the somatic mutation rate and eIF4B protein level, we identified three groups with different clinical outcomes, including a group with extremely good prognosis. We provide a comprehensive overview of the molecular alterations driving ILC and have explored links with therapy response. This molecular characterization may help to tailor treatment of ILC through the application of specific targeted, chemo- and/or immune-therapies.

  6. Identifying the conditions needed for integrated knowledge translation (IKT) in health care organizations: qualitative interviews with researchers and research users.

    Science.gov (United States)

    Gagliardi, Anna R; Dobrow, Mark J

    2016-07-12

    Collaboration among researchers and research users, or integrated knowledge translation (IKT), enhances the relevance and uptake of evidence into policy and practice. However, it is not widely practiced and, even when well-resourced, desired impacts may not be achieved. Given that large-scale investment is not the norm, further research is needed to identify how IKT can be optimized. Interviews were conducted with researchers and research users (clinicians, managers) in a health care delivery (HCDO) and health care monitoring (HCMO) organization that differed in size and infrastructure, and were IKT-naïve. Basic qualitative description was used. Participants were asked about IKT activities and challenges, and recommendations for optimizing IKT. Data were analysed inductively using constant comparative technique. Forty-three interviews were conducted (28 HCDO, 15 HCMO) with 13 researchers, 8 clinicians, and 22 managers. Little to no IKT took place. Participants articulated similar challenges and recommendations revealing that a considerable number of changes were needed at the organizational, professional and individual levels. Given the IKT-absent state of participating organizations, this research identified a core set of conditions which must be addressed to prepare an environment conducive to IKT. These conditions were compiled into a framework by which organizations can plan for, or evaluate their capacity for IKT. The IKT capacity framework is relevant for organizations in which there is no current IKT activity. Use of the IKT framework may result in more organizations that are ready to initiate and establish IKT, perhaps ultimately leading to more, and higher-quality collaboration for health system innovation. Further research is needed to confirm these findings in other organizations not yet resourced for, or undertaking IKT, and to explore the resource implications and mechanisms for establishing the conditions identified here as essential to preparing for

  7. Integrated genetic and epigenetic analysis identifies haplotype-specific methylation in the FTO type 2 diabetes and obesity susceptibility locus.

    Directory of Open Access Journals (Sweden)

    Christopher G Bell

    2010-11-01

    Full Text Available Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D, focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip and absolute methylation values were estimated using a Bayesian algorithm (BATMAN. Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10(-4, permutation p = 1.0×10(-3. Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10(-7. Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM, encapsulates a Highly Conserved Non-Coding Element (HCNE that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases.

  8. In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

    Science.gov (United States)

    Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-01

    Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

  9. Use of Persistent Identifiers to link Heterogeneous Data Systems in the Integrated Earth Data Applications (IEDA) Facility

    Science.gov (United States)

    Hsu, L.; Lehnert, K. A.; Carbotte, S. M.; Arko, R. A.; Ferrini, V.; O'hara, S. H.; Walker, J. D.

    2012-12-01

    The Integrated Earth Data Applications (IEDA) facility maintains multiple data systems with a wide range of solid earth data types from the marine, terrestrial, and polar environments. Examples of the different data types include syntheses of ultra-high resolution seafloor bathymetry collected on large collaborative cruises and analytical geochemistry measurements collected by single investigators in small, unique projects. These different data types have historically been channeled into separate, discipline-specific databases with search and retrieval tailored for the specific data type. However, a current major goal is to integrate data from different systems to allow interdisciplinary data discovery and scientific analysis. To increase discovery and access across these heterogeneous systems, IEDA employs several unique IDs, including sample IDs (International Geo Sample Number, IGSN), person IDs (GeoPass ID), funding award IDs (NSF Award Number), cruise IDs (from the Marine Geoscience Data System Expedition Metadata Catalog), dataset IDs (DOIs), and publication IDs (DOIs). These IDs allow linking of a sample registry (System for Earth SAmple Registration), data libraries and repositories (e.g. Geochemical Research Library, Marine Geoscience Data System), integrated synthesis databases (e.g. EarthChem Portal, PetDB), and investigator services (IEDA Data Compliance Tool). The linked systems allow efficient discovery of related data across different levels of granularity. In addition, IEDA data systems maintain links with several external data systems, including digital journal publishers. Links have been established between the EarthChem Portal and ScienceDirect through publication DOIs, returning sample-level objects and geochemical analyses for a particular publication. Linking IEDA-hosted data to digital publications with IGSNs at the sample level and with IEDA-allocated dataset DOIs are under development. As an example, an individual investigator could sign up

  10. The Magnetospheric Multiscale Mission

    Science.gov (United States)

    Burch, James

    Magnetospheric Multiscale (MMS), a NASA four-spacecraft mission scheduled for launch in November 2014, will investigate magnetic reconnection in the boundary regions of the Earth’s magnetosphere, particularly along its dayside boundary with the solar wind and the neutral sheet in the magnetic tail. Among the important questions about reconnection that will be addressed are the following: Under what conditions can magnetic-field energy be converted to plasma energy by the annihilation of magnetic field through reconnection? How does reconnection vary with time, and what factors influence its temporal behavior? What microscale processes are responsible for reconnection? What determines the rate of reconnection? In order to accomplish its goals the MMS spacecraft must probe both those regions in which the magnetic fields are very nearly antiparallel and regions where a significant guide field exists. From previous missions we know the approximate speeds with which reconnection layers move through space to be from tens to hundreds of km/s. For electron skin depths of 5 to 10 km, the full 3D electron population (10 eV to above 20 keV) has to be sampled at rates greater than 10/s. The MMS Fast-Plasma Instrument (FPI) will sample electrons at greater than 30/s. Because the ion skin depth is larger, FPI will make full ion measurements at rates of greater than 6/s. 3D E-field measurements will be made by MMS once every ms. MMS will use an Active Spacecraft Potential Control device (ASPOC), which emits indium ions to neutralize the photoelectron current and keep the spacecraft from charging to more than +4 V. Because ion dynamics in Hall reconnection depend sensitively on ion mass, MMS includes a new-generation Hot Plasma Composition Analyzer (HPCA) that corrects problems with high proton fluxes that have prevented accurate ion-composition measurements near the dayside magnetospheric boundary. Finally, Energetic Particle Detector (EPD) measurements of electrons and

  11. Integrative analysis of a cross-loci regulation network identifies App as a gene regulating insulin secretion from pancreatic islets.

    Directory of Open Access Journals (Sweden)

    Zhidong Tu

    Full Text Available Complex diseases result from molecular changes induced by multiple genetic factors and the environment. To derive a systems view of how genetic loci interact in the context of tissue-specific molecular networks, we constructed an F2 intercross comprised of >500 mice from diabetes-resistant (B6 and diabetes-susceptible (BTBR mouse strains made genetically obese by the Leptin(ob/ob mutation (Lep(ob. High-density genotypes, diabetes-related clinical traits, and whole-transcriptome expression profiling in five tissues (white adipose, liver, pancreatic islets, hypothalamus, and gastrocnemius muscle were determined for all mice. We performed an integrative analysis to investigate the inter-relationship among genetic factors, expression traits, and plasma insulin, a hallmark diabetes trait. Among five tissues under study, there are extensive protein-protein interactions between genes responding to different loci in adipose and pancreatic islets that potentially jointly participated in the regulation of plasma insulin. We developed a novel ranking scheme based on cross-loci protein-protein network topology and gene expression to assess each gene's potential to regulate plasma insulin. Unique candidate genes were identified in adipose tissue and islets. In islets, the Alzheimer's gene App was identified as a top candidate regulator. Islets from 17-week-old, but not 10-week-old, App knockout mice showed increased insulin secretion in response to glucose or a membrane-permeant cAMP analog, in agreement with the predictions of the network model. Our result provides a novel hypothesis on the mechanism for the connection between two aging-related diseases: Alzheimer's disease and type 2 diabetes.

  12. Multiscale stabilization for convection-dominated diffusion in heterogeneous media

    KAUST Repository

    Calo, Victor M.

    2016-02-23

    We develop a Petrov-Galerkin stabilization method for multiscale convection-diffusion transport systems. Existing stabilization techniques add a limited number of degrees of freedom in the form of bubble functions or a modified diffusion, which may not be sufficient to stabilize multiscale systems. We seek a local reduced-order model for this kind of multiscale transport problems and thus, develop a systematic approach for finding reduced-order approximations of the solution. We start from a Petrov-Galerkin framework using optimal weighting functions. We introduce an auxiliary variable to a mixed formulation of the problem. The auxiliary variable stands for the optimal weighting function. The problem reduces to finding a test space (a dimensionally reduced space for this auxiliary variable), which guarantees that the error in the primal variable (representing the solution) is close to the projection error of the full solution on the dimensionally reduced space that approximates the solution. To find the test space, we reformulate some recent mixed Generalized Multiscale Finite Element Methods. We introduce snapshots and local spectral problems that appropriately define local weight and trial spaces. In particular, we use energy minimizing snapshots and local spectral decompositions in the natural norm associated with the auxiliary variable. The resulting spectral decomposition adaptively identifies and builds the optimal multiscale space to stabilize the system. We discuss the stability and its relation to the approximation property of the test space. We design online basis functions, which accelerate convergence in the test space, and consequently, improve stability. We present several numerical examples and show that one needs a few test functions to achieve an error similar to the projection error in the primal variable irrespective of the Peclet number.

  13. An integrated structure- and system-based framework to identify new targets of metabolites and known drugs

    KAUST Repository

    Naveed, Hammad

    2015-08-18

    Motivation: The inherent promiscuity of small molecules towards protein targets impedes our understanding of healthy versus diseased metabolism. This promiscuity also poses a challenge for the pharmaceutical industry as identifying all protein targets is important to assess (side) effects and repositioning opportunities for a drug. Results: Here, we present a novel integrated structure- and system-based approach of drug-target prediction (iDTP) to enable the large-scale discovery of new targets for small molecules, such as pharmaceutical drugs, co-factors and metabolites (collectively called ‘drugs’). For a given drug, our method uses sequence order–independent structure alignment, hierarchical clustering, and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE) that captures promiscuous structural features of different binding sites on known targets. A drug’s PPE is combined with an approximation of its delivery profile to reduce false positives. In our cross-validation study, we use iDTP to predict the known targets of eleven drugs, with 63% sensitivity and 81% specificity. We then predicted novel targets for these drugs—two that are of high pharmacological interest, the nuclear receptor PPARγ and the oncogene Bcl-2, were successfully validated through in vitro binding experiments. Our method is broadly applicable for the prediction of protein-small molecule interactions with several novel applications to biological research and drug development.

  14. Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data.

    Science.gov (United States)

    Ryall, Karen A; Shin, Jimin; Yoo, Minjae; Hinz, Trista K; Kim, Jihye; Kang, Jaewoo; Heasley, Lynn E; Tan, Aik Choon

    2015-12-01

    Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret. We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We experimentally validated KAR predictions of FGFR and MTOR dependence in lung cancer cell line H1581, showing synergistic reduction in proliferation after combining ponatinib and AZD8055. KAR can be downloaded as a Python function or a MATLAB script along with example inputs and outputs at: http://tanlab.ucdenver.edu/KAR/. aikchoon.tan@ucdenver.edu. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  15. Evaluation of validity of Integrated Management of Childhood Illness guidelines in identifying edema of nutritional causes among Egyptian children.

    Science.gov (United States)

    El Habashy, Safinaz A; Mohamed, Maha H; Amin, Dina A; Marzouk, Diaa; Farid, Mohammed N

    2015-12-01

    The aim of this study was to assess the validity of the Integrated Management of Childhood Illness (IMCI) algorithm to detect edematous type of malnutrition in Egyptian infants and children ranging in age from 2 months to 5 years. This study was carried out by surveying 23 082 children aged between 2 months and 5 years visiting the pediatric outpatient clinic, Ain Shams University Hospital, over a period of 6 months. Thirty-eight patients with edema of both feet on their primary visit were enrolled in the study. Every child was assessed using the IMCI algorithm 'assess and classify' by the same physician, together with a systematic clinical evaluation with all relevant investigations. Twenty-two patients (57.9%) were proven to have nutritional etiology. 'Weight for age' sign had a sensitivity of 95.5%, a specificity of 56%, and a diagnostic accuracy of 78.95% in the identification of nutritional edema among all cases of bipedal edema. Combinations of IMCI symptoms 'pallor, visible severe wasting, fever, diarrhea', and 'weight for age' increased the sensitivity to 100%, but with a low specificity of 38% and a diagnostic accuracy of 73.68%. Bipedal edema and low weight for age as part of the IMCI algorithm can identify edema because of nutritional etiology with 100% sensitivity, but with 37% specificity. Revisions need to be made to the IMCI guidelines published in 2010 by the Egyptian Ministry of Health in the light of the new WHO guidelines of 2014.

  16. Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance

    Energy Technology Data Exchange (ETDEWEB)

    Estep, Donald [Colorado State Univ., Fort Collins, CO (United States); El-Azab, Anter [Florida State Univ., Tallahassee, FL (United States); Pernice, Michael [Idaho National Lab. (INL), Idaho Falls, ID (United States); Peterson, John W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Polyakov, Peter [Univ. of Wyoming, Laramie, WY (United States); Tavener, Simon [Colorado State Univ., Fort Collins, CO (United States); Xiu, Dongbin [Purdue Univ., West Lafayette, IN (United States); Univ. of Utah, Salt Lake City, UT (United States)

    2017-03-23

    In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis for computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.

  17. Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

    Science.gov (United States)

    Somogyi, Endre; Sluka, James P; Glazier, James A

    2016-10-01

    Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

  18. ProtoMD: A prototyping toolkit for multiscale molecular dynamics

    Science.gov (United States)

    Somogyi, Endre; Mansour, Andrew Abi; Ortoleva, Peter J.

    2016-05-01

    ProtoMD is a toolkit that facilitates the development of algorithms for multiscale molecular dynamics (MD) simulations. It is designed for multiscale methods which capture the dynamic transfer of information across multiple spatial scales, such as the atomic to the mesoscopic scale, via coevolving microscopic and coarse-grained (CG) variables. ProtoMD can be also be used to calibrate parameters needed in traditional CG-MD methods. The toolkit integrates 'GROMACS wrapper' to initiate MD simulations, and 'MDAnalysis' to analyze and manipulate trajectory files. It facilitates experimentation with a spectrum of coarse-grained variables, prototyping rare events (such as chemical reactions), or simulating nanocharacterization experiments such as terahertz spectroscopy, AFM, nanopore, and time-of-flight mass spectroscopy. ProtoMD is written in python and is freely available under the GNU General Public License from github.com/CTCNano/proto_md.

  19. Integration of mouse and human genome-wide association data identifies KCNIP4 as an asthma gene.

    Directory of Open Access Journals (Sweden)

    Blanca E Himes

    Full Text Available Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR. The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify asthma-related genes by integrating AHR associations in mouse with human genome-wide association study (GWAS data. We used Efficient Mixed Model Association (EMMA analysis to conduct a GWAS of baseline AHR measures from males and females of 31 mouse strains. Genes near or containing SNPs with EMMA p-values <0.001 were selected for further study in human GWAS. The results of the previously reported EVE consortium asthma GWAS meta-analysis consisting of 12,958 diverse North American subjects from 9 study centers were used to select a subset of homologous genes with evidence of association with asthma in humans. Following validation attempts in three human asthma GWAS (i.e., Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG and two human AHR GWAS (i.e., SHARP, DAG, the Kv channel interacting protein 4 (KCNIP4 gene was identified as nominally associated with both asthma and AHR at a gene- and SNP-level. In EVE, the smallest KCNIP4 association was at rs6833065 (P-value 2.9e-04, while the strongest associations for Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG were 1.5e-03, 1.0e-03, 3.1e-03 at rs7664617, rs4697177, rs4696975, respectively. At a SNP level, the strongest association across all asthma GWAS was at rs4697177 (P-value 1.1e-04. The smallest P-values for association with AHR were 2.3e-03 at rs11947661 in SHARP and 2.1e-03 at rs402802 in DAG. Functional studies are required to validate the potential involvement of KCNIP4 in modulating asthma susceptibility and/or AHR. Our results suggest that a useful approach to identify genes associated with human asthma is to leverage mouse AHR association data.

  20. Numerical Analysis of Multiscale Computations

    CERN Document Server

    Engquist, Björn; Tsai, Yen-Hsi R

    2012-01-01

    This book is a snapshot of current research in multiscale modeling, computations and applications. It covers fundamental mathematical theory, numerical algorithms as well as practical computational advice for analysing single and multiphysics models containing a variety of scales in time and space. Complex fluids, porous media flow and oscillatory dynamical systems are treated in some extra depth, as well as tools like analytical and numerical homogenization, and fast multipole method.

  1. MULTISCALE DYNAMICS OF SOLAR MAGNETIC STRUCTURES

    International Nuclear Information System (INIS)

    Uritsky, Vadim M.; Davila, Joseph M.

    2012-01-01

    Multiscale topological complexity of the solar magnetic field is among the primary factors controlling energy release in the corona, including associated processes in the photospheric and chromospheric boundaries. We present a new approach for analyzing multiscale behavior of the photospheric magnetic flux underlying these dynamics as depicted by a sequence of high-resolution solar magnetograms. The approach involves two basic processing steps: (1) identification of timing and location of magnetic flux origin and demise events (as defined by DeForest et al.) by tracking spatiotemporal evolution of unipolar and bipolar photospheric regions, and (2) analysis of collective behavior of the detected magnetic events using a generalized version of the Grassberger-Procaccia correlation integral algorithm. The scale-free nature of the developed algorithms makes it possible to characterize the dynamics of the photospheric network across a wide range of distances and relaxation times. Three types of photospheric conditions are considered to test the method: a quiet photosphere, a solar active region (NOAA 10365) in a quiescent non-flaring state, and the same active region during a period of M-class flares. The results obtained show (1) the presence of a topologically complex asymmetrically fragmented magnetic network in the quiet photosphere driven by meso- and supergranulation, (2) the formation of non-potential magnetic structures with complex polarity separation lines inside the active region, and (3) statistical signatures of canceling bipolar magnetic structures coinciding with flaring activity in the active region. Each of these effects can represent an unstable magnetic configuration acting as an energy source for coronal dissipation and heating.

  2. Relational grounding facilitates development of scientifically useful multiscale models

    Directory of Open Access Journals (Sweden)

    Lam Tai

    2011-09-01

    Full Text Available Abstract We review grounding issues that influence the scientific usefulness of any biomedical multiscale model (MSM. Groundings are the collection of units, dimensions, and/or objects to which a variable or model constituent refers. To date, models that primarily use continuous mathematics rely heavily on absolute grounding, whereas those that primarily use discrete software paradigms (e.g., object-oriented, agent-based, actor typically employ relational grounding. We review grounding issues and identify strategies to address them. We maintain that grounding issues should be addressed at the start of any MSM project and should be reevaluated throughout the model development process. We make the following points. Grounding decisions influence model flexibility, adaptability, and thus reusability. Grounding choices should be influenced by measures, uncertainty, system information, and the nature of available validation data. Absolute grounding complicates the process of combining models to form larger models unless all are grounded absolutely. Relational grounding facilitates referent knowledge embodiment within computational mechanisms but requires separate model-to-referent mappings. Absolute grounding can simplify integration by forcing common units and, hence, a common integration target, but context change may require model reengineering. Relational grounding enables synthesis of large, composite (multi-module models that can be robust to context changes. Because biological components have varying degrees of autonomy, corresponding components in MSMs need to do the same. Relational grounding facilitates achieving such autonomy. Biomimetic analogues designed to facilitate translational research and development must have long lifecycles. Exploring mechanisms of normal-to-disease transition requires model components that are grounded relationally. Multi-paradigm modeling requires both hyperspatial and relational grounding.

  3. Integrative Analysis of Hippocampus Gene Expression Profiles Identifies Network Alterations in Aging and Alzheimer’s Disease

    Directory of Open Access Journals (Sweden)

    Vinay Lanke

    2018-05-01

    Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder contributing to rapid decline in cognitive function and ultimately dementia. Most cases of AD occur in elderly and later years. There is a growing need for understanding the relationship between aging and AD to identify shared and unique hallmarks associated with the disease in a region and cell-type specific manner. Although genomic studies on AD have been performed extensively, the molecular mechanism of disease progression is still not clear. The major objective of our study is to obtain a higher-order network-level understanding of aging and AD, and their relationship using the hippocampal gene expression profiles of young (20–50 years, aging (70–99 years, and AD (70–99 years. The hippocampus is vulnerable to damage at early stages of AD and altered neurogenesis in the hippocampus is linked to the onset of AD. We combined the weighted gene co-expression network and weighted protein–protein interaction network-level approaches to study the transition from young to aging to AD. The network analysis revealed the organization of co-expression network into functional modules that are cell-type specific in aging and AD. We found that modules associated with astrocytes, endothelial cells and microglial cells are upregulated and significantly correlate with both aging and AD. The modules associated with neurons, mitochondria and endoplasmic reticulum are downregulated and significantly correlate with AD than aging. The oligodendrocytes module does not show significant correlation with neither aging nor disease. Further, we identified aging- and AD-specific interactions/subnetworks by integrating the gene expression with a human protein–protein interaction network. We found dysregulation of genes encoding protein kinases (FYN, SYK, SRC, PKC, MAPK1, ephrin receptors and transcription factors (FOS, STAT3, CEBPB, MYC, NFKβ, and EGR1 in AD. Further, we found genes that encode proteins

  4. MelanomaDB: a Web Tool for Integrative Analysis of Melanoma Genomic Information to Identify Disease-Associated Molecular Pathways

    Directory of Open Access Journals (Sweden)

    Alexander Joseph Trevarton

    2013-07-01

    Full Text Available Despite on-going research, metastatic melanoma survival rates remain low and treatment options are limited. Researchers can now access a rapidly growing amount of molecular and clinical information about melanoma. This information is becoming difficult to assemble and interpret due to its dispersed nature, yet as it grows it becomes increasingly valuable for understanding melanoma. Integration of this information into a comprehensive resource to aid rational experimental design and patient stratification is needed. As an initial step in this direction, we have assembled a web-accessible melanoma database, MelanomaDB, which incorporates clinical and molecular data from publically available sources, which will be regularly updated as new information becomes available. This database allows complex links to be drawn between many different aspects of melanoma biology: genetic changes (e.g. mutations in individual melanomas revealed by DNA sequencing, associations between gene expression and patient survival, data concerning drug targets, biomarkers, druggability and clinical trials, as well as our own statistical analysis of relationships between molecular pathways and clinical parameters that have been produced using these data sets. The database is freely available at http://genesetdb.auckland.ac.nz/melanomadb/about.html . A subset of the information in the database can also be accessed through a freely available web application in the Illumina genomic cloud computing platform BaseSpace at http://www.biomatters.com/apps/melanoma-profiler-for-research . This illustrates dysregulation of specific signalling pathways, both across 310 exome-sequenced melanomas and in individual tumours and identifies novel features about the distribution of somatic variants in melanoma. We suggest that this database can provide a context in which to interpret the tumour molecular profiles of individual melanoma patients relative to biological information and available

  5. Differential Geometry Based Multiscale Models

    Science.gov (United States)

    Wei, Guo-Wei

    2010-01-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that

  6. Differential geometry based multiscale models.

    Science.gov (United States)

    Wei, Guo-Wei

    2010-08-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier-Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson-Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson-Nernst-Planck equations that are

  7. Multiscale Simulation of Breaking Wave Impacts

    DEFF Research Database (Denmark)

    Lindberg, Ole

    compare reasonably well. The incompressible and inviscid ALE-WLS model is coupled with the potential flow model of Engsig-Karup et al. [2009], to perform multiscale calculation of breaking wave impacts on a vertical breakwater. The potential flow model provides accurate calculation of the wave...... with a potential flow model to provide multiscale calculation of forces from breaking wave impacts on structures....

  8. Multivariate refined composite multiscale entropy analysis

    International Nuclear Information System (INIS)

    Humeau-Heurtier, Anne

    2016-01-01

    Multiscale entropy (MSE) has become a prevailing method to quantify signals complexity. MSE relies on sample entropy. However, MSE may yield imprecise complexity estimation at large scales, because sample entropy does not give precise estimation of entropy when short signals are processed. A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. Nevertheless, RCMSE is for univariate signals only. The simultaneous analysis of multi-channel (multivariate) data often over-performs studies based on univariate signals. We therefore introduce an extension of RCMSE to multivariate data. Applications of multivariate RCMSE to simulated processes reveal its better performances over the standard multivariate MSE. - Highlights: • Multiscale entropy quantifies data complexity but may be inaccurate at large scale. • A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. • Nevertheless, RCMSE is adapted to univariate time series only. • We herein introduce an extension of RCMSE to multivariate data. • It shows better performances than the standard multivariate multiscale entropy.

  9. Integration of machine learning and meta-analysis identifies the transcriptomic bio-signature of mastitis disease in cattle.

    Science.gov (United States)

    Sharifi, Somayeh; Pakdel, Abbas; Ebrahimi, Mansour; Reecy, James M; Fazeli Farsani, Samaneh; Ebrahimie, Esmaeil

    2018-01-01

    Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the main agents that cause severe mastitis disease with clinical signs in dairy cattle. Rapid detection of this disease is so important in order to prevent transmission to other cows and helps to reduce inappropriate use of antibiotics. With the rapid progress in high-throughput technologies, and accumulation of various kinds of '-omics' data in public repositories, there is an opportunity to retrieve, integrate, and reanalyze these resources to improve the diagnosis and treatment of different diseases and to provide mechanistic insights into host resistance in an efficient way. Meta-analysis is a relatively inexpensive option with good potential to increase the statistical power and generalizability of single-study analysis. In the current meta-analysis research, six microarray-based studies that investigate the transcriptome profile of mammary gland tissue after induced mastitis by E. coli infection were used. This meta-analysis not only reinforced the findings in individual studies, but also several novel terms including responses to hypoxia, response to drug, anti-apoptosis and positive regulation of transcription from RNA polymerase II promoter enriched by up-regulated genes. Finally, in order to identify the small sets of genes that are sufficiently informative in E. coli mastitis, the differentially expressed gene introduced by meta-analysis were prioritized by using ten different attribute weighting algorithms. Twelve meta-genes were detected by the majority of attribute weighting algorithms (with weight above 0.7) as most informative genes including CXCL8 (IL8), NFKBIZ, HP, ZC3H12A, PDE4B, CASP4, CXCL2, CCL20, GRO1(CXCL1), CFB, S100A9, and S100A8. Interestingly, the results have been demonstrated that all of these genes are the key genes in the immune response, inflammation or mastitis. The Decision tree models efficiently discovered the best combination of the meta-genes as

  10. 49 CFR 192.917 - How does an operator identify potential threats to pipeline integrity and use the threat...

    Science.gov (United States)

    2010-10-01

    ... Transportation Other Regulations Relating to Transportation (Continued) PIPELINE AND HAZARDOUS MATERIALS SAFETY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) PIPELINE SAFETY TRANSPORTATION OF NATURAL AND OTHER GAS BY PIPELINE: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192...

  11. Multiscale empirical interpolation for solving nonlinear PDEs

    KAUST Repository

    Calo, Victor M.

    2014-12-01

    In this paper, we propose a multiscale empirical interpolation method for solving nonlinear multiscale partial differential equations. The proposed method combines empirical interpolation techniques and local multiscale methods, such as the Generalized Multiscale Finite Element Method (GMsFEM). To solve nonlinear equations, the GMsFEM is used to represent the solution on a coarse grid with multiscale basis functions computed offline. Computing the GMsFEM solution involves calculating the system residuals and Jacobians on the fine grid. We use empirical interpolation concepts to evaluate these residuals and Jacobians of the multiscale system with a computational cost which is proportional to the size of the coarse-scale problem rather than the fully-resolved fine scale one. The empirical interpolation method uses basis functions which are built by sampling the nonlinear function we want to approximate a limited number of times. The coefficients needed for this approximation are computed in the offline stage by inverting an inexpensive linear system. The proposed multiscale empirical interpolation techniques: (1) divide computing the nonlinear function into coarse regions; (2) evaluate contributions of nonlinear functions in each coarse region taking advantage of a reduced-order representation of the solution; and (3) introduce multiscale proper-orthogonal-decomposition techniques to find appropriate interpolation vectors. We demonstrate the effectiveness of the proposed methods on several nonlinear multiscale PDEs that are solved with Newton\\'s methods and fully-implicit time marching schemes. Our numerical results show that the proposed methods provide a robust framework for solving nonlinear multiscale PDEs on a coarse grid with bounded error and significant computational cost reduction.

  12. Pleural fluid cell-free DNA integrity index to identify cytologically negative malignant pleural effusions including mesotheliomas

    International Nuclear Information System (INIS)

    Sriram, Krishna B; Courtney, Deborah; Yang, Ian A; Bowman, Rayleen V; Fong, Kwun M; Relan, Vandana; Clarke, Belinda E; Duhig, Edwina E; Windsor, Morgan N; Matar, Kevin S; Naidoo, Rishendran; Passmore, Linda; McCaul, Elizabeth

    2012-01-01

    The diagnosis of malignant pleural effusions (MPE) is often clinically challenging, especially if the cytology is negative for malignancy. DNA integrity index has been reported to be a marker of malignancy. The aim of this study was to evaluate the utility of pleural fluid DNA integrity index in the diagnosis of MPE. We studied 75 pleural fluid and matched serum samples from consecutive subjects. Pleural fluid and serum ALU DNA repeats [115bp, 247bp and 247bp/115bp ratio (DNA integrity index)] were assessed by real-time quantitative PCR. Pleural fluid and serum mesothelin levels were quantified using ELISA. Based on clinico-pathological evaluation, 52 subjects had MPE (including 16 mesotheliomas) and 23 had benign effusions. Pleural fluid DNA integrity index was higher in MPE compared with benign effusions (1.2 vs. 0.8; p<0.001). Cytology had a sensitivity of 55% in diagnosing MPE. If cytology and pleural fluid DNA integrity index were considered together, they exhibited 81% sensitivity and 87% specificity in distinguishing benign and malignant effusions. In cytology-negative pleural effusions (35 MPE and 28 benign effusions), elevated pleural fluid DNA integrity index had an 81% positive predictive value in detecting MPEs. In the detection of mesothelioma, at a specificity of 90%, pleural fluid DNA integrity index had similar sensitivity to pleural fluid and serum mesothelin (75% each respectively). Pleural fluid DNA integrity index is a promising diagnostic biomarker for identification of MPEs, including mesothelioma. This biomarker may be particularly useful in cases of MPE where pleural aspirate cytology is negative, and could guide the decision to undertake more invasive definitive testing. A prospective validation study is being undertaken to validate our findings and test the clinical utility of this biomarker for altering clinical practice

  13. Shaken but not stirred: Multiscale habitat suitability modeling of sympatric marten species (Martes martes and Martes foina) in the northern Iberian Peninsula

    Science.gov (United States)

    Maria Vergara; Samuel A. Cushman; Fermin Urra; Aritz Ruiz-Gonzalez

    2016-01-01

    Multispecies and multiscale habitat suitability models (HSM) are important to identify the environmental variables and scales influencing habitat selection and facilitate the comparison of closely related species with different ecological requirements. Objectives This study explores the multiscale relationships of habitat suitability for the pine (Martes...

  14. Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers

    Energy Technology Data Exchange (ETDEWEB)

    Tang, Yu-Hang, E-mail: yuhang_tang@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Kudo, Shuhei, E-mail: shuhei-kudo@outlook.jp [Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe, 657-8501 (Japan); Bian, Xin, E-mail: xin_bian@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Li, Zhen, E-mail: zhen_li@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Collaboratory on Mathematics for Mesoscopic Modeling of Materials, Pacific Northwest National Laboratory, Richland, WA 99354 (United States)

    2015-09-15

    Graphical abstract: - Abstract: Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i.e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A data sampler concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create an easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers' own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and code flexibility. We validated the library by solving three different multiscale problems, which also serve to demonstrate the flexibility of the framework in handling heterogeneous models and solvers. In the first example, a Couette flow was simulated using two concurrently coupled Smoothed Particle Hydrodynamics (SPH) simulations of different spatial resolutions. In the second example, we coupled the deterministic SPH method with the stochastic Dissipative Particle Dynamics (DPD) method to study the effect of surface grafting on the hydrodynamics properties on the surface. In the third example, we consider conjugate heat transfer between a solid domain and a fluid domain by coupling the particle-based energy-conserving DPD (eDPD) method with the Finite Element Method (FEM)

  15. Peridynamic Multiscale Finite Element Methods

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Timothy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bond, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Littlewood, David John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moore, Stan Gerald [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic and local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the

  16. Metabolic dynamics in skeletal muscle during acute reduction in blood flow and oxygen supply to mitochondria: in-silico studies using a multi-scale, top-down integrated model.

    Science.gov (United States)

    Dash, Ranjan K; Li, Yanjun; Kim, Jaeyeon; Beard, Daniel A; Saidel, Gerald M; Cabrera, Marco E

    2008-09-09

    Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD(+). The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and

  17. Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.

    Science.gov (United States)

    Irigoyen, Antonio; Jimenez-Luna, Cristina; Benavides, Manuel; Caba, Octavio; Gallego, Javier; Ortuño, Francisco Manuel; Guillen-Ponce, Carmen; Rojas, Ignacio; Aranda, Enrique; Torres, Carolina; Prados, Jose

    2018-01-01

    Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

  18. Applying DLM and DCM concepts in a multi-scale data environment

    NARCIS (Netherlands)

    Stoter, Jantien; Meijers, Martijn; van Oosterom, Peter J.M.; Grünreich, Dietmar; Kraak, Menno-Jan

    2010-01-01

    This extended abstract presents work in progress in which we explore the DLM and DCM concepts in a multi-scale topographic data environment. The abstract is prepared as input for the Symposium on Generalisation and Data Integration (GDI), University of Colorado, Boulder, 20-22 June 2010.

  19. LANDSCAPE INFLUENCES ON IN-STREAM BIOTIC INTEGRITY: USE OF MACROINVERTEBRATE METRICS TO IDENTIFY LANDSCAPE STRESSORS IN HEADWATER CATCHMENTS

    Science.gov (United States)

    The biotic integrity of streams is profoundly influenced by quantitative and qualitative features in the landscape of the surrounding catchment. In this study, aquatic macroinvertebrate metrics (e.g., relative abundance of Ephemeroptera, Trichoptera, and/or Plecoptera taxa, or t...

  20. Multiscale modelling for tokamak pedestals

    Science.gov (United States)

    Abel, I. G.

    2018-04-01

    Pedestal modelling is crucial to predict the performance of future fusion devices. Current modelling efforts suffer either from a lack of kinetic physics, or an excess of computational complexity. To ameliorate these problems, we take a first-principles multiscale approach to the pedestal. We will present three separate sets of equations, covering the dynamics of edge localised modes (ELMs), the inter-ELM pedestal and pedestal turbulence, respectively. Precisely how these equations should be coupled to each other is covered in detail. This framework is completely self-consistent; it is derived from first principles by means of an asymptotic expansion of the fundamental Vlasov-Landau-Maxwell system in appropriate small parameters. The derivation exploits the narrowness of the pedestal region, the smallness of the thermal gyroradius and the low plasma (the ratio of thermal to magnetic pressures) typical of current pedestal operation to achieve its simplifications. The relationship between this framework and gyrokinetics is analysed, and possibilities to directly match our systems of equations onto multiscale gyrokinetics are explored. A detailed comparison between our model and other models in the literature is performed. Finally, the potential for matching this framework onto an open-field-line region is briefly discussed.

  1. Multi-scale organization of water vapor over low and mid-tropical Africa

    CSIR Research Space (South Africa)

    Botai, OJ

    2009-01-01

    Full Text Available stream_source_info Botai_2009.pdf.txt stream_content_type text/plain stream_size 23192 Content-Encoding UTF-8 stream_name Botai_2009.pdf.txt Content-Type text/plain; charset=UTF-8 1 MULTI-SCALE ORGANIZATION OF WATER.... Integrated water vapor field and multiscale variations over China from GPS measurements. J. appl., Meteo., Climatol., 47, pp. 3008-3015 8. Johnsen K. P., 2003. GPS atmosphere sounding project- An innovative approach for the recovery of atmospheric...

  2. Identifying and Integrating Relevant Educational/Instructional Technology (E/IT) for Culturally and Linguistically Diverse (CLD) Students with Disabilities in Urban Environments

    Science.gov (United States)

    Brown, Monica R.

    2013-01-01

    The aim of this manuscript is to address the significant void in the literature related to technology integration for culturally and linguistically diverse (CLD) students with disabilities living in urban communities. Given that the vast majority of CLD students attend school within urban districts, the focus of this article is to (a) identify and…

  3. Implementation of Grid-computing Framework for Simulation in Multi-scale Structural Analysis

    Directory of Open Access Journals (Sweden)

    Data Iranata

    2010-05-01

    Full Text Available A new grid-computing framework for simulation in multi-scale structural analysis is presented. Two levels of parallel processing will be involved in this framework: multiple local distributed computing environments connected by local network to form a grid-based cluster-to-cluster distributed computing environment. To successfully perform the simulation, a large-scale structural system task is decomposed into the simulations of a simplified global model and several detailed component models using various scales. These correlated multi-scale structural system tasks are distributed among clusters and connected together in a multi-level hierarchy and then coordinated over the internet. The software framework for supporting the multi-scale structural simulation approach is also presented. The program architecture design allows the integration of several multi-scale models as clients and servers under a single platform. To check its feasibility, a prototype software system has been designed and implemented to perform the proposed concept. The simulation results show that the software framework can increase the speedup performance of the structural analysis. Based on this result, the proposed grid-computing framework is suitable to perform the simulation of the multi-scale structural analysis.

  4. A high-throughput approach to identify compounds that impair envelope integrity in Escherichia coli

    DEFF Research Database (Denmark)

    Baker, Kristin Renee; Jana, Bimal; Franzyk, Henrik

    2016-01-01

    - to 125-fold) the MICs of erythromycin, fusidic acid, novobiocin and rifampin and displayed synergy (fractional inhibitory concentration index, antibiotics by checkerboard assays in two genetically distinct E. coli strains, including the high-risk multidrug-resistant, CTX-M-15-producing...... the discovery of antimicrobial helper drug candidates and targets that enhance the delivery of existing antibiotics by impairing envelope integrity in Gram-negative bacteria....

  5. A multiscale modeling approach for biomolecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)

    2015-04-15

    This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.

  6. Multiscale Concrete Modeling of Aging Degradation

    Energy Technology Data Exchange (ETDEWEB)

    Hammi, Yousseff [Mississippi State Univ., Mississippi State, MS (United States); Gullett, Philipp [Mississippi State Univ., Mississippi State, MS (United States); Horstemeyer, Mark F. [Mississippi State Univ., Mississippi State, MS (United States)

    2015-07-31

    In this work a numerical finite element framework is implemented to enable the integration of coupled multiscale and multiphysics transport processes. A User Element subroutine (UEL) in Abaqus is used to simultaneously solve stress equilibrium, heat conduction, and multiple diffusion equations for 2D and 3D linear and quadratic elements. Transport processes in concrete structures and their degradation mechanisms are presented along with the discretization of the governing equations. The multiphysics modeling framework is theoretically extended to the linear elastic fracture mechanics (LEFM) by introducing the eXtended Finite Element Method (XFEM) and based on the XFEM user element implementation of Giner et al. [2009]. A damage model that takes into account the damage contribution from the different degradation mechanisms is theoretically developed. The total contribution of damage is forwarded to a Multi-Stage Fatigue (MSF) model to enable the assessment of the fatigue life and the deterioration of reinforced concrete structures in a nuclear power plant. Finally, two examples are presented to illustrate the developed multiphysics user element implementation and the XFEM implementation of Giner et al. [2009].

  7. Multiscale Modeling of Mesoscale and Interfacial Phenomena

    Science.gov (United States)

    Petsev, Nikolai Dimitrov

    we provide a novel and general framework for multiscale modeling of systems featuring one or more dissolved species. This makes it possible to retain molecular detail for parts of the problem that require it while using a simple, continuum description for parts where high detail is unnecessary, reducing the number of degrees of freedom (i.e. number of particles) dramatically. This opens the possibility for modeling ion transport in biological processes and biomolecule assembly in ionic solution, as well as electrokinetic phenomena at interfaces such as corrosion. The number of particles in the system is further reduced through an integrated boundary approach, which we apply to colloidal suspensions. In this thesis, we describe this general framework for multiscale modeling single- and multicomponent systems, provide several simple equilibrium and non-equilibrium case studies, and discuss future applications.

  8. Foundations for a multiscale collaborative Earth model

    KAUST Repository

    Afanasiev, M.; Peter, Daniel; Sager, K.; Simut, S.; Ermert, L.; Krischer, L.; Fichtner, A.

    2015-01-01

    . The CSEM as a computational framework is intended to help bridging the gap between local, regional and global tomography, and to contribute to the development of a global multiscale Earth model. While the current construction serves as a first proof

  9. Integrative Bioinformatic Analysis of Transcriptomic Data Identifies Conserved Molecular Pathways Underlying Ionizing Radiation-Induced Bystander Effects (RIBE

    Directory of Open Access Journals (Sweden)

    Constantinos Yeles

    2017-11-01

    Full Text Available Ionizing radiation-induced bystander effects (RIBE encompass a number of effects with potential for a plethora of damages in adjacent non-irradiated tissue. The cascade of molecular events is initiated in response to the exposure to ionizing radiation (IR, something that may occur during diagnostic or therapeutic medical applications. In order to better investigate these complex response mechanisms, we employed a unified framework integrating statistical microarray analysis, signal normalization, and translational bioinformatics functional analysis techniques. This approach was applied to several microarray datasets from Gene Expression Omnibus (GEO related to RIBE. The analysis produced lists of differentially expressed genes, contrasting bystander and irradiated samples versus sham-irradiated controls. Furthermore, comparative molecular analysis through BioInfoMiner, which integrates advanced statistical enrichment and prioritization methodologies, revealed discrete biological processes, at the cellular level. For example, the negative regulation of growth, cellular response to Zn2+-Cd2+, and Wnt and NIK/NF-kappaB signaling, thus refining the description of the phenotypic landscape of RIBE. Our results provide a more solid understanding of RIBE cell-specific response patterns, especially in the case of high-LET radiations, like α-particles and carbon-ions.

  10. Integrative genome-wide expression profiling identifies three distinct molecular subgroups of renal cell carcinoma with different patient outcome

    Directory of Open Access Journals (Sweden)

    Beleut Manfred

    2012-07-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is characterized by a number of diverse molecular aberrations that differ among individuals. Recent approaches to molecularly classify RCC were based on clinical, pathological as well as on single molecular parameters. As a consequence, gene expression patterns reflecting the sum of genetic aberrations in individual tumors may not have been recognized. In an attempt to uncover such molecular features in RCC, we used a novel, unbiased and integrative approach. Methods We integrated gene expression data from 97 primary RCC of different pathologic parameters, 15 RCC metastases as well as 34 cancer cell lines for two-way nonsupervised hierarchical clustering using gene groups suggested by the PANTHER Classification System. We depicted the genomic landscape of the resulted tumor groups by means of Single Nuclear Polymorphism (SNP technology. Finally, the achieved results were immunohistochemically analyzed using a tissue microarray (TMA composed of 254 RCC. Results We found robust, genome wide expression signatures, which split RCC into three distinct molecular subgroups. These groups remained stable even if randomly selected gene sets were clustered. Notably, the pattern obtained from RCC cell lines was clearly distinguishable from that of primary tumors. SNP array analysis demonstrated differing frequencies of chromosomal copy number alterations among RCC subgroups. TMA analysis with group-specific markers showed a prognostic significance of the different groups. Conclusion We propose the existence of characteristic and histologically independent genome-wide expression outputs in RCC with potential biological and clinical relevance.

  11. An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

    Directory of Open Access Journals (Sweden)

    Lockwood William W

    2010-05-01

    Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.

  12. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro

    2016-01-01

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  13. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro

    2015-01-01

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  14. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro

    2015-01-07

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  15. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro

    2014-01-06

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  16. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro

    2016-01-06

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  17. Wavelets and multiscale signal processing

    CERN Document Server

    Cohen, Albert

    1995-01-01

    Since their appearance in mid-1980s, wavelets and, more generally, multiscale methods have become powerful tools in mathematical analysis and in applications to numerical analysis and signal processing. This book is based on "Ondelettes et Traitement Numerique du Signal" by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing. Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters and the importance of regularity for t...

  18. Multiphysics/multiscale multifluid computations

    International Nuclear Information System (INIS)

    Yadigaroglu, George

    2014-01-01

    Regarding experimentation, interesting examples of multi-scale approaches are found: the small-scale experiments to understand the mechanisms of counter-current flow limitations (CCFL) such as the growth of instabilities on films, droplet entrainment, etc; meso-scale experiments to quantify the CCFL conditions in typical geometries such as tubes and gaps between parallel plates, and finally full-scale experimentation in a typical reactor geometry - the UPTF tests. Another example is the mixing of the atmosphere produced by plumes and jets in a reactor containment: one needs first basic turbulence information that can be obtained at the microscopic level; follow medium-scale experiments to understand the behaviour of jets and plumes; finally reactor-scale tests can be conducted in facilities such as PANDA at PSI, in Switzerland to study the phenomena at large scale

  19. Multiscale modelling of DNA mechanics

    International Nuclear Information System (INIS)

    Dršata, Tomáš; Lankaš, Filip

    2015-01-01

    Mechanical properties of DNA are important not only in a wide range of biological processes but also in the emerging field of DNA nanotechnology. We review some of the recent developments in modeling these properties, emphasizing the multiscale nature of the problem. Modern atomic resolution, explicit solvent molecular dynamics simulations have contributed to our understanding of DNA fine structure and conformational polymorphism. These simulations may serve as data sources to parameterize rigid base models which themselves have undergone major development. A consistent buildup of larger entities involving multiple rigid bases enables us to describe DNA at more global scales. Free energy methods to impose large strains on DNA, as well as bead models and other approaches, are also briefly discussed. (topical review)

  20. Multiscale modeling of pedestrian dynamics

    CERN Document Server

    Cristiani, Emiliano; Tosin, Andrea

    2014-01-01

    This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually, and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.

  1. Integration of mouse and human genome-wide association data identifies KCNIP4 as an asthma gene

    NARCIS (Netherlands)

    Himes, Blanca E.; Sheppard, Keith; Berndt, Annerose; Leme, Adriana S.; Myers, Rachel A.; Gignoux, Christopher R.; Levin, Albert M.; Gauderman, W. James; Yang, James J.; Mathias, Rasika A.; Romieu, Isabelle; Torgerson, Dara G.; Roth, Lindsey A.; Huntsman, Scott; Eng, Celeste; Klanderman, Barbara; Ziniti, John; Senter-Sylvia, Jody; Szefler, Stanley J.; Lemanske, Robert F.; Zeiger, Robert S.; Strunk, Robert C.; Martinez, Fernando D.; Boushey, Homer; Chinchilli, Vernon M.; Israel, Elliot; Mauger, David; Koppelman, Gerard H.; Postma, Dirkje S.; Nieuwenhuis, Maartje A. E.; Vonk, Judith M.; Lima, John J.; Irvin, Charles G.; Peters, Stephen P.; Kubo, Michiaki; Tamari, Mayumi; Nakamura, Yusuke; Litonjua, Augusto A.; Tantisira, Kelan G.; Raby, Benjamin A.; Bleecker, Eugene R.; Meyers, Deborah A.; London, Stephanie J.; Barnes, Kathleen C.; Gilliland, Frank D.; Williams, L. Keoki; Burchard, Esteban G.; Nicolae, Dan L.; Ober, Carole; DeMeo, Dawn L.; Silverman, Edwin K.; Paigen, Beverly; Churchill, Gary; Shapiro, Steve D.; Weiss, Scott

    2013-01-01

    Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR). The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify

  2. Integration of molecular biology tools for identifying promoters and genes abundantly expressed in flowers of Oncidium Gower Ramsey

    Directory of Open Access Journals (Sweden)

    Tung Shu-Yun

    2011-04-01

    Full Text Available Abstract Background Orchids comprise one of the largest families of flowering plants and generate commercially important flowers. However, model plants, such as Arabidopsis thaliana do not contain all plant genes, and agronomic and horticulturally important genera and species must be individually studied. Results Several molecular biology tools were used to isolate flower-specific gene promoters from Oncidium 'Gower Ramsey' (Onc. GR. A cDNA library of reproductive tissues was used to construct a microarray in order to compare gene expression in flowers and leaves. Five genes were highly expressed in flower tissues, and the subcellular locations of the corresponding proteins were identified using lip transient transformation with fluorescent protein-fusion constructs. BAC clones of the 5 genes, together with 7 previously published flower- and reproductive growth-specific genes in Onc. GR, were identified for cloning of their promoter regions. Interestingly, 3 of the 5 novel flower-abundant genes were putative trypsin inhibitor (TI genes (OnTI1, OnTI2 and OnTI3, which were tandemly duplicated in the same BAC clone. Their promoters were identified using transient GUS reporter gene transformation and stable A. thaliana transformation analyses. Conclusions By combining cDNA microarray, BAC library, and bombardment assay techniques, we successfully identified flower-directed orchid genes and promoters.

  3. A concurrent multiscale micromorphic molecular dynamics

    International Nuclear Information System (INIS)

    Li, Shaofan; Tong, Qi

    2015-01-01

    In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from first principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation

  4. Integrating co-morbid depression and chronic physical disease management: identifying and resolving failures in self-regulation.

    Science.gov (United States)

    Detweiler-Bedell, Jerusha B; Friedman, Michael A; Leventhal, Howard; Miller, Ivan W; Leventhal, Elaine A

    2008-12-01

    Research suggests that treatments for depression among individuals with chronic physical disease do not improve disease outcomes significantly, and chronic disease management programs do not necessarily improve mood. For individuals experiencing co-morbid depression and chronic physical disease, demands on the self-regulation system are compounded, leading to a rapid depletion of self-regulatory resources. Because disease and depression management are not integrated, patients lack the understanding needed to prioritize self-regulatory goals in a way that makes disease and depression management synergistic. A framework in which the management of co-morbidity is considered alongside the management of either condition alone offers benefits to researchers and practitioners and may help improve clinical outcomes.

  5. Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

    Energy Technology Data Exchange (ETDEWEB)

    Verhaak, Roel GW; Hoadley, Katherine A; Purdom, Elizabeth; Wang, Victoria; Qi, Yuan; Wilkerson, Matthew D; Miller, C Ryan; Ding, Li; Golub, Todd; Mesirov, Jill P; Alexe, Gabriele; Lawrence, Michael; O' Kelly, Michael; Tamayo, Pablo; Weir, Barbara A; Gabriel, Stacey; Winckler, Wendy; Gupta, Supriya; Jakkula, Lakshmi; Feiler, Heidi S; Hodgson, J Graeme; James, C David; Sarkaria, Jann N; Brennan, Cameron; Kahn, Ari; Spellman, Paul T; Wilson, Richard K; Speed, Terence P; Gray, Joe W; Meyerson, Matthew; Getz, Gad; Perou, Charles M; Hayes, D Neil; Network, The Cancer Genome Atlas Research

    2009-09-03

    The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.

  6. Integrative analysis of functional genomic annotations and sequencing data to identify rare causal variants via hierarchical modeling

    Directory of Open Access Journals (Sweden)

    Marinela eCapanu

    2015-05-01

    Full Text Available Identifying the small number of rare causal variants contributing to disease has beena major focus of investigation in recent years, but represents a formidable statisticalchallenge due to the rare frequencies with which these variants are observed. In thiscommentary we draw attention to a formal statistical framework, namely hierarchicalmodeling, to combine functional genomic annotations with sequencing data with theobjective of enhancing our ability to identify rare causal variants. Using simulations weshow that in all configurations studied, the hierarchical modeling approach has superiordiscriminatory ability compared to a recently proposed aggregate measure of deleteriousness,the Combined Annotation-Dependent Depletion (CADD score, supportingour premise that aggregate functional genomic measures can more accurately identifycausal variants when used in conjunction with sequencing data through a hierarchicalmodeling approach

  7. An Integrated Approach Identifies Nhlh1 and Insm1 as Sonic Hedgehog-regulated Genes in Developing Cerebellum and Medulloblastoma

    Directory of Open Access Journals (Sweden)

    Enrico De Smaele

    2008-01-01

    Full Text Available Medulloblastoma (MB is the most common malignant brain tumor of childhood arising from deregulated cerebellar development. Sonic Hedgehog (Shh pathway plays a critical role in cerebellar development and its aberrant expression has been identified in MB. Gene expression profiling of cerebella from 1- to 14-day-old mice unveiled a cluster of genes whose expression correlates with the levels of Hedgehog (HH activity. From this cluster, we identified Insm1 and Nhlh1/NSCL1 as novel HH targets induced by Shh treatment in cultured cerebellar granule cell progenitors. Nhlh1 promoter was found to be bound and activated by Gli1 transcription factor. Remarkably, the expression of these genes is also upregulated in mouse and human HH-dependent MBs, suggesting that they may be either a part of the HH-induced tumorigenic process or a specific trait of HH-dependent tumor cells.

  8. Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes

    Directory of Open Access Journals (Sweden)

    Amanda M. Ackermann

    2016-03-01

    Conclusions: We have determined the genetic landscape of human α- and β-cells based on chromatin accessibility and transcript levels, which allowed for detection of novel α- and β-cell signature genes not previously known to be expressed in islets. Using fine-mapping of open chromatin, we have identified thousands of potential cis-regulatory elements that operate in an endocrine cell type-specific fashion.

  9. Integrated microarray and ChIP analysis identifies multiple Foxa2 dependent target genes in the notochord.

    Science.gov (United States)

    Tamplin, Owen J; Cox, Brian J; Rossant, Janet

    2011-12-15

    The node and notochord are key tissues required for patterning of the vertebrate body plan. Understanding the gene regulatory network that drives their formation and function is therefore important. Foxa2 is a key transcription factor at the top of this genetic hierarchy and finding its targets will help us to better understand node and notochord development. We performed an extensive microarray-based gene expression screen using sorted embryonic notochord cells to identify early notochord-enriched genes. We validated their specificity to the node and notochord by whole mount in situ hybridization. This provides the largest available resource of notochord-expressed genes, and therefore candidate Foxa2 target genes in the notochord. Using existing Foxa2 ChIP-seq data from adult liver, we were able to identify a set of genes expressed in the notochord that had associated regions of Foxa2-bound chromatin. Given that Foxa2 is a pioneer transcription factor, we reasoned that these sites might represent notochord-specific enhancers. Candidate Foxa2-bound regions were tested for notochord specific enhancer function in a zebrafish reporter assay and 7 novel notochord enhancers were identified. Importantly, sequence conservation or predictive models could not have readily identified these regions. Mutation of putative Foxa2 binding elements in two of these novel enhancers abrogated reporter expression and confirmed their Foxa2 dependence. The combination of highly specific gene expression profiling and genome-wide ChIP analysis is a powerful means of understanding developmental pathways, even for small cell populations such as the notochord. Copyright © 2011 Elsevier Inc. All rights reserved.

  10. Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

    Science.gov (United States)

    Lu, Zhao; Sun, Jing; Butts, Kenneth

    2014-05-01

    Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

  11. An integrated chemical biology approach identifies specific vulnerability of Ewing's sarcoma to combined inhibition of Aurora kinases A and B.

    Science.gov (United States)

    Winter, Georg E; Rix, Uwe; Lissat, Andrej; Stukalov, Alexey; Müllner, Markus K; Bennett, Keiryn L; Colinge, Jacques; Nijman, Sebastian M; Kubicek, Stefan; Kovar, Heinrich; Kontny, Udo; Superti-Furga, Giulio

    2011-10-01

    Ewing's sarcoma is a pediatric cancer of the bone that is characterized by the expression of the chimeric transcription factor EWS-FLI1 that confers a highly malignant phenotype and results from the chromosomal translocation t(11;22)(q24;q12). Poor overall survival and pronounced long-term side effects associated with traditional chemotherapy necessitate the development of novel, targeted, therapeutic strategies. We therefore conducted a focused viability screen with 200 small molecule kinase inhibitors in 2 different Ewing's sarcoma cell lines. This resulted in the identification of several potential molecular intervention points. Most notably, tozasertib (VX-680, MK-0457) displayed unique nanomolar efficacy, which extended to other cell lines, but was specific for Ewing's sarcoma. Furthermore, tozasertib showed strong synergies with the chemotherapeutic drugs etoposide and doxorubicin, the current standard agents for Ewing's sarcoma. To identify the relevant targets underlying the specific vulnerability toward tozasertib, we determined its cellular target profile by chemical proteomics. We identified 20 known and unknown serine/threonine and tyrosine protein kinase targets. Additional target deconvolution and functional validation by RNAi showed simultaneous inhibition of Aurora kinases A and B to be responsible for the observed tozasertib sensitivity, thereby revealing a new mechanism for targeting Ewing's sarcoma. We further corroborated our cellular observations with xenograft mouse models. In summary, the multilayered chemical biology approach presented here identified a specific vulnerability of Ewing's sarcoma to concomitant inhibition of Aurora kinases A and B by tozasertib and danusertib, which has the potential to become a new therapeutic option.

  12. Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics

    KAUST Repository

    Efendiev, Yalchin R.; Presho, Michael

    2015-01-01

    In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.

  13. Distributed multiscale computing with MUSCLE 2, the Multiscale Coupling Library and Environment

    NARCIS (Netherlands)

    Borgdorff, J.; Mamonski, M.; Bosak, B.; Kurowski, K.; Ben Belgacem, M.; Chopard, B.; Groen, D.; Coveney, P.V.; Hoekstra, A.G.

    2014-01-01

    We present the Multiscale Coupling Library and Environment: MUSCLE 2. This multiscale component-based execution environment has a simple to use Java, C++, C, Python and Fortran API, compatible with MPI, OpenMP and threading codes. We demonstrate its local and distributed computing capabilities and

  14. A distributed multiscale computation of a tightly coupled model using the Multiscale Modeling Language

    NARCIS (Netherlands)

    Borgdorff, J.; Bona-Casas, C.; Mamonski, M.; Kurowski, K.; Piontek, T.; Bosak, B.; Rycerz, K.; Ciepiela, E.; Gubala, T.; Harezlak, D.; Bubak, M.; Lorenz, E.; Hoekstra, A.G.

    2012-01-01

    Nature is observed at all scales; with multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed multiscale

  15. Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics

    KAUST Repository

    Efendiev, Yalchin R.

    2015-09-02

    In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.

  16. Integrating national community-based health worker programmes into health systems: a systematic review identifying lessons learned from low-and middle-income countries.

    Science.gov (United States)

    Zulu, Joseph Mumba; Kinsman, John; Michelo, Charles; Hurtig, Anna-Karin

    2014-09-22

    Despite the development of national community-based health worker (CBHW) programmes in several low- and middle-income countries, their integration into health systems has not been optimal. Studies have been conducted to investigate the factors influencing the integration processes, but systematic reviews to provide a more comprehensive understanding are lacking. We conducted a systematic review of published research to understand factors that may influence the integration of national CBHW programmes into health systems in low- and middle-income countries. To be included in the study, CBHW programmes should have been developed by the government and have standardised training, supervision and incentive structures. A conceptual framework on the integration of health innovations into health systems guided the review. We identified 3410 records, of which 36 were finally selected, and on which an analysis was conducted concerning the themes and pathways associated with different factors that may influence the integration process. Four programmes from Brazil, Ethiopia, India and Pakistan met the inclusion criteria. Different aspects of each of these programmes were integrated in different ways into their respective health systems. Factors that facilitated the integration process included the magnitude of countries' human resources for health problems and the associated discourses about how to address these problems; the perceived relative advantage of national CBHWs with regard to delivering health services over training and retaining highly skilled health workers; and the participation of some politicians and community members in programme processes, with the result that they viewed the programmes as legitimate, credible and relevant. Finally, integration of programmes within the existing health systems enhanced programme compatibility with the health systems' governance, financing and training functions. Factors that inhibited the integration process included a rapid

  17. Multiscale wavelet representations for mammographic feature analysis

    Science.gov (United States)

    Laine, Andrew F.; Song, Shuwu

    1992-12-01

    This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

  18. Identifying Pathways toward Sustainable Electricity Supply and Demand Using an Integrated Resource Strategic Planning Model for Saudi Arabia

    Science.gov (United States)

    Alabbas, Nabeel H.

    Despite holding 16% of proved oil reserves in the world, Saudi Arabia might be on an unsustainable path to become a net oil importer by the 2030s. Decades of domestic energy subsidies accompanied by a high population growth rate have encouraged inefficient production and high domestic consumption of fossil fuel energy, which has resulted in environmental degradation, and significant social and economic consequences. In addition, the government's dependence on oil as a main source of revenue (89%) to finance its development programs cannot be sustained due to oil's exhaustible nature and rapidly increasing domestic consumption. The electricity and water sectors consume more energy than other sectors. The literature review revealed that electricity use in Saudi Arabia is following an unsustainable path (7-8% annual growth over the last decade). The water sector is another major energy consumer due to an unprecedented demand for water in the Kingdom (18% of world's total desalinated water output with per capita consumption is twice the world average). Multiple entities have been involved in fragmented planning activities on the supply-side as well as to a certain extent on the demand-side; moreover, comprehensive integrated resource strategic plans have been lacking at the national level. This dissertation established an integrated resource strategic planning (IRSP) model for Saudi Arabia's electricity and water sectors. The IRSP can clearly determine the Kingdom's future vision of its utility sector, including goals, policies, programs, and an execution timetable, taking into consideration economic, environmental and social benefits. Also, a weather-based hybrid end-use econometric demand forecasting model was developed to project electricity demand until 2040. The analytical economic efficiency and technical assessments reveal that Saudi Arabia can supply almost 75% of its electricity from renewable energy sources with a significant achievable potential for saving

  19. An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection.

    Directory of Open Access Journals (Sweden)

    Vijay C Antharam

    Full Text Available Clostridium difficile infection (CDI is characterized by dysbiosis of the intestinal microbiota and a profound derangement in the fecal metabolome. However, the contribution of specific gut microbes to fecal metabolites in C. difficile-associated gut microbiome remains poorly understood. Using gas-chromatography mass spectrometry (GC-MS and 16S rRNA deep sequencing, we analyzed the metabolome and microbiome of fecal samples obtained longitudinally from subjects with Clostridium difficile infection (n = 7 and healthy controls (n = 6. From 155 fecal metabolites, we identified two sterol metabolites at >95% match to cholesterol and coprostanol that significantly discriminated C. difficile-associated gut microbiome from healthy microbiota. By correlating the levels of cholesterol and coprostanol in fecal extracts with 2,395 bacterial operational taxonomic units (OTUs determined by 16S rRNA sequencing, we identified 63 OTUs associated with high levels of coprostanol and 2 OTUs correlated with low coprostanol levels. Using indicator species analysis (ISA, 31 of the 63 coprostanol-associated bacteria correlated with health, and two Veillonella species were associated with low coprostanol levels that correlated strongly with CDI. These 65 bacterial taxa could be clustered into 12 sub-communities, with each community containing a consortium of organisms that co-occurred with one another. Our studies identified 63 human gut microbes associated with cholesterol-reducing activities. Given the importance of gut bacteria in reducing and eliminating cholesterol from the GI tract, these results support the recent finding that gut microbiome may play an important role in host lipid metabolism.

  20. An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection.

    Science.gov (United States)

    Antharam, Vijay C; McEwen, Daniel C; Garrett, Timothy J; Dossey, Aaron T; Li, Eric C; Kozlov, Andrew N; Mesbah, Zhubene; Wang, Gary P

    2016-01-01

    Clostridium difficile infection (CDI) is characterized by dysbiosis of the intestinal microbiota and a profound derangement in the fecal metabolome. However, the contribution of specific gut microbes to fecal metabolites in C. difficile-associated gut microbiome remains poorly understood. Using gas-chromatography mass spectrometry (GC-MS) and 16S rRNA deep sequencing, we analyzed the metabolome and microbiome of fecal samples obtained longitudinally from subjects with Clostridium difficile infection (n = 7) and healthy controls (n = 6). From 155 fecal metabolites, we identified two sterol metabolites at >95% match to cholesterol and coprostanol that significantly discriminated C. difficile-associated gut microbiome from healthy microbiota. By correlating the levels of cholesterol and coprostanol in fecal extracts with 2,395 bacterial operational taxonomic units (OTUs) determined by 16S rRNA sequencing, we identified 63 OTUs associated with high levels of coprostanol and 2 OTUs correlated with low coprostanol levels. Using indicator species analysis (ISA), 31 of the 63 coprostanol-associated bacteria correlated with health, and two Veillonella species were associated with low coprostanol levels that correlated strongly with CDI. These 65 bacterial taxa could be clustered into 12 sub-communities, with each community containing a consortium of organisms that co-occurred with one another. Our studies identified 63 human gut microbes associated with cholesterol-reducing activities. Given the importance of gut bacteria in reducing and eliminating cholesterol from the GI tract, these results support the recent finding that gut microbiome may play an important role in host lipid metabolism.

  1. Integration

    DEFF Research Database (Denmark)

    Emerek, Ruth

    2004-01-01

    Bidraget diskuterer de forskellige intergrationsopfattelse i Danmark - og hvad der kan forstås ved vellykket integration......Bidraget diskuterer de forskellige intergrationsopfattelse i Danmark - og hvad der kan forstås ved vellykket integration...

  2. Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics.

    Directory of Open Access Journals (Sweden)

    István A Kovács

    Full Text Available BACKGROUND: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. METHODOLOGY/PRINCIPAL FINDINGS: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1 determine persvasively overlapping modules with high resolution; (2 uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3 allow the determination of key network nodes and (4 help to predict network dynamics. CONCLUSIONS/SIGNIFICANCE: The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.

  3. MUSI: an integrated system for identifying multiple specificity from very large peptide or nucleic acid data sets.

    Science.gov (United States)

    Kim, Taehyung; Tyndel, Marc S; Huang, Haiming; Sidhu, Sachdev S; Bader, Gary D; Gfeller, David; Kim, Philip M

    2012-03-01

    Peptide recognition domains and transcription factors play crucial roles in cellular signaling. They bind linear stretches of amino acids or nucleotides, respectively, with high specificity. Experimental techniques that assess the binding specificity of these domains, such as microarrays or phage display, can retrieve thousands of distinct ligands, providing detailed insight into binding specificity. In particular, the advent of next-generation sequencing has recently increased the throughput of such methods by several orders of magnitude. These advances have helped reveal the presence of distinct binding specificity classes that co-exist within a set of ligands interacting with the same target. Here, we introduce a software system called MUSI that can rapidly analyze very large data sets of binding sequences to determine the relevant binding specificity patterns. Our pipeline provides two major advances. First, it can detect previously unrecognized multiple specificity patterns in any data set. Second, it offers integrated processing of very large data sets from next-generation sequencing machines. The results are visualized as multiple sequence logos describing the different binding preferences of the protein under investigation. We demonstrate the performance of MUSI by analyzing recent phage display data for human SH3 domains as well as microarray data for mouse transcription factors.

  4. Molecular cloning of the common acute lymphoblastic leukemia antigen (CALLA) identifies a type II integral membrane protein

    International Nuclear Information System (INIS)

    Shipp, M.A.; Richardson, N.E.; Sayre, P.H.; Brown, N.R.; Masteller, E.L.; Clayton, L.K.; Ritz, J.; Reinherz, E.L.

    1988-01-01

    Common acute lymphoblastic leukemia antigen (CALLA) is a 100-kDa cell-surface glycoprotein expressed on most acute lymphoblastic leukemias and certain other immature lymphoid malignancies and on normal lymphoid progenitors. The latter are either uncommitted to B- or T-cell lineage or committed to only the earliest stages of B- or T-lymphocyte maturation. To elucidate the primary structure of CALLA, the authors purified the protein to homogeneity, obtained the NH 2 -terminal sequence from both the intact protein and derived tryptic and V8 protease peptides and isolated CALLA cDNAs from a Nalm-6 cell line λgt10 library using redundant oligonucleotide probes. The CALLA cDNA sequence predicts a 750-amino acid integral membrane protein with a single 24-amino acid hydrophobic segment that could function as both a transmembrane region and a signal peptide. The COOH-terminal 700 amino acids, including six potential N-linked glycosylation sites compose the extracellular protein segment, whereas the 25 NM 2 -terminal amino acids remaining after cleavage of the initiation methionine form the cytoplasmic tail. CALLA + cells contain CALLA transcripts of 2.7 to 5.7 kilobases with the major 5.7- and 3.7-kilobase mRNAs being preferentially expressed in specific cell types

  5. An integrated structure- and system-based framework to identify new targets of metabolites and known drugs

    KAUST Repository

    Naveed, Hammad; Hameed, Umar Farook Shahul; Harrus, Deborah; Bourguet, William; Arold, Stefan T.; Gao, Xin

    2015-01-01

    Results: Here, we present a novel integrated structure- and system-based approach of drug-target prediction (iDTP) to enable the large-scale discovery of new targets for small molecules, such as pharmaceutical drugs, co-factors and metabolites (collectively called ‘drugs’). For a given drug, our method uses sequence order–independent structure alignment, hierarchical clustering, and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE) that captures promiscuous structural features of different binding sites on known targets. A drug’s PPE is combined with an approximation of its delivery profile to reduce false positives. In our cross-validation study, we use iDTP to predict the known targets of eleven drugs, with 63% sensitivity and 81% specificity. We then predicted novel targets for these drugs—two that are of high pharmacological interest, the nuclear receptor PPARγ and the oncogene Bcl-2, were successfully validated through in vitro binding experiments. Our method is broadly applicable for the prediction of protein-small molecule interactions with several novel applications to biological research and drug development.

  6. Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer

    Directory of Open Access Journals (Sweden)

    Deodutta Roy

    2015-10-01

    Full Text Available We present a combined environmental epidemiologic, genomic, and bioinformatics approach to identify: exposure of environmental chemicals with estrogenic activity; epidemiologic association between endocrine disrupting chemical (EDC and health effects, such as, breast cancer or endometriosis; and gene-EDC interactions and disease associations. Human exposure measurement and modeling confirmed estrogenic activity of three selected class of environmental chemicals, polychlorinated biphenyls (PCBs, bisphenols (BPs, and phthalates. Meta-analysis showed that PCBs exposure, not Bisphenol A (BPA and phthalates, increased the summary odds ratio for breast cancer and endometriosis. Bioinformatics analysis of gene-EDC interactions and disease associations identified several hundred genes that were altered by exposure to PCBs, phthalate or BPA. EDCs-modified genes in breast neoplasms and endometriosis are part of steroid hormone signaling and inflammation pathways. All three EDCs–PCB 153, phthalates, and BPA influenced five common genes—CYP19A1, EGFR, ESR2, FOS, and IGF1—in breast cancer as well as in endometriosis. These genes are environmentally and estrogen responsive, altered in human breast and uterine tumors and endometriosis lesions, and part of Mitogen Activated Protein Kinase (MAPK signaling pathways in cancer. Our findings suggest that breast cancer and endometriosis share some common environmental and molecular risk factors.

  7. Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.

    Science.gov (United States)

    Dao, Tien Tuan

    2017-06-01

    Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.

  8. Experience-based design for integrating the patient care experience into healthcare improvement: Identifying a set of reliable emotion words.

    Science.gov (United States)

    Russ, Lauren R; Phillips, Jennifer; Brzozowicz, Keely; Chafetz, Lynne A; Plsek, Paul E; Blackmore, C Craig; Kaplan, Gary S

    2013-12-01

    Experience-based design is an emerging method used to capture the emotional content of patient and family member healthcare experiences, and can serve as the foundation for patient-centered healthcare improvement. However, a core tool-the experience-based design questionnaire-requires words with consistent emotional meaning. Our objective was to identify and evaluate an emotion word set reliably categorized across the demographic spectrum as expressing positive, negative, or neutral emotions for experience-based design improvement work. We surveyed 407 patients, family members, and healthcare workers in 2011. Participants designated each of 67 potential emotion words as positive, neutral, or negative based on their emotional perception of the word. Overall agreement was assessed using the kappa statistic. Words were selected for retention in the final emotion word set based on 80% simple agreement on classification of meaning across subgroups. The participants were 47.9% (195/407) patients, 19.4% (33/407) family members and 32.7% (133/407) healthcare staff. Overall agreement adjusted for chance was moderate (k=0.55). However, agreement for positive (k=0.69) and negative emotions (k=0.68) was substantially higher, while agreement in the neutral category was low (k=0.11). There were 20 positive, 1 neutral, and 14 negative words retained for the final experience-based design emotion word set. We identified a reliable set of emotion words for experience questionnaires to serve as the foundation for patient-centered, experience-based redesign of healthcare. Incorporation of patient and family member perspectives in healthcare requires reliable tools to capture the emotional content of care touch points. Copyright © 2013 Elsevier Inc. All rights reserved.

  9. Fine mapping of a linkage peak with integration of lipid traits identifies novel coronary artery disease genes on chromosome 5

    Directory of Open Access Journals (Sweden)

    Nolan Daniel K

    2012-02-01

    Full Text Available Abstract Background Coronary artery disease (CAD, and one of its intermediate risk factors, dyslipidemia, possess a demonstrable genetic component, although the genetic architecture is incompletely defined. We previously reported a linkage peak on chromosome 5q31-33 for early-onset CAD where the strength of evidence for linkage was increased in families with higher mean low density lipoprotein-cholesterol (LDL-C. Therefore, we sought to fine-map the peak using association mapping of LDL-C as an intermediate disease-related trait to further define the etiology of this linkage peak. The study populations consisted of 1908 individuals from the CATHGEN biorepository of patients undergoing cardiac catheterization; 254 families (N = 827 individuals from the GENECARD familial study of early-onset CAD; and 162 aorta samples harvested from deceased donors. Linkage disequilibrium-tagged SNPs were selected with an average of one SNP per 20 kb for 126.6-160.2 MB (region of highest linkage and less dense spacing (one SNP per 50 kb for the flanking regions (117.7-126.6 and 160.2-167.5 MB and genotyped on all samples using a custom Illumina array. Association analysis of each SNP with LDL-C was performed using multivariable linear regression (CATHGEN and the quantitative trait transmission disequilibrium test (QTDT; GENECARD. SNPs associated with the intermediate quantitative trait, LDL-C, were then assessed for association with CAD (i.e., a qualitative phenotype using linkage and association in the presence of linkage (APL; GENECARD and logistic regression (CATHGEN and aortas. Results We identified four genes with SNPs that showed the strongest and most consistent associations with LDL-C and CAD: EBF1, PPP2R2B, SPOCK1, and PRELID2. The most significant results for association of SNPs with LDL-C were: EBF1, rs6865969, p = 0.01; PPP2R2B, rs2125443, p = 0.005; SPOCK1, rs17600115, p = 0.003; and PRELID2, rs10074645, p = 0.0002. The most significant results for

  10. Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

    Science.gov (United States)

    Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

    2015-01-01

    MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

  11. Multiscale Embedded Gene Co-expression Network Analysis.

    Directory of Open Access Journals (Sweden)

    Won-Min Song

    2015-11-01

    Full Text Available Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3, the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA by: i introducing quality control of co-expression similarities, ii parallelizing embedded network construction, and iii developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs. We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA. MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

  12. Multiscale Embedded Gene Co-expression Network Analysis.

    Science.gov (United States)

    Song, Won-Min; Zhang, Bin

    2015-11-01

    Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

  13. Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation

    Energy Technology Data Exchange (ETDEWEB)

    Hou, Thomas [California Inst. of Technology (CalTech), Pasadena, CA (United States); Efendiev, Yalchin [Stanford Univ., CA (United States); Tchelepi, Hamdi [Texas A & M Univ., College Station, TX (United States); Durlofsky, Louis [Stanford Univ., CA (United States)

    2016-05-24

    Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics.

  14. Multiscale analysis and computation for flows in heterogeneous media

    Energy Technology Data Exchange (ETDEWEB)

    Efendiev, Yalchin [Texas A & M Univ., College Station, TX (United States); Hou, T. Y. [California Inst. of Technology (CalTech), Pasadena, CA (United States); Durlofsky, L. J. [Stanford Univ., CA (United States); Tchelepi, H. [Stanford Univ., CA (United States)

    2016-08-04

    Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics. Below, we present a brief overview of each of these contributions.

  15. Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

    OpenAIRE

    Biggs, Matthew B.; Papin, Jason A.

    2013-01-01

    Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid mod...

  16. The NIF LinkOut broker: a web resource to facilitate federated data integration using NCBI identifiers.

    Science.gov (United States)

    Marenco, Luis; Ascoli, Giorgio A; Martone, Maryann E; Shepherd, Gordon M; Miller, Perry L

    2008-09-01

    This paper describes the NIF LinkOut Broker (NLB) that has been built as part of the Neuroscience Information Framework (NIF) project. The NLB is designed to coordinate the assembly of links to neuroscience information items (e.g., experimental data, knowledge bases, and software tools) that are (1) accessible via the Web, and (2) related to entries in the National Center for Biotechnology Information's (NCBI's) Entrez system. The NLB collects these links from each resource and passes them to the NCBI which incorporates them into its Entrez LinkOut service. In this way, an Entrez user looking at a specific Entrez entry can LinkOut directly to related neuroscience information. The information stored in the NLB can also be utilized in other ways. A second approach, which is operational on a pilot basis, is for the NLB Web server to create dynamically its own Web page of LinkOut links for each NCBI identifier in the NLB database. This approach can allow other resources (in addition to the NCBI Entrez) to LinkOut to related neuroscience information. The paper describes the current NLB system and discusses certain design issues that arose during its implementation.

  17. [Integrity].

    Science.gov (United States)

    Gómez Rodríguez, Rafael Ángel

    2014-01-01

    To say that someone possesses integrity is to claim that that person is almost predictable about responses to specific situations, that he or she can prudentially judge and to act correctly. There is a closed interrelationship between integrity and autonomy, and the autonomy rests on the deeper moral claim of all humans to integrity of the person. Integrity has two senses of significance for medical ethic: one sense refers to the integrity of the person in the bodily, psychosocial and intellectual elements; and in the second sense, the integrity is the virtue. Another facet of integrity of the person is la integrity of values we cherish and espouse. The physician must be a person of integrity if the integrity of the patient is to be safeguarded. The autonomy has reduced the violations in the past, but the character and virtues of the physician are the ultimate safeguard of autonomy of patient. A field very important in medicine is the scientific research. It is the character of the investigator that determines the moral quality of research. The problem arises when legitimate self-interests are replaced by selfish, particularly when human subjects are involved. The final safeguard of moral quality of research is the character and conscience of the investigator. Teaching must be relevant in the scientific field, but the most effective way to teach virtue ethics is through the example of the a respected scientist.

  18. Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L. Moench and related model species.

    Directory of Open Access Journals (Sweden)

    Adugna Abdi Woldesemayat

    Full Text Available Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations.In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO, Trait Ontology (TO, Plant Ontology (PO, Growth Ontology (GRO and Environment Ontology (EO were used to semantically integrate drought related information.Target genes linked to Quantitative Trait Loci (QTLs controlling yield and stress tolerance in sorghum (Sorghum bicolor (L. Moench and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%, salt (32%, cold (20%, heat (8% and oxidative stress (25% were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs

  19. Integration of Remote Sensing and other public GIS data source to identify suitable zones for groundwater exploitation by manual drilling

    Science.gov (United States)

    Fussi, Fabio; Fava, Francesco; Di Mauro, Biagio; Bonomi, Tullia; Fumagalli, Letizia; DI Leo, Margherita; Hamidou Kane, Cheik; Faye, Gayane; Niang, Magatte; Wade, Souleye; Hamidou, Barry; Colombo, Roberto

    2015-04-01

    In several countries of the world the situation of water supply is still critical, far from the international target defined by United Nations for 2015 (Millenium Development Goals) and producing a huge impact on health and living condition of the population. Manual drilling (it means techniques to drill boreholes for water using human or animal power) is well known and practiced for centuries in many countries. In recent years, it has been considered a potential strategy to increase water access in poor countries and has raised the attention of national governments and international organizations. Manual drilling is applicable only where hydrogeological context is suitable, according to the following conditions: thick layers of unconsolidated sediments and shallow water table. Mapping of zones with suitable hydrogeological context has been carried out in several countries in Africa, but the results have evident limitations; previous methods are based on existing direct data and qualitative experience, leading to unreliable interpretation when direct data are limited. This research aims to develop a methodology to estimate shallow hydrogeological features and asses the distribution of suitable zones for manual drilling through the integration of indirect information obtained from remote sensing and other existing source of data. The research is carried out in two different study areas, in Senegal and Guinea (Western Africa), with semi-arid climate, moderate vegetation cover, unconsolidated sandy and clay deposits overlaying sedimentary and igneous rocks A set of variables have been obtained through processing of three categories of data, listed below: - geology, geomorphology, soil and land cover, obtained from existing thematic maps; - vegetation phenology, apparent thermal inertia, and soil moisture, obtained from analysis of multitemporal optical (MOD13Q1), thermal (MOD11A1), and radar (ASAR) remotely sensed data: -morphometric parameters, obtained from public

  20. Oak Ridge Integrated Field-Scale Research Challenge ERKP686: Multi-scale Investigations on the Rates and Mechanisms of Targeted Immobilization and Natural Attenuation of Metal, Radionuclide and Co-Contaminants in the Subsurface (project overview)

    International Nuclear Information System (INIS)

    Phil Jardine; Dave Watson; Susan Hubbard; Ken Williams; J. Chen

    2007-01-01

    Historical disposal of wastes from the operation of three industrial plant sites on the Oak Ridge Reservation (ORR) has created extensive areas of subsurface inorganic, organic, and radioactive contamination (thousands of unlined trenches, pits, ponds). These wastes have resulted in approximately 1,500 acres of contaminated groundwater on the ORR. Much of the original contamination is now present as secondary sources within the soil-rock matrix outside of the original disposal sites. The secondary source areas are extensive and encompass regions on the watershed scale (tens of km). A significant limitation in assessing remediation needs of the secondary contaminant sources is the lack of information on the rates and mechanisms of coupled hydrological, geochemical, and microbial processes that control contaminant migration. Contaminant fluxes emanating from the secondary sources are often so high as to prevent complete attenuation of the groundwater plumes. Interventions such as source actions may be a prerequisite for effective and rapid natural attenuation (source actions such as: reduction of the soluble contaminant concentration at the source or controlling the flux from the source to groundwater by decreasing recharge). The goals are to advance the understanding and predictive capability of coupled hydrological, geochemical, and microbiological processes that control in situ transport, remediation and natural attenuation of metals, radionuclides, and co-contaminants (i.e. U, Tc, NO 3 ) across multiple scales ranging from molecular to watershed levels. Provide multi-process, multi-scale predictive monitoring and modeling tools that can be used at sites throughout the DOE complex to: (1) inform and improve the technical basis for decision making, and (2) assess which sites are amenable to natural attenuation and which would benefit from source zone remedial intervention. The objectives are: (1) quantify recharge and other hydraulic drivers for groundwater flow

  1. Hierarchical multiscale modeling for flows in fractured media using generalized multiscale finite element method

    KAUST Repository

    Efendiev, Yalchin R.

    2015-06-05

    In this paper, we develop a multiscale finite element method for solving flows in fractured media. Our approach is based on generalized multiscale finite element method (GMsFEM), where we represent the fracture effects on a coarse grid via multiscale basis functions. These multiscale basis functions are constructed in the offline stage via local spectral problems following GMsFEM. To represent the fractures on the fine grid, we consider two approaches (1) discrete fracture model (DFM) (2) embedded fracture model (EFM) and their combination. In DFM, the fractures are resolved via the fine grid, while in EFM the fracture and the fine grid block interaction is represented as a source term. In the proposed multiscale method, additional multiscale basis functions are used to represent the long fractures, while short-size fractures are collectively represented by a single basis functions. The procedure is automatically done via local spectral problems. In this regard, our approach shares common concepts with several approaches proposed in the literature as we discuss. We would like to emphasize that our goal is not to compare DFM with EFM, but rather to develop GMsFEM framework which uses these (DFM or EFM) fine-grid discretization techniques. Numerical results are presented, where we demonstrate how one can adaptively add basis functions in the regions of interest based on error indicators. We also discuss the use of randomized snapshots (Calo et al. Randomized oversampling for generalized multiscale finite element methods, 2014), which reduces the offline computational cost.

  2. Multiscale Processes in Magnetic Reconnection

    Science.gov (United States)

    Surjalal Sharma, A.; Jain, Neeraj

    The characteristic scales of the plasma processes in magnetic reconnection range from the elec-tron skin-depth to the magnetohydrodynamic (MHD) scale, and cross-scale coupling among them play a key role. Modeling these processes requires different physical models, viz. kinetic, electron-magnetohydrodynamics (EMHD), Hall-MHD, and MHD. The shortest scale processes are at the electron scale and these are modeled using an EMHD code, which provides many features of the multiscale behavior. In simulations using initial conditions consisting of pertur-bations with many scale sizes the reconnection takes place at many sites and the plasma flows from these interact with each other. This leads to thin current sheets with length less than 10 electron skin depths. The plasma flows also generate current sheets with multiple peaks, as observed by Cluster. The quadrupole structure of the magnetic field during reconnection starts on the electron scale and the interaction of inflow to the secondary sites and outflow from the dominant site generates a nested structure. In the outflow regions, the interaction of the electron outflows generated at the neighboring sites lead to the development of electron vortices. A signature of the nested structure of the Hall field is seen in Cluster observations, and more details of these features are expected from MMS.

  3. Multiscale reconstruction for MR fingerprinting.

    Science.gov (United States)

    Pierre, Eric Y; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A

    2016-06-01

    To reduce the acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in vivo data using the highly undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD), and B0 field variations in the brain was achieved in vivo for a 256 × 256 matrix for a total acquisition time of 10.2 s, representing a three-fold reduction in acquisition time. The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. Magn Reson Med 75:2481-2492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  4. Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

    Science.gov (United States)

    Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung

    2012-12-01

    What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To

  5. Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

    Science.gov (United States)

    Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

    2017-08-01

    Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

  6. Multiscale modeling in biomechanics and mechanobiology

    CERN Document Server

    Hwang, Wonmuk; Kuhl, Ellen

    2015-01-01

    Presenting a state-of-the-art overview of theoretical and computational models that link characteristic biomechanical phenomena, this book provides guidelines and examples for creating multiscale models in representative systems and organisms. It develops the reader's understanding of and intuition for multiscale phenomena in biomechanics and mechanobiology, and introduces a mathematical framework and computational techniques paramount to creating predictive multiscale models.   Biomechanics involves the study of the interactions of physical forces with biological systems at all scales – including molecular, cellular, tissue and organ scales. The emerging field of mechanobiology focuses on the way that cells produce and respond to mechanical forces – bridging the science of mechanics with the disciplines of genetics and molecular biology. Linking disparate spatial and temporal scales using computational techniques is emerging as a key concept in investigating some of the complex problems underlying these...

  7. Multi-scale modeling for sustainable chemical production.

    Science.gov (United States)

    Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J

    2013-09-01

    With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Multiscale modelling approaches for assessing cosmetic ingredients safety.

    Science.gov (United States)

    Bois, Frédéric Y; Ochoa, Juan G Diaz; Gajewska, Monika; Kovarich, Simona; Mauch, Klaus; Paini, Alicia; Péry, Alexandre; Benito, Jose Vicente Sala; Teng, Sophie; Worth, Andrew

    2017-12-01

    The European Union's ban on animal testing for cosmetic ingredients and products has generated a strong momentum for the development of in silico and in vitro alternative methods. One of the focus of the COSMOS project was ab initio prediction of kinetics and toxic effects through multiscale pharmacokinetic modeling and in vitro data integration. In our experience, mathematical or computer modeling and in vitro experiments are complementary. We present here a summary of the main models and results obtained within the framework of the project on these topics. A first section presents our work at the organelle and cellular level. We then go toward modeling cell levels effects (monitored continuously), multiscale physiologically based pharmacokinetic and effect models, and route to route extrapolation. We follow with a short presentation of the automated KNIME workflows developed for dissemination and easy use of the models. We end with a discussion of two challenges to the field: our limited ability to deal with massive data and complex computations. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  9. MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

    Directory of Open Access Journals (Sweden)

    Wasserman Wyeth W

    2011-03-01

    Full Text Available Abstract Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs, microRNAs (miRNAs and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs. Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL. In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT, an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http

  10. Euclidean distance can identify the mannitol level that produces the most remarkable integral effect on sugarcane micropropagation in temporary immersion bioreactors.

    Science.gov (United States)

    Gómez, Daviel; Hernández, L Ázaro; Yabor, Lourdes; Beemster, Gerrit T S; Tebbe, Christoph C; Papenbrock, Jutta; Lorenzo, José Carlos

    2018-03-15

    Plant scientists usually record several indicators in their abiotic factor experiments. The common statistical management involves univariate analyses. Such analyses generally create a split picture of the effects of experimental treatments since each indicator is addressed independently. The Euclidean distance combined with the information of the control treatment could have potential as an integrating indicator. The Euclidean distance has demonstrated its usefulness in many scientific fields but, as far as we know, it has not yet been employed for plant experimental analyses. To exemplify the use of the Euclidean distance in this field, we performed an experiment focused on the effects of mannitol on sugarcane micropropagation in temporary immersion bioreactors. Five mannitol concentrations were compared: 0, 50, 100, 150 and 200 mM. As dependent variables we recorded shoot multiplication rate, fresh weight, and levels of aldehydes, chlorophylls, carotenoids and phenolics. The statistical protocol which we then carried out integrated all dependent variables to easily identify the mannitol concentration that produced the most remarkable integral effect. Results provided by the Euclidean distance demonstrate a gradually increasing distance from the control in function of increasing mannitol concentrations. 200 mM mannitol caused the most significant alteration of sugarcane biochemistry and physiology under the experimental conditions described here. This treatment showed the longest statistically significant Euclidean distance to the control treatment (2.38). In contrast, 50 and 100 mM mannitol showed the lowest Euclidean distances (0.61 and 0.84, respectively) and thus poor integrated effects of mannitol. The analysis shown here indicates that the use of the Euclidean distance can contribute to establishing a more integrated evaluation of the contrasting mannitol treatments.

  11. Multiscale guidance and tools for implementing a landscape approach to resource management in the Bureau of Land Management

    Science.gov (United States)

    Carter, Sarah K.; Carr, Natasha B.; Miller, Kevin H.; Wood, David J.A.

    2017-01-19

    The Bureau of Land Management (BLM) is implementing a landscape approach to resource management (hereafter, landscape approach) to more effectively work with partners and understand the effects of management decisions. A landscape approach is a set of concepts and principles used to guide resource management when multiple stakeholders are involved and goals include diverse and sustainable social, environmental, and economic outcomes. Core principles of a landscape approach include seeking meaningful participation of diverse stakeholders, considering diverse resource values in multifunctional landscapes, acknowledging the tradeoffs needed to meet diverse objectives in the context of sustainable resource management, and addressing the complexity of social and ecological processes by embracing interdisciplinarity and considering multiple and broad spatial and temporal perspectives.In chapter 1, we outline the overall goal of this report: to provide a conceptual foundation and framework for implementing a landscape approach to resource management in the BLM, focusing on the role of multiscale natural resource monitoring and assessment information. In chapter 2, we describe a landscape approach to resource management. BLM actions taken to implement a landscape approach include a major effort to compile broad-scale data on natural resource status and condition across much of the west. These broadscale data now provide a regional context for interpreting monitoring data collected at individual sites and informing decisions made for local projects. We also illustrate the utility of using multiscale data to understand potential effects of different resource management decisions, define relevant terms in landscape ecology, and identify spatial scales at which planning and management decisions may be evaluated.In chapter 3, we describe how the BLM Rapid Ecoregional Assessment program and Assessment, Inventory and Monitoring program may be integrated to provide the multiscale

  12. State-of-the-Art Report on Multi-scale Modelling of Nuclear Fuels

    International Nuclear Information System (INIS)

    Bartel, T.J.; Dingreville, R.; Littlewood, D.; Tikare, V.; Bertolus, M.; Blanc, V.; Bouineau, V.; Carlot, G.; Desgranges, C.; Dorado, B.; Dumas, J.C.; Freyss, M.; Garcia, P.; Gatt, J.M.; Gueneau, C.; Julien, J.; Maillard, S.; Martin, G.; Masson, R.; Michel, B.; Piron, J.P.; Sabathier, C.; Skorek, R.; Toffolon, C.; Valot, C.; Van Brutzel, L.; Besmann, Theodore M.; Chernatynskiy, A.; Clarno, K.; Gorti, S.B.; Radhakrishnan, B.; Devanathan, R.; Dumont, M.; Maugis, P.; El-Azab, A.; Iglesias, F.C.; Lewis, B.J.; Krack, M.; Yun, Y.; Kurata, M.; Kurosaki, K.; Largenton, R.; Lebensohn, R.A.; Malerba, L.; Oh, J.Y.; Phillpot, S.R.; Tulenko, J. S.; Rachid, J.; Stan, M.; Sundman, B.; Tonks, M.R.; Williamson, R.; Van Uffelen, P.; Welland, M.J.; Valot, Carole; Stan, Marius; Massara, Simone; Tarsi, Reka

    2015-10-01

    Fuels is to document the development of multi-scale modelling approaches for fuels in support of current fuel optimisation programmes and innovative fuel designs. The objectives of the effort are: - assess international multi-scale modelling approaches devoted to nuclear fuels from the atomic to the macroscopic scale in order to share and promote such approaches; - address all types of fuels: both current (mainly oxide fuels) and advanced fuels (such as minor actinide containing oxide, carbide, nitride, or metal fuels); - address key engineering issues associated with each type of fuel; - assess the quality of existing links between the various scales and list needs for strengthening multi-scale modelling approaches; - identify the most relevant experimental data or experimental characterisation techniques that are missing for validation of fuel multi-scale modelling; - promote exchange between the actors involved at various scales; - promote exchange between multi-scale modelling experts and experimentalists; - exchange information with other expert groups of the WPMM. This report is organised as follows: - Part I lays out the different classes of phenomena relevant to nuclear fuel behaviour. Each chapter is further divided into topics relevant for each class of phenomena. - Part II is devoted to a description of the techniques used to obtain material properties necessary for describing the phenomena and their assessment. - Part III covers details relative to the principles and limits behind each modelling/computational technique as a reference for more detailed information. Included within the appropriate sections are critical analyses of the mid- and long-term challenges for the future (i.e., approximations, methods, scales, key experimental data, characterisation techniques missing or to be strengthened)

  13. Deductive multiscale simulation using order parameters

    Science.gov (United States)

    Ortoleva, Peter J.

    2017-05-16

    Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.

  14. Multiscale Modeling of Ceramic Matrix Composites

    Science.gov (United States)

    Bednarcyk, Brett A.; Mital, Subodh K.; Pineda, Evan J.; Arnold, Steven M.

    2015-01-01

    Results of multiscale modeling simulations of the nonlinear response of SiC/SiC ceramic matrix composites are reported, wherein the microstructure of the ceramic matrix is captured. This micro scale architecture, which contains free Si material as well as the SiC ceramic, is responsible for residual stresses that play an important role in the subsequent thermo-mechanical behavior of the SiC/SiC composite. Using the novel Multiscale Generalized Method of Cells recursive micromechanics theory, the microstructure of the matrix, as well as the microstructure of the composite (fiber and matrix) can be captured.

  15. EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis

    Science.gov (United States)

    Žvokelj, Matej; Zupan, Samo; Prebil, Ivan

    2016-05-01

    A novel multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role. The proposed method integrates the strengths of the Independent Component Analysis (ICA) multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD), which adaptively decomposes signals into different time scales and can thus cope with multiscale system dynamics. The method, which was named EEMD-based multiscale ICA (EEMD-MSICA), not only enables bearing fault detection but also offers a mechanism of multivariate signal denoising and, in combination with the Envelope Analysis (EA), a diagnostic tool. The multiscale nature of the proposed approach makes the method convenient to cope with data which emanate from bearings in complex real-world rotating machinery and frequently represent the cumulative effect of many underlying phenomena occupying different regions in the time-frequency plane. The efficiency of the proposed method was tested on simulated as well as real vibration and Acoustic Emission (AE) signals obtained through conducting an accelerated run-to-failure lifetime experiment on a purpose-built laboratory slewing bearing test stand. The ability to detect and locate the early-stage rolling-sliding contact fatigue failure of the bearing indicates that AE and vibration signals carry sufficient information on the bearing condition and that the developed EEMD-MSICA method is able to effectively extract it, thereby representing a reliable bearing fault detection and diagnosis strategy.

  16. Distinct high resolution genome profiles of early onset and late onset colorectal cancer integrated with gene expression data identify candidate susceptibility loci

    Directory of Open Access Journals (Sweden)

    Merok Marianne A

    2010-05-01

    Full Text Available Abstract Background Estimates suggest that up to 30% of colorectal cancers (CRC may develop due to an increased genetic risk. The mean age at diagnosis for CRC is about 70 years. Time of disease onset 20 years younger than the mean age is assumed to be indicative of genetic susceptibility. We have compared high resolution tumor genome copy number variation (CNV (Roche NimbleGen, 385 000 oligo CGH array in microsatellite stable (MSS tumors from two age groups, including 23 young at onset patients without known hereditary syndromes and with a median age of 44 years (range: 28-53 and 17 elderly patients with median age 79 years (range: 69-87. Our aim was to identify differences in the tumor genomes between these groups and pinpoint potential susceptibility loci. Integration analysis of CNV and genome wide mRNA expression data, available for the same tumors, was performed to identify a restricted candidate gene list. Results The total fraction of the genome with aberrant copy number, the overall genomic profile and the TP53 mutation spectrum were similar between the two age groups. However, both the number of chromosomal aberrations and the number of breakpoints differed significantly between the groups. Gains of 2q35, 10q21.3-22.1, 10q22.3 and 19q13.2-13.31 and losses from 1p31.3, 1q21.1, 2q21.2, 4p16.1-q28.3, 10p11.1 and 19p12, positions that in total contain more than 500 genes, were found significantly more often in the early onset group as compared to the late onset group. Integration analysis revealed a covariation of DNA copy number at these sites and mRNA expression for 107 of the genes. Seven of these genes, CLC, EIF4E, LTBP4, PLA2G12A, PPAT, RG9MTD2, and ZNF574, had significantly different mRNA expression comparing median expression levels across the transcriptome between the two groups. Conclusions Ten genomic loci, containing more than 500 protein coding genes, are identified as more often altered in tumors from early onset versus late

  17. Multivariate Generalized Multiscale Entropy Analysis

    Directory of Open Access Journals (Sweden)

    Anne Humeau-Heurtier

    2016-11-01

    Full Text Available Multiscale entropy (MSE was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii the computation of the sample entropy for each coarse-grained time series. A refined composite MSE (rcMSE—based on the same steps as MSE—also exists. Compared to MSE, rcMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy for short time series. The multivariate versions of MSE (MMSE and rcMSE (MrcMSE have also been introduced. In the coarse-graining step used in MSE, rcMSE, MMSE, and MrcMSE, the mean value is used to derive representations of the original data at different resolutions. A generalization of MSE was recently published, using the computation of different moments in the coarse-graining procedure. However, so far, this generalization only exists for univariate signals. We therefore herein propose an extension of this generalized MSE to multivariate data. The multivariate generalized algorithms of MMSE and MrcMSE presented herein (MGMSE and MGrcMSE, respectively are first analyzed through the processing of synthetic signals. We reveal that MGrcMSE shows better performance than MGMSE for short multivariate data. We then study the performance of MGrcMSE on two sets of short multivariate electroencephalograms (EEG available in the public domain. We report that MGrcMSE may show better performance than MrcMSE in distinguishing different types of multivariate EEG data. MGrcMSE could therefore supplement MMSE or MrcMSE in the processing of multivariate datasets.

  18. Big data-enabled multiscale serviceability analysis for aging bridges☆

    Directory of Open Access Journals (Sweden)

    Yu Liang

    2016-08-01

    Full Text Available This work is dedicated to constructing a multi-scale structural health monitoring system to monitor and evaluate the serviceability of bridges based on the Hadoop Ecosystem (MS-SHM-Hadoop. By taking the advantages of the fault-tolerant distributed file system called the Hadoop Distributed File System (HDFS and high-performance parallel data processing engine called MapReduce programming paradigm, MS-SHM-Hadoop features include high scalability and robustness in data ingestion, fusion, processing, retrieval, and analytics. MS-SHM-Hadoop is a multi-scale reliability analysis framework, which ranges from nationwide bridge-surveys, global structural integrity analysis, and structural component reliability analysis. This Nationwide bridge survey uses deep-learning techniques to evaluate the bridge serviceability according to real-time sensory data or archived bridge-related data such as traffic status, weather conditions and bridge structural configuration. The global structural integrity analysis of a targeted bridge is made by processing and analyzing the measured vibration signals incurred by external loads such as wind and traffic flow. Component-wise reliability analysis is also enabled by the deep learning technique, where the input data is derived from the measured structural load effects, hyper-spectral images, and moisture measurement of the structural components. As one of its major contributions, this work employs a Bayesian network to formulate the integral serviceability of a bridge according to its components serviceability and inter-component correlations. Here the inter-component correlations are jointly specified using a statistics-oriented machine learning method (e.g., association rule learning or structural mechanics modeling and simulation.

  19. Multiscale peak detection in wavelet space.

    Science.gov (United States)

    Zhang, Zhi-Min; Tong, Xia; Peng, Ying; Ma, Pan; Zhang, Ming-Jin; Lu, Hong-Mei; Chen, Xiao-Qing; Liang, Yi-Zeng

    2015-12-07

    Accurate peak detection is essential for analyzing high-throughput datasets generated by analytical instruments. Derivatives with noise reduction and matched filtration are frequently used, but they are sensitive to baseline variations, random noise and deviations in the peak shape. A continuous wavelet transform (CWT)-based method is more practical and popular in this situation, which can increase the accuracy and reliability by identifying peaks across scales in wavelet space and implicitly removing noise as well as the baseline. However, its computational load is relatively high and the estimated features of peaks may not be accurate in the case of peaks that are overlapping, dense or weak. In this study, we present multi-scale peak detection (MSPD) by taking full advantage of additional information in wavelet space including ridges, valleys, and zero-crossings. It can achieve a high accuracy by thresholding each detected peak with the maximum of its ridge. It has been comprehensively evaluated with MALDI-TOF spectra in proteomics, the CAMDA 2006 SELDI dataset as well as the Romanian database of Raman spectra, which is particularly suitable for detecting peaks in high-throughput analytical signals. Receiver operating characteristic (ROC) curves show that MSPD can detect more true peaks while keeping the false discovery rate lower than MassSpecWavelet and MALDIquant methods. Superior results in Raman spectra suggest that MSPD seems to be a more universal method for peak detection. MSPD has been designed and implemented efficiently in Python and Cython. It is available as an open source package at .

  20. Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

    Energy Technology Data Exchange (ETDEWEB)

    Stander, Nielen; Basudhar, Anirban; Basu, Ushnish; Gandikota, Imtiaz; Savic, Vesna; Sun, Xin; Choi, Kyoo Sil; Hu, Xiaohua; Pourboghrat, F.; Park, Taejoon; Mapar, Aboozar; Kumar, Shavan; Ghassemi-Armaki, Hassan; Abu-Farha, Fadi

    2015-09-14

    Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive

  1. Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

    Science.gov (United States)

    Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner

    2016-01-01

    Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.

  2. A multiscale method for assessing vegetation baseline of Environmental Impact Assessment (EIA) in protected areas of Chile

    Science.gov (United States)

    Anibal Pauchard; Eduardo Ugarte; Jaime Millan

    2000-01-01

    The exponential growth of recreation and tourism or ecotourism activities is affecting ecological processes in protected areas of Chile. In order to protect protected areas integrity, all projects inside their boundaries must pass through the Environmental Impact Assessment (EIA). The purpose of this research was to design a multiscale method to assess vegetation for...

  3. Low-carbon building assessment and multi-scale input-output analysis

    Science.gov (United States)

    Chen, G. Q.; Chen, H.; Chen, Z. M.; Zhang, Bo; Shao, L.; Guo, S.; Zhou, S. Y.; Jiang, M. M.

    2011-01-01

    Presented as a low-carbon building evaluation framework in this paper are detailed carbon emission account procedures for the life cycle of buildings in terms of nine stages as building construction, fitment, outdoor facility construction, transportation, operation, waste treatment, property management, demolition, and disposal for buildings, supported by integrated carbon intensity databases based on multi-scale input-output analysis, essential for low-carbon planning, procurement and supply chain design, and logistics management.

  4. Integrative systems analysis of diet-induced obesity identified a critical transition in the transcriptomes of the murine liver and epididymal white adipose tissue.

    Science.gov (United States)

    Kim, J; Kwon, E-Y; Park, S; Kim, J-R; Choi, S-W; Choi, M-S; Kim, S-J

    2016-02-01

    It is well known that high-fat diet (HFD) can cause immune system-related pathological alterations after a significant body weight gain. The mechanisms of the delayed pathological alterations during the development of diet-induced obesity (DIO) are not fully understood. To elucidate the mechanisms underlying DIO development, we analyzed time-course microarray data obtained from a previous study. First, differentially expressed genes (DEGs) were identified at each time point by comparing the hepatic transcriptome of mice fed HFD with that of mice fed normal diet. Next, we clustered the union of DEGs and identified annotations related to each cluster. Finally, we constructed an 'integrated obesity-associated gene regulatory network (GRN) in murine liver'. We analyzed the epididymal white adipose tissue (eWAT) transcriptome usig the same procedure. Based on time-course microarray data, we found that the genes associated with immune responses were upregulated with an oscillating expression pattern between weeks 2 and 8, relatively downregulated between weeks 12 and 16, and eventually upregulated after week 20 in the liver of the mice fed HFD. The genes associated with immune responses were also upregulated at late stage, in the eWAT of the mice fed HFD. These results suggested that a critical transition occurred in the immune system-related transcriptomes of the liver and eWAT around week 16 of the DIO development, and this may be associated with the delayed pathological alterations. The GRN analysis suggested that Maff may be a key transcription factor for the immune system-related critical transition thatoccurred at week 16. We found that transcription factors associated with immune responses were centrally located in the integrated obesity-associated GRN in the liver. In this study, systems analysis identified regulatory network modules underlying the delayed immune system-related pathological changes during the development of DIO and could suggest possible

  5. A multiscale approach to mutual information matching

    NARCIS (Netherlands)

    Pluim, J.P.W.; Maintz, J.B.A.; Viergever, M.A.; Hanson, K.M.

    1998-01-01

    Methods based on mutual information have shown promising results for matching of multimodal brain images. This paper discusses a multiscale approach to mutual information matching, aiming for an acceleration of the matching process while considering the accuracy and robustness of the method. Scaling

  6. Multiscale Lyapunov exponent for 2-microlocal functions

    International Nuclear Information System (INIS)

    Dhifaoui, Zouhaier; Kortas, Hedi; Ammou, Samir Ben

    2009-01-01

    The Lyapunov exponent is an important indicator of chaotic dynamics. Using wavelet analysis, we define a multiscale representation of this exponent which we demonstrate the scale-wise dependence for functions belonging to C x 0 s,s ' spaces. An empirical study involving simulated processes and financial time series corroborates the theoretical findings.

  7. Multiscale phenomenology of the cosmic web

    NARCIS (Netherlands)

    Aragón-Calvo, Miguel A.; van de Weygaert, Rien; Jones, Bernard J. T.

    2010-01-01

    We analyse the structure and connectivity of the distinct morphologies that define the cosmic web. With the help of our multiscale morphology filter (MMF), we dissect the matter distribution of a cosmological Lambda cold dark matter N-body computer simulation into cluster, filaments and walls. The

  8. Multiscale Modeling of Poromechanics in Geologic Media

    Science.gov (United States)

    Castelletto, N.; Hajibeygi, H.; Klevtsov, S.; Tchelepi, H.

    2017-12-01

    We describe a hybrid MultiScale Finite Element-Finite Volume (h-MSFE-FV) framework for the simulation of single-phase Darcy flow through deformable porous media that exhibit highly heterogeneous poromechanical properties over a wide range of length scales. In such systems, high resolution characterizations are a key requirement to obtain reliable modeling predictions and motivate the development of multiscale solution strategies to cope with the computational burden. A coupled two-field fine-scale mixed FE-FV discretization of the governing equations, namely conservation laws of linear momentum and mass, is first implemented based on a displacement-pressure formulation. After imposing a coarse-scale grid on the given fine-scale problem, for the MSFE displacement stage, the coarse-scale basis functions are obtained by solving local equilibrium problems within coarse elements. Such MSFE stage is then coupled with the MSFV method for flow, in which a dual-coarse grid is introduced to obtain approximate but conservative multiscale solutions. Robustness and accuracy of the proposed multiscale framework is demonstrated using a variety of challenging test problems.

  9. Multiscale empirical interpolation for solving nonlinear PDEs

    KAUST Repository

    Calo, Victor M.; Efendiev, Yalchin R.; Galvis, Juan; Ghommem, Mehdi

    2014-01-01

    residuals and Jacobians on the fine grid. We use empirical interpolation concepts to evaluate these residuals and Jacobians of the multiscale system with a computational cost which is proportional to the size of the coarse-scale problem rather than the fully

  10. Multiscale approach to equilibrating model polymer melts

    DEFF Research Database (Denmark)

    Svaneborg, Carsten; Ali Karimi-Varzaneh, Hossein; Hojdis, Nils

    2016-01-01

    We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed...

  11. Multiscale optimization of saturated poroelastic actuators

    DEFF Research Database (Denmark)

    Andreasen, Casper Schousboe; Sigmund, Ole

    A multiscale method for optimizing the material micro structure in a macroscopically heterogeneous saturated poroelastic media with respect to macro properties is presented. The method is based on topology optimization using the homogenization technique, here applied to the optimization of a bi...

  12. Generalized multiscale finite element methods: Oversampling strategies

    KAUST Repository

    Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian; Presho, Michael

    2014-01-01

    In this paper, we propose oversampling strategies in the generalized multiscale finite element method (GMsFEM) framework. The GMsFEM, which has been recently introduced in Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], allows solving multiscale parameter-dependent problems at a reduced computational cost by constructing a reduced-order representation of the solution on a coarse grid. The main idea of the method consists of (1) the construction of snapshot space, (2) the construction of the offline space, and (3) construction of the online space (the latter for parameter-dependent problems). In Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], it was shown that the GMsFEM provides a flexible tool to solve multiscale problems with a complex input space by generating appropriate snapshot, offline, and online spaces. In this paper, we develop oversampling techniques to be used in this context (see Hou and Wu (1997) where oversampling is introduced for multiscale finite element methods). It is known (see Hou and Wu (1997)) that the oversampling can improve the accuracy of multiscale methods. In particular, the oversampling technique uses larger regions (larger than the target coarse block) in constructing local basis functions. Our motivation stems from the analysis presented in this paper, which shows that when using oversampling techniques in the construction of the snapshot space and offline space, GMsFEM will converge independent of small scales and high contrast under certain assumptions. We consider the use of a multiple eigenvalue problems to improve the convergence and discuss their relation to single spectral problems that use oversampled regions. The oversampling procedures proposed in this paper differ from those in Hou and Wu (1997). In particular, the oversampling domains are partially used in constructing local

  13. Multi-scale dynamic modeling of atmospheric pollution in urban environment

    International Nuclear Information System (INIS)

    Thouron, Laetitia

    2017-01-01

    Urban air pollution has been identified as an important cause of health impacts, including premature deaths. In particular, ambient concentrations of gaseous pollutants such as nitrogen dioxide (NO 2 ) and particulate matter (PM10 and PM2.5) are regulated, which means that emission reduction strategies must be put in place to reduce these concentrations in places where the corresponding regulations are not respected. Besides, air pollution can contribute to the contamination of other media, for example through the contribution of atmospheric deposition to runoff contamination. The multifactorial and multi-scale aspects of urban make the pollution sources difficult to identify. Indeed, the urban environment is a heterogeneous space characterized by complex architectural structures (old buildings alongside a more modern building, residential, commercial, industrial zones, roads, etc.), non-uniform atmospheric pollutant emissions and therefore the population exposure to pollution is variable in space and time. The modeling of urban air pollution aims to understand the origin of pollutants, their spatial extent and their concentration/deposition levels. Some pollutants have long residence times and can stay several weeks in the atmosphere (PM2.5) and therefore be transported over long distances, while others are more local (NO x in the vicinity of traffic). The spatial distribution of a pollutant will therefore depend on several factors, and in particular on the surfaces encountered. Air quality depends strongly on weather, buildings (canyon-street) and emissions. The aim of this thesis is to address some of these aspects by modeling: (1) urban background pollution with a transport-chemical model (Polyphemus / POLAIR3D), which makes it possible to estimate atmospheric pollutants by type of urban surfaces (roofs, walls and roadways), (2) street-level pollution by explicitly integrating the effects of the building in a three-dimensional way with a multi-scale model of

  14. Cellular potts models multiscale extensions and biological applications

    CERN Document Server

    Scianna, Marco

    2013-01-01

    A flexible, cell-level, and lattice-based technique, the cellular Potts model accurately describes the phenomenological mechanisms involved in many biological processes. Cellular Potts Models: Multiscale Extensions and Biological Applications gives an interdisciplinary, accessible treatment of these models, from the original methodologies to the latest developments. The book first explains the biophysical bases, main merits, and limitations of the cellular Potts model. It then proposes several innovative extensions, focusing on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description. Through several biological examples, the authors demonstrate a qualitative and quantitative agreement with t...

  15. Model-to-model interface for multiscale materials modeling

    Energy Technology Data Exchange (ETDEWEB)

    Antonelli, Perry Edward [Iowa State Univ., Ames, IA (United States)

    2017-12-17

    A low-level model-to-model interface is presented that will enable independent models to be linked into an integrated system of models. The interface is based on a standard set of functions that contain appropriate export and import schemas that enable models to be linked with no changes to the models themselves. These ideas are presented in the context of a specific multiscale material problem that couples atomistic-based molecular dynamics calculations to continuum calculations of fluid ow. These simulations will be used to examine the influence of interactions of the fluid with an adjacent solid on the fluid ow. The interface will also be examined by adding it to an already existing modeling code, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and comparing it with our own molecular dynamics code.

  16. HAM-Based Adaptive Multiscale Meshless Method for Burgers Equation

    Directory of Open Access Journals (Sweden)

    Shu-Li Mei

    2013-01-01

    Full Text Available Based on the multilevel interpolation theory, we constructed a meshless adaptive multiscale interpolation operator (MAMIO with the radial basis function. Using this operator, any nonlinear partial differential equations such as Burgers equation can be discretized adaptively in physical spaces as a nonlinear matrix ordinary differential equation. In order to obtain the analytical solution of the system of ODEs, the homotopy analysis method (HAM proposed by Shijun Liao was developed to solve the system of ODEs by combining the precise integration method (PIM which can be employed to get the analytical solution of linear system of ODEs. The numerical experiences show that HAM is not sensitive to the time step, and so the arithmetic error is mainly derived from the discrete in physical space.

  17. Multiscale Computation. Needs and Opportunities for BER Science

    Energy Technology Data Exchange (ETDEWEB)

    Scheibe, Timothy D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Smith, Jeremy C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-01-01

    The Environmental Molecular Sciences Laboratory (EMSL), a scientific user facility managed by Pacific Northwest National Laboratory for the U.S. Department of Energy, Office of Biological and Environmental Research (BER), conducted a one-day workshop on August 26, 2014 on the topic of “Multiscale Computation: Needs and Opportunities for BER Science.” Twenty invited participants, from various computational disciplines within the BER program research areas, were charged with the following objectives; Identify BER-relevant models and their potential cross-scale linkages that could be exploited to better connect molecular-scale research to BER research at larger scales and; Identify critical science directions that will motivate EMSL decisions regarding future computational (hardware and software) architectures.

  18. Multiscale impact of fuel consumption on air quality

    Energy Technology Data Exchange (ETDEWEB)

    Hidy, G.M. [Envair/Aerochem, Placitas, NM (USA)

    2002-04-01

    Energy production from combustion of fossil fuels tends to dominate the emissions of criteria pollutants. Emissions derive both from large stationary sources with tall stacks such as fossil-fuelled power plants, and from the ground level use of fuels in transportation. Management of these sources presents a challenge in the light of multi-scale processes that influence ambient concentration and exposure patterns. Directly emitted pollutants and those resulting from atmospheric chemistry, like O{sub 3} and sulfate, nitrate and some organic material in fine particles, are affected by phenomena extending over a range of less than a meter to 10{sup 7} meters in spatial scale, and minutes to many years in temporal scale. Their environmental effects have an analogous wide range of descriptive spatial and temporal scale. Pollution phenomena can be thought of in terms of three major groupings: neighbourhood - urban, regional, and continental - global. Currently, decision-makers are developing emission reduction strategies that conceptually integrate considerations over this entire range of scales. In keeping with conceptual integration, recent studies and analyses are bridging different spatial and temporal scales in observations and in mathematical descriptions. Some examples of contemporary issues falling within different scales are described that illustrate approaches to add insight for developing regulatory strategies. A key element in the technical approaches is the application of air quality and exposure modeling using spatially nested descriptions of atmospheric phenomena. The reliability of multi-scale models remains a concern so that analyses for US regulatory applications combine the results of modeling with observations, and knowledge of spatially and temporally differentiated emissions. 32 refs., 3 tabs.

  19. Hybrid numerical methods for multiscale simulations of subsurface biogeochemical processes

    International Nuclear Information System (INIS)

    Scheibe, T D; Tartakovsky, A M; Tartakovsky, D M; Redden, G D; Meakin, P

    2007-01-01

    Many subsurface flow and transport problems of importance today involve coupled non-linear flow, transport, and reaction in media exhibiting complex heterogeneity. In particular, problems involving biological mediation of reactions fall into this class of problems. Recent experimental research has revealed important details about the physical, chemical, and biological mechanisms involved in these processes at a variety of scales ranging from molecular to laboratory scales. However, it has not been practical or possible to translate detailed knowledge at small scales into reliable predictions of field-scale phenomena important for environmental management applications. A large assortment of numerical simulation tools have been developed, each with its own characteristic scale. Important examples include 1. molecular simulations (e.g., molecular dynamics); 2. simulation of microbial processes at the cell level (e.g., cellular automata or particle individual-based models); 3. pore-scale simulations (e.g., lattice-Boltzmann, pore network models, and discrete particle methods such as smoothed particle hydrodynamics); and 4. macroscopic continuum-scale simulations (e.g., traditional partial differential equations solved by finite difference or finite element methods). While many problems can be effectively addressed by one of these models at a single scale, some problems may require explicit integration of models across multiple scales. We are developing a hybrid multi-scale subsurface reactive transport modeling framework that integrates models with diverse representations of physics, chemistry and biology at different scales (sub-pore, pore and continuum). The modeling framework is being designed to take advantage of advanced computational technologies including parallel code components using the Common Component Architecture, parallel solvers, gridding, data and workflow management, and visualization. This paper describes the specific methods/codes being used at each

  20. Reduced-Contrast Approximations for High-Contrast Multiscale Flow Problems

    KAUST Repository

    Chung, Eric T.; Efendiev, Yalchin

    2010-01-01

    In this paper, we study multiscale methods for high-contrast elliptic problems where the media properties change dramatically. The disparity in the media properties (also referred to as high contrast in the paper) introduces an additional scale that needs to be resolved in multiscale simulations. First, we present a construction that uses an integral equation to represent the highcontrast component of the solution. This representation involves solving an integral equation along the interface where the coefficients are discontinuous. The integral representation suggests some multiscale approaches that are discussed in the paper. One of these approaches entails the use of interface functions in addition to multiscale basis functions representing the heterogeneities without high contrast. In this paper, we propose an approximation for the solution of the integral equation using the interface problems in reduced-contrast media. Reduced-contrast media are obtained by lowering the variance of the coefficients. We also propose a similar approach for the solution of the elliptic equation without using an integral representation. This approach is simpler to use in the computations because it does not involve setting up integral equations. The main idea of this approach is to approximate the solution of the high-contrast problem by the solutions of the problems formulated in reduced-contrast media. In this approach, a rapidly converging sequence is proposed where only problems with lower contrast are solved. It was shown that this sequence possesses the convergence rate that is inversely proportional to the reduced contrast. This approximation allows choosing the reduced-contrast problem based on the coarse-mesh size as discussed in this paper. We present a simple application of this approach to homogenization of elliptic equations with high-contrast coefficients. The presented approaches are limited to the cases where there are sharp changes in the contrast (i.e., the high

  1. Identifying the Integrated Neural Networks Involved in Capsaicin-Induced Pain Using fMRI in Awake TRPV1 Knockout and Wild-Type Rats

    Directory of Open Access Journals (Sweden)

    Jason Richard Yee

    2015-02-01

    Full Text Available In the present study, we used functional MRI in awake rats to investigate the pain response that accompanies intradermal injection of capsaicin into the hindpaw. To this end, we used BOLD imaging together with a 3D segmented, annotated rat atlas and computational analysis to identify the integrated neural circuits involved in capsaicin-induced pain. The specificity of the pain response to capsaicin was tested in a transgenic model that contains a biallelic deletion of the gene encoding for the transient receptor potential cation channel subfamily V member 1 (TRPV1. Capsaicin is an exogenous ligand for the TRPV1 receptor, and in wild-type rats, activated the putative pain neural circuit. In addition, capsaicin-treated wild-type rats exhibited activation in brain regions comprising the Papez circuit and habenular system, systems that play important roles in the integration of emotional information, and learning and memory of aversive information, respectively. As expected, capsaicin administration to TRPV1-KO rats failed to elicit the robust BOLD activation pattern observed in wild-type controls. However, the intradermal injection of formalin elicited a significant activation of the putative pain pathway as represented by such areas as the anterior cingulate, somatosensory cortex, parabrachial nucleus, and periaqueductal gray. Notably, comparison of neural responses to capsaicin in wild-type versus knock-out rats uncovered evidence that capsaicin may function in an antinociceptive capacity independent of TRPV1 signaling. Our data suggest that neuroimaging of pain in awake, conscious animals has the potential to inform the neurobiological basis of full and integrated perceptions of pain.

  2. Identifying and intervening with substance-using women exposed to intimate partner violence: phenomenology, comorbidities, and integrated approaches within primary care and other agency settings.

    Science.gov (United States)

    Weaver, Terri L; Gilbert, Louisa; El-Bassel, Nabila; Resnick, Heidi S; Noursi, Samia

    2015-01-01

    Substance use and/or disorders (SUDs) have been identified as a significant correlate of intimate partner violence (IPV) exposure and present complex issues that intersect with the topography of IPV, attendant mental health, and physical co-morbidities and may pose barriers to primary care- and other agency-based screening and intervention efforts. Despite substantial research indicating significantly higher rates of all types and severity of IPV victimization among women with SUDs and bidirectional associations between partner or self-use of drugs or alcohol and IPV victimization, effective screening, brief interventions, coordinated systems of care, and treatment approaches to address these co-occurring problems remain very limited. We integrated select research examining the intersection of IPV victimization and SUDs and several comorbidities that have significant public health impact and provided recommendations for scaling up targeted interventions to redress these co-occurring problems among women in primary, emergency, and other care settings.

  3. Reading for Integration, Identifying Complementary Threshold Concepts: The ACRL Framework in Conversation with Naming What We Know: Threshold Concepts of Writing Studies

    Directory of Open Access Journals (Sweden)

    Brittney Johnson

    2016-12-01

    Full Text Available In 2015, threshold concepts formed the foundation of two disciplinary documents: the ACRL Framework for Information Literacy (2015 and Naming What We Know: Threshold Concepts of Writing Studies (2015. While there is no consensus in the fields about the value of threshold concepts in teaching, reading the six Frames in the ACRL document alongside the threshold concepts of writing studies illuminates overlapping elements that may empower faculty in both fields to advocate collectively against skills-focused writing and research instruction through cross-disciplinary integrations. To facilitate cross-disciplinary conversations around the documents, the authors propose an order for reading the Frames, identify the associated writing concepts, and explain how the shared concepts reveal an internal complexity which may have implications for teaching the ACRL Framework.

  4. Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

    International Nuclear Information System (INIS)

    Fukunaga, Satoki; Kakehashi, Anna; Sumida, Kayo; Kushida, Masahiko; Asano, Hiroyuki; Gi, Min; Wanibuchi, Hideki

    2015-01-01

    To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective of initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis

  5. Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

    Energy Technology Data Exchange (ETDEWEB)

    Fukunaga, Satoki [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558 (Japan); Kakehashi, Anna [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Sumida, Kayo; Kushida, Masahiko; Asano, Hiroyuki [Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558 (Japan); Gi, Min [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Wanibuchi, Hideki, E-mail: wani@med.osaka-cu.ac.jp [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan)

    2015-08-01

    To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective of initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis.

  6. Integration of Serum Protein Biomarker and Tumor Associated Autoantibody Expression Data Increases the Ability of a Blood-Based Proteomic Assay to Identify Breast Cancer.

    Directory of Open Access Journals (Sweden)

    Meredith C Henderson

    Full Text Available Despite significant advances in breast imaging, the ability to accurately detect Breast Cancer (BC remains a challenge. With the discovery of key biomarkers and protein signatures for BC, proteomic technologies are currently poised to serve as an ideal diagnostic adjunct to imaging. Research studies have shown that breast tumors are associated with systemic changes in levels of both serum protein biomarkers (SPB and tumor associated autoantibodies (TAAb. However, the independent contribution of SPB and TAAb expression data for identifying BC relative to a combinatorial SPB and TAAb approach has not been fully investigated. This study evaluates these contributions using a retrospective cohort of pre-biopsy serum samples with known clinical outcomes collected from a single site, thus minimizing potential site-to-site variation and enabling direct assessment of SPB and TAAb contributions to identify BC. All serum samples (n = 210 were collected prior to biopsy. These specimens were obtained from 18 participants with no evidence of breast disease (ND, 92 participants diagnosed with Benign Breast Disease (BBD and 100 participants diagnosed with BC, including DCIS. All BBD and BC diagnoses were based on pathology results from biopsy. Statistical models were developed to differentiate BC from non-BC (i.e., BBD and ND using expression data from SPB alone, TAAb alone, and a combination of SPB and TAAb. When SPB data was independently used for modeling, clinical sensitivity and specificity for detection of BC were 74.7% and 77.0%, respectively. When TAAb data was independently used, clinical sensitivity and specificity for detection of BC were 72.2% and 70.8%, respectively. When modeling integrated data from both SPB and TAAb, the clinical sensitivity and specificity for detection of BC improved to 81.0% and 78.8%, respectively. These data demonstrate the benefit of the integration of SPB and TAAb data and strongly support the further development of

  7. Integrative Analysis of Genetic, Genomic, and Phenotypic Data for Ethanol Behaviors: A Network-Based Pipeline for Identifying Mechanisms and Potential Drug Targets.

    Science.gov (United States)

    Bogenpohl, James W; Mignogna, Kristin M; Smith, Maren L; Miles, Michael F

    2017-01-01

    Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce nonbiased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA, and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x

  8. Supervision, support and mentoring interventions for health practitioners in rural and remote contexts: an integrative review and thematic synthesis of the literature to identify mechanisms for successful outcomes.

    Science.gov (United States)

    Moran, Anna M; Coyle, Julia; Pope, Rod; Boxall, Dianne; Nancarrow, Susan A; Young, Jennifer

    2014-02-13

    To identify mechanisms for the successful implementation of support strategies for health-care practitioners in rural and remote contexts. This is an integrative review and thematic synthesis of the empirical literature that examines support interventions for health-care practitioners in rural and remote contexts. This review includes 43 papers that evaluated support strategies for the rural and remote health workforce. Interventions were predominantly training and education programmes with limited evaluations of supervision and mentoring interventions. The mechanisms associated with successful outcomes included: access to appropriate and adequate training, skills and knowledge for the support intervention; accessible and adequate resources; active involvement of stakeholders in programme design, implementation and evaluation; a needs analysis prior to the intervention; external support, organisation, facilitation and/or coordination of the programme; marketing of the programme; organisational commitment; appropriate mode of delivery; leadership; and regular feedback and evaluation of the programme. Through a synthesis of the literature, this research has identified a number of mechanisms that are associated with successful support interventions for health-care practitioners in rural and remote contexts. This research utilised a methodology developed for studying complex interventions in response to the perceived limitations of traditional systematic reviews. This synthesis of the evidence will provide decision-makers at all levels with a collection of mechanisms that can assist the development and implementation of support strategies for staff in rural and remote contexts.

  9. Supervision, support and mentoring interventions for health practitioners in rural and remote contexts: an integrative review and thematic synthesis of the literature to identify mechanisms for successful outcomes

    Science.gov (United States)

    2014-01-01

    Objective To identify mechanisms for the successful implementation of support strategies for health-care practitioners in rural and remote contexts. Design This is an integrative review and thematic synthesis of the empirical literature that examines support interventions for health-care practitioners in rural and remote contexts. Results This review includes 43 papers that evaluated support strategies for the rural and remote health workforce. Interventions were predominantly training and education programmes with limited evaluations of supervision and mentoring interventions. The mechanisms associated with successful outcomes included: access to appropriate and adequate training, skills and knowledge for the support intervention; accessible and adequate resources; active involvement of stakeholders in programme design, implementation and evaluation; a needs analysis prior to the intervention; external support, organisation, facilitation and/or coordination of the programme; marketing of the programme; organisational commitment; appropriate mode of delivery; leadership; and regular feedback and evaluation of the programme. Conclusion Through a synthesis of the literature, this research has identified a number of mechanisms that are associated with successful support interventions for health-care practitioners in rural and remote contexts. This research utilised a methodology developed for studying complex interventions in response to the perceived limitations of traditional systematic reviews. This synthesis of the evidence will provide decision-makers at all levels with a collection of mechanisms that can assist the development and implementation of support strategies for staff in rural and remote contexts. PMID:24521004

  10. Integrated network analysis identifies fight-club nodes as a class of hubs encompassing key putative switch genes that induce major transcriptome reprogramming during grapevine development.

    Science.gov (United States)

    Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

    2014-12-01

    We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named "fight-club hubs" characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named "switch genes" was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. © 2014 American Society of Plant Biologists. All rights reserved.

  11. Multiscale Simulations for Coupled Flow and Transport Using the Generalized Multiscale Finite Element Method

    KAUST Repository

    Chung, Eric

    2015-12-11

    In this paper, we develop a mass conservative multiscale method for coupled flow and transport in heterogeneous porous media. We consider a coupled system consisting of a convection-dominated transport equation and a flow equation. We construct a coarse grid solver based on the Generalized Multiscale Finite Element Method (GMsFEM) for a coupled system. In particular, multiscale basis functions are constructed based on some snapshot spaces for the pressure and the concentration equations and some local spectral decompositions in the snapshot spaces. The resulting approach uses a few multiscale basis functions in each coarse block (for both the pressure and the concentration) to solve the coupled system. We use the mixed framework, which allows mass conservation. Our main contributions are: (1) the development of a mass conservative GMsFEM for the coupled flow and transport; (2) the development of a robust multiscale method for convection-dominated transport problems by choosing appropriate test and trial spaces within Petrov-Galerkin mixed formulation. We present numerical results and consider several heterogeneous permeability fields. Our numerical results show that with only a few basis functions per coarse block, we can achieve a good approximation.

  12. Multiscale Simulations for Coupled Flow and Transport Using the Generalized Multiscale Finite Element Method

    KAUST Repository

    Chung, Eric; Efendiev, Yalchin R.; Leung, Wing; Ren, Jun

    2015-01-01

    In this paper, we develop a mass conservative multiscale method for coupled flow and transport in heterogeneous porous media. We consider a coupled system consisting of a convection-dominated transport equation and a flow equation. We construct a coarse grid solver based on the Generalized Multiscale Finite Element Method (GMsFEM) for a coupled system. In particular, multiscale basis functions are constructed based on some snapshot spaces for the pressure and the concentration equations and some local spectral decompositions in the snapshot spaces. The resulting approach uses a few multiscale basis functions in each coarse block (for both the pressure and the concentration) to solve the coupled system. We use the mixed framework, which allows mass conservation. Our main contributions are: (1) the development of a mass conservative GMsFEM for the coupled flow and transport; (2) the development of a robust multiscale method for convection-dominated transport problems by choosing appropriate test and trial spaces within Petrov-Galerkin mixed formulation. We present numerical results and consider several heterogeneous permeability fields. Our numerical results show that with only a few basis functions per coarse block, we can achieve a good approximation.

  13. 'Integration'

    DEFF Research Database (Denmark)

    Olwig, Karen Fog

    2011-01-01

    , while the countries have adopted disparate policies and ideologies, differences in the actual treatment and attitudes towards immigrants and refugees in everyday life are less clear, due to parallel integration programmes based on strong similarities in the welfare systems and in cultural notions...... of equality in the three societies. Finally, it shows that family relations play a central role in immigrants’ and refugees’ establishment of a new life in the receiving societies, even though the welfare society takes on many of the social and economic functions of the family....

  14. International Conference on Multiscale Methods and Partial Differential Equations.

    Energy Technology Data Exchange (ETDEWEB)

    Thomas Hou

    2006-12-12

    The International Conference on Multiscale Methods and Partial Differential Equations (ICMMPDE for short) was held at IPAM, UCLA on August 26-27, 2005. The conference brought together researchers, students and practitioners with interest in the theoretical, computational and practical aspects of multiscale problems and related partial differential equations. The conference provided a forum to exchange and stimulate new ideas from different disciplines, and to formulate new challenging multiscale problems that will have impact in applications.

  15. Residual-driven online generalized multiscale finite element methods

    KAUST Repository

    Chung, Eric T.; Efendiev, Yalchin R.; Leung, Wing Tat

    2015-01-01

    In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.

  16. Generalized Multiscale Finite Element Methods for Wave Propagation in Heterogeneous Media

    KAUST Repository

    Chung, Eric T.

    2014-11-13

    Numerical modeling of wave propagation in heterogeneous media is important in many applications. Due to their complex nature, direct numerical simulations on the fine grid are prohibitively expensive. It is therefore important to develop efficient and accurate methods that allow the use of coarse grids. In this paper, we present a multiscale finite element method for wave propagation on a coarse grid. The proposed method is based on the generalized multiscale finite element method (GMsFEM) (see [Y. Efendiev, J. Galvis, and T. Hou, J. Comput. Phys., 251 (2012), pp. 116--135]). To construct multiscale basis functions, we start with two snapshot spaces in each coarse-grid block, where one represents the degrees of freedom on the boundary and the other represents the degrees of freedom in the interior. We use local spectral problems to identify important modes in each snapshot space. These local spectral problems are different from each other and their formulations are based on the analysis. To the best of knowledge, this is the first time that multiple snapshot spaces and multiple spectral problems are used and necessary for efficient computations. Using the dominant modes from local spectral problems, multiscale basis functions are constructed to represent the solution space locally within each coarse block. These multiscale basis functions are coupled via the symmetric interior penalty discontinuous Galerkin method which provides a block diagonal mass matrix and, consequently, results in fast computations in an explicit time discretization. Our methods\\' stability and spectral convergence are rigorously analyzed. Numerical examples are presented to show our methods\\' performance. We also test oversampling strategies. In particular, we discuss how the modes from different snapshot spaces can affect the proposed methods\\' accuracy.

  17. Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

    Science.gov (United States)

    Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

    2015-10-01

    Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.

  18. Integration of sequence data from a Consanguineous family with genetic data from an outbred population identifies PLB1 as a candidate rheumatoid arthritis risk gene.

    Directory of Open Access Journals (Sweden)

    Yukinori Okada

    Full Text Available Integrating genetic data from families with highly penetrant forms of disease together with genetic data from outbred populations represents a promising strategy to uncover the complete frequency spectrum of risk alleles for complex traits such as rheumatoid arthritis (RA. Here, we demonstrate that rare, low-frequency and common alleles at one gene locus, phospholipase B1 (PLB1, might contribute to risk of RA in a 4-generation consanguineous pedigree (Middle Eastern ancestry and also in unrelated individuals from the general population (European ancestry. Through identity-by-descent (IBD mapping and whole-exome sequencing, we identified a non-synonymous c.2263G>C (p.G755R mutation at the PLB1 gene on 2q23, which significantly co-segregated with RA in family members with a dominant mode of inheritance (P = 0.009. We further evaluated PLB1 variants and risk of RA using a GWAS meta-analysis of 8,875 RA cases and 29,367 controls of European ancestry. We identified significant contributions of two independent non-coding variants near PLB1 with risk of RA (rs116018341 [MAF = 0.042] and rs116541814 [MAF = 0.021], combined P = 3.2 × 10(-6. Finally, we performed deep exon sequencing of PLB1 in 1,088 RA cases and 1,088 controls (European ancestry, and identified suggestive dispersion of rare protein-coding variant frequencies between cases and controls (P = 0.049 for C-alpha test and P = 0.055 for SKAT. Together, these data suggest that PLB1 is a candidate risk gene for RA. Future studies to characterize the full spectrum of genetic risk in the PLB1 genetic locus are warranted.

  19. Diagnostic accuracy of an integrated respiratory guideline in identifying patients with respiratory symptoms requiring screening for pulmonary tuberculosis: a cross-sectional study

    Directory of Open Access Journals (Sweden)

    Majara Bosielo P

    2006-08-01

    Full Text Available Abstract Background To evaluate the diagnostic accuracy of the integrated Practical Approach to Lung Health in South Africa (PALSA guideline in identifying patients requiring bacteriological screening for tuberculosis (TB, and to determine which clinical features best predict suspected and bacteriologically-confirmed tuberculosis among patients with respiratory symptoms. Methods A prospective, cross-sectional study in which 1392 adult patients with cough and/or difficult breathing, attending a primary care facility in Cape Town, South Africa, were evaluated by a nurse using the guideline. The accuracy of a nurse using the guideline to identify TB suspects was compared to that of primary care physicians' diagnoses of (1 suspected TB, and (2 proven TB supported by clinical information and chest radiographs. Results The nurse using the guideline identified 516 patients as TB suspects compared with 365 by the primary care physicians, representing a sensitivity of 76% (95% confidence interval (CI 71%–79%, specificity of 77% (95% CI 74%–79%, positive predictive value of 53% (95% CI 49%–58%, negative predictive value of 90% (95% CI 88%–92%, and area under the receiver operating characteristic curve (ARUC of 0.76 (95% CI 0.74–0.79. Sputum results were obtained in 320 of the 365 primary care physicians TB suspects (88%; 40 (13% of these were positive for TB. Only 4 cases were not identified by the nurse using the guideline. The primary care physicians diagnostic accuracy in diagnosing bacteriologically-confirmed TB (n = 320 was as follows: sensitivity 90% (95% CI 76%–97%, specificity 65% (95% CI 63%–68%, negative predictive value 7% (95% CI 5%–10%, positive predictive value 99.5% (95% CI 98.8%–99.8%, and ARUC 0.78 (95% CI 0.73–0.82. Weight loss, pleuritic pain, and night sweats were independently associated with the diagnosis of bacteriologically-confirmed tuberculosis (positive likelihood ratio if all three present = 16.7, 95% CI 5

  20. Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems

    International Nuclear Information System (INIS)

    Kovalenko, Andriy

    2014-01-01

    enables rational design of CNC-based bionanocomposite materials and systems. Furthermore, the 3D-RISM-KH based multiscale modeling addresses the effect of hemicellulose and lignin composition on nanoscale forces that control cell wall strength towards overcoming plant biomass recalcitrance. It reveals molecular forces maintaining the cell wall structure and provides directions for genetic modulation of plants and pretreatment design to render biomass more amenable to processing. We envision integrated biomass valorization based on extracting and decomposing the non-cellulosic components to low molecular weight chemicals and utilizing the cellulose microfibrils to make CNC. This is an important alternative to approaches of full conversion of lignocellulose to biofuels that face challenges arising from the deleterious impact of cellulose crystallinity on enzymatic processing

  1. Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems

    Science.gov (United States)

    Kovalenko, Andriy

    2014-08-01

    enables rational design of CNC-based bionanocomposite materials and systems. Furthermore, the 3D-RISM-KH based multiscale modeling addresses the effect of hemicellulose and lignin composition on nanoscale forces that control cell wall strength towards overcoming plant biomass recalcitrance. It reveals molecular forces maintaining the cell wall structure and provides directions for genetic modulation of plants and pretreatment design to render biomass more amenable to processing. We envision integrated biomass valorization based on extracting and decomposing the non-cellulosic components to low molecular weight chemicals and utilizing the cellulose microfibrils to make CNC. This is an important alternative to approaches of full conversion of lignocellulose to biofuels that face challenges arising from the deleterious impact of cellulose crystallinity on enzymatic processing.

  2. 3D multiscale crack propagation using the XFEM applied to a gas turbine blade

    Science.gov (United States)

    Holl, Matthias; Rogge, Timo; Loehnert, Stefan; Wriggers, Peter; Rolfes, Raimund

    2014-01-01

    This work presents a new multiscale technique to investigate advancing cracks in three dimensional space. This fully adaptive multiscale technique is designed to take into account cracks of different length scales efficiently, by enabling fine scale domains locally in regions of interest, i.e. where stress concentrations and high stress gradients occur. Due to crack propagation, these regions change during the simulation process. Cracks are modeled using the extended finite element method, such that an accurate and powerful numerical tool is achieved. Restricting ourselves to linear elastic fracture mechanics, the -integral yields an accurate solution of the stress intensity factors, and with the criterion of maximum hoop stress, a precise direction of growth. If necessary, the on the finest scale computed crack surface is finally transferred to the corresponding scale. In a final step, the model is applied to a quadrature point of a gas turbine blade, to compute crack growth on the microscale of a real structure.

  3. An infrared small target detection method based on multiscale local homogeneity measure

    Science.gov (United States)

    Nie, Jinyan; Qu, Shaocheng; Wei, Yantao; Zhang, Liming; Deng, Lizhen

    2018-05-01

    Infrared (IR) small target detection plays an important role in the field of image detection area owing to its intrinsic characteristics. This paper presents a multiscale local homogeneity measure (MLHM) for infrared small target detection, which can enhance the performance of IR small target detection system. Firstly, intra-patch homogeneity of the target itself and the inter-patch heterogeneity between target and the local background regions are integrated to enhance the significant of small target. Secondly, a multiscale measure based on local regions is proposed to obtain the most appropriate response. Finally, an adaptive threshold method is applied to small target segmentation. Experimental results on three different scenarios indicate that the MLHM has good performance under the interference of strong noise.

  4. How next-generation sequencing and multiscale data analysis will transform infectious disease management.

    Science.gov (United States)

    Pak, Theodore R; Kasarskis, Andrew

    2015-12-01

    Recent reviews have examined the extent to which routine next-generation sequencing (NGS) on clinical specimens will improve the capabilities of clinical microbiology laboratories in the short term, but do not explore integrating NGS with clinical data from electronic medical records (EMRs), immune profiling data, and other rich datasets to create multiscale predictive models. This review introduces a range of "omics" and patient data sources relevant to managing infections and proposes 3 potentially disruptive applications for these data in the clinical workflow. The combined threats of healthcare-associated infections and multidrug-resistant organisms may be addressed by multiscale analysis of NGS and EMR data that is ideally updated and refined over time within each healthcare organization. Such data and analysis should form the cornerstone of future learning health systems for infectious disease. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.

  5. Multiscale Modeling of Point and Line Defects in Cubic Lattices

    National Research Council Canada - National Science Library

    Chung, P. W; Clayton, J. D

    2007-01-01

    .... This multiscale theory explicitly captures heterogeneity in microscopic atomic motion in crystalline materials, attributed, for example, to the presence of various point and line lattice defects...

  6. Towards practical multiscale approach for analysis of reinforced concrete structures

    Science.gov (United States)

    Moyeda, Arturo; Fish, Jacob

    2017-12-01

    We present a novel multiscale approach for analysis of reinforced concrete structural elements that overcomes two major hurdles in utilization of multiscale technologies in practice: (1) coupling between material and structural scales due to consideration of large representative volume elements (RVE), and (2) computational complexity of solving complex nonlinear multiscale problems. The former is accomplished using a variant of computational continua framework that accounts for sizeable reinforced concrete RVEs by adjusting the location of quadrature points. The latter is accomplished by means of reduced order homogenization customized for structural elements. The proposed multiscale approach has been verified against direct numerical simulations and validated against experimental results.

  7. Multiscale Cues Drive Collective Cell Migration

    Science.gov (United States)

    Nam, Ki-Hwan; Kim, Peter; Wood, David K.; Kwon, Sunghoon; Provenzano, Paolo P.; Kim, Deok-Ho

    2016-07-01

    To investigate complex biophysical relationships driving directed cell migration, we developed a biomimetic platform that allows perturbation of microscale geometric constraints with concomitant nanoscale contact guidance architectures. This permits us to elucidate the influence, and parse out the relative contribution, of multiscale features, and define how these physical inputs are jointly processed with oncogenic signaling. We demonstrate that collective cell migration is profoundly enhanced by the addition of contract guidance cues when not otherwise constrained. However, while nanoscale cues promoted migration in all cases, microscale directed migration cues are dominant as the geometric constraint narrows, a behavior that is well explained by stochastic diffusion anisotropy modeling. Further, oncogene activation (i.e. mutant PIK3CA) resulted in profoundly increased migration where extracellular multiscale directed migration cues and intrinsic signaling synergistically conspire to greatly outperform normal cells or any extracellular guidance cues in isolation.

  8. Plant trait detection with multi-scale spectrometry

    Science.gov (United States)

    Gamon, J. A.; Wang, R.

    2017-12-01

    Proximal and remote sensing using imaging spectrometry offers new opportunities for detecting plant traits, with benefits for phenotyping, productivity estimation, stress detection, and biodiversity studies. Using proximal and airborne spectrometry, we evaluated variation in plant optical properties at various spatial and spectral scales with the goal of identifying optimal scales for distinguishing plant traits related to photosynthetic function. Using directed approaches based on physiological vegetation indices, and statistical approaches based on spectral information content, we explored alternate ways of distinguishing plant traits with imaging spectrometry. With both leaf traits and canopy structure contributing to the signals, results exhibit a strong scale dependence. Our results demonstrate the benefits of multi-scale experimental approaches within a clear conceptual framework when applying remote sensing methods to plant trait detection for phenotyping, productivity, and biodiversity studies.

  9. Multiscale Study of Currents Affected by Topography

    Science.gov (United States)

    2015-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Multiscale Study of Currents Affected by Topography ...the effects of topography on the ocean general and regional circulation with a focus on the wide range of scales of interactions. The small-scale...details of the topography and the waves, eddies, drag, and turbulence it generates (at spatial scales ranging from meters to mesoscale) interact in the

  10. A multiscale approach to Brownian motors

    International Nuclear Information System (INIS)

    Pavliotis, G.A.

    2005-01-01

    The problem of Brownian motion in a periodic potential, under the influence of external forcing, which is either random or periodic in time, is studied in this Letter. Multiscale techniques are used to derive general formulae for the steady state particle current and the effective diffusion tensor. These formulae are then applied to calculate the effective diffusion coefficient for a Brownian particle in a periodic potential driven simultaneously by additive Gaussian white and colored noise. Our theoretical findings are supported by numerical simulations

  11. Multi-scale Regions from Edge Fragments

    DEFF Research Database (Denmark)

    Kazmi, Wajahat; Andersen, Hans Jørgen

    2014-01-01

    In this article we introduce a novel method for detecting multi-scale salient regions around edges using a graph based image compression algorithm. Images are recursively decomposed into triangles arranged into a binary tree using linear interpolation. The entropy of any local region of the image......), their performance is comparable to SIFT (Lowe, 2004).We also show that when they are used together with MSERs (Matas et al., 2002), the performance of MSERs is boosted....

  12. Integrated proteomics identified novel activation of dynein IC2-GR-COX-1 signaling in neurofibromatosis type I (NF1) disease model cells.

    Science.gov (United States)

    Hirayama, Mio; Kobayashi, Daiki; Mizuguchi, Souhei; Morikawa, Takashi; Nagayama, Megumi; Midorikawa, Uichi; Wilson, Masayo M; Nambu, Akiko N; Yoshizawa, Akiyasu C; Kawano, Shin; Araki, Norie

    2013-05-01

    Neurofibromatosis type 1 (NF1) tumor suppressor gene product, neurofibromin, functions in part as a Ras-GAP, and though its loss is implicated in the neuronal abnormality of NF1 patients, its precise cellular function remains unclear. To study the molecular mechanism of NF1 pathogenesis, we prepared NF1 gene knockdown (KD) PC12 cells, as a NF1 disease model, and analyzed their molecular (gene and protein) expression profiles with a unique integrated proteomics approach, comprising iTRAQ, 2D-DIGE, and DNA microarrays, using an integrated protein and gene expression analysis chart (iPEACH). In NF1-KD PC12 cells showing abnormal neuronal differentiation after NGF treatment, of 3198 molecules quantitatively identified and listed in iPEACH, 97 molecules continuously up- or down-regulated over time were extracted. Pathway and network analysis further revealed overrepresentation of calcium signaling and transcriptional regulation by glucocorticoid receptor (GR) in the up-regulated protein set, whereas nerve system development was overrepresented in the down-regulated protein set. The novel up-regulated network we discovered, "dynein IC2-GR-COX-1 signaling," was then examined in NF1-KD cells. Validation studies confirmed that NF1 knockdown induces altered splicing and phosphorylation patterns of dynein IC2 isomers, up-regulation and accumulation of nuclear GR, and increased COX-1 expression in NGF-treated cells. Moreover, the neurite retraction phenotype observed in NF1-KD cells was significantly recovered by knockdown of the dynein IC2-C isoform and COX-1. In addition, dynein IC2 siRNA significantly inhibited nuclear translocation and accumulation of GR and up-regulation of COX-1 expression. These results suggest that dynein IC2 up-regulates GR nuclear translocation and accumulation, and subsequently causes increased COX-1 expression, in this NF1 disease model. Our integrated proteomics strategy, which combines multiple approaches, demonstrates that NF1-related neural

  13. Engineering Digestion: Multiscale Processes of Food Digestion.

    Science.gov (United States)

    Bornhorst, Gail M; Gouseti, Ourania; Wickham, Martin S J; Bakalis, Serafim

    2016-03-01

    Food digestion is a complex, multiscale process that has recently become of interest to the food industry due to the developing links between food and health or disease. Food digestion can be studied by using either in vitro or in vivo models, each having certain advantages or disadvantages. The recent interest in food digestion has resulted in a large number of studies in this area, yet few have provided an in-depth, quantitative description of digestion processes. To provide a framework to develop these quantitative comparisons, a summary is given here between digestion processes and parallel unit operations in the food and chemical industry. Characterization parameters and phenomena are suggested for each step of digestion. In addition to the quantitative characterization of digestion processes, the multiscale aspect of digestion must also be considered. In both food systems and the gastrointestinal tract, multiple length scales are involved in food breakdown, mixing, absorption. These different length scales influence digestion processes independently as well as through interrelated mechanisms. To facilitate optimized development of functional food products, a multiscale, engineering approach may be taken to describe food digestion processes. A framework for this approach is described in this review, as well as examples that demonstrate the importance of process characterization as well as the multiple, interrelated length scales in the digestion process. © 2016 Institute of Food Technologists®

  14. Acoustics of multiscale sorptive porous materials

    Science.gov (United States)

    Venegas, R.; Boutin, C.; Umnova, O.

    2017-08-01

    This paper investigates sound propagation in multiscale rigid-frame porous materials that support mass transfer processes, such as sorption and different types of diffusion, in addition to the usual visco-thermo-inertial interactions. The two-scale asymptotic method of homogenization for periodic media is successively used to derive the macroscopic equations describing sound propagation through the material. This allowed us to conclude that the macroscopic mass balance is significantly modified by sorption, inter-scale (micro- to/from nanopore scales) mass diffusion, and inter-scale (pore to/from micro- and nanopore scales) pressure diffusion. This modification is accounted for by the dynamic compressibility of the effective saturating fluid that presents atypical properties that lead to slower speed of sound and higher sound attenuation, particularly at low frequencies. In contrast, it is shown that the physical processes occurring at the micro-nano-scale do not affect the macroscopic fluid flow through the material. The developed theory is exemplified by introducing an analytical model for multiscale sorptive granular materials, which is experimentally validated by comparing its predictions with acoustic measurements on granular activated carbons. Furthermore, we provide empirical evidence supporting an alternative method for measuring sorption and mass diffusion properties of multiscale sorptive materials using sound waves.

  15. Multivariate multiscale entropy of financial markets

    Science.gov (United States)

    Lu, Yunfan; Wang, Jun

    2017-11-01

    In current process of quantifying the dynamical properties of the complex phenomena in financial market system, the multivariate financial time series are widely concerned. In this work, considering the shortcomings and limitations of univariate multiscale entropy in analyzing the multivariate time series, the multivariate multiscale sample entropy (MMSE), which can evaluate the complexity in multiple data channels over different timescales, is applied to quantify the complexity of financial markets. Its effectiveness and advantages have been detected with numerical simulations with two well-known synthetic noise signals. For the first time, the complexity of four generated trivariate return series for each stock trading hour in China stock markets is quantified thanks to the interdisciplinary application of this method. We find that the complexity of trivariate return series in each hour show a significant decreasing trend with the stock trading time progressing. Further, the shuffled multivariate return series and the absolute multivariate return series are also analyzed. As another new attempt, quantifying the complexity of global stock markets (Asia, Europe and America) is carried out by analyzing the multivariate returns from them. Finally we utilize the multivariate multiscale entropy to assess the relative complexity of normalized multivariate return volatility series with different degrees.

  16. Integration analysis of microRNA and mRNA paired expression profiling identifies deregulated microRNA-transcription factor-gene regulatory networks in ovarian endometriosis.

    Science.gov (United States)

    Zhao, Luyang; Gu, Chenglei; Ye, Mingxia; Zhang, Zhe; Li, Li'an; Fan, Wensheng; Meng, Yuanguang

    2018-01-22

    The etiology and pathophysiology of endometriosis remain unclear. Accumulating evidence suggests that aberrant microRNA (miRNA) and transcription factor (TF) expression may be involved in the pathogenesis and development of endometriosis. This study therefore aims to survey the key miRNAs, TFs and genes and further understand the mechanism of endometriosis. Paired expression profiling of miRNA and mRNA in ectopic endometria compared with eutopic endometria were determined by high-throughput sequencing techniques in eight patients with ovarian endometriosis. Binary interactions and circuits among the miRNAs, TFs, and corresponding genes were identified by the Pearson correlation coefficients. miRNA-TF-gene regulatory networks were constructed using bioinformatic methods. Eleven selected miRNAs and TFs were validated by quantitative reverse transcription-polymerase chain reaction in 22 patients. Overall, 107 differentially expressed miRNAs and 6112 differentially expressed mRNAs were identified by comparing the sequencing of the ectopic endometrium group and the eutopic endometrium group. The miRNA-TF-gene regulatory network consists of 22 miRNAs, 12 TFs and 430 corresponding genes. Specifically, some key regulators from the miR-449 and miR-34b/c cluster, miR-200 family, miR-106a-363 cluster, miR-182/183, FOX family, GATA family, and E2F family as well as CEBPA, SOX9 and HNF4A were suggested to play vital regulatory roles in the pathogenesis of endometriosis. Integration analysis of the miRNA and mRNA expression profiles presents a unique insight into the regulatory network of this enigmatic disorder and possibly provides clues regarding replacement therapy for endometriosis.

  17. Multiscale Persistent Functions for Biomolecular Structure Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Kelin [Nanyang Technological University (Singapore). Division of Mathematical Sciences, School of Physical, Mathematical Sciences and School of Biological Sciences; Li, Zhiming [Central China Normal University, Wuhan (China). Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics; Mu, Lin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division

    2017-11-02

    Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolution parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first

  18. Integrating themes, evidence gaps, and research needs identified by workshop on iron screening and supplementation in iron-replete pregnant women and young children.

    Science.gov (United States)

    Brannon, Patsy M; Stover, Patrick J; Taylor, Christine L

    2017-12-01

    This report addresses the evidence and the uncertainties, knowledge gaps, and research needs identified by participants at the NIH workshop related to iron screening and routine iron supplementation of largely iron-replete pregnant women and young children (6-24 mo) in developed countries. The workshop presentations and panel discussions focused on current understanding and knowledge gaps related to iron homeostasis, measurement of and evidence for iron status, and emerging concerns about supplementing iron-replete members of these vulnerable populations. Four integrating themes emerged across workshop presentations and discussion and centered on 1 ) physiologic or developmental adaptations of iron homeostasis to pregnancy and early infancy, respectively, and their implications, 2 ) improvement of the assessment of iron status across the full continuum from iron deficiency anemia to iron deficiency to iron replete to iron excess, 3 ) the linkage of iron status with health outcomes beyond hematologic outcomes, and 4 ) the balance of benefit and harm of iron supplementation of iron-replete pregnant women and young children. Research that addresses these themes in the context of the full continuum of iron status is needed to inform approaches to the balancing of benefits and harms of screening and routine supplementation. © 2017 American Society for Nutrition.

  19. Learning to identify Protected Health Information by integrating knowledge- and data-driven algorithms: A case study on psychiatric evaluation notes.

    Science.gov (United States)

    Dehghan, Azad; Kovacevic, Aleksandar; Karystianis, George; Keane, John A; Nenadic, Goran

    2017-11-01

    De-identification of clinical narratives is one of the main obstacles to making healthcare free text available for research. In this paper we describe our experience in expanding and tailoring two existing tools as part of the 2016 CEGS N-GRID Shared Tasks Track 1, which evaluated de-identification methods on a set of psychiatric evaluation notes for up to 25 different types of Protected Health Information (PHI). The methods we used rely on machine learning on either a large or small feature space, with additional strategies, including two-pass tagging and multi-class models, which both proved to be beneficial. The results show that the integration of the proposed methods can identify Health Information Portability and Accountability Act (HIPAA) defined PHIs with overall F 1 -scores of ∼90% and above. Yet, some classes (Profession, Organization) proved again to be challenging given the variability of expressions used to reference given information. Copyright © 2017. Published by Elsevier Inc.

  20. Integrating microRNA and mRNA expression profiles of neuronal progenitors to identify regulatory networks underlying the onset of cortical neurogenesis

    Directory of Open Access Journals (Sweden)

    Barker Jeffery L

    2009-08-01

    Full Text Available Abstract Background Cortical development is a complex process that includes sequential generation of neuronal progenitors, which proliferate and migrate to form the stratified layers of the developing cortex. To identify the individual microRNAs (miRNAs and mRNAs that may regulate the genetic network guiding the earliest phase of cortical development, the expression profiles of rat neuronal progenitors obtained at embryonic day 11 (E11, E12 and E13 were analyzed. Results Neuronal progenitors were purified from telencephalic dissociates by a positive-selection strategy featuring surface labeling with tetanus-toxin and cholera-toxin followed by fluorescence-activated cell sorting. Microarray analyses revealed the fractions of miRNAs and mRNAs that were up-regulated or down-regulated in these neuronal progenitors at the beginning of cortical development. Nearly half of the dynamically expressed miRNAs were negatively correlated with the expression of their predicted target mRNAs. Conclusion These data support a regulatory role for miRNAs during the transition from neuronal progenitors into the earliest differentiating cortical neurons. In addition, by supplying a robust data set in which miRNA and mRNA profiles originate from the same purified cell type, this empirical study may facilitate the development of new algorithms to integrate various "-omics" data sets.

  1. Integrated molecular analysis of Tamoxifen-resistant invasive lobular breast cancer cells identifies MAPK and GRM/mGluR signaling as therapeutic vulnerabilities.

    Science.gov (United States)

    Stires, Hillary; Heckler, Mary M; Fu, Xiaoyong; Li, Zhao; Grasso, Catherine S; Quist, Michael J; Lewis, Joseph A; Klimach, Uwe; Zwart, Alan; Mahajan, Akanksha; Győrffy, Balázs; Cavalli, Luciane R; Riggins, Rebecca B

    2018-08-15

    Invasive lobular breast cancer (ILC) is an understudied malignancy with distinct clinical, pathological, and molecular features that distinguish it from the more common invasive ductal carcinoma (IDC). Mounting evidence suggests that estrogen receptor-alpha positive (ER+) ILC has a poor response to Tamoxifen (TAM), but the mechanistic drivers of this are undefined. In the current work, we comprehensively characterize the SUM44/LCCTam ILC cell model system through integrated analysis of gene expression, copy number, and mutation, with the goal of identifying actionable alterations relevant to clinical ILC that can be co-targeted along with ER to improve treatment outcomes. We show that TAM has several distinct effects on the transcriptome of LCCTam cells, that this resistant cell model has acquired copy number alterations and mutations that impinge on MAPK and metabotropic glutamate receptor (GRM/mGluR) signaling networks, and that pharmacological inhibition of either improves or restores the growth-inhibitory actions of endocrine therapy. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  2. An Integrative Analysis of the InR/PI3K/Akt Network Identifies the Dynamic Response to Insulin Signaling

    Directory of Open Access Journals (Sweden)

    Arunachalam Vinayagam

    2016-09-01

    Full Text Available Insulin regulates an essential conserved signaling pathway affecting growth, proliferation, and metabolism. To expand our understanding of the insulin pathway, we combine biochemical, genetic, and computational approaches to build a comprehensive Drosophila InR/PI3K/Akt network. First, we map the dynamic protein-protein interaction network surrounding the insulin core pathway using bait-prey interactions connecting 566 proteins. Combining RNAi screening and phospho-specific antibodies, we find that 47% of interacting proteins affect pathway activity, and, using quantitative phosphoproteomics, we demonstrate that ∼10% of interacting proteins are regulated by insulin stimulation at the level of phosphorylation. Next, we integrate these orthogonal datasets to characterize the structure and dynamics of the insulin network at the level of protein complexes and validate our method by identifying regulatory roles for the Protein Phosphatase 2A (PP2A and Reptin-Pontin chromatin-remodeling complexes as negative and positive regulators of ribosome biogenesis, respectively. Altogether, our study represents a comprehensive resource for the study of the evolutionary conserved insulin network.

  3. Na+/K+-ATPase α1 identified as an abundant protein in the blood-labyrinth barrier that plays an essential role in the barrier integrity.

    Directory of Open Access Journals (Sweden)

    Yue Yang

    2011-01-01

    Full Text Available The endothelial-blood/tissue barrier is critical for maintaining tissue homeostasis. The ear harbors a unique endothelial-blood/tissue barrier which we term "blood-labyrinth-barrier". This barrier is critical for maintaining inner ear homeostasis. Disruption of the blood-labyrinth-barrier is closely associated with a number of hearing disorders. Many proteins of the blood-brain-barrier and blood-retinal-barrier have been identified, leading to significant advances in understanding their tissue specific functions. In contrast, capillaries in the ear are small in volume and anatomically complex. This presents a challenge for protein analysis studies, which has resulted in limited knowledge of the molecular and functional components of the blood-labyrinth-barrier. In this study, we developed a novel method for isolation of the stria vascularis capillary from CBA/CaJ mouse cochlea and provided the first database of protein components in the blood-labyrinth barrier as well as evidence that the interaction of Na(+/K(+-ATPase α1 (ATP1A1 with protein kinase C eta (PKCη and occludin is one of the mechanisms of loud sound-induced vascular permeability increase.Using a mass-spectrometry, shotgun-proteomics approach combined with a novel "sandwich-dissociation" method, more than 600 proteins from isolated stria vascularis capillaries were identified from adult CBA/CaJ mouse cochlea. The ion transporter ATP1A1 was the most abundant protein in the blood-labyrinth barrier. Pharmacological inhibition of ATP1A1 activity resulted in hyperphosphorylation of tight junction proteins such as occludin which increased the blood-labyrinth-barrier permeability. PKCη directly interacted with ATP1A1 and was an essential mediator of ATP1A1-initiated occludin phosphorylation. Moreover, this identified signaling pathway was involved in the breakdown of the blood-labyrinth-barrier resulting from loud sound trauma.The results presented here provide a novel method for

  4. Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

    Science.gov (United States)

    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

  5. Multiscale methods in computational fluid and solid mechanics

    NARCIS (Netherlands)

    Borst, de R.; Hulshoff, S.J.; Lenz, S.; Munts, E.A.; Brummelen, van E.H.; Wall, W.; Wesseling, P.; Onate, E.; Periaux, J.

    2006-01-01

    First, an attempt is made towards gaining a more systematic understanding of recent progress in multiscale modelling in computational solid and fluid mechanics. Sub- sequently, the discussion is focused on variational multiscale methods for the compressible and incompressible Navier-Stokes

  6. Transitions of the Multi-Scale Singularity Trees

    DEFF Research Database (Denmark)

    Somchaipeng, Kerawit; Sporring, Jon; Kreiborg, Sven

    2005-01-01

    Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure...

  7. Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction

    KAUST Repository

    Ghasemi, Mohammadreza

    2015-02-23

    In this paper, we present a global-local model reduction for fast multiscale reservoir simulations in highly heterogeneous porous media with applications to optimization and history matching. Our proposed approach identifies a low dimensional structure of the solution space. We introduce an auxiliary variable (the velocity field) in our model reduction that allows achieving a high degree of model reduction. The latter is due to the fact that the velocity field is conservative for any low-order reduced model in our framework. Because a typical global model reduction based on POD is a Galerkin finite element method, and thus it can not guarantee local mass conservation. This can be observed in numerical simulations that use finite volume based approaches. Discrete Empirical Interpolation Method (DEIM) is used to approximate the nonlinear functions of fine-grid functions in Newton iterations. This approach allows achieving the computational cost that is independent of the fine grid dimension. POD snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3) inexpensive global POD operations in a small dimensional spaces on a coarse grid. By balancing the errors of the global and local reduced-order models, our new methodology can provide an error bound in simulations. Our numerical results, utilizing a two-phase immiscible flow, show a substantial speed-up and we compare our results to the standard POD-DEIM in finite volume setup.

  8. Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

    Science.gov (United States)

    Schwalbe, Michelle Kristin

    2010-01-01

    This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…

  9. Development of a Sampling-Based Global Sensitivity Analysis Workflow for Multiscale Computational Cancer Models

    Science.gov (United States)

    Wang, Zhihui; Deisboeck, Thomas S.; Cristini, Vittorio

    2014-01-01

    There are two challenges that researchers face when performing global sensitivity analysis (GSA) on multiscale in silico cancer models. The first is increased computational intensity, since a multiscale cancer model generally takes longer to run than does a scale-specific model. The second problem is the lack of a best GSA method that fits all types of models, which implies that multiple methods and their sequence need to be taken into account. In this article, we therefore propose a sampling-based GSA workflow consisting of three phases – pre-analysis, analysis, and post-analysis – by integrating Monte Carlo and resampling methods with the repeated use of analysis of variance (ANOVA); we then exemplify this workflow using a two-dimensional multiscale lung cancer model. By accounting for all parameter rankings produced by multiple GSA methods, a summarized ranking is created at the end of the workflow based on the weighted mean of the rankings for each input parameter. For the cancer model investigated here, this analysis reveals that ERK, a downstream molecule of the EGFR signaling pathway, has the most important impact on regulating both the tumor volume and expansion rate in the algorithm used. PMID:25257020

  10. Efficient algorithms for multiscale modeling in porous media

    KAUST Repository

    Wheeler, Mary F.; Wildey, Tim; Xue, Guangri

    2010-01-01

    We describe multiscale mortar mixed finite element discretizations for second-order elliptic and nonlinear parabolic equations modeling Darcy flow in porous media. The continuity of flux is imposed via a mortar finite element space on a coarse grid scale, while the equations in the coarse elements (or subdomains) are discretized on a fine grid scale. We discuss the construction of multiscale mortar basis and extend this concept to nonlinear interface operators. We present a multiscale preconditioning strategy to minimize the computational cost associated with construction of the multiscale mortar basis. We also discuss the use of appropriate quadrature rules and approximation spaces to reduce the saddle point system to a cell-centered pressure scheme. In particular, we focus on multiscale mortar multipoint flux approximation method for general hexahedral grids and full tensor permeabilities. Numerical results are presented to verify the accuracy and efficiency of these approaches. © 2010 John Wiley & Sons, Ltd.

  11. Efficient algorithms for multiscale modeling in porous media

    KAUST Repository

    Wheeler, Mary F.

    2010-09-26

    We describe multiscale mortar mixed finite element discretizations for second-order elliptic and nonlinear parabolic equations modeling Darcy flow in porous media. The continuity of flux is imposed via a mortar finite element space on a coarse grid scale, while the equations in the coarse elements (or subdomains) are discretized on a fine grid scale. We discuss the construction of multiscale mortar basis and extend this concept to nonlinear interface operators. We present a multiscale preconditioning strategy to minimize the computational cost associated with construction of the multiscale mortar basis. We also discuss the use of appropriate quadrature rules and approximation spaces to reduce the saddle point system to a cell-centered pressure scheme. In particular, we focus on multiscale mortar multipoint flux approximation method for general hexahedral grids and full tensor permeabilities. Numerical results are presented to verify the accuracy and efficiency of these approaches. © 2010 John Wiley & Sons, Ltd.

  12. Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane

    International Nuclear Information System (INIS)

    Zunino, Luciano; Ribeiro, Haroldo V.

    2016-01-01

    The aim of this paper is to further explore the usefulness of the two-dimensional complexity-entropy causality plane as a texture image descriptor. A multiscale generalization is introduced in order to distinguish between different roughness features of images at small and large spatial scales. Numerically generated two-dimensional structures are initially considered for illustrating basic concepts in a controlled framework. Then, more realistic situations are studied. Obtained results allow us to confirm that intrinsic spatial correlations of images are successfully unveiled by implementing this multiscale symbolic information-theory approach. Consequently, we conclude that the proposed representation space is a versatile and practical tool for identifying, characterizing and discriminating image textures.

  13. Multiscale mechanistic modeling in pharmaceutical research and development.

    Science.gov (United States)

    Kuepfer, Lars; Lippert, Jörg; Eissing, Thomas

    2012-01-01

    Discontinuation of drug development projects due to lack of efficacy or adverse events is one of the main cost drivers in pharmaceutical research and development (R&D). Investments have to be written-off and contribute to the total costs of a successful drug candidate receiving marketing authorization and allowing return on invest. A vital risk for pharmaceutical innovator companies is late stage clinical failure since costs for individual clinical trials may exceed the one billion Euro threshold. To guide investment decisions and to safeguard maximum medical benefit and safety for patients recruited in clinical trials, it is therefore essential to understand the clinical consequences of all information and data generated. The complexity of the physiological and pathophysiological processes and the sheer amount of information available overcharge the mental capacity of any human being and prevent a prediction of the success in clinical development. A rigorous integration of knowledge, assumption, and experimental data into computational models promises a significant improvement of the rationalization of decision making in pharmaceutical industry. We here give an overview of the current status of modeling and simulation in pharmaceutical R&D and outline the perspectives of more recent developments in mechanistic modeling. Specific modeling approaches for different biological scales ranging from intracellular processes to whole organism physiology are introduced and an example for integrative multiscale modeling of therapeutic efficiency in clinical oncology trials is showcased.

  14. The Multiscale Fluctuations of the Correlation between Oil Price and Wind Energy Stock

    Directory of Open Access Journals (Sweden)

    Shupei Huang

    2016-06-01

    Full Text Available Wind energy is considered a clear and sustainable substitution for fossil fuel, and the stock index of the wind energy industry is closely related to the oil price fluctuation. Their relationship is characterized by multiscale and time-varying features based on a variety of stakeholders who have different objectives within various time horizons, which makes it difficult to identify the factor in which time scale could be the most influential one in the market. Aiming to explore the correlation between oil price and the wind energy stock index from the time–frequency domain in a dynamic perspective, we propose an algorithm combining the wavelet transform, complex network, and gray correlation analyses and choose the Brent oil price and the international securities exchange (ISE global wind energy index from January 2006 to October 2015 in daily frequency as data sample. First, we define the multiscale conformation by a set of fluctuation information with different time horizons to represent the fluctuation status of the correlation of the oil–wind nexus rather than by a single original correlation value. Then, we transform the multiscale conformation evolution into a network model, and only 270 multiscale conformations and 710 transmissions could characterize 2451 data points. We find that only 30% of conformations and transmissions work as a backbone of the entire correlation series; through these major conformations, we identify that the main factor that could influence the oil–wind nexus are long-term components, such as policies, the status of the global economy and demand–supply issues. In addition, there is a clustering effect and transmissions among conformations that mainly happen inside clusters and rarely among clusters, which means the interaction of the oil–wind nexus is stable over a short period of time.

  15. Multiscale approaches to high efficiency photovoltaics

    Directory of Open Access Journals (Sweden)

    Connolly James Patrick

    2016-01-01

    Full Text Available While renewable energies are achieving parity around the globe, efforts to reach higher solar cell efficiencies becomes ever more difficult as they approach the limiting efficiency. The so-called third generation concepts attempt to break this limit through a combination of novel physical processes and new materials and concepts in organic and inorganic systems. Some examples of semi-empirical modelling in the field are reviewed, in particular for multispectral solar cells on silicon (French ANR project MultiSolSi. Their achievements are outlined, and the limits of these approaches shown. This introduces the main topic of this contribution, which is the use of multiscale experimental and theoretical techniques to go beyond the semi-empirical understanding of these systems. This approach has already led to great advances at modelling which have led to modelling software, which is widely known. Yet, a survey of the topic reveals a fragmentation of efforts across disciplines, firstly, such as organic and inorganic fields, but also between the high efficiency concepts such as hot carrier cells and intermediate band concepts. We show how this obstacle to the resolution of practical research obstacles may be lifted by inter-disciplinary cooperation across length scales, and across experimental and theoretical fields, and finally across materials systems. We present a European COST Action “MultiscaleSolar” kicking off in early 2015, which brings together experimental and theoretical partners in order to develop multiscale research in organic and inorganic materials. The goal of this defragmentation and interdisciplinary collaboration is to develop understanding across length scales, which will enable the full potential of third generation concepts to be evaluated in practise, for societal and industrial applications.

  16. A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

    Science.gov (United States)

    Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

    2008-12-01

    Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

  17. Structure and multiscale mechanics of carbon nanomaterials

    CERN Document Server

    2016-01-01

    This book aims at providing a broad overview on the relationship between structure and mechanical properties of carbon nanomaterials from world-leading scientists in the field. The main aim is to get an in-depth understanding of the broad range of mechanical properties of carbon materials based on their unique nanostructure and on defects of several types and at different length scales. Besides experimental work mainly based on the use of (in-situ) Raman and X-ray scattering and on nanoindentation, the book also covers some aspects of multiscale modeling of the mechanics of carbon nanomaterials.

  18. Multi-scale Modelling of Segmentation

    DEFF Research Database (Denmark)

    Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

    2016-01-01

    pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...

  19. Sustainable design and manufacturing of multifunctional polymer nanocomposite coatings: A multiscale systems approach

    Science.gov (United States)

    Xiao, Jie

    Polymer nanocomposites have a great potential to be a dominant coating material in a wide range of applications in the automotive, aerospace, ship-making, construction, and pharmaceutical industries. However, how to realize design sustainability of this type of nanostructured materials and how to ensure the true optimality of the product quality and process performance in coating manufacturing remain as a mountaintop area. The major challenges arise from the intrinsic multiscale nature of the material-process-product system and the need to manipulate the high levels of complexity and uncertainty in design and manufacturing processes. This research centers on the development of a comprehensive multiscale computational methodology and a computer-aided tool set that can facilitate multifunctional nanocoating design and application from novel function envisioning and idea refinement, to knowledge discovery and design solution derivation, and further to performance testing in industrial applications and life cycle analysis. The principal idea is to achieve exceptional system performance through concurrent characterization and optimization of materials, product and associated manufacturing processes covering a wide range of length and time scales. Multiscale modeling and simulation techniques ranging from microscopic molecular modeling to classical continuum modeling are seamlessly coupled. The tight integration of different methods and theories at individual scales allows the prediction of macroscopic coating performance from the fundamental molecular behavior. Goal-oriented design is also pursued by integrating additional methods for bio-inspired dynamic optimization and computational task management that can be implemented in a hierarchical computing architecture. Furthermore, multiscale systems methodologies are developed to achieve the best possible material application towards sustainable manufacturing. Automotive coating manufacturing, that involves paint spay and

  20. A Multi-scale, Multi-disciplinary Approach for Assessing the Technological, Economic, and Environmental Performance of Bio-based Chemicals

    DEFF Research Database (Denmark)

    Herrgard, Markus; Sukumara, Sumesh; Campodonico Alt, Miguel Angel

    2015-01-01

    , the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain...... towards a sustainable chemical industry....

  1. Integrated RNA-Seq and sRNA-Seq Analysis Identifies Chilling and Freezing Responsive Key Molecular Players and Pathways in Tea Plant (Camellia sinensis)

    Science.gov (United States)

    Zheng, Chao; Zhao, Lei; Wang, Yu; Shen, Jiazhi; Zhang, Yinfei; Jia, Sisi; Li, Yusheng; Ding, Zhaotang

    2015-01-01

    Tea [Camellia sinensis (L) O. Kuntze, Theaceae] is one of the most popular non-alcoholic beverages worldwide. Cold stress is one of the most severe abiotic stresses that limit tea plants’ growth, survival and geographical distribution. However, the genetic regulatory network and signaling pathways involved in cold stress responses in tea plants remain unearthed. Using RNA-Seq, DGE and sRNA-Seq technologies, we performed an integrative analysis of miRNA and mRNA expression profiling and their regulatory network of tea plants under chilling (4℃) and freezing (-5℃) stress. Differentially expressed (DE) miRNA and mRNA profiles were obtained based on fold change analysis, miRNAs and target mRNAs were found to show both coherent and incoherent relationships in the regulatory network. Furthermore, we compared several key pathways (e.g., ‘Photosynthesis’), GO terms (e.g., ‘response to karrikin’) and transcriptional factors (TFs, e.g., DREB1b/CBF1) which were identified as involved in the early chilling and/or freezing response of tea plants. Intriguingly, we found that karrikins, a new group of plant growth regulators, and β-primeverosidase (BPR), a key enzyme functionally relevant with the formation of tea aroma might play an important role in both early chilling and freezing response of tea plants. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-Seq and sRNA-Seq analysis. This is the first study to simultaneously profile the expression patterns of both miRNAs and mRNAs on a genome-wide scale to elucidate the molecular mechanisms of early responses of tea plants to cold stress. In addition to gaining a deeper insight into the cold resistant characteristics of tea plants, we provide a good case study to analyse mRNA/miRNA expression and profiling of non-model plant species using next-generation sequencing technology. PMID:25901577

  2. An integrated approach for identifying priority contaminant in the Great Lakes Basin -Investigations in the Lower Green Bay/Fox River and Milwaukee Estuary areas of concern

    Science.gov (United States)

    Environmental assessment of complex mixtures typically requires integration of chemical and biological measurements. This study demonstrates the use of a combination of instrumental chemical analyses, effects-based monitoring, and bio-effects prediction approaches to help identi...

  3. A multiscale model for virus capsid dynamics.

    Science.gov (United States)

    Chen, Changjun; Saxena, Rishu; Wei, Guo-Wei

    2010-01-01

    Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows.

  4. Neural network based multiscale image restoration approach

    Science.gov (United States)

    de Castro, Ana Paula A.; da Silva, José D. S.

    2007-02-01

    This paper describes a neural network based multiscale image restoration approach. Multilayer perceptrons are trained with artificial images of degraded gray level circles, in an attempt to make the neural network learn inherent space relations of the degraded pixels. The present approach simulates the degradation by a low pass Gaussian filter blurring operation and the addition of noise to the pixels at pre-established rates. The training process considers the degraded image as input and the non-degraded image as output for the supervised learning process. The neural network thus performs an inverse operation by recovering a quasi non-degraded image in terms of least squared. The main difference of the approach to existing ones relies on the fact that the space relations are taken from different scales, thus providing relational space data to the neural network. The approach is an attempt to come up with a simple method that leads to an optimum solution to the problem. Considering different window sizes around a pixel simulates the multiscale operation. In the generalization phase the neural network is exposed to indoor, outdoor, and satellite degraded images following the same steps use for the artificial circle image.

  5. Multiscale coherent structures in tokamak plasma turbulence

    International Nuclear Information System (INIS)

    Xu, G. S.; Wan, B. N.; Zhang, W.; Yang, Q. W.; Wang, L.; Wen, Y. Z.

    2006-01-01

    A 12-tip poloidal probe array is used on the HT-7 superconducting tokamak [Li, Wan, and Mao, Plasma Phys. Controlled Fusion 42, 135 (2000)] to measure plasma turbulence in the edge region. Some statistical analysis techniques are used to characterize the turbulence structures. It is found that the plasma turbulence is composed of multiscale coherent structures, i.e., turbulent eddies and there is self-similarity in a relative short scale range. The presence of the self-similarity is found due to the structural similarity of these eddies between different scales. These turbulent eddies constitute the basic convection cells, so the self-similar range is just the dominant scale range relevant to transport. The experimental results also indicate that the plasma turbulence is dominated by low-frequency and long-wavelength fluctuation components and its dispersion relation shows typical electron-drift-wave characteristics. Some large-scale coherent structures intermittently burst out and exhibit a very long poloidal extent, even longer than 6 cm. It is found that these large-scale coherent structures are mainly contributed by the low-frequency and long-wavelength fluctuating components and their presence is responsible for the observations of long-range correlations, i.e., the correlation in the scale range much longer than the turbulence decorrelation scale. These experimental observations suggest that the coexistence of multiscale coherent structures results in the self-similar turbulent state

  6. Multiscale structure in eco-evolutionary dynamics

    Science.gov (United States)

    Stacey, Blake C.

    In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.

  7. Institute for Multiscale Modeling of Biological Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham

    2009-12-26

    The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.

  8. Multi-scale biomedical systems: measurement challenges

    International Nuclear Information System (INIS)

    Summers, R

    2016-01-01

    Multi-scale biomedical systems are those that represent interactions in materials, sensors, and systems from a holistic perspective. It is possible to view such multi-scale activity using measurement of spatial scale or time scale, though in this paper only the former is considered. The biomedical application paradigm comprises interactions that range from quantum biological phenomena at scales of 10-12 for one individual to epidemiological studies of disease spread in populations that in a pandemic lead to measurement at a scale of 10+7. It is clear that there are measurement challenges at either end of this spatial scale, but those challenges that relate to the use of new technologies that deal with big data and health service delivery at the point of care are also considered. The measurement challenges lead to the use, in many cases, of model-based measurement and the adoption of virtual engineering. It is these measurement challenges that will be uncovered in this paper. (paper)

  9. Multiscale permutation entropy analysis of electrocardiogram

    Science.gov (United States)

    Liu, Tiebing; Yao, Wenpo; Wu, Min; Shi, Zhaorong; Wang, Jun; Ning, Xinbao

    2017-04-01

    To make a comprehensive nonlinear analysis to ECG, multiscale permutation entropy (MPE) was applied to ECG characteristics extraction to make a comprehensive nonlinear analysis of ECG. Three kinds of ECG from PhysioNet database, congestive heart failure (CHF) patients, healthy young and elderly subjects, are applied in this paper. We set embedding dimension to 4 and adjust scale factor from 2 to 100 with a step size of 2, and compare MPE with multiscale entropy (MSE). As increase of scale factor, MPE complexity of the three ECG signals are showing first-decrease and last-increase trends. When scale factor is between 10 and 32, complexities of the three ECG had biggest difference, entropy of the elderly is 0.146 less than the CHF patients and 0.025 larger than the healthy young in average, in line with normal physiological characteristics. Test results showed that MPE can effectively apply in ECG nonlinear analysis, and can effectively distinguish different ECG signals.

  10. A Multiscale Model for Virus Capsid Dynamics

    Directory of Open Access Journals (Sweden)

    Changjun Chen

    2010-01-01

    Full Text Available Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows.

  11. Multiscale Convolutional Neural Networks for Hand Detection

    Directory of Open Access Journals (Sweden)

    Shiyang Yan

    2017-01-01

    Full Text Available Unconstrained hand detection in still images plays an important role in many hand-related vision problems, for example, hand tracking, gesture analysis, human action recognition and human-machine interaction, and sign language recognition. Although hand detection has been extensively studied for decades, it is still a challenging task with many problems to be tackled. The contributing factors for this complexity include heavy occlusion, low resolution, varying illumination conditions, different hand gestures, and the complex interactions between hands and objects or other hands. In this paper, we propose a multiscale deep learning model for unconstrained hand detection in still images. Deep learning models, and deep convolutional neural networks (CNNs in particular, have achieved state-of-the-art performances in many vision benchmarks. Developed from the region-based CNN (R-CNN model, we propose a hand detection scheme based on candidate regions generated by a generic region proposal algorithm, followed by multiscale information fusion from the popular VGG16 model. Two benchmark datasets were applied to validate the proposed method, namely, the Oxford Hand Detection Dataset and the VIVA Hand Detection Challenge. We achieved state-of-the-art results on the Oxford Hand Detection Dataset and had satisfactory performance in the VIVA Hand Detection Challenge.

  12. Source-to-exposure assessment with the Pangea multi-scale framework - case study in Australia.

    Science.gov (United States)

    Wannaz, Cedric; Fantke, Peter; Lane, Joe; Jolliet, Olivier

    2018-01-24

    Effective planning of airshed pollution mitigation is often constrained by a lack of integrative analysis able to relate the relevant emitters to the receptor populations at risk. Both emitter and receptor perspectives are therefore needed to consistently inform emission and exposure reduction measures. This paper aims to extend the Pangea spatial multi-scale multimedia framework to evaluate source-to-receptor relationships of industrial sources of organic pollutants in Australia. Pangea solves a large compartmental system in parallel by block to determine arrays of masses at steady-state for 100 000+ compartments and 4000+ emission scenarios, and further computes population exposure by inhalation and ingestion. From an emitter perspective, radial spatial distributions of population intakes show high spatial variation in intake fractions from 0.68 to 33 ppm for benzene, and from 0.006 to 9.5 ppm for formaldehyde, contrasting urban, rural, desert, and sea source locations. Extending analyses to the receptor perspective, population exposures from the combined emissions of 4101 Australian point sources are more extended for benzene that travels over longer distances, versus formaldehyde that has a more local impact. Decomposing exposure per industrial sector shows petroleum and steel industry as the highest contributing industrial sectors for benzene, whereas the electricity sector and petroleum refining contribute most to formaldehyde exposures. The source apportionment identifies the main sources contributing to exposure at five locations. Overall, this paper demonstrates high interest in addressing exposures from both an emitter perspective well-suited to inform product oriented approaches such as LCA, and from a receptor perspective for health risk mitigation.

  13. Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata.

    Science.gov (United States)

    Leempoel, Kevin; Parisod, Christian; Geiser, Céline; Joost, Stéphane

    2018-02-01

    Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata . The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

  14. Residual-driven online generalized multiscale finite element methods

    KAUST Repository

    Chung, Eric T.

    2015-09-08

    The construction of local reduced-order models via multiscale basis functions has been an area of active research. In this paper, we propose online multiscale basis functions which are constructed using the offline space and the current residual. Online multiscale basis functions are constructed adaptively in some selected regions based on our error indicators. We derive an error estimator which shows that one needs to have an offline space with certain properties to guarantee that additional online multiscale basis function will decrease the error. This error decrease is independent of physical parameters, such as the contrast and multiple scales in the problem. The offline spaces are constructed using Generalized Multiscale Finite Element Methods (GMsFEM). We show that if one chooses a sufficient number of offline basis functions, one can guarantee that additional online multiscale basis functions will reduce the error independent of contrast. We note that the construction of online basis functions is motivated by the fact that the offline space construction does not take into account distant effects. Using the residual information, we can incorporate the distant information provided the offline approximation satisfies certain properties. In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.

  15. Simulation of left atrial function using a multi-scale model of the cardiovascular system.

    Directory of Open Access Journals (Sweden)

    Antoine Pironet

    Full Text Available During a full cardiac cycle, the left atrium successively behaves as a reservoir, a conduit and a pump. This complex behavior makes it unrealistic to apply the time-varying elastance theory to characterize the left atrium, first, because this theory has known limitations, and second, because it is still uncertain whether the load independence hypothesis holds. In this study, we aim to bypass this uncertainty by relying on another kind of mathematical model of the cardiac chambers. In the present work, we describe both the left atrium and the left ventricle with a multi-scale model. The multi-scale property of this model comes from the fact that pressure inside a cardiac chamber is derived from a model of the sarcomere behavior. Macroscopic model parameters are identified from reference dog hemodynamic data. The multi-scale model of the cardiovascular system including the left atrium is then simulated to show that the physiological roles of the left atrium are correctly reproduced. This include a biphasic pressure wave and an eight-shaped pressure-volume loop. We also test the validity of our model in non basal conditions by reproducing a preload reduction experiment by inferior vena cava occlusion with the model. We compute the variation of eight indices before and after this experiment and obtain the same variation as experimentally observed for seven out of the eight indices. In summary, the multi-scale mathematical model presented in this work is able to correctly account for the three roles of the left atrium and also exhibits a realistic left atrial pressure-volume loop. Furthermore, the model has been previously presented and validated for the left ventricle. This makes it a proper alternative to the time-varying elastance theory if the focus is set on precisely representing the left atrial and left ventricular behaviors.

  16. An open source platform for multi-scale spatially distributed simulations of microbial ecosystems

    Energy Technology Data Exchange (ETDEWEB)

    Segre, Daniel [Boston Univ., MA (United States)

    2014-08-14

    The goal of this project was to develop a tool for facilitating simulation, validation and discovery of multiscale dynamical processes in microbial ecosystems. This led to the development of an open-source software platform for Computation Of Microbial Ecosystems in Time and Space (COMETS). COMETS performs spatially distributed time-dependent flux balance based simulations of microbial metabolism. Our plan involved building the software platform itself, calibrating and testing it through comparison with experimental data, and integrating simulations and experiments to address important open questions on the evolution and dynamics of cross-feeding interactions between microbial species.

  17. A Multiscale Closed-Loop Cardiovascular Model, with Applications to Heart Pacing and Hemorrhage

    Science.gov (United States)

    Canuto, Daniel; Eldredge, Jeff; Chong, Kwitae; Benharash, Peyman; Dutson, Erik

    2017-11-01

    A computational tool is developed for simulating the dynamic response of the human cardiovascular system to various stressors and injuries. The tool couples zero-dimensional models of the heart, pulmonary vasculature, and peripheral vasculature to one-dimensional models of the major systemic arteries. To simulate autonomic response, this multiscale circulatory model is integrated with a feedback model of the baroreflex, allowing control of heart rate, cardiac contractility, and peripheral impedance. The performance of the tool is demonstrated in two scenarios: increasing heart rate by stimulating the sympathetic nervous system, and an acute 10 percent hemorrhage from the left femoral artery.

  18. Analysis of complex time series using refined composite multiscale entropy

    International Nuclear Information System (INIS)

    Wu, Shuen-De; Wu, Chiu-Wen; Lin, Shiou-Gwo; Lee, Kung-Yen; Peng, Chung-Kang

    2014-01-01

    Multiscale entropy (MSE) is an effective algorithm for measuring the complexity of a time series that has been applied in many fields successfully. However, MSE may yield an inaccurate estimation of entropy or induce undefined entropy because the coarse-graining procedure reduces the length of a time series considerably at large scales. Composite multiscale entropy (CMSE) was recently proposed to improve the accuracy of MSE, but it does not resolve undefined entropy. Here we propose a refined composite multiscale entropy (RCMSE) to improve CMSE. For short time series analyses, we demonstrate that RCMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy.

  19. Multi-Scale Scattering Transform in Music Similarity Measuring

    Science.gov (United States)

    Wang, Ruobai

    Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.

  20. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    Science.gov (United States)

    Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

    2016-05-01

    The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

  1. Multi-scale salient feature extraction on mesh models

    KAUST Repository

    Yang, Yongliang; Shen, ChaoHui

    2012-01-01

    We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.

  2. A New Multiscale Technique for Time-Accurate Geophysics Simulations

    Science.gov (United States)

    Omelchenko, Y. A.; Karimabadi, H.

    2006-12-01

    Large-scale geophysics systems are frequently described by multiscale reactive flow models (e.g., wildfire and climate models, multiphase flows in porous rocks, etc.). Accurate and robust simulations of such systems by traditional time-stepping techniques face a formidable computational challenge. Explicit time integration suffers from global (CFL and accuracy) timestep restrictions due to inhomogeneous convective and diffusion processes, as well as closely coupled physical and chemical reactions. Application of adaptive mesh refinement (AMR) to such systems may not be always sufficient since its success critically depends on a careful choice of domain refinement strategy. On the other hand, implicit and timestep-splitting integrations may result in a considerable loss of accuracy when fast transients in the solution become important. To address this issue, we developed an alternative explicit approach to time-accurate integration of such systems: Discrete-Event Simulation (DES). DES enables asynchronous computation by automatically adjusting the CPU resources in accordance with local timescales. This is done by encapsulating flux- conservative updates of numerical variables in the form of events, whose execution and synchronization is explicitly controlled by imposing accuracy and causality constraints. As a result, at each time step DES self- adaptively updates only a fraction of the global system state, which eliminates unnecessary computation of inactive elements. DES can be naturally combined with various mesh generation techniques. The event-driven paradigm results in robust and fast simulation codes, which can be efficiently parallelized via a new preemptive event processing (PEP) technique. We discuss applications of this novel technology to time-dependent diffusion-advection-reaction and CFD models representative of various geophysics applications.

  3. Multiscale Modeling of Microbial Communities

    Science.gov (United States)

    Blanchard, Andrew

    smooth expanding front. More specifically, mutualism promotes spatial homogeneity and population robustness while competition increases spatial segregation and population fluctuations. To examine the generality of these findings, a large set of initial conditions with varying density and species abundance was tested and analyzed. The results and the computational framework presented provide the basis for further explorations of individual based simulations of bacterial communities. For Chapter 4, I consider the role of gene regulation in shaping the outcome of competition between a bacteriocin (i.e. toxin) producing and sensitive strain. In natural systems, bacteriocin production is often conditional, governed by underlying quorum sensing regulatory circuitry. By developing an ordinary differential equation (ODE) model integrating population dynamics with molecular regulation, we find that the ecological contribution of bacteriocin production can be positive or negative, determined by the tradeoff between the benefit of bacteriocins in mediating competition and the fitness cost due to metabolic load. Interestingly, under the naturally occurring scenario where bacteriocin production has a high cost, density-dependent synthesis is more advantageous than constitutive synthesis, which offers a quantitative interpretation for the wide prevalence of density-related bacteriocin production in nature. By incorporating the modeling framework presented in Chapter 3, the results of the ODE model were extended to the spatial setting, providing ecological insights into the costs and benefits of bacteriocin synthesis in competitive environments. For the final research chapter, I consider the impact of growth coupling on protein production at both the single cell and population scales. The same machinery (e.g. ribosomes) and resources (e.g. amino acids and ATP) are used within cells to produce both endogenous (host) and exogenous (circuit) proteins. Thus, the introduction of a gene

  4. Modeling the effects of light and sucrose on in vitro propagated plants: a multiscale system analysis using artificial intelligence technology.

    Science.gov (United States)

    Gago, Jorge; Martínez-Núñez, Lourdes; Landín, Mariana; Flexas, Jaume; Gallego, Pedro P

    2014-01-01

    Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122-130 µmol m(-2) s(-1). Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work.

  5. Towards systems biology of the gravity response of higher plants -multiscale analysis of Arabidopsis thaliana root growth

    Science.gov (United States)

    Palme, Klaus; Aubry, D.; Bensch, M.; Schmidt, T.; Ronneberger, O.; Neu, C.; Li, X.; Wang, H.; Santos, F.; Wang, B.; Paponov, I.; Ditengou, F. A.; Teale, W. T.; Volkmann, D.; Baluska, F.; Nonis, A.; Trevisan, S.; Ruperti, B.; Dovzhenko, A.

    Gravity plays a fundamental role in plant growth and development. Up to now, little is known about the molecular organisation of the signal transduction cascades and networks which co-ordinate gravity perception and response. By using an integrated systems biological approach, a systems analysis of gravity perception and the subsequent tightly-regulated growth response is planned in the model plant Arabidopsis thaliana. This approach will address questions such as: (i) what are the components of gravity signal transduction pathways? (ii) what are the dynamics of these components? (iii) what is their spatio-temporal regulation in different tis-sues? Using Arabidopsis thaliana as a model-we use root growth to obtain insights in the gravity response. New techniques enable identification of the individual genes affected by grav-ity and further integration of transcriptomics and proteomics data into interaction networks and cell communication events that operate during gravitropic curvature. Using systematic multiscale analysis we have identified regulatory networks consisting of transcription factors, the protein degradation machinery, vesicle trafficking and cellular signalling during the gravire-sponse. We developed approach allowing to incorporate key features of the root system across all relevant spatial and temporal scales to describe gene-expression patterns and correlate them with individual gene and protein functions. Combination of high-resolution microscopy and novel computational tools resulted in development of the root 3D model in which quantitative descriptions of cellular network properties and of multicellular interactions important in root growth and gravitropism can be integrated for the first time.

  6. Multiscale Multilevel Approach to Solution of Nanotechnology Problems

    Directory of Open Access Journals (Sweden)

    Polyakov Sergey

    2018-01-01

    Full Text Available The paper is devoted to a multiscale multilevel approach for the solution of nanotechnology problems on supercomputer systems. The approach uses the combination of continuum mechanics models and the Newton dynamics for individual particles. This combination includes three scale levels: macroscopic, mesoscopic and microscopic. For gas–metal technical systems the following models are used. The quasihydrodynamic system of equations is used as a mathematical model at the macrolevel for gas and solid states. The system of Newton equations is used as a mathematical model at the mesoand microlevels; it is written for nanoparticles of the medium and larger particles moving in the medium. The numerical implementation of the approach is based on the method of splitting into physical processes. The quasihydrodynamic equations are solved by the finite volume method on grids of different types. The Newton equations of motion are solved by Verlet integration in each cell of the grid independently or in groups of connected cells. In the framework of the general methodology, four classes of algorithms and methods of their parallelization are provided. The parallelization uses the principles of geometric parallelism and the efficient partitioning of the computational domain. A special dynamic algorithm is used for load balancing the solvers. The testing of the developed approach was made by the example of the nitrogen outflow from a balloon with high pressure to a vacuum chamber through a micronozzle and a microchannel. The obtained results confirm the high efficiency of the developed methodology.

  7. Multiscale molecular dynamics using the matched interface and boundary method

    International Nuclear Information System (INIS)

    Geng Weihua; Wei, G.W.

    2011-01-01

    The Poisson-Boltzmann (PB) equation is an established multiscale model for electrostatic analysis of biomolecules and other dielectric systems. PB based molecular dynamics (MD) approach has a potential to tackle large biological systems. Obstacles that hinder the current development of PB based MD methods are concerns in accuracy, stability, efficiency and reliability. The presence of complex solvent-solute interface, geometric singularities and charge singularities leads to challenges in the numerical solution of the PB equation and electrostatic force evaluation in PB based MD methods. Recently, the matched interface and boundary (MIB) method has been utilized to develop the first second order accurate PB solver that is numerically stable in dealing with discontinuous dielectric coefficients, complex geometric singularities and singular source charges. The present work develops the PB based MD approach using the MIB method. New formulation of electrostatic forces is derived to allow the use of sharp molecular surfaces. Accurate reaction field forces are obtained by directly differentiating the electrostatic potential. Dielectric boundary forces are evaluated at the solvent-solute interface using an accurate Cartesian-grid surface integration method. The electrostatic forces located at reentrant surfaces are appropriately assigned to related atoms. Extensive numerical tests are carried out to validate the accuracy and stability of the present electrostatic force calculation. The new PB based MD method is implemented in conjunction with the AMBER package. MIB based MD simulations of biomolecules are demonstrated via a few example systems.

  8. Multiscale Multilevel Approach to Solution of Nanotechnology Problems

    Science.gov (United States)

    Polyakov, Sergey; Podryga, Viktoriia

    2018-02-01

    The paper is devoted to a multiscale multilevel approach for the solution of nanotechnology problems on supercomputer systems. The approach uses the combination of continuum mechanics models and the Newton dynamics for individual particles. This combination includes three scale levels: macroscopic, mesoscopic and microscopic. For gas-metal technical systems the following models are used. The quasihydrodynamic system of equations is used as a mathematical model at the macrolevel for gas and solid states. The system of Newton equations is used as a mathematical model at the mesoand microlevels; it is written for nanoparticles of the medium and larger particles moving in the medium. The numerical implementation of the approach is based on the method of splitting into physical processes. The quasihydrodynamic equations are solved by the finite volume method on grids of different types. The Newton equations of motion are solved by Verlet integration in each cell of the grid independently or in groups of connected cells. In the framework of the general methodology, four classes of algorithms and methods of their parallelization are provided. The parallelization uses the principles of geometric parallelism and the efficient partitioning of the computational domain. A special dynamic algorithm is used for load balancing the solvers. The testing of the developed approach was made by the example of the nitrogen outflow from a balloon with high pressure to a vacuum chamber through a micronozzle and a microchannel. The obtained results confirm the high efficiency of the developed methodology.

  9. Multi-scale Multi-mechanism Toughening of Hydrogels

    Science.gov (United States)

    Zhao, Xuanhe

    Hydrogels are widely used as scaffolds for tissue engineering, vehicles for drug delivery, actuators for optics and fluidics, and model extracellular matrices for biological studies. The scope of hydrogel applications, however, is often severely limited by their mechanical properties. Inspired by the mechanics and hierarchical structures of tough biological tissues, we propose that a general principle for the design of tough hydrogels is to implement two mechanisms for dissipating mechanical energy and maintaining high elasticity in hydrogels. A particularly promising strategy for the design is to integrate multiple pairs of mechanisms across multiple length scales into a hydrogel. We develop a multiscale theoretical framework to quantitatively guide the design of tough hydrogels. On the network level, we have developed micro-physical models to characterize the evolution of polymer networks under deformation. On the continuum level, we have implemented constitutive laws formulated from the network-level models into a coupled cohesive-zone and Mullins-effect model to quantitatively predict crack propagation and fracture toughness of hydrogels. Guided by the design principle and quantitative model, we will demonstrate a set of new hydrogels, based on diverse types of polymers, yet can achieve extremely high toughness superior to their natural counterparts such as cartilages. The work was supported by NSF(No. CMMI- 1253495) and ONR (No. N00014-14-1-0528).

  10. Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Z.; Bessa, M. A.; Liu, W.K.

    2017-10-25

    A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical and concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about

  11. Variational multiscale models for charge transport.

    Science.gov (United States)

    Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin

    2012-01-01

    This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle

  12. Variational multiscale models for charge transport

    Science.gov (United States)

    Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin

    2012-01-01

    This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle

  13. Identifying barriers to large-scale integration of variable renewable electricity into the electricity market : A literature review of market design

    NARCIS (Netherlands)

    Hu, J.; Harmsen, R.; Crijns-Graus, Wina; Worrell, E.; van den Broek, M.A.

    For reaching the 2 °C climate target, the robust growth of electricity generation from variable renewable energy sources (VRE) in the power sector is expected to continue. Accommodation of the power system to the variable, uncertain and locational-dependent outputs of VRE causes integration costs.

  14. Integrated automation for continuous high-throughput synthetic chromosome assembly and transformation to identify improved yeast strains for industrial production of peptide sweetener brazzein

    Science.gov (United States)

    Production and recycling of recombinant sweetener peptides in industrial biorefineries involves the evaluation of large numbers of genes and proteins. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly synthesize, clone, and express heterologous gene ope...

  15. Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

    Science.gov (United States)

    Liou, Frank; Newkirk, Joseph; Fan, Zhiqiang; Sparks, Todd; Chen, Xueyang; Fletcher, Kenneth; Zhang, Jingwei; Zhang, Yunlu; Kumar, Kannan Suresh; Karnati, Sreekar

    2015-01-01

    , after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion's direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification.

  16. RBF Multiscale Collocation for Second Order Elliptic Boundary Value Problems

    KAUST Repository

    Farrell, Patricio; Wendland, Holger

    2013-01-01

    In this paper, we discuss multiscale radial basis function collocation methods for solving elliptic partial differential equations on bounded domains. The approximate solution is constructed in a multilevel fashion, each level using compactly

  17. A multiscale mortar multipoint flux mixed finite element method

    KAUST Repository

    Wheeler, Mary Fanett; Xue, Guangri; Yotov, Ivan

    2012-01-01

    In this paper, we develop a multiscale mortar multipoint flux mixed finite element method for second order elliptic problems. The equations in the coarse elements (or subdomains) are discretized on a fine grid scale by a multipoint flux mixed finite

  18. Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction

    KAUST Repository

    Ghasemi, Mohammadreza; Yang, Yanfang; Gildin, Eduardo; Efendiev, Yalchin R.; Calo, Victor M.

    2015-01-01

    snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3

  19. Multi-Scale Simulation of High Energy Density Ionic Liquids

    National Research Council Canada - National Science Library

    Voth, Gregory A

    2007-01-01

    The focus of this AFOSR project was the molecular dynamics (MD) simulation of ionic liquid structure, dynamics, and interfacial properties, as well as multi-scale descriptions of these novel liquids (e.g...

  20. Multi-scale modeling strategies in materials science—The ...

    Indian Academy of Sciences (India)

    Unknown

    Multi-scale models; quasicontinuum method; finite elements. 1. Introduction ... boundary with external stresses, and the interaction of a lattice dislocation with a grain ..... mum value of se over the elements that touch node α. The acceleration of ...

  1. Lifetime statistics of quantum chaos studied by a multiscale analysis

    KAUST Repository

    Di Falco, A.; Krauss, T. F.; Fratalocchi, Andrea

    2012-01-01

    on a silicon-on-insulator substrate. We calculate resonances through a multiscale procedure that combines energy landscape analysis and wavelet transforms. Experimental data is found to follow the universal predictions arising from random matrix theory

  2. Randomized Oversampling for Generalized Multiscale Finite Element Methods

    KAUST Repository

    Calo, Victor M.; Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian

    2016-01-01

    boundary conditions defined in a domain larger than the target region. Furthermore, we perform an eigenvalue decomposition in this small space. We study the application of randomized sampling for GMsFEM in conjunction with adaptivity, where local multiscale

  3. Toward the multiscale nature of stress corrosion cracking

    Directory of Open Access Journals (Sweden)

    Xiaolong Liu

    2018-02-01

    Full Text Available This article reviews the multiscale nature of stress corrosion cracking (SCC observed by high-resolution characterizations in austenite stainless steels and Ni-base superalloys in light water reactors (including boiling water reactors, pressurized water reactors, and supercritical water reactors with related opinions. A new statistical summary and comparison of observed degradation phenomena at different length scales is included. The intrinsic causes of this multiscale nature of SCC are discussed based on existing evidence and related opinions, ranging from materials theory to practical processing technologies. Questions of interest are then discussed to improve bottom-up understanding of the intrinsic causes. Last, a multiscale modeling and simulation methodology is proposed as a promising interdisciplinary solution to understand the intrinsic causes of the multiscale nature of SCC in light water reactors, based on a review of related supporting application evidence.

  4. Multiscale model reduction for shale gas transport in fractured media

    KAUST Repository

    Akkutlu, I. Y.; Efendiev, Yalchin R.; Vasilyeva, Maria

    2016-01-01

    fracture distributions on an unstructured grid; (2) develop GMsFEM for nonlinear flows; and (3) develop online basis function strategies to adaptively improve the convergence. The number of multiscale basis functions in each coarse region represents

  5. Distributed Multiscale Data Analysis and Processing for Sensor Networks

    National Research Council Canada - National Science Library

    Wagner, Raymond; Sarvotham, Shriram; Choi, Hyeokho; Baraniuk, Richard

    2005-01-01

    .... Second, the communication overhead of multiscale algorithms can become prohibitive. In this paper, we take a first step in addressing both shortcomings by introducing two new distributed multiresolution transforms...

  6. Examining Multiscale Movement Coordination in Collaborative Problem Solving

    DEFF Research Database (Denmark)

    Wiltshire, Travis; Steffensen, Sune Vork

    2017-01-01

    During collaborative problem solving (CPS), coordination occurs at different spatial and temporal scales. This multiscale coordination should, at least on some scales, play a functional role in facilitating effective collaboration outcomes. To evaluate this, we conducted a study of computer...

  7. Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

    Directory of Open Access Journals (Sweden)

    Matthew B Biggs

    Full Text Available Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

  8. Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

    Science.gov (United States)

    Biggs, Matthew B; Papin, Jason A

    2013-01-01

    Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

  9. Multiscale multichroic focal planes for measurements of the cosmic microwave background

    Science.gov (United States)

    Cukierman, Ari; Lee, Adrian T.; Raum, Christopher; Suzuki, Aritoki; Westbrook, Benjamin

    2018-01-01

    We report on the development of multiscale multichroic focal planes for measurements of the cosmic microwave background (CMB). A multichroic focal plane, i.e., one that consists of pixels that are simultaneously sensitive in multiple frequency bands, is an efficient architecture for increasing the sensitivity of an experiment as well as for disentangling the contamination due to galactic foregrounds, which is increasingly becoming the limiting factor in extracting cosmological information from CMB measurements. To achieve these goals, it is necessary to observe across a broad frequency range spanning roughly 30-350 GHz. For this purpose, the Berkeley CMB group has been developing multichroic pixels consisting of planar superconducting sinuous antennas coupled to extended hemispherical lenslets, which operate at sub-Kelvin temperatures. The sinuous antennas, microwave circuitry and the transition-edge-sensor (TES) bolometers to which they are coupled are integrated in a single lithographed wafer.We describe the design, fabrication, testing and performance of multichroic pixels with bandwidths of 3:1 and 4:1 across the entire frequency range of interest. Additionally, we report on a demonstration of multiscale pixels, i.e., pixels whose effective size changes as a function of frequency. This property keeps the beam width approximately constant across all frequencies, which in turn allows the sensitivity of the experiment to be optimal in every frequency band. We achieve this by creating phased arrays from neighboring lenslet-coupled sinuous antennas, where the size of each phased array is chosen independently for each frequency band. We describe the microwave circuitry in detail as well as the benefits of a multiscale architecture, e.g., mitigation of beam non-idealities, reduced readout requirements, etc. Finally, we discuss the design and fabrication of the detector modules and focal-plane structures including cryogenic readout components, which enable the

  10. Long-term Stable Conservative Multiscale Methods for Vortex Flows

    Science.gov (United States)

    2017-10-31

    Computing Department, Florida State (January 2016) - L. Rebholz, SIAM Southeast 2016, Special session on Recent advances in fluid flow and...Multiscale Methods for Vortex Flows (x) Material has been given an OPSEC review and it has been determined to be non sensitive and, except for...distribution is unlimited. UU UU UU UU 31-10-2017 1-Aug-2014 31-Jul-2017 Final Report: Long-term Stable Conservative Multiscale Methods for Vortex Flows

  11. RFP for the Auroral Multiscale Midex (AMM) Mission star tracker

    DEFF Research Database (Denmark)

    Riis, Troels; Betto, Maurizio; Jørgensen, John Leif

    1999-01-01

    This document is in response to the John Hopkins University - Applied Physics Laboratory RFP for the Auroral Multiscale Midex Mission star tracker.It describes the functionality, the requirements and the performance of the ASC Star Tracker.......This document is in response to the John Hopkins University - Applied Physics Laboratory RFP for the Auroral Multiscale Midex Mission star tracker.It describes the functionality, the requirements and the performance of the ASC Star Tracker....

  12. MUSIC: MUlti-Scale Initial Conditions

    Science.gov (United States)

    Hahn, Oliver; Abel, Tom

    2013-11-01

    MUSIC generates multi-scale initial conditions with multiple levels of refinements for cosmological ‘zoom-in’ simulations. The code uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). MUSIC achieves rms relative errors of the order of 10-4 for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier space-induced interference ringing.

  13. Multi-scale modeling of composites

    DEFF Research Database (Denmark)

    Azizi, Reza

    A general method to obtain the homogenized response of metal-matrix composites is developed. It is assumed that the microscopic scale is sufficiently small compared to the macroscopic scale such that the macro response does not affect the micromechanical model. Therefore, the microscopic scale......-Mandel’s energy principle is used to find macroscopic operators based on micro-mechanical analyses using the finite element method under generalized plane strain condition. A phenomenologically macroscopic model for metal matrix composites is developed based on constitutive operators describing the elastic...... to plastic deformation. The macroscopic operators found, can be used to model metal matrix composites on the macroscopic scale using a hierarchical multi-scale approach. Finally, decohesion under tension and shear loading is studied using a cohesive law for the interface between matrix and fiber....

  14. Quantifying multiscale inefficiency in electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Uritskaya, Olga Y. [Department of Economics, University of Calgary, Calgary, Alberta T2N 1N4, and Department of Economics and Management, St. Petersburg Polytechnic University, St. Petersburg (Russian Federation); Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alberta (Canada)

    2008-11-15

    One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies. (author)

  15. On multiscale moving contact line theory.

    Science.gov (United States)

    Li, Shaofan; Fan, Houfu

    2015-07-08

    In this paper, a multiscale moving contact line (MMCL) theory is presented and employed to simulate liquid droplet spreading and capillary motion. The proposed MMCL theory combines a coarse-grained adhesive contact model with a fluid interface membrane theory, so that it can couple molecular scale adhesive interaction and surface tension with hydrodynamics of microscale flow. By doing so, the intermolecular force, the van der Waals or double layer force, separates and levitates the liquid droplet from the supporting solid substrate, which avoids the shear stress singularity caused by the no-slip condition in conventional hydrodynamics theory of moving contact line. Thus, the MMCL allows the difference of the surface energies and surface stresses to drive droplet spreading naturally. To validate the proposed MMCL theory, we have employed it to simulate droplet spreading over various elastic substrates. The numerical simulation results obtained by using MMCL are in good agreement with the molecular dynamics results reported in the literature.

  16. Numerical methods and analysis of multiscale problems

    CERN Document Server

    Madureira, Alexandre L

    2017-01-01

    This book is about numerical modeling of multiscale problems, and introduces several asymptotic analysis and numerical techniques which are necessary for a proper approximation of equations that depend on different physical scales. Aimed at advanced undergraduate and graduate students in mathematics, engineering and physics – or researchers seeking a no-nonsense approach –, it discusses examples in their simplest possible settings, removing mathematical hurdles that might hinder a clear understanding of the methods. The problems considered are given by singular perturbed reaction advection diffusion equations in one and two-dimensional domains, partial differential equations in domains with rough boundaries, and equations with oscillatory coefficients. This work shows how asymptotic analysis can be used to develop and analyze models and numerical methods that are robust and work well for a wide range of parameters.

  17. Quantifying multiscale inefficiency in electricity markets

    International Nuclear Information System (INIS)

    Uritskaya, Olga Y.; Serletis, Apostolos

    2008-01-01

    One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies. (author)

  18. Multiscale modeling of three-dimensional genome

    Science.gov (United States)

    Zhang, Bin; Wolynes, Peter

    The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

  19. Hybrid stochastic simplifications for multiscale gene networks

    Directory of Open Access Journals (Sweden)

    Debussche Arnaud

    2009-09-01

    Full Text Available Abstract Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion 123 which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.

  20. Parallel multiscale simulations of a brain aneurysm

    Energy Technology Data Exchange (ETDEWEB)

    Grinberg, Leopold [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Fedosov, Dmitry A. [Institute of Complex Systems and Institute for Advanced Simulation, Forschungszentrum Jülich, Jülich 52425 (Germany); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)

    2013-07-01

    Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300 K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in

  1. Parallel multiscale simulations of a brain aneurysm

    International Nuclear Information System (INIS)

    Grinberg, Leopold; Fedosov, Dmitry A.; Karniadakis, George Em

    2013-01-01

    Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific