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Sample records for models enable interpretation

  1. Interpretive Structural Modeling Of Implementation Enablers For Just In Time In ICPI

    Directory of Open Access Journals (Sweden)

    Nitin Upadhye

    2014-12-01

    Full Text Available Indian Corrugated Packaging Industries (ICPI have built up tough competition among the industries in terms of product cost, quality, product delivery, flexibility, and finally customer’s demand. As their customers, mostly OEMs are asking Just in Time deliveries, ICPI must implement JIT in their system. The term "JIT” as, it denotes a system that utilizes less, in terms of all inputs, to create the same outputs as those created by a traditional mass production system, while contributing increased varieties for the end customer. (Womack et al. 1990 "JIT" focuses on abolishing or reducing Muda (“Muda", the Japanese word for waste and on maximizing or fully utilizing activities that add value from the customer's perspective. There is lack of awareness in identifying the right enablers of JIT implementation. Therefore, this study has tried to find out the enablers from the literature review and expert’s opinions from corrugated packaging industries and developed the relationship matrix to see the driving power and dependence between them. In this study, modeling has been done in order to know the interrelationships between the enablers with the help of Interpretive Structural Modeling and Cross Impact Matrix Multiplication Applied to Classification (MICMAC analysis for the performance of Indian corrugated packaging industries.

  2. Formulation of court interpreting models: A South African perspective

    African Journals Online (AJOL)

    Kate H

    Wilcox and Shaffer (2005: 135) observe that a model of interpreting demonstrates how interpreters perform their role and guides them towards improving their performance. It is from this point of view that South African court interpreters need to be familiar with different models of interpreting to enable them to understand their ...

  3. Model-based biosignal interpretation.

    Science.gov (United States)

    Andreassen, S

    1994-03-01

    Two relatively new approaches to model-based biosignal interpretation, qualitative simulation and modelling by causal probabilistic networks, are compared to modelling by differential equations. A major problem in applying a model to an individual patient is the estimation of the parameters. The available observations are unlikely to allow a proper estimation of the parameters, and even if they do, the task appears to have exponential computational complexity if the model is non-linear. Causal probabilistic networks have both differential equation models and qualitative simulation as special cases, and they can provide both Bayesian and maximum-likelihood parameter estimates, in most cases in much less than exponential time. In addition, they can calculate the probabilities required for a decision-theoretical approach to medical decision support. The practical applicability of causal probabilistic networks to real medical problems is illustrated by a model of glucose metabolism which is used to adjust insulin therapy in type I diabetic patients.

  4. Enabling model customization and integration

    Science.gov (United States)

    Park, Minho; Fishwick, Paul A.

    2003-09-01

    Until fairly recently, the idea of dynamic model content and presentation were treated synonymously. For example, if one was to take a data flow network, which captures the dynamics of a target system in terms of the flow of data through nodal operators, then one would often standardize on rectangles and arrows for the model display. The increasing web emphasis on XML, however, suggests that the network model can have its content specified in an XML language, and then the model can be represented in a number of ways depending on the chosen style. We have developed a formal method, based on styles, that permits a model to be specified in XML and presented in 1D (text), 2D, and 3D. This method allows for customization and personalization to exert their benefits beyond e-commerce, to the area of model structures used in computer simulation. This customization leads naturally to solving the bigger problem of model integration - the act of taking models of a scene and integrating them with that scene so that there is only one unified modeling interface. This work focuses mostly on customization, but we address the integration issue in the future work section.

  5. Chain graph models and their causal interpretations

    DEFF Research Database (Denmark)

    Lauritzen, Steffen Lilholt; Richardson, Thomas S.

    2002-01-01

    , interpretations of chain graphs that are often invoked, implicitly or explicitly. These interpretations also lead to flawed methods for applying background knowledge to model selection. We present a valid interpretation by showing how the distribution corresponding to a chain graph may be generated from...... traditionally been used to model feed-back in econometrics....

  6. Modeling and interpretation of images*

    Directory of Open Access Journals (Sweden)

    Min Michiel

    2015-01-01

    Full Text Available Imaging protoplanetary disks is a challenging but rewarding task. It is challenging because of the glare of the central star outshining the weak signal from the disk at shorter wavelengths and because of the limited spatial resolution at longer wavelengths. It is rewarding because it contains a wealth of information on the structure of the disks and can (directly probe things like gaps and spiral structure. Because it is so challenging, telescopes are often pushed to their limitations to get a signal. Proper interpretation of these images therefore requires intimate knowledge of the instrumentation, the detection method, and the image processing steps. In this chapter I will give some examples and stress some issues that are important when interpreting images from protoplanetary disks.

  7. Kinetics interpretation model of isothermal martensite reactions

    International Nuclear Information System (INIS)

    Guimaraes, J.R.C.

    1976-01-01

    It was discussed details associated to the interpretation of kinetics of martencite heterogeneous nucleation in isothermal reactions. It was proposed a model which allows compute the variation of concentration of preferencial sites nucleation with a volumetric martencite fraction [pt

  8. Visualisation and interpretation of Support Vector Regression models.

    Science.gov (United States)

    Ustün, B; Melssen, W J; Buydens, L M C

    2007-07-09

    This paper introduces a technique to visualise the information content of the kernel matrix and a way to interpret the ingredients of the Support Vector Regression (SVR) model. Recently, the use of Support Vector Machines (SVM) for solving classification (SVC) and regression (SVR) problems has increased substantially in the field of chemistry and chemometrics. This is mainly due to its high generalisation performance and its ability to model non-linear relationships in a unique and global manner. Modeling of non-linear relationships will be enabled by applying a kernel function. The kernel function transforms the input data, usually non-linearly related to the associated output property, into a high dimensional feature space where the non-linear relationship can be represented in a linear form. Usually, SVMs are applied as a black box technique. Hence, the model cannot be interpreted like, e.g., Partial Least Squares (PLS). For example, the PLS scores and loadings make it possible to visualise and understand the driving force behind the optimal PLS machinery. In this study, we have investigated the possibilities to visualise and interpret the SVM model. Here, we exclusively have focused on Support Vector Regression to demonstrate these visualisation and interpretation techniques. Our observations show that we are now able to turn a SVR black box model into a transparent and interpretable regression modeling technique.

  9. Interpreting Results from the Multinomial Logit Model

    DEFF Research Database (Denmark)

    Wulff, Jesper

    2015-01-01

    This article provides guidelines and illustrates practical steps necessary for an analysis of results from the multinomial logit model (MLM). The MLM is a popular model in the strategy literature because it allows researchers to examine strategic choices with multiple outcomes. However, there seem...... to be systematic issues with regard to how researchers interpret their results when using the MLM. In this study, I present a set of guidelines critical to analyzing and interpreting results from the MLM. The procedure involves intuitive graphical representations of predicted probabilities and marginal effects...... suitable for both interpretation and communication of results. The pratical steps are illustrated through an application of the MLM to the choice of foreign market entry mode....

  10. Modeling and interpreting mesoscale network dynamics.

    Science.gov (United States)

    Khambhati, Ankit N; Sizemore, Ann E; Betzel, Richard F; Bassett, Danielle S

    2017-06-20

    Recent advances in brain imaging techniques, measurement approaches, and storage capacities have provided an unprecedented supply of high temporal resolution neural data. These data present a remarkable opportunity to gain a mechanistic understanding not just of circuit structure, but also of circuit dynamics, and its role in cognition and disease. Such understanding necessitates a description of the raw observations, and a delineation of computational models and mathematical theories that accurately capture fundamental principles behind the observations. Here we review recent advances in a range of modeling approaches that embrace the temporally-evolving interconnected structure of the brain and summarize that structure in a dynamic graph. We describe recent efforts to model dynamic patterns of connectivity, dynamic patterns of activity, and patterns of activity atop connectivity. In the context of these models, we review important considerations in statistical testing, including parametric and non-parametric approaches. Finally, we offer thoughts on careful and accurate interpretation of dynamic graph architecture, and outline important future directions for method development. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Modeling-Enabled Systems Nutritional Immunology

    Directory of Open Access Journals (Sweden)

    Meghna eVerma

    2016-02-01

    Full Text Available This review highlights the fundamental role of nutrition in the maintenance of health, the immune response and disease prevention. Emerging global mechanistic insights in the field of nutritional immunology cannot be gained through reductionist methods alone or by analyzing a single nutrient at a time. We propose to investigate nutritional immunology as a massively interacting system of interconnected multistage and multiscale networks that encompass hidden mechanisms by which nutrition, microbiome, metabolism, genetic predisposition and the immune system interact to delineate health and disease. The review sets an unconventional path to applying complex science methodologies to nutritional immunology research, discovery and development through ‘use cases’ centered around the impact of nutrition on the gut microbiome and immune responses. Our systems nutritional immunology analyses, that include modeling and informatics methodologies in combination with pre-clinical and clinical studies, have the potential to discover emerging systems-wide properties at the interface of the immune system, nutrition, microbiome, and metabolism.

  12. Software to Enable Modeling & Simulation as a Service

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop a Modeling and Simulation as a Service (M&SaaS) software service infrastructure to enable most modeling and simulation (M&S) activities to be...

  13. Interpretations

    Science.gov (United States)

    Bellac, Michel Le

    2014-11-01

    Although nobody can question the practical efficiency of quantum mechanics, there remains the serious question of its interpretation. As Valerio Scarani puts it, "We do not feel at ease with the indistinguishability principle (that is, the superposition principle) and some of its consequences." Indeed, this principle which pervades the quantum world is in stark contradiction with our everyday experience. From the very beginning of quantum mechanics, a number of physicists--but not the majority of them!--have asked the question of its "interpretation". One may simply deny that there is a problem: according to proponents of the minimalist interpretation, quantum mechanics is self-sufficient and needs no interpretation. The point of view held by a majority of physicists, that of the Copenhagen interpretation, will be examined in Section 10.1. The crux of the problem lies in the status of the state vector introduced in the preceding chapter to describe a quantum system, which is no more than a symbolic representation for the Copenhagen school of thought. Conversely, one may try to attribute some "external reality" to this state vector, that is, a correspondence between the mathematical description and the physical reality. In this latter case, it is the measurement problem which is brought to the fore. In 1932, von Neumann was first to propose a global approach, in an attempt to build a purely quantum theory of measurement examined in Section 10.2. This theory still underlies modern approaches, among them those grounded on decoherence theory, or on the macroscopic character of the measuring apparatus: see Section 10.3. Finally, there are non-standard interpretations such as Everett's many worlds theory or the hidden variables theory of de Broglie and Bohm (Section 10.4). Note, however, that this variety of interpretations has no bearing whatsoever on the practical use of quantum mechanics. There is no controversy on the way we should use quantum mechanics!

  14. Green communication: The enabler to multiple business models

    DEFF Research Database (Denmark)

    Lindgren, Peter; Clemmensen, Suberia; Taran, Yariv

    2010-01-01

    Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...... possibility to enable lower energy consumption. This paper shows how green communication enables innovation of green business models and multiple business models running simultaneously in different markets to different customers.......Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...

  15. An expert system for dispersion model interpretation

    International Nuclear Information System (INIS)

    Skyllingstad, E.D.; Ramsdell, J.V.

    1988-10-01

    A prototype expert system designed to diagnose dispersion model uncertainty is described in this paper with application to a puff transport model. The system obtains qualitative information from the model user and through an expert-derived knowledge base, performs a rating of the current simulation. These results can then be used in combination with dispersion model output for deciding appropriate evacuation measures. Ultimately, the goal of this work is to develop an expert system that may be operated accurately by an individual uneducated in meteorology or dispersion modeling. 5 refs., 3 figs

  16. Lumped parameter models for the interpretation of environmental tracer data

    International Nuclear Information System (INIS)

    Maloszewski, P.; Zuber, A.

    1996-01-01

    Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs

  17. Formulation of court interpreting models: A South African perspective

    African Journals Online (AJOL)

    The study follows a qualitative research approach and uses multifaceted theoretical frameworks, namely descriptive translation studies (DTS), cognitive process analysis, and content analysis in collecting and analysing the data. Keywords: court interpreters, cognitive teaching approach, court interpreting models, the role of ...

  18. Interpretive and Critical Phenomenological Crime Studies: A Model Design

    Science.gov (United States)

    Miner-Romanoff, Karen

    2012-01-01

    The critical and interpretive phenomenological approach is underutilized in the study of crime. This commentary describes this approach, guided by the question, "Why are interpretive phenomenological methods appropriate for qualitative research in criminology?" Therefore, the purpose of this paper is to describe a model of the interpretive…

  19. Model-Based Integration and Interpretation of Data

    DEFF Research Database (Denmark)

    Petersen, Johannes

    2004-01-01

    Data integration and interpretation plays a crucial role in supervisory control. The paper defines a set of generic inference steps for the data integration and interpretation process based on a three-layer model of system representations. The three-layer model is used to clarify the combination...... of constraint and object-centered representations of the work domain throwing new light on the basic principles underlying the data integration and interpretation process of Rasmussen's abstraction hierarchy as well as other model-based approaches combining constraint and object-centered representations. Based...

  20. Graphical interpretation of numerical model results

    International Nuclear Information System (INIS)

    Drewes, D.R.

    1979-01-01

    Computer software has been developed to produce high quality graphical displays of data from a numerical grid model. The code uses an existing graphical display package (DISSPLA) and overcomes some of the problems of both line-printer output and traditional graphics. The software has been designed to be flexible enough to handle arbitrarily placed computation grids and a variety of display requirements

  1. Plasma Modeling Enabled Technology Development Empowered by Fundamental Scattering Data

    Science.gov (United States)

    Kushner, Mark J.

    2016-05-01

    Technology development increasingly relies on modeling to speed the innovation cycle. This is particularly true for systems using low temperature plasmas (LTPs) and their role in enabling energy efficient processes with minimal environmental impact. In the innovation cycle, LTP modeling supports investigation of fundamental processes that seed the cycle, optimization of newly developed technologies, and prediction of performance of unbuilt systems for new applications. Although proof-of-principle modeling may be performed for idealized systems in simple gases, technology development must address physically complex systems that use complex gas mixtures that now may be multi-phase (e.g., in contact with liquids). The variety of fundamental electron and ion scattering, and radiation transport data (FSRD) required for this modeling increases as the innovation cycle progresses, while the accuracy required of that data depends on the intended outcome. In all cases, the fidelity, depth and impact of the modeling depends on the availability of FSRD. Modeling and technology development are, in fact, empowered by the availability and robustness of FSRD. In this talk, examples of the impact of and requirements for FSRD in the innovation cycle enabled by plasma modeling will be discussed using results from multidimensional and global models. Examples of fundamental studies and technology optimization will focus on microelectronics fabrication and on optically pumped lasers. Modeling of systems as yet unbuilt will address the interaction of atmospheric pressure plasmas with liquids. Work supported by DOE Office of Fusion Energy Science and the National Science Foundation.

  2. Sparsity enabled cluster reduced-order models for control

    Science.gov (United States)

    Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.

    2018-01-01

    Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.

  3. Superconnections: an interpretation of the standard model

    Directory of Open Access Journals (Sweden)

    Gert Roepstorff

    2000-07-01

    Full Text Available The mathematical framework of superbundles as pioneered by D. Quillen suggests that one consider the Higgs field as a natural constituent of a superconnection. I propose to take as superbundle the exterior algebra obtained from a Hermitian vector bundle of rank n where n=2 for the electroweak theory and n=5 for the full Standard Model. The present setup is similar to but avoids the use of non-commutative geometry.

  4. Conceptual design interpretations, mindset and models

    CERN Document Server

    Andreasen, Mogens Myrup; Cash, Philip

    2015-01-01

    Maximising reader insights into the theory, models, methods and fundamental reasoning of design, this book addresses design activities in industrial settings, as well as the actors involved. This approach offers readers a new understanding of design activities and related functions, properties and dispositions. Presenting a ‘design mindset’ that seeks to empower students, researchers, and practitioners alike, it features a strong focus on how designers create new concepts to be developed into products, and how they generate new business and satisfy human needs.   Employing a multi-faceted perspective, the book supplies the reader with a comprehensive worldview of design in the form of a proposed model that will empower their activities as student, researcher or practitioner. We draw the reader into the core role of design conceptualisation for society, for the development of industry, for users and buyers of products, and for citizens in relation to public systems. The book also features original con...

  5. Using Topic Models to Interpret MEDLINE's Medical Subject Headings

    Science.gov (United States)

    Newman, David; Karimi, Sarvnaz; Cavedon, Lawrence

    We consider the task of interpreting and understanding a taxonomy of classification terms applied to documents in a collection. In particular, we show how unsupervised topic models are useful for interpreting and understanding MeSH, the Medical Subject Headings applied to articles in MEDLINE. We introduce the resampled author model, which captures some of the advantages of both the topic model and the author-topic model. We demonstrate how topic models complement and add to the information conveyed in a traditional listing and description of a subject heading hierarchy.

  6. BIM-Enabled Conceptual Modelling and Representation of Building Circulation

    Directory of Open Access Journals (Sweden)

    Jin Kook Lee

    2014-08-01

    Full Text Available This paper describes how a building information modelling (BIM-based approach for building circulation enables us to change the process of building design in terms of its computational representation and processes, focusing on the conceptual modelling and representation of circulation within buildings. BIM has been designed for use by several BIM authoring tools, in particular with the widely known interoperable industry foundation classes (IFCs, which follow an object-oriented data modelling methodology. Advances in BIM authoring tools, using space objects and their relations defined in an IFC's schema, have made it possible to model, visualize and analyse circulation within buildings prior to their construction. Agent-based circulation has long been an interdisciplinary topic of research across several areas, including design computing, computer science, architectural morphology, human behaviour and environmental psychology. Such conventional approaches to building circulation are centred on navigational knowledge about built environments, and represent specific circulation paths and regulations. This paper, however, places emphasis on the use of ‘space objects’ in BIM-enabled design processes rather than on circulation agents, the latter of which are not defined in the IFCs' schemas. By introducing and reviewing some associated research and projects, this paper also surveys how such a circulation representation is applicable to the analysis of building circulation-related rules.

  7. Cooperative cognitive radio networking system model, enabling techniques, and performance

    CERN Document Server

    Cao, Bin; Mark, Jon W

    2016-01-01

    This SpringerBrief examines the active cooperation between users of Cooperative Cognitive Radio Networking (CCRN), exploring the system model, enabling techniques, and performance. The brief provides a systematic study on active cooperation between primary users and secondary users, i.e., (CCRN), followed by the discussions on research issues and challenges in designing spectrum-energy efficient CCRN. As an effort to shed light on the design of spectrum-energy efficient CCRN, they model the CCRN based on orthogonal modulation and orthogonally dual-polarized antenna (ODPA). The resource allocation issues are detailed with respect to both models, in terms of problem formulation, solution approach, and numerical results. Finally, the optimal communication strategies for both primary and secondary users to achieve spectrum-energy efficient CCRN are analyzed.

  8. DEFINE: A Service-Oriented Dynamically Enabling Function Model

    Directory of Open Access Journals (Sweden)

    Tan Wei-Yi

    2017-01-01

    In this paper, we introduce an innovative Dynamically Enable Function In Network Equipment (DEFINE to allow tenant get the network service quickly. First, DEFINE decouples an application into different functional components, and connects these function components in a reconfigurable method. Second, DEFINE provides a programmable interface to the third party, who can develop their own processing modules according to their own needs. To verify the effectiveness of this model, we set up an evaluating network with a FPGA-based OpenFlow switch prototype, and deployed several applications on it. Our results show that DEFINE has excellent flexibility and performance.

  9. [How to fit and interpret multilevel models using SPSS].

    Science.gov (United States)

    Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael

    2007-05-01

    Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.

  10. Alternative models for the interpretation of aeromagnetic data in ...

    African Journals Online (AJOL)

    ... half-width of magnetic anomalies and are therefore valuable for depth determination. The four interpretational models have been employed to analyse aeromagnetic data from crystalline basement and sedimentary areas of Nigeria. Global Journal of Pure and Applied Sciences Volume , No 1 January (2001) pp. 111-116

  11. Development of interpretation models for PFN uranium log analysis

    International Nuclear Information System (INIS)

    Barnard, R.W.

    1980-11-01

    This report presents the models for interpretation of borehole logs for the PFN (Prompt Fission Neutron) uranium logging system. Two models have been developed, the counts-ratio model and the counts/dieaway model. Both are empirically developed, but can be related to the theoretical bases for PFN analysis. The models try to correct for the effects of external factors (such as probe or formation parameters) in the calculation of uranium grade. The theoretical bases and calculational techniques for estimating uranium concentration from raw PFN data and other parameters are discussed. Examples and discussions of borehole logs are included

  12. Modeling Plume-Triggered, Melt-Enabled Lithospheric Delamination

    Science.gov (United States)

    Perry-Houts, J.; Humphreys, G.

    2015-12-01

    It has been suggested that arrival of the Yellowstone plume below North America triggered a lithospheric foundering event which aided the eruption of the Columbia River flood basalts. This hypothesis potentially accounts for some of the biggest mysteries related to the CRB's including their location as "off-track" plume volcanism; and the anomalous chemical signatures of the most voluminous units. The foundered lithosphere appears to be a remnant chunk of Farallon slab, which had been stranded beneath the Blue Mountains terrain since the accretion of Siletzia. If this is the case then the mechanisms by which this slab stayed metastable between Siletzia accretion and CRB time, and then so suddenly broke loose, is unclear. The addition of heat and mantle buoyancy supplied by the Yellowstone plume provides a clue, but the geodynamic process by which the slab was able to detach remains unclear.Efforts to model numerically the underlying processes behind delamination events have been gaining popularity. Typically, such models have relied on drastically weakened regions within the crust, or highly non-linear rheologies to enable initiation and propagation of lithosphere removal. Rather than impose such a weak region a priori, we investigated the role of mantle and crustal melt, generated by the addition of plume heat, as the source of such a rheologic boundary.We track melt generation and migration though geodynamic models using the Eulerian finite element code, ASPECT. Melt moves relative to the permeable, compacting, and viscously-deforming mantle using the approach of (Keller, et al. 2013) with the notable exception that ASPECT currently cannot model elasticity. Dike and sill emplacement is therefore still a work in progress. This work is still in the preliminary stages and results are yet inconclusive.

  13. Life course models: improving interpretation by consideration of total effects.

    Science.gov (United States)

    Green, Michael J; Popham, Frank

    2017-06-01

    Life course epidemiology has used models of accumulation and critical or sensitive periods to examine the importance of exposure timing in disease aetiology. These models are usually used to describe the direct effects of exposures over the life course. In comparison with consideration of direct effects only, we show how consideration of total effects improves interpretation of these models, giving clearer notions of when it will be most effective to intervene. We show how life course variation in the total effects depends on the magnitude of the direct effects and the stability of the exposure. We discuss interpretation in terms of total, direct and indirect effects and highlight the causal assumptions required for conclusions as to the most effective timing of interventions. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

  14. Interpretation of searches for supersymmetry with simplified models

    Energy Technology Data Exchange (ETDEWEB)

    Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Aguilo, E.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Pernicka, M.; Rabady, D.; Rahbaran, B.; Rohringer, C.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Waltenberger, W.; Wulz, C. -E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Luyckx, S.; Mucibello, L.; Ochesanu, S.; Roland, B.; Rougny, R.; Selvaggi, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D’Hondt, J.; Gonzalez Suarez, R.; Kalogeropoulos, A.; Maes, M.; Olbrechts, A.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Clerbaux, B.; De Lentdecker, G.; Dero, V.; Gay, A. P. R.; Hreus, T.; Léonard, A.; Marage, P. E.; Mohammadi, A.; Reis, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Adler, V.; Beernaert, K.; Cimmino, A.; Costantini, S.; Garcia, G.; Grunewald, M.; Klein, B.; Lellouch, J.; Marinov, A.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Walsh, S.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Bruno, G.; Castello, R.; Ceard, L.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; Pin, A.; Piotrzkowski, K.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Alves, G. A.; Correa Martins Junior, M.; Martins, T.; Pol, M. E.; Souza, M. H. G.; Aldá Júnior, W. L.; Carvalho, W.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Malek, M.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Soares Jorge, L.; Sznajder, A.; Vilela Pereira, A.; Anjos, T. S.; Bernardes, C. A.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Lagana, C.; Marinho, F.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Tcholakov, V.; Trayanov, R.; Vutova, M.; Dimitrov, A.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Tao, J.; Wang, J.; Wang, X.; Wang, Z.; Xiao, H.; Xu, M.; Zang, J.; Zhang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, Y.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Teng, H.; Wang, D.; Zhang, L.; Zou, W.; Avila, C.; Gomez, J. P.; Gomez Moreno, B.; Osorio Oliveros, A. F.; Sanabria, J. 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A.; Sonnenschein, L.; Steggemann, J.; Teyssier, D.; Thüer, S.; Weber, M.; Bontenackels, M.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Lingemann, J.; Nowack, A.; Perchalla, L.; Pooth, O.; Sauerland, P.; Stahl, A.; Aldaya Martin, M.; Behr, J.; Behrenhoff, W.; Behrens, U.; Bergholz, M.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Castro, E.; Costanza, F.; Dammann, D.; Diez Pardos, C.; Eckerlin, G.; Eckstein, D.; Flucke, G.; Geiser, A.; Glushkov, I.; Gunnellini, P.; Habib, S.; Hauk, J.; Hellwig, G.; Jung, H.; Kasemann, M.; Katsas, P.; Kleinwort, C.; Kluge, H.; Knutsson, A.; Krämer, M.; Krücker, D.; Kuznetsova, E.; Lange, W.; Leonard, J.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Marienfeld, M.; Melzer-Pellmann, I. -A.; Meyer, A. 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R.; Lobelle Pardo, P.; Martschei, D.; Mueller, S.; Müller, Th.; Niegel, M.; Nürnberg, A.; Oberst, O.; Oehler, A.; Ott, J.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Ratnikova, N.; Röcker, S.; Schilling, F. -P.; Schott, G.; Simonis, H. J.; Stober, F. M.; Troendle, D.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Zeise, M.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Kesisoglou, S.; Kyriakis, A.; Loukas, D.; Manolakos, I.; Markou, A.; Markou, C.; Ntomari, E.; Gouskos, L.; Mertzimekis, T. J.; Panagiotou, A.; Saoulidou, N.; Evangelou, I.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Patras, V.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Beni, N.; Czellar, S.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Karancsi, J.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Beri, S. B.; Bhatnagar, V.; Dhingra, N.; Gupta, R.; Kaur, M.; Mehta, M. Z.; Nishu, N.; Saini, L. K.; Sharma, A.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, V.; Shivpuri, R. K.; Banerjee, S.; Bhattacharya, S.; Dutta, S.; Gomber, B.; Jain, Sa.; Jain, Sh.; Khurana, R.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Dutta, D.; Kailas, S.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Aziz, T.; Ganguly, S.; Guchait, M.; Gurtu, A.; Maity, M.; Majumder, G.; Mazumdar, K.; Mohanty, G. B.; Parida, B.; Sudhakar, K.; Wickramage, N.; Banerjee, S.; Dugad, S.; Arfaei, H.; Bakhshiansohi, H.; Etesami, S. M.; Fahim, A.; Hashemi, M.; Hesari, H.; Jafari, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Paktinat Mehdiabadi, S.; Safarzadeh, B.; Zeinali, M.; Abbrescia, M.; Barbone, L.; Calabria, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Marangelli, B.; My, S.; Nuzzo, S.; Pacifico, N.; Pompili, A.; Pugliese, G.; Selvaggi, G.; Silvestris, L.; Singh, G.; Venditti, R.; Verwilligen, P.; Zito, G.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Meneghelli, M.; Montanari, A.; Navarria, F. L.; Odorici, F.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. 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T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Triossi, A.; Vanini, S.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Riccardi, C.; Torre, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Nappi, A.; Romeo, F.; Saha, A.; Santocchia, A.; Spiezia, A.; Taroni, S.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; D’Agnolo, R. T.; Dell’Orso, R.; Fiori, F.; Foà, L.; Giassi, A.; Kraan, A.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. 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S.; Kwon, E.; Lee, B.; Lee, J.; Lee, S.; Seo, H.; Yu, I.; Bilinskas, M. J.; Grigelionis, I.; Janulis, M.; Juodagalvis, A.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Lopez-Fernandez, R.; Martínez-Ortega, J.; Sanchez-Hernandez, A.; Villasenor-Cendejas, L. M.; Carrillo Moreno, S.; Vazquez Valencia, F.; Salazar Ibarguen, H. A.; Casimiro Linares, E.; Morelos Pineda, A.; Reyes-Santos, M. A.; Krofcheck, D.; Bell, A. J.; Butler, P. H.; Doesburg, R.; Reucroft, S.; Silverwood, H.; Ahmad, M.; Asghar, M. I.; Butt, J.; Hoorani, H. R.; Khalid, S.; Khan, W. A.; Khurshid, T.; Qazi, S.; Shah, M. A.; Shoaib, M.; Bialkowska, H.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Wrochna, G.; Zalewski, P.; Brona, G.; Bunkowski, K.; Cwiok, M.; Dominik, W.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Almeida, N.; Bargassa, P.; David, A.; Faccioli, P.; Ferreira Parracho, P. 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V.; Vinogradov, A.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Grishin, V.; Kachanov, V.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Djordjevic, M.; Ekmedzic, M.; Krpic, D.; Milosevic, J.; Aguilar-Benitez, M.; Alcaraz Maestre, J.; Arce, P.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Ferrando, A.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Merino, G.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Santaolalla, J.; Soares, M. S.; Willmott, C.; Albajar, C.; Codispoti, G.; de Trocóniz, J. F.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Lloret Iglesias, L.; Piedra Gomez, J.; Brochero Cifuentes, J. A.; Cabrillo, I. 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A.; D’Enterria, D.; Dabrowski, A.; De Roeck, A.; Di Guida, S.; Dobson, M.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Frisch, B.; Funk, W.; Georgiou, G.; Giffels, M.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Giunta, M.; Glege, F.; Gomez-Reino Garrido, R.; Govoni, P.; Gowdy, S.; Guida, R.; Gundacker, S.; Hammer, J.; Hansen, M.; Harris, P.; Hartl, C.; Harvey, J.; Hegner, B.; Hinzmann, A.; Innocente, V.; Janot, P.; Kaadze, K.; Karavakis, E.; Kousouris, K.; Lecoq, P.; Lee, Y. -J.; Lenzi, P.; Lourenço, C.; Magini, N.; Mäki, T.; Malberti, M.; Malgeri, L.; Mannelli, M.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moser, R.; Mozer, M. U.; Mulders, M.; Musella, P.; Nesvold, E.; Orsini, L.; Palencia Cortezon, E.; Perez, E.; Perrozzi, L.; Petrilli, A.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Polese, G.; Quertenmont, L.; Racz, A.; Reece, W.; Rodrigues Antunes, J.; Rolandi, G.; Rovelli, C.; Rovere, M.; Sakulin, H.; Santanastasio, F.; Schäfer, C.; Schwick, C.; Segoni, I.; Sekmen, S.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Tsirou, A.; Veres, G. I.; Vlimant, J. R.; Wöhri, H. K.; Worm, S. D.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Gabathuler, K.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; König, S.; Kotlinski, D.; Langenegger, U.; Meier, F.; Renker, D.; Rohe, T.; Bäni, L.; Bortignon, P.; Buchmann, M. A.; Casal, B.; Chanon, N.; Deisher, A.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Eugster, J.; Freudenreich, K.; Grab, C.; Hits, D.; Lecomte, P.; Lustermann, W.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Mohr, N.; Moortgat, F.; Nägeli, C.; Nef, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pape, L.; Pauss, F.; Peruzzi, M.; Ronga, F. J.; Rossini, M.; Sala, L.; Sanchez, A. K.; Starodumov, A.; Stieger, B.; Takahashi, M.; Tauscher, L.; Thea, A.; Theofilatos, K.; Treille, D.; Urscheler, C.; Wallny, R.; Weber, H. A.; Wehrli, L.; Amsler, C.; Chiochia, V.; De Visscher, S.; Favaro, C.; Ivova Rikova, M.; Kilminster, B.; Millan Mejias, B.; Otiougova, P.; Robmann, P.; Snoek, H.; Tupputi, S.; Verzetti, M.; Chang, Y. H.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Li, S. W.; Lin, W.; Lu, Y. J.; Singh, A. P.; Volpe, R.; Yu, S. S.; Bartalini, P.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Dietz, C.; Grundler, U.; Hou, W. -S.; Hsiung, Y.; Kao, K. Y.; Lei, Y. J.; Lu, R. -S.; Majumder, D.; Petrakou, E.; Shi, X.; Shiu, J. G.; Tzeng, Y. M.; Wan, X.; Wang, M.; Asavapibhop, B.; Srimanobhas, N.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Karaman, T.; Karapinar, G.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sogut, K.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, L. N.; Vergili, M.; Akin, I. V.; Aliev, T.; Bilin, B.; Bilmis, S.; Deniz, M.; Gamsizkan, H.; Guler, A. M.; Ocalan, K.; Ozpineci, A.; Serin, M.; Sever, R.; Surat, U. E.; Yalvac, M.; Yildirim, E.; Zeyrek, M.; Gülmez, E.; Isildak, B.; Kaya, M.; Kaya, O.; Ozkorucuklu, S.; Sonmez, N.; Cankocak, K.; Levchuk, L.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Frazier, R.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Kreczko, L.; Metson, S.; Newbold, D. M.; Nirunpong, K.; Poll, A.; Senkin, S.; Smith, V. J.; Williams, T.; Basso, L.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Jackson, J.; Kennedy, B. W.; Olaiya, E.; Petyt, D.; Radburn-Smith, B. C.; Shepherd-Themistocleous, C. H.; Tomalin, I. R.; Womersley, W. J.; Bainbridge, R.; Ball, G.; Beuselinck, R.; Buchmuller, O.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Ferguson, W.; Fulcher, J.; Futyan, D.; Gilbert, A.; Guneratne Bryer, A.; Hall, G.; Hatherell, Z.; Hays, J.; Iles, G.; Jarvis, M.; Karapostoli, G.; Lyons, L.; Magnan, A. -M.; Marrouche, J.; Mathias, B.; Nandi, R.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Pioppi, M.; Raymond, D. M.; Rogerson, S.; Rose, A.; Ryan, M. J.; Seez, C.; Sharp, P.; Sparrow, A.; Stoye, M.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Wakefield, S.; Wardle, N.; Whyntie, T.; Chadwick, M.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Hatakeyama, K.; Liu, H.; Scarborough, T.; Charaf, O.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Heister, A.; St. John, J.; Lawson, P.; Lazic, D.; Rohlf, J.; Sperka, D.; Sulak, L.; Alimena, J.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Jabeen, S.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Nguyen, D.; Segala, M.; Sinthuprasith, T.; Speer, T.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Dolen, J.; Erbacher, R.; Gardner, M.; Houtz, R.; Ko, W.; Kopecky, A.; Lander, R.; Mall, O.; Miceli, T.; Pellett, D.; Ricci-Tam, F.; Rutherford, B.; Searle, M.; Smith, J.; Squires, M.; Tripathi, M.; Vasquez Sierra, R.; Yohay, R.; Andreev, V.; Cline, D.; Cousins, R.; Duris, J.; Erhan, S.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Jarvis, C.; Rakness, G.; Schlein, P.; Traczyk, P.; Valuev, V.; Weber, M.; Babb, J.; Clare, R.; Dinardo, M. E.; Ellison, J.; Gary, J. W.; Giordano, F.; Hanson, G.; Liu, H.; Long, O. R.; Luthra, A.; Nguyen, H.; Paramesvaran, S.; Sturdy, J.; Sumowidagdo, S.; Wilken, R.; Wimpenny, S.; Andrews, W.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Evans, D.; Holzner, A.; Kelley, R.; Lebourgeois, M.; Letts, J.; Macneill, I.; Mangano, B.; Padhi, S.; Palmer, C.; Petrucciani, G.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Wasserbaech, S.; Würthwein, F.; Yagil, A.; Yoo, J.; Barge, D.; Bellan, R.; Campagnari, C.; D’Alfonso, M.; Danielson, T.; Flowers, K.; Geffert, P.; Golf, F.; Incandela, J.; Justus, C.; Kalavase, P.; Kovalskyi, D.; Krutelyov, V.; Lowette, S.; Magaña Villalba, R.; Mccoll, N.; Pavlunin, V.; Ribnik, J.; Richman, J.; Rossin, R.; Stuart, D.; To, W.; West, C.; Apresyan, A.; Bornheim, A.; Chen, Y.; Di Marco, E.; Duarte, J.; Gataullin, M.; Ma, Y.; Mott, A.; Newman, H. B.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Veverka, J.; Wilkinson, R.; Xie, S.; Yang, Y.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carroll, R.; Ferguson, T.; Iiyama, Y.; Jang, D. W.; Liu, Y. F.; Paulini, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Drell, B. R.; Ford, W. T.; Gaz, A.; Luiggi Lopez, E.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Eggert, N.; Gibbons, L. K.; Heltsley, B.; Hopkins, W.; Khukhunaishvili, A.; Kreis, B.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Vaughan, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Burkett, K.; Butler, J. N.; Chetluru, V.; Cheung, H. W. K.; Chlebana, F.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Green, D.; Gutsche, O.; Hanlon, J.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kunori, S.; Kwan, S.; Leonidopoulos, C.; Linacre, J.; Lincoln, D.; Lipton, R.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Newman-Holmes, C.; O’Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitmore, J.; Wu, W.; Yang, F.; Yun, J. C.; Acosta, D.; Avery, P.; Bourilkov, D.; Chen, M.; Cheng, T.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Dobur, D.; Drozdetskiy, A.; Field, R. D.; Fisher, M.; Fu, Y.; Furic, I. K.; Gartner, J.; Hugon, J.; Kim, B.; Konigsberg, J.; Korytov, A.; Kropivnitskaya, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Park, M.; Remington, R.; Rinkevicius, A.; Sellers, P.; Skhirtladze, N.; Snowball, M.; Yelton, J.; Zakaria, M.; Gaultney, V.; Hewamanage, S.; Lebolo, L. M.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Chen, J.; Diamond, B.; Gleyzer, S. V.; Haas, J.; Hagopian, S.; Hagopian, V.; Jenkins, M.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Dorney, B.; Hohlmann, M.; Kalakhety, H.; Vodopiyanov, I.; Yumiceva, F.; Adams, M. R.; Anghel, I. M.; Apanasevich, L.; Bai, Y.; Bazterra, V. E.; Betts, R. R.; Bucinskaite, I.; Callner, J.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Lacroix, F.; O’Brien, C.; Silkworth, C.; Strom, D.; Turner, P.; Varelas, N.; Akgun, U.; Albayrak, E. A.; Bilki, B.; Clarida, W.; Duru, F.; Griffiths, S.; Merlo, J. -P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Newsom, C. R.; Norbeck, E.; Onel, Y.; Ozok, F.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yetkin, T.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Giurgiu, G.; Gritsan, A. V.; Guo, Z. J.; Hu, G.; Maksimovic, P.; Swartz, M.; Whitbeck, A.; Baringer, P.; Bean, A.; Benelli, G.; Kenny, R. P.; Murray, M.; Noonan, D.; Sanders, S.; Stringer, R.; Tinti, G.; Wood, J. S.; Barfuss, A. F.; Bolton, T.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Shrestha, S.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kirn, M.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Temple, J.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Bauer, G.; Bendavid, J.; Busza, W.; Butz, E.; Cali, I. A.; Chan, M.; Dutta, V.; Gomez Ceballos, G.; Goncharov, M.; Kim, Y.; Klute, M.; Krajczar, K.; Levin, A.; Luckey, P. D.; Ma, T.; Nahn, S.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Rudolph, M.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Sung, K.; Velicanu, D.; Wenger, E. A.; Wolf, R.; Wyslouch, B.; Yang, M.; Yilmaz, Y.; Yoon, A. S.; Zanetti, M.; Zhukova, V.; Cooper, S. I.; Dahmes, B.; De Benedetti, A.; Franzoni, G.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Sasseville, M.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Cremaldi, L. M.; Kroeger, R.; Perera, L.; Rahmat, R.; Sanders, D. A.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Eads, M.; Keller, J.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Snow, G. R.; Godshalk, A.; Iashvili, I.; Jain, S.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Nash, D.; Orimoto, T.; Trocino, D.; Wood, D.; Zhang, J.; Anastassov, A.; Hahn, K. A.; Kubik, A.; Lusito, L.; Mucia, N.; Odell, N.; Ofierzynski, R. A.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Velasco, M.; Won, S.; Antonelli, L.; Berry, D.; Brinkerhoff, A.; Chan, K. M.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kolb, J.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Morse, D. M.; Pearson, T.; Planer, M.; Ruchti, R.; Slaunwhite, J.; Valls, N.; Wayne, M.; Wolf, M.; Bylsma, B.; Durkin, L. S.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Vuosalo, C.; Williams, G.; Winer, B. L.; Berry, E.; Elmer, P.; Halyo, V.; Hebda, P.; Hegeman, J.; Hunt, A.; Jindal, P.; Koay, S. A.; Lopes Pegna, D.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Raval, A.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Lopez, A.; Mendez, H.; Ramirez Vargas, J. E.; Alagoz, E.; Barnes, V. E.; Benedetti, D.; Bolla, G.; Bortoletto, D.; De Mattia, M.; Everett, A.; Hu, Z.; Jones, M.; Koybasi, O.; Kress, M.; Laasanen, A. T.; Leonardo, N.; Maroussov, V.; Merkel, P.; Miller, D. H.; Neumeister, N.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Vidal Marono, M.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Guragain, S.; Parashar, N.; Adair, A.; Akgun, B.; Boulahouache, C.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Chung, Y. S.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Miner, D. C.; Vishnevskiy, D.; Zielinski, M.; Bhatti, A.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Malik, S.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Rekovic, V.; Robles, J.; Rose, K.; Salur, S.; Schnetzer, S.; Seitz, C.; Somalwar, S.; Stone, R.; Thomas, S.; Walker, M.; Cerizza, G.; Hollingsworth, M.; Spanier, S.; Yang, Z. C.; York, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Safonov, A.; Sakuma, T.; Sengupta, S.; Suarez, I.; Tatarinov, A.; Toback, D.; Akchurin, N.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Jeong, C.; Kovitanggoon, K.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Florez, C.; Greene, S.; Gurrola, A.; Johns, W.; Kurt, P.; Maguire, C.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Balazs, M.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Lin, C.; Neu, C.; Wood, J.; Gollapinni, S.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sakharov, A.; Anderson, M.; Belknap, D. A.; Borrello, L.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Friis, E.; Gray, L.; Grogg, K. S.; Grothe, M.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Klukas, J.; Lanaro, A.; Lazaridis, C.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Palmonari, F.; Pierro, G. A.; Ross, I.; Savin, A.; Smith, W. H.; Swanson, J.

    2013-09-01

    The results of searches for supersymmetry by the CMS experiment are interpreted in the framework of simplified models. The results are based on data corresponding to an integrated luminosity of 4.73 to 4.98 inverse femtobarns. The data were collected at the LHC in proton-proton collisions at a center-of-mass energy of 7 TeV. This paper describes the method of interpretation and provides upper limits on the product of the production cross section and branching fraction as a function of new particle masses for a number of simplified models. These limits and the corresponding experimental acceptance calculations can be used to constrain other theoretical models and to compare different supersymmetry-inspired analyses.

  15. Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity.

    Science.gov (United States)

    Webb, Samuel J; Hanser, Thierry; Howlin, Brendan; Krause, Paul; Vessey, Jonathan D

    2014-03-25

    A new algorithm has been developed to enable the interpretation of black box models. The developed algorithm is agnostic to learning algorithm and open to all structural based descriptors such as fragments, keys and hashed fingerprints. The algorithm has provided meaningful interpretation of Ames mutagenicity predictions from both random forest and support vector machine models built on a variety of structural fingerprints.A fragmentation algorithm is utilised to investigate the model's behaviour on specific substructures present in the query. An output is formulated summarising causes of activation and deactivation. The algorithm is able to identify multiple causes of activation or deactivation in addition to identifying localised deactivations where the prediction for the query is active overall. No loss in performance is seen as there is no change in the prediction; the interpretation is produced directly on the model's behaviour for the specific query. Models have been built using multiple learning algorithms including support vector machine and random forest. The models were built on public Ames mutagenicity data and a variety of fingerprint descriptors were used. These models produced a good performance in both internal and external validation with accuracies around 82%. The models were used to evaluate the interpretation algorithm. Interpretation was revealed that links closely with understood mechanisms for Ames mutagenicity. This methodology allows for a greater utilisation of the predictions made by black box models and can expedite further study based on the output for a (quantitative) structure activity model. Additionally the algorithm could be utilised for chemical dataset investigation and knowledge extraction/human SAR development.

  16. Interpreting Marginal Effects in the Multinomial Logit Model

    DEFF Research Database (Denmark)

    Wulff, Jesper

    2014-01-01

    This paper presents the challenges when researchers interpret results about relationships between variables from discrete choice models with multiple outcomes. The recommended approach is demonstrated by testing predictions from transaction cost theory on a sample of 246 Scandinavian firms...... with a substantial increase in the probability of entering a foreign market using a joint venture, while increases in the unpredictability in the host country environment are associated with a lower probability of wholly owned subsidiaries and a higher probability of exporting entries....

  17. Cranking model interpretation of weakly coupled bands in Hg isotopes

    International Nuclear Information System (INIS)

    Guttormsen, M.; Huebel, H.

    1982-01-01

    The positive-parity yrast states of the transitional sup(189-198)Hg isotopes are interpreted within the Bengtsson and Frauendorf version of the cranking model. The very sharp backbendings can be explained by small interaction matrix elements between the ground and s-bands. The experimentally observed large aligned angular momenta and the low band-crossing frequencies are well reproduced in the calculations. (orig.)

  18. An IT-enabled supply chain model: a simulation study

    Science.gov (United States)

    Cannella, Salvatore; Framinan, Jose M.; Barbosa-Póvoa, Ana

    2014-11-01

    During the last decades, supply chain collaboration practices and the underlying enabling technologies have evolved from the classical electronic data interchange (EDI) approach to a web-based and radio frequency identification (RFID)-enabled collaboration. In this field, most of the literature has focused on the study of optimal parameters for reducing the total cost of suppliers, by adopting operational research (OR) techniques. Herein we are interested in showing that the considered information technology (IT)-enabled structure is resilient, that is, it works well across a reasonably broad range of parameter settings. By adopting a methodological approach based on system dynamics, we study a multi-tier collaborative supply chain. Results show that the IT-enabled supply chain improves operational performance and customer service level. Nonetheless, benefits for geographically dispersed networks are of minor entity.

  19. Creating Data and Modeling Enabled Hydrology Instruction Using Collaborative Approach

    Science.gov (United States)

    Merwade, V.; Rajib, A.; Ruddell, B. L.; Fox, S.

    2017-12-01

    Hydrology instruction typically involves teaching of the hydrologic cycle and the processes associated with it such as precipitation, evapotranspiration, infiltration, runoff generation and hydrograph analysis. With the availability of observed and remotely sensed data related to many hydrologic fluxes, there is an opportunity to use these data for place based learning in hydrology classrooms. However, it is not always easy and possible for an instructor to complement an existing hydrology course with new material that requires both the time and technical expertise, which the instructor may not have. The work presented here describes an effort where students create the data and modeling driven instruction material as a part of their class assignment for a hydrology course at Purdue University. The data driven hydrology education project within Science Education Resources Center (SERC) is used as a platform to publish and share the instruction material so it can be used by future students in the same course or any other course anywhere in the world. Students in the class were divided into groups, and each group was assigned a topic such as precipitation, evapotranspiration, streamflow, flow duration curve and frequency analysis. Each student in the group was then asked to get data and do some analysis for an area with specific landuse characteristic such as urban, rural and agricultural. The student contribution were then organized into learning units such that someone can do a flow duration curve analysis or flood frequency analysis to see how it changes for rural area versus urban area. The hydrology education project within SERC cyberinfrastructure enables any other instructor to adopt this material as is or through modification to suit his/her place based instruction needs.

  20. New Cosmological Model and Its Implications on Observational Data Interpretation

    Directory of Open Access Journals (Sweden)

    Vlahovic Branislav

    2013-09-01

    Full Text Available The paradigm of ΛCDM cosmology works impressively well and with the concept of inflation it explains the universe after the time of decoupling. However there are still a few concerns; after much effort there is no detection of dark matter and there are significant problems in the theoretical description of dark energy. We will consider a variant of the cosmological spherical shell model, within FRW formalism and will compare it with the standard ΛCDM model. We will show that our new topological model satisfies cosmological principles and is consistent with all observable data, but that it may require new interpretation for some data. Considered will be constraints imposed on the model, as for instance the range for the size and allowed thickness of the shell, by the supernovae luminosity distance and CMB data. In this model propagation of the light is confined along the shell, which has as a consequence that observed CMB originated from one point or a limited space region. It allows to interpret the uniformity of the CMB without inflation scenario. In addition this removes any constraints on the uniformity of the universe at the early stage and opens a possibility that the universe was not uniform and that creation of galaxies and large structures is due to the inhomogeneities that originated in the Big Bang.

  1. Interpreting parameters in the logistic regression model with random effects

    DEFF Research Database (Denmark)

    Larsen, Klaus; Petersen, Jørgen Holm; Budtz-Jørgensen, Esben

    2000-01-01

    interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects......interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects...

  2. Stability of the matrix model in operator interpretation

    Directory of Open Access Journals (Sweden)

    Katsuta Sakai

    2017-12-01

    Full Text Available The IIB matrix model is one of the candidates for nonperturbative formulation of string theory, and it is believed that the model contains gravitational degrees of freedom in some manner. In some preceding works, it was proposed that the matrix model describes the curved space where the matrices represent differential operators that are defined on a principal bundle. In this paper, we study the dynamics of the model in this interpretation, and point out the necessity of the principal bundle from the viewpoint of the stability and diffeomorphism invariance. We also compute the one-loop correction which yields a mass term for each field due to the principal bundle. We find that the stability is not violated.

  3. Cognitive model of image interpretation for artificial intelligence applications

    International Nuclear Information System (INIS)

    Raju, S.

    1988-01-01

    A cognitive model of imaging diagnosis was devised to aid in the development of expert systems that assist in the interpretation of diagnostic images. In this cognitive model, a small set of observations that are strongly predictive of a particular diagnosis lead to a search for other observations that would support this diagnosis but are not necessarily specific for it. Then a set of alternative diagnoses is considered. This is followed by a search for observations that might allow differentiation of the primary diagnostic consideration from the alternatives. The production rules needed to implement this model can be classified into three major categories, each of which have certain general characteristics. Knowledge of these characteristics simplifies the development of these expert systems

  4. LIME: 3D visualisation and interpretation of virtual geoscience models

    Science.gov (United States)

    Buckley, Simon; Ringdal, Kari; Dolva, Benjamin; Naumann, Nicole; Kurz, Tobias

    2017-04-01

    Three-dimensional and photorealistic acquisition of surface topography, using methods such as laser scanning and photogrammetry, has become widespread across the geosciences over the last decade. With recent innovations in photogrammetric processing software, robust and automated data capture hardware, and novel sensor platforms, including unmanned aerial vehicles, obtaining 3D representations of exposed topography has never been easier. In addition to 3D datasets, fusion of surface geometry with imaging sensors, such as multi/hyperspectral, thermal and ground-based InSAR, and geophysical methods, create novel and highly visual datasets that provide a fundamental spatial framework to address open geoscience research questions. Although data capture and processing routines are becoming well-established and widely reported in the scientific literature, challenges remain related to the analysis, co-visualisation and presentation of 3D photorealistic models, especially for new users (e.g. students and scientists new to geomatics methods). Interpretation and measurement is essential for quantitative analysis of 3D datasets, and qualitative methods are valuable for presentation purposes, for planning and in education. Motivated by this background, the current contribution presents LIME, a lightweight and high performance 3D software for interpreting and co-visualising 3D models and related image data in geoscience applications. The software focuses on novel data integration and visualisation of 3D topography with image sources such as hyperspectral imagery, logs and interpretation panels, geophysical datasets and georeferenced maps and images. High quality visual output can be generated for dissemination purposes, to aid researchers with communication of their research results. The background of the software is described and case studies from outcrop geology, in hyperspectral mineral mapping and geophysical-geospatial data integration are used to showcase the novel

  5. GeoPro: Technology to Enable Scientific Modeling

    International Nuclear Information System (INIS)

    C. Juan

    2004-01-01

    Development of the ground-water flow model for the Death Valley Regional Groundwater Flow System (DVRFS) required integration of numerous supporting hydrogeologic investigations. The results from recharge, discharge, hydraulic properties, water level, pumping, model boundaries, and geologic studies were integrated to develop the required conceptual and 3-D framework models, and the flow model itself. To support the complex modeling process and the needs of the multidisciplinary DVRFS team, a hardware and software system called GeoPro (Geoscience Knowledge Integration Protocol) was developed. A primary function of GeoPro is to manage the large volume of disparate data compiled for the 100,000-square-kilometer area of southern Nevada and California. The data are primarily from previous investigations and regional flow models developed for the Nevada Test Site and Yucca Mountain projects. GeoPro utilizes relational database technology (Microsoft SQL Server(trademark)) to store and manage these tabular point data, groundwater flow model ASCII data, 3-D hydrogeologic framework data, 2-D and 2.5-D GIS data, and text documents. Data management consists of versioning, tracking, and reporting data changes as multiple users access the centralized database. GeoPro also supports the modeling process by automating the routine data transformations required to integrate project software. This automation is also crucial to streamlining pre- and post-processing of model data during model calibration. Another function of GeoPro is to facilitate the dissemination and use of the model data and results through web-based documents by linking and allowing access to the underlying database and analysis tools. The intent is to convey to end-users the complex flow model product in a manner that is simple, flexible, and relevant to their needs. GeoPro is evolving from a prototype system to a production-level product. Currently the DVRFS pre- and post-processing modeling tools are being re

  6. Interpretation of Quantitative Structure-Activity Relationship Models: Past, Present, and Future.

    Science.gov (United States)

    Polishchuk, Pavel

    2017-11-27

    This paper is an overview of the most significant and impactful interpretation approaches of quantitative structure-activity relationship (QSAR) models, their development, and application. The evolution of the interpretation paradigm from "model → descriptors → (structure)" to "model → structure" is indicated. The latter makes all models interpretable regardless of machine learning methods or descriptors used for modeling. This opens wide prospects for application of corresponding interpretation approaches to retrieve structure-property relationships captured by any models. Issues of separate approaches are discussed as well as general issues and prospects of QSAR model interpretation.

  7. Enabling Business Model Change: Evidence from High-Technology Firms

    Directory of Open Access Journals (Sweden)

    Christiana Müller

    2015-01-01

    Full Text Available Companies today face volatie environments, short product life cycles, and changing customer requirements, which is especially the case in high-technology filds. In such environments, concentratig only on technological and product innovatins is not suffient to gain competiie advantages. Instead, companies need innovatie business models in order to stand out from their competiors. To successfully change business models, companies require appropriate competencies. Thus, the objectie of this research is to identiy how companies can prepare their business model(s to counteract environmental changes flxibly. With the aid of the chosen exploratory, qualitatie research design, we investiate companies operatig in hightechnology branches. In total, 20 companies partiipated in our study. The interviews were conducted with CEOs, vice-presidents, product managers or other managers responsible for business model developments. The research revealed that companies can prepare the business model and its elements ex ante through developing capabilitis in order to raise the flxibility of the business model. These capabilitis have to be developed with regard to several internal and external issues driving these changes.

  8. ARCHITECTURES AND ALGORITHMS FOR COGNITIVE NETWORKS ENABLED BY QUALITATIVE MODELS

    DEFF Research Database (Denmark)

    Balamuralidhar, P.

    2013-01-01

    Complexity of communication networks is ever increasing and getting complicated by their heterogeneity and dynamism. Traditional techniques are facing challenges in network performance management. Cognitive networking is an emerging paradigm to make networks more intelligent, thereby overcoming...... of the cognitive engine that incorporates a context space based information structure to its knowledge model. I propose a set of guiding principles behind a cognitive system to be autonomic and use them with additional requirements to build a detailed architecture for the cognitive engine. I define a context space...... structure integrating various information structures that are required for the knowledge model. Use graphical models towards representing and reasoning about context space is a direction followed here. Specifically I analyze the framework of qualitative models for their suitability to represent the dynamic...

  9. A Customizable Dashboarding System for Watershed Model Interpretation

    Science.gov (United States)

    Easton, Z. M.; Collick, A.; Wagena, M. B.; Sommerlot, A.; Fuka, D.

    2017-12-01

    Stakeholders, including policymakers, agricultural water managers, and small farm managers, can benefit from the outputs of commonly run watershed models. However, the information that each stakeholder needs is be different. While policy makers are often interested in the broader effects that small farm management may have on a watershed during extreme events or over long periods, farmers are often interested in field specific effects at daily or seasonal period. To provide stakeholders with the ability to analyze and interpret data from large scale watershed models, we have developed a framework that can support custom exploration of the large datasets produced. For the volume of data produced by these models, SQL-based data queries are not efficient; thus, we employ a "Not Only SQL" (NO-SQL) query language, which allows data to scale in both quantity and query volumes. We demonstrate a stakeholder customizable Dashboarding system that allows stakeholders to create custom `dashboards' to summarize model output specific to their needs. Dashboarding is a dynamic and purpose-based visual interface needed to display one-to-many database linkages so that the information can be presented for a single time period or dynamically monitored over time and allows a user to quickly define focus areas of interest for their analysis. We utilize a single watershed model that is run four times daily with a combined set of climate projections, which are then indexed, and added to an ElasticSearch datastore. ElasticSearch is a NO-SQL search engine built on top of Apache Lucene, a free and open-source information retrieval software library. Aligned with the ElasticSearch project is the open source visualization and analysis system, Kibana, which we utilize for custom stakeholder dashboarding. The dashboards create a visualization of the stakeholder selected analysis and can be extended to recommend robust strategies to support decision-making.

  10. The shared circuits model (SCM): how control, mirroring, and simulation can enable imitation, deliberation, and mindreading.

    Science.gov (United States)

    Hurley, Susan

    2008-02-01

    Imitation, deliberation, and mindreading are characteristically human sociocognitive skills. Research on imitation and its role in social cognition is flourishing across various disciplines. Imitation is surveyed in this target article under headings of behavior, subpersonal mechanisms, and functions of imitation. A model is then advanced within which many of the developments surveyed can be located and explained. The shared circuits model (SCM) explains how imitation, deliberation, and mindreading can be enabled by subpersonal mechanisms of control, mirroring, and simulation. It is cast at a middle, functional level of description, that is, between the level of neural implementation and the level of conscious perceptions and intentional actions. The SCM connects shared informational dynamics for perception and action with shared informational dynamics for self and other, while also showing how the action/perception, self/other, and actual/possible distinctions can be overlaid on these shared informational dynamics. It avoids the common conception of perception and action as separate and peripheral to central cognition. Rather, it contributes to the situated cognition movement by showing how mechanisms for perceiving action can be built on those for active perception.;>;>The SCM is developed heuristically, in five layers that can be combined in various ways to frame specific ontogenetic or phylogenetic hypotheses. The starting point is dynamic online motor control, whereby an organism is closely attuned to its embedding environment through sensorimotor feedback. Onto this are layered functions of prediction and simulation of feedback, mirroring, simulation of mirroring, monitored inhibition of motor output, and monitored simulation of input. Finally, monitored simulation of input specifying possible actions plus inhibited mirroring of such possible actions can generate information about the possible as opposed to actual instrumental actions of others, and the

  11. Healthcare waste management: an interpretive structural modeling approach.

    Science.gov (United States)

    Thakur, Vikas; Anbanandam, Ramesh

    2016-06-13

    Purpose - The World Health Organization identified infectious healthcare waste as a threat to the environment and human health. India's current medical waste management system has limitations, which lead to ineffective and inefficient waste handling practices. Hence, the purpose of this paper is to: first, identify the important barriers that hinder India's healthcare waste management (HCWM) systems; second, classify operational, tactical and strategical issues to discuss the managerial implications at different management levels; and third, define all barriers into four quadrants depending upon their driving and dependence power. Design/methodology/approach - India's HCWM system barriers were identified through the literature, field surveys and brainstorming sessions. Interrelationships among all the barriers were analyzed using interpretive structural modeling (ISM). Fuzzy-Matrice d'Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis was used to classify HCWM barriers into four groups. Findings - In total, 25 HCWM system barriers were identified and placed in 12 different ISM model hierarchy levels. Fuzzy-MICMAC analysis placed eight barriers in the second quadrant, five in third and 12 in fourth quadrant to define their relative ISM model importance. Research limitations/implications - The study's main limitation is that all the barriers were identified through a field survey and barnstorming sessions conducted only in Uttarakhand, Northern State, India. The problems in implementing HCWM practices may differ with the region, hence, the current study needs to be replicated in different Indian states to define the waste disposal strategies for hospitals. Practical implications - The model will help hospital managers and Pollution Control Boards, to plan their resources accordingly and make policies, targeting key performance areas. Originality/value - The study is the first attempt to identify India's HCWM system barriers and prioritize

  12. Interpretation of medical images by model guided analysis

    International Nuclear Information System (INIS)

    Karssemeijer, N.

    1989-01-01

    Progress in the development of digital pictorial information systems stimulates a growing interest in the use of image analysis techniques in medicine. Especially when precise quantitative information is required the use of fast and reproducable computer analysis may be more appropriate than relying on visual judgement only. Such quantitative information can be valuable, for instance, in diagnostics or in irradiation therapy planning. As medical images are mostly recorded in a prescribed way, human anatomy guarantees a common image structure for each particular type of exam. In this thesis it is investigated how to make use of this a priori knowledge to guide image analysis. For that purpose models are developed which are suited to capture common image structure. The first part of this study is devoted to an analysis of nuclear medicine images of myocardial perfusion. In ch. 2 a model of these images is designed in order to represent characteristic image properties. It is shown that for these relatively simple images a compact symbolic description can be achieved, without significant loss of diagnostically importance of several image properties. Possibilities for automatic interpretation of more complex images is investigated in the following chapters. The central topic is segmentation of organs. Two methods are proposed and tested on a set of abdominal X-ray CT scans. Ch. 3 describes a serial approach based on a semantic network and the use of search areas. Relational constraints are used to guide the image processing and to classify detected image segments. In teh ch.'s 4 and 5 a more general parallel approach is utilized, based on a markov random field image model. A stochastic model used to represent prior knowledge about the spatial arrangement of organs is implemented as an external field. (author). 66 refs.; 27 figs.; 6 tabs

  13. Computer Modeling of Carbon Metabolism Enables Biofuel Engineering (Fact Sheet)

    Energy Technology Data Exchange (ETDEWEB)

    2011-09-01

    In an effort to reduce the cost of biofuels, the National Renewable Energy Laboratory (NREL) has merged biochemistry with modern computing and mathematics. The result is a model of carbon metabolism that will help researchers understand and engineer the process of photosynthesis for optimal biofuel production.

  14. A 3D modelling tool to support interdisciplinary interpretation of GravMag fields and Gradiometry

    Science.gov (United States)

    Götze, Hans-Jürgen; Schmidt, Sabine; Plonka, Christian

    2013-04-01

    It is well known that 3D gravity and magnetic modelling appreciably improves the results of most of the depth imaging projects. Typical areas where gravity and magnetic modelling has been successfully used are sub-salt and sub-basalt. Modern geophysical interpretation requires an interdisciplinary approach and software capable of handling multiple inhomogeneous data like seismic, FTG gravity, magnetic and magnetotelluric. We introduce the IGMAS+ ("Interactive Geophysical Modelling Application System") geo-modelling software for realistic 3D FTG and magnetic modelling. The software is also capable for grid computing and allows extreme fast distributed calculations on normal hardware such as a network of PCs even of very large 3D underground models. The analytical solution of the volume integral for the gravity and magnetic effect of a homogeneous body is based on the reduction of the volume integral to an integral over the bounding polyhedrons). An approach is described to integrate constraining data into the interactive modeling process by means of modern visualization and combination of independent data. We demonstrate stress calculation and modeling of variable density/susceptibility structures. This visual combination of 2- and 3-D models (e.g. from seismic reflection or refraction surveys) enables a quantitative comparison and adjustment by the interpreter, and results in a model comprising as much independently derived information as possible. As an example we show results from the Central Andes. Both gravity and geoid of the Southern Central Andes and their eastern foreland between 20 deg. to 30 deg. S was investigated with regard to the isostatic state, the crustal density structure of the orogeny and the rigidity of the Andean Lithosphere. Estimates of stress and GPE (gravitational potential energy) at the western South American margin have been derived from an existing 3D density model. Here, sensitivity studies of gravity and gravity gradients indicate

  15. Models for Interpreting Tungsten Isotope Anomalies in the Earth's Crust

    Science.gov (United States)

    Humayun, M.; Brandon, A. D.; Righter, K.

    2012-12-01

    There have been several reports of positive tungsten isotope anomalies of about +15 ppm in rocks from Nuvvuagittuq (4.3 Ga), Isua (3.8 Ga) and Kostomuksha (2.8 Ga) that challenge models of differentiation and mantle mixing. Here, we employ constraints from experimental partitioning of W between metal and silicate, and from partial melting models, to evaluate the production and preservation of these W isotope anomalies in the Earth's earliest crust. We will also provide a revised interpretation of the Kostomuksha W isotope anomalies based on flow differentiation and metamorphism of komatiites. Two sets of models are produced. Model Set 1: Because D(metal-silicate) for W diminishes with increasing depth, the deep mantle has a higher W abundance, and a lower Hf/W ratio and consequently evolves a negative anomaly in W while the upper mantle evolves a complementary positive anomaly. Subsequent solid-state convection (4.55-2.8 Ga) mixes away the complementary W isotope anomalies to yield the modern mantle null value. This set of models predicts that the complementary negative anomalies in W should eventually be discovered in ancient magmatic rocks of deep mantle origin such as komatiites. Model Set 2: Tungsten is significantly more incompatible (like U, Th and Ba) than Hf, the latter being similar in compatibility to Sm. Our results show that extraction of low-degree partial melts (crust would result in negative anomalies in later plume lavas, while partitioning of W into an enriched "hidden reservoir" would not. Nd isotope anomalies indicate a melting event around 35-75 Ma after solar system formation, the upper end of which is consistent with our models of Hf/W fractionation, that also yield a depleted mantle composition consistent with DMM. Production of the anomalies is accompanied by the need to preserve the anomalies. We argue that the most effective means of preserving the W isotope anomalies is by crustal storage, and we hypothesize that W is efficiently recycled

  16. Domain-specific modeling enabling full code generation

    CERN Document Server

    Kelly, Steven

    2007-01-01

    Domain-Specific Modeling (DSM) is the latest approach tosoftware development, promising to greatly increase the speed andease of software creation. Early adopters of DSM have been enjoyingproductivity increases of 500–1000% in production for over adecade. This book introduces DSM and offers examples from variousfields to illustrate to experienced developers how DSM can improvesoftware development in their teams. Two authorities in the field explain what DSM is, why it works,and how to successfully create and use a DSM solution to improveproductivity and quality. Divided into four parts, the book covers:background and motivation; fundamentals; in-depth examples; andcreating DSM solutions. There is an emphasis throughout the book onpractical guidelines for implementing DSM, including how toidentify the nece sary language constructs, how to generate fullcode from models, and how to provide tool support for a new DSMlanguage. The example cases described in the book are available thebook's Website, www.dsmbook....

  17. Exploring Business Models for NFC Enabled Mobile Payment Services

    OpenAIRE

    Chae, Sang-Un; hedman, Jonas

    2013-01-01

    Over the past few years, mobile payments have been present like a storm on the horizon. They have generated a lot of attention; yet have not reached wide adoption. Issues such as the complexity of the mobile payment ecosystem and the lack of sustainable business models have been accounted for the slow market penetration. With the rise of new technologies such as NFC, the mobile payment sphere experiences a new height of talk, which materialized in a second wave of companies enteri...

  18. Enabling analytical and Modeling Tools for Enhanced Disease Surveillance

    Energy Technology Data Exchange (ETDEWEB)

    Dawn K. Manley

    2003-04-01

    Early detection, identification, and warning are essential to minimize casualties from a biological attack. For covert attacks, sick people are likely to provide the first indication of an attack. An enhanced medical surveillance system that synthesizes distributed health indicator information and rapidly analyzes the information can dramatically increase the number of lives saved. Current surveillance methods to detect both biological attacks and natural outbreaks are hindered by factors such as distributed ownership of information, incompatible data storage and analysis programs, and patient privacy concerns. Moreover, because data are not widely shared, few data mining algorithms have been tested on and applied to diverse health indicator data. This project addressed both integration of multiple data sources and development and integration of analytical tools for rapid detection of disease outbreaks. As a first prototype, we developed an application to query and display distributed patient records. This application incorporated need-to-know access control and incorporated data from standard commercial databases. We developed and tested two different algorithms for outbreak recognition. The first is a pattern recognition technique that searches for space-time data clusters that may signal a disease outbreak. The second is a genetic algorithm to design and train neural networks (GANN) that we applied toward disease forecasting. We tested these algorithms against influenza, respiratory illness, and Dengue Fever data. Through this LDRD in combination with other internal funding, we delivered a distributed simulation capability to synthesize disparate information and models for earlier recognition and improved decision-making in the event of a biological attack. The architecture incorporates user feedback and control so that a user's decision inputs can impact the scenario outcome as well as integrated security and role-based access-control for communicating

  19. Model sparsity and brain pattern interpretation of classification models in neuroimaging

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Madsen, Kristoffer Hougaard; Churchill, Nathan W

    2012-01-01

    Interest is increasing in applying discriminative multivariate analysis techniques to the analysis of functional neuroimaging data. Model interpretation is of great importance in the neuroimaging context, and is conventionally based on a ‘brain map’ derived from the classification model. In this ...

  20. The understanding and interpretation of innovative technology-enabled multidimensional physical activity feedback in patients at risk of future chronic disease.

    Directory of Open Access Journals (Sweden)

    Max J Western

    Full Text Available Innovative physical activity monitoring technology can be used to depict rich visual feedback that encompasses the various aspects of physical activity known to be important for health. However, it is unknown whether patients who are at risk of chronic disease would understand such sophisticated personalised feedback or whether they would find it useful and motivating. The purpose of the present study was to determine whether technology-enabled multidimensional physical activity graphics and visualisations are comprehensible and usable for patients at risk of chronic disease.We developed several iterations of graphics depicting minute-by-minute activity patterns and integrated physical activity health targets. Subsequently, patients at moderate/high risk of chronic disease (n=29 and healthcare practitioners (n=15 from South West England underwent full 7-days activity monitoring followed by individual semi-structured interviews in which they were asked to comment on their own personalised visual feedback Framework analysis was used to gauge their interpretation and of personalised feedback, graphics and visualisations.We identified two main components focussing on (a the interpretation of feedback designs and data and (b the impact of personalised visual physical activity feedback on facilitation of health behaviour change. Participants demonstrated a clear ability to understand the sophisticated personal information plus an enhanced physical activity knowledge. They reported that receiving multidimensional feedback was motivating and could be usefully applied to facilitate their efforts in becoming more physically active.Multidimensional physical activity feedback can be made comprehensible, informative and motivational by using appropriate graphics and visualisations. There is an opportunity to exploit the full potential created by technological innovation and provide sophisticated personalised physical activity feedback as an adjunct to

  1. The understanding and interpretation of innovative technology-enabled multidimensional physical activity feedback in patients at risk of future chronic disease.

    Science.gov (United States)

    Western, Max J; Peacock, Oliver J; Stathi, Afroditi; Thompson, Dylan

    2015-01-01

    Innovative physical activity monitoring technology can be used to depict rich visual feedback that encompasses the various aspects of physical activity known to be important for health. However, it is unknown whether patients who are at risk of chronic disease would understand such sophisticated personalised feedback or whether they would find it useful and motivating. The purpose of the present study was to determine whether technology-enabled multidimensional physical activity graphics and visualisations are comprehensible and usable for patients at risk of chronic disease. We developed several iterations of graphics depicting minute-by-minute activity patterns and integrated physical activity health targets. Subsequently, patients at moderate/high risk of chronic disease (n=29) and healthcare practitioners (n=15) from South West England underwent full 7-days activity monitoring followed by individual semi-structured interviews in which they were asked to comment on their own personalised visual feedback Framework analysis was used to gauge their interpretation and of personalised feedback, graphics and visualisations. We identified two main components focussing on (a) the interpretation of feedback designs and data and (b) the impact of personalised visual physical activity feedback on facilitation of health behaviour change. Participants demonstrated a clear ability to understand the sophisticated personal information plus an enhanced physical activity knowledge. They reported that receiving multidimensional feedback was motivating and could be usefully applied to facilitate their efforts in becoming more physically active. Multidimensional physical activity feedback can be made comprehensible, informative and motivational by using appropriate graphics and visualisations. There is an opportunity to exploit the full potential created by technological innovation and provide sophisticated personalised physical activity feedback as an adjunct to support behaviour

  2. Quality Systems. A Thermodynamics-Related Interpretive Model

    Directory of Open Access Journals (Sweden)

    Stefano A. Lollai

    2017-08-01

    Full Text Available In the present paper, a Quality Systems Theory is presented. Certifiable Quality Systems are treated and interpreted in accordance with a Thermodynamics-based approach. Analysis is also conducted on the relationship between Quality Management Systems (QMSs and systems theories. A measure of entropy is proposed for QMSs, including a virtual document entropy and an entropy linked to processes and organisation. QMSs are also interpreted in light of Cybernetics, and interrelations between Information Theory and quality are also highlighted. A measure for the information content of quality documents is proposed. Such parameters can be used as adequacy indices for QMSs. From the discussed approach, suggestions for organising QMSs are also derived. Further interpretive thermodynamic-based criteria for QMSs are also proposed. The work represents the first attempt to treat quality organisational systems according to a thermodynamics-related approach. At this stage, no data are available to compare statements in the paper.

  3. Software Infrastructure to Enable Modeling & Simulation as a Service (M&SaaS), Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR Phase 2 project will produce a software service infrastructure that enables most modeling and simulation (M&S) activities from code development and...

  4. Analysis of Challenges for Management Education in India Using Total Interpretive Structural Modelling

    Science.gov (United States)

    Mahajan, Ritika; Agrawal, Rajat; Sharma, Vinay; Nangia, Vinay

    2016-01-01

    Purpose: The purpose of this paper is to identify challenges for management education in India and explain their nature, significance and interrelations using total interpretive structural modelling (TISM), an innovative version of Warfield's interpretive structural modelling (ISM). Design/methodology/approach: The challenges have been drawn from…

  5. Influence of Occupational Socialization on Two Preservice Teachers' Interpretation and Delivery of the Sport Education Model

    Science.gov (United States)

    Stran, Margaret; Curtner-Smith, Matthew D.

    2009-01-01

    The purpose of this study was to (a) examine how two preservice teachers (PTs) interpreted and delivered the sport education (SE) model during their student teaching and (b) discover factors that led to the their interpreting and delivering the model in the ways they did. The theoretical framework used to guide data collection and analysis was…

  6. INTEGRATION OF QSAR AND SAR METHODS FOR THE MECHANISTIC INTERPRETATION OF PREDICTIVE MODELS FOR CARCINOGENICITY

    Directory of Open Access Journals (Sweden)

    Natalja Fjodorova

    2012-07-01

    Full Text Available The knowledge-based Toxtree expert system (SAR approach was integrated with the statistically based counter propagation artificial neural network (CP ANN model (QSAR approach to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon descriptors and carcinogenic potency for rats as a response. The transparency of the CP ANN algorithm was demonstrated using intrinsic mapping technique specifically Kohonen maps. Chemical structures were represented by Dragon descriptors that express the structural and electronic features of molecules such as their shape and electronic surrounding related to reactivity of molecules. It was illustrated how the descriptors are correlated with particular structural alerts (SAs for carcinogenicity with recognized mechanistic link to carcinogenic activity. Moreover, the Kohonen mapping technique enables one to examine the separation of carcinogens and non-carcinogens (for rats within a family of chemicals with a particular SA for carcinogenicity. The mechanistic interpretation of models is important for the evaluation of safety of chemicals.

  7. Concept Communication and Interpretation of Illness: A Holistic Model of Understanding in Nursing Practice.

    Science.gov (United States)

    Nordby, Halvor

    To ensure patient communication in nursing, certain conditions must be met that enable successful exchange of beliefs, thoughts, and other mental states. The conditions that have received most attention in the nursing literature are derived from general communication theories, psychology, and ethical frameworks of interpretation. This article focuses on a condition more directly related to an influential coherence model of concept possession from recent philosophy of mind and language. The basic ideas in this model are (i) that the primary source of understanding of illness experiences is communicative acts that express concepts of illness, and (ii) that the key to understanding patients' concepts of illness is to understand how they depend on patients' lifeworlds. The article argues that (i) and (ii) are especially relevant in caring practice since it has been extensively documented that patients' perspectives on disease and illness are shaped by their subjective horizons. According to coherentism, nurses need to focus holistically on patients' horizons in order to understand the meaning of patients' expressions of meaning. Furthermore, the coherence model implies that fundamental aims of understanding can be achieved only if nurses recognize the interdependence of patients' beliefs and experiences of ill health. The article uses case studies to elucidate how the holistic implications of coherentism can be used as conceptual tools in nursing.

  8. Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity

    Directory of Open Access Journals (Sweden)

    Natalja Fjodorova

    2012-07-01

    Full Text Available The knowledge-based Toxtree expert system (SAR approach was integrated with the statistically based counter propagation artificial neural network (CP ANN model (QSAR approach to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon descriptors and carcinogenic potency for rats as a response. The transparency of the CP ANN algorithm was demonstrated using intrinsic mapping technique specifically Kohonen maps. Chemical structures were represented by Dragon descriptors that express the structural and electronic features of molecules such as their shape and electronic surrounding related to reactivity of molecules. It was illustrated how the descriptors are correlated with particular structural alerts (SAs for carcinogenicity with recognized mechanistic link to carcinogenic activity. Moreover, the Kohonen mapping technique enables one to examine the separation of carcinogens and non-carcinogens (for rats within a family of chemicals with a particular SA for carcinogenicity. The mechanistic interpretation of models is important for the evaluation of safety of chemicals.

  9. Comparing heat flow models for interpretation of precast quadratic pile heat exchanger thermal response tests

    DEFF Research Database (Denmark)

    Alberdi Pagola, Maria; Poulsen, Søren Erbs; Loveridge, Fleur

    2018-01-01

    This paper investigates the applicability of currently available analytical, empirical and numerical heat flow models for interpreting thermal response tests (TRT) of quadratic cross section precast pile heat exchangers. A 3D finite element model (FEM) is utilised for interpreting five TRTs...... by inverse modelling. The calibrated estimates of soil and concrete thermal conductivity are consistent with independent laboratory measurements. Due to the computational cost of inverting the 3D model, simpler models are utilised in additional calibrations. Interpretations based on semi-empirical pile G-functions...... the potential of applying TRTs for sizing quadratic, precast pile heat exchanger foundations....

  10. Modelling and interpreting biologically crusted dryland soil sub-surface structure using automated micropenetrometry

    Science.gov (United States)

    Hoon, Stephen R.; Felde, Vincent J. M. N. L.; Drahorad, Sylvie L.; Felix-Henningsen, Peter

    2015-04-01

    Soil penetrometers are used routinely to determine the shear strength of soils and deformable sediments both at the surface and throughout a depth profile in disciplines as diverse as soil science, agriculture, geoengineering and alpine avalanche-safety (e.g. Grunwald et al. 2001, Van Herwijnen et al. 2009). Generically, penetrometers comprise two principal components: An advancing probe, and a transducer; the latter to measure the pressure or force required to cause the probe to penetrate or advance through the soil or sediment. The force transducer employed to determine the pressure can range, for example, from a simple mechanical spring gauge to an automatically data-logged electronic transducer. Automated computer control of the penetrometer step size and probe advance rate enables precise measurements to be made down to a resolution of 10's of microns, (e.g. the automated electronic micropenetrometer (EMP) described by Drahorad 2012). Here we discuss the determination, modelling and interpretation of biologically crusted dryland soil sub-surface structures using automated micropenetrometry. We outline a model enabling the interpretation of depth dependent penetration resistance (PR) profiles and their spatial differentials using the model equations, σ {}(z) ={}σ c0{}+Σ 1n[σ n{}(z){}+anz + bnz2] and dσ /dz = Σ 1n[dσ n(z) /dz{} {}+{}Frn(z)] where σ c0 and σ n are the plastic deformation stresses for the surface and nth soil structure (e.g. soil crust, layer, horizon or void) respectively, and Frn(z)dz is the frictional work done per unit volume by sliding the penetrometer rod an incremental distance, dz, through the nth layer. Both σ n(z) and Frn(z) are related to soil structure. They determine the form of σ {}(z){} measured by the EMP transducer. The model enables pores (regions of zero deformation stress) to be distinguished from changes in layer structure or probe friction. We have applied this method to both artificial calibration soils in the

  11. The fractional volatility model: An agent-based interpretation

    Science.gov (United States)

    Vilela Mendes, R.

    2008-06-01

    Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.

  12. Futures Business Models for an IoT Enabled Healthcare Sector: A Causal Layered Analysis Perspective

    OpenAIRE

    Julius Francis Gomes; Sara Moqaddemerad

    2016-01-01

    Purpose: To facilitate futures business research by proposing a novel way to combine business models as a conceptual tool with futures research techniques. Design: A futures perspective is adopted to foresight business models of the Internet of Things (IoT) enabled healthcare sector by using business models as a futures business research tool. In doing so, business models is coupled with one of the most prominent foresight methodologies, Causal Layered Analysis (CLA). Qualitative analysis...

  13. Building interpretable predictive models for pediatric hospital readmission using Tree-Lasso logistic regression.

    Science.gov (United States)

    Jovanovic, Milos; Radovanovic, Sandro; Vukicevic, Milan; Van Poucke, Sven; Delibasic, Boris

    2016-09-01

    Quantification and early identification of unplanned readmission risk have the potential to improve the quality of care during hospitalization and after discharge. However, high dimensionality, sparsity, and class imbalance of electronic health data and the complexity of risk quantification, challenge the development of accurate predictive models. Predictive models require a certain level of interpretability in order to be applicable in real settings and create actionable insights. This paper aims to develop accurate and interpretable predictive models for readmission in a general pediatric patient population, by integrating a data-driven model (sparse logistic regression) and domain knowledge based on the international classification of diseases 9th-revision clinical modification (ICD-9-CM) hierarchy of diseases. Additionally, we propose a way to quantify the interpretability of a model and inspect the stability of alternative solutions. The analysis was conducted on >66,000 pediatric hospital discharge records from California, State Inpatient Databases, Healthcare Cost and Utilization Project between 2009 and 2011. We incorporated domain knowledge based on the ICD-9-CM hierarchy in a data driven, Tree-Lasso regularized logistic regression model, providing the framework for model interpretation. This approach was compared with traditional Lasso logistic regression resulting in models that are easier to interpret by fewer high-level diagnoses, with comparable prediction accuracy. The results revealed that the use of a Tree-Lasso model was as competitive in terms of accuracy (measured by area under the receiver operating characteristic curve-AUC) as the traditional Lasso logistic regression, but integration with the ICD-9-CM hierarchy of diseases provided more interpretable models in terms of high-level diagnoses. Additionally, interpretations of models are in accordance with existing medical understanding of pediatric readmission. Best performing models have

  14. Implementations and interpretations of the talbot-ogden infiltration model

    KAUST Repository

    Seo, Mookwon

    2014-11-01

    The interaction between surface and subsurface hydrology flow systems is important for water supplies. Accurate, efficient numerical models are needed to estimate the movement of water through unsaturated soil. We investigate a water infiltration model and develop very fast serial and parallel implementations that are suitable for a computer with a graphical processing unit (GPU).

  15. ASPECTS OF MATHEMATICAL MODELING AND INTERPRETATION OF A MANUFACTURING SYSTEM

    Directory of Open Access Journals (Sweden)

    Mihaela ALDEA

    2013-05-01

    Full Text Available In the paper developing we started from a model that allows a detailed decoding of causalrelationships and getting the laws that determine the evolution of the phenomenon.The model chosen for the study is a discrete event system applicable to optimize the transport systemused in pottery. In order to simulate the manufacturing process we chose Matlab package that contains pntoollibrary, by which can be realized modeling of analyzed graphs. Since the timings of manufacture are very highand the process simulation is conducted with difficulty, we divided the graph according to the transport system.

  16. Experimental software for modeling and interpreting educational data analysis processes

    Directory of Open Access Journals (Sweden)

    Natalya V. Zorina

    2017-12-01

    Full Text Available Problems, tasks and processes of educational data mining are considered in this article. The objective is to create a fundamentally new information system of the University using the results educational data analysis. One of the functions of such a system is knowledge extraction from accumulated in the operation process data. The creation of the national system of this type is an iterative and time-consuming process requiring the preliminary studies and incremental prototyping modules. The novelty of such systems is that there is a lack of those using this methodology of the development, for this purpose a number of experiments was carried out in order to collect data, choose appropriate methods for the study and to interpret them. As a result of the experiment, the authors were available sources available for analysis in the information environment of the home university. The data were taken from the semester performance, obtained from the information system of the training department of the Institute of IT MTU MIREA, the data obtained as a result of the independent work of students and data, using specially designed Google-forms. To automate the collection of information and analysis of educational data, an experimental software package was created. As a methodology for developing the experimental software complex, a decision was made using the methodologies of rational-empirical complexes (REX and single-experimentation program technologies (TPEI. The details of the program implementation of the complex are described in detail, conclusions are given about the availability of the data sources used, and conclusions are drawn about the prospects for further development.

  17. Mathematical models for interpretation of tracer data in groundwater hydrology

    International Nuclear Information System (INIS)

    1986-07-01

    The Advisory Group Meeting had the overall objective of discussing in detail the methodologies and approaches in the development of mathematical models for quantitative evaluations of tracer data in groundwater hydrology and reviewing the recent advances in this field. A separate abstract was prepared for each of the eight papers

  18. Delta-tilde interpretation of standard linear mixed model results

    DEFF Research Database (Denmark)

    Brockhoff, Per Bruun; Amorim, Isabel de Sousa; Kuznetsova, Alexandra

    2016-01-01

    data set and compared to actual d-prime calculations based on Thurstonian regression modeling through the ordinal package. For more challenging cases we offer a generic "plug-in" implementation of a version of the method as part of the R-package SensMixed. We discuss and clarify the bias mechanisms...

  19. Stieltjes electrostatic model interpretation for bound state problems

    Indian Academy of Sciences (India)

    In this paper, it is shown that Stieltjes electrostatic model and quantum Hamilton Jacobi formalism are analogous to each other. This analogy allows the bound state problem to mimic as unit moving imaginary charges i ℏ , which are placed in between the two fixed imaginary charges arising due to the classical turning ...

  20. Exploring Arthur's Pass Topographic Map and Model Interpretation.

    Science.gov (United States)

    Fastier, Murray; Macaulay, John

    1995-01-01

    Provides instructional materials, tasks, and activities to supplement a unit on map reading. Presents a two-page color topographical map of Arthur's Pass (New Zealand). Includes learning activities covering reading grid references, estimating distances, cross-sections, and sketch mapping. Briefly discusses and illustrates digital terrain models.…

  1. Stieltjes electrostatic model interpretation for bound state problems

    Indian Academy of Sciences (India)

    Abstract. In this paper, it is shown that Stieltjes electrostatic model and quantum Hamilton Jacobi formalism are analogous to each other. This analogy allows the bound state problem to mimic as n unit moving imaginary charges i¯h, which are placed in between the two fixed imaginary charges arising due to the classical ...

  2. Geometric interpretation for the interacting-boson-fermion model

    Energy Technology Data Exchange (ETDEWEB)

    Leviatan, A.

    1988-08-11

    A geometric oriented approach for studying the interacting-boson-fermion model for odd-A nuclei is presented. A deformed single-particle hamiltonian is derived by means of an algebraic Born-Oppenheimer treatment. Observables concerning spectrum and transitions are calculated for the case of a single-j fermion coupled to a prolate core charge boson number and arbitrary deformations.

  3. A geometric interpretation for the interacting-boson-fermion model

    International Nuclear Information System (INIS)

    Leviatan, A.

    1988-01-01

    A geometric oriented approach for studying the interacting-boson-fermion model for odd-A nuclei is presented. A deformed single-particle hamiltonian is derived by means of an algebraic Born-Oppenheimer treatment. Observables concerning spectrum and transitions are calculated for the case of a single-j fermion coupled to a prolate core charge boson number and arbitrary deformations

  4. A statistical model for interpreting computerized dynamic posturography data

    Science.gov (United States)

    Feiveson, Alan H.; Metter, E. Jeffrey; Paloski, William H.

    2002-01-01

    Computerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.

  5. Futures Business Models for an IoT Enabled Healthcare Sector: A Causal Layered Analysis Perspective

    Directory of Open Access Journals (Sweden)

    Julius Francis Gomes

    2016-12-01

    Full Text Available Purpose: To facilitate futures business research by proposing a novel way to combine business models as a conceptual tool with futures research techniques. Design: A futures perspective is adopted to foresight business models of the Internet of Things (IoT enabled healthcare sector by using business models as a futures business research tool. In doing so, business models is coupled with one of the most prominent foresight methodologies, Causal Layered Analysis (CLA. Qualitative analysis provides deeper understanding of the phenomenon through the layers of CLA; litany, social causes, worldview and myth. Findings: It is di cult to predict the far future for a technology oriented sector like healthcare. This paper presents three scenarios for short-, medium- and long-term future. Based on these scenarios we also present a set of business model elements for different future time frames. This paper shows a way to combine business models with CLA, a foresight methodology; in order to apply business models in futures business research. Besides offering early results for futures business research, this study proposes a conceptual space to work with individual business models for managerial stakeholders. Originality / Value: Much research on business models has offered conceptualization of the phenomenon, innovation through business model and transformation of business models. However, existing literature does not o er much on using business model as a futures research tool. Enabled by futures thinking, we collected key business model elements and building blocks for the futures market and ana- lyzed them through the CLA framework.

  6. Montmorillonite dissolution kinetics: Experimental and reactive transport modeling interpretation

    Science.gov (United States)

    Cappelli, Chiara; Yokoyama, Shingo; Cama, Jordi; Huertas, F. Javier

    2018-04-01

    The dissolution kinetics of K-montmorillonite was studied at 25 °C, acidic pH (2-4) and 0.01 M ionic strength by means of well-mixed flow-through experiments. The variations of Si, Al and Mg over time resulted in high releases of Si and Mg and Al deficit, which yielded long periods of incongruent dissolution before reaching stoichiometric steady state. This behavior was caused by simultaneous dissolution of nanoparticles and cation exchange between the interlayer K and released Ca, Mg and Al and H. Since Si was only involved in the dissolution reaction, it was used to calculate steady-state dissolution rates, RSi, over a wide solution saturation state (ΔGr ranged from -5 to -40 kcal mol-1). The effects of pH and the degree of undersaturation (ΔGr) on the K-montmorillonite dissolution rate were determined using RSi. Employing dissolution rates farthest from equilibrium, the catalytic pH effect on the K-montmorillonite dissolution rate was expressed as Rdiss = k·aH0.56±0.05 whereas using all dissolution rates, the ΔGr effect was expressed as a non-linear f(ΔGr) function Rdiss = k · [1 - exp(-3.8 × 10-4 · (|ΔGr|/RT)2.13)] The functionality of this expression is similar to the equations reported for dissolution of Na-montmorillonite at pH 3 and 50 °C (Metz, 2001) and Na-K-Ca-montmorillonite at pH 9 and 80 °C (Cama et al., 2000; Marty et al., 2011), which lends support to the use of a single f(ΔGr) term to calculate the rate over the pH range 0-14. Thus, we propose a rate law that also accounts for the effect of pOH and temperature by using the pOH-rate dependence and the apparent activation energy proposed by Rozalén et al. (2008) and Amram and Ganor (2005), respectively, and normalizing the dissolution rate constant with the edge surface area of the K-montmorillonite. 1D reactive transport simulations of the experimental data were performed using the Crunchflow code (Steefel et al., 2015) to quantitatively interpret the evolution of the released cations

  7. Modelling and interpretation of gas detection using remote laser pointers.

    Science.gov (United States)

    Hodgkinson, J; van Well, B; Padgett, M; Pride, R D

    2006-04-01

    We have developed a quantitative model of the performance of laser pointer style gas leak detectors, which are based on remote detection of backscattered radiation. The model incorporates instrumental noise limits, the reflectivity of the target background surface and a mathematical description of gas leak dispersion in constant wind speed and turbulence conditions. We have investigated optimum instrument performance and limits of detection in simulated leak detection situations. We predict that the optimum height for instruments is at eye level or above, giving an operating range of 10 m or more for most background surfaces, in wind speeds of up to 2.5 ms(-1). For ground based leak sources, we find laser pointer measurements are dominated by gas concentrations over a short distance close to the target surface, making their readings intuitive to end users in most cases. This finding is consistent with the results of field trials.

  8. An exotic k-essence interpretation of interactive cosmological models

    Energy Technology Data Exchange (ETDEWEB)

    Forte, Monica [Universidad de Buenos Aires, Departamento de Fisica, Facultad de ciencias Exactas y Naturales, Buenos Aires (Argentina)

    2016-01-15

    We define a generalization of scalar fields with non-canonical kinetic term which we call exotic k-essence or, briefly, exotik. These fields are generated by the global description of cosmological models with two interactive fluids in the dark sector and under certain conditions they correspond to usual k-essences. The formalism is applied to the cases of constant potential and of inverse square potential and also we develop the purely exotik version for the modified holographic Ricci type (MHR) of dark energy, where the equations of state are not constant. With the kinetic function F = 1 + mx and the inverse square potential we recover, through the interaction term, the identification between k-essences and quintessences of an exponential potential, already known for Friedmann-Robertson-Walker and Bianchi type I geometries. Worked examples are shown that include the self-interacting MHR and also models with crossing of the phantom divide line (PDL). (orig.)

  9. Exploring How Usage-Focused Business Models Enable Circular Economy through Digital Technologies

    Directory of Open Access Journals (Sweden)

    Gianmarco Bressanelli

    2018-02-01

    Full Text Available Recent studies advocate that digital technologies are key enabling factors for the introduction of servitized business models. At the same time, these technologies support the implementation of the circular economy (CE paradigm into businesses. Despite this general agreement, the literature still overlooks how digital technologies enable such a CE transition. To fill the gap, this paper develops a conceptual framework, based on the literature and a case study of a company implementing a usage-focused servitized business model in the household appliance industry. This study focuses on the Internet of Things (IoT, Big Data, and analytics, and identifies eight specific functionalities enabled by such technologies (improving product design, attracting target customers, monitoring and tracking product activity, providing technical support, providing preventive and predictive maintenance, optimizing the product usage, upgrading the product, enhancing renovation and end-of-life activities. By investigating how these functionalities affect three CE value drivers (increasing resource efficiency, extending lifespan, and closing the loop, the conceptual framework developed in this paper advances knowledge about the role of digital technologies as an enabler of the CE within usage-focused business models. Finally, this study shows how digital technologies help overcome the drawback of usage-focused business models for the adoption of CE pointed out by previous literature.

  10. Interpreting Hierarchical Linear and Hierarchical Generalized Linear Models with Slopes as Outcomes

    Science.gov (United States)

    Tate, Richard

    2004-01-01

    Current descriptions of results from hierarchical linear models (HLM) and hierarchical generalized linear models (HGLM), usually based only on interpretations of individual model parameters, are incomplete in the presence of statistically significant and practically important "slopes as outcomes" terms in the models. For complete description of…

  11. Some Observations on the Identification and Interpretation of the 3PL IRT Model

    Science.gov (United States)

    Azevedo, Caio Lucidius Naberezny

    2009-01-01

    The paper by Maris, G., & Bechger, T. (2009) entitled, "On the Interpreting the Model Parameters for the Three Parameter Logistic Model," addressed two important questions concerning the three parameter logistic (3PL) item response theory (IRT) model (and in a broader sense, concerning all IRT models). The first one is related to the model…

  12. Modeling sequential context effects in diagnostic interpretation of screening mammograms.

    Science.gov (United States)

    Alamudun, Folami; Paulus, Paige; Yoon, Hong-Jun; Tourassi, Georgia

    2018-07-01

    Prior research has shown that physicians' medical decisions can be influenced by sequential context, particularly in cases where successive stimuli exhibit similar characteristics when analyzing medical images. This type of systematic error is known to psychophysicists as sequential context effect as it indicates that judgments are influenced by features of and decisions about the preceding case in the sequence of examined cases, rather than being based solely on the peculiarities unique to the present case. We determine if radiologists experience some form of context bias, using screening mammography as the use case. To this end, we explore correlations between previous perceptual behavior and diagnostic decisions and current decisions. We hypothesize that a radiologist's visual search pattern and diagnostic decisions in previous cases are predictive of the radiologist's current diagnostic decisions. To test our hypothesis, we tasked 10 radiologists of varied experience to conduct blind reviews of 100 four-view screening mammograms. Eye-tracking data and diagnostic decisions were collected from each radiologist under conditions mimicking clinical practice. Perceptual behavior was quantified using the fractal dimension of gaze scanpath, which was computed using the Minkowski-Bouligand box-counting method. To test the effect of previous behavior and decisions, we conducted a multifactor fixed-effects ANOVA. Further, to examine the predictive value of previous perceptual behavior and decisions, we trained and evaluated a predictive model for radiologists' current diagnostic decisions. ANOVA tests showed that previous visual behavior, characterized by fractal analysis, previous diagnostic decisions, and image characteristics of previous cases are significant predictors of current diagnostic decisions. Additionally, predictive modeling of diagnostic decisions showed an overall improvement in prediction error when the model is trained on additional information about

  13. Interpretation of PSI-mesons in the three-triplet model with integral charges

    International Nuclear Information System (INIS)

    Gerasimov, S.B.; Govorkov, A.B.

    1975-01-01

    We interpret recently discovered narrow psi (3105)-and psi (3695) -mesons as the new ω tilde - and phi tilde -mesons predicted by the three-triplet model and discuss consequences of this identification

  14. Interpretation of Higgs and Susy searches in MSUGRA and GMSB Models

    International Nuclear Information System (INIS)

    Vivie, J.B. de

    1999-10-01

    HIGGS and SUSY searches performed by the ALEPH Experiment at LEP are interpreted in the framework of two constrained R-parity conserving models: Minimal Supergravity and minimal Gauge Mediated Supersymmetry Breaking. (author)

  15. Enabling new graduate midwives to work in midwifery continuity of care models: A conceptual model for implementation.

    Science.gov (United States)

    Cummins, Allison M; Catling, Christine; Homer, Caroline S E

    2017-12-04

    High-level evidence demonstrates midwifery continuity of care is beneficial for women and babies. Women have limited access to midwifery continuity of care models in Australia. One of the factors limiting women's access is recruiting enough midwives to work in continuity. Our research found that newly graduated midwives felt well prepared to work in midwifery led continuity of care models, were well supported to work in the models and the main driver to employing them was a need to staff the models. However limited opportunities exist for new graduate midwives to work in midwifery continuity of care. The aim of this paper therefore is to describe a conceptual model developed to enable new graduate midwives to work in midwifery continuity of care models. The findings from a qualitative study were synthesised with the existing literature to develop a conceptual model that enables new graduate midwives to work in midwifery continuity of care. The model contains the essential elements to enable new graduate midwives to work in midwifery continuity of care models. Each of the essential elements discussed are to assist midwifery managers, educators and new graduates to facilitate the organisational changes required to accommodate new graduates. The conceptual model is useful to show maternity services how to enable new graduate midwives to work in midwifery continuity of care models. Copyright © 2017 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

  16. Logistic regression modelling: procedures and pitfalls in developing and interpreting prediction models

    Directory of Open Access Journals (Sweden)

    Nataša Šarlija

    2017-01-01

    Full Text Available This study sheds light on the most common issues related to applying logistic regression in prediction models for company growth. The purpose of the paper is 1 to provide a detailed demonstration of the steps in developing a growth prediction model based on logistic regression analysis, 2 to discuss common pitfalls and methodological errors in developing a model, and 3 to provide solutions and possible ways of overcoming these issues. Special attention is devoted to the question of satisfying logistic regression assumptions, selecting and defining dependent and independent variables, using classification tables and ROC curves, for reporting model strength, interpreting odds ratios as effect measures and evaluating performance of the prediction model. Development of a logistic regression model in this paper focuses on a prediction model of company growth. The analysis is based on predominantly financial data from a sample of 1471 small and medium-sized Croatian companies active between 2009 and 2014. The financial data is presented in the form of financial ratios divided into nine main groups depicting following areas of business: liquidity, leverage, activity, profitability, research and development, investing and export. The growth prediction model indicates aspects of a business critical for achieving high growth. In that respect, the contribution of this paper is twofold. First, methodological, in terms of pointing out pitfalls and potential solutions in logistic regression modelling, and secondly, theoretical, in terms of identifying factors responsible for high growth of small and medium-sized companies.

  17. Mechanistic interpretation of glass reaction: Input to kinetic model development

    International Nuclear Information System (INIS)

    Bates, J.K.; Ebert, W.L.; Bradley, J.P.; Bourcier, W.L.

    1991-05-01

    Actinide-doped SRL 165 type glass was reacted in J-13 groundwater at 90 degree C for times up to 278 days. The reaction was characterized by both solution and solid analyses. The glass was seen to react nonstoichiometrically with preferred leaching of alkali metals and boron. High resolution electron microscopy revealed the formation of a complex layer structure which became separated from the underlying glass as the reaction progressed. The formation of the layer and its effect on continued glass reaction are discussed with respect to the current model for glass reaction used in the EQ3/6 computer simulation. It is concluded that the layer formed after 278 days is not protective and may eventually become fractured and generate particulates that may be transported by liquid water. 5 refs., 5 figs. , 3 tabs

  18. Model-Based Interpretation and Experimental Verification of ECT Signals of Steam Generator Tubes

    International Nuclear Information System (INIS)

    Song, Sung Jin; Kim, Young Hwan; Kim, Eui Lae; Yim, Chang Jae; Lee, Jin Ho

    2004-01-01

    Model-based inversion tools for eddy current signals have been developed by combining neural networks and finite element modeling, for quantitative flaw characterization in steam generator tubes. In the present work, interpretation of experimental eddy current signals was carried out in order to validate the developed inversion tools. A database was constructed using the synthetic flaw signals generated by the finite element model. The hybrid neural networks composed of a PNN classifier and BPNN size estimators were trained using the synthetic signals. Experimental eddy current signals were obtained from axisymmetric artificial flaws. Interpretation of flaw signals was conducted by feeding the experimental signals into the neural networks. The interpretation was excellent, which shows that the developed inversion tools would be applicable to the Interpretation of real eddy current signals

  19. Collaborative Cloud Manufacturing: Design of Business Model Innovations Enabled by Cyberphysical Systems in Distributed Manufacturing Systems

    Directory of Open Access Journals (Sweden)

    Erwin Rauch

    2016-01-01

    Full Text Available Collaborative cloud manufacturing, as a concept of distributed manufacturing, allows different opportunities for changing the logic of generating and capturing value. Cyberphysical systems and the technologies behind them are the enablers for new business models which have the potential to be disruptive. This paper introduces the topics of distributed manufacturing as well as cyberphysical systems. Furthermore, the main business model clusters of distributed manufacturing systems are described, including collaborative cloud manufacturing. The paper aims to provide support for developing business model innovations based on collaborative cloud manufacturing. Therefore, three business model architecture types of a differentiated business logic are discussed, taking into consideration the parameters which have an influence and the design of the business model and its architecture. As a result, new business models can be developed systematically and new ideas can be generated to boost the concept of collaborative cloud manufacturing within all sustainable business models.

  20. Modeling of surface myoelectric signals--Part II: Model-based signal interpretation.

    Science.gov (United States)

    Merletti, R; Roy, S H; Kupa, E; Roatta, S; Granata, A

    1999-07-01

    Experimental electromyogram (EMG) data from the human biceps brachii were simulated using the model described in [10] of this work. A multichannel linear electrode array, spanning the length of the biceps, was used to detect monopolar and bipolar signals, from which double differential signals were computed, during either voluntary or electrically elicited isometric contractions. For relatively low-level voluntary contractions (10%-30% of maximum force) individual firings of three to four-different motor units were identified and their waveforms were closely approximated by the model. Motor unit parameters such as depth, size, fiber orientation and length, location of innervation and tendonous zones, propagation velocity, and source width were estimated using the model. Two applications of the model are described. The first analyzes the effects of electrode rotation with respect to the muscle fiber direction and shows the possibility of conduction velocity (CV) over- and under-estimation. The second focuses on the myoelectric manifestations of fatigue during a sustained electrically elicited contraction and the interrelationship between muscle fiber CV, spectral and amplitude variables, and the length of the depolarization zone. It is concluded that a) surface EMG detection using an electrode array, when combined with a model of signal propagation, provides a useful method for understanding the physiological and anatomical determinants of EMG waveform characteristics and b) the model provides a way for the interpretation of fatigue plots.

  1. Enabling interoperability in planetary sciences and heliophysics: The case for an information model

    Science.gov (United States)

    Hughes, J. Steven; Crichton, Daniel J.; Raugh, Anne C.; Cecconi, Baptiste; Guinness, Edward A.; Isbell, Christopher E.; Mafi, Joseph N.; Gordon, Mitchell K.; Hardman, Sean H.; Joyner, Ronald S.

    2018-01-01

    The Planetary Data System has developed the PDS4 Information Model to enable interoperability across diverse science disciplines. The Information Model is based on an integration of International Organization for Standardization (ISO) level standards for trusted digital archives, information model development, and metadata registries. Where controlled vocabularies provides a basic level of interoperability by providing a common set of terms for communication between both machines and humans the Information Model improves interoperability by means of an ontology that provides semantic information or additional related context for the terms. The information model was defined by team of computer scientists and science experts from each of the diverse disciplines in the Planetary Science community, including Atmospheres, Geosciences, Cartography and Imaging Sciences, Navigational and Ancillary Information, Planetary Plasma Interactions, Ring-Moon Systems, and Small Bodies. The model was designed to be extensible beyond the Planetary Science community, for example there are overlaps between certain PDS disciplines and the Heliophysics and Astrophysics disciplines. "Interoperability" can apply to many aspects of both the developer and the end-user experience, for example agency-to-agency, semantic level, and application level interoperability. We define these types of interoperability and focus on semantic level interoperability, the type of interoperability most directly enabled by an information model.

  2. MODELLING THE FUTURE MUSIC TEACHERS’ READINESS TO PERFORMING AND INTERPRETIVE ACTIVITY DURING INSTRUMENTAL TRAINING

    Directory of Open Access Journals (Sweden)

    Chenj Bo

    2016-11-01

    Full Text Available One of the main fields of training future music teachers in Ukrainian system of higher education is instrumental music one, such as skills of performing and interpretive activities. The aim of the article is to design a model of the future music teachers’ readiness to performing and interpretive activities in musical and instrumental training. The process of modelling is based on several interrelated scientific approaches, including systemic, personality-centered, reflective, competence, active and creative ones. While designing a model of music future teachers’ readinesses to musical interpretive activities, its philosophical, informative, interactive, hedonistic, creative functions are taken into account. Important theoretical and methodological factors are thought to be principles of musical and pedagogical education: culture correspondence and reflection; unity of emotional and conscious, artistic and technical items in musical education; purposeful interrelations and art and pedagogical communication between teachers and students; intensification of music and creative activity. Above-mentioned pedagogical phenomenon is subdivided into four components: motivation-oriented, cognitive-evaluating, performance-independent, creative and productive. For each component relevant criteria and indicators are identified. The stages of future music teachers’ readiness to performing interpretative activity are highlighted: information searching one, which contributes to the implementation of complex diagnostic methods (surveys, questionnaires, testing; regulative and performing one, which is characterized by future music teachers’ immersion into music performing and interpretative activities; operational and reflective stage, which involves activation of mechanisms of future music teachers’ self-knowledge, self-realization, formation of skills of independent artistic and expressive various music genres and styles interpretation; projective and

  3. Information Management Workflow and Tools Enabling Multiscale Modeling Within ICME Paradigm

    Science.gov (United States)

    Arnold, Steven M.; Bednarcyk, Brett A.; Austin, Nic; Terentjev, Igor; Cebon, Dave; Marsden, Will

    2016-01-01

    With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, material information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to establish workflow for and demonstrate a unique set of web application tools for linking NASA GRC's Integrated Computational Materials Engineering (ICME) Granta MI database schema and NASA GRC's Integrated multiscale Micromechanics Analysis Code (ImMAC) software toolset are presented. The goal is to enable seamless coupling between both test data and simulation data, which is captured and tracked automatically within Granta MI®, with full model pedigree information. These tools, and this type of linkage, are foundational to realizing the full potential of ICME, in which materials processing, microstructure, properties, and performance are coupled to enable application-driven design and optimization of materials and structures.

  4. Testing three different sequential mediational interpretations of Beck's cognitive model of the development of depression.

    Science.gov (United States)

    Pössel, Patrick; Black, Stephanie Winkeljohn

    2014-01-01

    This study tested and compared three sequential interpretations of Beck's cognitive model of the development of depression (1996). The causal mediational interpretation identifies dysfunctional attitudes as most distal to depressive symptoms, followed by cognitive distortions, the cognitive triad, and negative automatic thoughts, with each construct successively more proximal to depressive symptoms. By contrast, the symptom model reverses the causal chain with negative automatic thoughts as the most proximal consequence and dysfunctional attitudes as the most distal consequence of depression. The bidirectional model merges both interpretations into one model. Previous studies on sequential interpretations of Beck's model have not included cognitive distortions or the cognitive triad and did not test the bidirectional model finding contradictory empirical evidence for the sequential order. In the 3-wave longitudinal study, 308 German university students without clinically significant depressive symptoms (245 female, average age: 23.69 years) completed self-report questionnaires measuring their dysfunctional attitudes, cognitive distortions, cognitive triad, negative automatic thoughts, and depressive symptoms. The bidirectional model with partial mediation fit the data best and cognitive distortions mediated the relationship between dysfunctional attitudes and negative automatic thoughts and vice versa. The findings have important consequences for the prevention of depression. Prevention programs may want to focus on cognitive distortions, the only construct in Beck's model that influences every other construct in the model. © 2013 Wiley Periodicals, Inc.

  5. COINSTAC: A privacy enabled model and prototype for leveraging and processing decentralized brain imaging data

    Directory of Open Access Journals (Sweden)

    Sergey M Plis

    2016-08-01

    Full Text Available The field of neuroimaging has embraced the need for sharing and collaboration. Data sharing mandates from public funding agencies and major journal publishers have spurred the development of data repositories and neuroinformatics consortia. However, efficient and effective data sharing still faces several hurdles. For example, open data sharing is on the rise but is not suitable for sensitive data that are not easily shared, such as genetics. Current approaches can be cumbersome (such as negotiating multiple data sharing agreements. There are also significant data transfer, organization and computational challenges. Centralized repositories only partially address the issues. We propose a dynamic, decentralized platform for large scale analyses called the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC. The COINSTAC solution can include data missing from central repositories, allows pooling of both open and ``closed'' repositories by developing privacy-preserving versions of widely-used algorithms, and incorporates the tools within an easy-to-use platform enabling distributed computation. We present an initial prototype system which we demonstrate on two multi-site data sets, without aggregating the data. In addition, by iterating across sites, the COINSTAC model enables meta-analytic solutions to converge to ``pooled-data'' solutions (i.e. as if the entire data were in hand. More advanced approaches such as feature generation, matrix factorization models, and preprocessing can be incorporated into such a model. In sum, COINSTAC enables access to the many currently unavailable data sets, a user friendly privacy enabled interface for decentralized analysis, and a powerful solution that complements existing data sharing solutions.

  6. Investigating the Direct Meltwater Effect in Terrestrial Oxygen-Isotope Paleoclimate Records Using an Isotope-Enabled Earth System Model

    Science.gov (United States)

    Zhu, Jiang; Liu, Zhengyu; Brady, Esther C.; Otto-Bliesner, Bette L.; Marcott, Shaun A.; Zhang, Jiaxu; Wang, Xianfeng; Nusbaumer, Jesse; Wong, Tony E.; Jahn, Alexandra; Noone, David

    2017-12-01

    Variations in terrestrial oxygen-isotope reconstructions from ice cores and speleothems have been primarily attributed to climatic changes of surface air temperature, precipitation amount, or atmospheric circulation. Here we demonstrate with the fully coupled isotope-enabled Community Earth System Model an additional process contributing to the oxygen-isotope variations during glacial meltwater events. This process, termed "the direct meltwater effect," involves propagating large amounts of isotopically depleted meltwater throughout the hydrological cycle and is independent of climatic changes. We find that the direct meltwater effect can make up 15-35% of the δ18O signals in precipitation over Greenland and eastern Brazil for large freshwater forcings (0.25-0.50 sverdrup (106 m3/s)). Model simulations further demonstrate that the direct meltwater effect increases with the magnitude and duration of the freshwater forcing and is sensitive to both the location and shape of the meltwater. These new modeling results have important implications for past climate interpretations of δ18O.

  7. Using the model statement to elicit information and cues to deceit in interpreter-based interviews.

    Science.gov (United States)

    Vrij, Aldert; Leal, Sharon; Mann, Samantha; Dalton, Gary; Jo, Eunkyung; Shaboltas, Alla; Khaleeva, Maria; Granskaya, Juliana; Houston, Kate

    2017-06-01

    We examined how the presence of an interpreter during an interview affects eliciting information and cues to deceit, while using a method that encourages interviewees to provide more detail (model statement, MS). A total of 199 Hispanic, Korean and Russian participants were interviewed either in their own native language without an interpreter, or through an interpreter. Interviewees either lied or told the truth about a trip they made during the last twelve months. Half of the participants listened to a MS at the beginning of the interview. The dependent variables were 'detail', 'complications', 'common knowledge details', 'self-handicapping strategies' and 'ratio of complications'. In the MS-absent condition, the interviews resulted in less detail when an interpreter was present than when an interpreter was absent. In the MS-present condition, the interviews resulted in a similar amount of detail in the interpreter present and absent conditions. Truthful statements included more complications and fewer common knowledge details and self-handicapping strategies than deceptive statements, and the ratio of complications was higher for truth tellers than liars. The MS strengthened these results, whereas an interpreter had no effect on these results. Copyright © 2017. Published by Elsevier B.V.

  8. A Hierarchical Structural Model for the Interpretation of Mercury Porosimetry and Nitrogen Sorption.

    Science.gov (United States)

    Rigby

    2000-04-15

    A new model of interpretation for the mercury porosimetry experiment has been presented. The void space of a porous solid is modeled by separate representations of both the macroscopic (>10 µm) and the mesoscopic (catalyst manufacture and the deactivation of catalysts by coke deposition. Copyright 2000 Academic Press.

  9. Featuring Multiple Local Optima to Assist the User in the Interpretation of Induced Bayesian Network Models

    DEFF Research Database (Denmark)

    Dalgaard, Jens; Pena, Jose; Kocka, Tomas

    2004-01-01

    We propose a method to assist the user in the interpretation of the best Bayesian network model indu- ced from data. The method consists in extracting relevant features from the model (e.g. edges, directed paths and Markov blankets) and, then, assessing the con¯dence in them by studying multiple...

  10. Re-orienting a remote acute care model towards a primary health care approach: key enablers.

    Science.gov (United States)

    Carroll, Vicki; Reeve, Carole A; Humphreys, John S; Wakerman, John; Carter, Maureen

    2015-01-01

    The objective of this study was to identify the key enablers of change in re-orienting a remote acute care model to comprehensive primary healthcare delivery. The setting of the study was a 12-bed hospital in Fitzroy Crossing, Western Australia. Individual key informant, in-depth interviews were completed with five of six identified senior leaders involved in the development of the Fitzroy Valley Health Partnership. Interviews were recorded and transcripts were thematically analysed by two investigators for shared views about the enabling factors strengthening primary healthcare delivery in a remote region of Australia. Participants described theestablishment of a culturally relevant primary healthcare service, using a community-driven, 'bottom up' approach characterised by extensive community participation. The formal partnership across the government and community controlled health services was essential, both to enable change to occur and to provide sustainability in the longer term. A hierarchy of major themes emerged. These included community participation, community readiness and desire for self-determination; linkages in the form of a government community controlled health service partnership; leadership; adequate infrastructure; enhanced workforce supply; supportive policy; and primary healthcare funding. The strong united leadership shown by the community and the health service enabled barriers to be overcome and it maximised the opportunities provided by government policy changes. The concurrent alignment around a common vision enabled implementation of change. The key principle learnt from this study is the importance of community and health service relationships and local leadership around a shared vision for the re-orientation of community health services.

  11. Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

    Science.gov (United States)

    Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong; Baudry, Michel; Berger, Theodore W

    2015-01-01

    Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.

  12. Service and business model for technology enabled and home-based cardiac rehabilitation programs.

    Science.gov (United States)

    Sarela, Antti; Whittaker, Frank; Korhonen, Ilkka

    2009-01-01

    Cardiac rehabilitation programs are comprehensive life-style programs aimed at preventing recurrence of a cardiac event. However, the current programs have globally significantly low levels of uptake. Home-based model can be a viable alternative to hospital-based programs. We developed and analysed a service and business model for home based cardiac rehabilitation based on personal mentoring using mobile phones and web services. We analysed the different organizational and economical aspects of setting up and running the home based program and propose a potential business model for a sustainable and viable service. The model can be extended to management of other chronic conditions to enable transition from hospital and care centre based treatments to sustainable home-based care.

  13. An Observation Capability Metadata Model for EO Sensor Discovery in Sensor Web Enablement Environments

    Directory of Open Access Journals (Sweden)

    Chuli Hu

    2014-10-01

    Full Text Available Accurate and fine-grained discovery by diverse Earth observation (EO sensors ensures a comprehensive response to collaborative observation-required emergency tasks. This discovery remains a challenge in an EO sensor web environment. In this study, we propose an EO sensor observation capability metadata model that reuses and extends the existing sensor observation-related metadata standards to enable the accurate and fine-grained discovery of EO sensors. The proposed model is composed of five sub-modules, namely, ObservationBreadth, ObservationDepth, ObservationFrequency, ObservationQuality and ObservationData. The model is applied to different types of EO sensors and is formalized by the Open Geospatial Consortium Sensor Model Language 1.0. The GeosensorQuery prototype retrieves the qualified EO sensors based on the provided geo-event. An actual application to flood emergency observation in the Yangtze River Basin in China is conducted, and the results indicate that sensor inquiry can accurately achieve fine-grained discovery of qualified EO sensors and obtain enriched observation capability information. In summary, the proposed model enables an efficient encoding system that ensures minimum unification to represent the observation capabilities of EO sensors. The model functions as a foundation for the efficient discovery of EO sensors. In addition, the definition and development of this proposed EO sensor observation capability metadata model is a helpful step in extending the Sensor Model Language (SensorML 2.0 Profile for the description of the observation capabilities of EO sensors.

  14. Analysis of diet optimization models for enabling conditions for hypertrophic muscle enlargement in athletes

    Directory of Open Access Journals (Sweden)

    L. Matijević

    2013-01-01

    Full Text Available In this study mathematical models were created and used in diet optimization for an athlete – recreational bodybuilder for pretournament period. The main aim was to determine weekly menus that can enable conditions for the hypertrophic muscle enlargement and to reduce the fat mass in a body. Each daily offer was planned to contain six to seven meals but with respect to several user’s personal demands. Optimal carbohydrates, fat and protein ratio in diet for enabling hypertrophy, recommended in literature, was found to be 43:30:27 and was chosen as the target in this research. Variables included in models were presented dishes and constraints, observed values of the offers; price, mass of consumed food, energy, water and content of different nutrients. The general idea was to create the models and to compare different programs in solving a problem. LINDO and MS Excel were recognized as widely spread and were chosen for model testing and examination. Both programs were suggested weekly menus that were acceptable to the user and were met all recommendations and demands. Weekly menus were analysed and compared. Sensitivity tests from both programs were used to detect possible critical points in the menu. Used programs produced slightly different results but still with very high correlation between proposed weekly intakes (R2=0.99856, p<0.05 so both can be successfully used in the pretournament period of bodybuilding and recommended for this complex task.

  15. Adoption of mobile learning among 3g-enabled handheld users using extended technology acceptance model

    Directory of Open Access Journals (Sweden)

    Fadare Oluwaseun Gbenga

    2013-12-01

    Full Text Available This paper examines various constructs of an extended TAM, Technology Acceptance Model, that are theoretically influencing the adoption and acceptability of mobile learning among 3G enabled mobile users. Mobile learning activity- based, used for this study were drawn from behaviourist and “learning and teaching support” educational paradigms. An online and manual survey instruments were used to gather data. The structural equation modelling techniques were then employed to explain the adoption processes of hypothesized research model. A theoretical model ETAM is developed based on TAM. Our result proved that psychometric constructs of TAM can be extended and that ETAM is well suited, and of good pedagogical tool in understanding mobile learning among 3G enabled handheld devices in southwest part of Nigeria. Cognitive constructs, attitude toward m-learning, self-efficacy play significant roles in influencing behavioural intention for mobile learning, of which self-efficacy is the most importance construct. Implications of results and directions for future research are discussed.

  16. Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

    Science.gov (United States)

    Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

  17. Interpretation and mapping of geological features using mobile devices for 3D outcrop modelling

    Science.gov (United States)

    Buckley, Simon J.; Kehl, Christian; Mullins, James R.; Howell, John A.

    2016-04-01

    Advances in 3D digital geometric characterisation have resulted in widespread adoption in recent years, with photorealistic models utilised for interpretation, quantitative and qualitative analysis, as well as education, in an increasingly diverse range of geoscience applications. Topographic models created using lidar and photogrammetry, optionally combined with imagery from sensors such as hyperspectral and thermal cameras, are now becoming commonplace in geoscientific research. Mobile devices (tablets and smartphones) are maturing rapidly to become powerful field computers capable of displaying and interpreting 3D models directly in the field. With increasingly high-quality digital image capture, combined with on-board sensor pose estimation, mobile devices are, in addition, a source of primary data, which can be employed to enhance existing geological models. Adding supplementary image textures and 2D annotations to photorealistic models is therefore a desirable next step to complement conventional field geoscience. This contribution reports on research into field-based interpretation and conceptual sketching on images and photorealistic models on mobile devices, motivated by the desire to utilise digital outcrop models to generate high quality training images (TIs) for multipoint statistics (MPS) property modelling. Representative training images define sedimentological concepts and spatial relationships between elements in the system, which are subsequently modelled using artificial learning to populate geocellular models. Photorealistic outcrop models are underused sources of quantitative and qualitative information for generating TIs, explored further in this research by linking field and office workflows through the mobile device. Existing textured models are loaded to the mobile device, allowing rendering in a 3D environment. Because interpretation in 2D is more familiar and comfortable for users, the developed application allows new images to be captured

  18. Interpretation of ANN-based QSAR models for prediction of antioxidant activity of flavonoids.

    Science.gov (United States)

    Žuvela, Petar; David, Jonathan; Wong, Ming Wah

    2018-02-05

    Quantitative structure-activity relationships (QSARs) built using machine learning methods, such as artificial neural networks (ANNs) are powerful in prediction of (antioxidant) activity from quantum mechanical (QM) parameters describing the molecular structure, but are usually not interpretable. This obvious difficulty is one of the most common obstacles in application of ANN-based QSAR models for design of potent antioxidants or elucidating the underlying mechanism. Interpreting the resulting models is often omitted or performed erroneously altogether. In this work, a comprehensive comparative study of six methods (PaD, PaD 2 , weights, stepwise, perturbation and profile) for exploration and interpretation of ANN models built for prediction of Trolox-equivalent antioxidant capacity (TEAC) QM descriptors, is presented. Sum of ranking differences (SRD) was used for ranking of the six methods with respect to the contributions of the calculated QM molecular descriptors toward TEAC. The results show that the PaD, PaD 2 and profile methods are the most stable and give rise to realistic interpretation of the observed correlations. Therefore, they are safely applicable for future interpretations without the opinion of an experienced chemist or bio-analyst. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

  19. Interpretable Predictive Models for Knowledge Discovery from Home-Care Electronic Health Records

    Directory of Open Access Journals (Sweden)

    Bonnie L. Westra

    2011-01-01

    Full Text Available The purpose of this methodological study was to compare methods of developing predictive rules that are parsimonious and clinically interpretable from electronic health record (EHR home visit data, contrasting logistic regression with three data mining classification models. We address three problems commonly encountered in EHRs: the value of including clinically important variables with little variance, handling imbalanced datasets, and ease of interpretation of the resulting predictive models. Logistic regression and three classification models using Ripper, decision trees, and Support Vector Machines were applied to a case study for one outcome of improvement in oral medication management. Predictive rules for logistic regression, Ripper, and decision trees are reported and results compared using F-measures for data mining models and area under the receiver-operating characteristic curve for all models. The rules generated by the three classification models provide potentially novel insights into mining EHRs beyond those provided by standard logistic regression, and suggest steps for further study.

  20. Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

    Science.gov (United States)

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

    2018-01-01

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

  1. Ames Culture Chamber System: Enabling Model Organism Research Aboard the international Space Station

    Science.gov (United States)

    Steele, Marianne

    2014-01-01

    Understanding the genetic, physiological, and behavioral effects of spaceflight on living organisms and elucidating the molecular mechanisms that underlie these effects are high priorities for NASA. Certain organisms, known as model organisms, are widely studied to help researchers better understand how all biological systems function. Small model organisms such as nem-atodes, slime mold, bacteria, green algae, yeast, and moss can be used to study the effects of micro- and reduced gravity at both the cellular and systems level over multiple generations. Many model organisms have sequenced genomes and published data sets on their transcriptomes and proteomes that enable scientific investigations of the molecular mechanisms underlying the adaptations of these organisms to space flight.

  2. Test-driven modeling and development of cloud-enabled cyber-physical smart systems

    DEFF Research Database (Denmark)

    Munck, Allan; Madsen, Jan

    2017-01-01

    . Using test-driven modeling (TDM) is likely to be the best way to design smart systems such that these qualities are ensured. However, the TDM methods that are applied to development of simpler systems do not scale to smart systems because the modeling technologies cannot handle the complexity and size...... of the systems. In this paper, we present a method for test-driven modeling that scales to very large and complex systems. The method uses a combination of formal verification of basic interactions, simulations of complex scenarios, and mathematical forecasting to predict system behavior and performance. We...... utilized the method to analyze, design and develop various scenarios for a cloud-enabled medical system. Our approach provides a versatile method that may be adapted and improved for future development of very large and complex smart systems in various domains....

  3. Kinetic Modeling of Accelerated Stability Testing Enabled by Second Harmonic Generation Microscopy.

    Science.gov (United States)

    Song, Zhengtian; Sarkar, Sreya; Vogt, Andrew D; Danzer, Gerald D; Smith, Casey J; Gualtieri, Ellen J; Simpson, Garth J

    2018-04-03

    The low limits of detection afforded by second harmonic generation (SHG) microscopy coupled with image analysis algorithms enabled quantitative modeling of the temperature-dependent crystallization of active pharmaceutical ingredients (APIs) within amorphous solid dispersions (ASDs). ASDs, in which an API is maintained in an amorphous state within a polymer matrix, are finding increasing use to address solubility limitations of small-molecule APIs. Extensive stability testing is typically performed for ASD characterization, the time frame for which is often dictated by the earliest detectable onset of crystal formation. Here a study of accelerated stability testing on ritonavir, a human immunodeficiency virus (HIV) protease inhibitor, has been conducted. Under the condition for accelerated stability testing at 50 °C/75%RH and 40 °C/75%RH, ritonavir crystallization kinetics from amorphous solid dispersions were monitored by SHG microscopy. SHG microscopy coupled by image analysis yielded limits of detection for ritonavir crystals as low as 10 ppm, which is about 2 orders of magnitude lower than other methods currently available for crystallinity detection in ASDs. The four decade dynamic range of SHG microscopy enabled quantitative modeling with an established (JMAK) kinetic model. From the SHG images, nucleation and crystal growth rates were independently determined.

  4. An approach to the interpretation of backpropagation neural network models in QSAR studies.

    Science.gov (United States)

    Baskin, I I; Ait, A O; Halberstam, N M; Palyulin, V A; Zefirov, N S

    2002-03-01

    An approach to the interpretation of backpropagation neural network models for quantitative structure-activity and structure-property relationships (QSAR/QSPR) studies is proposed. The method is based on analyzing the first and second moments of distribution of the values of the first and the second partial derivatives of neural network outputs with respect to inputs calculated at data points. The use of such statistics makes it possible not only to obtain actually the same characteristics as for the case of traditional "interpretable" statistical methods, such as the linear regression analysis, but also to reveal important additional information regarding the non-linear character of QSAR/QSPR relationships. The approach is illustrated by an example of interpreting a backpropagation neural network model for predicting position of the long-wave absorption band of cyane dyes.

  5. Dream interpretation, affect, and the theory of neuronal group selection: Freud, Winnicott, Bion, and Modell.

    Science.gov (United States)

    Shields, Walker

    2006-12-01

    The author uses a dream specimen as interpreted during psychoanalysis to illustrate Modell's hypothesis that Edelman's theory of neuronal group selection (TNGS) may provide a valuable neurobiological model for Freud's dynamic unconscious, imaginative processes in the mind, the retranscription of memory in psychoanalysis, and intersubjective processes in the analytic relationship. He draws parallels between the interpretation of the dream material with keen attention to affect-laden meanings in the evolving analytic relationship in the domain of psychoanalysis and the principles of Edelman's TNGS in the domain of neurobiology. The author notes how this correlation may underscore the importance of dream interpretation in psychoanalysis. He also suggests areas for further investigation in both realms based on study of their interplay.

  6. Cloud-enabled large-scale land surface model simulations with the NASA Land Information System

    Science.gov (United States)

    Duffy, D.; Vaughan, G.; Clark, M. P.; Peters-Lidard, C. D.; Nijssen, B.; Nearing, G. S.; Rheingrover, S.; Kumar, S.; Geiger, J. V.

    2017-12-01

    Developed by the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC), the Land Information System (LIS) is a high-performance software framework for terrestrial hydrology modeling and data assimilation. LIS provides the ability to integrate satellite and ground-based observational products and advanced modeling algorithms to extract land surface states and fluxes. Through a partnership with the National Center for Atmospheric Research (NCAR) and the University of Washington, the LIS model is currently being extended to include the Structure for Unifying Multiple Modeling Alternatives (SUMMA). With the addition of SUMMA in LIS, meaningful simulations containing a large multi-model ensemble will be enabled and can provide advanced probabilistic continental-domain modeling capabilities at spatial scales relevant for water managers. The resulting LIS/SUMMA application framework is difficult for non-experts to install due to the large amount of dependencies on specific versions of operating systems, libraries, and compilers. This has created a significant barrier to entry for domain scientists that are interested in using the software on their own systems or in the cloud. In addition, the requirement to support multiple run time environments across the LIS community has created a significant burden on the NASA team. To overcome these challenges, LIS/SUMMA has been deployed using Linux containers, which allows for an entire software package along with all dependences to be installed within a working runtime environment, and Kubernetes, which orchestrates the deployment of a cluster of containers. Within a cloud environment, users can now easily create a cluster of virtual machines and run large-scale LIS/SUMMA simulations. Installations that have taken weeks and months can now be performed in minutes of time. This presentation will discuss the steps required to create a cloud-enabled large-scale simulation, present examples of its use, and

  7. Cloud-Enabled Space Weather Modeling and Data Assimilation Platform (CESWP)

    Science.gov (United States)

    Satchwill, B.; Rankin, R.; Shillington, J.; Toews, E.

    2010-12-01

    Multi-space-agency partnerships in the development and flight of space science payloads, and in sharing of complex models and data sets (including ground-based data sets), make a compelling case for providing standardized interfaces and platforms to access data and models. However, developing and executing simulations requires space physicists to either develop knowledge of specialized high-performance computing environments and environment-specific simulations, or run simulations multiple times serially in order to examine the results of different parametric inputs. Barriers also exist where data and models reside in different geographic locations, which is typically the case. The emergence of cloud computing, and its Infrastructure-as-a-Service (IaaS) variant, provides an opportunity to develop software architectures that reduce barriers to simulation development and use, while simultaneously reducing the proliferation of hardware in the research community, and all its inherent high cost. The Cloud-Enabled Space Weather Modeling and Data Assimilation Platform (CESWP) utilizes cloud technologies to dramatically improve the sustainability, flexibility and performance of research tools and services, enabling an attendant improvement in researcher productivity and research funding efficacy. CESWP integrates complex modeling and simulation functionality into the federated data capabilities of the Canadian Space Sciences Data Portal (http://cssdp.ca). The CESWP cloud is innovative in its use of a versatile IaaS approach to provision a space sciences cloud. The platform helps researchers deal with the explosion of new data sets that require international cooperation and complex modeling as part of their analysis. This paper will describe the current implementation of the CESWP private cloud, which is based on Eucalyptus, KVM, CentOS, and Amazon Web Services compatible API’s.

  8. Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.

    Science.gov (United States)

    Bandeira E Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

    2017-06-07

    Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. Copyright © 2017 Bandeira e Sousa et al.

  9. Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction

    Directory of Open Access Journals (Sweden)

    Massaine Bandeira e Sousa

    2017-06-01

    Full Text Available Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1 single-environment, main genotypic effect model (SM; (2 multi-environment, main genotypic effects model (MM; (3 multi-environment, single variance G×E deviation model (MDs; and (4 multi-environment, environment-specific variance G×E deviation model (MDe. Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB, and a nonlinear kernel Gaussian kernel (GK. The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets, having different numbers of maize hybrids evaluated in different environments for grain yield (GY, plant height (PH, and ear height (EH. Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied.

  10. Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization.

    Science.gov (United States)

    Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

    2016-03-15

    Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. The annotation ontology for rule-based models can be found at http://purl.org/rbm/rbmo The krdf tool and associated executable examples are

  11. Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization

    Science.gov (United States)

    Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

    2016-01-01

    Motivation: Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. Results: We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. Availability and implementation: The annotation ontology for rule-based models can be found at http

  12. Interpreting and Understanding Logits, Probits, and other Non-Linear Probability Models

    DEFF Research Database (Denmark)

    Breen, Richard; Karlson, Kristian Bernt; Holm, Anders

    2018-01-01

    guidelines take little or no account of a body of work that, over the past 30 years, has pointed to problematic aspects of these nonlinear probability models and, particularly, to difficulties in interpreting their parameters. In this chapterreview, we draw on that literature to explain the problems, show...

  13. Enhancing CIDOC-CRM and compatible models with the concept of multiple interpretation

    Science.gov (United States)

    Van Ruymbeke, M.; Hallot, P.; Billen, R.

    2017-08-01

    Modelling cultural heritage and archaeological objects is used as much for management as for research purposes. To ensure the sustainable benefit of digital data, models benefit from taking the data specificities of historical and archaeological domains into account. Starting from a conceptual model tailored to storing these specificities, we present, in this paper, an extended mapping to CIDOC-CRM and its compatible models. Offering an ideal framework to structure and highlight the best modelling practices, these ontologies are essentially dedicated to storing semantic data which provides information about cultural heritage objects. Based on this standard, our proposal focuses on multiple interpretation and sequential reality.

  14. Risk of the Maritime Supply Chain System Based on Interpretative Structural Model

    Directory of Open Access Journals (Sweden)

    Jiang He

    2017-11-01

    Full Text Available Marine transportation is the most important transport mode of in the international trade, but the maritime supply chain is facing with many risks. At present, most of the researches on the risk of the maritime supply chain focus on the risk identification and risk management, and barely carry on the quantitative analysis of the logical structure of each influencing factor. This paper uses the interpretative structure model to analysis the maritime supply chain risk system. On the basis of comprehensive literature analysis and expert opinion, this paper puts forward 16 factors of maritime supply chain risk system. Using the interpretative structure model to construct maritime supply chain risk system, and then optimize the model. The model analyzes the structure of the maritime supply chain risk system and its forming process, and provides a scientific basis for the controlling the maritime supply chain risk, and puts forward some corresponding suggestions for the prevention and control the maritime supply chain risk.

  15. Interpretation of structural data on superionic conductors in terms of the hindered-rotation diffusion model

    International Nuclear Information System (INIS)

    Polyakov, V.I.

    2000-01-01

    Basic notions of a hindered-rotation diffusion model, which permits refining and supplementing the interpretation of structural and dynamic data obtained when studying superionic conductors, are briefly described. Using the model, dynamic features of β-AgI structure and the compound near order, studied by the EXAFS method, are considered, relative intensities of the Debye peaks in X-ray patterns for superionic conductors AgI and Ag 3 SI being refined [ru

  16. Applying total interpretive structural modeling to study factors affecting construction labour productivity

    Directory of Open Access Journals (Sweden)

    Sayali Shrikrishna Sandbhor

    2014-03-01

    Full Text Available Construction sector has always been dependent on manpower. Most of the activities carried out on any construction site are labour intensive. Since productivity of any project depends directly on productivity of labour, it is a prime responsibility of the employer to enhance labour productivity. Measures to improve the same depend on analysis of positive and negative factors affecting productivity. Major attention should be given to factors that decrease the productivity of labour. Factor analysis thus is an integral part of any study aiming to improve productivity.  Interpretive structural modeling is a methodology for identifying and summarizing relationships among factors which define an issue or problem. It provides a means to arrange the factors in an order as per their complexity. This study attempts to use the latest version of interpretive structural modeling i.e. total interpretive structural modeling to analyze factors negatively affecting construction labour productivity. It establishes interpretive relationship among these factors facilitating improvement in the overall productivity of construction site.

  17. Interpretation of the Superpave IDT strength test using a viscoelastic-damage constitutive model

    Science.gov (United States)

    Onifade, Ibrahim; Balieu, Romain; Birgisson, Bjorn

    2016-08-01

    This paper presents a new interpretation for the Superpave IDT strength test based on a viscoelastic-damage framework. The framework is based on continuum damage mechanics and the thermodynamics of irreversible processes with an anisotropic damage representation. The new approach introduces considerations for the viscoelastic effects and the damage accumulation that accompanies the fracture process in the interpretation of the Superpave IDT strength test for the identification of the Dissipated Creep Strain Energy (DCSE) limit from the test result. The viscoelastic model is implemented in a Finite Element Method (FEM) program for the simulation of the Superpave IDT strength test. The DCSE values obtained using the new approach is compared with the values obtained using the conventional approach to evaluate the validity of the assumptions made in the conventional interpretation of the test results. The result shows that the conventional approach over-estimates the DCSE value with increasing estimation error at higher deformation rates.

  18. Social networks enabled coordination model for cost management of patient hospital admissions.

    Science.gov (United States)

    Uddin, Mohammed Shahadat; Hossain, Liaquat

    2011-09-01

    In this study, we introduce a social networks enabled coordination model for exploring the effect of network position of "patient," "physician," and "hospital" actors in a patient-centered care network that evolves during patient hospitalization period on the total cost of coordination. An actor is a node, which represents an entity such as individual and organization in a social network. In our analysis of actor networks and coordination in the healthcare literature, we identified that there is significant gap where a number of promising hospital coordination model have been developed (e.g., Guided Care Model, Chronic Care Model) for the current healthcare system focusing on quality of service and patient satisfaction. The health insurance dataset for total hip replacement (THR) from hospital contribution fund, a prominent Australian Health Insurance Company, are analyzed to examine our proposed coordination model. We consider network attributes of degree, connectedness, in-degree, out-degree, and tie strength to measure network position of actors. To measure the cost of coordination for a particular hospital, average of total hospitalization expenses for all THR hospital admissions is used. Results show that network positions of "patient," "physician," and "hospital" actors considering all hospital admissions that a particular hospital has have effect on the average of total hospitalization expenses of that hospital. These results can be used as guidelines to set up a cost-effective healthcare practice structure for patient hospitalization expenses. © 2011 National Association for Healthcare Quality.

  19. Antagonism and Mutual Dependency. Critial Models of Performance and “Piano Interpretation Schools”

    Directory of Open Access Journals (Sweden)

    Rui Cruz

    2011-12-01

    Full Text Available To polarize and, coincidently, intersect two different concepts, in terms of a distinction/analogy between “piano interpretation schools” and “critical models” is the aim of this paper. The former, with its prior connotations of both empiricism and dogmatism and not directly shaped by aesthetic criteria or interpretational ideals, depends mainly on the aural and oral tradition as well the teacher-student legacy; the latter employs ideally the generic criteria of interpretativeness, which can be measured in accordance to an aesthetic formula and can include features such as non-obviousness, inferentially, lack of consensus, concern with meaning or significance, concern with structure or design, etc. The relative autonomy of the former is a challenge to the latter, which embraces the range of perspectives available in the horizon of the history of ideas about music and interpretation. The effort of recognizing models of criticism within musical interpretation creates the vehicle for new understandings of the nature and the historical development of Western classical piano performance, promoting also the production of quality critical argument and the communication of key performance tendencies and styles.

  20. Pattern recognition and lithological interpretation of collocated seismic and magnetotelluric models using self-organizing maps

    Science.gov (United States)

    Bauer, K.; Muñoz, G.; Moeck, I.

    2012-05-01

    Joint interpretation of models from seismic tomography and inversion of magnetotelluric (MT) data is an efficient approach to determine the lithology of the subsurface. Statistical methods are well established but were developed for only two types of models so far (seismic P velocity and electrical resistivity). We apply self-organizing maps (SOMs), which have no limitations in the number of parameters considered in the joint interpretation. Our SOM method includes (1) generation of data vectors from the seismic and MT images, (2) unsupervised learning, (3) definition of classes by algorithmic segmentation of the SOM using image processing techniques and (4) application of learned knowledge to classify all data vectors and assign a lithological interpretation for each data vector. We apply the workflow to collocated P velocity, vertical P-velocity gradient and resistivity models derived along a 40 km profile around the geothermal site Groß Schönebeck in the Northeast German Basin. The resulting lithological model consists of eight classes covering Cenozoic, Mesozoic and Palaeozoic sediments down to 5 km depth. There is a remarkable agreement between the litho-type distribution from the SOM analysis and regional marker horizons interpolated from sparse 2-D industrial reflection seismic data. The most interesting features include (1) characteristic properties of the Jurassic (low P-velocity gradients, low resistivity values) interpreted as the signature of shales, and (2) a pattern within the Upper Permian Zechstein layer with low resistivity and increased P-velocity values within the salt depressions and increased resistivity and decreased P velocities in the salt pillows. The latter is explained in our interpretation by flow of less dense salt matrix components to form the pillows while denser and more brittle evaporites such as anhydrite remain in place during the salt mobilization.

  1. Statistical analysis of road-vehicle-driver interaction as an enabler to designing behavioural models

    International Nuclear Information System (INIS)

    Chakravarty, T; Chowdhury, A; Ghose, A; Bhaumik, C; Balamuralidhar, P

    2014-01-01

    Telematics form an important technology enabler for intelligent transportation systems. By deploying on-board diagnostic devices, the signatures of vehicle vibration along with its location and time are recorded. Detailed analyses of the collected signatures offer deep insights into the state of the objects under study. Towards that objective, we carried out experiments by deploying telematics device in one of the office bus that ferries employees to office and back. Data is being collected from 3-axis accelerometer, GPS, speed and the time for all the journeys. In this paper, we present initial results of the above exercise by applying statistical methods to derive information through systematic analysis of the data collected over four months. It is demonstrated that the higher order derivative of the measured Z axis acceleration samples display the properties Weibull distribution when the time axis is replaced by the amplitude of such processed acceleration data. Such an observation offers us a method to predict future behaviour where deviations from prediction are classified as context-based aberrations or progressive degradation of the system. In addition we capture the relationship between speed of the vehicle and median of the jerk energy samples using regression analysis. Such results offer an opportunity to develop a robust method to model road-vehicle interaction thereby enabling us to predict such like driving behaviour and condition based maintenance etc

  2. Supporting interpretation of dynamic simulation. Application to chemical kinetic models; Aides a l`interpretation de simulations dynamiques. Application aux modeles de cinetique chimique

    Energy Technology Data Exchange (ETDEWEB)

    Braunschweig, B.

    1998-04-22

    Numerous scientific and technical domains make constant use of dynamical simulations. Such simulators are put in the hands of a growing number of users. This phenomenon is due both to the extraordinary increase in computing performance, and to better graphical user interfaces which make simulation models easy to operate. But simulators are still computer programs which produce series of numbers from other series of numbers, even if they are displayed graphically. This thesis presents new interaction paradigms between a dynamical simulator and its user. The simulator produces a self-made interpretation of its results, thanks to a dedicated representation of its domain with objects. It shows dominant cyclic mechanisms identified by their instantaneous loop gain estimates, it uses a notion of episodes for splitting the simulation into homogeneous time intervals, and completes this by animations which rely on the graphical structure of the system. These new approaches are demonstrated with examples from chemical kinetics, because of the energic and exemplary characteristics of the encountered behaviors. They are implemented in the Spike software, Software Platform for Interactive Chemical Kinetics Experiments. Similar concepts are also shown in two other domains: interpretation of seismic wave propagation, and simulation of large projects. (author) 95 refs.

  3. [Interpretative method as a synthesis of explicative, teleologic and analogic models].

    Science.gov (United States)

    Yáñez Cortés, R

    1980-06-01

    To establish the basis of the interpretative method is congruous with finding a solid basis--epistemologically speaking--to the analytic theory. This basis would be the means to transform this theory into a real science with its necessary adecuation among method, act and object of knowledge. It is only from a scientific stand that the psychoanalytic theory will be able to face successfully the reductionisms that menace it, be it the biologist-naturalism with its explanations of the psychic phenomena by means of mechanisms and biologic models or be it the speculative ideologies with their nucleus of technical praxis which make it impossible for the social-factic sciences to become real sciences. We propose as interpretative method the union of two models: the teleologic one which makes possible the appearance of intelligible, contingent and variable explanations between an antecedent and a consequent on one side, and on the other, the analogic model with its two moments: the comparative and the symbolic one. These moments makes possible the comparison and the union between antecedent and consequent baring in mind the "natural" ambiguity of the subject-object in question. The principal objective of the method--as a regulative idea in the Kantian sense--would be the search of univocity as regards the choice of one and only one sense from all the possible senses that "explain" the motive relationship or motive-end relationship in order to make the interpretation scientific. This status of scientificity should obey the rules of explanation: that the interpretations be derived effectively from the presupposed theory, that they really explain what they claim to explain, that they are not contradictory or contrary in the same ontologic level. We postulate that the synthesis of the two mentioned models, the teleologic-explanative and the analogic one allows us to find a possibility to make clear the "dark" sense of the noun interpretation and in this way the factibility of

  4. A Novel Experimental and Modelling Strategy for Nanoparticle Toxicity Testing Enabling the Use of Small Quantities

    Directory of Open Access Journals (Sweden)

    Marinda van Pomeren

    2017-11-01

    Full Text Available Metallic nanoparticles (NPs differ from other metal forms with respect to their large surface to volume ratio and subsequent inherent reactivity. Each new modification to a nanoparticle alters the surface to volume ratio, fate and subsequently the toxicity of the particle. Newly-engineered NPs are commonly available only in low quantities whereas, in general, rather large amounts are needed for fate characterizations and effect studies. This challenge is especially relevant for those NPs that have low inherent toxicity combined with low bioavailability. Therefore, within our study, we developed new testing strategies that enable working with low quantities of NPs. The experimental testing method was tailor-made for NPs, whereas we also developed translational models based on different dose-metrics allowing to determine dose-response predictions for NPs. Both the experimental method and the predictive models were verified on the basis of experimental effect data collected using zebrafish embryos exposed to metallic NPs in a range of different chemical compositions and shapes. It was found that the variance in the effect data in the dose-response predictions was best explained by the minimal diameter of the NPs, whereas the data confirmed that the predictive model is widely applicable to soluble metallic NPs. The experimental and model approach developed in our study support the development of (ecotoxicity assays tailored to nano-specific features.

  5. A Novel Experimental and Modelling Strategy for Nanoparticle Toxicity Testing Enabling the Use of Small Quantities.

    Science.gov (United States)

    van Pomeren, Marinda; Peijnenburg, Willie J G M; Brun, Nadja R; Vijver, Martina G

    2017-11-06

    Metallic nanoparticles (NPs) differ from other metal forms with respect to their large surface to volume ratio and subsequent inherent reactivity. Each new modification to a nanoparticle alters the surface to volume ratio, fate and subsequently the toxicity of the particle. Newly-engineered NPs are commonly available only in low quantities whereas, in general, rather large amounts are needed for fate characterizations and effect studies. This challenge is especially relevant for those NPs that have low inherent toxicity combined with low bioavailability. Therefore, within our study, we developed new testing strategies that enable working with low quantities of NPs. The experimental testing method was tailor-made for NPs, whereas we also developed translational models based on different dose-metrics allowing to determine dose-response predictions for NPs. Both the experimental method and the predictive models were verified on the basis of experimental effect data collected using zebrafish embryos exposed to metallic NPs in a range of different chemical compositions and shapes. It was found that the variance in the effect data in the dose-response predictions was best explained by the minimal diameter of the NPs, whereas the data confirmed that the predictive model is widely applicable to soluble metallic NPs. The experimental and model approach developed in our study support the development of (eco)toxicity assays tailored to nano-specific features.

  6. Modeling of RFID-Enabled Real-Time Manufacturing Execution System in Mixed-Model Assembly Lines

    Directory of Open Access Journals (Sweden)

    Zhixin Yang

    2015-01-01

    Full Text Available To quickly respond to the diverse product demands, mixed-model assembly lines are well adopted in discrete manufacturing industries. Besides the complexity in material distribution, mixed-model assembly involves a variety of components, different process plans and fast production changes, which greatly increase the difficulty for agile production management. Aiming at breaking through the bottlenecks in existing production management, a novel RFID-enabled manufacturing execution system (MES, which is featured with real-time and wireless information interaction capability, is proposed to identify various manufacturing objects including WIPs, tools, and operators, etc., and to trace their movements throughout the production processes. However, being subject to the constraints in terms of safety stock, machine assignment, setup, and scheduling requirements, the optimization of RFID-enabled MES model for production planning and scheduling issues is a NP-hard problem. A new heuristical generalized Lagrangian decomposition approach has been proposed for model optimization, which decomposes the model into three subproblems: computation of optimal configuration of RFID senor networks, optimization of production planning subjected to machine setup cost and safety stock constraints, and optimization of scheduling for minimized overtime. RFID signal processing methods that could solve unreliable, redundant, and missing tag events are also described in detail. The model validity is discussed through algorithm analysis and verified through numerical simulation. The proposed design scheme has important reference value for the applications of RFID in multiple manufacturing fields, and also lays a vital research foundation to leverage digital and networked manufacturing system towards intelligence.

  7. Random generalized linear model: a highly accurate and interpretable ensemble predictor.

    Science.gov (United States)

    Song, Lin; Langfelder, Peter; Horvath, Steve

    2013-01-16

    Ensemble predictors such as the random forest are known to have superior accuracy but their black-box predictions are difficult to interpret. In contrast, a generalized linear model (GLM) is very interpretable especially when forward feature selection is used to construct the model. However, forward feature selection tends to overfit the data and leads to low predictive accuracy. Therefore, it remains an important research goal to combine the advantages of ensemble predictors (high accuracy) with the advantages of forward regression modeling (interpretability). To address this goal several articles have explored GLM based ensemble predictors. Since limited evaluations suggested that these ensemble predictors were less accurate than alternative predictors, they have found little attention in the literature. Comprehensive evaluations involving hundreds of genomic data sets, the UCI machine learning benchmark data, and simulations are used to give GLM based ensemble predictors a new and careful look. A novel bootstrap aggregated (bagged) GLM predictor that incorporates several elements of randomness and instability (random subspace method, optional interaction terms, forward variable selection) often outperforms a host of alternative prediction methods including random forests and penalized regression models (ridge regression, elastic net, lasso). This random generalized linear model (RGLM) predictor provides variable importance measures that can be used to define a "thinned" ensemble predictor (involving few features) that retains excellent predictive accuracy. RGLM is a state of the art predictor that shares the advantages of a random forest (excellent predictive accuracy, feature importance measures, out-of-bag estimates of accuracy) with those of a forward selected generalized linear model (interpretability). These methods are implemented in the freely available R software package randomGLM.

  8. The Nuclear Energy Advanced Modeling and Simulation Enabling Computational Technologies FY09 Report

    Energy Technology Data Exchange (ETDEWEB)

    Diachin, L F; Garaizar, F X; Henson, V E; Pope, G

    2009-10-12

    In this document we report on the status of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Enabling Computational Technologies (ECT) effort. In particular, we provide the context for ECT In the broader NEAMS program and describe the three pillars of the ECT effort, namely, (1) tools and libraries, (2) software quality assurance, and (3) computational facility (computers, storage, etc) needs. We report on our FY09 deliverables to determine the needs of the integrated performance and safety codes (IPSCs) in these three areas and lay out the general plan for software quality assurance to meet the requirements of DOE and the DOE Advanced Fuel Cycle Initiative (AFCI). We conclude with a brief description of our interactions with the Idaho National Laboratory computer center to determine what is needed to expand their role as a NEAMS user facility.

  9. Enabling Data Fusion via a Common Data Model and Programming Interface

    Science.gov (United States)

    Lindholm, D. M.; Wilson, A.

    2011-12-01

    Much progress has been made in scientific data interoperability, especially in the areas of metadata and discovery. However, while a data user may have improved techniques for finding data, there is often a large chasm to span when it comes to acquiring the desired subsets of various datasets and integrating them into a data processing environment. Some tools such as OPeNDAP servers and the Unidata Common Data Model (CDM) have introduced improved abstractions for accessing data via a common interface, but they alone do not go far enough to enable fusion of data from multidisciplinary sources. Although data from various scientific disciplines may represent semantically similar concepts (e.g. time series), the user may face widely varying structural representations of the data (e.g. row versus column oriented), not to mention radically different storage formats. It is not enough to convert data to a common format. The key to fusing scientific data is to represent each dataset with consistent sampling. This can best be done by using a data model that expresses the functional relationship that each dataset represents. The domain of those functions determines how the data can be combined. The Visualization for Algorithm Development (VisAD) Java API has provided a sophisticated data model for representing the functional nature of scientific datasets for well over a decade. Because VisAD is largely designed for its visualization capabilities, the data model can be cumbersome to use for numerical computation, especially for those not comfortable with Java. Although both VisAD and the implementation of the CDM are written in Java, neither defines a pure Java interface that others could implement and program to, further limiting potential for interoperability. In this talk, we will present a solution for data integration based on a simple discipline-agnostic scientific data model and programming interface that enables a dataset to be defined in terms of three variable types

  10. RWater - A Novel Cyber-enabled Data-driven Educational Tool for Interpreting and Modeling Hydrologic Processes

    Science.gov (United States)

    Rajib, M. A.; Merwade, V.; Zhao, L.; Song, C.

    2014-12-01

    Explaining the complex cause-and-effect relationships in hydrologic cycle can often be challenging in a classroom with the use of traditional teaching approaches. With the availability of observed rainfall, streamflow and other hydrology data on the internet, it is possible to provide the necessary tools to students to explore these relationships and enhance their learning experience. From this perspective, a new online educational tool, called RWater, is developed using Purdue University's HUBzero technology. RWater's unique features include: (i) its accessibility including the R software from any java supported web browser; (ii) no installation of any software on user's computer; (iii) all the work and resulting data are stored in user's working directory on RWater server; and (iv) no prior programming experience with R software is necessary. In its current version, RWater can dynamically extract streamflow data from any USGS gaging station without any need for post-processing for use in the educational modules. By following data-driven modules, students can write small scripts in R and thereby create visualizations to identify the effect of rainfall distribution and watershed characteristics on runoff generation, investigate the impacts of landuse and climate change on streamflow, and explore the changes in extreme hydrologic events in actual locations. Each module contains relevant definitions, instructions on data extraction and coding, as well as conceptual questions based on the possible analyses which the students would perform. In order to assess its suitability in classroom implementation, and to evaluate users' perception over its utility, the current version of RWater has been tested with three different groups: (i) high school students, (ii) middle and high school teachers; and (iii) upper undergraduate/graduate students. The survey results from these trials suggest that the RWater has potential to improve students' understanding on various relationships in hydrologic cycle, leading towards effective dissemination of hydrology education ranging from K-12 to the graduate level. RWater is a publicly available for use at: https://mygeohub.org/tools/rwater.

  11. Numerical Well Testing Interpretation Model and Applications in Crossflow Double-Layer Reservoirs by Polymer Flooding

    Directory of Open Access Journals (Sweden)

    Haiyang Yu

    2014-01-01

    Full Text Available This work presents numerical well testing interpretation model and analysis techniques to evaluate formation by using pressure transient data acquired with logging tools in crossflow double-layer reservoirs by polymer flooding. A well testing model is established based on rheology experiments and by considering shear, diffusion, convection, inaccessible pore volume (IPV, permeability reduction, wellbore storage effect, and skin factors. The type curves were then developed based on this model, and parameter sensitivity is analyzed. Our research shows that the type curves have five segments with different flow status: (I wellbore storage section, (II intermediate flow section (transient section, (III mid-radial flow section, (IV crossflow section (from low permeability layer to high permeability layer, and (V systematic radial flow section. The polymer flooding field tests prove that our model can accurately determine formation parameters in crossflow double-layer reservoirs by polymer flooding. Moreover, formation damage caused by polymer flooding can also be evaluated by comparison of the interpreted permeability with initial layered permeability before polymer flooding. Comparison of the analysis of numerical solution based on flow mechanism with observed polymer flooding field test data highlights the potential for the application of this interpretation method in formation evaluation and enhanced oil recovery (EOR.

  12. Interpretive Structural Model of Key Performance Indicators for Sustainable Maintenance Evaluatian in Rubber Industry

    Science.gov (United States)

    Amrina, E.; Yulianto, A.

    2018-03-01

    Sustainable maintenance is a new challenge for manufacturing companies to realize sustainable development. In this paper, an interpretive structural model is developed to evaluate sustainable maintenance in the rubber industry. The initial key performance indicators (KPIs) is identified and derived from literature and then validated by academic and industry experts. As a result, three factors of economic, social, and environmental dividing into a total of thirteen indicators are proposed as the KPIs for sustainable maintenance evaluation in rubber industry. Interpretive structural modeling (ISM) methodology is applied to develop a network structure model of the KPIs consisting of three levels. The results show the economic factor is regarded as the basic factor, the social factor as the intermediate factor, while the environmental factor indicated to be the leading factor. Two indicators of social factor i.e. labor relationship, and training and education have both high driver and dependence power, thus categorized as the unstable indicators which need further attention. All the indicators of environmental factor and one indicator of social factor are indicated as the most influencing indicator. The interpretive structural model hoped can aid the rubber companies in evaluating sustainable maintenance performance.

  13. Using global magnetospheric models for simulation and interpretation of Swarm external field measurements

    DEFF Research Database (Denmark)

    Moretto, T.; Vennerstrøm, Susanne; Olsen, Nils

    2006-01-01

    simulated external contributions relevant for internal field modeling. These have proven very valuable for the design and planning of the up-coming multi-satellite Swarm mission. In addition, a real event simulation was carried out for a moderately active time interval when observations from the Orsted...... it consistently underestimates the dayside region 2 currents and overestimates the horizontal ionospheric closure currents in the dayside polar cap. Furthermore, with this example we illustrate the great benefit of utilizing the global model for the interpretation of Swarm external field observations and......, likewise, the potential of using Swarm measurements to test and improve the global model....

  14. Nonlinear Synapses for Large-Scale Models: An Efficient Representation Enables Complex Synapse Dynamics Modeling in Large-Scale Simulations

    Directory of Open Access Journals (Sweden)

    Eric eHu

    2015-09-01

    Full Text Available Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.

  15. Structural interpretation of El Hierro (Canary Islands) rifts system from gravity inversion modelling

    Science.gov (United States)

    Sainz-Maza, S.; Montesinos, F. G.; Martí, J.; Arnoso, J.; Calvo, M.; Borreguero, A.

    2017-08-01

    Recent volcanism in El Hierro Island is mostly concentrated along three elongated and narrow zones which converge at the center of the island. These zones with extensive volcanism have been identified as rift zones. The presence of similar structures is common in many volcanic oceanic islands, so understanding their origin, dynamics and structure is important to conduct hazard assessment in such environments. There is still not consensus on the origin of the El Hierro rift zones, having been associated with mantle uplift or interpreted as resulting from gravitational spreading and flank instability. To further understand the internal structure and origin of the El Hierro rift systems, starting from the previous gravity studies, we developed a new 3D gravity inversion model for its shallower layers, gathering a detailed picture of this part of the island, which has permitted a new interpretation about these rifts. Previous models already identified a main central magma accumulation zone and several shallower high density bodies. The new model allows a better resolution of the pathways that connect both levels and the surface. Our results do not point to any correspondence between the upper parts of these pathways and the rift identified at the surface. Non-clear evidence of progression toward deeper parts into the volcanic system is shown, so we interpret them as very shallow structures, probably originated by local extensional stresses derived from gravitational loading and flank instability, which are used to facilitate the lateral transport of magma when it arrives close to the surface.

  16. A study of well test data interpretation model for waterbearing reservoirs with phase redistribution

    Science.gov (United States)

    Zhang, Junxiang; Deng, Rui; Liang, Haipeng; Yang, Jing

    2017-05-01

    In China, plentiful marine reservoirs exist. Net pay thickness in individual gas reservoirs where partial penetration was performed can be hundreds of meters. Due to the influence of condensate water and formation, water phase separation phenomenon, where gas rose up and liquid moved down, and a morsel of water production emerged in some gas wells, which makes the build-up curves distorted and thus unable to be interpreted. On the basis of seepage theory and Laplace transformation, a seepage mathematical model and a well test interpretation model for gas wells with phase separation considered are developed to analyze the impact of such various elements as phase separation and partial penetration on the pressure and pressure derivative log-log plot. With practical data of well test in Xihu Sag, reliability analysis of the mathematical model mentioned above was demonstrated. Theoretical research results proposed in our study substantially improved the accuracy of well test interpretation for thick water-bearing gas reservoirs and laid a technical foundation of development of the similar oil & gas reservoirs.

  17. An approach based on Hierarchical Bayesian Graphical Models for measurement interpretation under uncertainty

    Science.gov (United States)

    Skataric, Maja; Bose, Sandip; Zeroug, Smaine; Tilke, Peter

    2017-02-01

    It is not uncommon in the field of non-destructive evaluation that multiple measurements encompassing a variety of modalities are available for analysis and interpretation for determining the underlying states of nature of the materials or parts being tested. Despite and sometimes due to the richness of data, significant challenges arise in the interpretation manifested as ambiguities and inconsistencies due to various uncertain factors in the physical properties (inputs), environment, measurement device properties, human errors, and the measurement data (outputs). Most of these uncertainties cannot be described by any rigorous mathematical means, and modeling of all possibilities is usually infeasible for many real time applications. In this work, we will discuss an approach based on Hierarchical Bayesian Graphical Models (HBGM) for the improved interpretation of complex (multi-dimensional) problems with parametric uncertainties that lack usable physical models. In this setting, the input space of the physical properties is specified through prior distributions based on domain knowledge and expertise, which are represented as Gaussian mixtures to model the various possible scenarios of interest for non-destructive testing applications. Forward models are then used offline to generate the expected distribution of the proposed measurements which are used to train a hierarchical Bayesian network. In Bayesian analysis, all model parameters are treated as random variables, and inference of the parameters is made on the basis of posterior distribution given the observed data. Learned parameters of the posterior distribution obtained after the training can therefore be used to build an efficient classifier for differentiating new observed data in real time on the basis of pre-trained models. We will illustrate the implementation of the HBGM approach to ultrasonic measurements used for cement evaluation of cased wells in the oil industry.

  18. Enabling Grid Computing resources within the KM3NeT computing model

    Directory of Open Access Journals (Sweden)

    Filippidis Christos

    2016-01-01

    Full Text Available KM3NeT is a future European deep-sea research infrastructure hosting a new generation neutrino detectors that – located at the bottom of the Mediterranean Sea – will open a new window on the universe and answer fundamental questions both in particle physics and astrophysics. International collaborative scientific experiments, like KM3NeT, are generating datasets which are increasing exponentially in both complexity and volume, making their analysis, archival, and sharing one of the grand challenges of the 21st century. These experiments, in their majority, adopt computing models consisting of different Tiers with several computing centres and providing a specific set of services for the different steps of data processing such as detector calibration, simulation and data filtering, reconstruction and analysis. The computing requirements are extremely demanding and, usually, span from serial to multi-parallel or GPU-optimized jobs. The collaborative nature of these experiments demands very frequent WAN data transfers and data sharing among individuals and groups. In order to support the aforementioned demanding computing requirements we enabled Grid Computing resources, operated by EGI, within the KM3NeT computing model. In this study we describe our first advances in this field and the method for the KM3NeT users to utilize the EGI computing resources in a simulation-driven use-case.

  19. The Role of Stochastic Models in Interpreting the Origins of Biological Chirality

    Directory of Open Access Journals (Sweden)

    Gábor Lente

    2010-04-01

    Full Text Available This review summarizes recent stochastic modeling efforts in the theoretical research aimed at interpreting the origins of biological chirality. Stochastic kinetic models, especially those based on the continuous time discrete state approach, have great potential in modeling absolute asymmetric reactions, experimental examples of which have been reported in the past decade. An overview of the relevant mathematical background is given and several examples are presented to show how the significant numerical problems characteristic of the use of stochastic models can be overcome by non-trivial, but elementary algebra. In these stochastic models, a particulate view of matter is used rather than the concentration-based view of traditional chemical kinetics using continuous functions to describe the properties system. This has the advantage of giving adequate description of single-molecule events, which were probably important in the origin of biological chirality. The presented models can interpret and predict the random distribution of enantiomeric excess among repetitive experiments, which is the most striking feature of absolute asymmetric reactions. It is argued that the use of the stochastic kinetic approach should be much more widespread in the relevant literature.

  20. PBPK and population modelling to interpret urine cadmium concentrations of the French population

    International Nuclear Information System (INIS)

    Béchaux, Camille; Bodin, Laurent; Clémençon, Stéphan; Crépet, Amélie

    2014-01-01

    As cadmium accumulates mainly in kidney, urinary concentrations are considered as relevant data to assess the risk related to cadmium. The French Nutrition and Health Survey (ENNS) recorded the concentration of cadmium in the urine of the French population. However, as with all biomonitoring data, it needs to be linked to external exposure for it to be interpreted in term of sources of exposure and for risk management purposes. The objective of this work is thus to interpret the cadmium biomonitoring data of the French population in terms of dietary and cigarette smoke exposures. Dietary and smoking habits recorded in the ENNS study were combined with contamination levels in food and cigarettes to assess individual exposures. A PBPK model was used in a Bayesian population model to link this external exposure with the measured urinary concentrations. In this model, the level of the past exposure was corrected thanks to a scaling function which account for a trend in the French dietary exposure. It resulted in a modelling which was able to explain the current urinary concentrations measured in the French population through current and past exposure levels. Risk related to cadmium exposure in the general French population was then assessed from external and internal critical values corresponding to kidney effects. The model was also applied to predict the possible urinary concentrations of the French population in 2030 assuming there will be no more changes in the exposures levels. This scenario leads to significantly lower concentrations and consequently lower related risk. - Highlights: • Interpretation of urine cadmium concentrations in France • PBPK and Bayesian population modelling of cadmium exposure • Assessment of the historic time-trend of the cadmium exposure in France • Risk assessment from current and future external and internal exposure

  1. PBPK and population modelling to interpret urine cadmium concentrations of the French population

    Energy Technology Data Exchange (ETDEWEB)

    Béchaux, Camille, E-mail: Camille.bechaux@anses.fr [ANSES, French Agency for Food, Environmental and Occupational Health Safety, 27-31 Avenue du Général Leclerc, 94701 Maisons-Alfort (France); Bodin, Laurent [ANSES, French Agency for Food, Environmental and Occupational Health Safety, 27-31 Avenue du Général Leclerc, 94701 Maisons-Alfort (France); Clémençon, Stéphan [Telecom ParisTech, 46 rue Barrault, 75634 Paris Cedex 13 (France); Crépet, Amélie [ANSES, French Agency for Food, Environmental and Occupational Health Safety, 27-31 Avenue du Général Leclerc, 94701 Maisons-Alfort (France)

    2014-09-15

    As cadmium accumulates mainly in kidney, urinary concentrations are considered as relevant data to assess the risk related to cadmium. The French Nutrition and Health Survey (ENNS) recorded the concentration of cadmium in the urine of the French population. However, as with all biomonitoring data, it needs to be linked to external exposure for it to be interpreted in term of sources of exposure and for risk management purposes. The objective of this work is thus to interpret the cadmium biomonitoring data of the French population in terms of dietary and cigarette smoke exposures. Dietary and smoking habits recorded in the ENNS study were combined with contamination levels in food and cigarettes to assess individual exposures. A PBPK model was used in a Bayesian population model to link this external exposure with the measured urinary concentrations. In this model, the level of the past exposure was corrected thanks to a scaling function which account for a trend in the French dietary exposure. It resulted in a modelling which was able to explain the current urinary concentrations measured in the French population through current and past exposure levels. Risk related to cadmium exposure in the general French population was then assessed from external and internal critical values corresponding to kidney effects. The model was also applied to predict the possible urinary concentrations of the French population in 2030 assuming there will be no more changes in the exposures levels. This scenario leads to significantly lower concentrations and consequently lower related risk. - Highlights: • Interpretation of urine cadmium concentrations in France • PBPK and Bayesian population modelling of cadmium exposure • Assessment of the historic time-trend of the cadmium exposure in France • Risk assessment from current and future external and internal exposure.

  2. An Empirically-Calibrated Model For Interpreting the Evolution of Galaxies During the Reionization Era

    OpenAIRE

    Stark, Daniel P.; Loeb, Abraham; Ellis, Richard S.

    2007-01-01

    [Abridged] We develop a simple star formation model whose goal is to interpret the emerging body of observational data on star-forming galaxies at z>~6. The efficiency and duty cycle of the star formation activity within dark matter halos are determined by fitting the luminosity functions of Lya emitter and Lyman-break galaxies at redshifts z~5-6. Using our model parameters we predict the likely abundance of star forming galaxies at earlier epochs and compare these to the emerging data in the...

  3. The application of release models to the interpretation of rare gas coolant activities

    International Nuclear Information System (INIS)

    Wise, C.

    1985-01-01

    Much research is carried out into the release of fission products from UO 2 fuel and from failed pins. A significant application of this data is to define models of release which can be used to interpret measured coolant activities of rare gas isotopes. Such interpretation is necessary to extract operationally relevant parameters, such as the number and size of failures in the core and the 131 I that might be released during depressurization faults. The latter figure forms part of the safety case for all operating CAGRs. This paper describes and justifies the models which are used in the ANAGRAM program to interpret CAGR coolant activities, highlighting any remaining uncertainties. The various methods by which the program can extract relevant information from the measurements are outlined, and examples are given of the analysis of coolant data. These analyses point to a generally well understood picture of fission gas release from low temperature failures. Areas of higher temperature release are identified where further research would be beneficial to coolant activity analysis. (author)

  4. The use of cloud enabled building information models – an expert analysis

    Directory of Open Access Journals (Sweden)

    Alan Redmond

    2015-10-01

    Full Text Available The dependency of today’s construction professionals to use singular commercial applications for design possibilities creates the risk of being dictated by the language-tools they use. This unknowingly approach to converting to the constraints of a particular computer application’s style, reduces one’s association with cutting-edge design as no single computer application can support all of the tasks associated with building-design and production. Interoperability depicts the need to pass data between applications, allowing multiple types of experts and applications to contribute to the work at hand. Cloud computing is a centralized heterogeneous platform that enables different applications to be connected to each other through using remote data servers. However, the possibility of providing an interoperable process based on binding several construction applications through a single repository platform ‘cloud computing’ required further analysis. The following Delphi questionnaires analysed the exchanging information opportunities of Building Information Modelling (BIM as the possible solution for the integration of applications on a cloud platform. The survey structure is modelled to; (i identify the most appropriate applications for advancing interoperability at the early design stage, (ii detect the most severe barriers of BIM implementation from a business and legal viewpoint, (iii examine the need for standards to address information exchange between design team, and (iv explore the use of the most common interfaces for exchanging information. The anticipated findings will assist in identifying a model that will enhance the standardized passing of information between systems at the feasibility design stage of a construction project.

  5. The use of cloud enabled building information models – an expert analysis

    Directory of Open Access Journals (Sweden)

    Alan Redmond

    2012-12-01

    Full Text Available The dependency of today’s construction professionals to use singular commercial applications for design possibilities creates the risk of being dictated by the language-tools they use. This unknowingly approach to converting to the constraints of a particular computer application’s style, reduces one’s association with cutting-edge design as no single computer application can support all of the tasks associated with building-design and production. Interoperability depicts the need to pass data between applications, allowing multiple types of experts and applications to contribute to the work at hand. Cloud computing is a centralized heterogeneous platform that enables different applications to be connected to each other through using remote data servers. However, the possibility of providing an interoperable process based on binding several construction applications through a single repository platform ‘cloud computing’ required further analysis. The following Delphi questionnaires analysed the exchanging information opportunities of Building Information Modelling (BIM as the possible solution for the integration of applications on a cloud platform. The survey structure is modelled to; (i identify the most appropriate applications for advancing interoperability at the early design stage, (ii detect the most severe barriers of BIM implementation from a business and legal viewpoint, (iii examine the need for standards to address information exchange between design team, and (iv explore the use of the most common interfaces for exchanging information. The anticipated findings will assist in identifying a model that will enhance the standardized passing of information between systems at the feasibility design stage of a construction project.

  6. Digital structural interpretation of mountain-scale photogrammetric 3D models (Kamnik Alps, Slovenia)

    Science.gov (United States)

    Dolžan, Erazem; Vrabec, Marko

    2015-04-01

    From the earliest days of geological science, mountainous terrains with their extreme topographic relief and sparse to non-existent vegetation were utilized to a great advantage for gaining 3D insight into geological structure. But whereas Alpine vistas may offer perfect panoramic views of geology, the steep mountain slopes and vertical cliffs make it very time-consuming and difficult (if not impossible) to acquire quantitative mapping data such as precisely georeferenced traces of geological boundaries and attitudes of structural planes. We faced this problem in mapping the central Kamnik Alps of northern Slovenia, which are built up from Mid to Late Triassic succession of carbonate rocks. Polyphase brittle tectonic evolution, monotonous lithology and the presence of temporally and spatially irregular facies boundary between bedded platform carbonates and massive reef limestones considerably complicate the structural interpretation of otherwise perfectly exposed, but hardly accessible massif. We used Agisoft Photoscan Structure-from-Motion photogrammetric software to process a series of overlapping high-resolution (~0.25 m ground resolution) vertical aerial photographs originally acquired by the Geodetic Authority of the Republic of Slovenia for surveying purposes, to derive very detailed 3D triangular mesh models of terrain and associated photographic textures. Phototextures are crucial for geological interpretation of the models as they provide additional levels of detail and lithological information which is not resolvable from geometrical mesh models alone. We then exported the models to Paradigm Gocad software to refine and optimize the meshing. Structural interpretation of the models, including mapping of traces and surfaces of faults and stratigraphic boundaries and determining dips of structural planes, was performed in MVE Move suite which offers a range of useful tools for digital mapping and interpretation. Photogrammetric model was complemented by

  7. Interpreting space-based trends in carbon monoxide with multiple models

    Directory of Open Access Journals (Sweden)

    S. A. Strode

    2016-06-01

    Full Text Available We use a series of chemical transport model and chemistry climate model simulations to investigate the observed negative trends in MOPITT CO over several regions of the world, and to examine the consistency of time-dependent emission inventories with observations. We find that simulations driven by the MACCity inventory, used for the Chemistry Climate Modeling Initiative (CCMI, reproduce the negative trends in the CO column observed by MOPITT for 2000–2010 over the eastern United States and Europe. However, the simulations have positive trends over eastern China, in contrast to the negative trends observed by MOPITT. The model bias in CO, after applying MOPITT averaging kernels, contributes to the model–observation discrepancy in the trend over eastern China. This demonstrates that biases in a model's average concentrations can influence the interpretation of the temporal trend compared to satellite observations. The total ozone column plays a role in determining the simulated tropospheric CO trends. A large positive anomaly in the simulated total ozone column in 2010 leads to a negative anomaly in OH and hence a positive anomaly in CO, contributing to the positive trend in simulated CO. These results demonstrate that accurately simulating variability in the ozone column is important for simulating and interpreting trends in CO.

  8. On the use of musculoskeletal models to interpret motor control strategies from performance data

    Science.gov (United States)

    Cheng, Ernest J.; Loeb, Gerald E.

    2008-06-01

    The intrinsic viscoelastic properties of muscle are central to many theories of motor control. Much of the debate over these theories hinges on varying interpretations of these muscle properties. In the present study, we describe methods whereby a comprehensive musculoskeletal model can be used to make inferences about motor control strategies that would account for behavioral data. Muscle activity and kinematic data from a monkey were recorded while the animal performed a single degree-of-freedom pointing task in the presence of pseudo-random torque perturbations. The monkey's movements were simulated by a musculoskeletal model with accurate representations of musculotendon morphometry and contractile properties. The model was used to quantify the impedance of the limb while moving rapidly, the differential action of synergistic muscles, the relative contribution of reflexes to task performance and the completeness of recorded EMG signals. Current methods to address these issues in the absence of musculoskeletal models were compared with the methods used in the present study. We conclude that musculoskeletal models and kinetic analysis can improve the interpretation of kinematic and electrophysiological data, in some cases by illuminating shortcomings of the experimental methods or underlying assumptions that may otherwise escape notice.

  9. Expert judgment based multi-criteria decision model to address uncertainties in risk assessment of nanotechnology-enabled food products

    International Nuclear Information System (INIS)

    Flari, Villie; Chaudhry, Qasim; Neslo, Rabin; Cooke, Roger

    2011-01-01

    Currently, risk assessment of nanotechnology-enabled food products is considered difficult due to the large number of uncertainties involved. We developed an approach which could address some of the main uncertainties through the use of expert judgment. Our approach employs a multi-criteria decision model, based on probabilistic inversion that enables capturing experts’ preferences in regard to safety of nanotechnology-enabled food products, and identifying their opinions in regard to the significance of key criteria that are important in determining the safety of such products. An advantage of these sample-based techniques is that they provide out-of-sample validation and therefore a robust scientific basis. This validation in turn adds predictive power to the model developed. We achieved out-of-sample validation in two ways: (1) a portion of the expert preference data was excluded from the model’s fitting and was then predicted by the model fitted on the remaining rankings and (2) a (partially) different set of experts generated new scenarios, using the same criteria employed in the model, and ranked them; their ranks were compared with ranks predicted by the model. The degree of validation in each method was less than perfect but reasonably substantial. The validated model we applied captured and modelled experts’ preferences regarding safety of hypothetical nanotechnology-enabled food products. It appears therefore that such an approach can provide a promising route to explore further for assessing the risk of nanotechnology-enabled food products.

  10. A grey DEMATEL-based approach for modeling enablers of green innovation in manufacturing organizations.

    Science.gov (United States)

    Gupta, Himanshu; Barua, Mukesh Kumar

    2018-04-01

    Incorporating green practices into the manufacturing process has gained momentum over the past few years and is a matter of great concern for both manufacturers as well as researchers. Regulatory pressures in developed countries have forced the organizations to adopt green practices; however, this issue still lacks attention in developing economies like India. There is an urgent need to identify enablers of green innovation for manufacturing organizations and also to identify prominent enablers among those. This study is an attempt to first identify enablers of green innovation and then establish a causal relationship among them to identify the enablers that can drive others. Grey DEMATEL (Decision Making Trial and Evaluation Laboratory) methodology is used for establishing the causal relationship among enablers. The novelty of this study lies in the fact that no study has been done in the past to identify the enablers of green innovation and then establishing the causal relationship among them. A total of 21 enablers of green innovation have been identified; research indicates developing green manufacturing capabilities, resources for green innovation, ease of getting loans from financial institutions, and environmental regulations as the most influential enablers of green innovation. Managerial and practical implications of the research are also presented to assist managers of the case company in adopting green innovation practices at their end.

  11. The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity

    Science.gov (United States)

    Barretina, Jordi; Caponigro, Giordano; Stransky, Nicolas; Venkatesan, Kavitha; Margolin, Adam A.; Kim, Sungjoon; Wilson, Christopher J.; Lehár, Joseph; Kryukov, Gregory V.; Sonkin, Dmitriy; Reddy, Anupama; Liu, Manway; Murray, Lauren; Berger, Michael F.; Monahan, John E.; Morais, Paula; Meltzer, Jodi; Korejwa, Adam; Jané-Valbuena, Judit; Mapa, Felipa A.; Thibault, Joseph; Bric-Furlong, Eva; Raman, Pichai; Shipway, Aaron; Engels, Ingo H.; Cheng, Jill; Yu, Guoying K.; Yu, Jianjun; Aspesi, Peter; de Silva, Melanie; Jagtap, Kalpana; Jones, Michael D.; Wang, Li; Hatton, Charles; Palescandolo, Emanuele; Gupta, Supriya; Mahan, Scott; Sougnez, Carrie; Onofrio, Robert C.; Liefeld, Ted; MacConaill, Laura; Winckler, Wendy; Reich, Michael; Li, Nanxin; Mesirov, Jill P.; Gabriel, Stacey B.; Getz, Gad; Ardlie, Kristin; Chan, Vivien; Myer, Vic E.; Weber, Barbara L.; Porter, Jeff; Warmuth, Markus; Finan, Peter; Harris, Jennifer L.; Meyerson, Matthew; Golub, Todd R.; Morrissey, Michael P.; Sellers, William R.; Schlegel, Robert; Garraway, Levi A.

    2012-01-01

    The systematic translation of cancer genomic data into knowledge of tumor biology and therapeutic avenues remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacologic annotation is available1. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number, and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacologic profiles for 24 anticancer drugs across 479 of the lines, this collection allowed identification of genetic, lineage, and gene expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Altogether, our results suggest that large, annotated cell line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of “personalized” therapeutic regimens2. PMID:22460905

  12. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

    Science.gov (United States)

    Barretina, Jordi; Caponigro, Giordano; Stransky, Nicolas; Venkatesan, Kavitha; Margolin, Adam A; Kim, Sungjoon; Wilson, Christopher J; Lehár, Joseph; Kryukov, Gregory V; Sonkin, Dmitriy; Reddy, Anupama; Liu, Manway; Murray, Lauren; Berger, Michael F; Monahan, John E; Morais, Paula; Meltzer, Jodi; Korejwa, Adam; Jané-Valbuena, Judit; Mapa, Felipa A; Thibault, Joseph; Bric-Furlong, Eva; Raman, Pichai; Shipway, Aaron; Engels, Ingo H; Cheng, Jill; Yu, Guoying K; Yu, Jianjun; Aspesi, Peter; de Silva, Melanie; Jagtap, Kalpana; Jones, Michael D; Wang, Li; Hatton, Charles; Palescandolo, Emanuele; Gupta, Supriya; Mahan, Scott; Sougnez, Carrie; Onofrio, Robert C; Liefeld, Ted; MacConaill, Laura; Winckler, Wendy; Reich, Michael; Li, Nanxin; Mesirov, Jill P; Gabriel, Stacey B; Getz, Gad; Ardlie, Kristin; Chan, Vivien; Myer, Vic E; Weber, Barbara L; Porter, Jeff; Warmuth, Markus; Finan, Peter; Harris, Jennifer L; Meyerson, Matthew; Golub, Todd R; Morrissey, Michael P; Sellers, William R; Schlegel, Robert; Garraway, Levi A

    2012-03-28

    The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.

  13. Fullrmc, a rigid body Reverse Monte Carlo modeling package enabled with machine learning and artificial intelligence.

    Science.gov (United States)

    Aoun, Bachir

    2016-05-05

    A new Reverse Monte Carlo (RMC) package "fullrmc" for atomic or rigid body and molecular, amorphous, or crystalline materials is presented. fullrmc main purpose is to provide a fully modular, fast and flexible software, thoroughly documented, complex molecules enabled, written in a modern programming language (python, cython, C and C++ when performance is needed) and complying to modern programming practices. fullrmc approach in solving an atomic or molecular structure is different from existing RMC algorithms and software. In a nutshell, traditional RMC methods and software randomly adjust atom positions until the whole system has the greatest consistency with a set of experimental data. In contrast, fullrmc applies smart moves endorsed with reinforcement machine learning to groups of atoms. While fullrmc allows running traditional RMC modeling, the uniqueness of this approach resides in its ability to customize grouping atoms in any convenient way with no additional programming efforts and to apply smart and more physically meaningful moves to the defined groups of atoms. In addition, fullrmc provides a unique way with almost no additional computational cost to recur a group's selection, allowing the system to go out of local minimas by refining a group's position or exploring through and beyond not allowed positions and energy barriers the unrestricted three dimensional space around a group. © 2016 Wiley Periodicals, Inc.

  14. Explicit kinetic heterogeneity: mechanistic models for interpretation of labeling data in heterogeneous populations

    Energy Technology Data Exchange (ETDEWEB)

    Ganusov, Vitaly V [Los Alamos National Laboratory

    2008-01-01

    Estimation of division and death rates of lymphocytes in different conditions is vital for quantitative understanding of the immune system. Deuterium, in the form of deuterated glucose or heavy water, can be used to measure rates of proliferation and death of lymphocytes in vivo. Inferring these rates from labeling and delabeling curves has been subject to considerable debate with different groups suggesting different mathematical models for that purpose. We show that the three models that are most commonly used are in fact mathematically identical and differ only in their interpretation of the estimated parameters. By extending these previous models, we here propose a more mechanistic approach for the analysis of data from deuterium labeling experiments. We construct a model of 'kinetic heterogeneity' in which the total cell population consists of many sub-populations with different rates of cell turnover. In this model, for a given distribution of the rates of turnover, the predicted fraction of labeled DNA accumulated and lost can be calculated. Our model reproduces several previously made experimental observations, such as a negative correlation between the length of the labeling period and the rate at which labeled DNA is lost after label cessation. We demonstrate the reliability of the new explicit kinetic heterogeneity model by applying it to artificially generated datasets, and illustrate its usefulness by fitting experimental data. In contrast to previous models, the explicit kinetic heterogeneity model (1) provides a mechanistic way of interpreting labeling data; (2) allows for a non-exponential loss of labeled cells during delabeling, and (3) can be used to describe data with variable labeling length.

  15. Enabling Parametric Optimal Ascent Trajectory Modeling During Early Phases of Design

    Science.gov (United States)

    Holt, James B.; Dees, Patrick D.; Diaz, Manuel J.

    2015-01-01

    -modal due to the interaction of various constraints. Additionally, when these obstacles are coupled with The Program to Optimize Simulated Trajectories [1] (POST), an industry standard program to optimize ascent trajectories that is difficult to use, it requires expert trajectory analysts to effectively optimize a vehicle's ascent trajectory. As it has been pointed out, the paradigm of trajectory optimization is still a very manual one because using modern computational resources on POST is still a challenging problem. The nuances and difficulties involved in correctly utilizing, and therefore automating, the program presents a large problem. In order to address these issues, the authors will discuss a methodology that has been developed. The methodology is two-fold: first, a set of heuristics will be introduced and discussed that were captured while working with expert analysts to replicate the current state-of-the-art; secondly, leveraging the power of modern computing to evaluate multiple trajectories simultaneously, and therefore, enable the exploration of the trajectory's design space early during the pre-conceptual and conceptual phases of design. When this methodology is coupled with design of experiments in order to train surrogate models, the authors were able to visualize the trajectory design space, enabling parametric optimal ascent trajectory information to be introduced with other pre-conceptual and conceptual design tools. The potential impact of this methodology's success would be a fully automated POST evaluation suite for the purpose of conceptual and preliminary design trade studies. This will enable engineers to characterize the ascent trajectory's sensitivity to design changes in an arbitrary number of dimensions and for finding settings for trajectory specific variables, which result in optimal performance for a "dialed-in" launch vehicle design. The effort described in this paper was developed for the Advanced Concepts Office [2] at NASA Marshall

  16. Institutional analysis of milkfish supply chain using interpretive structural modelling (ISM) (case study of UD. Bunda Foods, Sidoarjo District)

    Science.gov (United States)

    Silalahi, R. L. R.; Mustaniroh, S. A.; Ikasari, D. M.; Sriulina, R. P.

    2018-03-01

    UD. Bunda Foods is an SME located in the district of Sidoarjo. UD. Bunda Foods has problems of maintaining its milkfish’s quality assurance and developing marketing strategies. Improving those problems enables UD. Bunda Foods to compete with other similar SMEs and to market its product for further expansion of their business. The objectives of this study were to determine the model of the institutional structure of the milkfish supply chain, to determine the elements, the sub-elements, and the relationship among each element. The method used in this research was Interpretive Structural Modeling (ISM), involving 5 experts as respondents consisting of 1 practitioner, 1 academician, and 3 government organisation employees. The results showed that there were two key elements include requirement and goals elements. Based on the Drive Power-Dependence (DP-D) matrix, the key sub-elements of requirement element, consisted of raw material continuity, appropriate marketing strategy, and production capital, were positioned in the Linkage sector quadrant. The DP-D matrix for the key sub-elements of the goal element also showed a similar position. The findings suggested several managerial implications to be carried out by UD. Bunda Foods include establishing good relationships with all involved institutions, obtaining capital assistance, and attending the marketing training provided by the government.

  17. Enabling School Structure, Collective Responsibility, and a Culture of Academic Optimism: Toward a Robust Model of School Performance in Taiwan

    Science.gov (United States)

    Wu, Jason H.; Hoy, Wayne K.; Tarter, C. John

    2013-01-01

    Purpose: The purpose of this research is twofold: to test a theory of academic optimism in Taiwan elementary schools and to expand the theory by adding new variables, collective responsibility and enabling school structure, to the model. Design/methodology/approach: Structural equation modeling was used to test, refine, and expand an…

  18. Energy Consumption Model and Measurement Results for Network Coding-enabled IEEE 802.11 Meshed Wireless Networks

    DEFF Research Database (Denmark)

    Paramanathan, Achuthan; Rasmussen, Ulrik Wilken; Hundebøll, Martin

    2012-01-01

    This paper presents an energy model and energy measurements for network coding enabled wireless meshed networks based on IEEE 802.11 technology. The energy model and the energy measurement testbed is limited to a simple Alice and Bob scenario. For this toy scenario we compare the energy usages...

  19. New interpretation of arterial stiffening due to cigarette smoking using a structurally motivated constitutive model

    DEFF Research Database (Denmark)

    Enevoldsen, Majken; Henneberg, K-A; Jensen, J A

    2011-01-01

    Cigarette smoking is the leading self-inflicted risk factor for cardiovascular diseases; it causes arterial stiffening with serious sequelea including atherosclerosis and abdominal aortic aneurysms. This work presents a new interpretation of arterial stiffening caused by smoking based on data...... by smoking was reflected by consistent increase in an elastin-associated parameter and moreover by marked increase in the collagen-associated parameters. That is, we suggest that arterial stiffening due to cigarette smoking appears to be isotropic, which may allow simpler phenomenological models to capture...

  20. Comprehensive Interpretation of the Laboratory Experiments Results to Construct Model of the Polish Shale Gas Rocks

    Science.gov (United States)

    Jarzyna, Jadwiga A.; Krakowska, Paulina I.; Puskarczyk, Edyta; Wawrzyniak-Guz, Kamila; Zych, Marcin

    2018-03-01

    More than 70 rock samples from so-called sweet spots, i.e. the Ordovician Sa Formation and Silurian Ja Member of Pa Formation from the Baltic Basin (North Poland) were examined in the laboratory to determine bulk and grain density, total and effective/dynamic porosity, absolute permeability, pore diameters size, total surface area, and natural radioactivity. Results of the pyrolysis, i.e., TOC (Total Organic Carbon) together with S1 and S2 - parameters used to determine the hydrocarbon generation potential of rocks, were also considered. Elemental composition from chemical analyses and mineral composition from XRD measurements were also included. SCAL analysis, NMR experiments, Pressure Decay Permeability measurements together with water immersion porosimetry and adsorption/ desorption of nitrogen vapors method were carried out along with the comprehensive interpretation of the outcomes. Simple and multiple linear statistical regressions were used to recognize mutual relationships between parameters. Observed correlations and in some cases big dispersion of data and discrepancies in the property values obtained from different methods were the basis for building shale gas rock model for well logging interpretation. The model was verified by the result of the Monte Carlo modelling of spectral neutron-gamma log response in comparison with GEM log results.

  1. Interpretation of ensembles created by multiple iterative rebuilding of macromolecular models

    International Nuclear Information System (INIS)

    Terwilliger, Thomas C.; Grosse-Kunstleve, Ralf W.; Afonine, Pavel V.; Adams, Paul D.; Moriarty, Nigel W.; Zwart, Peter; Read, Randy J.; Turk, Dusan; Hung, Li-Wei

    2007-01-01

    Heterogeneity in ensembles generated by independent model rebuilding principally reflects the limitations of the data and of the model-building process rather than the diversity of structures in the crystal. Automation of iterative model building, density modification and refinement in macromolecular crystallography has made it feasible to carry out this entire process multiple times. By using different random seeds in the process, a number of different models compatible with experimental data can be created. Sets of models were generated in this way using real data for ten protein structures from the Protein Data Bank and using synthetic data generated at various resolutions. Most of the heterogeneity among models produced in this way is in the side chains and loops on the protein surface. Possible interpretations of the variation among models created by repetitive rebuilding were investigated. Synthetic data were created in which a crystal structure was modelled as the average of a set of ‘perfect’ structures and the range of models obtained by rebuilding a single starting model was examined. The standard deviations of coordinates in models obtained by repetitive rebuilding at high resolution are small, while those obtained for the same synthetic crystal structure at low resolution are large, so that the diversity within a group of models cannot generally be a quantitative reflection of the actual structures in a crystal. Instead, the group of structures obtained by repetitive rebuilding reflects the precision of the models, and the standard deviation of coordinates of these structures is a lower bound estimate of the uncertainty in coordinates of the individual models

  2. An interpretation of the behavior of EoS/GE models for asymmetric systems

    DEFF Research Database (Denmark)

    Kontogeorgis, Georgios; Panayiotis, Vlamos

    2000-01-01

    or zero pressure or at other conditions (system's pressure, constant volume packing fraction). In a number of publications over the last years, the achievements and the shortcomings of the various EoS/G(E) models have been presented via phase equilibrium calculations. This short communication provides...... an explanation of several literature EoSIGE models, especially those based on zero-reference pressure (PSRK, MHV1, MHV2), in the prediction of phase equilibria for asymmetric systems as well as an interpretation of the LCVM and kappa-MHV1 models which provide an empirical - yet as shown here theoretically...... justified - solution to these problems. (C) 2000 Elsevier Science Ltd. All rights reserved....

  3. Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Data Sets.

    Science.gov (United States)

    Marchese Robinson, Richard L; Palczewska, Anna; Palczewski, Jan; Kidley, Nathan

    2017-08-28

    The ability to interpret the predictions made by quantitative structure-activity relationships (QSARs) offers a number of advantages. While QSARs built using nonlinear modeling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modeling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting nonlinear QSAR models in general and Random Forest in particular. In the current work, we compare the performance of Random Forest to those of two widely used linear modeling approaches: linear Support Vector Machines (SVMs) (or Support Vector Regression (SVR)) and partial least-squares (PLS). We compare their performance in terms of their predictivity as well as the chemical interpretability of the predictions using novel scoring schemes for assessing heat map images of substructural contributions. We critically assess different approaches for interpreting Random Forest models as well as for obtaining predictions from the forest. We assess the models on a large number of widely employed public-domain benchmark data sets corresponding to regression and binary classification problems of relevance to hit identification and toxicology. We conclude that Random Forest typically yields comparable or possibly better predictive performance than the linear modeling approaches and that its predictions may also be interpreted in a chemically and biologically meaningful way. In contrast to earlier work looking at interpretation of nonlinear QSAR models, we directly compare two methodologically distinct approaches for interpreting Random Forest models. The approaches for interpreting Random Forest assessed in our article were implemented using open-source programs that we have made available to the community. These programs are the rfFC package ( https://r-forge.r-project.org/R/?group_id=1725 ) for the R statistical

  4. A pattern-based analysis of clinical computer-interpretable guideline modeling languages.

    Science.gov (United States)

    Mulyar, Nataliya; van der Aalst, Wil M P; Peleg, Mor

    2007-01-01

    Languages used to specify computer-interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this article are: (1) to examine the expressive power of CIG modeling languages, and (2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines. The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration. We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly, or not at all. PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support basic control-flow patterns, cancellation patterns, and some advance branching and synchronization patterns. None support multiple instances patterns. They offer varying levels of support for synchronizing merge patterns and state-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns. CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications.

  5. Under the pile. Understanding subsurface dynamics of historical cities trough geophysical models interpretation

    Science.gov (United States)

    Bernardes, Paulo; Pereira, Bruno; Alves, Mafalda; Fontes, Luís; Sousa, Andreia; Martins, Manuela; Magalhães, Fernanda; Pimenta, Mário

    2017-04-01

    Braga is one of the oldest cities of the Iberian NW and as of so, the research team's studying the city's historical core for the past 40 years is often confronted with the unpredictability factor laying beneath an urban site with such a long construction history. In fact, Braga keeps redesigning its urban structure over itself on for the past 2000 years, leaving us with a research object filled with an impressive set of construction footprints from the various planning decisions that were taken in the city along its historical path. Aiming for a predicting understanding of the subsoil, we have used near surface geophysics as an effort of minimizing the areas of intervention for traditional archaeological survey techniques. The Seminário de Santiago integrated geophysical survey is an example of the difficulties of interpreting geophysical models in very complex subsurface scenarios. This geophysical survey was planned in order to aid the requalification project being designed for this set of historical buildings, that are estimated to date back to the 16h century, and that were built over one of the main urban arteries of both roman and medieval layers of Braga. We have used both GPR as well as ERT methods for the geophysical survey, but for the purpose of this article, we will focus in the use of the ERT alone. For the interpretation of the geophysical models we've cross-referenced the dense knowledge existing over the building's construction phases with the complex geophysical data collected, using mathematical processing and volume-based visualization techniques, resorting to the use of Res2Inv©, Paraview© and Voxler® software's. At the same time we tried to pinpoint the noise caused by the past 30 year's infrastructural interventions regarding the replacement of the building's water and sanitation systems and for which we had no design plants, regardless of its recent occurring. The deep impact of this replacement actions revealed by the archaeological

  6. Usage Intention Framework Model: A Fuzzy Logic Interpretation of the Classical Utaut Model

    Science.gov (United States)

    Sandaire, Johnny

    2009-01-01

    A fuzzy conjoint analysis (FCA: Turksen, 1992) model for enhancing management decision in the technology adoption domain was implemented as an extension to the UTAUT model (Venkatesh, Morris, Davis, & Davis, 2003). Additionally, a UTAUT-based Usage Intention Framework Model (UIFM) introduced a closed-loop feedback system. The empirical evidence…

  7. Models of fluorescence and photosynthesis for interpreting measurements of solar-induced chlorophyll fluorescence

    Science.gov (United States)

    van der Tol, C.; Berry, J. A.; Campbell, P. K. E.; Rascher, U.

    2014-12-01

    We have extended a conventional photosynthesis model to simulate field and laboratory measurements of chlorophyll fluorescence at the leaf scale. The fluorescence paramaterization is based on a close nonlinear relationship between the relative light saturation of photosynthesis and nonradiative energy dissipation in plants of different species. This relationship diverged only among examined data sets under stressed (strongly light saturated) conditions, possibly caused by differences in xanthophyll pigment concentrations. The relationship was quantified after analyzing data sets of pulse amplitude modulated measurements of chlorophyll fluorescence and gas exchange of leaves of different species exposed to different levels of light, CO2, temperature, nitrogen fertilization treatments, and drought. We used this relationship in a photosynthesis model. The coupled model enabled us to quantify the relationships between steady state chlorophyll fluorescence yield, electron transport rate, and photosynthesis in leaves under different environmental conditions.

  8. Customer involvement in greening the supply chain: an interpretive structural modeling methodology

    Science.gov (United States)

    Kumar, Sanjay; Luthra, Sunil; Haleem, Abid

    2013-04-01

    The role of customers in green supply chain management needs to be identified and recognized as an important research area. This paper is an attempt to explore the involvement aspect of customers towards greening of the supply chain (SC). An empirical research approach has been used to collect primary data to rank different variables for effective customer involvement in green concept implementation in SC. An interpretive structural-based model has been presented, and variables have been classified using matrice d' impacts croises- multiplication appliqué a un classement analysis. Contextual relationships among variables have been established using experts' opinions. The research may help practicing managers to understand the interaction among variables affecting customer involvement. Further, this understanding may be helpful in framing the policies and strategies to green SC. Analyzing interaction among variables for effective customer involvement in greening SC to develop the structural model in the Indian perspective is an effort towards promoting environment consciousness.

  9. Interpretation of hydraulic conductivity data and parameter evaluation for groundwater flow models

    International Nuclear Information System (INIS)

    Niemi, A.

    1991-01-01

    The report reviews recent developments in evaluating effective permeabilities for groundwater flow models, starting from methods of well test interpretation for and proceeding to the principles of parameter estimation. Basic concepts of parameter evaluation as well as expressions derived for effective permeabilities in traditional porous medium are described. Due to the assumptions made, these do often not apply for fractured media. Specific features of fractured medium are discussed, including approaches used determining the size of a possible REV and questions related to the application of stochastic theories. Due to the difficulties encountered when applying traditional deterministic models for fractured media, stochastic and fracture network approaches have been developed. The application of these techniques is still under development, the main questions to be resolved being related to the scarcity of data

  10. Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology

    Directory of Open Access Journals (Sweden)

    Nicola A. Wardrop

    2014-11-01

    Full Text Available The application of spatial modelling to epidemiology has increased significantly over the past decade, delivering enhanced understanding of the environmental and climatic factors affecting disease distributions and providing spatially continuous representations of disease risk (predictive maps. These outputs provide significant information for disease control programmes, allowing spatial targeting and tailored interventions. However, several factors (e.g. sampling protocols or temporal disease spread can influence predictive mapping outputs. This paper proposes a conceptual framework which defines several scenarios and their potential impact on resulting predictive outputs, using simulated data to provide an exemplar. It is vital that researchers recognise these scenarios and their influence on predictive models and their outputs, as a failure to do so may lead to inaccurate interpretation of predictive maps. As long as these considerations are kept in mind, predictive mapping will continue to contribute significantly to epidemiological research and disease control planning.

  11. Measurement and interpretation of swarm parameters and their application in plasma modelling

    International Nuclear Information System (INIS)

    Petrovic, Z Lj; Dujko, S; Maric, D; Malovic, G; Nikitovic, Z; Sasic, O; Jovanovic, J; Stojanovic, V; Radmilovic-Radenovic, M

    2009-01-01

    In this review paper, we discuss the current status of the physics of charged particle swarms, mainly electrons, having plasma modelling in mind. The measurements of the swarm coefficients and the availability of the data are briefly discussed. We try to give a summary of the past ten years and cite the main reviews and databases, which store the majority of the earlier work. The need for reinitiating the swarm experiments and where and how those would be useful is pointed out. We also add some guidance on how to find information on ions and fast neutrals. Most space is devoted to interpretation of transport data, analysis of kinetic phenomena, and accuracy of calculation and proper use of transport data in plasma models. We have tried to show which aspects of kinetic theory developed for swarm physics and which segments of data would be important for further improvement of plasma models. Finally, several examples are given where actual models are mostly based on the physics of swarms and those include Townsend discharges, afterglows, breakdown and some atmospheric phenomena. Finally we stress that, while complex, some of the results from the kinetic theory of swarms and the related phenomenology must be used either to test the plasma models or even to bring in new physics or higher accuracy and reliability to the models. (review article)

  12. Introduction of a methodology for visualization and graphical interpretation of Bayesian classification models.

    Science.gov (United States)

    Balfer, Jenny; Bajorath, Jürgen

    2014-09-22

    Supervised machine learning models are widely used in chemoinformatics, especially for the prediction of new active compounds or targets of known actives. Bayesian classification methods are among the most popular machine learning approaches for the prediction of activity from chemical structure. Much work has focused on predicting structure-activity relationships (SARs) on the basis of experimental training data. By contrast, only a few efforts have thus far been made to rationalize the performance of Bayesian or other supervised machine learning models and better understand why they might succeed or fail. In this study, we introduce an intuitive approach for the visualization and graphical interpretation of naïve Bayesian classification models. Parameters derived during supervised learning are visualized and interactively analyzed to gain insights into model performance and identify features that determine predictions. The methodology is introduced in detail and applied to assess Bayesian modeling efforts and predictions on compound data sets of varying structural complexity. Different classification models and features determining their performance are characterized in detail. A prototypic implementation of the approach is provided.

  13. Rock physics models for constraining quantitative interpretation of ultrasonic data for biofilm growth and development

    Science.gov (United States)

    Alhadhrami, Fathiya Mohammed

    This study examines the use of rock physics modeling for quantitative interpretation of seismic data in the context of microbial growth and biofilm formation in unconsolidated sediment. The impetus for this research comes from geophysical experiments by Davis et al. (2010) and Kwon and Ajo-Franklin et al. (2012). These studies observed that microbial growth has a small effect on P-wave velocities (VP) but a large effect on seismic amplitudes. Davis et al. (2010) and Kwon and Ajo-Franklin et al. (2012) speculated that the amplitude variations were due to a combination of rock mechanical changes from accumulation of microbial growth related features such as biofilms. A more definite conclusion can be drawn by developing rock physics models that connect rock properties to seismic amplitudes. The primary objective of this work is to provide an explanation for high amplitude attenuation due to biofilm growth. The results suggest that biofilm formation in the Davis et al. (2010) experiment exhibit two growth styles: a loadbearing style where biofilm behaves like an additional mineral grain and a non-loadbearing mode where the biofilm grows into the pore spaces. In the loadbearing mode, the biofilms contribute to the stiffness of the sediments. We refer to this style as "filler." In the non-loadbearing mode, the biofilms contribute only to change in density of sediments without affecting their strength. We refer to this style of microbial growth as "mushroom." Both growth styles appear to be changing permeability more than the moduli or the density. As the result, while the VP velocity remains relatively unchanged, the amplitudes can change significantly depending on biofilm saturation. Interpreting seismic data from biofilm growths in term of rock physics models provide a greater insight into the sediment-fluid interaction. The models in turn can be used to understand microbial enhanced oil recovery and in assisting in solving environmental issues such as creating bio

  14. Model Interpretation of Topological Spatial Analysis for the Visually Impaired (Blind Implemented in Google Maps

    Directory of Open Access Journals (Sweden)

    Marcelo Franco Porto

    2013-06-01

    Full Text Available The technological innovations promote the availability of geographic information on the Internet through Web GIS such as Google Earth and Google Maps. These systems contribute to the teaching and diffusion of geographical knowledge that instigates the recognition of the space we live in, leading to the creation of a spatial identity. In these products available on the Web, the interpretation and analysis of spatial information gives priority to one of the human senses: vision. Due to the fact that this representation of information is transmitted visually (image and vectors, a portion of the population is excluded from part of this knowledge because categories of analysis of geographic data such as borders, territory, and space can only be understood by people who can see. This paper deals with the development of a model of interpretation of topological spatial analysis based on the synthesis of voice and sounds that can be used by the visually impaired (blind.The implementation of a prototype in Google Maps and the usability tests performed are also examined. For the development work it was necessary to define the model of topological spatial analysis, focusing on computational implementation, which allows users to interpret the spatial relationships of regions (countries, states and municipalities, recognizing its limits, neighborhoods and extension beyond their own spatial relationships . With this goal in mind, several interface and usability guidelines were drawn up to be used by the visually impaired (blind. We conducted a detailed study of the Google Maps API (Application Programming Interface, which was the environment selected for prototype development, and studied the information available for the users of that system. The prototype was developed based on the synthesis of voice and sounds that implement the proposed model in C # language and in .NET environment. To measure the efficiency and effectiveness of the prototype, usability

  15. Interpretive sociology of foreign policy: “agent” model of state behavior on the international arena

    Directory of Open Access Journals (Sweden)

    Ivan Nikolaevich Timofeev

    2017-12-01

    Full Text Available The article revisits the utility of sociological theories for the students of international relations. The failure of IR scholars to predict Ukrainian crisis revealed the limits of realism, which still remains most influential IR theory. These limits make rethink the prospects of convergence of IR and sociological theories. Pros and cons of holistic constructivist theory are examined. The article results in making an “agent-focused” model composed of the concepts of Max Weber’s interpretive sociology, Graham Allison’s typology of models of decision making and Mark Haas’s model of ideological origins of great powers’ politics. In doing so, it also revisits the concept of identity as a mean to understand “social facts” and their influence on foreign policy. The emphasis on the “agent” though not the “structure” is approached as an alternative to holistic constructivism of Alexander Wendt and his epigones. The “agent” model is supposed to be more capable for studies of great powers’, which play an active role in setting up the “structure’s” parameters. Three different approaches to “agent” are considered - “agent” as a state, as a bureaucratic body or structure within the state and as decision-makers and their staff. The model is designed for further empirical research of the Russian foreign policy.

  16. Development of a semantic-enabled cybersecurity threat intelligence sharing model

    CSIR Research Space (South Africa)

    Mtsweni, Jabu

    2016-03-01

    Full Text Available complex sets of information” that is continuously increasing in volume, velocity, and variety (Khan et al., 2014; Zikopoulos, Eaton, & DeRoos, 2012). Although, Big Data presents various opportunities for organisations (Kaisler, Armour, Espinosa, & Money... strategy. In the context of the government and military environments, intelligence is a well-understood concept and involves the collection, analysis, and interpretation of information for battlespace awareness (Waltz, 1998), and eventually for decision...

  17. Characterization of Rock Mechanical Properties Using Lab Tests and Numerical Interpretation Model of Well Logs

    Directory of Open Access Journals (Sweden)

    Hao Xu

    2016-01-01

    Full Text Available The tight gas reservoir in the fifth member of the Xujiahe formation contains heterogeneous interlayers of sandstone and shale that are low in both porosity and permeability. Elastic characteristics of sandstone and shale are analyzed in this study based on petrophysics tests. The tests indicate that sandstone and mudstone samples have different stress-strain relationships. The rock tends to exhibit elastic-plastic deformation. The compressive strength correlates with confinement pressure and elastic modulus. The results based on thin-bed log interpretation match dynamic Young’s modulus and Poisson’s ratio predicted by theory. The compressive strength is calculated from density, elastic impedance, and clay contents. The tensile strength is calibrated using compressive strength. Shear strength is calculated with an empirical formula. Finally, log interpretation of rock mechanical properties is performed on the fifth member of the Xujiahe formation. Natural fractures in downhole cores and rock microscopic failure in the samples in the cross section demonstrate that tensile fractures were primarily observed in sandstone, and shear fractures can be observed in both mudstone and sandstone. Based on different elasticity and plasticity of different rocks, as well as the characteristics of natural fractures, a fracture propagation model was built.

  18. A latent class model for individual differences in the interpretation of conditionals.

    Science.gov (United States)

    Rijmen, Frank; De Boeck, Paul

    2003-08-01

    We investigated the hypothesis that there are three levels of performance associated with conditional reasoning: (1) Unsophisticated reasoners solve a modus tollens by accepting the invited inferences, treating the conditional as if it were a biconditional. (2) Reasoners of an intermediate level can resist the invited inferences, but cannot find the line of reasoning needed to endorse modus tollens. (3) Sophisticated reasoners do not draw the invited inferences either, but they do master the strategy to solve a modus tollens. On a first set of six problems, solved by 214 adolescents, an unrestricted latent class analysis revealed the existence of a large subgroup of reasoners with a biconditional interpretation of the conditional, and a smaller subgroup with a conditional interpretation. On a second set of 24 problems, solved by the same participants, a restricted latent class model corroborated the existence of a large subgroup of unsophisticated reasoners and a smaller subgroup of reasoners of an intermediate level. No evidence was found for the existence of a subgroup of sophisticated reasoners. As expected, the class of biconditional reasoners was associated with the class of unsophisticated reasoners, and the class of conditional reasoners was associated with the class of reasoners of an intermediate level. Furthermore, the former showed a biconditonal response pattern on truth table tasks, whereas the latter showed a conditional response pattern.

  19. Model-based ECT signal interpretation and experimental verification for the quantitative flaw characterization in steam generator tubes

    International Nuclear Information System (INIS)

    Song, Sung Jin; Kim, Young Hwan; Kim, Eui Lae; Chung, Tae Eon; Yim, Chang Jae

    2002-01-01

    The model-based inversion tools for eddy current signals have been developed by the novel combination of neural networks and finite element modeling for quantitative flaw characterization in steam generator tubes. In the present work, interpretation of experimental eddy current signals was carried out in order to validate the developed inversion tools. A database was constructed using the synthetic flaw signals generated by the finite element modeling. The hybrid neural networks of a PNN classifier and BPNN size estimators were trained using the synthetic signals. Experimental eddy current signals were obtained from axisymmetric artificial flaws. Interpretations of flaws were carried out by feeding experimental signals into the neural networks. The results of interpretations were excellent, so that the developed inversion tools would be applicable to the interpretation of experimental eddy current signals.

  20. Model-supported interpretation of Cedars-Sinai '201 Tl SPECT polar maps

    International Nuclear Information System (INIS)

    Petta, P.

    1994-10-01

    Cardiac scintigraphic imaging yields information about regional heart muscle perfusion distribution. The scintigraphic technique does not directly depict the coronary arteries. Inferring alterations of the supplying vessels from the characteristics of abnormally perfused areas of the myocardium is the difficult task in the interpretation of these image data. We investigate ways of applying model-based techniques to this end. Encoding of a model of myocardial perfusion as background knowledge supplied to a first-order inductive learner yielded classifiers capable of identifying presence of coronary artery disease down to the level of determination of affected vessels with an accuracy comparable to other diagnostic systems for this domain. We also identified criteria setting a limit to the performance obtainable by any single approach, such as machine learning or probabilistic techniques. This led to the realization of a model-supported diagnostic system, integrating an abductive perfusion model with heuristics embodying other domain knowledge, such as common variations of vessel anatomy and information related to the image-delivering process, including typical image artefacts. This system achieves excellent accuracy in the identification of diseased vessels and is additionally capable of locating stenosed vessel segments of affected arteries with satisfactory precision. (author)

  1. A numerical cloud model to interpret the isotope content of hailstones

    International Nuclear Information System (INIS)

    Jouzel, J.; Brichet, N.; Thalmann, B.; Federer, B.

    1980-07-01

    Measurements of the isotope content of hailstones are frequently used to deduce their trajectories and updraft speeds within severe storms. The interpretation was made in the past on the basis of an adiabatic equilibrium model in which the stones grew exclusively by interaction with droplets and vapor. Using the 1D steady-state model of Hirsch with parametrized cloud physics these unrealistic assumptions were dropped and the effects of interactions between droplets, drops, ice crystals and graupel on the concentrations of stable isotopes in hydrometeors were taken into account. The construction of the model is briefly discussed. The resulting height profiles of D and O 18 in hailstones deviate substantially from the equilibrium case, rendering most earlier trajectory calculations invalid. It is also seen that in the lower cloud layers the ice of the stones is richer due to relaxation effects, but at higher cloud layers (T(a) 0 C) the ice is much poorer in isotopes. This yields a broader spread of the isotope values in the interval 0>T(a)>-35 0 C or alternatively, it means that hailstones with a very large range of measured isotope concentrations grow in a smaller and therefore more realistic temperature interval. The use of the model in practice will be demonstrated

  2. A physiological model for interpretation of arterial spin labeling reactive hyperemia of calf muscles.

    Science.gov (United States)

    Chen, Hou-Jen; Wright, Graham A

    2017-01-01

    To characterize and interpret arterial spin labeling (ASL) reactive hyperemia of calf muscles for a better understanding of the microcirculation in peripheral arterial disease (PAD), we present a physiological model incorporating oxygen transport, tissue metabolism, and vascular regulation mechanisms. The model demonstrated distinct effects between arterial stenoses and microvascular dysfunction on reactive hyperemia, and indicated a higher sensitivity of 2-minute thigh cuffing to microvascular dysfunction than 5-minute cuffing. The recorded perfusion responses in PAD patients (n = 9) were better differentiated from the normal subjects (n = 7) using the model-based analysis rather than characterization using the apparent peak and time-to-peak of the responses. The analysis results suggested different amounts of microvascular disease within the patient group. Overall, this work demonstrates a novel analysis method and facilitates understanding of the physiology involved in ASL reactive hyperemia. ASL reactive hyperemia with model-based analysis may be used as a noninvasive microvascular assessment in the presence of arterial stenoses, allowing us to look beyond the macrovascular disease in PAD. A subgroup who will have a poor prognosis after revascularization in the patients with critical limb ischemia may be associated with more severe microvascular diseases, which may potentially be identified using ASL reactive hyperemia.

  3. ARTEFACT MOBILE DATA MODEL TO SUPPORT CULTURAL HERITAGE DATA COLLECTION AND INTERPRETATION

    Directory of Open Access Journals (Sweden)

    Z. S. Mohamed-Ghouse

    2012-07-01

    Full Text Available This paper discusses the limitation of existing data structures in mobile mapping applications to support archaeologists to manage the artefact (any object made or modified by a human culture, and later recovered by an archaeological endeavor details excavated at a cultural heritage site. Current limitations of data structure in the mobile mapping application allow archeologist to record only one artefact per test pit location. In reality, more than one artefact can be excavated from the same test pit location. A spatial data model called Artefact Mobile Data Model (AMDM was developed applying existing Relational Data Base Management System (RDBMS technique to overcome the limitation. The data model was implemented in a mobile database environment called SprintDB Pro which was in turn connected to ArcPad 7.1 mobile mapping application through Open Data Base Connectivity (ODBC. In addition, the design of a user friendly application built on top of AMDM to interpret and record the technology associated with each artefact excavated in the field is also discussed in the paper. In summary, the paper discusses the design and implementation of a data model to facilitate the collection of artefacts in the field using integrated mobile mapping and database approach.

  4. Enabling Wireless Power Transfer in Cellular Networks: Architecture, Modeling and Deployment

    OpenAIRE

    Huang, Kaibin; Lau, Vincent K. N.

    2012-01-01

    Microwave power transfer (MPT) delivers energy wirelessly from stations called power beacons (PBs) to mobile devices by microwave radiation. This provides mobiles practically infinite battery lives and eliminates the need of power cords and chargers. To enable MPT for mobile charging, this paper proposes a new network architecture that overlays an uplink cellular network with randomly deployed PBs for powering mobiles, called a hybrid network. The deployment of the hybrid network under an out...

  5. Interaction-A missing piece of the jigsaw in interpreter-mediated medical consultation models.

    Science.gov (United States)

    Li, Shuangyu; Gerwing, Jennifer; Krystallidou, Demi; Rowlands, Angela; Cox, Antoon; Pype, Peter

    2017-09-01

    In 2015, at the International Conference on Communication in Healthcare in New Orleans, USA, we formed a symposium panel to discuss and debate how interdisciplinary research can inform interpreter-mediated medical consultation training. In all our work, a recurring theme is not just the strengths but also the shortcomings of the guidelines proposed in the textbooks and widely used in medical education. This paper is an account of our multidisciplinary reflections on a prominent issue of the lack of attention to interaction in communications, which shed light on the limitations of these guidelines and clinical communication models. We propose that an international network be established for all stakeholders to foster interprofessional and interdisciplinary collaboration for research and clinical interventions, and to inform training and policy making. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Interpretation for ''high''-Tc of the totally interconnected solution of the Ma and Lee model

    International Nuclear Information System (INIS)

    Wiecko, C.

    1988-09-01

    The already presented totally interconnected (mean-field) approximation of the Ma and Lee model, pictures very well many ingredients of the present status of comprehension of high-T c superconductors. The picture is that of a disordered grain with variable number of particles available for an attractive on-site pairing interaction, embedded in a reservoir of normal particles which fix the chemical potential. Interesting effect of absence of T c and then a sharp increase and slow decay of T c with disorder appears for weak coupling pairing as compared with the hopping probability for single particles. Interpretation is given in terms of one-particle Anderson localization theory and standard mechanisms. (author). 13 refs, 4 figs

  7. Analysis of interactions among the barriers to JIT production: interpretive structural modelling approach

    Science.gov (United States)

    Jadhav, J. R.; Mantha, S. S.; Rane, S. B.

    2015-09-01

    `Survival of the fittest' is the reality in modern global competition. Organizations around the globe are adopting or willing to embrace just-in-time (JIT) production to reinforce the competitiveness. Even though JIT is the most powerful inventory management methodologies it is not free from barriers. Barriers derail the implementation of JIT production system. One of the most significant tasks of top management is to identify and understand the relationship between the barriers to JIT production for alleviating its bad effects. The aims of this paper are to study the barriers hampering the implementation of successful JIT production and analysing the interactions among the barriers using interpretive structural modelling technique. Twelve barriers have been identified after reviewing literature. This paper offers a roadmap for preparing an action plan to tackle the barriers in successful implementation of JIT production.

  8. Psycho-social aspects of youth unemployment: an interpretative theoretical model.

    Science.gov (United States)

    Hendry, L B; Raymond, M J

    1986-12-01

    By utilizing representative samples of short-term (n = 33), long term (n = 14) unemployed adolescents and YTS trainees (n = 49) in North-East Scotland, the present study attempted to identify psycho-social variables involved in the individual adolescent's ability to cope with unemployment. The research was built around a series of semi-structured interviews with all subjects. Results suggested a variety of apparent contradictions--family support vs. parental pressure; informal community-based education as helpful vs. school education as irrelevant; high aspirations as reinforcing or frustrating; peer groups as supportive or socially constraining; time structure as welcome or monotonous and restrictive; self-esteem being sapped or maintained aggressively and defensively high. From the data a theoretical model is offered which attempts to resolve the paradoxes by interpreting the experience of unemployment for young people in terms of positive and negative "trade-offs".

  9. A Time-Space Symmetry Based Cylindrical Model for Quantum Mechanical Interpretations

    Science.gov (United States)

    Vo Van, Thuan

    2017-12-01

    Following a bi-cylindrical model of geometrical dynamics, our study shows that a 6D-gravitational equation leads to geodesic description in an extended symmetrical time-space, which fits Hubble-like expansion on a microscopic scale. As a duality, the geodesic solution is mathematically equivalent to the basic Klein-Gordon-Fock equations of free massive elementary particles, in particular, the squared Dirac equations of leptons. The quantum indeterminism is proved to have originated from space-time curvatures. Interpretation of some important issues of quantum mechanical reality is carried out in comparison with the 5D space-time-matter theory. A solution of lepton mass hierarchy is proposed by extending to higher dimensional curvatures of time-like hyper-spherical surfaces than one of the cylindrical dynamical geometry. In a result, the reasonable charged lepton mass ratios have been calculated, which would be tested experimentally.

  10. Enabling Integrated Decision Making for Electronic-Commerce by Modelling an Enterprise's Sharable Knowledge.

    Science.gov (United States)

    Kim, Henry M.

    2000-01-01

    An enterprise model, a computational model of knowledge about an enterprise, is a useful tool for integrated decision-making by e-commerce suppliers and customers. Sharable knowledge, once represented in an enterprise model, can be integrated by the modeled enterprise's e-commerce partners. Presents background on enterprise modeling, followed by…

  11. Utilization of a mental health collaborative care model among patients who require interpreter services.

    Science.gov (United States)

    Njeru, Jane W; DeJesus, Ramona S; St Sauver, Jennifer; Rutten, Lila J; Jacobson, Debra J; Wilson, Patrick; Wieland, Mark L

    2016-01-01

    Immigrants and refugees to the United States have a higher prevalence of depression compared to the general population and are less likely to receive adequate mental health services and treatment. Those with limited English proficiency (LEP) are at an even higher risk of inadequate mental health care. Collaborative care management (CCM) models for depression are effective in achieving treatment goals among a wide range of patient populations, including patients with LEP. The purpose of this study was to assess the utilization of a statewide initiative that uses CCM for depression management, among patients with LEP in a large primary care practice. This was a retrospective cohort study of patients with depression in a large primary care practice in Minnesota. Patients who met criteria for enrollment into the CCM [with a provider-generated diagnosis of depression or dysthymia in the electronic medical records, and a Patient Health Questionnaire-9 (PHQ-9) score ≥10]. Patient-identified need for interpreter services was used as a proxy for LEP. Rates of enrollment into the DIAMOND (Depression Improvement Across Minnesota, Offering A New Direction) program, a statewide initiative that uses CCM for depression management were measured. These rates were compared between eligible patients who require interpreter services versus patients who do not. Of the 7561 patients who met criteria for enrollment into the DIAMOND program during the study interval, 3511 were enrolled. Only 18.2 % of the eligible patients with LEP were enrolled into DIAMOND compared with the 47.2 % of the eligible English proficient patients. This finding persisted after adjustment for differences in age, gender and depression severity scores (adjusted OR [95 % confidence interval] = 0.43 [0.23, 0.81]). Within primary care practices, tailored interventions are needed, including those that address cultural competence and language navigation, to improve the utilization of this effective model among

  12. Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project

    International Nuclear Information System (INIS)

    Wu, Wei-Shing; Yang, Chen-Feng; Chang, Jung-Chuan; Château, Pierre-Alexandre; Chang, Yang-Chi

    2015-01-01

    The sound development of marine resource usage relies on a strong maritime engineering industry. The perilous marine environment poses the highest risk to all maritime work. It is therefore imperative to reduce the risk associated with maritime work by using some analytical methods other than engineering techniques. This study addresses this issue by using an integrated interpretive structure modeling (ISM) and Bayesian network (BN) approach in a risk assessment context. Mitigating or managing maritime risk relies primarily on domain expert experience and knowledge. ISM can be used to incorporate expert knowledge in a systematic manner and helps to impose order and direction on complex relationships that exist among system elements. Working with experts, this research used ISM to clearly specify an engineering risk factor relationship represented by a cause–effect diagram, which forms the structure of the BN. The expert subjective judgments were further transformed into a prior and conditional probability set to be embedded in the BN. We used the BN to evaluate the risks of two offshore pipeline projects in Taiwan. The results indicated that the BN can provide explicit risk information to support better project management. - Highlights: • We adopt an integrated method for risk assessment of offshore pipeline projects. • We conduct semi-structural interview with the experts for risk factor identification. • Interpretive structural modeling helps to form the digraph of Bayesian network (BN) • We perform the risk analysis with the experts by building a BN. • Risk evaluations of two case studies using the BN show effectiveness of the methods

  13. Causality in cancer research: a journey through models in molecular epidemiology and their philosophical interpretation

    Directory of Open Access Journals (Sweden)

    Paolo Vineis

    2017-06-01

    Full Text Available Abstract In the last decades, Systems Biology (including cancer research has been driven by technology, statistical modelling and bioinformatics. In this paper we try to bring biological and philosophical thinking back. We thus aim at making different traditions of thought compatible: (a causality in epidemiology and in philosophical theorizing—notably, the “sufficient-component-cause framework” and the “mark transmission” approach; (b new acquisitions about disease pathogenesis, e.g. the “branched model” in cancer, and the role of biomarkers in this process; (c the burgeoning of omics research, with a large number of “signals” and of associations that need to be interpreted. In the paper we summarize first the current views on carcinogenesis, and then explore the relevance of current philosophical interpretations of “cancer causes”. We try to offer a unifying framework to incorporate biomarkers and omic data into causal models, referring to a position called “evidential pluralism”. According to this view, causal reasoning is based on both “evidence of difference-making” (e.g. associations and on “evidence of underlying biological mechanisms”. We conceptualize the way scientists detect and trace signals in terms of information transmission, which is a generalization of the mark transmission theory developed by philosopher Wesley Salmon. Our approach is capable of helping us conceptualize how heterogeneous factors such as micro and macro-biological and psycho-social—are causally linked. This is important not only to understand cancer etiology, but also to design public health policies that target the right causal factors at the macro-level.

  14. Interpretive Structural Modeling of MLearning Curriculum Implementation Model of English Language Communication Skills for Undergraduates

    Science.gov (United States)

    Abdullah, Muhammad Ridhuan Tony Lim; Siraj, Saedah; Asra; Hussin, Zaharah

    2014-01-01

    In the field of distance education, learning mediated through mobile technology or mobile learning (mLearning) has rapidly building a repertoire of influence in distance education research. This paper aims to propose an mLearning curriculum implementation model for English Language and Communication skills course among undergraduates using…

  15. Fitting and interpreting continuous-time latent Markov models for panel data.

    Science.gov (United States)

    Lange, Jane M; Minin, Vladimir N

    2013-11-20

    Multistate models characterize disease processes within an individual. Clinical studies often observe the disease status of individuals at discrete time points, making exact times of transitions between disease states unknown. Such panel data pose considerable modeling challenges. Assuming the disease process progresses accordingly, a standard continuous-time Markov chain (CTMC) yields tractable likelihoods, but the assumption of exponential sojourn time distributions is typically unrealistic. More flexible semi-Markov models permit generic sojourn distributions yet yield intractable likelihoods for panel data in the presence of reversible transitions. One attractive alternative is to assume that the disease process is characterized by an underlying latent CTMC, with multiple latent states mapping to each disease state. These models retain analytic tractability due to the CTMC framework but allow for flexible, duration-dependent disease state sojourn distributions. We have developed a robust and efficient expectation-maximization algorithm in this context. Our complete data state space consists of the observed data and the underlying latent trajectory, yielding computationally efficient expectation and maximization steps. Our algorithm outperforms alternative methods measured in terms of time to convergence and robustness. We also examine the frequentist performance of latent CTMC point and interval estimates of disease process functionals based on simulated data. The performance of estimates depends on time, functional, and data-generating scenario. Finally, we illustrate the interpretive power of latent CTMC models for describing disease processes on a dataset of lung transplant patients. We hope our work will encourage wider use of these models in the biomedical setting. Copyright © 2013 John Wiley & Sons, Ltd.

  16. Upgrading aquifer test interpretations with numerical axisymmetric flow models using MODFLOW in the Donana area (Spain)

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Bravo, N.; Guardiola-Albert, C.

    2011-07-01

    Though axisymmetric modelling is not widely used it can be incorporated into MODFLOW by tricking the grids with a log-scaling method to simulate the radial flow to a well and to upgrade hydraulic properties. Furthermore, it may reduce computer runtimes considerably by decreasing the number of dimensions. The Almonte-Marismas aquifer is a heterogeneous multi-layer aquifer underlying the Donana area, one of the most important wetlands in Europe. The characterization of hydraulic conductivity is of great importance, because this factor is included in the regional groundwater model, the main water-management support tool in the area. Classical interpretations of existing pumping tests have never taken into account anisotropy, heterogeneity and large head gradients. Thus, to improve the characterization of hydraulic conductivity in the groundwater model, five former pumping tests, located in different hydrogeological areas, have been modelled numerically to represent radial flow in different parts of the aquifer. These numerical simulations have proved to be suitable for reproducing groundwater flow during a pumping test, to corroborate hypotheses concerning unconfined or semi-confined aquifers and even to estimate different hydraulic conductivity values for each lithological layer drilled, which constitutes the main improvement of this model in comparison with classical methods. A comparison of the results shows that the values of the numerical model are similar to those obtained by classical analytic techniques but are always lower for the most permeable layer. It is also clear that the less complex the lithological distribution the more accurate the estimations of hydraulic conductivity. (Author) 46 refs.

  17. Significance of kinetics for sorption on inorganic colloids: modeling and experiment interpretation issues.

    Science.gov (United States)

    Painter, S; Cvetkovic, V; Pickett, D; Turner, D R

    2002-12-15

    A two-site kinetic model for solute sorption on inorganic colloids is developed. The model quantifies linear first-order sorption on two types of sites ("fast" and "slow") characterized by two pairs of rates (forward and reverse). We use the model to explore data requirements for long-term predictive calculations of colloid-facilitated transport and to evaluate laboratory kinetic sorption data of Lu et al.. Five batch sorption data sets are considered with plutonium as the tracer and montmorillonite, hematite, silica, and smectite as colloids. Using asymptotic results applicable on the time scale of limited duration experiments, a robust estimation procedure is developed for the fast-site partitioning coefficient K(C) and the slow forward rate alpha. The estimated range of K(C) is 1.1-76 L/g, and the range for alpha is 0.0017-0.02 1/h. The fast reverse rate k(r) is estimated in the range 0.012-0.1 1/h. Comparison of one-site and two-site sorption interpretations reveals the difficulty in discriminating between the two models for montmorillonite and to a lesser extent for hematite. For silica and smectite, the two-site model clearly provides a better representation of the data as compared with a single site model. Kinetic data for silica are available for different colloid concentrations (0.2 g/L and 1 g/L). For the range of experimental conditions considered, alpha appears to be independent of colloid concentration.

  18. RNA Pol II transcription model and interpretation of GRO-seq data.

    Science.gov (United States)

    Lladser, Manuel E; Azofeifa, Joseph G; Allen, Mary A; Dowell, Robin D

    2017-01-01

    A mixture model and statistical method is proposed to interpret the distribution of reads from a nascent transcriptional assay, such as global run-on sequencing (GRO-seq) data. The model is annotation agnostic and leverages on current understanding of the behavior of RNA polymerase II. Briefly, it assumes that polymerase loads at key positions (transcription start sites) within the genome. Once loaded, polymerase either remains in the initiation form (with some probability) or transitions into an elongating form (with the remaining probability). The model can be fit genome-wide, allowing patterns of Pol II behavior to be assessed on each distinct transcript. Furthermore, it allows for the first time a principled approach to distinguishing the initiation signal from the elongation signal; in particular, it implies a data driven method for calculating the pausing index, a commonly used metric that informs on the behavior of RNA polymerase II. We demonstrate that this approach improves on existing analyses of GRO-seq data and uncovers a novel biological understanding of the impact of knocking down the Male Specific Lethal (MSL) complex in Drosophilia melanogaster.

  19. Integrated petrophysics and rock physics modeling for well log interpretation of elastic, electrical, and petrophysical properties

    Science.gov (United States)

    Wu, Wenting; Grana, Dario

    2017-11-01

    Rock and fluid volumetric properties, such as porosity, saturation, and mineral volumes, are generally estimated from petrophysical measurements such as density, resistivity, neutron porosity and gamma ray, through petrophysical equations. The computed petrophysical properties and sonic log measurements are generally used to estimate the petro-elastic relationship between elastic and rock and fluid volumetric properties used in reservoir characterization. In this paper, we present a unified workflow that includes petrophysical relations and rock physics models for the estimation of rock and fluid properties from elastic, electrical, and petrophysical (porosity, density, and lithology) measurements. The multi-physics model we propose has the advantage of accounting for the coupled effect of rock and fluid properties in the joint petro-elastic and electrical domains, and potentially reduce the uncertainty in the well log interpretation. Furthermore, the presented workflow can be eventually extended to three-dimensional reservoir characterization problems, where seismic and electromagnetic data are available. To demonstrate the validity of the methodology, we show the application of this multi-physics model to both laboratory measurements and well log data.

  20. Model-unrestricted scattering potentials for light ions and their interpretation in the folding model

    International Nuclear Information System (INIS)

    Ermer, M.; Clement, H.; Frank, G.; Grabmayr, P.; Heberle, N.; Wagner, G.J.

    1989-01-01

    High-quality data for elastic proton, deuteron and α-particle scattering on 40 Ca and 208 Pb at 26-30 MeV/N have been analyzed in terms of the model-unrestricted Fourier-Bessel concept. While extracted scattering potentials show substantial deviations from Woods-Saxon shapes, their real central parts are well described by folding calculations using a common effective nucleon-nucleon interaction with a weak density dependence. (orig.)

  1. Underground gas storage Lobodice geological model development based on 3D seismic interpretation

    International Nuclear Information System (INIS)

    Kopal, L.

    2015-01-01

    Aquifer type underground gas storage (UGS) Lobodice was developed in the Central Moravian part of Carpathian foredeep in Czech Republic 50 years ago. In order to improve knowledge about UGS geological structure 3D seismic survey was performed in 2009. Reservoir is rather shallow (400 - 500 m below surface) it is located in complicated locality so limitations for field acquisition phase were abundant. This article describes process work flow from 3D seismic field data acquisition to geological model creation. The outcomes of this work flow define geometry of UGS reservoir, its tectonics, structure spill point, cap rock and sealing features of the structure. Improving of geological knowledge about the reservoir enables less risky new well localization for UGS withdrawal rate increasing. (authors)

  2. A formal approach to the analysis of clinical computer-interpretable guideline modeling languages.

    Science.gov (United States)

    Grando, M Adela; Glasspool, David; Fox, John

    2012-01-01

    To develop proof strategies to formally study the expressiveness of workflow-based languages, and to investigate their applicability to clinical computer-interpretable guideline (CIG) modeling languages. We propose two strategies for studying the expressiveness of workflow-based languages based on a standard set of workflow patterns expressed as Petri nets (PNs) and notions of congruence and bisimilarity from process calculus. Proof that a PN-based pattern P can be expressed in a language L can be carried out semi-automatically. Proof that a language L cannot provide the behavior specified by a PNP requires proof by exhaustion based on analysis of cases and cannot be performed automatically. The proof strategies are generic but we exemplify their use with a particular CIG modeling language, PROforma. To illustrate the method we evaluate the expressiveness of PROforma against three standard workflow patterns and compare our results with a previous similar but informal comparison. We show that the two proof strategies are effective in evaluating a CIG modeling language against standard workflow patterns. We find that using the proposed formal techniques we obtain different results to a comparable previously published but less formal study. We discuss the utility of these analyses as the basis for principled extensions to CIG modeling languages. Additionally we explain how the same proof strategies can be reused to prove the satisfaction of patterns expressed in the declarative language CIGDec. The proof strategies we propose are useful tools for analysing the expressiveness of CIG modeling languages. This study provides good evidence of the benefits of applying formal methods of proof over semi-formal ones. Copyright © 2011 Elsevier B.V. All rights reserved.

  3. The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, Claire L.; Bond-Lamberty, Ben; Desai, Ankur R.; Lavoie, Martin; Risk, Dave; Tang, Jianwu; Todd-Brown, Katherine; Vargas, Rodrigo

    2016-11-16

    A recent acceleration of model-data synthesis activities has leveraged many terrestrial carbon (C) datasets, but utilization of soil respiration (RS) data has not kept pace with other types such as eddy covariance (EC) fluxes and soil C stocks. Here we argue that RS data, including non-continuous measurements from survey sampling campaigns, have unrealized value and should be utilized more extensively and creatively in data synthesis and modeling activities. We identify three major challenges in interpreting RS data, and discuss opportunities to address them. The first challenge is that when RS is compared to ecosystem respiration (RECO) measured from EC towers, it is not uncommon to find substantial mismatch, indicating one or both flux methodologies are unreliable. We argue the most likely cause of mismatch is unreliable EC data, and there is an unrecognized opportunity to utilize RS for EC quality control. The second challenge is that RS integrates belowground heterotrophic (RH) and autotrophic (RA) activity, whereas modelers generally prefer partitioned fluxes, and few models include an explicit RS output. Opportunities exist to use the total RS flux for data assimilation and model benchmarking methods rather than less-certain partitioned fluxes. Pushing for more experiments that not only partition RS but also monitor the age of RA and RH, as well as for the development of belowground RA components in models, would allow for more direct comparison between measured and modeled values. The third challenge is that soil respiration is generally measured at a very different resolution than that needed for comparison to EC or ecosystem- to global-scale models. Measuring soil fluxes with finer spatial resolution and more extensive coverage, and downscaling EC fluxes to match the scale of RS, will improve chamber and tower comparisons. Opportunities also exist to estimate RH at regional scales by implementing decomposition functional types, akin to plant functional

  4. Upside-Down Meta-Interpretation of the Model Elimination Theorem-Proving Procedure for Deduction and Abduction

    Science.gov (United States)

    1992-09-14

    search. Oil tile other hand. in deductive database, logic programming, and artificial intelligence applications , the lack of goal-directedness of pure...Proceedings of the First Conference on Artificial Intelligence Applications , Denver, Colorado, December 1984, 417-423. [35] Poole, D. Explanation and... intelligence applications . Upside-down meta-interpretation, the execution of the top-down model elimination pro- cedure by a bottom-up interpreter like

  5. Applying Interpretive Structural Modeling to Cost Overruns in Construction Projects in the Sultanate of Oman

    Directory of Open Access Journals (Sweden)

    K. Alzebdeh

    2015-06-01

    Full Text Available Cost overruns in construction projects are a problem faced by project managers, engineers, and clients throughout the Middle East.  Globally, several studies in the literature have focused on identifying the causes of these overruns and used statistical methods to rank them according to their impacts. None of these studies have considered the interactions among these factors. This paper examines interpretive structural modelling (ISM as a viable technique for modelling complex interactions among factors responsible for cost overruns in construction projects in the Sultanate of Oman. In particular, thirteen interrelated factors associated with cost overruns were identified, along with their contextual interrelationships. Application of ISM leads to organizing these factors in a hierarchical structure which effectively demonstrates their interactions in a simple way. Four factors were found to be at the root of cost overruns: instability of the US dollar, changes in governmental regulations, faulty cost estimation, and poor coordination among projects’ parties. Taking appropriate actions to minimize the influence of these factors can ultimately lead to better control of future project costs. Thisstudy is of value to managers and decision makers because it provides a powerful yet very easy to apply approach for investigating the problem of cost overruns and other similar issues.

  6. Interpreting the R K (*) anomaly in the colored Zee-Babu model

    Science.gov (United States)

    Guo, Shu-Yuan; Han, Zhi-Long; Li, Bin; Liao, Yi; Ma, Xiao-Dong

    2018-03-01

    We consider the feasibility of interpreting the R K (*) anomaly in the colored Zee-Babu model. The model generates neutrino masses at two loops with the help of a scalar leptoquark S ∼ (3 , 3 , - 1/3) and a scalar diquark ω ∼ (6 , 1 , - 2/3), and contributes to the transition b → sℓ-ℓ+ via the exchange of a leptoquark S at tree level. Under constraints from lepton flavor violating (LFV) and flavor changing neutral current (FCNC) processes, and direct collider searches for heavy particles, we acquire certain parameter space that can accommodate the R K (*) anomaly for both normal (NH) and inverted (IH) hierarchies of neutrino masses. We further examine the LFV decays of the B meson, and find a strong correlation with the neutrino mass hierarchy, i.e., Br (B+ →K+μ±τ∓) ≳Br (B+ →K+μ±e∓) ≈Br (B+ →K+τ±e∓) for NH, while Br (B+ →K+μ±τ∓) ≪Br (B+ →K+μ±e∓) ≈Br (B+ →K+τ±e∓) for IH. Among these decays, only B+ →K+μ±e∓ in the case of NH is promising at the LHCb RUN II, while for IH all LFV decays are hard to detect in the near future.

  7. Mars’ Low Dissipation Factor at 11-h - Interpretation from Anelasticity-Based Dissipation Model

    Science.gov (United States)

    Castillo-Rogez, Julie; Choukroun, M.

    2010-10-01

    We explore the information contained in the ratio of the tidal Love number k2 to the dissipation factor Q characterizing the response of Mars to the tides exerted by its satellite Phobos (11-h period). Assuming that Mars can be approximated as a Maxwell body, Bills et al. [1] have inferred an average viscosity of the Martian mantle 8.7x1014 Pa s. Such a low viscosity appears inconsistent with Mars’ thermal evolution and current heat budget models. Alternative explanations include the presence of partial melt in the mantle [2], or the presence of an aquifer in the crust [3]. We revisit the interpretation of Mars’ k2/Q using a laboratory-based attenuation model that accounts for material viscoelasticity and anelasticity. As a first step, we have computed Mars’ k2/Q for an interior model that includes a solid inner core, a liquid core layer, a mantle, and crust (consistent with the observed moment of inertia, and k2 measured at the orbital period), and searched for the range of mantle viscosities that can explain the observed k2/Q. Successful models are characterized by an average mantle viscosity between 1018 and 1022 Pa s, which rules out the presence of partial melt in the mantle. We can narrow down that range by performing a more detailed calculation of the mineralogy and temperature profiles. Preliminary results will be presented at the meeting. References: [1] Bills et al. (2005) JGR 110, E00704; [2] Ruedas et al. (2009 White paper to the NRC Planetary Science decadal survey; [3] Bills et al. (2009) LPS 40, 1712. MC is supported by a NASA Postdoctoral Program Fellowship, administered by Oak Ridge Associated Universities. This work has been conducted at the Jet Propulsion Laboratory, California Institute of Technology, under a contract to NASA. Government sponsorship acknowledged.

  8. Enabling full-field physics-based optical proximity correction via dynamic model generation

    Science.gov (United States)

    Lam, Michael; Clifford, Chris; Raghunathan, Ananthan; Fenger, Germain; Adam, Kostas

    2017-07-01

    As extreme ultraviolet lithography becomes closer to reality for high volume production, its peculiar modeling challenges related to both inter and intrafield effects have necessitated building an optical proximity correction (OPC) infrastructure that operates with field position dependency. Previous state-of-the-art approaches to modeling field dependency used piecewise constant models where static input models are assigned to specific x/y-positions within the field. OPC and simulation could assign the proper static model based on simulation-level placement. However, in the realm of 7 and 5 nm feature sizes, small discontinuities in OPC from piecewise constant model changes can cause unacceptable levels of edge placement errors. The introduction of dynamic model generation (DMG) can be shown to effectively avoid these dislocations by providing unique mask and optical models per simulation region, allowing a near continuum of models through the field. DMG allows unique models for electromagnetic field, apodization, aberrations, etc. to vary through the entire field and provides a capability to precisely and accurately model systematic field signatures.

  9. Clustering and interpretation of local earthquake tomography models in the southern Dead Sea basin

    Science.gov (United States)

    Bauer, Klaus; Braeuer, Benjamin

    2016-04-01

    The Dead Sea transform (DST) marks the boundary between the Arabian and the African plates. Ongoing left-lateral relative plate motion and strike-slip deformation started in the Early Miocene (20 MA) and produced a total shift of 107 km until presence. The Dead Sea basin (DSB) located in the central part of the DST is one of the largest pull-apart basins in the world. It was formed from step-over of different fault strands at a major segment boundary of the transform fault system. The basin development was accompanied by deposition of clastics and evaporites and subsequent salt diapirism. Ongoing deformation within the basin and activity of the boundary faults are indicated by increased seismicity. The internal architecture of the DSB and the crustal structure around the DST were subject of several large scientific projects carried out since 2000. Here we report on a local earthquake tomography study from the southern DSB. In 2006-2008, a dense seismic network consisting of 65 stations was operated for 18 months in the southern part of the DSB and surrounding regions. Altogether 530 well-constrained seismic events with 13,970 P- and 12,760 S-wave arrival times were used for a travel time inversion for Vp, Vp/Vs velocity structure and seismicity distribution. The work flow included 1D inversion, 2.5D and 3D tomography, and resolution analysis. We demonstrate a possible strategy how several tomographic models such as Vp, Vs and Vp/Vs can be integrated for a combined lithological interpretation. We analyzed the tomographic models derived by 2.5D inversion using neural network clustering techniques. The method allows us to identify major lithologies by their petrophysical signatures. Remapping the clusters into the subsurface reveals the distribution of basin sediments, prebasin sedimentary rocks, and crystalline basement. The DSB shows an asymmetric structure with thickness variation from 5 km in the west to 13 km in the east. Most importantly, a well-defined body

  10. Systemic therapy and the social relational model of disability: enabling practices with people with intellectual disability

    OpenAIRE

    Haydon-Laurelut, Mark

    2009-01-01

    Therapy has been critiqued for personalizing the political (Kitzinger, 1993). The social-relational model (Thomas, 1999) is one theoretical resource for understanding the practices of therapy through a political lens. The social model(s) have viewed therapy with suspicion. This paper highlights – using composite case examples and the authors primary therapeutic modality, systemic therapy – some systemic practices with adults with Intellectual Disability (ID) that enact a position that it is s...

  11. Investigating dye performance and crosstalk in fluorescence enabled bioimaging using a model system

    DEFF Research Database (Denmark)

    Arppe, Riikka; R. Carro-Temboury, Miguel; Hempel, Casper

    2017-01-01

    studies and between research groups very difficult. Therefore, we suggest a model system to benchmark instrumentation, methods and staining procedures. The system we introduce is based on doped zeolites in stained polyvinyl alcohol (PVA) films: a highly accessible model system which has the properties......-talk of fluorophores on the detected fluorescence signal. The described model system comprises of lanthanide (III) ion doped Linde Type A zeolites dispersed in a PVA film stained with fluorophores. We tested: F18, MitoTracker Red and ATTO647N. This model system allowed comparing performance of the fluorophores...

  12. Enabling intelligent copernicus services for carbon and water balance modeling of boreal forest ecosystems - North State

    Science.gov (United States)

    Häme, Tuomas; Mutanen, Teemu; Rauste, Yrjö; Antropov, Oleg; Molinier, Matthieu; Quegan, Shaun; Kantzas, Euripides; Mäkelä, Annikki; Minunno, Francesco; Atli Benediktsson, Jon; Falco, Nicola; Arnason, Kolbeinn; Storvold, Rune; Haarpaintner, Jörg; Elsakov, Vladimir; Rasinmäki, Jussi

    2015-04-01

    The objective of project North State, funded by Framework Program 7 of the European Union, is to develop innovative data fusion methods that exploit the new generation of multi-source data from Sentinels and other satellites in an intelligent, self-learning framework. The remote sensing outputs are interfaced with state-of-the-art carbon and water flux models for monitoring the fluxes over boreal Europe to reduce current large uncertainties. This will provide a paradigm for the development of products for future Copernicus services. The models to be interfaced are a dynamic vegetation model and a light use efficiency model. We have identified four groups of variables that will be estimated with remote sensed data: land cover variables, forest characteristics, vegetation activity, and hydrological variables. The estimates will be used as model inputs and to validate the model outputs. The earth observation variables are computed as automatically as possible, with an objective to completely automatic estimation. North State has two sites for intensive studies in southern and northern Finland, respectively, one in Iceland and one in state Komi of Russia. Additionally, the model input variables will be estimated and models applied over European boreal and sub-arctic region from Ural Mountains to Iceland. The accuracy assessment of the earth observation variables will follow statistical sampling design. Model output predictions are compared to earth observation variables. Also flux tower measurements are applied in the model assessment. In the paper, results of hyperspectral, Sentinel-1, and Landsat data and their use in the models is presented. Also an example of a completely automatic land cover class prediction is reported.

  13. Interpretation of two compact planetary nebulae, IC 4997 and NGC 6572, with aid of theoretical models.

    Science.gov (United States)

    Hyung, S; Aller, L H

    1993-01-15

    Observations of two dense compact planetary nebulae secured with the Hamilton Echelle spectrograph at Lick Observatory combined with previously published UV spectra secured with the International Ultraviolet Explorer enable us to probe the electron densities and temperatures (plasma diagnostics) and ionic concentrations in these objects. The diagnostic diagrams show that no homogenous model will work for these nebulae. NGC 6572 may consist of an inner torordal ring of density 25,000 atoms/cm3 and an outer conical shell of density 10,000 atoms/cm3. The simplest model of IC 4997 suggests a thick inner shell with a density of about 107 atoms/cm3 and an outer envelope of density 10,000 atoms/cm3. The abundances of all elements heavier than He appear to be less than the solar values in NGC 6572, whereas He, C, N, and O may be more abundant in IC 4997 than in the sun. IC 4997 presents puzzling problems.

  14. An Adaptive Temporal-Causal Network Model for Enabling Learning of Social Interaction

    NARCIS (Netherlands)

    Commu, Charlotte; Theelen, Mathilde; Treur, J.

    2017-01-01

    In this study, an adaptive temporal-causal network model is present-ed for learning of basic skills for social interaction. It focuses on greeting a known person and how that relates to learning how to recognize a person from seeing his or her face. The model involves a Hebbian learning process. The

  15. Open Knee: Open Source Modeling & Simulation to Enable Scientific Discovery and Clinical Care in Knee Biomechanics

    Science.gov (United States)

    Erdemir, Ahmet

    2016-01-01

    Virtual representations of the knee joint can provide clinicians, scientists, and engineers the tools to explore mechanical function of the knee and its tissue structures in health and disease. Modeling and simulation approaches such as finite element analysis also provide the possibility to understand the influence of surgical procedures and implants on joint stresses and tissue deformations. A large number of knee joint models are described in the biomechanics literature. However, freely accessible, customizable, and easy-to-use models are scarce. Availability of such models can accelerate clinical translation of simulations, where labor intensive reproduction of model development steps can be avoided. The interested parties can immediately utilize readily available models for scientific discovery and for clinical care. Motivated by this gap, this study aims to describe an open source and freely available finite element representation of the tibiofemoral joint, namely Open Knee, which includes detailed anatomical representation of the joint's major tissue structures, their nonlinear mechanical properties and interactions. Three use cases illustrate customization potential of the model, its predictive capacity, and its scientific and clinical utility: prediction of joint movements during passive flexion, examining the role of meniscectomy on contact mechanics and joint movements, and understanding anterior cruciate ligament mechanics. A summary of scientific and clinically directed studies conducted by other investigators are also provided. The utilization of this open source model by groups other than its developers emphasizes the premise of model sharing as an accelerator of simulation-based medicine. Finally, the imminent need to develop next generation knee models are noted. These are anticipated to incorporate individualized anatomy and tissue properties supported by specimen-specific joint mechanics data for evaluation, all acquired in vitro from varying age

  16. A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction

    Directory of Open Access Journals (Sweden)

    Osval A. Montesinos-López

    2017-06-01

    Full Text Available There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is very large, while, in non-Bayesian models, there are often important and unsolved convergence problems. The variational Bayes method is popular in machine learning, and, by approximating the probability distributions through optimization, it tends to be faster than Markov Chain Monte Carlo methods. For this reason, in this paper, we propose a new genomic variational Bayes version of the Bayesian genomic model with G×E using half-t priors on each standard deviation (SD term to guarantee highly noninformative and posterior inferences that are not sensitive to the choice of hyper-parameters. We show the complete theoretical derivation of the full conditional and the variational posterior distributions, and their implementations. We used eight experimental genomic maize and wheat data sets to illustrate the new proposed variational Bayes approximation, and compared its predictions and implementation time with a standard Bayesian genomic model with G×E. Results indicated that prediction accuracies are slightly higher in the standard Bayesian model with G×E than in its variational counterpart, but, in terms of computation time, the variational Bayes genomic model with G×E is, in general, 10 times faster than the conventional Bayesian genomic model with G×E. For this reason, the proposed model may be a useful tool for researchers who need to predict and select genotypes in several environments.

  17. Factors Influencing Implementation of OHSAS 18001 in Indian Construction Organizations: Interpretive Structural Modeling Approach.

    Science.gov (United States)

    Rajaprasad, Sunku Venkata Siva; Chalapathi, Pasupulati Venkata

    2015-09-01

    Construction activity has made considerable breakthroughs in the past two decades on the back of increases in development activities, government policies, and public demand. At the same time, occupational health and safety issues have become a major concern to construction organizations. The unsatisfactory safety performance of the construction industry has always been highlighted since the safety management system is neglected area and not implemented systematically in Indian construction organizations. Due to a lack of enforcement of the applicable legislation, most of the construction organizations are forced to opt for the implementation of Occupational Health Safety Assessment Series (OHSAS) 18001 to improve safety performance. In order to better understand factors influencing the implementation of OHSAS 18001, an interpretive structural modeling approach has been applied and the factors have been classified using matrice d'impacts croises-multiplication appliqué a un classement (MICMAC) analysis. The study proposes the underlying theoretical framework to identify factors and to help management of Indian construction organizations to understand the interaction among factors influencing in implementation of OHSAS 18001. Safety culture, continual improvement, morale of employees, and safety training have been identified as dependent variables. Safety performance, sustainable construction, and conducive working environment have been identified as linkage variables. Management commitment and safety policy have been identified as the driver variables. Management commitment has the maximum driving power and the most influential factor is safety policy, which states clearly the commitment of top management towards occupational safety and health.

  18. Understanding influential factors on implementing green supply chain management practices: An interpretive structural modelling analysis.

    Science.gov (United States)

    Agi, Maher A N; Nishant, Rohit

    2017-03-01

    In this study, we establish a set of 19 influential factors on the implementation of Green Supply Chain Management (GSCM) practices and analyse the interaction between these factors and their effect on the implementation of GSCM practices using the Interpretive Structural Modelling (ISM) method and the "Matrice d'Impacts Croisés Multiplication Appliquée à un Classement" (MICMAC) analysis on data compiled from interviews with supply chain (SC) executives based in the Gulf countries (Middle East region). The study reveals a strong influence and driving power of the nature of the relationships between SC partners on the implementation of GSCM practices. We especially found that dependence, trust, and durability of the relationship with SC partners have a very high influence. In addition, the size of the company, the top management commitment, the implementation of quality management and the employees training and education exert a critical influence on the implementation of GSCM practices. Contextual elements such as the industry sector and region and their effect on the prominence of specific factors are also highlighted through our study. Finally, implications for research and practice are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Interpretive Medicine

    Science.gov (United States)

    Reeve, Joanne

    2010-01-01

    Patient-centredness is a core value of general practice; it is defined as the interpersonal processes that support the holistic care of individuals. To date, efforts to demonstrate their relationship to patient outcomes have been disappointing, whilst some studies suggest values may be more rhetoric than reality. Contextual issues influence the quality of patient-centred consultations, impacting on outcomes. The legitimate use of knowledge, or evidence, is a defining aspect of modern practice, and has implications for patient-centredness. Based on a critical review of the literature, on my own empirical research, and on reflections from my clinical practice, I critique current models of the use of knowledge in supporting individualised care. Evidence-Based Medicine (EBM), and its implementation within health policy as Scientific Bureaucratic Medicine (SBM), define best evidence in terms of an epistemological emphasis on scientific knowledge over clinical experience. It provides objective knowledge of disease, including quantitative estimates of the certainty of that knowledge. Whilst arguably appropriate for secondary care, involving episodic care of selected populations referred in for specialist diagnosis and treatment of disease, application to general practice can be questioned given the complex, dynamic and uncertain nature of much of the illness that is treated. I propose that general practice is better described by a model of Interpretive Medicine (IM): the critical, thoughtful, professional use of an appropriate range of knowledges in the dynamic, shared exploration and interpretation of individual illness experience, in order to support the creative capacity of individuals in maintaining their daily lives. Whilst the generation of interpreted knowledge is an essential part of daily general practice, the profession does not have an adequate framework by which this activity can be externally judged to have been done well. Drawing on theory related to the

  20. Environmental Models as a Service: Enabling Interoperability through RESTful Endpoints and API Documentation (presentation)

    Science.gov (United States)

    Achieving interoperability in environmental modeling has evolved as software technology has progressed. The recent rise of cloud computing and proliferation of web services initiated a new stage for creating interoperable systems. Scientific programmers increasingly take advantag...

  1. Environmental Models as a Service: Enabling Interoperability through RESTful Endpoints and API Documentation.

    Science.gov (United States)

    Achieving interoperability in environmental modeling has evolved as software technology has progressed. The recent rise of cloud computing and proliferation of web services initiated a new stage for creating interoperable systems. Scientific programmers increasingly take advantag...

  2. Psycho-Motor and Error Enabled Simulations: Modeling Vulnerable Skills in the Pre-Mastery Phase

    Science.gov (United States)

    2016-04-01

    associated with movement initiation, ballistic action, and stabilization of movement. For all participants that attempted the laparoscopic ventral hernia...equipment placement. First, the orientation of the pelvic model was placed on the table in a fashion to mimic the positioning of a patient lying on a bed...positioning and equipment placement. First, the orientation of the pelvic model was placed on the table in a fashion to mimic the positioning of a patient

  3. Compact Ocean Models Enable Onboard AUV Autonomy and Decentralized Adaptive Sampling

    Science.gov (United States)

    2013-09-30

    ocean modeling and assimilation system that can be deployed on-board of an underwater vehicle. The developed system estimates a synoptic picture of...Award Number: N00014-10-1-0424 LONG-TERM GOALS Improve synoptic observations and enhance ocean prediction through development of new...ability of mobile agents to respond adaptively by providing them with a synoptic realization of the environment in the form of compact models of the

  4. Parametric Generation of Polygonal Tree Models for Rendering on Tessellation-Enabled Hardware

    OpenAIRE

    Nystad, Jørgen

    2010-01-01

    The main contribution of this thesis is a parametric method for generation of single-mesh polygonal tree models that follow natural rules as indicated by da Vinci in his notebooks. Following these rules allow for a relatively simple scheme of connecting branches to parent branches. Proper branch connection is a requirement for gaining the benefits of subdivision. Techniques for proper texture coordinate generation and subdivision are also explored.The result is a tree model generation scheme ...

  5. Investigating dye performance and crosstalk in fluorescence enabled bioimaging using a model system.

    Directory of Open Access Journals (Sweden)

    Riikka Arppe

    Full Text Available Detailed imaging of biological structures, often smaller than the diffraction limit, is possible in fluorescence microscopy due to the molecular size and photophysical properties of fluorescent probes. Advances in hardware and multiple providers of high-end bioimaging makes comparing images between studies and between research groups very difficult. Therefore, we suggest a model system to benchmark instrumentation, methods and staining procedures. The system we introduce is based on doped zeolites in stained polyvinyl alcohol (PVA films: a highly accessible model system which has the properties needed to act as a benchmark in bioimaging experiments. Rather than comparing molecular probes and imaging methods in complicated biological systems, we demonstrate that the model system can emulate this complexity and can be used to probe the effect of concentration, brightness, and cross-talk of fluorophores on the detected fluorescence signal. The described model system comprises of lanthanide (III ion doped Linde Type A zeolites dispersed in a PVA film stained with fluorophores. We tested: F18, MitoTracker Red and ATTO647N. This model system allowed comparing performance of the fluorophores in experimental conditions. Importantly, we here report considerable cross-talk of the dyes when exchanging excitation and emission settings. Additionally, bleaching was quantified. The proposed model makes it possible to test and benchmark staining procedures before these dyes are applied to more complex biological systems.

  6. The Policy Dystopia Model: An Interpretive Analysis of Tobacco Industry Political Activity.

    Science.gov (United States)

    Ulucanlar, Selda; Fooks, Gary J; Gilmore, Anna B

    2016-09-01

    Tobacco industry interference has been identified as the greatest obstacle to the implementation of evidence-based measures to reduce tobacco use. Understanding and addressing industry interference in public health policy-making is therefore crucial. Existing conceptualisations of corporate political activity (CPA) are embedded in a business perspective and do not attend to CPA's social and public health costs; most have not drawn on the unique resource represented by internal tobacco industry documents. Building on this literature, including systematic reviews, we develop a critically informed conceptual model of tobacco industry political activity. We thematically analysed published papers included in two systematic reviews examining tobacco industry influence on taxation and marketing of tobacco; we included 45 of 46 papers in the former category and 20 of 48 papers in the latter (n = 65). We used a grounded theory approach to build taxonomies of "discursive" (argument-based) and "instrumental" (action-based) industry strategies and from these devised the Policy Dystopia Model, which shows that the industry, working through different constituencies, constructs a metanarrative to argue that proposed policies will lead to a dysfunctional future of policy failure and widely dispersed adverse social and economic consequences. Simultaneously, it uses diverse, interlocking insider and outsider instrumental strategies to disseminate this narrative and enhance its persuasiveness in order to secure its preferred policy outcomes. Limitations are that many papers were historical (some dating back to the 1970s) and focused on high-income regions. The model provides an evidence-based, accessible way of understanding diverse corporate political strategies. It should enable public health actors and officials to preempt these strategies and develop realistic assessments of the industry's claims.

  7. Geomorphic Map of Worcester County, Maryland, Interpreted from a LIDAR-Based, Digital Elevation Model

    Science.gov (United States)

    Newell, Wayne L.; Clark, Inga

    2008-01-01

    A recently compiled mosaic of a LIDAR-based digital elevation model (DEM) is presented with geomorphic analysis of new macro-topographic details. The geologic framework of the surficial and near surface late Cenozoic deposits of the central uplands, Pocomoke River valley, and the Atlantic Coast includes Cenozoic to recent sediments from fluvial, estuarine, and littoral depositional environments. Extensive Pleistocene (cold climate) sandy dune fields are deposited over much of the terraced landscape. The macro details from the LIDAR image reveal 2 meter-scale resolution of details of the shapes of individual dunes, and fields of translocated sand sheets. Most terrace surfaces are overprinted with circular to elliptical rimmed basins that represent complex histories of ephemeral ponds that were formed, drained, and overprinted by younger basins. The terrains of composite ephemeral ponds and the dune fields are inter-shingled at their margins indicating contemporaneous erosion, deposition, and re-arrangement and possible internal deformation of the surficial deposits. The aggregate of these landform details and their deposits are interpreted as the products of arid, cold climate processes that were common to the mid-Atlantic region during the Last Glacial Maximum. In the Pocomoke valley and its larger tributaries, erosional remnants of sandy flood plains with anastomosing channels indicate the dynamics of former hydrology and sediment load of the watershed that prevailed at the end of the Pleistocene. As the climate warmed and precipitation increased during the transition from late Pleistocene to Holocene, dune fields were stabilized by vegetation, and the stream discharge increased. The increased discharge and greater local relief of streams graded to lower sea levels stimulated down cutting and created the deeply incised valleys out onto the continental shelf. These incised valleys have been filling with fluvial to intertidal deposits that record the rising sea

  8. An alternative modeling framework for better interpretation of the observed volcano-hydrothermal system data

    Science.gov (United States)

    Yue, Z. Q. Q.

    2015-12-01

    Many phenomena and data related to volcanoes and volcano eruptions have been observed and collected over the past four hundred years. They have been interpreted with the conventional and widely accepted hypothesis or theory of hot magma fluid from mantle. However, the prediction of volcano eruption sometimes is incorrect. For example, the devastating eruption of the Mount Ontake on Sept. 27, 2014 was not predicted and/or warned at all, which caused 55 fatalities, 9 missing and more than 60 injured. Therefore, there is a need to reconsider the cause and mechanism of active volcano and its hydrothermal system. On the basis of more than 30 year study and research in geology, volcano, earthquake, geomechanics, geophysics, geochemistry and geohazards, the author has developed a new and alternative modeling framework (or hypothesis) to better interpret the observed volcano-hydrothermal system data and to more accurately predict the occurrence of volcano explosion. An active volcano forms a cone-shape mountain and has a crater with vertical pipe conduit to allow hot lava, volcanic ash and gases to escape or erupt from its chamber (Figure). The chamber locates several kilometers below the ground rocks. The active volcanos are caused by highly compressed and dense gases escaped from the Mantle of the Earth. The gases are mainly CH4 and further trapped in the upper crustal rock mass. They make chemical reactions with the surrounding rocks in the chamber. The chemical reactions are the types of reduction and decomposition. The reactions change the gas chemical compounds into steam water gas H2O, CO2, H2S, SO2 and others. The oxygen in the chemical reaction comes from the surrounding rocks. So, the product lava has a less amount of oxygen than that of the surrounding rocks. The gas-rock chemical reactions produce heat. The gas expansion and penetration power and the heat further break and crack the surrounding rock mass and make them into lavas, fragments, ashes or bombs. The

  9. Interpretation of scintillometry measurements over heterogeneous landcovers using LES modeling and a virtual scintillometer

    Science.gov (United States)

    Pianezze, J.; Cohard, J.; Anquetin, S.; Gagne, Y.

    2010-12-01

    Turbulent surface fluxes are usually measured over homogeneous surface conditions using conventional instruments that sense all turbulent scales (hot-wire, laser, sonic, ...). Unfortunately natural landscapes are highly heterogeneous most of the time with varying vegetation cover type, roughness lengths, moisture and temperature distribution, orography. For these natural conditions, measurement of the turbulent fluxes is therefore not straightforward. To overcome these problems, instruments like scintillometer were developped to estimate agregated surface fluxes. This method allows to evaluate average turbulent fluxes at square kilometers scale, which is hundred times larger than the surface covered by local instruments. However, questions remain about the significance of the measurement if such instruments are used over very complex land surface. Indeed, complex land covers generate stationary turbulent structure that are difficult to be captured with the conventional instruments, and particularly sinctillometers which hypothize homogeneous turbulence produced by homogeneous covers. To solve the problems of measurement interpretation related to heterogeneity and estimate the footprint area, we use the large eddy simulation which is able to reproduce the main flow and turbulent features over complex and heteregeneous covers. The study proposes to implement a diagnostic tool that can produce 3D fields of the refractive index structure parameter. This diagnostic allows direct comparison between simulations and measurements of turbulent characteristics obtained with radar profiler or scintillometer. After a short description of the method, the study shows a first comparison of an average profile measured during the IHOP campaign with simulated fields. Then, the study shows how such a tool can be used to interpret a scintillometer signal in a case of a flow generated by a complexed topography (2D or 3D bell shape hill ) or in a case of sudden change of surface

  10. Improving the effectiveness of ecological site descriptions: General state-and-transition models and the Ecosystem Dynamics Interpretive Tool (EDIT)

    Science.gov (United States)

    Bestelmeyer, Brandon T.; Williamson, Jeb C.; Talbot, Curtis J.; Cates, Greg W.; Duniway, Michael C.; Brown, Joel R.

    2016-01-01

    State-and-transition models (STMs) are useful tools for management, but they can be difficult to use and have limited content.STMs created for groups of related ecological sites could simplify and improve their utility. The amount of information linked to models can be increased using tables that communicate management interpretations and important within-group variability.We created a new web-based information system (the Ecosystem Dynamics Interpretive Tool) to house STMs, associated tabular information, and other ecological site data and descriptors.Fewer, more informative, better organized, and easily accessible STMs should increase the accessibility of science information.

  11. Finger Thickening during Extra-Heavy Oil Waterflooding: Simulation and Interpretation Using Pore-Scale Modelling.

    Directory of Open Access Journals (Sweden)

    Mohamed Regaieg

    Full Text Available Although thermal methods have been popular and successfully applied in heavy oil recovery, they are often found to be uneconomic or impractical. Therefore, alternative production protocols are being actively pursued and interesting options include water injection and polymer flooding. Indeed, such techniques have been successfully tested in recent laboratory investigations, where X-ray scans performed on homogeneous rock slabs during water flooding experiments have shown evidence of an interesting new phenomenon-post-breakthrough, highly dendritic water fingers have been observed to thicken and coalesce, forming braided water channels that improve sweep efficiency. However, these experimental studies involve displacement mechanisms that are still poorly understood, and so the optimization of this process for eventual field application is still somewhat problematic. Ideally, a combination of two-phase flow experiments and simulations should be put in place to help understand this process more fully. To this end, a fully dynamic network model is described and used to investigate finger thickening during water flooding of extra-heavy oils. The displacement physics has been implemented at the pore scale and this is followed by a successful benchmarking exercise of the numerical simulations against the groundbreaking micromodel experiments reported by Lenormand and co-workers in the 1980s. A range of slab-scale simulations has also been carried out and compared with the corresponding experimental observations. We show that the model is able to replicate finger architectures similar to those observed in the experiments and go on to reproduce and interpret, for the first time to our knowledge, finger thickening following water breakthrough. We note that this phenomenon has been observed here in homogeneous (i.e. un-fractured media: the presence of fractures could be expected to exacerbate such fingering still further. Finally, we examine the impact of

  12. MLDs, LABs, and Moho's, Oh My! Using Geodynamical Models to Guide Interpretations of Geophysical Observations

    Science.gov (United States)

    Cooper, C. M.; Miller, M. S.

    2014-12-01

    As we peer deeper and in more detail into cratonic lithosphere, intriguing structures arise to peak our curiosity and imagination. Seismic discontinuity imaging reveals anomalous features that appear as depths (~100-160 km) that appear to be shallower than the base of the tomographically inferred cratonic lithosphere (~150-300 km). These are now been known as mid-lithospheric discontinuities (MLD). Magnetotelluric data shows regions of low resistivity suggesting regions of hydration or presence of carbon in graphite form. But how do we interpret these observations and how do we use them to learn more about craton formation and evolution? Some explanations for these anomalies include melt accumulation, the lithosphere-asthenosphere boundary (LAB), and phase transitions. We propose that many of the structures might actually be related to the initial formation of the cratonic lithosphere. We use a combination of geodynamic models and observations of the depths and orientations of mid-lithospheric seismic discontinuities from a compilation of recent receiver function observations within various regions of cratonic lithosphere around the world and new results from the West African Craton to test whether some of the imaged structure can be attributed to the initial formation of thickened cratonic lithosphere. The formation of thick, cratonic lithosphere should introduce complex structures that could then be preserved within the long-lived regions (to then be later captured by eager geophysicists). We performed numerical simulations of the thickening of lithosphere. We considered two types of thickening - either a process akin to (1) thrust stacking or (2) viscous thickening of the lithospheric material.. In particular, we looked to delineate regions that showed regions with mid-lithospheric discontinuities occurring at variable depths and orientations. Our geodynamic models provide an explanation for the observation that some cratonic regions exhibit mid

  13. Estimating and interpreting migration of Amazonian forests using spatially implicit and semi-explicit neutral models.

    Science.gov (United States)

    Pos, Edwin; Guevara Andino, Juan Ernesto; Sabatier, Daniel; Molino, Jean-François; Pitman, Nigel; Mogollón, Hugo; Neill, David; Cerón, Carlos; Rivas-Torres, Gonzalo; Di Fiore, Anthony; Thomas, Raquel; Tirado, Milton; Young, Kenneth R; Wang, Ophelia; Sierra, Rodrigo; García-Villacorta, Roosevelt; Zagt, Roderick; Palacios Cuenca, Walter; Aulestia, Milton; Ter Steege, Hans

    2017-06-01

    With many sophisticated methods available for estimating migration, ecologists face the difficult decision of choosing for their specific line of work. Here we test and compare several methods, performing sanity and robustness tests, applying to large-scale data and discussing the results and interpretation. Five methods were selected to compare for their ability to estimate migration from spatially implicit and semi-explicit simulations based on three large-scale field datasets from South America (Guyana, Suriname, French Guiana and Ecuador). Space was incorporated semi-explicitly by a discrete probability mass function for local recruitment, migration from adjacent plots or from a metacommunity. Most methods were able to accurately estimate migration from spatially implicit simulations. For spatially semi-explicit simulations, estimation was shown to be the additive effect of migration from adjacent plots and the metacommunity. It was only accurate when migration from the metacommunity outweighed that of adjacent plots, discrimination, however, proved to be impossible. We show that migration should be considered more an approximation of the resemblance between communities and the summed regional species pool. Application of migration estimates to simulate field datasets did show reasonably good fits and indicated consistent differences between sets in comparison with earlier studies. We conclude that estimates of migration using these methods are more an approximation of the homogenization among local communities over time rather than a direct measurement of migration and hence have a direct relationship with beta diversity. As betadiversity is the result of many (non)-neutral processes, we have to admit that migration as estimated in a spatial explicit world encompasses not only direct migration but is an ecological aggregate of these processes. The parameter m of neutral models then appears more as an emerging property revealed by neutral theory instead of

  14. Subject-enabled analytics model on measurement statistics in health risk expert system for public health informatics.

    Science.gov (United States)

    Chung, Chi-Jung; Kuo, Yu-Chen; Hsieh, Yun-Yu; Li, Tsai-Chung; Lin, Cheng-Chieh; Liang, Wen-Miin; Liao, Li-Na; Li, Chia-Ing; Lin, Hsueh-Chun

    2017-11-01

    This study applied open source technology to establish a subject-enabled analytics model that can enhance measurement statistics of case studies with the public health data in cloud computing. The infrastructure of the proposed model comprises three domains: 1) the health measurement data warehouse (HMDW) for the case study repository, 2) the self-developed modules of online health risk information statistics (HRIStat) for cloud computing, and 3) the prototype of a Web-based process automation system in statistics (PASIS) for the health risk assessment of case studies with subject-enabled evaluation. The system design employed freeware including Java applications, MySQL, and R packages to drive a health risk expert system (HRES). In the design, the HRIStat modules enforce the typical analytics methods for biomedical statistics, and the PASIS interfaces enable process automation of the HRES for cloud computing. The Web-based model supports both modes, step-by-step analysis and auto-computing process, respectively for preliminary evaluation and real time computation. The proposed model was evaluated by computing prior researches in relation to the epidemiological measurement of diseases that were caused by either heavy metal exposures in the environment or clinical complications in hospital. The simulation validity was approved by the commercial statistics software. The model was installed in a stand-alone computer and in a cloud-server workstation to verify computing performance for a data amount of more than 230K sets. Both setups reached efficiency of about 10 5 sets per second. The Web-based PASIS interface can be used for cloud computing, and the HRIStat module can be flexibly expanded with advanced subjects for measurement statistics. The analytics procedure of the HRES prototype is capable of providing assessment criteria prior to estimating the potential risk to public health. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Modeling techniques for analysis and interpretation of electron magnetic resonance (EMR) data for transition ions at low symmetry sites in crystals-A primer for experimentalists

    International Nuclear Information System (INIS)

    Rudowicz, Czeslaw; Gnutek, Pawel

    2009-01-01

    Electron magnetic resonance (EMR) studies of paramagnetic centers exhibiting monoclinic and triclinic local site symmetry have gained renewed importance, since such centers occur often in various technologically important materials and biological systems. The intricate low symmetry aspects, which arise for such centers, bear on meaningful interpretation of EMR data and their correlation with structural data. This review provides a primer for experimentalists who wish to utilize efficiently the modeling techniques for analysis and interpretation of EMR data for transition ions, especially ions located at low symmetry sites in crystals. This requires proper understanding of the low symmetry effects observable in EMR spectra as well as related theoretical questions concerning, e.g., (i) existence of physically equivalent zero-field splitting (ZFS) parameter sets, (ii) clear definitions of the axis systems, (iii) proper forms of spin Hamiltonians, and (iv) distinction between apparent and actual low symmetry cases. The question (i) involves consideration of the orthorhombic standardization, which provides basis for standardization of monoclinic and triclinic ZFS parameters. Thus, the aspects pertaining to orthorhombic site symmetry are also outlined. To solve other questions several modeling techniques have been utilized and related computer packages have recently been developed in our group: (1) the superposition model calculations of the zero-field splitting parameters (ZFSPs) in arbitrary symmetry, (2) the procedure for diagonalization of the 2nd-rank ZFSPs and transformation of respective 4th- and 6th-rank ZFSPs, (3) the pseudosymmetry axes method for approximation of the 4th- and 6th-rank ZFSPs to higher symmetry, and (4) the closeness factors and norm ratios for quantitative comparisons of various ZFSP sets. These modeling techniques enable deeper analysis and interpretation of the low symmetry aspects involved in the fitted and theoretical ZFSPs. The computer

  16. ENABLING “ENERGY-AWARENESS” IN THE SEMANTIC 3D CITY MODEL OF VIENNA

    Directory of Open Access Journals (Sweden)

    G. Agugiaro

    2016-09-01

    Full Text Available This paper presents and discusses the first results regarding selection, analysis, preparation and eventual integration of a number of energy-related datasets, chosen in order to enrich a CityGML-based semantic 3D city model of Vienna. CityGML is an international standard conceived specifically as information and data model for semantic city models at urban and territorial scale. The still-in-development Energy Application Domain Extension (ADE is a CityGML extension conceived to specifically model, manage and store energy-related features and attributes for buildings. The work presented in this paper is embedded within the European Marie-Curie ITN project “CINERGY, Smart cities with sustainable energy systems”, which aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities. Given the scope and scale of the project, it is therefore vital to set up a common, unique and spatio-semantically coherent urban data model to be used as information hub for all applications being developed. This paper reports about the experiences done so far, it describes the test area in Vienna, Austria, and the available data sources, it shows and exemplifies the main data integration issues, the strategies developed to solve them in order to obtain the enriched 3D city model. The first results as well as some comments about their quality and limitations are presented, together with the discussion regarding the next steps and some planned improvements.

  17. IMPEx : enabling model/observational data comparison in planetary plasma sciences

    Science.gov (United States)

    Génot, V.; Khodachenko, M.; Kallio, E. J.; Al-Ubaidi, T.; Alexeev, I. I.; Topf, F.; Gangloff, M.; André, N.; Bourrel, N.; Modolo, R.; Hess, S.; Perez-Suarez, D.; Belenkaya, E. S.; Kalegaev, V.

    2013-09-01

    The FP7 IMPEx infrastructure, whose general goal is to encourage and facilitate inter-comparison between observational and model data in planetary plasma sciences, is now established for 2 years. This presentation will focus on a tour of the different achievements which occurred during this period. Within the project, data originate from multiple sources : large observational databases (CDAWeb, AMDA at CDPP, CLWeb at IRAP), simulation databases for hybrid and MHD codes (FMI, LATMOS), planetary magnetic field models database and online services (SINP). Each of these databases proposes dedicated access to their models and runs (HWA@FMI, LATHYS@LATMOS, SMDC@SINP). To gather this large data ensemble, IMPEx offers a distributed framework in which these data may be visualized, analyzed, and shared thanks to interoperable tools; they comprise of AMDA - an online space physics analysis tool -, 3DView - a tool for data visualization in 3D planetary context -, and CLWeb - an online space physics visualization tool. A simulation data model, based on SPASE, has been designed to ease data exchange within the infrastructure. On the communication point of view, the VO paradigm has been retained and the architecture is based on web services and the IVOA protocol SAMP. The presentation will focus on how the tools may be operated synchronously to manipulate these heterogeneous data sets. Use cases based on in-flight missions and associated model runs will be proposed for the demonstration. Finally the motivation and functionalities of the future IMPEx portal will be exposed. As requirements to and potentialities of joining the IMPEx infrastructure will be shown, the presentation could be seen as an invitation to other modeling teams in the community which may be interested to promote their results via IMPEx.

  18. Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data.

    Science.gov (United States)

    Dinov, Ivo D

    2016-01-01

    Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex healthcare data, advanced analytic tools, and distributed scientific computing. Using imaging, genetic and healthcare data we provide examples of processing heterogeneous datasets using distributed cloud services, automated and semi-automated classification techniques, and open-science protocols. Despite substantial advances, new innovative technologies need to be developed that enhance, scale and optimize the management and processing of large, complex and heterogeneous data. Stakeholder investments in data acquisition, research and development, computational infrastructure and education will be critical to realize the huge potential of big data, to reap the expected information benefits and to build lasting knowledge assets. Multi-faceted proprietary, open-source, and community developments will be essential to enable broad, reliable, sustainable and efficient data-driven discovery and analytics. Big data will affect every sector of the economy and their hallmark will be 'team science'.

  19. Modeling, Simulation, and Analysis of a Decoy State Enabled Quantum Key Distribution System

    Science.gov (United States)

    2015-03-26

    Protecting Information, New York: Cambridge University Press, 2006. [6] M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information...configurable to interfere with Bob’s ability to detect a weak coherent pulse. DR D 5 The QKD model shall be accurate, flexible, usable , extensible

  20. Quality Concerns in Technical Education in India: A Quantifiable Quality Enabled Model

    Science.gov (United States)

    Gambhir, Victor; Wadhwa, N. C.; Grover, Sandeep

    2016-01-01

    Purpose: The paper aims to discuss current Technical Education scenarios in India. It proposes modelling the factors affecting quality in a technical institute and then applying a suitable technique for assessment, comparison and ranking. Design/methodology/approach: The paper chose graph theoretic approach for quantification of quality-enabled…

  1. Neonatal tolerance induction enables accurate evaluation of gene therapy for MPS I in a canine model.

    Science.gov (United States)

    Hinderer, Christian; Bell, Peter; Louboutin, Jean-Pierre; Katz, Nathan; Zhu, Yanqing; Lin, Gloria; Choa, Ruth; Bagel, Jessica; O'Donnell, Patricia; Fitzgerald, Caitlin A; Langan, Therese; Wang, Ping; Casal, Margret L; Haskins, Mark E; Wilson, James M

    2016-09-01

    High fidelity animal models of human disease are essential for preclinical evaluation of novel gene and protein therapeutics. However, these studies can be complicated by exaggerated immune responses against the human transgene. Here we demonstrate that dogs with a genetic deficiency of the enzyme α-l-iduronidase (IDUA), a model of the lysosomal storage disease mucopolysaccharidosis type I (MPS I), can be rendered immunologically tolerant to human IDUA through neonatal exposure to the enzyme. Using MPS I dogs tolerized to human IDUA as neonates, we evaluated intrathecal delivery of an adeno-associated virus serotype 9 vector expressing human IDUA as a therapy for the central nervous system manifestations of MPS I. These studies established the efficacy of the human vector in the canine model, and allowed for estimation of the minimum effective dose, providing key information for the design of first-in-human trials. This approach can facilitate evaluation of human therapeutics in relevant animal models, and may also have clinical applications for the prevention of immune responses to gene and protein replacement therapies. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Developmental Impact Analysis of an ICT-Enabled Scalable Healthcare Model in BRICS Economies

    Directory of Open Access Journals (Sweden)

    Dhrubes Biswas

    2012-06-01

    Full Text Available This article highlights the need for initiating a healthcare business model in a grassroots, emerging-nation context. This article’s backdrop is a history of chronic anomalies afflicting the healthcare sector in India and similarly placed BRICS nations. In these countries, a significant percentage of populations remain deprived of basic healthcare facilities and emergency services. Community (primary care services are being offered by public and private stakeholders as a panacea to the problem. Yet, there is an urgent need for specialized (tertiary care services at all levels. As a response to this challenge, an all-inclusive health-exchange system (HES model, which utilizes information communication technology (ICT to provide solutions in rural India, has been developed. The uniqueness of the model lies in its innovative hub-and-spoke architecture and its emphasis on affordability, accessibility, and availability to the masses. This article describes a developmental impact analysis (DIA that was used to assess the impact of this model. The article contributes to the knowledge base of readers by making them aware of the healthcare challenges emerging nations are facing and ways to mitigate those challenges using entrepreneurial solutions.

  3. Integrating semantics and procedural generation: key enabling factors for declarative modeling of virtual worlds

    NARCIS (Netherlands)

    Bidarra, R.; Kraker, K.J. de; Smelik, R.M.; Tutenel, T.

    2010-01-01

    Manual content creation for virtual worlds can no longer satisfy the increasing demand arising from areas as entertainment and serious games, simulations, movies, etc. Furthermore, currently deployed modeling tools basically do not scale up: while they become more and more specialized and complex,

  4. Modeling orbital relative motion to enable formation design from application requirements

    Science.gov (United States)

    Fasano, Giancarmine; D'Errico, Marco

    2009-11-01

    While trajectory design for single satellite Earth observation missions is usually performed by means of analytical and relatively simple models of orbital dynamics including the main perturbations for the considered cases, most literature on formation flying dynamics is devoted to control issues rather than mission design. This work aims at bridging the gap between mission requirements and relative dynamics in multi-platform missions by means of an analytical model that describes relative motion for satellites moving on near circular low Earth orbits. The development is based on the orbital parameters approach and both the cases of close and large formations are taken into account. Secular Earth oblateness effects are included in the derivation. Modeling accuracy, when compared to a nonlinear model with two body and J2 forces, is shown to be of the order of 0.1% of relative coordinates for timescales of hundreds of orbits. An example of formation design is briefly described shaping a two-satellite formation on the basis of geometric requirements for synthetic aperture radar interferometry.

  5. A controlled human malaria infection model enabling evaluation of transmission-blocking interventions.

    Science.gov (United States)

    Collins, Katharine A; Wang, Claire Yt; Adams, Matthew; Mitchell, Hayley; Rampton, Melanie; Elliott, Suzanne; Reuling, Isaie J; Bousema, Teun; Sauerwein, Robert; Chalon, Stephan; Möhrle, Jörg J; McCarthy, James S

    2018-03-12

    Drugs and vaccines that can interrupt the transmission of Plasmodium falciparum will be important for malaria control and elimination. However, models for early clinical evaluation of candidate transmission-blocking interventions are currently unavailable. Here, we describe a new model for evaluating malaria transmission from humans to Anopheles mosquitoes using controlled human malaria infection (CHMI). Seventeen healthy malaria-naive volunteers underwent CHMI by intravenous inoculation of P. falciparum-infected erythrocytes to initiate blood-stage infection. Seven to eight days after inoculation, participants received piperaquine (480 mg) to attenuate asexual parasite replication while allowing gametocytes to develop and mature. Primary end points were development of gametocytemia, the transmissibility of gametocytes from humans to mosquitoes, and the safety and tolerability of the CHMI transmission model. To investigate in vivo gametocytocidal drug activity in this model, participants were either given an experimental antimalarial, artefenomel (500 mg), or a known gametocytocidal drug, primaquine (15 mg), or remained untreated during the period of gametocyte carriage. Male and female gametocytes were detected in all participants, and transmission to mosquitoes was achieved from 8 of 11 (73%) participants evaluated. Compared with results in untreated controls (n = 7), primaquine (15 mg, n = 5) significantly reduced gametocyte burden (P = 0.01), while artefenomel (500 mg, n = 4) had no effect. Adverse events (AEs) were mostly mild or moderate. Three AEs were assessed as severe - fatigue, elevated alanine aminotransferase, and elevated aspartate aminotransferase - and were attributed to malaria infection. Transaminase elevations were transient, asymptomatic, and resolved without intervention. We report the safe and reproducible induction of P. falciparum gametocytes in healthy malaria-naive volunteers at densities infectious to mosquitoes, thereby demonstrating the

  6. Relationships of radiation track structure to biological effect: a re-interpretation of the parameters of the Katz model

    International Nuclear Information System (INIS)

    Goodhead, D.T.

    1989-01-01

    The Katz track-model of cell inactivation has been more successful than any other biophysical model in fitting and predicting inactivation of mammalian cells exposed to a wide variety of ionising radiations. Although the model was developed as a parameterised phenomenological description, without necessarily implying any particular mechanistic processes, the present analysis attempts to interpret it and thereby benefit further from its success to date. A literal interpretation of the parameters leads to contradictions with other experimental and theoretical information, especially since the fitted parameters imply very large (> ∼ 4 μm) subcellular sensitive sites which each require very large amounts (> ∼ 100 keV) of energy deposition in order to be inactivated. Comparisons of these fits with those for cell mutation suggest a re-interpretation in terms of (1) very much smaller sites and (2) a clearer distinction between the ion-kill and γ-kill modes of inactivation. It is suggested that this re-interpretation may be able to guide future development of the phenomenological Katz model and also parameterisation of mechanistic biophysical models. (author)

  7. A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment.

    Science.gov (United States)

    Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae

    2015-09-18

    User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service.

  8. A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment

    Science.gov (United States)

    Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae

    2015-01-01

    User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service. PMID:26393609

  9. New models for energy beam machining enable accurate generation of free forms.

    Science.gov (United States)

    Axinte, Dragos; Billingham, John; Bilbao Guillerna, Aitor

    2017-09-01

    We demonstrate that, despite differences in their nature, many energy beam controlled-depth machining processes (for example, waterjet, pulsed laser, focused ion beam) can be modeled using the same mathematical framework-a partial differential evolution equation that requires only simple calibrations to capture the physics of each process. The inverse problem can be solved efficiently through the numerical solution of the adjoint problem and leads to beam paths that generate prescribed three-dimensional features with minimal error. The viability of this modeling approach has been demonstrated by generating accurate free-form surfaces using three processes that operate at very different length scales and with different physical principles for material removal: waterjet, pulsed laser, and focused ion beam machining. Our approach can be used to accurately machine materials that are hard to process by other means for scalable applications in a wide variety of industries.

  10. A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways.

    Science.gov (United States)

    Äijö, Tarmo; Huang, Yun; Mannerström, Henrik; Chavez, Lukas; Tsagaratou, Ageliki; Rao, Anjana; Lähdesmäki, Harri

    2016-03-14

    We present a generative model, Lux, to quantify DNA methylation modifications from any combination of bisulfite sequencing approaches, including reduced, oxidative, TET-assisted, chemical-modification assisted, and methylase-assisted bisulfite sequencing data. Lux models all cytosine modifications (C, 5mC, 5hmC, 5fC, and 5caC) simultaneously together with experimental parameters, including bisulfite conversion and oxidation efficiencies, as well as various chemical labeling and protection steps. We show that Lux improves the quantification and comparison of cytosine modification levels and that Lux can process any oxidized methylcytosine sequencing data sets to quantify all cytosine modifications. Analysis of targeted data from Tet2-knockdown embryonic stem cells and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathways and reveals 5hmC localization in putative regulatory regions.

  11. Efficiency-centered, innovation-enabling business models of high tech SMEs: evidence from Hong Kong

    OpenAIRE

    Loon, M; Chik, R

    2017-01-01

    High technology small and medium-sized enterprises are compelled to innovate to differentiate themselves from their competitors but at the same time be efficient, as they do not have economies of scale enjoyed by larger organizations. This qualitative study explores this paradoxical challenge faced by Hong Kong SMEs in designing their business model to strike such a balance. In doing so, it investigates the competencies of these firms in technology management and their innovation practices. I...

  12. Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis

    KAUST Repository

    Gharbieh, Mohammad

    2017-05-02

    The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

  13. Building and analyzing timed influence net models with internet-enabled pythia

    Science.gov (United States)

    Pachowicz, Peter W.; Wagenhals, Lee W.; Pham, John; Levis, Alexander H.

    2007-04-01

    The most recent client-server version of Pythia modeling software is presented. Pythia is a software implementation of a Bayesian Net framework and is used for course of action development, evaluation, and selection in the context of effects-based planning. A new version, Pythia 1.5, is a part of a larger suite of tools for behavioral influence analysis, brought into the state-of-the-art client-server computing environment. This server application for multi-user and multiprocess computing relies on the Citrix Presentation Server for integration, security and maintenance. While Pythia's process is run on a server, the input/output services are controlled and displayed through a client PC. Example use of Pythia is illustrated through its application to a suppression of IED activity in an Iraqi province. This case study demonstrates how analysts can create executable (probabilistic) models that link potential actions to effects, based on knowledge about the cultural and social environment. Both the tool and the process for creating and analyzing the model are described as well as the benefits of using the new server based version of the tool.

  14. Composition of uppermost mantle beneath the Northern Fennoscandia - numerical modeling and petrological interpretation

    Science.gov (United States)

    Virshylo, Ivan; Kozlovskaya, Elena; Prodaivoda, George; Silvennoinen, Hanna

    2013-04-01

    Studying of the uppermost mantle beneath the northern Fennoscandia is based on the data of the POLENET/LAPNET passive seismic array. Firstly, arrivals of P-waves of teleseismic events were inverted into P-wave velocity model using non-linear tomography (Silvennoinen et al., in preparation). The second stage was numerical petrological interpretation of referred above velocity model. This study presents estimation of mineralogical composition of the uppermost mantle as a result of numerical modeling. There are many studies concerning calculation of seismic velocities for polymineral media under high pressure and temperature conditions (Afonso, Fernàndez, Ranalli, Griffin, & Connolly, 2008; Fullea et al., 2009; Hacker, 2004; Xu, Lithgow-Bertelloni, Stixrude, & Ritsema, 2008). The elastic properties under high pressure and temperature (PT) conditions were modelled using the expanded Hook's law - Duhamel-Neumann equation, which allows computation of thermoelastic strains. Furthermore, we used a matrix model with multi-component inclusions that has no any restrictions on shape, orientation or concentration of inclusions. Stochastic method of conditional moment with computation scheme of Mori-Tanaka (Prodaivoda, Khoroshun, Nazarenko, & Vyzhva, 2000) is applied instead of traditional Voigt-Reuss-Hill and Hashin-Shtrikman equations. We developed software for both forward and inverse problem calculation. Inverse algorithm uses methods of global non-linear optimization. We prefer a "model-based" approach for ill-posed problem, which means that the problem is solved using geological and geophysical constraints for each parameter of a priori and final models. Additionally, we are checking at least several different hypothesis explaining how it is possible to get the solution with good fit to the observed data. If the a priori model is close to the real medium, the nearest solution would be found by the inversion. Otherwise, the global optimization is searching inside the

  15. Predictability and interpretability of hybrid link-level crash frequency models for urban arterials compared to cluster-based and general negative binomial regression models.

    Science.gov (United States)

    Najaf, Pooya; Duddu, Venkata R; Pulugurtha, Srinivas S

    2018-03-01

    Machine learning (ML) techniques have higher prediction accuracy compared to conventional statistical methods for crash frequency modelling. However, their black-box nature limits the interpretability. The objective of this research is to combine both ML and statistical methods to develop hybrid link-level crash frequency models with high predictability and interpretability. For this purpose, M5' model trees method (M5') is introduced and applied to classify the crash data and then calibrate a model for each homogenous class. The data for 1134 and 345 randomly selected links on urban arterials in the city of Charlotte, North Carolina was used to develop and validate models, respectively. The outputs from the hybrid approach are compared with the outputs from cluster-based negative binomial regression (NBR) and general NBR models. Findings indicate that M5' has high predictability and is very reliable to interpret the role of different attributes on crash frequency compared to other developed models.

  16. SciDAC-Data, A Project to Enabling Data Driven Modeling of Exascale Computing

    Energy Technology Data Exchange (ETDEWEB)

    Mubarak, M.; Ding, P.; Aliaga, L.; Tsaris, A.; Norman, A.; Lyon, A.; Ross, R.

    2016-10-10

    The SciDAC-Data project is a DOE funded initiative to analyze and exploit two decades of information and analytics that have been collected by the Fermilab Data Center on the organization, movement, and consumption of High Energy Physics data. The project will analyze the analysis patterns and data organization that have been used by the NOvA, MicroBooNE, MINERvA and other experiments, to develop realistic models of HEP analysis workflows and data processing. The SciDAC-Data project aims to provide both realistic input vectors and corresponding output data that can be used to optimize and validate simulations of HEP analysis. These simulations are designed to address questions of data handling, cache optimization and workflow structures that are the prerequisites for modern HEP analysis chains to be mapped and optimized to run on the next generation of leadership class exascale computing facilities. We will address the use of the SciDAC-Data distributions acquired from Fermilab Data Center’s analysis workflows and corresponding to around 71,000 HEP jobs, as the input to detailed queuing simulations that model the expected data consumption and caching behaviors of the work running in HPC environments. In particular we describe in detail how the Sequential Access via Metadata (SAM) data handling system in combination with the dCache/Enstore based data archive facilities have been analyzed to develop the radically different models of the analysis of HEP data. We present how the simulation may be used to analyze the impact of design choices in archive facilities.

  17. UAV-enabled reconnaissance and trajectory modeling of a co-seismic rockfall in Lefkada

    OpenAIRE

    Saroglou, Charalampos; Asteriou, Pavlos; Zekkos, Dimitris; Tsiambaos, George; Clark, Marin; Manousakis, John

    2017-01-01

    The paper presents the field evidence and the kinematical study of the motion of a rock block mobilised by an earthquake-induced rockfall in Ponti area in the island of Lefkada during a Mw 6.5 earthquake on 17th November 2015. A detailed field survey was deployed using an Unmanned Aerial Vehicle (UAV) with an ultra-high definition (UHD) camera, which produced a high-resolution orthophoto and a Digital Surface Model (DSM) of the terrain. The sequence of impact marks from the rock trajectory on...

  18. Lazy Updating of hubs can enable more realistic models by speeding up stochastic simulations

    Science.gov (United States)

    Ehlert, Kurt; Loewe, Laurence

    2014-11-01

    To respect the nature of discrete parts in a system, stochastic simulation algorithms (SSAs) must update for each action (i) all part counts and (ii) each action's probability of occurring next and its timing. This makes it expensive to simulate biological networks with well-connected "hubs" such as ATP that affect many actions. Temperature and volume also affect many actions and may be changed significantly in small steps by the network itself during fever and cell growth, respectively. Such trends matter for evolutionary questions, as cell volume determines doubling times and fever may affect survival, both key traits for biological evolution. Yet simulations often ignore such trends and assume constant environments to avoid many costly probability updates. Such computational convenience precludes analyses of important aspects of evolution. Here we present "Lazy Updating," an add-on for SSAs designed to reduce the cost of simulating hubs. When a hub changes, Lazy Updating postpones all probability updates for reactions depending on this hub, until a threshold is crossed. Speedup is substantial if most computing time is spent on such updates. We implemented Lazy Updating for the Sorting Direct Method and it is easily integrated into other SSAs such as Gillespie's Direct Method or the Next Reaction Method. Testing on several toy models and a cellular metabolism model showed >10× faster simulations for its use-cases—with a small loss of accuracy. Thus we see Lazy Updating as a valuable tool for some special but important simulation problems that are difficult to address efficiently otherwise.

  19. Computational Laboratory Astrophysics to Enable Transport Modeling of Protons and Hydrogen in Stellar Winds, the ISM, and other Astrophysical Environments

    Science.gov (United States)

    Schultz, David

    As recognized prominently by the APRA program, interpretation of NASA astrophysical mission observations requires significant products of laboratory astrophysics, for example, spectral lines and transition probabilities, electron-, proton-, or heavy-particle collision data. Availability of these data underpin robust and validated models of astrophysical emissions and absorptions, energy, momentum, and particle transport, dynamics, and reactions. Therefore, measured or computationally derived, analyzed, and readily available laboratory astrophysics data significantly enhances the scientific return on NASA missions such as HST, Spitzer, and JWST. In the present work a comprehensive set of data will be developed for the ubiquitous proton-hydrogen and hydrogen-hydrogen collisions in astrophysical environments including ISM shocks, supernova remnants and bubbles, HI clouds, young stellar objects, and winds within stellar spheres, covering the necessary wide range of energy- and charge-changing channels, collision energies, and most relevant scattering parameters. In addition, building on preliminary work, a transport and reaction simulation will be developed incorporating the elastic and inelastic collision data collected and produced. The work will build upon significant previous efforts of the principal investigators and collaborators, will result in a comprehensive data set required for modeling these environments and interpreting NASA astrophysical mission observations, and will benefit from feedback from collaborators who are active users of the work proposed.

  20. Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

    Directory of Open Access Journals (Sweden)

    Ickwon Choi

    2015-04-01

    Full Text Available The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release. We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.

  1. Modular degradable dendrimers enable small RNAs to extend survival in an aggressive liver cancer model.

    Science.gov (United States)

    Zhou, Kejin; Nguyen, Liem H; Miller, Jason B; Yan, Yunfeng; Kos, Petra; Xiong, Hu; Li, Lin; Hao, Jing; Minnig, Jonathan T; Zhu, Hao; Siegwart, Daniel J

    2016-01-19

    RNA-based cancer therapies are hindered by the lack of delivery vehicles that avoid cancer-induced organ dysfunction, which exacerbates carrier toxicity. We address this issue by reporting modular degradable dendrimers that achieve the required combination of high potency to tumors and low hepatotoxicity to provide a pronounced survival benefit in an aggressive genetic cancer model. More than 1,500 dendrimers were synthesized using sequential, orthogonal reactions where ester degradability was systematically integrated with chemically diversified cores, peripheries, and generations. A lead dendrimer, 5A2-SC8, provided a broad therapeutic window: identified as potent [EC50 75 mg/kg dendrimer repeated dosing). Delivery of let-7 g microRNA (miRNA) mimic inhibited tumor growth and dramatically extended survival. Efficacy stemmed from a combination of a small RNA with the dendrimer's own negligible toxicity, therefore illuminating an underappreciated complication in treating cancer with RNA-based drugs.

  2. Porcine familial adenomatous polyposis model enables systematic analysis of early events in adenoma progression.

    Science.gov (United States)

    Flisikowska, Tatiana; Stachowiak, Monika; Xu, Hongen; Wagner, Alexandra; Hernandez-Caceres, Alejandra; Wurmser, Christine; Perleberg, Carolin; Pausch, Hubert; Perkowska, Anna; Fischer, Konrad; Frishman, Dmitrij; Fries, Ruedi; Switonski, Marek; Kind, Alexander; Saur, Dieter; Schnieke, Angelika; Flisikowski, Krzysztof

    2017-07-26

    We compared gene expression in low and high-grade intraepithelial dysplastic polyps from pigs carrying an APC 1311 truncating mutation orthologous to human APC 1309 , analysing whole samples and microdissected dysplastic epithelium. Gene set enrichment analysis revealed differential expression of gene sets similar to human normal mucosa versus T1 stage polyps. Transcriptome analysis of whole samples revealed many differentially-expressed genes reflecting immune infiltration. Analysis of microdissected dysplastic epithelium was markedly different and showed increased expression in high-grade intraepithelial neoplasia of several genes known to be involved in human CRC; and revealed possible new roles for GBP6 and PLXND1. The pig model thus facilitates analysis of CRC pathogenesis.

  3. Enabling Persistent Autonomy for Underwater Gliders with Ocean Model Predictions and Terrain Based Navigation

    Directory of Open Access Journals (Sweden)

    Andrew eStuntz

    2016-04-01

    Full Text Available Effective study of ocean processes requires sampling over the duration of long (weeks to months oscillation patterns. Such sampling requires persistent, autonomous underwater vehicles, that have a similarly long deployment duration. The spatiotemporal dynamics of the ocean environment, coupled with limited communication capabilities, make navigation and localization difficult, especially in coastal regions where the majority of interesting phenomena occur. In this paper, we consider the combination of two methods for reducing navigation and localization error; a predictive approach based on ocean model predictions and a prior information approach derived from terrain-based navigation. The motivation for this work is not only for real-time state estimation, but also for accurately reconstructing the actual path that the vehicle traversed to contextualize the gathered data, with respect to the science question at hand. We present an application for the practical use of priors and predictions for large-scale ocean sampling. This combined approach builds upon previous works by the authors, and accurately localizes the traversed path of an underwater glider over long-duration, ocean deployments. The proposed method takes advantage of the reliable, short-term predictions of an ocean model, and the utility of priors used in terrain-based navigation over areas of significant bathymetric relief to bound uncertainty error in dead-reckoning navigation. This method improves upon our previously published works by 1 demonstrating the utility of our terrain-based navigation method with multiple field trials, and 2 presenting a hybrid algorithm that combines both approaches to bound navigational error and uncertainty for long-term deployments of underwater vehicles. We demonstrate the approach by examining data from actual field trials with autonomous underwater gliders, and demonstrate an ability to estimate geographical location of an underwater glider to 2

  4. Modeling ductal carcinoma in situ: a HER2-Notch3 collaboration enables luminal filling.

    LENUS (Irish Health Repository)

    Pradeep, C-R

    2012-02-16

    A large fraction of ductal carcinoma in situ (DCIS), a non-invasive precursor lesion of invasive breast cancer, overexpresses the HER2\\/neu oncogene. The ducts of DCIS are abnormally filled with cells that evade apoptosis, but the underlying mechanisms remain incompletely understood. We overexpressed HER2 in mammary epithelial cells and observed growth factor-independent proliferation. When grown in extracellular matrix as three-dimensional spheroids, control cells developed a hollow lumen, but HER2-overexpressing cells populated the lumen by evading apoptosis. We demonstrate that HER2 overexpression in this cellular model of DCIS drives transcriptional upregulation of multiple components of the Notch survival pathway. Importantly, luminal filling required upregulation of a signaling pathway comprising Notch3, its cleaved intracellular domain and the transcriptional regulator HES1, resulting in elevated levels of c-MYC and cyclin D1. In line with HER2-Notch3 collaboration, drugs intercepting either arm reverted the DCIS-like phenotype. In addition, we report upregulation of Notch3 in hyperplastic lesions of HER2 transgenic animals, as well as an association between HER2 levels and expression levels of components of the Notch pathway in tumor specimens of breast cancer patients. Therefore, it is conceivable that the integration of the Notch and HER2 signaling pathways contributes to the pathophysiology of DCIS.

  5. Analysis and interpretation of the model of a Faraday cage for electromagnetic compatibility testing

    Directory of Open Access Journals (Sweden)

    Nenad V. Munić

    2014-02-01

    Full Text Available In order to improve the work of the Laboratory for Electromagnetic Compatibility Testing in the Technical Test Center (TTC, we investigated the influence of the Faraday cage on measurement results. The primary goal of this study is the simulation of the fields in the cage, especially around resonant frequencies, in order to be able to predict results of measurements of devices under test in the anechoic chamber or in any other environment. We developed simulation (computer models of the cage step by step, by using the Wipl-D program and by comparing the numerical results with measurements as well as by resolving difficulties due to the complex structure and imperfections of the cage. The subject of this paper is to present these simulation models and the corresponding results of the computations and measurements. Construction of the cage The cage is made of steel plates with the dimensions 1.25 m x 2.5 m. The base of the cage is a square; the footprint interior dimensions are 3.76 m x 3.76 m, and the height is 2.5 m. The cage ceiling is lowered by plasticized aluminum strips. The strips are loosely attached to the carriers which are screwed to the ceiling. The cage has four ventilation openings (two on the ceiling and two on one wall, made of honeycomb waveguide holes. In one corner of the cage, there is a single door with springs made of beryllium bronze. For frequencies of a few tens of MHz, the skin effect is fully developed in the cage walls. By measuring the input impedance of the wire line parallel to a wall of the cage, we calculated the surface losses of the cage plates. In addition, we used a magnetic probe to detect shield discontinuities. We generated a strong current at a frequency of 106 kHz outside the cage and measured the magnetic field inside the cage at the places of cage shield discontinuities. In this paper, we showed the influence of these places on the measurement results, especially on the qualitative and quantitative

  6. Conceptual model and economic experiments to explain nonpersistence and enable mechanism designs fostering behavioral change.

    Science.gov (United States)

    Djawadi, Behnud Mir; Fahr, René; Turk, Florian

    2014-12-01

    Medical nonpersistence is a worldwide problem of striking magnitude. Although many fields of studies including epidemiology, sociology, and psychology try to identify determinants for medical nonpersistence, comprehensive research to explain medical nonpersistence from an economics perspective is rather scarce. The aim of the study was to develop a conceptual framework that augments standard economic choice theory with psychological concepts of behavioral economics to understand how patients' preferences for discontinuing with therapy arise over the course of the medical treatment. The availability of such a framework allows the targeted design of mechanisms for intervention strategies. Our conceptual framework models the patient as an active economic agent who evaluates the benefits and costs for continuing with therapy. We argue that a combination of loss aversion and mental accounting operations explains why patients discontinue with therapy at a specific point in time. We designed a randomized laboratory economic experiment with a student subject pool to investigate the behavioral predictions. Subjects continue with therapy as long as experienced utility losses have to be compensated. As soon as previous losses are evened out, subjects perceive the marginal benefit of persistence lower than in the beginning of the treatment. Consequently, subjects start to discontinue with therapy. Our results highlight that concepts of behavioral economics capture the dynamic structure of medical nonpersistence better than does standard economic choice theory. We recommend that behavioral economics should be a mandatory part of the development of possible intervention strategies aimed at improving patients' compliance and persistence behavior. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  7. A suite of R packages for web-enabled modeling and analysis of surface waters

    Science.gov (United States)

    Read, J. S.; Winslow, L. A.; Nüst, D.; De Cicco, L.; Walker, J. I.

    2014-12-01

    Researchers often create redundant methods for downloading, manipulating, and analyzing data from online resources. Moreover, the reproducibility of science can be hampered by complicated and voluminous data, lack of time for documentation and long-term maintenance of software, and fear of exposing programming skills. The combination of these factors can encourage unshared one-off programmatic solutions instead of openly provided reusable methods. Federal and academic researchers in the water resources and informatics domains have collaborated to address these issues. The result of this collaboration is a suite of modular R packages that can be used independently or as elements in reproducible analytical workflows. These documented and freely available R packages were designed to fill basic needs for the effective use of water data: the retrieval of time-series and spatial data from web resources (dataRetrieval, geoknife), performing quality assurance and quality control checks of these data with robust statistical methods (sensorQC), the creation of useful data derivatives (including physically- and biologically-relevant indices; GDopp, LakeMetabolizer), and the execution and evaluation of models (glmtools, rLakeAnalyzer). Here, we share details and recommendations for the collaborative coding process, and highlight the benefits of an open-source tool development pattern with a popular programming language in the water resources discipline (such as R). We provide examples of reproducible science driven by large volumes of web-available data using these tools, explore benefits of accessing packages as standardized web processing services (WPS) and present a working platform that allows domain experts to publish scientific algorithms in a service-oriented architecture (WPS4R). We assert that in the era of open data, tools that leverage these data should also be freely shared, transparent, and developed in an open innovation environment.

  8. Interpreting DNAPL saturations in a laboratory-scale injection using one- and two-dimensional modeling of GPR Data

    Science.gov (United States)

    Johnson, R.H.; Poeter, E.P.

    2005-01-01

    Ground-penetrating radar (GPR) is used to track a dense non-aqueous phase liquid (DNAPL) injection in a laboratory sand tank. Before modeling, the GPR data provide a qualitative image of DNAPL saturation and movement. One-dimensional (1D) GPR modeling provides a quantitative interpretation of DNAPL volume within a given thickness during and after the injection. DNAPL saturation in sublayers of a specified thickness could not be quantified because calibration of the 1D GPR model is nonunique when both permittivity and depth of multiple layers are unknown. One-dimensional GPR modeling of the sand tank indicates geometric interferences in a small portion of the tank. These influences are removed from the interpretation using an alternate matching target. Two-dimensional (2D) GPR modeling provides a qualitative interpretation of the DNAPL distribution through pattern matching and tests for possible 2D influences that are not accounted for in the 1D GPR modeling. Accurate quantitative interpretation of DNAPL volumes using GPR modeling requires (1) identification of a suitable target that produces a strong reflection and is not subject to any geometric interference; (2) knowledge of the exact depth of that target; and (3) use of two-way radar-wave travel times through the medium to the target to determine the permittivity of the intervening material, which eliminates reliance on signal amplitude. With geologic conditions that are suitable for GPR surveys (i.e., shallow depths, low electrical conductivities, and a known reflective target), the procedures in this laboratory study can be adapted to a field site to delineate shallow DNAPL source zones.

  9. Fuzzy knot theory interpretation of Yang-Mills instantons and Witten's 5-Brane model

    International Nuclear Information System (INIS)

    El Naschie, M.S.

    2008-01-01

    A knot theory interpretation of 'tHooft's instanton based on hyperbolic volume, crossing numbers and exceptional Lie symmetry groups is given. Subsequently it is shown that although instantons and particle-like states of Heterotic super strings may appear to be different concepts, on a very deep fuzzy level they are not

  10. Exploring Prospective Secondary Mathematics Teachers' Interpretation of Student Thinking through Analysing Students' Work in Modelling

    Science.gov (United States)

    Didis, Makbule Gozde; Erbas, Ayhan Kursat; Cetinkaya, Bulent; Cakiroglu, Erdinc; Alacaci, Cengiz

    2016-01-01

    Researchers point out the importance of teachers' knowledge of student thinking and the role of examining student work in various contexts to develop a knowledge base regarding students' ways of thinking. This study investigated prospective secondary mathematics teachers' interpretations of students' thinking as manifested in students' work that…

  11. Modeling and Inversion Methods for the Interpretation of Resistivity Logging Tool Response

    NARCIS (Netherlands)

    Anderson, B.I.

    2001-01-01

    The electrical resistivity measured by well logging tools is one of the most important rock parameters for indicating the amount of hydrocarbons present in a reservoir. The main interpretation challenge is to invert the measured data, solving for the true resistivity values in each zone of a

  12. MALDI-TOF-MS with PLS Modeling Enables Strain Typing of the Bacterial Plant Pathogen Xanthomonas axonopodis

    Science.gov (United States)

    Sindt, Nathan M.; Robison, Faith; Brick, Mark A.; Schwartz, Howard F.; Heuberger, Adam L.; Prenni, Jessica E.

    2017-11-01

    Matrix-assisted desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) is a fast and effective tool for microbial species identification. However, current approaches are limited to species-level identification even when genetic differences are known. Here, we present a novel workflow that applies the statistical method of partial least squares discriminant analysis (PLS-DA) to MALDI-TOF-MS protein fingerprint data of Xanthomonas axonopodis, an important bacterial plant pathogen of fruit and vegetable crops. Mass spectra of 32 X. axonopodis strains were used to create a mass spectral library and PLS-DA was employed to model the closely related strains. A robust workflow was designed to optimize the PLS-DA model by assessing the model performance over a range of signal-to-noise ratios (s/n) and mass filter (MF) thresholds. The optimized parameters were observed to be s/n = 3 and MF = 0.7. The model correctly classified 83% of spectra withheld from the model as a test set. A new decision rule was developed, termed the rolled-up Maximum Decision Rule (ruMDR), and this method improved identification rates to 92%. These results demonstrate that MALDI-TOF-MS protein fingerprints of bacterial isolates can be utilized to enable identification at the strain level. Furthermore, the open-source framework of this workflow allows for broad implementation across various instrument platforms as well as integration with alternative modeling and classification algorithms. [Figure not available: see fulltext.

  13. DLNA: a simple one-dimensional dynamical model as a possible interpretation of fragment size distribution in nuclear multifragmentation

    International Nuclear Information System (INIS)

    Lacroix, D.; Dayras, R.

    1996-08-01

    The possibility of interpreting multifragmentation data obtained from heavy-ion collisions at intermediate energies, by a new type of model: the DLNA (Dynamical Limited Nuclear Aggregation) is discussed. This model is connected to a more general class of models presenting Self-Organization Criticality (SOC). It is shown that the fragment size distributions exhibit a power-law dependence comparable to those obtained in second-order phase transition or percolation models. Fluctuations in term of scaled-factorial moments and cumulants are also studied: no signal of intermittency is seen. (K.A.)

  14. Conference Interpreters

    DEFF Research Database (Denmark)

    Leal Lobato, Ana Isabel

    2017-01-01

    Conference Interpreters: How to serve the cause of minorized communities in the new postmonolingual / ‘postmonodiscoursive’ order,......Conference Interpreters: How to serve the cause of minorized communities in the new postmonolingual / ‘postmonodiscoursive’ order,...

  15. Lithostratigraphic interpretation from joint analysis of seismic tomography and magnetotelluric resistivity models using self-organizing map techniques

    Science.gov (United States)

    Bauer, K.; Muñoz, G.; Moeck, I.

    2012-12-01

    The combined interpretation of different models as derived from seismic tomography and magnetotelluric (MT) inversion represents a more efficient approach to determine the lithology of the subsurface compared with the separate treatment of each discipline. Such models can be developed independently or by application of joint inversion strategies. After the step of model generation using different geophysical methodologies, a joint interpretation work flow includes the following steps: (1) adjustment of a joint earth model based on the adapted, identical model geometry for the different methods, (2) classification of the model components (e.g. model blocks described by a set of geophysical parameters), and (3) re-mapping of the classified rock types to visualise their distribution within the earth model, and petrophysical characterization and interpretation. One possible approach for the classification of multi-parameter models is based on statistical pattern recognition, where different models are combined and translated into probability density functions. Classes of rock types are identified in these methods as isolated clusters with high probability density function values. Such techniques are well-established for the analysis of two-parameter models. Alternatively we apply self-organizing map (SOM) techniques, which have no limitations in the number of parameters to be analysed in the joint interpretation. Our SOM work flow includes (1) generation of a joint earth model described by so-called data vectors, (2) unsupervised learning or training, (3) analysis of the feature map by adopting image processing techniques, and (4) application of the knowledge to derive a lithological model which is based on the different geophysical parameters. We show the usage of the SOM work flow for a synthetic and a real data case study. Both tests rely on three geophysical properties: P velocity and vertical velocity gradient from seismic tomography, and electrical resistivity

  16. Using Water and Agrochemicals in the Soil, Crop and Vadose Environment (WAVE Model to Interpret Nitrogen Balance and Soil Water Reserve Under Different Tillage Managements

    Directory of Open Access Journals (Sweden)

    Zare Narjes

    2014-10-01

    Full Text Available Applying models to interpret soil, water and plant relationships under different conditions enable us to study different management scenarios and then to determine the optimum option. The aim of this study was using Water and Agrochemicals in the soil, crop and Vadose Environment (WAVE model to predict water content, nitrogen balance and its components over a corn crop season under both conventional tillage (CT and direct seeding into mulch (DSM. In this study a corn crop was cultivated at the Irstea experimental station in Montpellier, France under both CT and DSM. Model input data were weather data, nitrogen content in both the soil and mulch at the beginning of the season, the amounts and the dates of irrigation and nitrogen application. The results show an appropriate agreement between measured and model simulations (nRMSE < 10%. Using model outputs, nitrogen balance and its components were compared with measured data in both systems. The amount of N leaching in validation period were 10 and 8 kgha–1 in CT and DSM plots, respectively; therefore, these results showed better performance of DSM in comparison with CT. Simulated nitrogen leaching from CT and DSM can help us to assess groundwater pollution risk caused by these two systems.

  17. Improving Service Quality in Technical Education: Use of Interpretive Structural Modeling

    Science.gov (United States)

    Debnath, Roma Mitra; Shankar, Ravi

    2012-01-01

    Purpose: The purpose of this paper is to identify the relevant enablers and barriers related to technical education. It seeks to critically analyze the relationship amongst them so that policy makers can focus on relevant parameters to improve the service quality of technical education. Design/methodology/approach: The present study employs the…

  18. New interpretation of arterial stiffening due to cigarette smoking using a structurally motivated constitutive model

    DEFF Research Database (Denmark)

    Enevoldsen, Majken; Henneberg, K-A; Jensen, J A

    2011-01-01

    Cigarette smoking is the leading self-inflicted risk factor for cardiovascular diseases; it causes arterial stiffening with serious sequelea including atherosclerosis and abdominal aortic aneurysms. This work presents a new interpretation of arterial stiffening caused by smoking based on data...... published for rat pulmonary arteries. A structurally motivated "four fiber family" constitutive relation was used to fit the available biaxial data and associated best-fit values of material parameters were estimated using multivariate nonlinear regression. Results suggested that arterial stiffening caused...

  19. GATE V6: a major enhancement of the GATE simulation platform enabling modelling of CT and radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Jan, S; Becheva, E [DSV/I2BM/SHFJ, Commissariat a l' Energie Atomique, Orsay (France); Benoit, D; Rehfeld, N; Stute, S; Buvat, I [IMNC-UMR 8165 CNRS-Paris 7 and Paris 11 Universities, 15 rue Georges Clemenceau, 91406 Orsay Cedex (France); Carlier, T [INSERM U892-Cancer Research Center, University of Nantes, Nantes (France); Cassol, F; Morel, C [Centre de physique des particules de Marseille, CNRS-IN2P3 and Universite de la Mediterranee, Aix-Marseille II, 163, avenue de Luminy, 13288 Marseille Cedex 09 (France); Descourt, P; Visvikis, D [INSERM, U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), CHU Morvan, Brest (France); Frisson, T; Grevillot, L; Guigues, L; Sarrut, D; Zahra, N [Universite de Lyon, CREATIS, CNRS UMR5220, Inserm U630, INSA-Lyon, Universite Lyon 1, Centre Leon Berard (France); Maigne, L; Perrot, Y [Laboratoire de Physique Corpusculaire, 24 Avenue des Landais, 63177 Aubiere Cedex (France); Schaart, D R [Delft University of Technology, Radiation Detection and Medical Imaging, Mekelweg 15, 2629 JB Delft (Netherlands); Pietrzyk, U, E-mail: buvat@imnc.in2p3.fr [Reseach Center Juelich, Institute of Neurosciences and Medicine and Department of Physics, University of Wuppertal (Germany)

    2011-02-21

    GATE (Geant4 Application for Emission Tomography) is a Monte Carlo simulation platform developed by the OpenGATE collaboration since 2001 and first publicly released in 2004. Dedicated to the modelling of planar scintigraphy, single photon emission computed tomography (SPECT) and positron emission tomography (PET) acquisitions, this platform is widely used to assist PET and SPECT research. A recent extension of this platform, released by the OpenGATE collaboration as GATE V6, now also enables modelling of x-ray computed tomography and radiation therapy experiments. This paper presents an overview of the main additions and improvements implemented in GATE since the publication of the initial GATE paper (Jan et al 2004 Phys. Med. Biol. 49 4543-61). This includes new models available in GATE to simulate optical and hadronic processes, novelties in modelling tracer, organ or detector motion, new options for speeding up GATE simulations, examples illustrating the use of GATE V6 in radiotherapy applications and CT simulations, and preliminary results regarding the validation of GATE V6 for radiation therapy applications. Upon completion of extensive validation studies, GATE is expected to become a valuable tool for simulations involving both radiotherapy and imaging.

  20. Tumor-Specific Fluorescent Antibody Imaging Enables Accurate Staging Laparoscopy in an Orthotopic Model of Pancreatic Cancer

    Science.gov (United States)

    Cao, Hop S Tran; Kaushal, Sharmeela; Metildi, Cristina A; Menen, Rhiana S; Lee, Claudia; Snyder, Cynthia S; Messer, Karen; Pu, Minya; Luiken, George A; Talamini, Mark A; Hoffman, Robert M; Bouvet, Michael

    2014-01-01

    Background/Aims Laparoscopy is important in staging pancreatic cancer, but false negatives remain problematic. Making tumors fluorescent has the potential to improve the accuracy of staging laparoscopy. Methodology Orthotopic and carcinomatosis models of pancreatic cancer were established with BxPC-3 human pancreatic cancer cells in nude mice. Alexa488-anti-CEA conjugates were injected via tail vein 24 hours prior to laparoscopy. Mice were examined under bright field laparoscopic (BL) and fluorescence laparoscopic (FL) modes. Outcomes measured included time to identification of primary tumor for the orthotopic model and number of metastases identified within 2 minutes for the carcinomatosis model. Results FL enabled more rapid and accurate identification and localization of primary tumors and metastases than BL. Using BL took statistically significantly longer time than FL. More metastatic lesions were detected and localized under FL compared to BL and with greater accuracy, with sensitivities of 96% vs. 40%, respectively, when compared to control. FL was sensitive enough to detect metastatic lesions laparoscopy with tumors labeled with fluorophore-conjugated anti-CEA antibody permits rapid detection and accurate localization of primary and metastatic pancreatic cancer in an orthotopic model. The results of the present report demonstrate the future clinical potential of fluorescence laparoscopy. PMID:22369743

  1. The debbuggable interpreter design pattern

    OpenAIRE

    Vrany, Jan; Bergel, Alexandre

    2007-01-01

    peer-reviewed The use of Interpreter and Visitor design patterns has been widely adopted to implement programming language interpreters due to their expressive and simple design. However, no general approach to conceive a debugger is commonly adopted. This paper presents the debuggable interpreter design pattern as a general approach to extend a language interpreter with debugging facilities such as step-over and step-into. Moreover, it enables multiple debuggers coexisting and extends ...

  2. Enablers and inhibitors of the implementation of the Casalud Model, a Mexican innovative healthcare model for non-communicable disease prevention and control.

    Science.gov (United States)

    Tapia-Conyer, Roberto; Saucedo-Martinez, Rodrigo; Mujica-Rosales, Ricardo; Gallardo-Rincon, Hector; Campos-Rivera, Paola Abril; Lee, Evan; Waugh, Craig; Guajardo, Lucia; Torres-Beltran, Braulio; Quijano-Gonzalez, Ursula; Soni-Gallardo, Lidia

    2016-07-22

    The Mexican healthcare system is under increasing strain due to the rising prevalence of non-communicable diseases (especially type 2 diabetes), mounting costs, and a reactive curative approach focused on treating existing diseases and their complications rather than preventing them. Casalud is a comprehensive primary healthcare model that enables proactive prevention and disease management throughout the continuum of care, using innovative technologies and a patient-centred approach. Data were collected over a 2-year period in eight primary health clinics (PHCs) in two states in central Mexico to identify and assess enablers and inhibitors of the implementation process of Casalud. We used mixed quantitative and qualitative data collection tools: surveys, in-depth interviews, and participant and non-participant observations. Transcripts and field notes were analyzed and coded using Framework Analysis, focusing on defining and describing enablers and inhibitors of the implementation process. We identified seven recurring topics in the analyzed textual data. Four topics were categorized as enablers: political support for the Casalud model, alignment with current healthcare trends, ongoing technical improvements (to ease adoption and support), and capacity building. Three topics were categorized as inhibitors: administrative practices, health clinic human resources, and the lack of a shared vision of the model. Enablers are located at PHCs and across all levels of government, and include political support for, and the technological validity of, the model. The main inhibitor is the persistence of obsolete administrative practices at both state and PHC levels, which puts the administrative feasibility of the model's implementation in jeopardy. Constructing a shared vision around the model could facilitate the implementation of Casalud as well as circumvent administrative inhibitors. In order to overcome PHC-level barriers, it is crucial to have an efficient and

  3. Application of the Perceptual Factors, Enabling and Reinforcing Model on Pap Smaear Screening in Iranian Northern Woman

    Directory of Open Access Journals (Sweden)

    Abolhassan Naghibi

    2016-03-01

    Full Text Available Background and Purpose: Cervical cancer is the most prevalent cancer among women in the world. Cervical cancer is no symptoms and can be treated if diagnosed in the first stage of the disease. The aim of this study was to survey the affecting factors of the Pap smears test on perceptual factors, enabling and reinforcing (PEN-3 model constructs in women. Materials and Methods: This study was a descriptive cross-sectional study. The sample size was 416 married women with random sampling. The questionnaire had 50 questions based on PEN-3 model structures. Data were analyzed by descriptive statistics and logistic regression method in software SPSS 20. Results: The mean age of women was 32.70 ± 21.00 years. The knowledge of risk factors and screening methods for cervical cancer was 37.2. About 40% of women had a history of Pap smears. The most important of perception factors were effective, family history of the disease, encourage people to Pap smear, and fear of detecting of cervical cancer. The most important enabling factors were the presence of expert health personnel to provide training and Pap smear test (50.3%, lack of time and too busy to do Pap smear test (23.2%. The reinforcing factors were the media advice (41.3%, doctor’s advice (32.5% and neglect and forgetfulness (36.2%. Conclusion: This study has shown the Pap smear screening behavior affected by personal factors, family, cultural and economic. Application of PEN-3 can effective in planning and designing intervention programs for cervical cancer screening.

  4. Using Enabling Technologies to Facilitate the Comparison of Satellite Observations with the Model Forecasts for Hurricane Study

    Science.gov (United States)

    Li, P.; Knosp, B.; Hristova-Veleva, S. M.; Niamsuwan, N.; Johnson, M. P.; Shen, T. P. J.; Tanelli, S.; Turk, J.; Vu, Q. A.

    2014-12-01

    Due to their complexity and volume, the satellite data are underutilized in today's hurricane research and operations. To better utilize these data, we developed the JPL Tropical Cyclone Information System (TCIS) - an Interactive Data Portal providing fusion between Near-Real-Time satellite observations and model forecasts to facilitate model evaluation and improvement. We have collected satellite observations and model forecasts in the Atlantic Basin and the East Pacific for the hurricane seasons since 2010 and supported the NASA Airborne Campaigns for Hurricane Study such as the Genesis and Rapid Intensification Processes (GRIP) in 2010 and the Hurricane and Severe Storm Sentinel (HS3) from 2012 to 2014. To enable the direct inter-comparisons of the satellite observations and the model forecasts, the TCIS was integrated with the NASA Earth Observing System Simulator Suite (NEOS3) to produce synthetic observations (e.g. simulated passive microwave brightness temperatures) from a number of operational hurricane forecast models (HWRF and GFS). An automated process was developed to trigger NEOS3 simulations via web services given the location and time of satellite observations, monitor the progress of the NEOS3 simulations, display the synthetic observation and ingest them into the TCIS database when they are done. In addition, three analysis tools, the joint PDF analysis of the brightness temperatures, ARCHER for finding the storm-center and the storm organization and the Wave Number Analysis tool for storm asymmetry and morphology analysis were integrated into TCIS to provide statistical and structural analysis on both observed and synthetic data. Interactive tools were built in the TCIS visualization system to allow the spatial and temporal selections of the datasets, the invocation of the tools with user specified parameters, and the display and the delivery of the results. In this presentation, we will describe the key enabling technologies behind the design of

  5. How to interpret the results of medical time series data analysis: Classical statistical approaches versus dynamic Bayesian network modeling.

    Science.gov (United States)

    Onisko, Agnieszka; Druzdzel, Marek J; Austin, R Marshall

    2016-01-01

    Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the Bayesian approach, argued by many of its proponents to be superior to the classical frequentist approach, is still not well-recognized in the analysis of medical data. The goal of this study is to encourage data analysts to use the Bayesian approach, such as modeling with graphical probabilistic networks, as an insightful alternative to classical statistical analysis of medical data. This paper offers a comparison of two approaches to analysis of medical time series data: (1) classical statistical approach, such as the Kaplan-Meier estimator and the Cox proportional hazards regression model, and (2) dynamic Bayesian network modeling. Our comparison is based on time series cervical cancer screening data collected at Magee-Womens Hospital, University of Pittsburgh Medical Center over 10 years. The main outcomes of our comparison are cervical cancer risk assessments produced by the three approaches. However, our analysis discusses also several aspects of the comparison, such as modeling assumptions, model building, dealing with incomplete data, individualized risk assessment, results interpretation, and model validation. Our study shows that the Bayesian approach is (1) much more flexible in terms of modeling effort, and (2) it offers an individualized risk assessment, which is more cumbersome for classical statistical approaches.

  6. A healthy fear of the unknown: perspectives on the interpretation of parameter fits from computational models in neuroscience.

    Directory of Open Access Journals (Sweden)

    Matthew R Nassar

    2013-04-01

    Full Text Available Fitting models to behavior is commonly used to infer the latent computational factors responsible for generating behavior. However, the complexity of many behaviors can handicap the interpretation of such models. Here we provide perspectives on problems that can arise when interpreting parameter fits from models that provide incomplete descriptions of behavior. We illustrate these problems by fitting commonly used and neurophysiologically motivated reinforcement-learning models to simulated behavioral data sets from learning tasks. These model fits can pass a host of standard goodness-of-fit tests and other model-selection diagnostics even when the models do not provide a complete description of the behavioral data. We show that such incomplete models can be misleading by yielding biased estimates of the parameters explicitly included in the models. This problem is particularly pernicious when the neglected factors are unknown and therefore not easily identified by model comparisons and similar methods. An obvious conclusion is that a parsimonious description of behavioral data does not necessarily imply an accurate description of the underlying computations. Moreover, general goodness-of-fit measures are not a strong basis to support claims that a particular model can provide a generalized understanding of the computations that govern behavior. To help overcome these challenges, we advocate the design of tasks that provide direct reports of the computational variables of interest. Such direct reports complement model-fitting approaches by providing a more complete, albeit possibly more task-specific, representation of the factors that drive behavior. Computational models then provide a means to connect such task-specific results to a more general algorithmic understanding of the brain.

  7. Visual Environment for Rich Data Interpretation (VERDI) program for environmental modeling systems

    Science.gov (United States)

    VERDI is a flexible, modular, Java-based program used for visualizing multivariate gridded meteorology, emissions and air quality modeling data created by environmental modeling systems such as the CMAQ model and WRF.

  8. New interpretation of arterial stiffening due to cigarette smoking using a structurally motivated constitutive model

    DEFF Research Database (Denmark)

    Enevoldsen, Marie Sand; Henneberg, Kaj-Åge; Jensen, Jørgen Arendt

    2011-01-01

    Cigarette smoking is the leading self-inflicted risk factor for cardiovascular diseases; it causes arterial stiffening with serious sequelea including atherosclerosis and abdominal aortic aneurysms. This work presents a new interpretation of arterial stiffening caused by smoking based on data...... published for rat pulmonary arteries. A structurally motivated ‘‘four fiber family’’ constitutive relation was used to fit the available biaxial data and associated best-fit values of material parameters were estimated using multivariate nonlinear regression. Results suggested that arterial stiffening...

  9. Interpretive Journalism

    OpenAIRE

    Salgado, Susana; Strömbäck, Jesper; Aalberg, Toril; Esser, Frank

    2017-01-01

    In summary one-third of the political coverage analyzed in the 16 countries was found to contain interpretive journalism, with some countries - including France and the United States - making use of it much more than the rest. Indeed, the story genres and the interpretive journalism used in the various countries differ substantially, indicating distinct motives and news cultures. A multivariate analysis conducted to identify the most powerful predictors of interpretive journ...

  10. Linguistics in Text Interpretation

    DEFF Research Database (Denmark)

    Togeby, Ole

    2011-01-01

    A model for how text interpretation proceeds from what is pronounced, through what is said to what is comunicated, and definition of the concepts 'presupposition' and 'implicature'.......A model for how text interpretation proceeds from what is pronounced, through what is said to what is comunicated, and definition of the concepts 'presupposition' and 'implicature'....

  11. Linguistic Processing in a Mathematics Tutoring System: Cooperative Input Interpretation and Dialogue Modelling

    Science.gov (United States)

    Wolska, Magdalena; Buckley, Mark; Horacek, Helmut; Kruijff-Korbayová, Ivana; Pinkal, Manfred

    Formal domains, such as mathematics, require exact language to communicate the intended content. Special symbolic notations are used to express the semantics precisely, compactly, and unambiguously. Mathematical textbooks offer plenty of examples of concise, accurate presentations. This effective communication is enabled by interleaved use of formulas and natural language. Since natural language interaction has been shown to be an important factor in the efficiency of human tutoring [29], it would be desirable to enhance interaction with Intelligent Tutoring Systems for mathematics by allowing elements of mixed language combining the exactness of formal expressions with natural language flexibility.

  12. Construction and Optimization of a Heterologous Pathway for Protocatechuate Catabolism in Escherichia coli Enables Bioconversion of Model Aromatic Compounds

    Energy Technology Data Exchange (ETDEWEB)

    Clarkson, Sonya M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biosciences Division; Giannone, Richard J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Chemical Sciences Division; Kridelbaugh, Donna M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biosciences Division; Elkins, James G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biosciences Division; Guss, Adam M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biosciences Division; Michener, Joshua K. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biosciences Division, BioEnergy Science Center; Vieille, Claire [Michigan State Univ., East Lansing, MI (United States)

    2017-07-21

    The production of biofuels from lignocellulose yields a substantial lignin by-product stream that currently has few applications. Biological conversion of lignin-derived compounds into chemicals and fuels has the potential to improve the economics of lignocellulose-derived biofuels, but few microbes are able both to catabolize lignin-derived aromatic compounds and to generate valuable products. WhileEscherichia colihas been engineered to produce a variety of fuels and chemicals, it is incapable of catabolizing most aromatic compounds. Therefore, we engineeredE. colito catabolize protocatechuate, a common intermediate in lignin degradation, as the sole source of carbon and energy via heterologous expression of a nine-gene pathway fromPseudomonas putidaKT2440. Then, we used experimental evolution to select for mutations that increased growth with protocatechuate more than 2-fold. Increasing the strength of a single ribosome binding site in the heterologous pathway was sufficient to recapitulate the increased growth. After optimization of the core pathway, we extended the pathway to enable catabolism of a second model compound, 4-hydroxybenzoate. These engineered strains will be useful platforms to discover, characterize, and optimize pathways for conversions of lignin-derived aromatics.

    IMPORTANCELignin is a challenging substrate for microbial catabolism due to its polymeric and heterogeneous chemical structure. Therefore, engineering microbes for improved catabolism of lignin-derived aromatic compounds will require the assembly of an entire network of catabolic reactions, including pathways from genetically intractable strains. By constructing defined pathways for aromatic compound degradation in a model host would allow rapid

  13. Fast bootstrapping and permutation testing for assessing reproducibility and interpretability of multivariate fMRI decoding models.

    Directory of Open Access Journals (Sweden)

    Bryan R Conroy

    Full Text Available Multivariate decoding models are increasingly being applied to functional magnetic imaging (fMRI data to interpret the distributed neural activity in the human brain. These models are typically formulated to optimize an objective function that maximizes decoding accuracy. For decoding models trained on full-brain data, this can result in multiple models that yield the same classification accuracy, though some may be more reproducible than others--i.e. small changes to the training set may result in very different voxels being selected. This issue of reproducibility can be partially controlled by regularizing the decoding model. Regularization, along with the cross-validation used to estimate decoding accuracy, typically requires retraining many (often on the order of thousands of related decoding models. In this paper we describe an approach that uses a combination of bootstrapping and permutation testing to construct both a measure of cross-validated prediction accuracy and model reproducibility of the learned brain maps. This requires re-training our classification method on many re-sampled versions of the fMRI data. Given the size of fMRI datasets, this is normally a time-consuming process. Our approach leverages an algorithm called fast simultaneous training of generalized linear models (FaSTGLZ to create a family of classifiers in the space of accuracy vs. reproducibility. The convex hull of this family of classifiers can be used to identify a subset of Pareto optimal classifiers, with a single-optimal classifier selectable based on the relative cost of accuracy vs. reproducibility. We demonstrate our approach using full-brain analysis of elastic-net classifiers trained to discriminate stimulus type in an auditory and visual oddball event-related fMRI design. Our approach and results argue for a computational approach to fMRI decoding models in which the value of the interpretation of the decoding model ultimately depends upon optimizing a

  14. Two-zone model for the broadband Crab nebula spectrum: microscopic interpretation

    Directory of Open Access Journals (Sweden)

    Fraschetti F.

    2017-01-01

    Full Text Available We develop a simple two-zone interpretation of the broadband baseline Crab nebula spectrum between 10−5 eV and ~ 100 TeV by using two distinct log-parabola energetic electrons distributions. We determine analytically the very-high energy photon spectrum as originated by inverse-Compton scattering of the far-infrared soft ambient photons within the nebula off a first population of electrons energized at the nebula termination shock. The broad and flat 200 GeV peak jointly observed by Fermi/LAT and MAGIC is naturally reproduced. The synchrotron radiation from a second energetic electron population explains the spectrum from the radio range up to ~ 10 keV. We infer from observations the energy dependence of the microscopic probability of remaining in proximity of the shock of the accelerating electrons.

  15. Effects of waveform model systematics on the interpretation of GW150914

    NARCIS (Netherlands)

    Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Phythian-Adams, A.T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.T.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K.M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, R.D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Beer, C.; Bejger, M.; Belahcene, I.; Belgin, M.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, M.J.; Birney, R.; Birnholtz, O.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, A.L.S.; Bock, O.; Boer, M.; Bogaert, J.G.; Bohe, A.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, A.D.; Brown, D.; Brown, N. M.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, D. S.; Charlton, P.; Chassande-Mottin, E.; Cheeseboro, B. D.; Chen, H. Y.; Chen, Y; Cheng, H. -P.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Qian; Chua, A. J. K.; Chua, S. S. Y.; Chung, E.S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P. -F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M., Jr.; Conti, L.; Cooper, S. J.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, A.C.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J. -P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, Laura; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Daw, E. J.; Day, B.; Day, R.; De, S.; Debra, D.; Debreczeni, G.; Degallaix, J.; De laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dergachev, V.A.; Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Devenson, J.; Devine, R. C.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Giovanni, M. Di; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H. -B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Eisenstein, R. A.; Essick, R. C.; Etienne, Z.; Etzel, T.; Evans, T. M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.M.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Fernández Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M; Fong, H.; Forsyth, S. S.; Fournier, J. -D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.P.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Lee-Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.M.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Buffoni-Hall, R.; Hall, E. D.; Hammond, G.L.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, P.J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C. -J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.A.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J. -M.; Isi, M.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W.; Jones, I.D.; Jones, R.; Jonker, R. J.G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.H.; Kanner, J. B.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kelley, D. B.; Kennedy, R.E.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan., S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, Whansun; Kim, W.; Kim, Y.M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kirchhoff, R.; Kissel, J. S.; Klein, B.; Kleybolte, L.; Klimenko, S.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C.H.; Lee, K.H.; Lee, M.H.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G.F.; Libson, A.; Littenberg, T. B.; Liu, J.; Lockerbie, N. A.; Lombardi, A. L.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lovelace, G.; Lück, H.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGrath Hoareau, C.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, A. L.; Miller, B.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B.C.; Moore, Brian C J; Moraru, D.; Gutierrez Moreno, M.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, S.D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muniz, E. A. M.; Murray, P.G.; Mytidis, A.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nelemans, G.; Nelson, T. J. N.; Gutierrez-Neri, M.; Nery, M.; Neunzert, A.; Newport, J. M.; Newton-Howes, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; Oelker, E.; Ogin, G. H.; Oh, J.; Oh, S. H.; Ohme, F.; Oliver, M. B.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.S; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Castro-Perez, J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Rhoades, E.; Ricci, F.; Riles, K.; Rizzo, D.M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.A.; Sachdev, Perminder S; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sandberg, V.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheuer, J.; Schmidt, E.; Schmidt, J; Schmidt, P.; Schnabel, R.B.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, K.E.C.; Schuette, D.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, M.S.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Setyawati, Y.; Shaddock, D. A.; Shaffer, T. J.; Shahriar, M. S.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, António Dias da; Singer, A; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, R. J. E.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stevenson-Moore, P.; Stone, J.R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.D.; Talukder, D.; Tanner, D. B.; Tápai, M.; Taracchini, A.; Taylor, W.R.; Theeg, T.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Tippens, T.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tomlinson, C.; Tonelli, M.; Tornasi, Z.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifir, D.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tse, M.; Tso, R.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; Van Bakel, N.; Van Beuzekom, Martin; Van Den Brand, J. F.J.; Van Den Broeck, C.F.F.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P.J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J. -Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, MT; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L. -W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.M.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Williams, D.; Williams, D.R.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Worden, J.; Wright, J.L.; Wu, D.S.; Wu, G.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, Hang; Yu, Haocun; Yvert, M.; Zadrożny, A.; Zangrando, L.; Zanolin, M.; Zendri, J. -P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S.J.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; Boyle, M.; Chu, I.W.T.; Hemberger, D.; Hinder, I.; Kidder, L. E.; Ossokine, S.; Scheel, M.; Szilagyi, B.; Teukolsky, S.; Vano-Vinuales, A.

    2017-01-01

    Parameter estimates of GW150914 were obtained using Bayesian inference, based on three semi-analytic waveform models for binary black hole coalescences. These waveform models differ from each other in their treatment of black hole spins, and all three models make some simplifying assumptions,

  16. An Outcrop-based Detailed Geological Model to Test Automated Interpretation of Seismic Inversion Results

    NARCIS (Netherlands)

    Feng, R.; Sharma, S.; Luthi, S.M.; Gisolf, A.

    2015-01-01

    Previously, Tetyukhina et al. (2014) developed a geological and petrophysical model based on the Book Cliffs outcrops that contained eight lithotypes. For reservoir modelling purposes, this model is judged to be too coarse because in the same lithotype it contains reservoir and non-reservoir

  17. Interpretation of cloud-climate feedback as produced by 14 atmospheric general circulation models

    Science.gov (United States)

    Cess, R. D.; Potter, G. L.; Ghan, S. J.; Blanchet, J. P.; Boer, G. J.

    1989-01-01

    Understanding the cause of differences among general circulation model projections of carbon dioxide-induced climatic change is a necessary step toward improving the models. An intercomparison of 14 atmospheric general circulation models, for which sea surface temperature perturbations were used as a surrogate climate change, showed that there was a roughly threefold variation in global climate sensitivity. Most of this variation is attributable to differences in the models' depictions of cloud-climate feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as climatic predictors.

  18. Interpretation miniatures

    Science.gov (United States)

    Nikolić, Hrvoje

    Most physicists do not have patience for reading long and obscure interpretation arguments and disputes. Hence, to attract attention of a wider physics community, in this paper various old and new aspects of quantum interpretations are explained in a concise and simple (almost trivial) form. About the “Copenhagen” interpretation, we note that there are several different versions of it and explain how to make sense of “local nonreality” interpretation. About the many-world interpretation (MWI), we explain that it is neither local nor nonlocal, that it cannot explain the Born rule, that it suffers from the preferred basis problem, and that quantum suicide cannot be used to test it. About the Bohmian interpretation, we explain that it is analogous to dark matter, use it to explain that there is no big difference between nonlocal correlation and nonlocal causation, and use some condensed-matter ideas to outline how nonrelativistic Bohmian theory could be a theory of everything. We also explain how different interpretations can be used to demystify the delayed choice experiment, to resolve the problem of time in quantum gravity, and to provide alternatives to quantum nonlocality. Finally, we explain why is life compatible with the second law.

  19. Animal-Assisted Therapy for persons with disabilities based on canine tail language interpretation via fuzzy emotional behavior model.

    Science.gov (United States)

    Phanwanich, Warangkhana; Kumdee, Orrawan; Ritthipravat, Panrasee; Wongsawat, Yodchanan

    2011-01-01

    Animal-Assisted Therapy (AAT) is the science that employs the merit of human-animal interaction to alleviate mental and physical problems of persons with disabilities. However, to achieve the goal of AAT for persons with severe disabilities (e.g. spinal cord injury and amyotrophic lateral sclerosis), real-time animal language interpretation is needed. Since canine behaviors can be visually distinguished from its tail, this paper proposes the automatic real-time interpretation of canine tail language for human-canine interaction in the case of persons with severe disabilities. Canine tail language is captured via two 3-axis accelerometers. Directions and frequency are selected as our features of interests. New fuzzy rules and center of gravity (COG)-based defuzzification method are proposed in order to interpret the features into three canine emotional behaviors, i.e., agitate, happy, and scare as well as its blended emotional behaviors. The emotional behavior model is performed in the simulated dog. The average recognition rate in real dog is 93.75% accuracy.

  20. Impact of the interfaces for wind and wave modeling - interpretation using COAWST, SAR and point measurements

    DEFF Research Database (Denmark)

    Air and sea interacts, where winds generate waves and waves affect the winds. This topic is ever relevant for offshore functions such as shipping, portal routines, wind farm operation and maintenance. In a coupled modeling system, the atmospheric modeling and the wave modeling interfere with each...... use the stress directly, thus avoiding the uncertainties caused by parameterizations. This study examines the efficiency of the wave impact transfer to the atmospheric modeling through the two types of interfaces, roughness length and stress, through the coupled-ocean...

  1. Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes

    Science.gov (United States)

    Dugan, Hilary; Woolway, R. Iestyn; Santoso, Arianto; Corman, Jessica; Jaimes, Aline; Nodine, Emily; Patil, Vijay; Zwart, Jacob A.; Brentrup, Jennifer A.; Hetherington, Amy; Oliver, Samantha K.; Read, Jordan S.; Winters, Kirsten; Hanson, Paul; Read, Emily; Winslow, Luke; Weathers, Kathleen

    2016-01-01

    Ecosystem metabolism and the contribution of carbon dioxide from lakes to the atmosphere can be estimated from free-water gas measurements through the use of mass balance models, which rely on a gas transfer coefficient (k) to model gas exchange with the atmosphere. Theoretical and empirically based models of krange in complexity from wind-driven power functions to complex surface renewal models; however, model choice is rarely considered in most studies of lake metabolism. This study used high-frequency data from 15 lakes provided by the Global Lake Ecological Observatory Network (GLEON) to study how model choice of kinfluenced estimates of lake metabolism and gas exchange with the atmosphere. We tested 6 models of k on lakes chosen to span broad gradients in surface area and trophic states; a metabolism model was then fit to all 6 outputs of k data. We found that hourly values for k were substantially different between models and, at an annual scale, resulted in significantly different estimates of lake metabolism and gas exchange with the atmosphere.

  2. Towards a Good Practice Model for an Entrepreneurial HEI: Perspectives of Academics, Enterprise Enablers and Graduate Entrepreneurs

    Science.gov (United States)

    Williams, Perri; Fenton, Mary

    2013-01-01

    This paper reports on an examination of the perspectives of academics, enterprise enablers and graduate entrepreneurs of an entrepreneurial higher education institution (HEI). The research was conducted in Ireland among 30 graduate entrepreneurs and 15 academics and enterprise enablers (enterprise development agency personnel) to provide a…

  3. Objective interpretation as conforming interpretation

    Directory of Open Access Journals (Sweden)

    Lidka Rodak

    2011-12-01

    Full Text Available The practical discourse willingly uses the formula of “objective interpretation”, with no regards to its controversial nature that has been discussed in literature.The main aim of the article is to investigate what “objective interpretation” could mean and how it could be understood in the practical discourse, focusing on the understanding offered by judicature.The thesis of the article is that objective interpretation, as identified with textualists’ position, is not possible to uphold, and should be rather linked with conforming interpretation. And what this actually implies is that it is not the virtue of certainty and predictability – which are usually associated with objectivity- but coherence that makes the foundation of applicability of objectivity in law.What could be observed from the analyses, is that both the phenomenon of conforming interpretation and objective interpretation play the role of arguments in the interpretive discourse, arguments that provide justification that interpretation is not arbitrary or subjective. With regards to the important part of the ideology of legal application which is the conviction that decisions should be taken on the basis of law in order to exclude arbitrariness, objective interpretation could be read as a question “what kind of authority “supports” certain interpretation”? that is almost never free of judicial creativity and judicial activism.One can say that, objective and conforming interpretation are just another arguments used in legal discourse.

  4. Acid deposition modelling and the interpretation of the United Kingdom secondary precipitation network data

    Science.gov (United States)

    Metcalfe, S. E.; Atkins, D. H. F.; Derwent, R. G.

    Acid deposition modelling calculations have been compared against the data obtained during the first year's operation of the United Kingdom Secondary Precipitation Network. The model adopted employed a single level trajectory approach to describe the coupled atmospheric chemistry and deposition of SO x NO y and NH x species. For the precipitation sulphate concentrations, the model results over the 47 network sites correlated well with the observations. When corrections were applied within the model calculations for background deposition and for dry deposition into the bulk collector, then the model results overestimated the precipitation sulphate observations by about 27%. For the precipitation nitrate concentrations, again the model results correlated well with the observations. Over the whole network, the model underestimated the observations by about 6% and no significant background correction was required for background sources. For the precipitation ammonium concentrations, good agreement with the observations could only be obtained if an additional ammonia source over and above that from animal manure was included in the model. One possibility investigated was exhalation from agricultural soils with an emission rate of 50-100 kg NH x ha -1 a -1. The model was able to reproduce the main features of the distributions of NO 2 and NH 3 in terms of gradients across the U.K. and in the location of the respective maxima. However, in both cases, severe underestimation by the model was apparent. The source of this underestimation was found to involve the assumption of complete vertical mixing in the model and the neglect of nocturnal stable layers.

  5. Interpretable exemplar-based shape classification using constrained sparse linear models.

    Science.gov (United States)

    Sigurdsson, Gunnar A; Yang, Zhen; Tran, Trac D; Prince, Jerry L

    2015-02-01

    Many types of diseases manifest themselves as observable changes in the shape of the affected organs. Using shape classification, we can look for signs of disease and discover relationships between diseases. We formulate the problem of shape classification in a holistic framework that utilizes a lossless scalar field representation and a non-parametric classification based on sparse recovery. This framework generalizes over certain classes of unseen shapes while using the full information of the shape, bypassing feature extraction. The output of the method is the class whose combination of exemplars most closely approximates the shape, and furthermore, the algorithm returns the most similar exemplars along with their similarity to the shape, which makes the result simple to interpret. Our results show that the method offers accurate classification between three cerebellar diseases and controls in a database of cerebellar ataxia patients. For reproducible comparison, promising results are presented on publicly available 2D datasets, including the ETH-80 dataset where the method achieves 88.4% classification accuracy.

  6. Use of modeling and simulation in the planning, analysis and interpretation of ultrasonic testing

    International Nuclear Information System (INIS)

    Algernon, Daniel; Grosse, Christian U.

    2016-01-01

    Acoustic testing methods such as ultrasound and impact echo are an important tool in building diagnostics. The range includes thickness measurements, the representation of the internal component geometry as well as the detection of voids (gravel pockets), delaminations or possibly locating grouting faults in the interior of metallic cladding tubes of tendon ducts. Basically acoustic method for non-destructive testing (NDT) is based on the excitation of elastic waves that interact with the target object (e.g. to detect discontinuity in the component) at the acoustic interface. From the signal received at the component surface this interaction shall be detected and interpreted to draw conclusions about the presence of the target object, and optionally to determine its size and position (approximately). Although the basic underlying physical principles of the application of elastic waves in NDT are known, it can be complicated by complex relationships in the form of restricted access, component geometries, or the type and form of reflectors. To estimate the chances of success of a test is already often not trivial. These circumstances highlight the importance of using simulations that allow a theoretically sound basis for testing and allow easy optimizing test systems. The deployable simulation methods are varied. Common are in particular the finite element method, the Elasto Finite Integration Technique and semi-analytical calculation methods. [de

  7. Long-term development of how students interpret a model; Complementarity of contexts and mathematics

    NARCIS (Netherlands)

    Vos, Pauline; Roorda, Gerrit; Stillman, Gloria Ann; Blum, Werner; Kaiser, Gabriele

    2017-01-01

    When students engage in rich mathematical modelling tasks, they have to handle real-world contexts and mathematics in chorus. This is not easy. In this chapter, contexts and mathematics are perceived as complementary, which means they can be integrated. Based on four types of approaches to modelling

  8. Proposal for a Conceptual Model for Evaluating Lean Product Development Performance: A Study of LPD Enablers in Manufacturing Companies

    Science.gov (United States)

    Osezua Aikhuele, Daniel; Mohd Turan, Faiz

    2016-02-01

    The instability in today's market and the emerging demands for mass customized products by customers, are driving companies to seek for cost effective and time efficient improvements in their production system and this have led to real pressure for the adaptation of new developmental architecture and operational parameters to remain competitive in the market. Among such developmental architecture adopted, is the integration of lean thinking in the product development process. However, due to lack of clear understanding of the lean performance and its measurements, many companies are unable to implement and fully integrate the lean principle into their product development process and without a proper performance measurement, the performance level of the organizational value stream will be unknown and the specific area of improvement as it relates to the LPD program cannot be tracked. Hence, it will result in poor decision making in the LPD implementation. This paper therefore seeks to present a conceptual model for evaluation of LPD performances by identifying and analysing the core existing LPD enabler (Chief Engineer, Cross-functional teams, Set-based engineering, Poka-yoke (mistakeproofing), Knowledge-based environment, Value-focused planning and development, Top management support, Technology, Supplier integration, Workforce commitment and Continuous improvement culture) for assessing the LPD performance.

  9. Use of eHealth technologies to enable the implementation of musculoskeletal Models of Care: Evidence and practice.

    Science.gov (United States)

    Slater, Helen; Dear, Blake F; Merolli, Mark A; Li, Linda C; Briggs, Andrew M

    2016-06-01

    Musculoskeletal (MSK) conditions are the second leading cause of morbidity-related burden of disease globally. EHealth is a potentially critical factor that enables the implementation of accessible, sustainable and more integrated MSK models of care (MoCs). MoCs serve as a vehicle to drive evidence into policy and practice through changes at a health system, clinician and patient level. The use of eHealth to implement MoCs is intuitive, given the capacity to scale technologies to deliver system and economic efficiencies, to contribute to sustainability, to adapt to low-resource settings and to mitigate access and care disparities. We follow a practice-oriented approach to describing the 'what' and 'how' to harness eHealth in the implementation of MSK MoCs. We focus on the practical application of eHealth technologies across care settings to those MSK conditions contributing most substantially to the burden of disease, including osteoarthritis and inflammatory arthritis, skeletal fragility-associated conditions and persistent MSK pain. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. Enabled interferon signaling evasion in an immune-competent transgenic mouse model of parainfluenza virus 5 infection.

    Science.gov (United States)

    Kraus, Thomas A; Garza, Lily; Horvath, Curt M

    2008-02-05

    Parainfluenza virus 5 (PIV5 or SV5) infects several mammalian species but is restricted from efficient replication in mice. In humans, PIV5 evades IFN signaling by targeting STAT1 for proteasomal degradation in a STAT2-dependent reaction. In contrast, cell culture experiments have demonstrated that the divergent murine STAT2 protein fails to support STAT1 targeting. Expression of human STAT2 in mouse cells can overcome the species restriction to enable PIV5-induced STAT1 degradation and subsequent IFN antagonism. Here, we describe a transgenic mouse that ubiquitously expresses human STAT2. PIV5 infection induces STAT1 degradation leading to enhanced virus replication and protein expression in the cells from the transgenic mouse but not from the non-transgenic littermates. Importantly, intranasal inoculation with PIV5 results in increased viral load in the lungs of the transgenic mice compared to wild-type littermates. These transgenic mice provide a small animal model to study the role of innate immune evasion in paramyxovirus pathogenesis.

  11. Interpretive Experiments

    Science.gov (United States)

    DeHaan, Frank, Ed.

    1977-01-01

    Describes an interpretative experiment involving the application of symmetry and temperature-dependent proton and fluorine nmr spectroscopy to the solution of structural and kinetic problems in coordination chemistry. (MLH)

  12. Bayesian parameter estimation and interpretation for an intermediate model of tree-ring width

    Directory of Open Access Journals (Sweden)

    S. E. Tolwinski-Ward

    2013-07-01

    Full Text Available We present a Bayesian model for estimating the parameters of the VS-Lite forward model of tree-ring width for a particular chronology and its local climatology. The scheme also provides information about the uncertainty of the parameter estimates, as well as the model error in representing the observed proxy time series. By inferring VS-Lite's parameters independently for synthetically generated ring-width series at several hundred sites across the United States, we show that the algorithm is skillful. We also infer optimal parameter values for modeling observed ring-width data at the same network of sites. The estimated parameter values covary in physical space, and their locations in multidimensional parameter space provide insight into the dominant climatic controls on modeled tree-ring growth at each site as well as the stability of those controls. The estimation procedure is useful for forward and inverse modeling studies using VS-Lite to quantify the full range of model uncertainty stemming from its parameterization.

  13. Genome-Enabled Modeling of Biogeochemical Processes Predicts Metabolic Dependencies that Connect the Relative Fitness of Microbial Functional Guilds

    Science.gov (United States)

    Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Steefel, C. I.; Banfield, J. F.; Beller, H. R.; Anantharaman, K.; Ligocki, T. J.; Trebotich, D.

    2015-12-01

    Pore-scale processes mediated by microorganisms underlie a range of critical ecosystem services, regulating carbon stability, nutrient flux, and the purification of water. Advances in cultivation-independent approaches now provide us with the ability to reconstruct thousands of genomes from microbial populations from which functional roles may be assigned. With this capability to reveal microbial metabolic potential, the next step is to put these microbes back where they belong to interact with their natural environment, i.e. the pore scale. At this scale, microorganisms communicate, cooperate and compete across their fitness landscapes with communities emerging that feedback on the physical and chemical properties of their environment, ultimately altering the fitness landscape and selecting for new microbial communities with new properties and so on. We have developed a trait-based model of microbial activity that simulates coupled functional guilds that are parameterized with unique combinations of traits that govern fitness under dynamic conditions. Using a reactive transport framework, we simulate the thermodynamics of coupled electron donor-acceptor reactions to predict energy available for cellular maintenance, respiration, biomass development, and enzyme production. From metagenomics, we directly estimate some trait values related to growth and identify the linkage of key traits associated with respiration and fermentation, macromolecule depolymerizing enzymes, and other key functions such as nitrogen fixation. Our simulations were carried out to explore abiotic controls on community emergence such as seasonally fluctuating water table regimes across floodplain organic matter hotspots. Simulations and metagenomic/metatranscriptomic observations highlighted the many dependencies connecting the relative fitness of functional guilds and the importance of chemolithoautotrophic lifestyles. Using an X-Ray microCT-derived soil microaggregate physical model combined

  14. A Phillips curve interpretation of error-correction models of the wage and price dynamics

    DEFF Research Database (Denmark)

    Harck, Søren H.

     This paper presents a model of employment, distribution and inflation in which a modern error correction specification of the nominal wage and price dynamics (referring to claims on income by workers and firms) occupies a prominent role. It is brought out, explicitly, how this rather typical error......-correction setting, which actually seems to capture the wage and price dynamics of many large- scale econometric models quite well, is fully compatible with the notion of an old-fashioned Phillips curve with finite slope. It is shown how the steady-state impact of various shocks to the model can be profitably...

  15. A Phillips curve interpretation of error-correction models of the wage and price dynamics

    DEFF Research Database (Denmark)

    Harck, Søren H.

    2009-01-01

    This paper presents a model of employment, distribution and inflation in which a modern error correction specification of the nominal wage and price dynamics (referring to claims on income by workers and firms) occupies a prominent role. It is brought out, explicitly, how this rather typical error......-correction setting, which actually seems to capture the wage and price dynamics of many large- scale econometric models quite well, is fully compatible with the notion of an old-fashioned Phillips curve with finite slope. It is shown how the steady-state impact of various shocks to the model can be profitably...

  16. Analysing, Interpreting, and Testing the Invariance of the Actor-Partner Interdependence Model

    Directory of Open Access Journals (Sweden)

    Gareau, Alexandre

    2016-09-01

    Full Text Available Although in recent years researchers have begun to utilize dyadic data analyses such as the actor-partner interdependence model (APIM, certain limitations to the applicability of these models still exist. Given the complexity of APIMs, most researchers will often use observed scores to estimate the model's parameters, which can significantly limit and underestimate statistical results. The aim of this article is to highlight the importance of conducting a confirmatory factor analysis (CFA of equivalent constructs between dyad members (i.e. measurement equivalence/invariance; ME/I. Different steps for merging CFA and APIM procedures will be detailed in order to shed light on new and integrative methods.

  17. Managing risks in the fisheries supply chain using House of Risk Framework (HOR) and Interpretive Structural Modeling (ISM)

    Science.gov (United States)

    Nguyen, T. L. T.; Tran, T. T.; Huynh, T. P.; Ho, T. K. D.; Le, A. T.; Do, T. K. H.

    2018-04-01

    One of the sectors which contributes importantly to the development of Vietnam economy is fishery industry. However, during recent year, it has been witnessed many difficulties on managing the performance of the fishery supply chain operations as a whole. In this paper, a framework for supply chain risk management (SCRM) is proposed. Initially, all the activities are mapped by using Supply Chain Operations Reference (SCOR) model. Next, the risk ranking is analyzed in House of Risk. Furthermore, interpretive structural modeling (ISM) is used to identify inter-relationships among supply chain risks and to visualize the risks according to their levels. For illustration, the model has been tested in several case studies with fishery companies in Can Tho, Mekong Delta. This study identifies 22 risk events and 20 risk agents through the supply chain. Also, the risk priority could be used for further House of Risk with proactive actions in future studies.

  18. Mathematical interpretation of Brownian motor model: Limit cycles and directed transport phenomena

    Science.gov (United States)

    Yang, Jianqiang; Ma, Hong; Zhong, Suchuang

    2018-03-01

    In this article, we first suggest that the attractor of Brownian motor model is one of the reasons for the directed transport phenomenon of Brownian particle. We take the classical Smoluchowski-Feynman (SF) ratchet model as an example to investigate the relationship between limit cycles and directed transport phenomenon of the Brownian particle. We study the existence and variation rule of limit cycles of SF ratchet model at changing parameters through mathematical methods. The influences of these parameters on the directed transport phenomenon of a Brownian particle are then analyzed through numerical simulations. Reasonable mathematical explanations for the directed transport phenomenon of Brownian particle in SF ratchet model are also formulated on the basis of the existence and variation rule of the limit cycles and numerical simulations. These mathematical explanations provide a theoretical basis for applying these theories in physics, biology, chemistry, and engineering.

  19. Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation

    Data.gov (United States)

    National Aeronautics and Space Administration — This article discusses several aspects of uncertainty represen- tation and management for model-based prognostics method- ologies based on our experience with Kalman...

  20. The practical use of resistance modelling to interpret the gas separation properties of hollow fiber membranes

    International Nuclear Information System (INIS)

    Ahmad Fauzi Ismail; Shilton, S.J.

    2000-01-01

    A simple resistance modelling methodology is presented for gas transport through asymmetric polymeric membranes. The methodology allows fine structural properties such as active layer thickness and surface porosity, to be determined from experimental gas permeation data. This paper, which could be regarded as a practical guide, shows that resistance modeling, if accompanied by realistic working assumptions, need not be difficult and can provide a valuable insight into the relationships between the membrane fabrication conditions and performance of gas separation membranes. (Author)

  1. Fluid flow model of the Cerro Prieto Geothermal Field based on well log interpretation

    Energy Technology Data Exchange (ETDEWEB)

    Halfman, S.E.; Lippmann, M.J.; Zelwe, R.; Howard, J.H.

    1982-08-10

    The subsurface geology of the Cerro Prieto geothermal field was analyzed using geophysical and lithologic logs. The distribution of permeable and relatively impermeable units and the location of faults are shown in a geologic model of the system. By incorporating well completion data and downhole temperature profiles into the geologic model, it was possible to determine the direction of geothermal fluid flow and the role of subsurface geologic features that control this movement.

  2. A criticism of big bang cosmological models based on interpretation of the red shift

    Energy Technology Data Exchange (ETDEWEB)

    Kierein, J.W. (Ball Aerospace Systems Div., Boulder, CO (USA))

    1988-08-01

    The interaction of light with the intergalactic plasma produces the Hubble red shift versus distance relationship. This interaction also produces an isotopic long wavelength background radiation from the plasma. Intrinsic red shifts in quasars and other objects are similarly explained, showing why they are exceptions to Hubble's law. Because the red shift is not doppler-shifted, big bang cosmological models should be replaced with static models. (author).

  3. The Role of Electrical Anisotropy in Modeling and Interpreting Controlled-Source Electromagnetic Responses for Hydraulic Fracture Monitoring

    Science.gov (United States)

    Trevino, S., III; Hickey, M. S.; Everett, M. E.

    2017-12-01

    Controlled-Source Electromagnetics (CSEM) can be used to monitor the movement and extent of injection fluid during a hydraulic fracture. The response of the fluid to energization by a CSEM source is dependent upon the electrical conductivity difference between the fluid and background geological formation. An important property that must be taken into account when modeling and interpreting CSEM responses is that electrical conductivity may be anisotropic. We study the effect of electrical anisotropy in both the background formation and the fluid-injection zone. First, various properties of the background formation can affect anisotropy including variations in grain size, composition and bedding-plane orientation. In certain formations, such as shale, the horizontal component of the conductivity can be more than an order of magnitude larger than the vertical component. We study this effect by computing differences in surface CSEM responses using the analytic 1-D anisotropic primary solution of a horizontal electric dipole positioned at the surface. Second, during hydraulic fracturing, the injected fluid can create new fractures and infill existing natural fractures. To include the explicit fracture geometry in modeling, a large increase in the number of nodes and computational time is required which may not be feasible. An alternative is to instead model the large-scale fracture geometry as a uniform slab with an appropriate bulk conductivity. Micro-scale fracture geometry may cause preferential fluid propagation in a single direction or plane which can be represented by electrical anisotropy of the slab. To study such effects of bulk anisotropy on CSEM responses we present results from multiple scenarios of surface to surface hydraulic fracture monitoring using 3-D finite element modeling. The model uses Coulomb-gauged potentials to solve Maxwell's equations in the frequency domain and we have updated the code to allow a triaxial electrical conductivity tensor to

  4. The Connecting South West Ontario (cSWO) Benefits Model: An Approach for the Collaborative Capture of Value of Electronic Health Records and Enabling Technology.

    Science.gov (United States)

    Alexander, Ted; Huebner, Lori-Anne; Alarakhia, Mohamed; Hollohan, Kirk

    2017-01-01

    This paper explains the benefits model developed and deployed by the connecting South West Ontario (cSWO) program. The cSWO approach is founded on the principles of enabling clinical and organizational value and the recognition that enabling requires a collaborative approach that can include several perspectives. We describe our approach which is aimed at creating a four-part harmony between change management and adoption, best practice research and quality indicators, data analytics and clinical value production.

  5. Interpreting the cosmic far-infrared background anisotropies using a gas regulator model

    Science.gov (United States)

    Wu, Hao-Yi; Doré, Olivier; Teyssier, Romain; Serra, Paolo

    2018-04-01

    Cosmic far-infrared background (CFIRB) is a powerful probe of the history of star formation rate (SFR) and the connection between baryons and dark matter across cosmic time. In this work, we explore to which extent the CFIRB anisotropies can be reproduced by a simple physical framework for galaxy evolution, the gas regulator (bathtub) model. This model is based on continuity equations for gas, stars, and metals, taking into account cosmic gas accretion, star formation, and gas ejection. We model the large-scale galaxy bias and small-scale shot noise self-consistently, and we constrain our model using the CFIRB power spectra measured by Planck. Because of the simplicity of the physical model, the goodness of fit is limited. We compare our model predictions with the observed correlation between CFIRB and gravitational lensing, bolometric infrared luminosity functions, and submillimetre source counts. The strong clustering of CFIRB indicates a large galaxy bias, which corresponds to haloes of mass 1012.5 M⊙ at z = 2, higher than the mass associated with the peak of the star formation efficiency. We also find that the far-infrared luminosities of haloes above 1012 M⊙ are higher than the expectation from the SFR observed in ultraviolet and optical surveys.

  6. Simple Elastic Dislocation Models for Interpreting Interseismic Deformation in Subduction Zones

    Science.gov (United States)

    Kanda, R. V.; Simons, M.

    2006-12-01

    Models of interseismic surface deformation in the vicinity of subduction zones frequently rely on the back slip model (BSM). This model employs artificial extensional slip along the locked zone in order to explain the observed sense of interseismic displacements. Here, we introduce the elastic subducting plate model (ESPM) which is more representative of plate subduction. This model has only one additional degree of freedom over the standard BSM the thickness of the subducting elastic plate. In our present formulation, the base of the elastic plate is forced to move continuously at the long term convergence rate, as is the top surface of the subducting plate below the locking depth. The ESPM reduces exactly to the BSM in the limiting case of zero plate thickness - thereby providing a more intuitive rationale for the success of the BSM since details associated with finite plate thickness are hard to resolve with data distant from the trench. If the effective thickness of a subducting plate is large compared to the depth of its locked zone, or when the curvature of the subduction interface is sufficiently high, it may be more appropriate to adopt the ESPM. Practically, our ability to distinguish between the BSM and the ESPM depends on simultaneously modeling vertical and horizontal displacement fields, and on having data from close to the trench. We use geodetic measurements from Japan and Sumatra to compare the observed surface deformation with that predicted by both ESPM & BSM, and invert for the allowable ranges of effective plate thickness.

  7. Predictive modelling of the dielectric response of plasmonic substrates: application to the interpretation of ellipsometric spectra

    Science.gov (United States)

    Pugliara, A.; Bayle, M.; Bonafos, C.; Carles, R.; Respaud, M.; Makasheva, K.

    2018-03-01

    A predictive modelling of plasmonic substrates appropriate to read ellipsometric spectra is presented in this work. We focus on plasmonic substrates containing a single layer of silver nanoparticles (AgNPs) embedded in silica matrices. The model uses the Abeles matrix formalism and is based on the quasistatic approximation of the classical Maxwell-Garnett mixing rule, however accounting for the electronic confinement effect through the damping parameter. It is applied on samples elaborated by: (i) RF-diode sputtering followed by Plasma Enhanced Chemical Vapor Deposition (PECVD) and (ii) Low Energy Ion Beam Synthesis (LE-IBS), and represents situations with increasing degree of complexity that can be accounted for by the model. It allows extraction of the main characteristics of the AgNPs population: average size, volume fraction and distance of the AgNPs layer from the matrix free surface. Model validation is achieved through comparison with results obtained from transmission electron microscopy approving for its applicability. The advantages and limitations of the proposed model are discussed after eccentricity-based statistical analysis along with further developments related to the quality of comparison between the model-generated spectra and the experimentally-recorded ellipsometric spectra.

  8. Exploring the uncertainties of early detection results: model-based interpretation of mayo lung project

    Directory of Open Access Journals (Sweden)

    Berman Barbara

    2011-03-01

    Full Text Available Abstract Background The Mayo Lung Project (MLP, a randomized controlled clinical trial of lung cancer screening conducted between 1971 and 1986 among male smokers aged 45 or above, demonstrated an increase in lung cancer survival since the time of diagnosis, but no reduction in lung cancer mortality. Whether this result necessarily indicates a lack of mortality benefit for screening remains controversial. A number of hypotheses have been proposed to explain the observed outcome, including over-diagnosis, screening sensitivity, and population heterogeneity (initial difference in lung cancer risks between the two trial arms. This study is intended to provide model-based testing for some of these important arguments. Method Using a micro-simulation model, the MISCAN-lung model, we explore the possible influence of screening sensitivity, systematic error, over-diagnosis and population heterogeneity. Results Calibrating screening sensitivity, systematic error, or over-diagnosis does not noticeably improve the fit of the model, whereas calibrating population heterogeneity helps the model predict lung cancer incidence better. Conclusions Our conclusion is that the hypothesized imperfection in screening sensitivity, systematic error, and over-diagnosis do not in themselves explain the observed trial results. Model fit improvement achieved by accounting for population heterogeneity suggests a higher risk of cancer incidence in the intervention group as compared with the control group.

  9. Teaching Real Data Interpretation with Models (TRIM): Analysis of Student Dialogue in a Large-Enrollment Cell and Developmental Biology Course

    Science.gov (United States)

    Zagallo, Patricia; Meddleton, Shanice; Bolger, Molly S.

    2016-01-01

    We present our design for a cell biology course to integrate content with scientific practices, specifically data interpretation and model-based reasoning. A 2-year research project within this course allowed us to understand how students interpret authentic biological data in this setting. Through analysis of written work, we measured the extent…

  10. Ignoring imperfect detection in biological surveys is dangerous: a response to 'fitting and interpreting occupancy models'.

    Directory of Open Access Journals (Sweden)

    Gurutzeta Guillera-Arroita

    Full Text Available In a recent paper, Welsh, Lindenmayer and Donnelly (WLD question the usefulness of models that estimate species occupancy while accounting for detectability. WLD claim that these models are difficult to fit and argue that disregarding detectability can be better than trying to adjust for it. We think that this conclusion and subsequent recommendations are not well founded and may negatively impact the quality of statistical inference in ecology and related management decisions. Here we respond to WLD's claims, evaluating in detail their arguments, using simulations and/or theory to support our points. In particular, WLD argue that both disregarding and accounting for imperfect detection lead to the same estimator performance regardless of sample size when detectability is a function of abundance. We show that this, the key result of their paper, only holds for cases of extreme heterogeneity like the single scenario they considered. Our results illustrate the dangers of disregarding imperfect detection. When ignored, occupancy and detection are confounded: the same naïve occupancy estimates can be obtained for very different true levels of occupancy so the size of the bias is unknowable. Hierarchical occupancy models separate occupancy and detection, and imprecise estimates simply indicate that more data are required for robust inference about the system in question. As for any statistical method, when underlying assumptions of simple hierarchical models are violated, their reliability is reduced. Resorting in those instances where hierarchical occupancy models do no perform well to the naïve occupancy estimator does not provide a satisfactory solution. The aim should instead be to achieve better estimation, by minimizing the effect of these issues during design, data collection and analysis, ensuring that the right amount of data is collected and model assumptions are met, considering model extensions where appropriate.

  11. Formal models in animal-metacognition research: the problem of interpreting animals' behavior.

    Science.gov (United States)

    Smith, J David; Zakrzewski, Alexandria C; Church, Barbara A

    2016-10-01

    Ongoing research explores whether animals have precursors to metacognition-that is, the capacity to monitor mental states or cognitive processes. Comparative psychologists have tested apes, monkeys, rats, pigeons, and a dolphin using perceptual, memory, foraging, and information-seeking paradigms. The consensus is that some species have a functional analog to human metacognition. Recently, though, associative modelers have used formal-mathematical models hoping to describe animals' "metacognitive" performances in associative-behaviorist ways. We evaluate these attempts to reify formal models as proof of particular explanations of animal cognition. These attempts misunderstand the content and proper application of models. They embody mistakes of scientific reasoning. They blur fundamental distinctions in understanding animal cognition. They impede theoretical development. In contrast, an energetic empirical enterprise is achieving strong success in describing the psychology underlying animals' metacognitive performances. We argue that this careful empirical work is the clear path to useful theoretical development. The issues raised here about formal modeling-in the domain of animal metacognition-potentially extend to biobehavioral research more broadly.

  12. Interpretation of Snow-Climate Feedback as Produced by 17 General Circulation Models

    Science.gov (United States)

    Cess, R. D.; Potter, G. L.; Zhang, M.-H.; Blanchet, J.-P.; Chalita, S.; Colman, R.; Dazlich, D. A.; del Genio, A. D.; Dymnikov, V.; Galin, V.; Jerrett, D.; Keup, E.; Lacis, A. A.; Le Treut, H.; Liang, X.-Z.; Mahfouf, J.-F.; McAvaney, B. J.; Meleshko, V. P.; Mitchell, J. F. B.; Morcrette, J.-J.; Norris, P. M.; Randall, D. A.; Rikus, L.; Roeckner, E.; Royer, J.-F.; Schlese, U.; Sheinin, D. A.; Slingo, J. M.; Sokolov, A. P.; Taylor, K. E.; Washington, W. M.; Wetherald, R. T.; Yagai, I.

    1991-08-01

    Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer Earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

  13. Developing interpretable models with optimized set reduction for identifying high risk software components

    Science.gov (United States)

    Briand, Lionel C.; Basili, Victor R.; Hetmanski, Christopher J.

    1993-01-01

    Applying equal testing and verification effort to all parts of a software system is not very efficient, especially when resources are limited and scheduling is tight. Therefore, one needs to be able to differentiate low/high fault frequency components so that testing/verification effort can be concentrated where needed. Such a strategy is expected to detect more faults and thus improve the resulting reliability of the overall system. This paper presents the Optimized Set Reduction approach for constructing such models, intended to fulfill specific software engineering needs. Our approach to classification is to measure the software system and build multivariate stochastic models for predicting high risk system components. We present experimental results obtained by classifying Ada components into two classes: is or is not likely to generate faults during system and acceptance test. Also, we evaluate the accuracy of the model and the insights it provides into the error making process.

  14. Modelling as a tool when interpreting biodegradation of micro pollutants in activated sludge systems

    DEFF Research Database (Denmark)

    Press-Kristensen, Kåre; Lindblom, Erik Ulfson; Henze, Mogens

    2007-01-01

    The aims of the present work were to improve the biodegradation of the endocrine disrupting micro pollutant, bisphenol A (BPA), used as model compound in an activated sludge system and to underline the importance of modelling the system. Previous results have shown that BPA mainly is degraded under...... aerobic conditions. Therefore the aerobic phase time in the BioDenitro process of the activated sludge system was increased from 50% to 70%. The hypothesis was that this would improve the biodegradation of BPA. Both the influent and the effluent concentrations of BPA in the experiment dropped...... significantly after increasing the aerobic time. From simulations with a growth-based biological/physical/chemical process model it was concluded that although the simulated effluent concentration of BPA was independent of the influent concentration at steady-state, the observed drop in effluent concentrations...

  15. A numerical analysis model for the interpretation of in vivo platelet consumption data.

    Directory of Open Access Journals (Sweden)

    Ted S Strom

    Full Text Available Unlike anemias, most thrombocytopenias cannot be separated into those due to impaired production and those due to accelerated consumption. While rapid clearance of labeled platelets from the bloodstream can be followed in thrombocytopenic individuals, no model exists for quantitatively inferring from autologous or allogeneic platelet consumption data what changes in random consumption, lifespan dependent consumption, and platelet production rate may have caused the thrombocytopenia. Here we describe a numerical analysis model which resolves these issues. The model applies three parameter values (a random consumption rate constant, a lognormally-distributed platelet lifespan, and the standard deviation of the latter to a matrix comprising a series of platelet cohorts which are sequentially produced and fractionally consumed in a series of time intervals. The cohort platelet counts achieved after equilibration of production and consumption both enumerate the population age distribution and sum to the population platelet count. Continued platelet consumption after production is halted then serves to model in vivo platelet consumption data, with consumption rate in the first such interval defining the equilibrium platelet production rate. We use a least squares fitting procedure to find parameter values which best fit observed platelet consumption data obtained in WT and thrombocytopenic WASP(- mice. Equilibrium platelet age distributions are then 'grafted' into the matrix to allow modeling of the consumption of WT platelets in WASP(- recipients, and vice versa. The optimal parameter values obtained indicate that random WT platelet consumption accounts for a larger fraction of platelet turnover than was previously suspected. Platelet WASP deficiency accelerates random consumption, and a trans effect of recipient WASP deficiency contributes to this. Application of the model to clinical data will allow distinctions to be made between thrombocytopenias

  16. A novel humanized GLP-1 receptor model enables both affinity purification and Cre-LoxP deletion of the receptor.

    Directory of Open Access Journals (Sweden)

    Lucy S Jun

    Full Text Available Class B G protein-coupled receptors (GPCRs are important regulators of endocrine physiology, and peptide-based therapeutics targeting some of these receptors have proven effective at treating disorders such as hypercalcemia, osteoporosis, and type 2 diabetes mellitus (T2DM. As next generation efforts attempt to develop novel non-peptide, orally available molecules for these GPCRs, new animal models expressing human receptor orthologs may be required because small molecule ligands make fewer receptor contacts, and thus, the impact of amino acid differences across species may be substantially greater. The objective of this report was to generate and characterize a new mouse model of the human glucagon-like peptide-1 receptor (hGLP-1R, a class B GPCR for which established peptide therapeutics exist for the treatment of T2DM. hGLP-1R knock-in mice express the receptor from the murine Glp-1r locus. Glucose tolerance tests and gastric emptying studies show hGLP-1R mice and their wild-type littermates display similar physiological responses for glucose metabolism, insulin secretion, and gastric transit, and treatment with the GLP-1R agonist, exendin-4, elicits similar responses in both groups. Further, ex vivo assays show insulin secretion from humanized islets is glucose-dependent and enhanced by GLP-1R agonists. To enable additional utility, the targeting construct of the knock-in line was engineered to contain both flanking LoxP sites and a C-terminal FLAG epitope. Anti-FLAG affinity purification shows strong expression of hGLP-1R in islets, lung, and stomach. We crossed the hGLP-1R line with Rosa26Cre mice and generated global Glp-1r-/- animals. Immunohistochemistry of pancreas from humanized and knock-out mice identified a human GLP-1R-specific antibody that detects the GLP-1R in human pancreas as well as in the pancreas of hGLP-1r knock-in mice. This new hGLP-1R model will allow tissue-specific deletion of the GLP-1R, purification of potential

  17. A Model Based Framework for Semantic Interpretation of Architectural Construction Drawings

    Science.gov (United States)

    Babalola, Olubi Oluyomi

    2011-01-01

    The study addresses the automated translation of architectural drawings from 2D Computer Aided Drafting (CAD) data into a Building Information Model (BIM), with emphasis on the nature, possible role, and limitations of a drafting language Knowledge Representation (KR) on the problem and process. The central idea is that CAD to BIM translation is a…

  18. Household Labour Supply in Britain and Denmark: Some Interpretations Using a Model of Pareto Optimal Behaviour

    DEFF Research Database (Denmark)

    Barmby, Tim; Smith, Nina

    1996-01-01

    This paper analyses the labour supply behaviour of households in Denmark and Britain. It employs models in which the preferences of individuals within the household are explicitly represented. The households are then assumed to decide on their labour supply in a Pareto-Optimal fashion. Describing...

  19. Energetic protons at Mars: interpretation of SLED/Phobos-2 observations by a kinetic model

    Directory of Open Access Journals (Sweden)

    E. Kallio

    2012-11-01

    Full Text Available Mars has neither a significant global intrinsic magnetic field nor a dense atmosphere. Therefore, solar energetic particles (SEPs from the Sun can penetrate close to the planet (under some circumstances reaching the surface. On 13 March 1989 the SLED instrument aboard the Phobos-2 spacecraft recorded the presence of SEPs near Mars while traversing a circular orbit (at 2.8 RM. In the present study the response of the Martian plasma environment to SEP impingement on 13 March was simulated using a kinetic model. The electric and magnetic fields were derived using a 3-D self-consistent hybrid model (HYB-Mars where ions are modelled as particles while electrons form a massless charge neutralizing fluid. The case study shows that the model successfully reproduced several of the observed features of the in situ observations: (1 a flux enhancement near the inbound bow shock, (2 the formation of a magnetic shadow where the energetic particle flux was decreased relative to its solar wind values, (3 the energy dependency of the flux enhancement near the bow shock and (4 how the size of the magnetic shadow depends on the incident particle energy. Overall, it is demonstrated that the Martian magnetic field environment resulting from the Mars–solar wind interaction significantly modulated the Martian energetic particle environment.

  20. Interpretation and modeling of a subsurface injection test, 200 East Area, Hanford, Washington

    International Nuclear Information System (INIS)

    Smoot, J.L.; Lu, A.H.

    1994-11-01

    A tracer experiment was conducted in 1980 and 1981 in the unsaturated zone in the southeast portion of the Hanford 200 East Area near the Plutonium-Uranium Extraction (PUREX) facility. The field design consisted of a central injection well with 32 monitoring wells within an 8-m radius. Water containing radioactive and other tracers was injected weekly during the experiment. The unique features of the experiment were the documented control of the inputs, the experiment's three-dimensional nature, the in-situ measurement of radioactive tracers, and the use of multiple injections. The spacing of the test wells provided reasonable lag distribution for spatial correlation analysis. Preliminary analyses indicated spatial correlation on the order of 400 to 500 cm in the vertical direction. Previous researchers found that two-dimensional axisymmetric modeling of moisture content generally underpredicts lateral spreading and overpredicts vertical movement of the injected water. Incorporation of anisotropic hydraulic properties resulted in the best model predictions. Three-dimensional modeling incorporated the geologic heterogeneity of discontinuous layers and lenses of sediment apparent in the site geology. Model results were compared statistically with measured experimental data and indicate reasonably good agreement with vertical and lateral field moisture distributions

  1. A spatial interpretation of the density dependence model in industrial demography

    NARCIS (Netherlands)

    van Wissen, L

    2004-01-01

    In this paper the density dependence model, which was developed in organizational ecology, is compared to the economic-geographical notion of agglomeration economies. There is a basic resemblance: both involve some form of positive feedback between size of the population and growth. The paper

  2. Formal models in animal-metacognition research: the problem of interpreting animals’ behavior

    Science.gov (United States)

    Smith, J. David; Zakrzewski, Alexandria C.; Church, Barbara A.

    2015-01-01

    Ongoing research explores whether animals have precursors to metacognition—that is, the capacity to monitor mental states or cognitive processes. Comparative psychologists have tested apes, monkeys, rats, pigeons, and a dolphin using perceptual, memory, foraging, and information-seeking paradigms. The consensus is that some species have a functional analog to human metacognition. Recently, though, associative modelers have used formal-mathematical models hoping to describe animals’ “metacognitive” performances in associative-behaviorist ways. We evaluate these attempts to reify formal models as proof of particular explanations of animal cognition. These attempts misunderstand the content and proper application of models. They embody mistakes of scientific reasoning. They blur fundamental distinctions in understanding animal cognition. They impede theoretical development. In contrast, an energetic empirical enterprise is achieving strong success in describing the psychology underlying animals’ metacognitive performances. We argue that this careful empirical work is the clear path to useful theoretical development. The issues raised here about formal modeling—in the domain of animal metacognition—potentially extend to biobehavioral research more broadly. PMID:26669600

  3. Energetic protons at Mars. Interpretation of SLED/Phobos-2 observations by a kinetic model

    Energy Technology Data Exchange (ETDEWEB)

    Kallio, E.; Alho, M.; Jarvinen, R.; Dyadechkin, S. [Finnish Meteorological Institute, Helsinki (Finland); McKenna-Lawlor, S. [Space Technology Ireland, Maynooth, Co. Kildare (Ireland); Afonin, V.V. [Space Research Institute, Moscow (Russian Federation)

    2012-07-01

    Mars has neither a significant global intrinsic magnetic field nor a dense atmosphere. Therefore, solar energetic particles (SEPs) from the Sun can penetrate close to the planet (under some circumstances reaching the surface). On 13 March 1989 the SLED instrument aboard the Phobos- 2 spacecraft recorded the presence of SEPs near Mars while traversing a circular orbit (at 2.8RM). In the present study the response of the Martian plasma environment to SEP impingement on 13 March was simulated using a kinetic model. The electric and magnetic fields were derived using a 3- D self-consistent hybrid model (HYB-Mars) where ions are modelled as particles while electrons form a massless charge neutralizing fluid. The case study shows that the model successfully reproduced several of the observed features of the in situ observations: (1) a flux enhancement near the inbound bow shock, (2) the formation of a magnetic shadow where the energetic particle flux was decreased relative to its solar wind values, (3) the energy dependency of the flux enhancement near the bow shock and (4) how the size of the magnetic shadow depends on the incident particle energy. Overall, it is demonstrated that the Martian magnetic field environment resulting from the Mars-solar wind interaction significantly modulated the Martian energetic particle environment. (orig.)

  4. Interpretation and extrapolation of ecological responses in model ecosystems stressed with non-persistent insecticides

    NARCIS (Netherlands)

    Wijngaarden, van R.P.A.

    2006-01-01

    This thesis aims to contribute to the discussion concerning whether micro- and mesocosm studies can serve as adequate models for robust risk assessment of pesticides. For this purpose, results from freshwater micro- and mesocosm experiments conducted under different experimental conditions are

  5. On the geometrical interpretation of scale-invariant models of inflation

    Directory of Open Access Journals (Sweden)

    Georgios K. Karananas

    2016-10-01

    Full Text Available We study the geometrical properties of scale-invariant two-field models of inflation. In particular, we show that when the field-derivative space in the Einstein frame is maximally symmetric during inflation, the inflationary predictions can be universal and independent of the details of the theory.

  6. Study of nickel nuclei by (p,d) and (p,t) reactions. Shell model interpretation

    International Nuclear Information System (INIS)

    Kong-A-Siou, D.-H.

    1975-01-01

    The experimental techniques employed at the Nuclear Science Institute (Grenoble) and at Michigan State University are described. The development of the transition amplitude calculation of the one-or two-nucleon transfer reactions is described first, after which the principle of shell model calculations is outlined. The choices of configuration space and two-body interactions are discussed. The DWBA method of analysis is studied in more detail. The effects of different approximations and the influence of the parameters are examined. Special attention is paid to the j-dependence of the form of the angular distributions, on effect not explained in the standard DWBA framework. The results are analysed and a large section is devoted to a comparative study of the experimental results obtained and those from other nuclear reactions. The spectroscopic data obtained are compared with the results of shell model calculations [fr

  7. Capacitor model to interpret the electric behavior of fluidized beds. Influence of apparatus geometry

    Energy Technology Data Exchange (ETDEWEB)

    Rojo, V.; Guardiola, J.; Vian, A.

    1986-01-01

    This work provides a model to know the degree of electrification in fluidized beds on the basis of voltage measurements between an electric probe and a metallic distributor. The model is based on the similarity of behavior between the probe-bed-distributor system and a capacitor. The influence of three variables related to apparatus geometry - height of probe, column diameter and height of bed - has been studied in an air fluidized bed of glass beads. The results show that the degree of bed electrification is not influenced by the column diameter; the effect of bed height depends on the quality of fluidization: with a bubbling bed the degree of electrification increases with bed height whereas the opposite effect is observed with a slugging bed. Additional fixed bed experiments make clear that the rate of charge dissipation grows for increasing values of bed height and column diameter, and for decreasing values of probe height.

  8. Interactions of Cosmic Rays around the Universe. Models for UHECR data interpretation

    Directory of Open Access Journals (Sweden)

    Boncioli Denise

    2017-01-01

    Full Text Available Ultra high energy cosmic rays (UHECRs are expected to be accelerated inastrophysical sources and to travel through extragalactic space before hitting the Earth atmosphere. They interact both with the environment in the source and with the intergalactic photon fields they encounter, causing different processes at various scales depending on the photon energy in the nucleus rest frame. UHECR interactions are sensitive to uncertainties in the extragalactic background spectrum and in the photo-disintegration models.

  9. Deficit of the "primacy effect" in parkinsonians interpreted by means of the working memory model.

    Science.gov (United States)

    Della Sala, S; Pasetti, C; Sempio, P

    1987-01-01

    29 Parkinsonians and 29 controls matched for age and schooling were tested for memory by means of a free recall test (serial position curve) and two spans (verbal and non-verbal). The free recall test yields three measures: primacy (item 1); secondary memory (items 2-7) and recency (items 8-12). The Parkinsonians displayed a selective deficit of primacy, which is taken to be evidence of defective functioning of the Central Executive in the Working Memory model.

  10. Army Sustainability Modelling Analysis and Reporting Tool Phase 1: User Manual and Results Interpretation Guide

    Science.gov (United States)

    2009-11-01

    Force Sustainability Modelling Tool Prototype GB Gigabyte GRES General Reserve HQ Headquarters HTA Hardening the Army JOLTS Joint Operational...Hardening the Army ( HTA ) proposed force structure.1 Following this work, the Director General Preparedness and Plans – Army (DGPP-A) approached DSTO to...that the different elements of the results for the corps have been identified, we can turn our attention to what the results say about the

  11. Paramagnetic Meissner effect of high-temperature granular superconductors: Interpretation by anisotropic and isotropic models

    International Nuclear Information System (INIS)

    Chen, F.H.; Horng, W.C.; Hsu, H.T.; Tseng, T.Y.

    1995-01-01

    The field-cooled magnetization of high-T c superconducting ceramics measured in low magnetic field exhibits the paramagnetic Meissner effect (PME), i.e., the diamagnetic signal initially increases with decrease in temperature but reaches a maximum at temperature T d and later decreases with decrease in temperature. Even in some samples the signal is ultimately able to transform inversely into a paramagnetic regime once the sample is cooled below a temperature T p as long as the applied field is sufficiently small. This PME has been observed in various high-T c cuprates and is explained by disparate aspects. An anisotropic model, in which the granular superconductors are assumed to be ideally anisotropic, was first alternatively proposed in the present work so as to theoretically account for this effect. On the other hand, an isotropic model, suitable for granular superconductors with randomly oriented grains, was proposed to deal with the samples prepared by a conventional solid-state reaction method. The anomalous magnetization behavior in the present model was demonstrated to be the superposition of the diamagnetic signal, which occurs as a result of the intragranular shielding currents, over the paramagnetic one due to the induction of the intergranular component induced by these currents where the intergranular one behaved as the effective pinning centers. The PME was demonstrated by this model to exist parasitically in granular superconductors. This intergranular effect is therefore worthy of remark when evaluating the volume fraction of superconductivity for the samples from the Meissner signal, in particular, at a low magnetic field

  12. Interpretation of correlated neural variability from models of feed-forward and recurrent circuits

    Science.gov (United States)

    2018-01-01

    Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures—recurrent connections, shared feed-forward projections, and shared gain fluctuations—on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing. PMID:29408930

  13. Rock Physics Modeling and Seismic Interpretation to Estimate Shally Cemented Zone in Carbonate Reservoir Rock

    Directory of Open Access Journals (Sweden)

    Handoyo Handoyo

    2016-12-01

    Full Text Available Carbonate rock are important hydrocarbon reservoir rocks with complex texture and petrophysical properties (porosity and permeability. These complexities make the prediction reservoir characteristics (e.g. porosity and permeability from their seismic properties more difficult. The goal of this paper are to understanding the relationship of physical properties and to see the signature carbonate initial rock and shally-carbonate rock from the reservoir. To understand the relationship between the seismic, petrophysical and geological properties, we used rock physics modeling from ultrasonic P- and S- wave velocity that measured from log data. The measurements obtained from carbonate reservoir field (gas production. X-ray diffraction and scanning electron microscope studies shown the reservoir rock are contain wackestone-packstone content. Effective medium theory to rock physics modeling are using Voigt, Reuss, and Hill.  It is shown the elastic moduly proposionally decrease with increasing porosity. Elastic properties and wave velocity are decreasing proporsionally with increasing porosity and shally cemented on the carbonate rock give higher elastic properties than initial carbonate non-cemented. Rock physics modeling can separated zones which rich of shale and less of shale.

  14. Modelling and interpreting the isotopic composition of water vapour in convective updrafts

    Directory of Open Access Journals (Sweden)

    M. Bolot

    2013-08-01

    Full Text Available The isotopic compositions of water vapour and its condensates have long been used as tracers of the global hydrological cycle, but may also be useful for understanding processes within individual convective clouds. We review here the representation of processes that alter water isotopic compositions during processing of air in convective updrafts and present a unified model for water vapour isotopic evolution within undiluted deep convective cores, with a special focus on the out-of-equilibrium conditions of mixed-phase zones where metastable liquid water and ice coexist. We use our model to show that a combination of water isotopologue measurements can constrain critical convective parameters, including degree of supersaturation, supercooled water content and glaciation temperature. Important isotopic processes in updrafts include kinetic effects that are a consequence of diffusive growth or decay of cloud particles within a supersaturated or subsaturated environment; isotopic re-equilibration between vapour and supercooled droplets, which buffers isotopic distillation; and differing mechanisms of glaciation (droplet freezing vs. the Wegener–Bergeron–Findeisen process. As all of these processes are related to updraft strength, particle size distribution and the retention of supercooled water, isotopic measurements can serve as a probe of in-cloud conditions of importance to convective processes. We study the sensitivity of the profile of water vapour isotopic composition to differing model assumptions and show how measurements of isotopic composition at cloud base and cloud top alone may be sufficient to retrieve key cloud parameters.

  15. Interpreting Physics

    CERN Document Server

    MacKinnon, Edward

    2012-01-01

    This book is the first to offer a systematic account of the role of language in the development and interpretation of physics. An historical-conceptual analysis of the co-evolution of mathematical and physical concepts leads to the classical/quatum interface. Bohrian orthodoxy stresses the indispensability of classical concepts and the functional role of mathematics. This book analyses ways of extending, and then going beyond this orthodoxy orthodoxy. Finally, the book analyzes how a revised interpretation of physics impacts on basic philosophical issues: conceptual revolutions, realism, and r

  16. Validation of the containment code Sirius: interpretation of an explosion experiment on a scale model

    International Nuclear Information System (INIS)

    Blanchet, Y.; Obry, P.; Louvet, J.; Deshayes, M.; Phalip, C.

    1979-01-01

    The explicit 2-D axisymmetric Langrangian code SIRIUS, developed at the CEA/DRNR, Cadarache, deals with transient compressive flows in deformable primary tanks with more or less complex internal component geometries. This code has been subjected to a two-year intensive validation program on scale model experiments and a number of improvements have been incorporated. This paper presents a recent calculation of one of these experiments using the SIRIUS code, and the comparison with experimental results shows the encouraging possibilities of this Lagrangian code

  17. Zigzagging causility model of EPR correlations and on the interpretation of quantum mechanics

    International Nuclear Information System (INIS)

    de Beauregard, O.C.

    1988-01-01

    Being formalized inside the S-matrix scheme, the zigzagging causility model of EPR correlations has full Lorentz and CPT invariance. EPR correlations, proper or reversed, and Wheeler's smoky dragon metaphor are respectively pictured in a spacetime or in the momentum-energy space, as V-shaped, anti LAMBDA-shaped, or C-shaped ABC zigzags, with a summation at B over virtual states absolute value B> = *. The reversibility = * implies that causality is CPT-invariant, or arrowless, at the microlevel. Arrowed causality is a macroscopic emergence, corollary to wave retardation and probability increase. Factlike irreversibility states repression, not suppression, of blind statistical retrodiction- that is, of final cause

  18. A SEMI-ANALYTICAL LINE TRANSFER MODEL TO INTERPRET THE SPECTRA OF GALAXY OUTFLOWS

    International Nuclear Information System (INIS)

    Scarlata, C.; Panagia, N.

    2015-01-01

    We present a semi-analytical line transfer model, (SALT), to study the absorption and re-emission line profiles from expanding galactic envelopes. The envelopes are described as a superposition of shells with density and velocity varying with the distance from the center. We adopt the Sobolev approximation to describe the interaction between the photons escaping from each shell and the remainder of the envelope. We include the effect of multiple scatterings within each shell, properly accounting for the atomic structure of the scattering ions. We also account for the effect of a finite circular aperture on actual observations. For equal geometries and density distributions, our models reproduce the main features of the profiles generated with more complicated transfer codes. Also, our SALT line profiles nicely reproduce the typical asymmetric resonant absorption line profiles observed in starforming/starburst galaxies whereas these absorption profiles cannot be reproduced with thin shells moving at a fixed outflow velocity. We show that scattered resonant emission fills in the resonant absorption profiles, with a strength that is different for each transition. Observationally, the effect of resonant filling depends on both the outflow geometry and the size of the outflow relative to the spectroscopic aperture. Neglecting these effects will lead to incorrect values of gas covering fraction and column density. When a fluorescent channel is available, the resonant profiles alone cannot be used to infer the presence of scattered re-emission. Conversely, the presence of emission lines of fluorescent transitions reveals that emission filling cannot be neglected

  19. Hysteresis model and statistical interpretation of energy losses in non-oriented steels

    Energy Technology Data Exchange (ETDEWEB)

    Mănescu, Veronica, E-mail: veronica.paltanea@upb.ro; Păltânea, Gheorghe; Gavrilă, Horia

    2016-04-01

    In this paper the hysteresis energy losses in two non-oriented industrial steels (M400-65A and M800-65A) were determined, by means of an efficient classical Preisach model, which is based on the Pescetti–Biorci method for the identification of the Preisach density. The excess and the total energy losses were also determined, using a statistical framework, based on magnetic object theory. The hysteresis energy losses, in a non-oriented steel alloy, depend on the peak magnetic polarization and they can be computed using a Preisach model, due to the fact that in these materials there is a direct link between the elementary rectangular loops and the discontinuous character of the magnetization process (Barkhausen jumps). To determine the Preisach density it was necessary to measure the normal magnetization curve and the saturation hysteresis cycle. A system of equations was deduced and the Preisach density was calculated for a magnetic polarization of 1.5 T; then the hysteresis cycle was reconstructed. Using the same pattern for the Preisach distribution, it was computed the hysteresis cycle for 1 T. The classical losses were calculated using a well known formula and the excess energy losses were determined by means of the magnetic object theory. The total energy losses were mathematically reconstructed and compared with those, measured experimentally.

  20. Mechanistic QSAR models for interpreting degradation rates of sulfonamides in UV-photocatalysis systems.

    Science.gov (United States)

    Huang, Xiangfeng; Feng, Yi; Hu, Cui; Xiao, Xiaoyu; Yu, Daliang; Zou, Xiaoming

    2015-11-01

    Photocatalysis is one of the most effective methods for treating antibiotic wastewater. Thus, it is of great significance to determine the relationship between degradation rates and structural characteristics of antibiotics in photocatalysis processes. In the present study, the photocatalytic degradation characteristics of 10 sulfonamides (SAs) were studied using two photocatalytic systems composed of nanophase titanium dioxide (nTiO2) plus ultraviolet (UV) and nTiO2/activated carbon fiber (ACF) plus UV. The results indicated that the largest apparent SA degradation rate constant (Kapp) is approximately 5 times as large as that of the smallest one. Based on the degradation mechanism and the partial least squares regression (PLS) method, optimum Quantitative Structure Activity Relationship (QSAR) models were developed for the two systems. Mechanistic models indicated that the degradation rule of SAs in the TiO2 systems strongly relates to their highest occupied molecular orbital (Ehomo), the maximum values of nucleophilic attack (f(+)x), and the minimum values of the most negative partial charge on a main-chain atom (q(C)min), whereas the maximum values of OH radical attack (f(0)x) and the apparent adsorption rate constant values (kad) are key factors affecting the degradation rule of SAs in the TiO2/ACF system. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Lithology-derived structure classification from the joint interpretation of magnetotelluric and seismic models

    Science.gov (United States)

    Bedrosian, P.A.; Maercklin, N.; Weckmann, U.; Bartov, Y.; Ryberg, T.; Ritter, O.

    2007-01-01

    Magnetotelluric and seismic methods provide complementary information about the resistivity and velocity structure of the subsurface on similar scales and resolutions. No global relation, however, exists between these parameters, and correlations are often valid for only a limited target area. Independently derived inverse models from these methods can be combined using a classification approach to map geologic structure. The method employed is based solely on the statistical correlation of physical properties in a joint parameter space and is independent of theoretical or empirical relations linking electrical and seismic parameters. Regions of high correlation (classes) between resistivity and velocity can in turn be mapped back and re-examined in depth section. The spatial distribution of these classes, and the boundaries between them, provide structural information not evident in the individual models. This method is applied to a 10 km long profile crossing the Dead Sea Transform in Jordan. Several prominent classes are identified with specific lithologies in accordance with local geology. An abrupt change in lithology across the fault, together with vertical uplift of the basement suggest the fault is sub-vertical within the upper crust. ?? 2007 The Authors Journal compilation ?? 2007 RAS.

  2. Seasonality of Oxygen isotope composition in cow (Bos taurus) hair and its model interpretation

    Science.gov (United States)

    Chen, Guo; Schnyder, Hans; Auerswald, Karl

    2017-04-01

    Oxygen isotopes in animal and human tissues are expected to be good recorders of geographical origin and migration histories based on the isotopic relationship between hair oxygen and annual precipitation and the well-known spatial pattern of oxygen isotope composition in meteoric water. However, seasonal variation of oxygen isotope composition may diminish the origin information in the tissues. Here the seasonality of oxygen isotope composition in tail hair was investigated in a domestic suckler cow (Bos taurus) that underwent different ambient conditions, physiological states, and keeping and feeding strategies during five years. A detailed mechanistic model involving in ambient conditions, soil properties and animal physiology was built to explain this variation. The measured oxygen isotope composition in hair was significantly related (panalysis. Modelling suggested that this relation was only partly derived from the direct influence of feed moisture. Ambient conditions (temperature, moisture) did not only influence the isotopic signal of precipitation but also affected the animal itself (drinking water demand, transcutaneous vapor etc.). The clear temporal variation thus resulted from complex interactions with multiple influences. The twofold influence of ambient conditions via the feed and via the animal itself is advantageous for tracing the geographic origin because the oxygen isotope composition is then less influenced by variations in moisture uptake; however, it is unfavorable for indicating the production system, e.g. to distinguish between milk produced from fresh grass or from silage.

  3. Interpretation Of Wind Regime of Bagnold Dunes In Gale Crater, Guided By Third-Generation Models Of Dune Formation

    Science.gov (United States)

    Rubin, D. M.; Courrech Du Pont, S.; Narteau, C.; Newman, C. E.; Bridges, N.; Lapotre, M. G. A.

    2016-12-01

    HiRISE images show that barchan dunes in the Bagnold dune field merge and change abruptly into linear dunes as they migrate southward (Fig. 1). Models of the conditions required to produce this kind of change have evolved substantially over the past half-century. First-generation models (pre-1980s) generally considered dunes to be either transverse or parallel to the sand-transport direction and interpreted winds accordingly. These models required drastic changes in winds to convert barchans to linear dunes (from unidirectional to bi-directional winds). Second-generation models used experiments and theory to quantify the orientation of transverse, oblique, and longitudinal dunes in bi-directional wind regimes, but these models also require substantial differences in wind regime between barchans and linear dunes (Rubin & Hunter, 1987, Science). Third-generation models—which are still in their infancy—have used lab experiments and stability analysis to show that where the bed is partially starved, a surprisingly weak secondary wind can induce grossly different dune morphology and orientation (Courrech du Pont, et al., 2014, Geology). For example, adding a secondary wind oriented at an angle of 150° to the main wind and having a magnitude of only 20% of it will convert barchans to linear dunes on a partially starved bed. We interpret the wind regime of the Bagnold dunes using lab experiments, third-generation dune models, observations of migration of superimposed ripples, and wind-models. Several characteristics of these dunes make starved-bed models appealing. First, the bed is, in fact, partially starved. Second, the change from barchans to linear dunes coincides with changes in sand coverage and occurs over an extremely short distance ( a single dune wavelength). In this situation, the secondary wind required to produce linear dunes can be nearly an order of magnitude weaker than the main mode, allowing the required abrupt change in winds to be less extreme

  4. Modeling of the Enceladus water vapor jets for interpreting UVIS star and solar occultation observations

    Science.gov (United States)

    Portyankina, Ganna; Esposito, Larry W.; Aye, Klaus-Michael; Hansen, Candice J.

    2015-11-01

    One of the most spectacular discoveries of the Cassini mission is jets emitting from the southern pole of Saturn’s moon Enceladus. The composition of the jets is water vapor and salty ice grains with traces of organic compounds. Jets, merging into a wide plume at a distance, are observed by multiple instruments on Cassini. Recent observations of the visible dust plume by the Cassini Imaging Science Subsystem (ISS) identified as many as 98 jet sources located along “tiger stripes” [Porco et al. 2014]. There is a recent controversy on the question if some of these jets are “optical illusion” caused by geometrical overlap of continuous source eruptions along the “tiger stripes” in the field of view of ISS [Spitale et al. 2015]. The Cassini’s Ultraviolet Imaging Spectrograph (UVIS) observed occultations of several stars and the Sun by the water vapor plume of Enceladus. During the solar occultation separate collimated gas jets were detected inside the background plume [Hansen et al., 2006 and 2011]. These observations directly provide data about water vapor column densities along the line of sight of the UVIS instrument and could help distinguish between the presence of only localized or also continuous sources. We use Monte Carlo simulations and Direct Simulation Monte Carlo (DSMC) to model the plume of Enceladus with multiple (or continuous) jet sources. The models account for molecular collisions, gravitational and Coriolis forces. The models result in the 3-D distribution of water vapor density and surface deposition patterns. Comparison between the simulation results and column densities derived from UVIS observations provide constraints on the physical characteristics of the plume and jets. The specific geometry of the UVIS observations helps to estimate the production rates and velocity distribution of the water molecules emitted by the individual jets.Hansen, C. J. et al., Science 311:1422-1425 (2006); Hansen, C. J. et al, GRL 38:L11202 (2011

  5. Deep geothermal systems interpreted by coupled thermo-hydraulic-mechanical-chemical numerical modeling

    Science.gov (United States)

    Peters, Max; Lesueur, Martin; Held, Sebastian; Poulet, Thomas; Veveakis, Manolis; Regenauer-Lieb, Klaus; Kohl, Thomas

    2017-04-01

    The dynamic response of the geothermal reservoirs of Soultz-sous-Forêts (NE France) and a new site in Iceland are theoretically studied upon fluid injection and production. Since the Soultz case can be considered the most comprehensive project in the area of enhanced geothermal systems (EGS), it is tailored for the testing of forward modeling techniques that aim at the characterization of fluid dynamics and mechanical properties in any deeply-seated fractured cystalline reservoir [e.g. Held et al., 2014]. We present multi-physics finite element models using the recently developed framework MOOSE (mooseframework.org) that implicitly consider fully-coupled feedback mechanisms of fluid-rock interaction at depth where EGS are located (depth > 5 km), i.e. the effects of dissipative strain softening on chemical reactions and reactive transport [Poulet et al., 2016]. In a first suite of numerical experiments, we show that an accurate simulation of propagation fronts allows studying coupled fluid and heat transport, following preferred pathways, and the transport time of the geothermal fluid between injection and production wells, which is in good agreement with tracer experiments performed inside the natural reservoir. Based on induced seismicity experiments and related damage along boreholes, we concern with borehole instabilities resulting from pore pressure variations and (a)seismic creep in a second series of simulations. To this end, we account for volumetric and deviatoric components, following the approach of Veveakis et al. (2016), and discuss the mechanisms triggering slow earthquakes in the stimulated reservoirs. Our study will allow applying concepts of unconventional geomechanics, which were previously reviewed on a theoretical basis [Regenauer-Lieb et al., 2015], to substantial engineering problems of deep geothermal reservoirs in the future. REFERENCES Held, S., Genter, A., Kohl, T., Kölbel, T., Sausse, J. and Schoenball, M. (2014). Economic evaluation of

  6. Shaded computer graphic techniques for visualizing and interpreting analytic fluid flow models

    Science.gov (United States)

    Parke, F. I.

    1981-01-01

    Mathematical models which predict the behavior of fluid flow in different experiments are simulated using digital computers. The simulations predict values of parameters of the fluid flow (pressure, temperature and velocity vector) at many points in the fluid. Visualization of the spatial variation in the value of these parameters is important to comprehend and check the data generated, to identify the regions of interest in the flow, and for effectively communicating information about the flow to others. The state of the art imaging techniques developed in the field of three dimensional shaded computer graphics is applied to visualization of fluid flow. Use of an imaging technique known as 'SCAN' for visualizing fluid flow, is studied and the results are presented.

  7. The Collaborative Improvement Model: An Interpretive Study of Revising a Curriculum.

    Science.gov (United States)

    Nosek, Catherine M; Scheckel, Martha M; Waterbury, Theresa; MacDonald, Ann; Wozney, Nancee

    Curriculum revisions in nursing programs are necessary to maintain currency and ensure that nursing students are prepared to competently practice nursing. Yet, the research for curriculum revisions in nursing education is sparse, leaving nursing educators with a thin evidence base upon which to revise curricula. The purpose of this phenomenological and hermeneutical study was to understand the experiences of faculty members and students who used the Collaborative Improvement Model (CIM) at a midwestern nursing department as an approach to revise their curriculum. The findings of this study demonstrate how the CIM (a) promoted student involvement in revising a curriculum, (b) facilitated faculty collaboration across two campuses with different campus cultures, (c) encouraged the Scholarship of Teaching and Learning, and (d) emphasized the need to use external facilitators when revising a curriculum. Faculty members in nursing programs can use this study when considering the CIM as a framework for revising their curricula. Published by Elsevier Inc.

  8. Analytic modeling, simulation and interpretation of broadband beam coupling impedance bench measurements

    Energy Technology Data Exchange (ETDEWEB)

    Niedermayer, U., E-mail: niedermayer@temf.tu-darmstadt.de [Institut für Theorie Elektromagnetischer Felder (TEMF), Technische Universität Darmstadt, Schloßgartenstraße 8, 64289 Darmstadt (Germany); Eidam, L. [Institut für Theorie Elektromagnetischer Felder (TEMF), Technische Universität Darmstadt, Schloßgartenstraße 8, 64289 Darmstadt (Germany); Boine-Frankenheim, O. [Institut für Theorie Elektromagnetischer Felder (TEMF), Technische Universität Darmstadt, Schloßgartenstraße 8, 64289 Darmstadt (Germany); GSI Helmholzzentrum für Schwerionenforschung, Planckstraße 1, 64291 Darmstadt (Germany)

    2015-03-11

    First, a generalized theoretical approach towards beam coupling impedances and stretched-wire measurements is introduced. Applied to a circular symmetric setup, this approach allows to compare beam and wire impedances. The conversion formulas for TEM scattering parameters from measurements to impedances are thoroughly analyzed and compared to the analytical beam impedance solution. A proof of validity for the distributed impedance formula is given. The interaction of the beam or the TEM wave with dispersive material such as ferrite is discussed. The dependence of the obtained beam impedance on the relativistic velocity β is investigated and found as material property dependent. Second, numerical simulations of wakefields and scattering parameters are compared. The applicability of scattering parameter conversion formulas for finite device length is investigated. Laboratory measurement results for a circularly symmetric test setup, i.e. a ferrite ring, are shown and compared to analytic and numeric models. The optimization of the measurement process and error reduction strategies are discussed.

  9. Modeling flow in nanoporous, membrane reservoirs and interpretation of coupled fluxes

    Science.gov (United States)

    Geren, Filiz

    The average pore size in unconventional, tight-oil reservoirs is estimated to be less than 100 nm. At this pore size, Darcy flow is no longer the dominating flow mechanism and a combination of diffusive flows determines the flow characteristics. Concentration driven self-diffusion has been well known and included in the flow and transport models in porous media. However, when the sizes of the pores and pore-throats decrease down to the size of the hydrocarbon molecules, the porous medium acts like a semi-permeable membrane, and the size of the pore openings dictates the direction of transport between adjacent pores. Accordingly, characterization of flow and transport in tight unconventional plays requires understanding of their membrane properties. This Master of Science thesis first highlights the membrane properties of nanoporous, unconventional reservoirs and then discusses how filtration effects can be incorporated into the models of transport in nanoporous media within the coupled flux concept. The effect of filtration on fluid composition and its impact on black-oil fluid properties like bubble point pressure is also demonstrated. To define filtration and filtration pressure in unconventional, tight-oil reservoirs, analogy to chemical osmosis is applied two pore systems connected with a pore throat, which shows membrane properties. Because the pore throat selectivity permits the passage of fluid molecules by their sizes, given a filtration pressure difference between the two pore systems, the concentration difference between the systems is determined by flash calculations. The results are expressed in the form of filtration (membrane) efficiency, which is essential parameter to define coupled fluxes for porous media flow.

  10. Modeling GPR data to interpret porosity and DNAPL saturations for calibration of a 3-D multiphase flow simulation

    Science.gov (United States)

    Sneddon, Kristen W.; Powers, Michael H.; Johnson, Raymond H.; Poeter, Eileen P.

    2002-01-01

    Dense nonaqueous phase liquids (DNAPLs) are a pervasive and persistent category of groundwater contamination. In an effort to better understand their unique subsurface behavior, a controlled and carefully monitored injection of PCE (perchloroethylene), a typical DNAPL, was performed in conjunction with the University of Waterloo at Canadian Forces Base Borden in 1991. Of the various geophysical methods used to monitor the migration of injected PCE, the U.S. Geological Survey collected 500-MHz ground penetrating radar (GPR) data. These data are used in determining calibration parameters for a multiphase flow simulation. GPR data were acquired over time on a fixed two-dimensional surficial grid as the DNAPL was injected into the subsurface. Emphasis is on the method of determining DNAPL saturation values from this time-lapse GPR data set. Interactive full-waveform GPR modeling of regularized field traces resolves relative dielectric permittivity versus depth profiles for pre-injection and later-time data. Modeled values are end members in recursive calculations of the Bruggeman-Hanai-Sen (BHS) mixing formula, yielding interpreted pre-injection porosity and post-injection DNAPL saturation values. The resulting interpreted physical properties of porosity and DNAPL saturation of the Borden test cell, defined on a grid spacing of 50 cm with 1-cm depth resolution, are used as observations for calibration of a 3-D multiphase flow simulation. Calculated values of DNAPL saturation in the subsurface at 14 and 22 hours after the start of injection, from both the GPR and the multiphase flow modeling, are interpolated volumetrically and presented for visual comparison.

  11. Development and validation of open-source software for DNA mixture interpretation based on a quantitative continuous model.

    Science.gov (United States)

    Manabe, Sho; Morimoto, Chie; Hamano, Yuya; Fujimoto, Shuntaro; Tamaki, Keiji

    2017-01-01

    In criminal investigations, forensic scientists need to evaluate DNA mixtures. The estimation of the number of contributors and evaluation of the contribution of a person of interest (POI) from these samples are challenging. In this study, we developed a new open-source software "Kongoh" for interpreting DNA mixture based on a quantitative continuous model. The model uses quantitative information of peak heights in the DNA profile and considers the effect of artifacts and allelic drop-out. By using this software, the likelihoods of 1-4 persons' contributions are calculated, and the most optimal number of contributors is automatically determined; this differs from other open-source software. Therefore, we can eliminate the need to manually determine the number of contributors before the analysis. Kongoh also considers allele- or locus-specific effects of biological parameters based on the experimental data. We then validated Kongoh by calculating the likelihood ratio (LR) of a POI's contribution in true contributors and non-contributors by using 2-4 person mixtures analyzed through a 15 short tandem repeat typing system. Most LR values obtained from Kongoh during true-contributor testing strongly supported the POI's contribution even for small amounts or degraded DNA samples. Kongoh correctly rejected a false hypothesis in the non-contributor testing, generated reproducible LR values, and demonstrated higher accuracy of the estimated number of contributors than another software based on the quantitative continuous model. Therefore, Kongoh is useful in accurately interpreting DNA evidence like mixtures and small amounts or degraded DNA samples.

  12. Simplified mathematical models for interpreting the results of tests carried out by labelling the whole piezometric column in water wells

    International Nuclear Information System (INIS)

    Munera, H.A.

    1974-01-01

    Approximate methods used to interpret the results of tests based on radioactive tracer dilution in a single water well by labelling the whole piezometric column are described; these simple mathematical models have been used to obtain semi-quantitative data on the apparent velocity (horizontal) in non-homogeneous aquifers with flow rates of metres daily. Measurements have also been made in a homogeneous aquifer with velocities of centimetres daily. Interpretation is based on determination of the average concentration for the various well zones; this involves recognition of a mean velocity for each region. All the tracer dilution effects that are not due to horizontal or vertical flow between two zones, i.e. convection, artificial mixing, diffusion and so on, are grouped together as a single term, which is taken arbitrarily to be proportional to the difference in concentration between the regions under consideration; its value is obtained from the experimental dilution curve. The model was applied to the solution of the three cases encountered most frequently during our measurements in Colombia: (a) when the well penetrates a permeable zone and adjacent impermeable zone; (b) when the well penetrates a permeable zone contained between impermeable regions; and (c) when the well traverses an aquifer with two adjacent zones of different permeability contained between impermeable zones. The shape of the dilution curve (logarithm of concentration versus time, usually with two or more slopes) is predicted by the model, the approximate nature of which is consistent with the fact that the method of labelling the whole piezometric column is semi-quantitative. The results obtained for measurements made when there are considerable vertical flows are apparently correct, but there is no other experimental measurement available to confirm them. (author) [es

  13. How a joint interpretation of seismic scattering, velocity, and attenuation models explains the nature of the Campi Flegrei (Italy).

    Science.gov (United States)

    Calo, M.; Tramelli, A.

    2017-12-01

    Seismic P and S velocity models (and their ratio Vp/Vs) help illuminating the geometrical structure of the bodies and give insight on the presence of water, molten or gas saturated regions. Seismic attenuation represents the anelastic behavior of the medium. Due to its dependence on temperature, fluid contents and cracks presence, this parameter is also largely used to characterize the structures of volcanoes and geothermal areas. Scattering attenuation is related, in the upper crust, to the amount, size and organization of the fractures giving complementary information on the state of the medium.Therefore a joint interpretation of these models provides an exhaustive view of the elastic parameters in volcanic regions. Campi Flegrei is an active Caldera marked by strong vertical deformations of the ground called bradyseisms and several models have been proposed to describe the nature and the geometry of the bodies responsible of the bradyseisms. Here we show Vp, Vp/Vs, Qp and scattering models carried out by applying an enhanced seismic tomography method that combines de double difference approach (Zhang and Thurber, 2003) and the Weigthed Average Method (Calò et al., 2009, Calò et al., 2011, 2013). The data used are the earthquakes recorded during the largest bradyseism crisis of the 80's. Our method allowed to image structures with linear dimension of 0.5-1.2km, resulting in an improvement of the resolving power at least two times of the other published models (e.g. Priolo et al., 2012). The joint interpretation of seismic models allowed to discern small anomalous bodies at shallow depth (0.5-2.0 km) marked by relatively low Vp, high Vp/Vs ratio and low Qp values associated with the presence of shallow geothermal water saturated reservoir from regions with low Vp, low Vp/Vs and low Qp related to the gas saturated part of the reservoir. At deeper depth (2-3.5 km) bodies with high Vp and Vp/Vs and low Qp are associated with magmatic intrusions. The Scattering

  14. The System Dynamics Model User Sustainability Explorer (SD-MUSE): a user-friendly tool for interpreting system dynamic models

    Science.gov (United States)

    System Dynamics (SD) models are useful for holistic integration of data to evaluate indirect and cumulative effects and inform decisions. Complex SD models can provide key insights into how decisions affect the three interconnected pillars of sustainability. However, the complexi...

  15. Mountains on Io: High-resolution Galileo observations, initial interpretations, and formation models

    Science.gov (United States)

    Turtle, E.P.; Jaeger, W.L.; Keszthelyi, L.P.; McEwen, A.S.; Milazzo, M.; Moore, J.; Phillips, C.B.; Radebaugh, J.; Simonelli, D.; Chuang, F.; Schuster, P.; Alexander, D.D.A.; Capraro, K.; Chang, S.-H.; Chen, A.C.; Clark, J.; Conner, D.L.; Culver, A.; Handley, T.H.; Jensen, D.N.; Knight, D.D.; LaVoie, S.K.; McAuley, M.; Mego, V.; Montoya, O.; Mortensen, H.B.; Noland, S.J.; Patel, R.R.; Pauro, T.M.; Stanley, C.L.; Steinwand, D.J.; Thaller, T.F.; Woncik, P.J.; Yagi, G.M.; Yoshimizu, J.R.; Alvarez Del Castillo, E.M.; Beyer, R.; Branston, D.; Fishburn, M.B.; Muller, Birgit; Ragan, R.; Samarasinha, N.; Anger, C.D.; Cunningham, C.; Little, B.; Arriola, S.; Carr, M.H.; Asphaug, E.; Morrison, D.; Rages, K.; Banfield, D.; Bell, M.; Burns, J.A.; Carcich, B.; Clark, B.; Currier, N.; Dauber, I.; Gierasch, P.J.; Helfenstein, P.; Mann, M.; Othman, O.; Rossier, L.; Solomon, N.; Sullivan, R.; Thomas, P.C.; Veverka, J.; Becker, T.; Edwards, K.; Gaddis, L.; Kirk, R.; Lee, E.; Rosanova, T.; Sucharski, R.M.; Beebe, R.F.; Simon, A.; Belton, M.J.S.; Bender, K.; Fagents, S.; Figueredo, P.; Greeley, R.; Homan, K.; Kadel, S.; Kerr, J.; Klemaszewski, J.; Lo, E.; Schwarz, W.; Williams, D.; Williams, K.; Bierhaus, B.; Brooks, S.; Chapman, C.R.; Merline, B.; Keller, J.; Tamblyn, P.; Bouchez, A.; Dyundian, U.; Ingersoll, A.P.; Showman, A.; Spitale, J.; Stewart, S.; Vasavada, A.; Breneman, H.H.; Cunningham, W.F.; Johnson, T.V.; Jones, T.J.; Kaufman, J.M.; Klaasen, K.P.; Levanas, G.; Magee, K.P.; Meredith, M.K.; Orton, G.S.; Senske, D.A.; West, A.; Winther, D.; Collins, G.; Fripp, W.J.; Head, J. W.; Pappalardo, R.; Pratt, S.; Prockter, L.; Spaun, N.; Colvin, T.; Davies, M.; DeJong, E.M.; Hall, J.; Suzuki, S.; Gorjian, Z.; Denk, T.; Giese, B.; Koehler, U.; Neukum, G.; Oberst, J.; Roatsch, T.; Tost, W.; Wagner, R.; Dieter, N.; Durda, D.; Geissler, P.; Greenberg, R.J.; Hoppa, G.; Plassman, J.; Tufts, R.; Fanale, F.P.; Granahan, J.C.

    2001-01-01

    During three close flybys in late 1999 and early 2000 the Galileo spacecraft ac-quired new observations of the mountains that tower above Io's surface. These images have revealed surprising variety in the mountains' morphologies. They range from jagged peaks several kilometers high to lower, rounded structures. Some are very smooth, others are covered by numerous parallel ridges. Many mountains have margins that are collapsing outward in large landslides or series of slump blocks, but a few have steep, scalloped scarps. From these observations we can gain insight into the structure and material properties of Io's crust as well as into the erosional processes acting on Io. We have also investigated formation mechanisms proposed for these structures using finite-element analysis. Mountain formation might be initiated by global compression due to the high rate of global subsidence associated with Io's high resurfacing rate; however, our models demonstrate that this hypothesis lacks a mechanism for isolating the mountains. The large fraction (???40%) of mountains that are associated with paterae suggests that in some cases these features are tectonically related. Therefore we have also simulated the stresses induced in Io's crust by a combination of a thermal upwelling in the mantle with global lithospheric compression and have shown that this can focus compressional stresses. If this mechanism is responsible for some of Io's mountains, it could also explain the common association of mountains with paterae. Copyright 2001 by the American Geophysical Union.

  16. Use of modeling and simulation in the planning, analysis and interpretation of ultrasonic testing; Einsatz von Modellierung und Simulation bei der Planung, Analyse und Interpretation von Ultraschallpruefungen

    Energy Technology Data Exchange (ETDEWEB)

    Algernon, Daniel [SVTI Schweizerischer Verein fuer technische Inspektionen, Wallisellen (Switzerland). ZfP-Labor; Grosse, Christian U. [Technische Univ. Muenchen (Germany). Lehrstuhl fuer Zerstoerungsfreie Pruefung

    2016-05-01

    Acoustic testing methods such as ultrasound and impact echo are an important tool in building diagnostics. The range includes thickness measurements, the representation of the internal component geometry as well as the detection of voids (gravel pockets), delaminations or possibly locating grouting faults in the interior of metallic cladding tubes of tendon ducts. Basically acoustic method for non-destructive testing (NDT) is based on the excitation of elastic waves that interact with the target object (e.g. to detect discontinuity in the component) at the acoustic interface. From the signal received at the component surface this interaction shall be detected and interpreted to draw conclusions about the presence of the target object, and optionally to determine its size and position (approximately). Although the basic underlying physical principles of the application of elastic waves in NDT are known, it can be complicated by complex relationships in the form of restricted access, component geometries, or the type and form of reflectors. To estimate the chances of success of a test is already often not trivial. These circumstances highlight the importance of using simulations that allow a theoretically sound basis for testing and allow easy optimizing test systems. The deployable simulation methods are varied. Common are in particular the finite element method, the Elasto Finite Integration Technique and semi-analytical calculation methods. [German] Akustische Pruefverfahren wie Ultraschall und Impact-Echo sind ein wichtiges Werkzeug der Bauwerksdiagnose. Das Einsatzspektrum beinhaltet Dickenmessungen, die Darstellung der inneren Bauteilgeometrie ebenso wie die Ortung von Kiesnestern, Delaminationen oder u.U. die Ortung von Verpressfehlern im Innern metallischer Huellrohre von Spannkanaelen. Grundsaetzlich beruhen akustische Verfahren zur Zerstoerungsfreien Pruefung (ZfP) auf der Anregung elastischer Wellen, die mit dem Zielobjekt (z. B. zu detektierende Ungaenze

  17. An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

    Science.gov (United States)

    Nemati, Shamim; Holder, Andre; Razmi, Fereshteh; Stanley, Matthew D; Clifford, Gari D; Buchman, Timothy G

    2018-04-01

    clinical utility of the proposed sepsis prediction model.

  18. Contagion effect of enabling or coercive use of costing model within the managerial couple in lean organizations

    DEFF Research Database (Denmark)

    Kristensen, Thomas; Israelsen, Poul

    In the lean strategy is enabling formalization behaviour expected at the lower levels of management to be successful. We study the contagion effect between the superior, middle manager, of the lower level manager. This effect is proposed to be a dominant contingency variable for the use of costin...

  19. How to Develop and Interpret a Credibility Assessment of Numerical Models for Human Research: NASA-STD-7009 Demystified

    Science.gov (United States)

    Nelson, Emily S.; Mulugeta, Lealem; Walton, Marlei; Myers, Jerry G.

    2014-01-01

    In the wake of the Columbia accident, the NASA-STD-7009 [1] credibility assessment was developed as a unifying platform to describe model credibility and the uncertainties in its modeling predictions. This standard is now being adapted by NASAs Human Research Program to cover a wide range of numerical models for human research. When used properly, the standard can improve the process of code development by encouraging the use of best practices. It can also give management more insight in making informed decisions through a better understanding of the models capabilities and limitations.To a newcomer, the abstractions presented in NASA-STD-7009 and the sheer volume of information that must be absorbed can be overwhelming. This talk is aimed at describing the credibility assessment, which is the heart of the standard, in plain terms. It will outline how to develop a credibility assessment under the standard. It will also show how to quickly interpret the graphs and tables that result from the assessment and how to drill down from the top-level view to the foundation of the assessment. Finally, it will highlight some of the resources that are available for further study.

  20. Analysis of Success Factors to Implement Sustainable Supply Chain Management Using Interpretive Structural Modeling Technique: A Real Case Perspective

    Directory of Open Access Journals (Sweden)

    Mengke Yang

    2017-01-01

    Full Text Available Sustainability draws increased supply chain management (SCM attention. This article analyzes critical success to the assessment, evaluation, and attainment of sustainable supply chain management (SSCM, assessed through critical-success identification and qualitative data analysis. Namely, a literature review selected of 188 articles, published between January 1994 and November 2016, helps identify the most influential success factors. The qualitative data analysis pertains to fifteen such successes, identified in the literature review and through our collaboration with other academic researchers and industrial specialists. Notably, the study’s qualitative data analysis, interpretive structural modeling (ISM, unconceals the mutual impact among the most prominent SSCM success factors. The economic benefits and environmental awareness of suppliers are recognized as the most significant success factors, which could allow business enterprises and other organizations to implement a SSCM framework, with intentionality and the sustainability in their business. The article concludes with suggestions for future research directions.

  1. Interpreting the nonlinear dielectric response of glass-formers in terms of the coupling model

    International Nuclear Information System (INIS)

    Ngai, K. L.

    2015-01-01

    Nonlinear dielectric measurements at high electric fields of glass-forming glycerol and propylene carbonate initially were carried out to elucidate the dynamic heterogeneous nature of the structural α-relaxation. Recently, the measurements were extended to sufficiently high frequencies to investigate the nonlinear dielectric response of faster processes including the so-called excess wing (EW), appearing as a second power law at high frequencies in the loss spectra of many glass formers without a resolved secondary relaxation. While a strong increase of dielectric constant and loss is found in the nonlinear dielectric response of the α-relaxation, there is a lack of significant change in the EW. A surprise to the experimentalists finding it, this difference in the nonlinear dielectric properties between the EW and the α-relaxation is explained in the framework of the coupling model by identifying the EW investigated with the nearly constant loss (NCL) of caged molecules, originating from the anharmonicity of the intermolecular potential. The NCL is terminated at longer times (lower frequencies) by the onset of the primitive relaxation, which is followed sequentially by relaxation processes involving increasing number of molecules until the terminal Kohlrausch α-relaxation is reached. These intermediate faster relaxations, combined to form the so-called Johari-Goldstein (JG) β-relaxation, are spatially and dynamically heterogeneous, and hence exhibit nonlinear dielectric effects, as found in glycerol and propylene carbonate, where the JG β-relaxation is not resolved and in D-sorbitol where it is resolved. Like the linear susceptibility, χ 1 (f), the frequency dispersion of the third-order dielectric susceptibility, χ 3 (f), was found to depend primarily on the α-relaxation time, and independent of temperature T and pressure P. I show this property of the frequency dispersions of χ 1 (f) and χ 3 (f) is the characteristic of the many-body relaxation

  2. Scanning Tunneling Microscopy - image interpretation

    International Nuclear Information System (INIS)

    Maca, F.

    1998-01-01

    The basic ideas of image interpretation in Scanning Tunneling Microscopy are presented using simple quantum-mechanical models and supplied with examples of successful application. The importance is stressed of a correct interpretation of this brilliant experimental surface technique

  3. Interpreting the nonlinear dielectric response of glass-formers in terms of the coupling model

    Energy Technology Data Exchange (ETDEWEB)

    Ngai, K. L. [CNR-IPCF, Largo Bruno Pontecorvo 3, I-56127 Pisa, Italy and Dipartimento di Fisica, Università di Pisa, Largo B. Pontecorvo 3, I-56127 Pisa (Italy)

    2015-03-21

    Nonlinear dielectric measurements at high electric fields of glass-forming glycerol and propylene carbonate initially were carried out to elucidate the dynamic heterogeneous nature of the structural α-relaxation. Recently, the measurements were extended to sufficiently high frequencies to investigate the nonlinear dielectric response of faster processes including the so-called excess wing (EW), appearing as a second power law at high frequencies in the loss spectra of many glass formers without a resolved secondary relaxation. While a strong increase of dielectric constant and loss is found in the nonlinear dielectric response of the α-relaxation, there is a lack of significant change in the EW. A surprise to the experimentalists finding it, this difference in the nonlinear dielectric properties between the EW and the α-relaxation is explained in the framework of the coupling model by identifying the EW investigated with the nearly constant loss (NCL) of caged molecules, originating from the anharmonicity of the intermolecular potential. The NCL is terminated at longer times (lower frequencies) by the onset of the primitive relaxation, which is followed sequentially by relaxation processes involving increasing number of molecules until the terminal Kohlrausch α-relaxation is reached. These intermediate faster relaxations, combined to form the so-called Johari-Goldstein (JG) β-relaxation, are spatially and dynamically heterogeneous, and hence exhibit nonlinear dielectric effects, as found in glycerol and propylene carbonate, where the JG β-relaxation is not resolved and in D-sorbitol where it is resolved. Like the linear susceptibility, χ{sub 1}(f), the frequency dispersion of the third-order dielectric susceptibility, χ{sub 3}(f), was found to depend primarily on the α-relaxation time, and independent of temperature T and pressure P. I show this property of the frequency dispersions of χ{sub 1}(f) and χ{sub 3}(f) is the characteristic of the many

  4. Evolution of the quaternary magmatic system, Mineral Mountains, Utah: Interpretations from chemical and experimental modeling

    Energy Technology Data Exchange (ETDEWEB)

    Nash, W.P.; Crecraft, H.R.

    1982-09-01

    The evolution of silicic magmas in the upper crust is characterized by the establishment of chemical and thermal gradients in the upper portion of magma chambers. The chemical changes observed in rhyolite magmas erupted over a period of 300,000 years in the Mineral Mountains are similar to those recorded at Twin Peaks, Utah, and in the spatially zoned Bishop Tuff from Long Valley, California. Chemical and fluid dynamic models indicate that cooling of a silicic magma body from the top and sides can result in the formation of a roof zone above a convecting region which is chemically and thermally stratified, as well as highly fractionated and water rich. Crystallization experiments have been performed with sodium carbonate solutions as an analog to crystallization in magmatic systems. Top and side cooling of a homogeneous sodium carbonate solution results in crystallization along the top and sides and upward convection of sodium carbonate-depleted fluid. A stably stratified roof zone, which is increasingly water rich and cooler upwards, develops over a thermally and chemically homogeneous convecting region. Crystallization at the top ultimately ceases, and continued upward convection of water-rich fluid causes a slight undersaturation adjacent to the roof despite cooler temperatures. By analogy, crystallization at the margins of a magma chamber and buoyant rise of the fractionated boundary layer into the roof zone can account for the chemical evolution of the magma system at the Mineral Mountains. To produce compositionally stratified silicic magmas requires thermal input to a silicic system via mafic magmas. The small volume, phenocryst-poor rhyolite magma which persisted for at least 300,000 years in the Mineral Mountains requires the presence of a continued thermal input from a mafic magma source. The presence of silicic lavas signifies that there is a substantial thermal anomaly both in the crust and upper mantle. The production of silicic lavas requires (1) the

  5. Interpretation of single and competitive adsorption of cadmium and zinc on activated carbon using monolayer and exclusive extended monolayer models.

    Science.gov (United States)

    Sellaoui, Lotfi; Dotto, Guilherme L; Lamine, Abdelmottaleb Ben; Erto, Alessandro

    2017-08-01

    In this work, a modeling analysis based on experimental tests of cadmium/zinc adsorption, in both single-compound and binary systems, was carried out. All the experimental tests were conducted at constant pH (around neutrality) and temperature (20 °C). The experimental results showed that the zinc adsorption capacity was higher than that of cadmium and it does not depend on cadmium presence in binary system. Conversely, cadmium adsorption is affected by zinc presence. In order to provide good understanding of the adsorption process, two statistical physics models were proposed. A monolayer and exclusive extended monolayer models were applied to interpret the single-compound and binary adsorption isotherms of zinc and cadmium on activated carbon. Based on these models, the modeling analysis demonstrated that zinc is dominant in solution and more favorably adsorbed on activated carbon surface. For instance, in single-compound systems, the number of ions bound per each receptor site was n (Zn 2+ ) = 2.12 > n (Cd 2+ ) = 0.98. Thus, the receptor sites of activated carbon are more selective for Zn 2+ than for Cd 2+ . Moreover, the determination of adsorption energy through the adopted models confirmed that zinc is more favored for adsorption in single-compound system (adsorption energies equal to 12.12 and 7.12 kJ/mol for Zn and Cd, respectively) and its adsorption energy does not depend on the cadmium presence in binary system. Finally, the adsorption energy values suggested that single-compound and binary adsorption of zinc and cadmium is a physisorption.

  6. Interpreting the GyPSuM Tomography Model in Terms of Thermal Heterogeneity and Major Oxide Composition

    Science.gov (United States)

    Bremner, P. M.; Forte, A. M.; Simmons, N. A.; Grand, S.

    2017-12-01

    Global seismic mantle tomography has advanced greatly over the past two decades with improved methods and increasing data coverage. However, interpreting these velocity distributions as thermochemical distributions remains challenging, and is the focus of our work here. Several groups of researchers [e.g., Forte & Mitrovica 2001, Cobden et al. 2009] have calculated the sensitivity of density and seismic velocities to temperature and compositional variations to estimate thermochemical heterogeneity in the lower mantle. Building on this work, we have assembled new expressions to calculate these derivatives throughout Earth's mantle, and included five major oxides: SiO2, MgO, FeO, Al2O3, and CaO. To do this, we constructed a layered 1-D compositional Earth model, and calculated its seismic and density profile using the mineral physics software package BurnMan [Cottaar et al. 2014]. Likewise, we calculated a series of profiles by systematically perturbing the compositional structure within individual layers and the temperature. From these profiles, we calculated the temperature and compositional derivatives, and determined the relative perturbations to shear velocity, bulk sound velocity, and density in terms of temperature and mineral concentration. We applied these new expressions to the 3-D GyPSuM tomography model [Simmons et al. 2010] in order to reinterpret the model's heterogeneity in terms of large-scale temperature and major element perturbations. The GyPSuM model is ideal because it incorporates P and S seismic travel times, geodynamic observations related to mantle density (and also includes initial, simplified mineral physical constraints) to simultaneously invert for global distributions of density and P and S velocities. The importance of this analysis is underscored by the ongoing debate concerning the interpretation of the Large Low Shear Velocity Provinces and their dynamic relationship to the convecting mantle. In addition to gaining insight into major

  7. Laboratory Experiments and Modeling for Interpreting Field Studies of Secondary Organic Aerosol Formation Using an Oxidation Flow Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Jimenez, Jose-Luis [Univ. of Colorado, Boulder, CO (United States)

    2016-02-01

    This grant was originally funded for deployment of a suite of aerosol instrumentation by our group in collaboration with other research groups and DOE/ARM to the Ganges Valley in India (GVAX) to study aerosols sources and processing. Much of the first year of this grant was focused on preparations for GVAX. That campaign was cancelled due to political reasons and with the consultation with our program manager, the research of this grant was refocused to study the applications of oxidation flow reactors (OFRs) for investigating secondary organic aerosol (SOA) formation and organic aerosol (OA) processing in the field and laboratory through a series of laboratory and modeling studies. We developed a gas-phase photochemical model of an OFR which was used to 1) explore the sensitivities of key output variables (e.g., OH exposure, O3, HO2/OH) to controlling factors (e.g., water vapor, external reactivity, UV irradiation), 2) develop simplified OH exposure estimation equations, 3) investigate under what conditions non-OH chemistry may be important, and 4) help guide design of future experiments to avoid conditions with undesired chemistry for a wide range of conditions applicable to the ambient, laboratory, and source studies. Uncertainties in the model were quantified and modeled OH exposure was compared to tracer decay measurements of OH exposure in the lab and field. Laboratory studies using OFRs were conducted to explore aerosol yields and composition from anthropogenic and biogenic VOC as well as crude oil evaporates. Various aspects of the modeling and laboratory results and tools were applied to interpretation of ambient and source measurements using OFR. Additionally, novel measurement methods were used to study gas/particle partitioning. The research conducted was highly successful and details of the key results are summarized in this report through narrative text, figures, and a complete list of publications acknowledging this grant.

  8. Barriers to implement green supply chain management in automobile industry using interpretive structural modeling technique: An Indian perspective

    Directory of Open Access Journals (Sweden)

    Sunil Luthra

    2011-07-01

    Full Text Available Purpose: Green Supply Chain Management (GSCM has received growing attention in the last few years. Most of the automobile industries are setting up their own manufacturing plants in competitive Indian market. Due to public awareness, economic, environmental or legislative reasons, the requirement of GSCM has increased.  In this context, this study aims to develop a structural model of the barriers to implement GSCM in Indian automobile industry.Design/methodology/approach: We have identified various barriers and contextual relationships among the identified barriers. Classification of barriers has been carried out based upon dependence and driving power with the help of MICMAC analysis. In addition to this, a structural model of barriers to implement GSCM in Indian automobile industry has also been put forward using Interpretive Structural Modeling (ISM technique. Findings: Eleven numbers of relevant barriers have been identified from literature and subsequent discussions with experts from academia and industry. Out of which, five numbers of barriers have been identified as dependent variables; three number of barriers have been identified as the driver variables and three number of barriers have been identified as the linkage variables. No barrier has been identified as autonomous variable. Four barriers have been identified as top level barriers and one bottom level barrier. Removal of these barriers has also been discussed.Research limitations/implications: A hypothetical model of these barriers has been developed based upon experts’ opinions. The conclusions so drawn may be further modified to apply in real situation problem. Practical implications: Clear understanding of these barriers will help organizations to prioritize better and manage their resources in an efficient and effective way.Originality/value: Through this paper we contribute to identify the barriers to implement GSCM in Indian automobile industry and to prioritize them

  9. The cloud services innovation platform- enabling service-based environmental modelling using infrastructure-as-a-service cloud computing

    Science.gov (United States)

    Service oriented architectures allow modelling engines to be hosted over the Internet abstracting physical hardware configuration and software deployments from model users. Many existing environmental models are deployed as desktop applications running on user's personal computers (PCs). Migration ...

  10. Localized Smart-Interpretation

    Science.gov (United States)

    Lundh Gulbrandsen, Mats; Mejer Hansen, Thomas; Bach, Torben; Pallesen, Tom

    2014-05-01

    The complex task of setting up a geological model consists not only of combining available geological information into a conceptual plausible model, but also requires consistency with availably data, e.g. geophysical data. However, in many cases the direct geological information, e.g borehole samples, are very sparse, so in order to create a geological model, the geologist needs to rely on the geophysical data. The problem is however, that the amount of geophysical data in many cases are so vast that it is practically impossible to integrate all of them in the manual interpretation process. This means that a lot of the information available from the geophysical surveys are unexploited, which is a problem, due to the fact that the resulting geological model does not fulfill its full potential and hence are less trustworthy. We suggest an approach to geological modeling that 1. allow all geophysical data to be considered when building the geological model 2. is fast 3. allow quantification of geological modeling. The method is constructed to build a statistical model, f(d,m), describing the relation between what the geologists interpret, d, and what the geologist knows, m. The para- meter m reflects any available information that can be quantified, such as geophysical data, the result of a geophysical inversion, elevation maps, etc... The parameter d reflects an actual interpretation, such as for example the depth to the base of a ground water reservoir. First we infer a statistical model f(d,m), by examining sets of actual interpretations made by a geological expert, [d1, d2, ...], and the information used to perform the interpretation; [m1, m2, ...]. This makes it possible to quantify how the geological expert performs interpolation through f(d,m). As the geological expert proceeds interpreting, the number of interpreted datapoints from which the statistical model is inferred increases, and therefore the accuracy of the statistical model increases. When a model f

  11. Teaching Real Data Interpretation with Models (TRIM): Analysis of Student Dialogue in a Large-Enrollment Cell and Developmental Biology Course.

    Science.gov (United States)

    Zagallo, Patricia; Meddleton, Shanice; Bolger, Molly S

    2016-01-01

    We present our design for a cell biology course to integrate content with scientific practices, specifically data interpretation and model-based reasoning. A 2-yr research project within this course allowed us to understand how students interpret authentic biological data in this setting. Through analysis of written work, we measured the extent to which students' data interpretations were valid and/or generative. By analyzing small-group audio recordings during in-class activities, we demonstrated how students used instructor-provided models to build and refine data interpretations. Often, students used models to broaden the scope of data interpretations, tying conclusions to a biological significance. Coding analysis revealed several strategies and challenges that were common among students in this collaborative setting. Spontaneous argumentation was present in 82% of transcripts, suggesting that data interpretation using models may be a way to elicit this important disciplinary practice. Argumentation dialogue included frequent co-construction of claims backed by evidence from data. Other common strategies included collaborative decoding of data representations and noticing data patterns before making interpretive claims. Focusing on irrelevant data patterns was the most common challenge. Our findings provide evidence to support the feasibility of supporting students' data-interpretation skills within a large lecture course. © 2016 P. Zagallo et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  12. Objective interpretation as conforming interpretation

    OpenAIRE

    Lidka Rodak

    2011-01-01

    The practical discourse willingly uses the formula of “objective interpretation”, with no regards to its controversial nature that has been discussed in literature.The main aim of the article is to investigate what “objective interpretation” could mean and how it could be understood in the practical discourse, focusing on the understanding offered by judicature.The thesis of the article is that objective interpretation, as identified with textualists’ position, is not possible to uphold, and ...

  13. Enabling benchmarking and improving operational efficiency at nuclear power plants through adoption of a common process model: SNPM (standard nuclear performance model)

    International Nuclear Information System (INIS)

    Pete Karns

    2006-01-01

    others. The goal of the SNPM is to give the people maintaining and operating nuclear power stations a common model on which to base their business processes and measure/benchmark themselves against others. The importance of benchmarking and comparing 'apples to apples' has and will continue to safely drive improvement and efficiencies throughout the business. For example, in the mid 1990's it was quite difficult to compare work management statistics and programs between plants. The introduction of several INPO documents, which eventually became the SNPM work management process (AP 928) enabled plants to benchmark and compare information on many aspects of work management, in fact INPO began to evaluate the nuclear plants on their implementation and usage of AP 928. Also, the standardization enabled the identification and benchmarking of innovations in plant processes and performance, which in turn helped to facilitate those innovations being accepted in other plants-thus furthering the cycle of continuous improvement. Using a master plan, all communities of practice are able to identify specific improvement projects and coordinate the implementation of the processes to ensure smooth transitions between the various process interface or intersection points. In essence the nuclear energy industry in the United States is working as one company-driving efficiencies and operational improvements. Key enablers in adopting the best practices like the SNPM are work, asset and supply chain management solutions - both from a functional and a technological point of view. In addition to the importance of supporting industry best practices, there are two additional attributes a nuclear power operating company should evaluate regarding software solutions for work, asset, and supply chain management: breadth of assets managed, and the architecture of solution. (author)

  14. Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures

    Directory of Open Access Journals (Sweden)

    M. Gergely

    2017-10-01

    Full Text Available The snowflake microstructure determines the microwave scattering properties of individual snowflakes and has a strong impact on snowfall radar signatures. In this study, individual snowflakes are represented by collections of randomly distributed ice spheres where the size and number of the constituent ice spheres are specified by the snowflake mass and surface-area-to-volume ratio (SAV and the bounding volume of each ice sphere collection is given by the snowflake maximum dimension. Radar backscatter cross sections for the ice sphere collections are calculated at X-, Ku-, Ka-, and W-band frequencies and then used to model triple-frequency radar signatures for exponential snowflake size distributions (SSDs. Additionally, snowflake complexity values obtained from high-resolution multi-view snowflake images are used as an indicator of snowflake SAV to derive snowfall triple-frequency radar signatures. The modeled snowfall triple-frequency radar signatures cover a wide range of triple-frequency signatures that were previously determined from radar reflectivity measurements and illustrate characteristic differences related to snow type, quantified through snowflake SAV, and snowflake size. The results show high sensitivity to snowflake SAV and SSD maximum size but are generally less affected by uncertainties in the parameterization of snowflake mass, indicating the importance of snowflake SAV for the interpretation of snowfall triple-frequency radar signatures.

  15. The Application of an Expert Model of Interpretive Skill to a Multicultural-Multimedia System on Ethnic Dance.

    Science.gov (United States)

    Beck, Robert J.; Martinez, Michael E.; Lires, Valerie

    1999-01-01

    Investigates the nature of expertise in the interpretation of cultural artifacts, particularly the Concheros dance of Mexico. Tests CD-ROM-based multimedia software designed to teach expert evaluation strategies. Shows that, compared with a control group, students using the software exhibited a greater ability to interpret the Concheros dance.…

  16. Interpreting Gender

    Directory of Open Access Journals (Sweden)

    Linda Nicholson

    2000-01-01

    Full Text Available In this article the author deconstructs dominant understandings of two concepts central to feminist analysis itself: gender and woman. Much of post-1960s feminist scholarship has relied on the distinction between “sex” and gender. Although this distinction has served many useful purposes (particularly that of allowing feminists to challenge biological determinism, it has also enabled feminists to preserve a type of dualistic thinking about women's identity. It has allowed feminists to think of differences among women as separable from that which women share. The author argues that this polar framework has enabled feminists to stress the deep differences between women's and men's culture-generated experiences. But, because the polar framework of contemporary society is neither completely stable or hegemonic nor links perfectly male and female experiences with male and female identified bodies, employing it as an unquestioned element of one's analysis also leads to problems. This framework falls to capture the gender deviance of many of us, reinforces cultural stereotypes of the meaning of female and male experience, and acts politically to suppress modes of being that challenge gender dualisms.

  17. Interpretation of Landscape Scale SWAT Model Outputs in the Western Lake Erie Basin: Potential Implications for Conservation Decision-Making

    Science.gov (United States)

    Johnson, M. V. V.; Behrman, K. D.; Atwood, J. D.; White, M. J.; Norfleet, M. L.

    2017-12-01

    takes time for monitoring efforts to measure meaningful changes over time. Careful interpretation of model outputs is imperative for appropriate application of current scientific knowledge to inform decision making, especially when models are used to set spatial and temporal goals around conservation practice adoption and water quality.

  18. Mammographic interpretation

    International Nuclear Information System (INIS)

    Tabor, L.

    1987-01-01

    For mammography to be an effective diagnostic method, it must be performed to a very high standard of quality. Otherwise many lesions, in particular cancer in its early stages, will simply not be detectable on the films, regardless of the skill of the mammographer. Mammographic interpretation consists of two basic steps: perception and analysis. The process of mammographic interpretation begins with perception of the lesion on the mammogram. Perception is influenced by several factors. One of the most important is the parenchymal pattern of the breast tissue, detection of pathologic lesions being easier with fatty involution. The mammographer should use a method for the systematic viewing of the mammograms that will ensure that all parts of each mammogram are carefully searched for the presence of lesions. The method of analysis proceeds according to the type of lesion. The contour analysis of primary importance in the evaluation of circumscribed tumors. After having analyzed the contour and density of a lesion and considered its size, the mammographer should be fairly certain whether the circumscribed tumor is benign or malignant. Fine-needle puncture and/or US may assist the mammographer in making this decision. Painstaking analysis is required because many circumscribed tumors do not need to be biopsied. The perception of circumscribed tumors seldom causes problems, but their analysis needs careful attention. On the other hand, the major challenge with star-shaped lesions is perception. They may be difficult to discover when small. Although the final diagnosis of a stellate lesion can be made only with the help of histologic examination, the preoperative mammorgraphic differential diagnosis can be highly accurate. The differential diagnostic problem is between malignant tumors (scirrhous carcinoma), on the one hand, and traumatic fat necrosis as well as radial scars on the other hand

  19. THE "MAN INCULTS" AND PACIFICATION DURING BRAZILIAN EMPIRE: A MODEL OF HISTORICAL INTERPRETATION BUILT FROM THE APPROACH TO HUMAN RIGHTS

    Directory of Open Access Journals (Sweden)

    José Ernesto Pimentel Filho

    2011-06-01

    Full Text Available The construction of peace in the Empire of Brazil was one of the forms of public space’s monopoly by the dominant sectors of the Empire Society. On the one hand, the Empire built an urban sociability based on patriarchal relations. On the other hand, the Empire was struggling against all forms of disorder and social deviance, as in a diptych image. The center of that peace was the capitals of the provinces. We he discuss here how to construct a model for approaching a mentality of combating crime in rural areas according to the patriarchal minds during the nineteenth century in Brazil. For it, the case of Ceara has been chosen. A historical hermeneutic might been applied for understanding the role of poor white men in social life of the Empire of Brazil. We observe that the education, when associated with the moral, has been seen as able to modify any violent behavior and able shaping the individual attitude before the justice and punishment policy. Discrimination and stereotypes are part of our interpretation as contribution to a debate on Human Rights in the history of Brazil.

  20. Modeling of plasma distortions by laser-induced ablation spectroscopy (LIAS) and implications for the interpretation of LIAS measurements

    Science.gov (United States)

    Tokar, M. Z.; Gierse, N.; Philipps, V.; Samm, U.

    2015-09-01

    For the interpretation of the line radiation observed from laser induced ablation spectroscopy (LIAS) such parameters as the density and temperature of electrons within very compact clouds of atoms and singly charged ions of ablated material have to be known. Compared to the local plasma conditions prior to the laser pulse, these can be strongly changed during LIAS since new electrons are generated by the ionisation of particles ejected from the irradiated target. Because of their transience and spatial inhomogeneity it is technically difficult to measure disturbances induced in the plasma by LIAS. To overcome this uncertainty a numerical model has been elaborated, providing a self-consistent description for the spreading of ablated particles and accompanying modifications in the plasma. The results of calculations for LIAS performed on carbon-containing targets in Ohmic and additionally heated discharges in the tokamak TEXTOR are presented. Due to the increase in the electron density the ‘ionisation per photon’ ratio, S/XB factor, is significantly enhanced compared to unperturbed plasma conditions. The impact of the amount of material ablated and of the plasma conditions before LIAS on the level of the S/XB-enhancement is investigated.

  1. Backward transfer entropy: Informational measure for detecting hidden Markov models and its interpretations in thermodynamics, gambling and causality

    Science.gov (United States)

    Ito, Sosuke

    2016-01-01

    The transfer entropy is a well-established measure of information flow, which quantifies directed influence between two stochastic time series and has been shown to be useful in a variety fields of science. Here we introduce the transfer entropy of the backward time series called the backward transfer entropy, and show that the backward transfer entropy quantifies how far it is from dynamics to a hidden Markov model. Furthermore, we discuss physical interpretations of the backward transfer entropy in completely different settings of thermodynamics for information processing and the gambling with side information. In both settings of thermodynamics and the gambling, the backward transfer entropy characterizes a possible loss of some benefit, where the conventional transfer entropy characterizes a possible benefit. Our result implies the deep connection between thermodynamics and the gambling in the presence of information flow, and that the backward transfer entropy would be useful as a novel measure of information flow in nonequilibrium thermodynamics, biochemical sciences, economics and statistics. PMID:27833120

  2. Using occupancy models to accommodate uncertainty in the interpretation of aerial photograph data: status of beaver in Central Oregon, USA

    Science.gov (United States)

    Pearl, Christopher A.; Adams, Michael J.; Haggerty, Patricia K.; Urban, Leslie

    2015-01-01

    Beavers (Castor canadensis) influence habitat for many species and pose challenges in developed landscapes. They are increasingly viewed as a cost-efficient means of riparian habitat restoration and water storage. Still, information on their status is rare, particularly in western North America. We used aerial photography to evaluate changes in beaver occupancy between 1942–1968 and 2009 in upper portions of 2 large watersheds in Oregon, USA. We used multiple observers and occupancy modeling to account for bias related to photo quality, observers, and imperfect detection of beaver impoundments. Our analysis suggested a slightly higher rate of beaver occupancy in the upper Deschutes than the upper Klamath basin. We found weak evidence for beaver increases in the west and declines in eastern parts of the study area. Our study presents a method for dealing with observer variation in photo interpretation and provides the first assessment of the extent of beaver influence in 2 basins with major water-use challenges. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

  3. Interpretation as doing

    DEFF Research Database (Denmark)

    Majgaard Krarup, Jonna

    2008-01-01

    The intent of the paper is to address and discuss relationships between the aesthetic perception and interpretation of contemporary landscape architecture. I will try to do this by setting up a cross-disciplinary perspective that looks into themes from the contemporary art scene and aesthetic...... theories, and relate them to observations in contemporary landscape architecture. It is my premise that investigating the relationship between modes of aesthetic perception and examples in contemporary art, and landscape architecture, will enable us to better understand characteristics of a contemporary...... concept of landscape and design in landscape architecture, and hereby address the question of how interpretation might be processed. It is also my premise that a key point in this is the interplay between different sensory experiences of both material and non-material aspects...

  4. An Interpreter's Interpretation: Sign Language Interpreters' View of Musculoskeletal Disorders

    National Research Council Canada - National Science Library

    Johnson, William L

    2003-01-01

    Sign language interpreters are at increased risk for musculoskeletal disorders. This study used content analysis to obtain detailed information about these disorders from the interpreters' point of view...

  5. A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

    Science.gov (United States)

    Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

  6. Interpretation of Ocular Melanin Drug Binding Assays. Alternatives to the Model of Multiple Classes of Independent Sites.

    Science.gov (United States)

    Manzanares, José A; Rimpelä, Anna-Kaisa; Urtti, Arto

    2016-04-04

    Melanin has a high binding affinity for a wide range of drugs. The determination of the melanin binding capacity and its binding affinity are important, e.g., in the determination of the ocular drug distribution, the prediction of drug effects in the eye, and the trans-scleral drug delivery. The binding parameters estimated from a given data set vary significantly when using different isotherms or different nonlinear fitting methods. In this work, the commonly used bi-Langmuir isotherm, which assumes two classes of independent sites, is confronted with the Sips isotherm. Direct, log-log, and Scatchard plots are used, and the interpretation of the binding curves in the latter is critically analyzed. In addition to the goodness of fit, the emphasis is placed on the physical meaning of the binding parameters. The bi-Langmuir model imposes a bimodal distribution of binding energies for the sites on the melanin granules, but the actual distribution is most likely continuous and unimodal, as assumed by the Sips isotherm. Hence, the latter describes more accurately the distribution of binding energies and also the experimental results of melanin binding to drugs and metal ions. Simulations are used to show that the existence of two classes of sites cannot be confirmed on the sole basis of the shape of the binding curve in the Scatchard plot, and that serious doubts may appear on the meaning of the binding parameters of the bi-Langmuir model. Experimental results of melanin binding to chloroquine and metoprolol are used to illustrate the importance of the choice of the binding isotherm and of the method used to evaluate the binding parameters.

  7. Microkinetic interpretation of HDS/HYDO selectivity of the transformation of a model FCC gasoline over transition metal sulfides

    Energy Technology Data Exchange (ETDEWEB)

    Daudin, A. [UMR CNRS 6503, Catalyse en Chimie Organique, Universite de Poitiers, Faculte des Sciences Fondamentales et Appliquees, 40 Avenue du Recteur Pineau, 86022 Poitiers Cedex (France); IFP-Lyon, Direction Catalyse et Separation, BP 3, 69390 Vernaison (France); Lamic, A.F.; Perot, G.; Brunet, S. [UMR CNRS 6503, Catalyse en Chimie Organique, Universite de Poitiers, Faculte des Sciences Fondamentales et Appliquees, 40 Avenue du Recteur Pineau, 86022 Poitiers Cedex (France); Raybaud, P. [IFP, Direction Chimie et Physico-Chimie Appliquees, 1-4 Av. de Bois Preau, 92858 Rueil Malmaison (France); IFP-Lyon, Direction Catalyse et Separation, BP 3, 69390 Vernaison (France); Bouchy, C. [IFP-Lyon, Direction Catalyse et Separation, BP 3, 69390 Vernaison (France)

    2008-01-15

    The conversion of a model FCC gasoline (composed of 2-methylthiophene (2MT), 2,3-dimethylbut-2-ene (23DMDB2N) and orthoxylene in n-heptane) under realistic hydrodesulfurization (HDS) conditions was investigated over a series of transition monometallic sulfides (Ni{sub 3}S{sub 2}, PdS, Co{sub 9}S{sub 8}, Rh{sub 2}S{sub 3}, RuS{sub 2}, PtS and MoS{sub 2}) and unsupported transition bimetallic sulfide catalysts (NiMoS and CoMoS). The results reveal for the first time that a volcano curve relationship exists between the ab initio calculated sulfur-metal bond energy, E(MS), descriptor of bulk TMS and their activities in olefin hydrogenation and in alkylthiophene desulfurization measured simultaneously. In particular, Rh{sub 2}S{sub 3} with an intermediate sulfur-metal bond energy of 119 kJ/mol is the most active catalyst in both case hydrogenation of the olefin and in HDS of a sulfur compound. Furthermore, the HDS/HYDO selectivity which is the most important parameter in the deep HDS of gasoline, presents a maximum for the NiMoS catalyst with E(MS) of 128 kJ/mol. A microkinetic model based on Broensted-Evans-Polanyi relationships and the competitive adsorption of the sulfur molecule and alkene on the catalytic site is proposed to give a rational interpretation of the experimental catalytic results. (author)

  8. High-Resolution Modeling of ENSO-Induced Precipitation in the Tropical Andes: Implications for Proxy Interpretation.

    Science.gov (United States)

    Kiefer, J.; Karamperidou, C.

    2017-12-01

    Clastic sediment flux into high-elevation Andean lakes is controlled by glacial processes and soil erosion caused by high precipitation events, making these lakes suitable archives of past climate. To wit, sediment records from Laguna Pallcacocha in Ecuador have been interpreted as proxies of ENSO variability, owing to increased precipitation in the greater region during El Niño events. However, the location of the lake's watershed, the presence of glaciers, and the different impacts of ENSO on precipitation in the eastern vs western Andes have challenged the suitability of the Pallcacocha record as an ENSO proxy. Here, we employ WRF, a high-resolution regional mesoscale weather prediction model, to investigate the circulation dynamics, sources of moisture, and resulting precipitation response in the L. Pallcacocha region during different flavors of El Niño and La Niña events, and in the presence or absence of ice caps. In patricular, we investigate Eastern Pacific (EP), Central Pacific (CP), coastal El Niño, and La Niña events. We validate the model simulations against spatially interpolated station measurements and reanalysis data. We find that during EP events, moisture is primarily advected from the Pacific, whereas during CP events, moisture primarily originates from the Atlantic. More moisture is available during EP events, which implies higher precipitation rates. Furthermore, we find that precipitation during EP events is mostly non-convective in contrast to primarily convective precipitation during CP events. Finally, a synthesis of the sedimentary record and the EP:CP ratio of accumulated precipitation and specific humidity in the L. Pallcacocha region allows us to assess whether past changes in the relative frequency of the two ENSO flavors may have been recorded in paleoclimate archives in this region.

  9. Interpretation of Microseismicity Observed From Surface and Borehole Seismic Arrays During Hydraulic Fracturing in Shale - Bedding Plane Slip Model

    Science.gov (United States)

    Stanek, F.; Jechumtalova, Z.; Eisner, L.

    2017-12-01

    We present a geomechanical model explaining microseismicity induced by hydraulic fracturing in shales developed from many datasets acquired with two most common types of seismic monitoring arrays, surface and dual-borehole arrays. The geomechanical model explains the observed source mechanisms and locations of induced events from two stimulated shale reservoirs. We observe shear dip-slip source mechanisms with nodal planes aligned with location trends. We show that such seismicity can be explained as a shearing along bedding planes caused by aseismic opening of vertical hydraulic fractures. The source mechanism inversion was applied only to selected high-quality events with sufficient signal-to-noise ratio. We inverted P- and P- and S-wave arrival amplitudes to full-moment tensor and decomposed it to shear, volumetric and compensated linear vector dipole components. We also tested an effect of noise presented in the data to evaluate reliability of non-shear components. The observed seismicity from both surface and downhole monitoring of shale stimulations is very similar. The locations of induced microseismic events are limited to narrow depth intervals and propagate along distinct trend(s) showing fracture propagation in direction of maximum horizontal stress from injection well(s). The source mechanisms have a small non-shear component which can be partly explained as an effect of noise in the data, i.e. events represent shearing on faults. We observe predominantly dip-slip events with a strike of the steeper (almost vertical) nodal plane parallel to the fracture propagation. Therefore the other possible nodal plane is almost horizontal. The rake angles of the observed mechanisms divide these dip-slips into two groups with opposite polarities. It means that we observe opposite movements on the nearly identically oriented faults. Realizing a typical structural weakness of shale in horizontal planes, we interpret observed microseismicity as a result of shearing

  10. Total Productive Maintenance And Role Of Interpretive Structural Modeling And Structural Equation Modeling In Analyzing Barriers In Its Implementation A Literature Review

    Directory of Open Access Journals (Sweden)

    Prasanth S. Poduval

    2015-08-01

    Full Text Available Abstract - The aim of the authors is to present a review of literature of Total Productive Maintenance and the barriers in implementation of Total Productive Maintenance TPM. The paper begins with a brief description of TPM and the barriers in implementation of TPM. Interpretive Structural Modeling ISM and its role in analyzing the barriers in TPM implementation is explained in brief. Applications of ISM in analyzing issues in various fields are highlighted with special emphasis on TPM. The paper moves on to introduction to Structural Equation Modeling SEM and its role in validating ISM in analyzing barriers in implementation of TPM. The paper concludes with a gap analysis from the current literature research that can be carried out and expected outcomes from the proposed research.

  11. Three-Dimensional Human iPSC-Derived Artificial Skeletal Muscles Model Muscular Dystrophies and Enable Multilineage Tissue Engineering

    Directory of Open Access Journals (Sweden)

    Sara Martina Maffioletti

    2018-04-01

    Full Text Available Summary: Generating human skeletal muscle models is instrumental for investigating muscle pathology and therapy. Here, we report the generation of three-dimensional (3D artificial skeletal muscle tissue from human pluripotent stem cells, including induced pluripotent stem cells (iPSCs from patients with Duchenne, limb-girdle, and congenital muscular dystrophies. 3D skeletal myogenic differentiation of pluripotent cells was induced within hydrogels under tension to provide myofiber alignment. Artificial muscles recapitulated characteristics of human skeletal muscle tissue and could be implanted into immunodeficient mice. Pathological cellular hallmarks of incurable forms of severe muscular dystrophy could be modeled with high fidelity using this 3D platform. Finally, we show generation of fully human iPSC-derived, complex, multilineage muscle models containing key isogenic cellular constituents of skeletal muscle, including vascular endothelial cells, pericytes, and motor neurons. These results lay the foundation for a human skeletal muscle organoid-like platform for disease modeling, regenerative medicine, and therapy development. : Maffioletti et al. generate human 3D artificial skeletal muscles from healthy donors and patient-specific pluripotent stem cells. These human artificial muscles accurately model severe genetic muscle diseases. They can be engineered to include other cell types present in skeletal muscle, such as vascular cells and motor neurons. Keywords: skeletal muscle, pluripotent stem cells, iPS cells, myogenic differentiation, tissue engineering, disease modeling, muscular dystrophy, organoids

  12. Interpretation of seismic section by acoustic modeling. Study of large amplitude events; Hadoba modeling ni yoru jishin tansa danmen no kaishaku. Kyoshinhaba event ni taisuru kosatsu

    Energy Technology Data Exchange (ETDEWEB)

    Tamagawa, T.; Matsuoka, T.; Sato, T. [Japan Petroleum Exploration Corp., Tokyo (Japan); Minegishi, M.; Tsuru, T. [Japan National Oil Corp., Tokyo (Japan)

    1996-05-01

    A large amplitude event difficult to interpret was discovered in the overlap section in offset data beyond 10km targeting at deep structures, and the event was examined. A wave field modeling was carried out by use of a simplified synclinal structure model because it had been estimated that the large amplitude event had something to do with a synclinal structure. A pseudospectral program was used for modeling the wave field on the assumption that the synclinal structure model would be an acoustic body and that the surface would contain free boundaries and multiple reflection. It was found as the result that a discontinuous large amplitude event is mapped out in the synclinal part of the overlap section when a far trace is applied beyond the structure during a CMP overlap process. This can be attributed to the concentration of energy produced by multiple reflection in the synclinal part and by the reflection waves beyond the critical angle. Accordingly, it is possible that phenomena similar to those encountered in the modeling process are emerging during actual observation. 2 refs., 8 figs.

  13. Adaptive learning in a compartmental model of visual cortex - how feedback enables stable category learning and refinement

    Directory of Open Access Journals (Sweden)

    Georg eLayher

    2014-12-01

    Full Text Available The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, but both belong to the category of felines. In other words, tigers and leopards are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in the computational neurosciences. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of (sub- category representations. We demonstrate the temporal evolution of such learning and show how the approach successully establishes category and subcategory

  14. A Framework for Interpreting Type I Error Rates from a Product-Term Model of Interaction Applied to Quantitative Traits.

    Science.gov (United States)

    Rao, Tara J; Province, Michael A

    2016-02-01

    Adequate control of type I error rates will be necessary in the increasing genome-wide search for interactive effects on complex traits. After observing unexpected variability in type I error rates from SNP-by-genome interaction scans, we sought to characterize this variability and test the ability of heteroskedasticity-consistent standard errors to correct it. We performed 81 SNP-by-genome interaction scans using a product-term model on quantitative traits in a sample of 1,053 unrelated European Americans from the NHLBI Family Heart Study, and additional scans on five simulated datasets. We found that the interaction-term genomic inflation factor (lambda) showed inflation and deflation that varied with sample size and allele frequency; that similar lambda variation occurred in the absence of population substructure; and that lambda was strongly related to heteroskedasticity but not to minor non-normality of phenotypes. Heteroskedasticity-consistent standard errors narrowed the range of lambda, with HC3 outperforming HC0, but in individual scans tended to create new P-value outliers related to sparse two-locus genotype classes. We explain the lambda variation as a result of non-independence of test statistics coupled with stochastic biases in test statistics due to a failure of the test to reach asymptotic properties. We propose that one way to interpret lambda is by comparison to an empirical distribution generated from data simulated under the null hypothesis and without population substructure. We further conclude that the interaction-term lambda should not be used to adjust test statistics and that heteroskedasticity-consistent standard errors come with limitations that may outweigh their benefits in this setting. © 2015 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.

  15. Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

    Energy Technology Data Exchange (ETDEWEB)

    Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

    2015-07-14

    The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project

  16. High-order feature-based mixture models of classification learning predict individual learning curves and enable personalized teaching.

    Science.gov (United States)

    Cohen, Yarden; Schneidman, Elad

    2013-01-08

    Pattern classification learning tasks are commonly used to explore learning strategies in human subjects. The universal and individual traits of learning such tasks reflect our cognitive abilities and have been of interest both psychophysically and clinically. From a computational perspective, these tasks are hard, because the number of patterns and rules one could consider even in simple cases is exponentially large. Thus, when we learn to classify we must use simplifying assumptions and generalize. Studies of human behavior in probabilistic learning tasks have focused on rules in which pattern cues are independent, and also described individual behavior in terms of simple, single-cue, feature-based models. Here, we conducted psychophysical experiments in which people learned to classify binary sequences according to deterministic rules of different complexity, including high-order, multicue-dependent rules. We show that human performance on such tasks is very diverse, but that a class of reinforcement learning-like models that use a mixture of features captures individual learning behavior surprisingly well. These models reflect the important role of subjects' priors, and their reliance on high-order features even when learning a low-order rule. Further, we show that these models predict future individual answers to a high degree of accuracy. We then use these models to build personally optimized teaching sessions and boost learning.

  17. Interpretation training influences memory for prior interpretations

    NARCIS (Netherlands)

    Salemink, E.; Hertel, P.; Mackintosh, B.

    2010-01-01

    Anxiety is associated with memory biases when the initial interpretation of the event is taken into account. This experiment examined whether modification of interpretive bias retroactively affects memory for prior events and their initial interpretation. Before training, participants imagined

  18. Toward a Conceptual Model for Social Mechanisms Enabling Knowledge Sharing: Dynamic Relationships among Three Dimensions of Social Capital

    Science.gov (United States)

    Jo, Sung Jun

    2008-01-01

    Knowledge sharing is important because individual knowledge is not transformed into organizational knowledge until it is shared. The conceptual model presents how social factors create the conditions for effective knowledge sharing. It illustrates how three dimensions of social capital impact with each other and with knowledge sharing. Social…

  19. The chain of care enabling tPA treatment in acute ischemic stroke : a comprehensive review of organisational models

    NARCIS (Netherlands)

    Lahr, Maarten M. H.; Luijckx, Gert-Jan; Vroomen, Patrick; van der Zee, D.J.; Buskens, Erik

    Protracted and partial implementation of treatment with intravenous tissue plasminogen activator (tPA) within 4.5 h after acute stroke onset results in potentially eligible patients not receiving optimal treatment. The goal of this study was to review the performance of various organisational models

  20. Representations and Techniques for 3D Object Recognition and Scene Interpretation

    CERN Document Server

    Hoiem, Derek

    2011-01-01

    One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physi

  1. Enabling sense-making for patients receiving outpatient palliative treatment: A participatory action research driven model for person-centered communication.

    Science.gov (United States)

    Öhlén, J; Carlsson, G; Jepsen, A; Lindberg, I; Friberg, F

    2016-06-01

    In clinical palliative cancer care, the diversity of patient concerns over time makes information provision a critical issue, the demands of information-seeking patients presenting a challenge to both the communicative and organizational skills of the health provider. This study puts forward a practice model for communication between patients, their family members, and professional health providers during ongoing palliative chemotherapy; a model which supports the providers in enabling person-centered communication. A constant comparative analysis adapted to participatory action research was applied. The model was developed step-wise in three interrelated cycles, with results from previous studies from palliative cancer care processed in relation to professional health providers' experience-based clinical knowledge. In doing this, focus group discussions were carried out with providers and patients to develop and revise the model. The Enabling Sense Making model for person-centered communication gave rise to three domains (which are also the major communicative actors in palliative care): the patient, the family, and the provider. These actors were placed in the context of a communicative arena. The three respective domains were built up in different layers discriminating between significant aspects of person-centered communication, from the manifest that is most usually explicated in dialogues, to the latent that tends to be implicitly mediated. The model intends to facilitate timely reorientation of care from curative treatment or rehabilitation to palliation, as well as the introduction of appropriate palliative interventions over time during palliative phases. In this way the model is to be regarded a frame for directing the awareness of the professionals, which focuses on how to communicate and how to consider the patient's way of reasoning. The model could be used as a complement to other strategic initiatives for the advancement of palliative care

  2. Investigating a model for lecturer training that enables lecturers to plan and carry out meaningful e-learning activities

    DEFF Research Database (Denmark)

    Kjær, Christopher; Hansen, Pernille Stenkil; Christensen, Inger-Marie F.

    2014-01-01

    This paper reports on the effect of a lecturer training model in the shape of an e-learning project based on research on adult and work-based learning. A survey was conducted to explore participants’ learning experiences. Findings show high overall satisfaction, motivation and engagement. Suggest....... Suggestions for improvement include better integration of the e-learning project with other lecturer training components, supporting participants in formulating the e-learning project and providing additional opportunities for reflection and feedback....

  3. Translation, Interpreting and Lexicography

    DEFF Research Database (Denmark)

    Dam, Helle Vrønning; Tarp, Sven

    2018-01-01

    Translation, interpreting and lexicography represent three separate areas of human activity, each of them with its own theories, models and methods and, hence, with its own disciplinary underpinnings. At the same time, all three disciplines are characterized by a marked interdisciplinary dimension...... in the sense that their practice fields are typically ‘about something else’. Translators may, for example, be called upon to translate medical texts, and interpreters may be assigned to work on medical speeches. Similarly, practical lexicography may produce medical dictionaries. In this perspective, the three...

  4. A non-parametric mixture model for genome-enabled prediction of genetic value for a quantitative trait.

    Science.gov (United States)

    Gianola, Daniel; Wu, Xiao-Lin; Manfredi, Eduardo; Simianer, Henner

    2010-10-01

    A Bayesian nonparametric form of regression based on Dirichlet process priors is adapted to the analysis of quantitative traits possibly affected by cryptic forms of gene action, and to the context of SNP-assisted genomic selection, where the main objective is to predict a genomic signal on phenotype. The procedure clusters unknown genotypes into groups with distinct genetic values, but in a setting in which the number of clusters is unknown a priori, so that standard methods for finite mixture analysis do not work. The central assumption is that genetic effects follow an unknown distribution with some "baseline" family, which is a normal process in the cases considered here. A Bayesian analysis based on the Gibbs sampler produces estimates of the number of clusters, posterior means of genetic effects, a measure of credibility in the baseline distribution, as well as estimates of parameters of the latter. The procedure is illustrated with a simulation representing two populations. In the first one, there are 3 unknown QTL, with additive, dominance and epistatic effects; in the second, there are 10 QTL with additive, dominance and additive × additive epistatic effects. In the two populations, baseline parameters are inferred correctly. The Dirichlet process model infers the number of unique genetic values correctly in the first population, but it produces an understatement in the second one; here, the true number of clusters is over 900, and the model gives a posterior mean estimate of about 140, probably because more replication of genotypes is needed for correct inference. The impact on inferences of the prior distribution of a key parameter (M), and of the extent of replication, was examined via an analysis of mean body weight in 192 paternal half-sib families of broiler chickens, where each sire was genotyped for nearly 7,000 SNPs. In this small sample, it was found that inference about the number of clusters was affected by the prior distribution of M. For a

  5. Reduced-order modeling (ROM) for simulation and optimization powerful algorithms as key enablers for scientific computing

    CERN Document Server

    Milde, Anja; Volkwein, Stefan

    2018-01-01

    This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box algorithmic solutions for scientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for electrochemical processes. The target audience comprises research experts and practitioners in the field of simulation, optimization and control, but the book may also be beneficial for graduate students alike. .

  6. Immunoassay for Capsular Antigen of Bacillus anthracis Enables Rapid Diagnosis in a Rabbit Model of Inhalational Anthrax.

    Directory of Open Access Journals (Sweden)

    Marcellene A Gates-Hollingsworth

    Full Text Available Inhalational anthrax is a serious biothreat. Effective antibiotic treatment of inhalational anthrax requires early diagnosis; the further the disease has progressed, the less the likelihood for cure. Current means for diagnosis such as blood culture require several days to a result and require advanced laboratory infrastructure. An alternative approach to diagnosis is detection of a Bacillus anthracis antigen that is shed into blood and can be detected by rapid immunoassay. The goal of the study was to evaluate detection of poly-γ-D-glutamic acid (PGA, the capsular antigen of B. anthracis, as a biomarker surrogate for blood culture in a rabbit model of inhalational anthrax. The mean time to a positive blood culture was 26 ± 5.7 h (mean ± standard deviation, whereas the mean time to a positive ELISA was 22 ± 4.2 h; P = 0.005 in comparison with blood culture. A lateral flow immunoassay was constructed for detection of PGA in plasma at concentrations of less than 1 ng PGA/ml. Use of the lateral flow immunoassay for detection of PGA in the rabbit model found that antigen was detected somewhat earlier than the earliest time point at which the blood culture became positive. The low cost, ease of use, and rapid time to result of the lateral flow immunoassay format make an immunoassay for PGA a viable surrogate for blood culture for detection of infection in individuals who have a likelihood of exposure to B. anthracis.

  7. Immunoassay for Capsular Antigen of Bacillus anthracis Enables Rapid Diagnosis in a Rabbit Model of Inhalational Anthrax.

    Science.gov (United States)

    Gates-Hollingsworth, Marcellene A; Perry, Mark R; Chen, Hongjing; Needham, James; Houghton, Raymond L; Raychaudhuri, Syamal; Hubbard, Mark A; Kozel, Thomas R

    2015-01-01

    Inhalational anthrax is a serious biothreat. Effective antibiotic treatment of inhalational anthrax requires early diagnosis; the further the disease has progressed, the less the likelihood for cure. Current means for diagnosis such as blood culture require several days to a result and require advanced laboratory infrastructure. An alternative approach to diagnosis is detection of a Bacillus anthracis antigen that is shed into blood and can be detected by rapid immunoassay. The goal of the study was to evaluate detection of poly-γ-D-glutamic acid (PGA), the capsular antigen of B. anthracis, as a biomarker surrogate for blood culture in a rabbit model of inhalational anthrax. The mean time to a positive blood culture was 26 ± 5.7 h (mean ± standard deviation), whereas the mean time to a positive ELISA was 22 ± 4.2 h; P = 0.005 in comparison with blood culture. A lateral flow immunoassay was constructed for detection of PGA in plasma at concentrations of less than 1 ng PGA/ml. Use of the lateral flow immunoassay for detection of PGA in the rabbit model found that antigen was detected somewhat earlier than the earliest time point at which the blood culture became positive. The low cost, ease of use, and rapid time to result of the lateral flow immunoassay format make an immunoassay for PGA a viable surrogate for blood culture for detection of infection in individuals who have a likelihood of exposure to B. anthracis.

  8. Identification of Value Proposition and Development of Innovative Business Models for Demand Response Products and Services Enabled by the DR-BOB Solution

    Directory of Open Access Journals (Sweden)

    Mario Sisinni

    2017-10-01

    Full Text Available The work presented is the result of an ongoing European H2020 project entitled DR-BOB Demand Response in Blocks of Buildings (DR-BOB that seeks to integrate existing technologies to create a scalable solution for Demand Response (DR in blocks of buildings. In most EU countries, DR programs are currently limited to the industrial sector and to direct asset control. The DR-BOB solution extends applicability to the building sector, providing predictive building management in blocks of buildings, enabling facilities managers to respond to implicit and explicit DR schemes, and enabling the aggregation of the DR potential of many blocks of buildings for use in demand response markets. The solution consists of three main components: the Local Energy Manager (LEM, which adds intelligence and provides the capacity for predictive building management in blocks of buildings, a Consumer Portal (CP to enable building managers and building occupants to interact with the system and be engaged in demand response operations, and a Decentralized Energy Management System (DEMS®, Siemens plc, Nottingham, England, UK, which enables the aggregation of the DR potential of many blocks of buildings, thus allowing participation in incentive-based demand response with or without an aggregator. The paper reports the key results around Business Modelling development for demand response products and services enabled by the DR-BOB solution. The scope is threefold: (1 illustrate how the functionality of the demand response solution can provide value proposition to underpin its exploitation by four specific customer segments, namely aggregators and three types of Owners of Blocks of Buildings in different market conditions, (2 explore key aspects of the Business Model from the point of view of a demand response solution provider, in particular around most the suitable revenue stream and key partnership, and (3 assess the importance of key variables such as market maturity, user

  9. Is the Polder Model Good for the Economy?: A New Interpretation of Dutch Economic and Social History

    Directory of Open Access Journals (Sweden)

    Karel Davids

    2014-03-01

    Full Text Available The book Nederland en het poldermodel [The Netherlands and the Polder Model] is a commendable effort to present a new, theory-informed interpretation of the economic and social history of the Netherlands of the last thousand years. However, this review questions the supposed causal relationship between civil society (‘polder model’ and economic growth. The authors assume that economic growth emanates from a vibrant civil society and that likewise economic decline coincides with a weakening of civil society. Upon closer inspection however, their concepts seem to be imperfectly related to the theories they claim to use as inspiration. Thesupposed waning of civil society after 1670 and after 1815 is not substantiated by historical facts either. Their thesis would have benefited greatly from a comparative analysis, both spatially and in time. The rather haphazard use of the term ‘civil society’ precludes convincing conclusions over time, while an international perspective is lacking altogether – a sadly missed opportunity.Is het poldermodel goed voor de economie? Een nieuwe interpretatie van de Nederlandse economische en sociale geschiedenisHet boek Nederland en het poldermodel is een lovenswaardige poging om een nieuwe, op theoretische basis geschoeide interpretatie van de sociale en economische geschiedenis van Nederland van de laatste duizend jaar te presenteren. Deze bijdrage stelt echter vragen bij het veronderstelde causale verband tussen ‘civil society’ (het poldermodel en economische groei. De auteurs nemen aan dat economische groei optreedt als een civil society sterk is en dat omgekeerd economisch verval zich voordoet als een civil society verzwakt. Bij nader inzien blijken hun concepten niet goed te sporen met de theorieën die hen tot inspiratie dienen. De veronderstelde kwijnende civil society na 1670 en na 1815 is ook niet op historische feiten gebaseerd. Hun stelling zou aan kracht hebben gewonnen indien zij een

  10. Integrated management model. Methodology and software-enabled tood designed to assist a utility in developing a station-wide optimization

    International Nuclear Information System (INIS)

    Llovet, R.; Ibanez, R.; Woodcock, J.

    2005-01-01

    A key concern for utilities today is optimizing station aging and realibility management activities in a manner that maximizes the value of those activities withing an affordable budget. The Westinghouse Proactive Asset Management Model is a methodology and software-enabled tood designed to assist a utility in developing a station-wide optimization of those activities. The process and tool support the development of an optimized, station-wide plan for inspection, testing, maintenance, repaor and replacement of aging components. The optimization identifies the benefit and optimal timing of those activities based on minimizing unplanned outage costs (avoided costs) and maximizing station Net Present Value. (Author)

  11. Some feature of interpretation of tension single pulsed electromagnetic field of the Earth to create the model parameter fields physical properties

    Directory of Open Access Journals (Sweden)

    Mokritskaya T.P.

    2014-12-01

    Full Text Available Stochastic analysis of the results of different methods of obtaining and processing of information allows us to solve problems on a qualitatively different level. This is important when creating complex earth models and fields of its parameters, particularly the physical properties. Application of remote sensing methods (geophysical investigations with the registration of a single pulse intensity of the electromagnetic field of the Earth (EIEMPZ seismic profiling, is expanding. Interesting results of the joint interpretation of the results of geophysical and laboratory studies of physical soil. Interesting results of the joint interpretation of the results of geophysical and laboratory studies of physical soil. For the first time a methodology for assessing the state of the soil [3] applied for a joint interpretation of materials determine the field strength EMPZ, seismic profiling, and laboratory techniques. This has allowed to characterize the state of the geological environment and to build a model of inhomogeneous density distribution of fractured rocks at depth. In this paper we made a mathematical analysis of the results of research and talus deposits eluvial clay Taurian series, studied at one of the construction sites southern coast at a depth of 12.0 -25.0 m. Methods of statistical analysis, assessment of homogeneity and symmetrically distributed, rank correlation and multiple regression analysis described in [3]. The analysis of the spatial distribution of areas extrem value of EMPZ, heterogeneity of seismic rigidity. Statistical characteristics of indicators of physical properties reflect the genetic characteristics of the formation and the current state of silty-clay sediments of different genesis.It is proved that the regression model can be applied to interpret the state of the array in the construction of geodynamic model. It is established that the creation of forward-looking (dynamic models for the distribution of the physical

  12. An evolutionary game theoretical model shows the limitations of the additive partitioning method for interpreting biodiversity experiments

    NARCIS (Netherlands)

    Vermeulen, Peter J.; Ruijven, van Jasper; Anten, Niels P.R.; Werf, van der Wopke; Satake, Akiko

    2017-01-01

    1.The relationship between diversity and ecosystem functioning is often analysed by partitioning the change in species performance in mixtures into a complementarity effect (CE) and a selection effect (SE). There is continuing ambiguity in the literature on the interpretation of these effects,

  13. Statistical analysis of time-resolved emission from ensembles of semiconductor quantum dots: interpretations of exponantial decay models

    NARCIS (Netherlands)

    van Driel, A.F.; Nikolaev, I.; Vergeer, P.; Lodahl, P.; Vanmaekelbergh, D.; Vos, Willem L.

    2007-01-01

    We present a statistical analysis of time-resolved spontaneous emission decay curves from ensembles of emitters, such as semiconductor quantum dots, with the aim of interpreting ubiquitous non-single-exponential decay. Contrary to what is widely assumed, the density of excited emitters and the

  14. Basic skills in a complex task: A graphical model relating memory and lexical retrieval to simultaneous interpreting.

    NARCIS (Netherlands)

    Christoffels, I.K.; de Gtoor, A.M.B.; Waldorp, L.J.

    2003-01-01

    Simultaneous interpreting (SI) is a complex skill, where language comprehension and production take place at the same time in two different languages. In this study we identified some of the basic cognitive skills involved in SI, focusing on the roles of memory and lexical retrieval. We administered

  15. FEA modeling of CMUT with membrane stand-off structures to enable selectable frequency-mode operation.

    Science.gov (United States)

    Eames, Matthew D C; Reck, Theodore J; Kilroy, Joseph P; Hossack, John A

    2011-12-01

    A selectable, dual-frequency, capacitive micro- machined ultrasonic transducer (CMUT) designed for both high-frequency imaging and low-frequency therapeutic effect is presented. A validated finite element analysis (FEA) CMUT model was used to examine the performance of the proposed dual-frequency transducer. CMUT device simulations were used to design a hybrid device incorporating stand-off structures that divide a large, low-frequency membrane into smaller, high-frequency sub-membranes when the membrane is partially collapsed so that the stand-offs contact the substrate. In low-frequency operation, simulations indicated that the peak negative pressure achieved by the hybrid device, when biased by 30.0 VDC and excited by a 2-MHz signal with 30.0 V amplitude, exceeded 190 kPa, which is sufficient for microbubble rupture. Low-frequency mode bandwidth was 93% at a center frequency of 2.1 MHz. In the high-frequency mode of operation, the device was excited by 175 Vdc and 87.5 Vac, which generated a peak negative pressure of 247 kPa. Device center frequency was 44.1 MHz with a - 6-dB fractional bandwidth of 42%.

  16. Assessing the ability of isotope-enabled General Circulation Models to simulate the variability of Iceland water vapor isotopic composition

    Science.gov (United States)

    Erla Sveinbjornsdottir, Arny; Steen-Larsen, Hans Christian; Jonsson, Thorsteinn; Ritter, Francois; Riser, Camilla; Messon-Delmotte, Valerie; Bonne, Jean Louis; Dahl-Jensen, Dorthe

    2014-05-01

    During the fall of 2010 we installed an autonomous water vapor spectroscopy laser (Los Gatos Research analyzer) in a lighthouse on the Southwest coast of Iceland (63.83°N, 21.47°W). Despite initial significant problems with volcanic ash, high wind, and attack of sea gulls, the system has been continuously operational since the end of 2011 with limited down time. The system automatically performs calibration every 2 hours, which results in high accuracy and precision allowing for analysis of the second order parameter, d-excess, in the water vapor. We find a strong linear relationship between d-excess and local relative humidity (RH) when normalized to SST. The observed slope of approximately -45 o/oo/% is similar to theoretical predictions by Merlivat and Jouzel [1979] for smooth surface, but the calculated intercept is significant lower than predicted. Despite this good linear agreement with theoretical calculations, mismatches arise between the simulated seasonal cycle of water vapour isotopic composition using LMDZiso GCM nudged to large-scale winds from atmospheric analyses, and our data. The GCM is not able to capture seasonal variations in local RH, nor seasonal variations in d-excess. Based on daily data, the performance of LMDZiso to resolve day-to-day variability is measured based on the strength of the correlation coefficient between observations and model outputs. This correlation coefficient reaches ~0.8 for surface absolute humidity, but decreases to ~0.6 for δD and ~0.45 d-excess. Moreover, the magnitude of day-to-day humidity variations is also underestimated by LMDZiso, which can explain the underestimated magnitude of isotopic depletion. Finally, the simulated and observed d-excess vs. RH has similar slopes. We conclude that the under-estimation of d-excess variability may partly arise from the poor performance of the humidity simulations.

  17. A New Cyber-enabled Platform for Scale-independent Interoperability of Earth Observations with Hydrologic Models

    Science.gov (United States)

    Rajib, A.; Zhao, L.; Merwade, V.; Shin, J.; Smith, J.; Song, C. X.

    2017-12-01

    Despite the significant potential of remotely sensed earth observations, their application is still not full-fledged in water resources research, management and education. Inconsistent storage structures, data formats and spatial resolution among different platforms/sources of earth observations hinder the use of these data. Available web-services can help bulk data downloading and visualization, but they are not sufficiently tailored to meet the degree of interoperability required for direct application of earth observations in hydrologic modeling at user-defined spatio-temporal scales. Similarly, the least ambiguous way for educators and watershed managers is to instantaneously obtain a time-series at any watershed of interest without spending time and computational resources on data download and post-processing activities. To address this issue, an open access, online platform, named HydroGlobe, is developed that minimizes all these processing tasks and delivers ready-to-use data from different earth observation sources. HydroGlobe can provide spatially-averaged time series of earth observations by using the following inputs: (i) data source, (ii) temporal extent in the form of start/end date, and (iii) geographic units (e.g., grid cell or sub-basin boundary) and extent in the form of GIS shapefile. In its preliminary version, HydroGlobe simultaneously handles five data sources including the surface and root zone soil moisture from SMAP (Soil Moisture Active Passive Mission), actual and potential evapotranspiration from MODIS (Moderate Resolution Imaging Spectroradiometer), and precipitation from GPM (Global Precipitation Measurements). This presentation will demonstrate the HydroGlobe interface and its applicability using few test cases on watersheds from different parts of the globe.

  18. New interpretations based on seismic and modelled well data and their implications for the tectonic evolution of the west Greenland continental margin

    DEFF Research Database (Denmark)

    Mcgregor, E.D.; Nielsen, S.B.; Stephenson, R.A.

    Davis Strait is situated between Baffin Island and Greenland and forms part of a sedimentary basin system, linking Labrador Sea and Baffin Bay, developed during Cretaceous and Palaeocene rifting that culminated in a brief period of sea-floor spreading in the late Palaeocene and Eocene. Seismic...... on and offshore. Subsidence and thermal history has been modelled in four offshore wells, constrained by borehole temperatures and vitrinite reflectance. Offshore reflection profiles have been newly interpreted and show the presence of unconformities at the base mid-Eocene (roughly) and base Quaternary....... The investigated offshore wells penetrate these two unconformities. It has been argued from published interpretations of fission track data and inferred episodes of cooling that onshore topography was created by Neogene uplift. However, all five wells can be satisfactorily modelled without invoking any Neogene...

  19. Enabling scientific workflows in virtual reality

    Science.gov (United States)

    Kreylos, O.; Bawden, G.; Bernardin, T.; Billen, M.I.; Cowgill, E.S.; Gold, R.D.; Hamann, B.; Jadamec, M.; Kellogg, L.H.; Staadt, O.G.; Sumner, D.Y.

    2006-01-01

    To advance research and improve the scientific return on data collection and interpretation efforts in the geosciences, we have developed methods of interactive visualization, with a special focus on immersive virtual reality (VR) environments. Earth sciences employ a strongly visual approach to the measurement and analysis of geologic data due to the spatial and temporal scales over which such data ranges, As observations and simulations increase in size and complexity, the Earth sciences are challenged to manage and interpret increasing amounts of data. Reaping the full intellectual benefits of immersive VR requires us to tailor exploratory approaches to scientific problems. These applications build on the visualization method's strengths, using both 3D perception and interaction with data and models, to take advantage of the skills and training of the geological scientists exploring their data in the VR environment. This interactive approach has enabled us to develop a suite of tools that are adaptable to a range of problems in the geosciences and beyond. Copyright ?? 2008 by the Association for Computing Machinery, Inc.

  20. Interpreting the results of a modified gravity model: examining access to primary health care physicians in five Canadian provinces and territories

    Directory of Open Access Journals (Sweden)

    Crooks Valorie A

    2012-08-01

    Full Text Available Abstract Background Primary health care (PHC encompasses an array of health and social services that focus on preventative, diagnostic, and basic care measures to maintain wellbeing and address illnesses. In Canada, PHC involves the provision of first-contact health care services by providers such as family physicians and general practitioners – collectively referred as PHC physicians here. Ensuring access is a key requirement of effective PHC delivery. This is because having access to PHC has been shown to positively impact a number of health outcomes. Methods We build on recent innovations in measuring potential spatial access to PHC physicians using geographic information systems (GIS by running and then interpreting the findings of a modified gravity model. Elsewhere we have introduced the protocol for this model. In this article we run it for five selected Canadian provinces and territories. Our objectives are to present the results of the modified gravity model in order to: (1 understand how potential spatial access to PHC physicians can be interpreted in these Canadian jurisdictions, and (2 provide guidance regarding how findings of the modified gravity model should be interpreted in other analyses. Results Regarding the first objective, two distinct spatial patterns emerge regarding potential spatial access to PHC physicians in the five selected Canadian provinces: (1 a clear north–south pattern, where southern areas have greater potential spatial access than northern areas; and (2 while gradients of potential spatial access exist in and around urban areas, access outside of densely-to-moderately populated areas is fairly binary. Regarding the second objective, we identify three principles that others can use to interpret the findings of the modified gravity model when used in other research contexts. Conclusions Future applications of the modified gravity model are needed in order to refine the recommendations we provide on

  1. A LabVIEW-based electrical bioimpedance spectroscopic data interpreter (LEBISDI) for biological tissue impedance analysis and equivalent circuit modelling

    KAUST Repository

    Bera, Tushar Kanti

    2016-12-05

    Under an alternating electrical signal, biological tissues produce a complex electrical bioimpedance that is a function of tissue composition and applied signal frequencies. By studying the bioimpedance spectra of biological tissues over a wide range of frequencies, we can noninvasively probe the physiological properties of these tissues to detect possible pathological conditions. Electrical impedance spectroscopy (EIS) can provide the spectra that are needed to calculate impedance parameters within a wide range of frequencies. Before impedance parameters can be calculated and tissue information extracted, impedance spectra should be processed and analyzed by a dedicated software program. National Instruments (NI) Inc. offers LabVIEW, a fast, portable, robust, user-friendly platform for designing dataanalyzing software. We developed a LabVIEW-based electrical bioimpedance spectroscopic data interpreter (LEBISDI) to analyze the electrical impedance spectra for tissue characterization in medical, biomedical and biological applications. Here, we test, calibrate and evaluate the performance of LEBISDI on the impedance data obtained from simulation studies as well as the practical EIS experimentations conducted on electronic circuit element combinations and the biological tissue samples. We analyze the Nyquist plots obtained from the EIS measurements and compare the equivalent circuit parameters calculated by LEBISDI with the corresponding original circuit parameters to assess the accuracy of the program developed. Calibration studies show that LEBISDI not only interpreted the simulated and circuitelement data accurately, but also successfully interpreted tissues impedance data and estimated the capacitive and resistive components produced by the compositions biological cells. Finally, LEBISDI efficiently calculated and analyzed variation in bioimpedance parameters of different tissue compositions, health and temperatures. LEBISDI can also be used for human tissue

  2. Interpretive Media Study and Interpretive Social Science.

    Science.gov (United States)

    Carragee, Kevin M.

    1990-01-01

    Defines the major theoretical influences on interpretive approaches in mass communication, examines the central concepts of these perspectives, and provides a critique of these approaches. States that the adoption of interpretive approaches in mass communication has ignored varied critiques of interpretive social science. Suggests that critical…

  3. Statistical analysis of time-resolved emission from ensembles of semiconductor quantum dots: Interpretation of exponential decay models

    DEFF Research Database (Denmark)

    Van Driel, A.F.; Nikolaev, I.S.; Vergeer, P.

    2007-01-01

    We present a statistical analysis of time-resolved spontaneous emission decay curves from ensembles of emitters, such as semiconductor quantum dots, with the aim of interpreting ubiquitous non-single-exponential decay. Contrary to what is widely assumed, the density of excited emitters and the in......We present a statistical analysis of time-resolved spontaneous emission decay curves from ensembles of emitters, such as semiconductor quantum dots, with the aim of interpreting ubiquitous non-single-exponential decay. Contrary to what is widely assumed, the density of excited emitters...... decay component is multiplied by its radiative decay rate. A central result of our paper is the derivation of the emission decay curve when both radiative and nonradiative decays are independently distributed. In this case, the well-known emission quantum efficiency can no longer be expressed...... by a single number, but is also distributed. We derive a practical description of non-single-exponential emission decay curves in terms of a single distribution of decay rates; the resulting distribution is identified as the distribution of total decay rates weighted with the radiative rates. We apply our...

  4. Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems.

    Science.gov (United States)

    Lomnitz, Jason G; Savageau, Michael A

    2016-01-01

    Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment, and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1) enumeration of the repertoire of model phenotypes, (2) prediction of values for the parameters for any model phenotype, and (3) analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3, and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between three stable states by transient stimulation through one of two input channels: a positive channel that increases the count

  5. Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems

    Science.gov (United States)

    Lomnitz, Jason G.; Savageau, Michael A.

    2016-01-01

    Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment, and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1) enumeration of the repertoire of model phenotypes, (2) prediction of values for the parameters for any model phenotype, and (3) analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3, and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between three stable states by transient stimulation through one of two input channels: a positive channel that increases the count

  6. Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems

    Directory of Open Access Journals (Sweden)

    Jason Gunther Lomnitz

    2016-07-01

    Full Text Available Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1 enumeration of the repertoire of model phenotypes, (2 prediction of values for the parameters for any model phenotype and (3 analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3 and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between 3 stable states by transient stimulation through one of two input channels: a positive channel that increases

  7. Multiscale modeling and experimental interpretation of perovskite oxide materials in thermochemical energy storage and conversion for application in concentrating solar power

    Science.gov (United States)

    Albrecht, Kevin J.

    storage in CSP plants are presented. Comparisons of sweep gas and vacuum pumping reduction as well as hot storage conditions indicate that solar-to-electric efficiencies are higher for sweep gas reduction system at equivalent values of energy storage if the energy parasitics of commercially available devices are considered. However, if vacuum pump efficiency between 15% and 30% can be achieved, the reduction methods will be approximately equal. Reducing condition oxygen partial pressures below 10-3 bar for sweep gas reduction and 10-2 bar for vacuum pumping reduction result in large electrical parasitics, which significantly reduce solar-to-electric efficiency. A model based interpretation of experimental measurements made for perovskite redox cycling using sweep gas in a packed bed is presented. The model indicates that long reduction times for equilibrating perovskites with low oxygen partial pressure sweep gas, compared to reoxidation, are primarily due to the oxygen carrying capacity of high purity sweep gas and not surface kinetic limitations. Therefore, achieving rapid reduction in the limited receiver residence time will be controlled by the quantity of sweep gas introduced. Effective kinetic parameters considering surface reaction and radial particle diffusion are fit to the experimental data. Variable order rate expressions without significant particle radial diffusion limitations are shown to be capable of representing the reduction and oxidation data. Modeling of a particle reduction receiver using continuous flow of perovskite solid and sweep gas in counter-flow configuration has identified issues with managing the oxygen evolved by the solid as well as sweep gas flow rates. Introducing sweep gas quantities necessary for equilibrating the solid with oxygen partial pressures below 10-2 are shown to result in gas phase velocities above the entrainment velocity of 500 um particles. Receiver designs with considerations for gas management are investigated and the

  8. The Influence of Volcanic Eruptions on the Climate of Tropical South America During the Last Millennium in an Isotope-Enabled General Circulation Model

    Science.gov (United States)

    Colose, Christopher M.; LeGrande, Allegra N.; Vuille, Mathias

    2016-01-01

    Currently, little is known on how volcanic eruptions impact large-scale climate phenomena such as South American paleo-intertropical Convergence Zone (ITCZ) position and summer monsoon behavior. In this paper, an analysis of observations and model simulations is employed to assess the influence of large volcanic eruptions on the climate of tropical South America. This problem is first considered for historically recent volcanic episodes for which more observations are available but where fewer events exist and the confounding effects of El Niño-Southern Oscillation (ENSO) lead to inconclusive interpretation of the impact of volcanic eruptions at the continental scale. Therefore, we also examine a greater number of reconstructed volcanic events for the period 850 CE to present that are incorporated into the NASA GISS ModelE2-R simulation of the last millennium. An advantage of this model is its ability to explicitly track water isotopologues throughout the hydrologic cycle and simulating the isotopic imprint following a large eruption. This effectively removes a degree of uncertainty associated with error-prone conversion of isotopic signals into climate variables, and allows for a direct comparison between GISS simulations and paleoclimate proxy records. Our analysis reveals that both precipitation and oxygen isotope variability respond with a distinct seasonal and spatial structure across tropical South America following an eruption. During austral winter, the heavy oxygen isotope in precipitation is enriched, likely due to reduced moisture convergence in the ITCZ domain and reduced rainfall over northern South America. During austral summer, however, more negative values of the precipitation isotopic composition are simulated over Amazonia, despite reductions in rainfall, suggesting that the isotopic response is not a simple function of the "amount effect". During the South American monsoon season, the amplitude of the temperature response to volcanic forcing is

  9. Supplement of: The Influence of Volcanic Eruptions on the Climate of Tropical South America During the Last Millennium in an Isotope-Enabled General Circulation Model

    Science.gov (United States)

    Colose, Christopher; LeGrande, Allegra N.; Vuille, Mathias

    2016-01-01

    Currently, little is known on how volcanic eruptions impact large-scale climate phenomena such as South American paleo-intertropical Convergence Zone (ITCZ) position and summer monsoon behavior. In this paper, an analysis of observations and model simulations is employed to assess the influence of large volcanic eruptions on the climate of tropical South America. This problem is first considered for historically recent volcanic episodes for which more observations are available but where fewer events exist and the confounding effects of El NioSouthern Oscillation (ENSO) lead to inconclusive interpretation of the impact of volcanic eruptions at the continental scale. Therefore, we also examine a greater number of reconstructed volcanic events for the period 850CE to present that are incorporated into the NASA GISS ModelE2-R simulation of the last millennium.An advantage of this model is its ability to explicitly track water isotopologues throughout the hydrologic cycle and simulating the isotopic imprint following a large eruption. This effectively removes a degree of uncertainty associated with error-prone conversion