Energy Technology Data Exchange (ETDEWEB)
Hu, R. [Argonne National Lab. (ANL), Argonne, IL (United States)
2017-09-01
This report documents the initial progress on the reduced-order flow model developments in SAM for thermal stratification and mixing modeling. Two different modeling approaches are pursued. The first one is based on one-dimensional fluid equations with additional terms accounting for the thermal mixing from both flow circulations and turbulent mixing. The second approach is based on three-dimensional coarse-grid CFD approach, in which the full three-dimensional fluid conservation equations are modeled with closure models to account for the effects of turbulence.
Progressive IRP Models for Power Resources Including EPP
Directory of Open Access Journals (Sweden)
Yiping Zhu
2017-01-01
Full Text Available In the view of optimizing regional power supply and demand, the paper makes effective planning scheduling of supply and demand side resources including energy efficiency power plant (EPP, to achieve the target of benefit, cost, and environmental constraints. In order to highlight the characteristics of different supply and demand resources in economic, environmental, and carbon constraints, three planning models with progressive constraints are constructed. Results of three models by the same example show that the best solutions to different models are different. The planning model including EPP has obvious advantages considering pollutant and carbon emission constraints, which confirms the advantages of low cost and emissions of EPP. The construction of progressive IRP models for power resources considering EPP has a certain reference value for guiding the planning and layout of EPP within other power resources and achieving cost and environmental objectives.
Progress in modeling hypersonic turbulent boundary layers
Zeman, Otto
1993-01-01
A good knowledge of the turbulence structure, wall heat transfer, and friction in turbulent boundary layers (TBL) at high speeds is required for the design of hypersonic air breathing airplanes and reentry space vehicles. This work reports on recent progress in the modeling of high speed TBL flows. The specific research goal described here is the development of a second order closure model for zero pressure gradient TBL's for the range of Mach numbers up to hypersonic speeds with arbitrary wall cooling requirements.
Model-based setup assistant for progressive tools
Springer, Robert; Gräler, Manuel; Homberg, Werner; Henke, Christian; Trächtler, Ansgar
2018-05-01
In the field of production systems, globalization and technological progress lead to increasing requirements regarding part quality, delivery time and costs. Hence, today's production is challenged much more than a few years ago: it has to be very flexible and produce economically small batch sizes to satisfy consumer's demands and avoid unnecessary stock. Furthermore, a trend towards increasing functional integration continues to lead to an ongoing miniaturization of sheet metal components. In the industry of electric connectivity for example, the miniaturized connectors are manufactured by progressive tools, which are usually used for very large batches. These tools are installed in mechanical presses and then set up by a technician, who has to manually adjust a wide range of punch-bending operations. Disturbances like material thickness, temperatures, lubrication or tool wear complicate the setup procedure. In prospect of the increasing demand of production flexibility, this time-consuming process has to be handled more and more often. In this paper, a new approach for a model-based setup assistant is proposed as a solution, which is exemplarily applied in combination with a progressive tool. First, progressive tools, more specifically, their setup process is described and based on that, the challenges are pointed out. As a result, a systematic process to set up the machines is introduced. Following, the process is investigated with an FE-Analysis regarding the effects of the disturbances. In the next step, design of experiments is used to systematically develop a regression model of the system's behaviour. This model is integrated within an optimization in order to calculate optimal machine parameters and the following necessary adjustment of the progressive tool due to the disturbances. Finally, the assistant is tested in a production environment and the results are discussed.
A MATHEMATICAL MODELLING APPROACH TO ONE-DAY CRICKET BATTING ORDERS
Directory of Open Access Journals (Sweden)
Matthews Ovens1
2006-12-01
Full Text Available While scoring strategies and player performance in cricket have been studied, there has been little published work about the influence of batting order with respect to One-Day cricket. We apply a mathematical modelling approach to compute efficiently the expected performance (runs distribution of a cricket batting order in an innings. Among other applications, our method enables one to solve for the probability of one team beating another or to find the optimal batting order for a set of 11 players. The influence of defence and bowling ability can be taken into account in a straightforward manner. In this presentation, we outline how we develop our Markov Chain approach to studying the progress of runs for a batting order of non- identical players along the lines of work in baseball modelling by Bukiet et al., 1997. We describe the issues that arise in applying such methods to cricket, discuss ideas for addressing these difficulties and note limitations on modelling batting order for One-Day cricket. By performing our analysis on a selected subset of the possible batting orders, we apply the model to quantify the influence of batting order in a game of One Day cricket using available real-world data for current players
Advanced Fluid Reduced Order Models for Compressible Flow.
Energy Technology Data Exchange (ETDEWEB)
Tezaur, Irina Kalashnikova [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Fike, Jeffrey A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Barone, Matthew F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Maddix, Danielle [Stanford Univ., CA (United States); Mussoni, Erin E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Balajewicz, Maciej [Univ. of Illinois, Urbana-Champaign, IL (United States)
2017-09-01
This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly the POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.
Modeling the self-assembly of ordered nanoporous materials
Energy Technology Data Exchange (ETDEWEB)
Monson, Peter [Univ. of Massachusetts, Amherst, MA (United States); Auerbach, Scott [Univ. of Massachusetts, Amherst, MA (United States)
2017-11-13
This report describes progress on a collaborative project on the multiscale modeling of the assembly processes in the synthesis of nanoporous materials. Such materials are of enormous importance in modern technology with application in the chemical process industries, biomedicine and biotechnology as well as microelectronics. The project focuses on two important classes of materials: i) microporous crystalline materials, such as zeolites, and ii) ordered mesoporous materials. In the first case the pores are part of the crystalline structure, while in the second the structures are amorphous on the atomistic length scale but where surfactant templating gives rise to order on the length scale of 2 - 20 nm. We have developed a modeling framework that encompasses both these kinds of materials. Our models focus on the assembly of corner sharing silica tetrahedra in the presence of structure directing agents. We emphasize a balance between sufficient realism in the models and computational tractibility given the complex many-body phenomena. We use both on-lattice and off-lattice models and the primary computational tools are Monte Carlo simulations with sampling techniques and ensembles appropriate to specific situations. Our modeling approach is the first to capture silica polymerization, nanopore crystallization, and mesopore formation through computer-simulated self assembly.
Coupled Immunological and Biomechanical Model of Emphysema Progression
Directory of Open Access Journals (Sweden)
Mario Ceresa
2018-04-01
Full Text Available Chronic Obstructive Pulmonary Disease (COPD is a disabling respiratory pathology, with a high prevalence and a significant economic and social cost. It is characterized by different clinical phenotypes with different risk profiles. Detecting the correct phenotype, especially for the emphysema subtype, and predicting the risk of major exacerbations are key elements in order to deliver more effective treatments. However, emphysema onset and progression are influenced by a complex interaction between the immune system and the mechanical properties of biological tissue. The former causes chronic inflammation and tissue remodeling. The latter influences the effective resistance or appropriate mechanical response of the lung tissue to repeated breathing cycles. In this work we present a multi-scale model of both aspects, coupling Finite Element (FE and Agent Based (AB techniques that we would like to use to predict the onset and progression of emphysema in patients. The AB part is based on existing biological models of inflammation and immunological response as a set of coupled non-linear differential equations. The FE part simulates the biomechanical effects of repeated strain on the biological tissue. We devise a strategy to couple the discrete biological model at the molecular /cellular level and the biomechanical finite element simulations at the tissue level. We tested our implementation on a public emphysema image database and found that it can indeed simulate the evolution of clinical image biomarkers during disease progression.
A theoretical model to describe progressions and regressions for exercise rehabilitation.
Blanchard, Sam; Glasgow, Phil
2014-08-01
This article aims to describe a new theoretical model to simplify and aid visualisation of the clinical reasoning process involved in progressing a single exercise. Exercise prescription is a core skill for physiotherapists but is an area that is lacking in theoretical models to assist clinicians when designing exercise programs to aid rehabilitation from injury. Historical models of periodization and motor learning theories lack any visual aids to assist clinicians. The concept of the proposed model is that new stimuli can be added or exchanged with other stimuli, either intrinsic or extrinsic to the participant, in order to gradually progress an exercise whilst remaining safe and effective. The proposed model maintains the core skills of physiotherapists by assisting clinical reasoning skills, exercise prescription and goal setting. It is not limited to any one pathology or rehabilitation setting and can adapted by any level of skilled clinician. Copyright © 2014 Elsevier Ltd. All rights reserved.
A Mathematical Modelling Approach to One-Day Cricket Batting Orders
Bukiet, Bruce; Ovens, Matthews
2006-01-01
While scoring strategies and player performance in cricket have been studied, there has been little published work about the influence of batting order with respect to One-Day cricket. We apply a mathematical modelling approach to compute efficiently the expected performance (runs distribution) of a cricket batting order in an innings. Among other applications, our method enables one to solve for the probability of one team beating another or to find the optimal batting order for a set of 11 players. The influence of defence and bowling ability can be taken into account in a straightforward manner. In this presentation, we outline how we develop our Markov Chain approach to studying the progress of runs for a batting order of non- identical players along the lines of work in baseball modelling by Bukiet et al., 1997. We describe the issues that arise in applying such methods to cricket, discuss ideas for addressing these difficulties and note limitations on modelling batting order for One-Day cricket. By performing our analysis on a selected subset of the possible batting orders, we apply the model to quantify the influence of batting order in a game of One Day cricket using available real-world data for current players. Key Points Batting order does effect the expected runs distribution in one-day cricket. One-day cricket has fewer data points than baseball, thus extreme values have greater effect on estimated probabilities. Dismissals rare and probabilities very small by comparison to baseball. Probability distribution for lower order batsmen is potentially skewed due to increased risk taking. Full enumeration of all possible line-ups is impractical using a single average computer. PMID:24357943
Tumor heterogeneity and progression: conceptual foundations for modeling.
Greller, L D; Tobin, F L; Poste, G
1996-01-01
A conceptual foundation for modeling tumor progression, growth, and heterogeneity is presented. The purpose of such models is to aid understanding, test ideas, formulate experiments, and to model cancer 'in machina' to address the dynamic features of tumor cell heterogeneity, progression, and growth. The descriptive capabilities of such an approach provides a consistent language for qualitatively reasoning about tumor behavior. This approach provides a schema for building conceptual models that combine three key phenomenological driving elements: growth, progression, and genetic instability. The growth element encompasses processes contributing to changes in tumor bulk and is distinct from progression per se. The progression element subsumes a broad collection of processes underlying phenotypic progression. The genetics elements represents heritable changes which potentially affect tumor character and behavior. Models, conceptual and mathematical, can be built for different tumor situations by drawing upon the interaction of these three distinct driving elements. These models can be used as tools to explore a diversity of hypotheses concerning dynamic changes in cellular populations during tumor progression, including the generation of intratumor heterogeneity. Such models can also serve to guide experimentation and to gain insight into dynamic aspects of complex tumor behavior.
The Model of Optimum Economic Growth with the Induced Scientific-Technological Progress
Directory of Open Access Journals (Sweden)
Dilenko Viktor A.
2017-07-01
Full Text Available On the basis of the economic dynamics of the Harrod – Domar model, a model of optimum economic growth in line with the induced scientific-technological progress (STP has been built. In order to reflect the induced scientific-technological progress, with this model is proposed to further allocate the income element that is specially used for the investment of innovation activity, implementation of which reduces the capital intensity in development of the discussed economy. For the simplest way of presenting an economic mechanism for the investment of induced STP, analytical solutions of an appropriate task in optimum management have been obtained. Studying these decisions allowed to reveal the characteristics of the impact of parameters of scientific-technological progress and the analyzed economic system on choosing the best trajectory for its evolution. Possible directions for further developing the results presented can be considered the tasks in building and analyzing models of optimum economic growth that implement different investment options for the induced STP, as well as the models in which this investment mechanism is not exogenouslyed, but rather the result of the corresponding economic-mathematical research.
Computation of nonlinear water waves with a high-order Boussinesq model
DEFF Research Database (Denmark)
Fuhrman, David R.; Madsen, Per A.; Bingham, Harry
2005-01-01
Computational highlights from a recently developed high-order Boussinesq model are shown. The model is capable of treating fully nonlinear waves (up to the breaking point) out to dimensionless depths of (wavenumber times depth) kh \\approx 25. Cases considered include the study of short......-crested waves in shallow/deep water, resulting in hexagonal/rectangular surface patterns; crescent waves, resulting from unstable perturbations of plane progressive waves; and highly-nonlinear wave-structure interactions. The emphasis is on physically demanding problems, and in eachcase qualitative and (when...
On nonlinear reduced order modeling
International Nuclear Information System (INIS)
Abdel-Khalik, Hany S.
2011-01-01
When applied to a model that receives n input parameters and predicts m output responses, a reduced order model estimates the variations in the m outputs of the original model resulting from variations in its n inputs. While direct execution of the forward model could provide these variations, reduced order modeling plays an indispensable role for most real-world complex models. This follows because the solutions of complex models are expensive in terms of required computational overhead, thus rendering their repeated execution computationally infeasible. To overcome this problem, reduced order modeling determines a relationship (often referred to as a surrogate model) between the input and output variations that is much cheaper to evaluate than the original model. While it is desirable to seek highly accurate surrogates, the computational overhead becomes quickly intractable especially for high dimensional model, n ≫ 10. In this manuscript, we demonstrate a novel reduced order modeling method for building a surrogate model that employs only 'local first-order' derivatives and a new tensor-free expansion to efficiently identify all the important features of the original model to reach a predetermined level of accuracy. This is achieved via a hybrid approach in which local first-order derivatives (i.e., gradient) of a pseudo response (a pseudo response represents a random linear combination of original model’s responses) are randomly sampled utilizing a tensor-free expansion around some reference point, with the resulting gradient information aggregated in a subspace (denoted by the active subspace) of dimension much less than the dimension of the input parameters space. The active subspace is then sampled employing the state-of-the-art techniques for global sampling methods. The proposed method hybridizes the use of global sampling methods for uncertainty quantification and local variational methods for sensitivity analysis. In a similar manner to
Models and correlations of the DEBRIS Late-Phase Melt Progression Model
International Nuclear Information System (INIS)
Schmidt, R.C.; Gasser, R.D.
1997-09-01
The DEBRIS Late Phase Melt Progression Model is an assembly of models, embodied in a computer code, which is designed to treat late-phase melt progression in dry rubble (or debris) regions that can form as a consequence of a severe core uncover accident in a commercial light water nuclear reactor. The approach is fully two-dimensional, and incorporates a porous medium modeling framework together with conservation and constitutive relationships to simulate the time-dependent evolution of such regions as various physical processes act upon the materials. The objective of the code is to accurately model these processes so that the late-phase melt progression that would occur in different hypothetical severe nuclear reactor accidents can be better understood and characterized. In this report the models and correlations incorporated and used within the current version of DEBRIS are described. These include the global conservation equations solved, heat transfer and fission heating models, melting and refreezing models (including material interactions), liquid and solid relocation models, gas flow and pressure field models, and the temperature and compositionally dependent material properties employed. The specific models described here have been used in the experiment design analysis of the Phebus FPT-4 debris-bed fission-product release experiment. An earlier DEBRIS code version was used to analyze the MP-1 and MP-2 late-phase melt progression experiments conducted at Sandia National Laboratories for the US Nuclear Regulatory Commission
Ordering dynamics of microscopic models with nonconserved order parameter of continuous symmetry
DEFF Research Database (Denmark)
Zhang, Z.; Mouritsen, Ole G.; Zuckermann, Martin J.
1993-01-01
crystals. For both models, which have a nonconserved order parameter, it is found that the linear scale, R(t), of the evolving order, following quenches to below the transition temperature, grows at late times in an effectively algebraic fashion, R(t)∼tn, with exponent values which are strongly temperature......Numerical Monte Carlo temperature-quenching experiments have been performed on two three-dimensional classical lattice models with continuous ordering symmetry: the Lebwohl-Lasher model [Phys. Rev. A 6, 426 (1972)] and the ferromagnetic isotropic Heisenberg model. Both models describe a transition...... from a disordered phase to an orientationally ordered phase of continuous symmetry. The Lebwohl-Lasher model accounts for the orientational ordering properties of the nematic-isotropic transition in liquid crystals and the Heisenberg model for the ferromagnetic-paramagnetic transition in magnetic...
Zimmerer, V. C.; Varley, R. A.
2015-01-01
Processing of linear word order (linear configuration) is important for virtually all languages and essential to languages such as English which have little functional morphology. Damage to systems underpinning configurational processing may specifically affect word-order reliant sentence structures. We explore order processing in WR, a man with primary progressive aphasia (PPA). In a previous report, we showed how WR showed impaired processing of actives, which rely strongly on word order, b...
Sepsis progression and outcome: a dynamical model
Directory of Open Access Journals (Sweden)
Gessler Damian DG
2006-02-01
Full Text Available Abstract Background Sepsis (bloodstream infection is the leading cause of death in non-surgical intensive care units. It is diagnosed in 750,000 US patients per annum, and has high mortality. Current understanding of sepsis is predominately observational and correlational, with only a partial and incomplete understanding of the physiological dynamics underlying the syndrome. There exists a need for dynamical models of sepsis progression, based upon basic physiologic principles, which could eventually guide hourly treatment decisions. Results We present an initial mathematical model of sepsis, based on metabolic rate theory that links basic vascular and immunological dynamics. The model includes the rate of vascular circulation, a surrogate for the metabolic rate that is mechanistically associated with disease progression. We use the mass-specific rate of blood circulation (SRBC, a correlate of the body mass index, to build a differential equation model of circulation, infection, organ damage, and recovery. This introduces a vascular component into an infectious disease model that describes the interaction between a pathogen and the adaptive immune system. Conclusion The model predicts that deviations from normal SRBC correlate with disease progression and adverse outcome. We compare the predictions with population mortality data from cardiovascular disease and cancer and show that deviations from normal SRBC correlate with higher mortality rates.
Green, Colin; Shearer, James; Ritchie, Craig W; Zajicek, John P
2011-01-01
To consider the methods available to model Alzheimer's disease (AD) progression over time to inform on the structure and development of model-based evaluations, and the future direction of modelling methods in AD. A systematic search of the health care literature was undertaken to identify methods to model disease progression in AD. Modelling methods are presented in a descriptive review. The literature search identified 42 studies presenting methods or applications of methods to model AD progression over time. The review identified 10 general modelling frameworks available to empirically model the progression of AD as part of a model-based evaluation. Seven of these general models are statistical models predicting progression of AD using a measure of cognitive function. The main concerns with models are on model structure, around the limited characterization of disease progression, and on the use of a limited number of health states to capture events related to disease progression over time. None of the available models have been able to present a comprehensive model of the natural history of AD. Although helpful, there are serious limitations in the methods available to model progression of AD over time. Advances are needed to better model the progression of AD and the effects of the disease on peoples' lives. Recent evidence supports the need for a multivariable approach to the modelling of AD progression, and indicates that a latent variable analytic approach to characterising AD progression is a promising avenue for advances in the statistical development of modelling methods. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Fernandez, R.; Deveaux, V.
2010-01-01
We provide a formal definition and study the basic properties of partially ordered chains (POC). These systems were proposed to model textures in image processing and to represent independence relations between random variables in statistics (in the later case they are known as Bayesian networks).
First-Order SPICE Modeling of Extreme-Temperature 4H-SiC JFET Integrated Circuits
Neudeck, Philip G.; Spry, David J.; Chen, Liang-Yu
2016-01-01
A separate submission to this conference reports that 4H-SiC Junction Field Effect Transistor (JFET) digital and analog Integrated Circuits (ICs) with two levels of metal interconnect have reproducibly demonstrated electrical operation at 500 C in excess of 1000 hours. While this progress expands the complexity and durability envelope of high temperature ICs, one important area for further technology maturation is the development of reasonably accurate and accessible computer-aided modeling and simulation tools for circuit design of these ICs. Towards this end, we report on development and verification of 25 C to 500 C SPICE simulation models of first order accuracy for this extreme-temperature durable 4H-SiC JFET IC technology. For maximum availability, the JFET IC modeling is implemented using the baseline-version SPICE NMOS LEVEL 1 model that is common to other variations of SPICE software and importantly includes the body-bias effect. The first-order accuracy of these device models is verified by direct comparison with measured experimental device characteristics.
Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B
2017-05-01
Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.
On an orthotropic model for progressive degradation
DEFF Research Database (Denmark)
Hammer, Velaja B.; Pedersen, Pauli
1999-01-01
Progressive degradation in orthotropic materials is modelled from a smear-out point of view, and physical measurable quantities are used as the describing parameters. Evolution of stiffness and evolution of strength are kept uncoupled. For plane problems the stiffness evolution is modelled...
Fractional-order in a macroeconomic dynamic model
David, S. A.; Quintino, D. D.; Soliani, J.
2013-10-01
In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.
Multi-Criteria Model for Determining Order Size
Directory of Open Access Journals (Sweden)
Katarzyna Jakowska-Suwalska
2013-01-01
Full Text Available A multi-criteria model for determining the order size for materials used in production has been presented. It was assumed that the consumption rate of each material is a random variable with a known probability distribution. Using such a model, in which the purchase cost of materials ordered is limited, three criteria were considered: order size, probability of a lack of materials in the production process, and deviations in the order size from the consumption rate in past periods. Based on an example, it has been shown how to use the model to determine the order sizes for polyurethane adhesive and wood in a hard-coal mine. (original abstract
International Nuclear Information System (INIS)
Nagler, S.E.
1989-01-01
We report on the progress of our project entitled ''X-ray Scattering Studies of Non-Equilibrium Ordering Processes.'' In-house time-resolved x-ray scattering has been used to investigate ordering kinetics in single crystal thin films of Cu 3 Au. Scaling analysis of the results shows that two dimensional kinetic behavior is observed in 260 /angstrom/ thick films. Significant improvements have been made in the local capabilities for fast time resolved measurements and data analysis. Measurements of microphase separation and ordering kinetics have been made in block-co-polymers, and experiments on Au-Cd martensitic material are continuing. 15 refs., 7 figs
Model selection criteria : how to evaluate order restrictions
Kuiper, R.M.
2012-01-01
Researchers often have ideas about the ordering of model parameters. They frequently have one or more theories about the ordering of the group means, in analysis of variance (ANOVA) models, or about the ordering of coefficients corresponding to the predictors, in regression models.A researcher might
Using Rasch models to develop and validate an environmental thinking learning progression
Hashimoto-Martell, Erin A.
Environmental understanding is highly relevant in today's global society. Social, economic, and political structures are connected to the state of environmental degradation and exploitation, and disproportionately affect those in poor or urban communities (Brulle & Pellow, 2006; Executive Order No. 12898, 1994). Environmental education must challenge the way we live, and our social and ecological quality of life, with the goal of responsible action. The development of a learning progression in environmental thinking, along with a corresponding assessment, could provide a tool that could be used across environmental education programs to help evaluate and guide programmatic decisions. This study sought to determine if a scale could be constructed that allowed individuals to be ordered along a continuum of environmental thinking. First, I developed the Environmental Thinking Learning Progression, a scale of environmental thinking from novice to advanced, based on the current available research and literature. The scale consisted of four subscales, each measuring a different aspect of environmental thinking: place consciousness, human connection, agency, and science concepts. Second, a measurement instrument was developed, so that the data appropriately fit the model using Rasch analysis. A Rasch analysis of the data placed respondents along a continuum, given the range of item difficulty for each subscale. Across three iterations of instrument revision and data collection, findings indicated that the items were ordered in a hierarchical way that corresponded to the construct of environmental thinking. Comparisons between groups showed that the average score of respondents who had participated in environmental education programs was significantly higher than those who had not. A comparison between males and females showed no significant difference in average measure, however, there were varied significant differences between how racial/ethnic groups performed. Overall
XY model with higher-order exchange.
Žukovič, Milan; Kalagov, Georgii
2017-08-01
An XY model, generalized by inclusion of up to an infinite number of higher-order pairwise interactions with an exponentially decreasing strength, is studied by spin-wave theory and Monte Carlo simulations. At low temperatures the model displays a quasi-long-range-order phase characterized by an algebraically decaying correlation function with the exponent η=T/[2πJ(p,α)], nonlinearly dependent on the parameters p and α that control the number of the higher-order terms and the decay rate of their intensity, respectively. At higher temperatures the system shows a crossover from the continuous Berezinskii-Kosterlitz-Thouless to the first-order transition for the parameter values corresponding to a highly nonlinear shape of the potential well. The role of topological excitations (vortices) in changing the nature of the transition is discussed.
Lye, Ribin; Tan, James Peng Lung; Cheong, Siew Ann
2012-11-01
We describe a bottom-up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We illustrate this framework by starting with a deterministic toy model, whereby N independent traders buy and sell M stocks through an order book that acts as a clearing house. The price of a stock increases whenever it is bought and decreases whenever it is sold. Price changes are updated by the order book before the next transaction takes place. In this deterministic model, all traders based their buy decisions on a call utility function, and all their sell decisions on a put utility function. We then make the agent-based model more realistic, by either having a fraction fb of traders buy a random stock on offer, or a fraction fs of traders sell a random stock in their portfolio. Based on our simulations, we find that it is possible to identify useful order parameters from the steady-state price distributions of all three models. Using these order parameters as a guide, we find three phases: (i) the dead market; (ii) the boom market; and (iii) the jammed market in the phase diagram of the deterministic model. Comparing the phase diagrams of the stochastic models against that of the deterministic model, we realize that the primary effect of stochasticity is to eliminate the dead market phase.
Model predictive control based on reduced order models applied to belt conveyor system.
Chen, Wei; Li, Xin
2016-11-01
In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
A comparison of zero-order, first-order, and Monod biotransformation models
International Nuclear Information System (INIS)
Bekins, B.A.; Warren, E.; Godsy, E.M.
1998-01-01
Under some conditions, a first-order kinetic model is a poor representation of biodegradation in contaminated aquifers. Although it is well known that the assumption of first-order kinetics is valid only when substrate concentration, S, is much less than the half-saturation constant, K S , this assumption is often made without verification of this condition. The authors present a formal error analysis showing that the relative error in the first-order approximation is S/K S and in the zero-order approximation the error is K S /S. They then examine the problems that arise when the first-order approximation is used outside the range for which it is valid. A series of numerical simulations comparing results of first- and zero-order rate approximations to Monod kinetics for a real data set illustrates that if concentrations observed in the field are higher than K S , it may be better to model degradation using a zero-order rate expression. Compared with Monod kinetics, extrapolation of a first-order rate to lower concentrations under-predicts the biotransformation potential, while extrapolation to higher concentrations may grossly over-predict the transformation rate. A summary of solubilities and Monod parameters for aerobic benzene, toluene, and xylene (BTX) degradation shows that the a priori assumption of first-order degradation kinetics at sites contaminated with these compounds is not valid. In particular, out of six published values of K S for toluene, only one is greater than 2 mg/L, indicating that when toluene is present in concentrations greater than about a part per million, the assumption of first-order kinetics may be invalid. Finally, the authors apply an existing analytical solution for steady-state one-dimensional advective transport with Monod degradation kinetics to a field data set
Recent progress in sorption mechanisms and models
International Nuclear Information System (INIS)
Fedoroff, M.; Lefevre, G.
2005-01-01
Full text of publication follows: Sorption-desorption phenomena play an important role in the migration of radioactive species in surface and underground waters. In order to predict the transport of these species, we need a good knowledge of sorption processes and data, together with reliable models able to be included in transport calculation. Traditional approaches based on experimentally determined distribution coefficients (Kd) and sorption isotherms have a limited predictive capability, since they are very sensitive to the numerous parameters characterizing the solution and the solid. Models based on thermodynamic equilibria were developed to account for the influence these parameters: the ion exchange model and the surface complexation models (2-pK mono-site, 1-pK multi-site, with several different electrostatic models: CCM, DLM, BSM, TLM,...). Although these models are very useful, studies performed in recent years showed that they have important theoretical and experimental limitations, which result in the fact that we must be very careful when we use them for extrapolating sorption data to long term and to large natural systems. Among all problems which can be found are: the possibility to fit a set of experimental data with different models, sometimes bad adequacy with the real sorption processes, some theoretical limitations such as a rigorous definition of reference and standard states in surface equilibria, slow kinetics which prevent from equilibrium achievement, irreversibility, solubility and evolution of solid phases... Through the increase of the number of sensitive spectroscopic methods, we are now able to know more about sorption processes at the atomic scale. Models such as the 1-pK CD-MUSIC model can account for the influence of orientation of the faces of the solid. More and more examples of the influence of this orientation on the sorption properties are known. Calculations performed by 'ab initio' modeling is also useful to predict the
Directory of Open Access Journals (Sweden)
Lubna Moin
2009-04-01
analyzed. The approach towards the Genetic Tree formation from the Bond Graph is also developed. The model order reduction using Genetic Tree is in progress.
Building a progressive vertical integration
International Nuclear Information System (INIS)
Charette, D.
2008-01-01
AAER Inc. is a Quebec-based company that manufactures turbines using proven European designs. This presentation discussed the company's business model. The company places an emphasis on identifying strategic and key components currently available for its turbines. Market analyses are performed in order to determine ideal suppliers and define business strategies and needs. The company invests in long-term relationships with its suppliers. Business partners for AAER are of a similar size and have a mutual understanding and respect for the company's business practices. Long-term agreements with suppliers are signed in order to ensure reliability and control over costs. Progressive vertical integration has been achieved by progressively manufacturing key components and integrating a North American supply chain. The company's secure supply chain and progressive vertical integration has significantly reduced financial costs and provided better quality control. It was concluded that vertical integration has also allowed AAER to provide better customer service and reduce transportation costs. tabs., figs
Birth order progressively affects childhood height.
Savage, Tim; Derraik, José G B; Miles, Harriet L; Mouat, Fran; Cutfield, Wayne S; Hofman, Paul L
2013-09-01
There is evidence suggesting that first-born children and adults are anthropometrically different to later-borns. Thus, we aimed to assess whether birth order was associated with changes in growth and metabolism in childhood. We studied 312 healthy prepubertal children: 157 first-borns and 155 later-borns. Children were aged 3-10 years, born 37-41 weeks gestation, and of birth weight appropriate-for-gestational-age. Clinical assessments included measurement of children's height, weight, fasting lipid and hormonal profiles and DEXA-derived body composition. First-borns were taller than later-borns (P < 0·0001), even when adjusted for parents' heights (0·31 vs 0·03 SDS; P = 0·001). There was an incremental height decrease with increasing birth order, so that first-borns were taller than second-borns (P < 0·001), who were in turn taller than third-borns (P = 0·007). Further, among sibling pairs both height SDS (P = 0·009) and adjusted height SDS (P < 0·0001) were lower in second- vs first-born children. Consistent with differences in stature, first- (P = 0·043) and second-borns (P = 0·003) had higher IGF-I concentrations than third-borns. Both first- (P < 0·001) and second-borns (P = 0·004) also had reduced abdominal adiposity (lower android fat to gynoid fat ratio) when compared with third-borns. Other parameters of adiposity and blood lipids were unaffected by birth order. First-borns were taller than later-born children, with an incremental height reduction from first to third birth order. These differences were present after correction for genetic height, and associated to some extent with alterations in plasma IGF-I. Our findings strengthen the evidence that birth order is associated with phenotypic changes in childhood. © 2013 John Wiley & Sons Ltd.
Mixed-order phase transition in a one-dimensional model.
Bar, Amir; Mukamel, David
2014-01-10
We introduce and analyze an exactly soluble one-dimensional Ising model with long range interactions that exhibits a mixed-order transition, namely a phase transition in which the order parameter is discontinuous as in first order transitions while the correlation length diverges as in second order transitions. Such transitions are known to appear in a diverse classes of models that are seemingly unrelated. The model we present serves as a link between two classes of models that exhibit a mixed-order transition in one dimension, namely, spin models with a coupling constant that decays as the inverse distance squared and models of depinning transitions, thus making a step towards a unifying framework.
Progression of Diabetic Capillary Occlusion: A Model.
Directory of Open Access Journals (Sweden)
Xiao Fu
2016-06-01
Full Text Available An explanatory computational model is developed of the contiguous areas of retinal capillary loss which play a large role in diabetic maculapathy and diabetic retinal neovascularization. Strictly random leukocyte mediated capillary occlusion cannot explain the occurrence of large contiguous areas of retinal ischemia. Therefore occlusion of an individual capillary must increase the probability of occlusion of surrounding capillaries. A retinal perifoveal vascular sector as well as a peripheral retinal capillary network and a deleted hexagonal capillary network are modelled using Compucell3D. The perifoveal modelling produces a pattern of spreading capillary loss with associated macular edema. In the peripheral network, spreading ischemia results from the progressive loss of the ladder capillaries which connect peripheral arterioles and venules. System blood flow was elevated in the macular model before a later reduction in flow in cases with progression of capillary occlusions. Simulations differing only in initial vascular network structures but with identical dynamics for oxygen, growth factors and vascular occlusions, replicate key clinical observations of ischemia and macular edema in the posterior pole and ischemia in the retinal periphery. The simulation results also seem consistent with quantitative data on macular blood flow and qualitative data on venous oxygenation. One computational model applied to distinct capillary networks in different retinal regions yielded results comparable to clinical observations in those regions.
Developing and Validating a Predictive Model for Stroke Progression
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L.E. Craig
2011-12-01
Full Text Available Background: Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Methods: Two patient cohorts were used for this study – the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863 was used to develop the model. Variables that were statistically significant (p 0.1 in turn. The second cohort (n = 216 was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Results: Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72–0.73] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50–0.92]. Conclusion: The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the
Developing and validating a predictive model for stroke progression.
Craig, L E; Wu, O; Gilmour, H; Barber, M; Langhorne, P
2011-01-01
Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Two patient cohorts were used for this study - the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p p > 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72-0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50-0.92)]. The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and calibration of the predictive model appear
Developing and Validating a Predictive Model for Stroke Progression
Craig, L.E.; Wu, O.; Gilmour, H.; Barber, M.; Langhorne, P.
2011-01-01
Background Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Methods Two patient cohorts were used for this study – the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Results Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72–0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50–0.92)]. Conclusion The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and
Hanford Federal Facility Agreement and Consent Order, quarterly progress report, March 31, 1992
International Nuclear Information System (INIS)
1992-05-01
This is the twelfth quarterly report as required by the Hanford Federal Facility Agreement and Consent Order (Tri-Party Agreement) (Ecology et al. 1990), established between the US Department of Energy (DOE), the US Environmental Protection Agency (EPA), and the Washington State Department of Ecology (Ecology). The Tri-Party Agreement sets the plan and schedule for achieving regulatory compliance and cleanup of waste sites at the Hanford Site. This report covers progress for the quarter that ended March 31, 1992. Topics covered under technical status include: disposal of tank wastes; cleanup of past-practice units; permitting and closure of treatment, storage, and disposal units; and other tri-party agreement activities and issues
Directory of Open Access Journals (Sweden)
Salvador Lucas
2015-12-01
Full Text Available Recent developments in termination analysis for declarative programs emphasize the use of appropriate models for the logical theory representing the program at stake as a generic approach to prove termination of declarative programs. In this setting, Order-Sorted First-Order Logic provides a powerful framework to represent declarative programs. It also provides a target logic to obtain models for other logics via transformations. We investigate the automatic generation of numerical models for order-sorted first-order logics and its use in program analysis, in particular in termination analysis of declarative programs. We use convex domains to give domains to the different sorts of an order-sorted signature; we interpret the ranked symbols of sorted signatures by means of appropriately adapted convex matrix interpretations. Such numerical interpretations permit the use of existing algorithms and tools from linear algebra and arithmetic constraint solving to synthesize the models.
Computational algebraic geometry for statistical modeling FY09Q2 progress.
Energy Technology Data Exchange (ETDEWEB)
Thompson, David C.; Rojas, Joseph Maurice; Pebay, Philippe Pierre
2009-03-01
This is a progress report on polynomial system solving for statistical modeling. This is a progress report on polynomial system solving for statistical modeling. This quarter we have developed our first model of shock response data and an algorithm for identifying the chamber cone containing a polynomial system in n variables with n+k terms within polynomial time - a significant improvement over previous algorithms, all having exponential worst-case complexity. We have implemented and verified the chamber cone algorithm for n+3 and are working to extend the implementation to handle arbitrary k. Later sections of this report explain chamber cones in more detail; the next section provides an overview of the project and how the current progress fits into it.
Optimal tax progressivity in imperfect labour markets
DEFF Research Database (Denmark)
Sørensen, Peter Birch
1999-01-01
that there may be an optimal degree of tax progressivity where the marginal welfare gain from reduced involuntary unemployment is just offset by the marginal welfare loss from lower productivity. This paper sets up four different models of an imperfect labour market in order to identify the degree of tax......All modern labour market theories capable of explaining involuntary unemployment as an equilibrium phenomenon imply that increased income tax progressivity reduces unemployment, but they also imply that higher progressivity tends to reduce work effort and labour productivity. This suggests...
Interleukin-1 may link helplessness-hopelessness with cancer progression: A proposed model
Argaman, M; Gidron, Y; Ariad, S
2005-01-01
A model of the relations between psychological factors and cancer progression should include brain and systemic components and their link with critical cellular stages in cancer progression. We present a psychoneuroimmunological (PNI) model that links helplessness-hopelessness (HH) with cancer progression via interleukin-1β (IL-1β). IL-1β was elevated in the brain following exposure to inescapable shock, and HH was minimized by antagonizing cerebral IL-1β. Elevated cerebral IL-1β increased ca...
Modeling Ability Differentiation in the Second-Order Factor Model
Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.
2011-01-01
In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…
Progressive Damage Modeling of Durable Bonded Joint Technology
Leone, Frank A.; Davila, Carlos G.; Lin, Shih-Yung; Smeltzer, Stan; Girolamo, Donato; Ghose, Sayata; Guzman, Juan C.; McCarville, Duglas A.
2013-01-01
The development of durable bonded joint technology for assembling composite structures for launch vehicles is being pursued for the U.S. Space Launch System. The present work is related to the development and application of progressive damage modeling techniques to bonded joint technology applicable to a wide range of sandwich structures for a Heavy Lift Launch Vehicle. The joint designs studied in this work include a conventional composite splice joint and a NASA-patented Durable Redundant Joint. Both designs involve a honeycomb sandwich with carbon/epoxy facesheets joined with adhesively bonded doublers. Progressive damage modeling allows for the prediction of the initiation and evolution of damage. For structures that include multiple materials, the number of potential failure mechanisms that must be considered increases the complexity of the analyses. Potential failure mechanisms include fiber fracture, matrix cracking, delamination, core crushing, adhesive failure, and their interactions. The joints were modeled using Abaqus parametric finite element models, in which damage was modeled with user-written subroutines. Each ply was meshed discretely, and layers of cohesive elements were used to account for delaminations and to model the adhesive layers. Good correlation with experimental results was achieved both in terms of load-displacement history and predicted failure mechanisms.
Distributed-Order Dynamic Systems Stability, Simulation, Applications and Perspectives
Jiao, Zhuang; Podlubny, Igor
2012-01-01
Distributed-order differential equations, a generalization of fractional calculus, are of increasing importance in many fields of science and engineering from the behaviour of complex dielectric media to the modelling of nonlinear systems. This Brief will broaden the toolbox available to researchers interested in modeling, analysis, control and filtering. It contains contextual material outlining the progression from integer-order, through fractional-order to distributed-order systems. Stability issues are addressed with graphical and numerical results highlighting the fundamental differences between constant-, integer-, and distributed-order treatments. The power of the distributed-order model is demonstrated with work on the stability of noncommensurate-order linear time-invariant systems. Generic applications of the distributed-order operator follow: signal processing and viscoelastic damping of a mass–spring set up. A new general approach to discretization of distributed-order derivatives and integrals ...
A Novel Method for Decoding Any High-Order Hidden Markov Model
Directory of Open Access Journals (Sweden)
Fei Ye
2014-01-01
Full Text Available This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model. This method provides a unified algorithm framework for decoding hidden Markov models including the first-order hidden Markov model and any high-order hidden Markov model.
Model-order reduction of lumped parameter systems via fractional calculus
Hollkamp, John P.; Sen, Mihir; Semperlotti, Fabio
2018-04-01
This study investigates the use of fractional order differential models to simulate the dynamic response of non-homogeneous discrete systems and to achieve efficient and accurate model order reduction. The traditional integer order approach to the simulation of non-homogeneous systems dictates the use of numerical solutions and often imposes stringent compromises between accuracy and computational performance. Fractional calculus provides an alternative approach where complex dynamical systems can be modeled with compact fractional equations that not only can still guarantee analytical solutions, but can also enable high levels of order reduction without compromising on accuracy. Different approaches are explored in order to transform the integer order model into a reduced order fractional model able to match the dynamic response of the initial system. Analytical and numerical results show that, under certain conditions, an exact match is possible and the resulting fractional differential models have both a complex and frequency-dependent order of the differential operator. The implications of this type of approach for both model order reduction and model synthesis are discussed.
MacNab, Ying C
2016-08-01
This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.
Generalized Reduced Order Model Generation, Phase I
National Aeronautics and Space Administration — M4 Engineering proposes to develop a generalized reduced order model generation method. This method will allow for creation of reduced order aeroservoelastic state...
Investigation of Effectiveness of Order Review and Release Models in Make to Order Supply Chain
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Kundu Kaustav
2016-01-01
Full Text Available Nowadays customisation becomes more common due to vast requirement from the customers for which industries are trying to use make-to-order (MTO strategy. Due to high variation in the process, workload control models are extensively used for jobshop companies which usually adapt MTO strategy. Some authors tried to implement workload control models, order review and release systems, in non-repetitive manufacturing companies, where there is a dominant flow in production. Those models are better in shop floor but their performances are never been investigated in high variation situations like MTO supply chain. This paper starts with the introduction of particular issues in MTO companies and a general overview of order review and release systems widely used in the industries. Two order review and release systems, the Limited and Balanced models, particularly suitable for flow shop system are applied to MTO supply chain, where the processing times are difficult to estimate due to high variation. Simulation results show that the Balanced model performs much better than the Limited model if the processing times can be estimated preciously.
Spiking and bursting patterns of fractional-order Izhikevich model
Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha
2018-03-01
Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.
A reduced order model of a quadruped walking system
International Nuclear Information System (INIS)
Sano, Akihito; Furusho, Junji; Naganuma, Nobuyuki
1990-01-01
Trot walking has recently been studied by several groups because of its stability and realizability. In the trot, diagonally opposed legs form pairs. While one pair of legs provides support, the other pair of legs swings forward in preparation for the next step. In this paper, we propose a reduced order model for the trot walking. The reduced order model is derived by using two dominant modes of the closed loop system in which the local feedback at each joint is implemented. It is shown by numerical examples that the obtained reduced order model can well approximate the original higher order model. (author)
Applicability of the capability maturity model for engineer-to-order firms
Veldman, J.; Klingenberg, W.
2009-01-01
Most of the well-known management and improvement systems and techniques, Such as Lean Production (e.g. Just-In-Time (JIT) Pull production, one piece flow) and Six Sigma (reduction in variation) were developed in high Volume industries. In order to measure the progress of the implementation of Such
Applicability of the capability maturity model for engineer-to-order firms
Veldman, Jasper; Klingenberg, Warse
2009-01-01
Most of the well-known management and improvement systems and techniques, such as Lean Production (e.g. Just-In-Time (JIT) pull production, one piece flow) and Six Sigma (reduction in variation) were developed in high volume industries. In order to measure the progress of the implementation of such
Dynamical models of happiness with fractional order
Song, Lei; Xu, Shiyun; Yang, Jianying
2010-03-01
This present study focuses on a dynamical model of happiness described through fractional-order differential equations. By categorizing people of different personality and different impact factor of memory (IFM) with different set of model parameters, it is demonstrated via numerical simulations that such fractional-order models could exhibit various behaviors with and without external circumstance. Moreover, control and synchronization problems of this model are discussed, which correspond to the control of emotion as well as emotion synchronization in real life. This study is an endeavor to combine the psychological knowledge with control problems and system theories, and some implications for psychotherapy as well as hints of a personal approach to life are both proposed.
Hybrid reduced order modeling for assembly calculations
Energy Technology Data Exchange (ETDEWEB)
Bang, Youngsuk, E-mail: ysbang00@fnctech.com [FNC Technology, Co. Ltd., Yongin-si (Korea, Republic of); Abdel-Khalik, Hany S., E-mail: abdelkhalik@purdue.edu [Purdue University, West Lafayette, IN (United States); Jessee, Matthew A., E-mail: jesseema@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States); Mertyurek, Ugur, E-mail: mertyurek@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States)
2015-12-15
Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.
Hybrid reduced order modeling for assembly calculations
International Nuclear Information System (INIS)
Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; Mertyurek, Ugur
2015-01-01
Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.
Hu, Yong; Olguin, Hernan; Gutheil, Eva
2017-05-01
A spray flamelet/progress variable approach is developed for use in spray combustion with partly pre-vaporised liquid fuel, where a laminar spray flamelet library accounts for evaporation within the laminar flame structures. For this purpose, the standard spray flamelet formulation for pure evaporating liquid fuel and oxidiser is extended by a chemical reaction progress variable in both the turbulent spray flame model and the laminar spray flame structures, in order to account for the effect of pre-vaporised liquid fuel for instance through use of a pilot flame. This new approach is combined with a transported joint probability density function (PDF) method for the simulation of a turbulent piloted ethanol/air spray flame, and the extension requires the formulation of a joint three-variate PDF depending on the gas phase mixture fraction, the chemical reaction progress variable, and gas enthalpy. The molecular mixing is modelled with the extended interaction-by-exchange-with-the-mean (IEM) model, where source terms account for spray evaporation and heat exchange due to evaporation as well as the chemical reaction rate for the chemical reaction progress variable. This is the first formulation using a spray flamelet model considering both evaporation and partly pre-vaporised liquid fuel within the laminar spray flamelets. Results with this new formulation show good agreement with the experimental data provided by A.R. Masri, Sydney, Australia. The analysis of the Lagrangian statistics of the gas temperature and the OH mass fraction indicates that partially premixed combustion prevails near the nozzle exit of the spray, whereas further downstream, the non-premixed flame is promoted towards the inner rich-side of the spray jet since the pilot flame heats up the premixed inner spray zone. In summary, the simulation with the new formulation considering the reaction progress variable shows good performance, greatly improving the standard formulation, and it provides new
Progress in D-brane model building
International Nuclear Information System (INIS)
Marchesano, F.
2007-01-01
The state of the art in D-brane model building is briefly reviewed, focusing on recent achievements in the construction of D=4 N=1 type II string vacua with semi-realistic gauge sectors. Such progress relies on a better understanding of the spectrum of BPS D-branes, the effective field theory obtained from them and the explicit construction of vacua. We first consider D-branes in standard Calabi-Yau compactifications, and then the more involved case of compactifications with fluxes. We discuss how the non-trivial interplay between D-branes and fluxes modifies the previous model-building rules, as well as provides new possibilities to connect string theory to particle physics. (Abstract Copyright [2007], Wiley Periodicals, Inc.)
Fractional Order Models of Industrial Pneumatic Controllers
Directory of Open Access Journals (Sweden)
Abolhassan Razminia
2014-01-01
Full Text Available This paper addresses a new approach for modeling of versatile controllers in industrial automation and process control systems such as pneumatic controllers. Some fractional order dynamical models are developed for pressure and pneumatic systems with bellows-nozzle-flapper configuration. In the light of fractional calculus, a fractional order derivative-derivative (FrDD controller and integral-derivative (FrID are remodeled. Numerical simulations illustrate the application of the obtained theoretical results in simple examples.
SyntEyes KTC: higher order statistical eye model for developing keratoconus.
Rozema, Jos J; Rodriguez, Pablo; Ruiz Hidalgo, Irene; Navarro, Rafael; Tassignon, Marie-José; Koppen, Carina
2017-05-01
To present and validate a stochastic eye model for developing keratoconus to e.g. improve optical corrective strategies. This could be particularly useful for researchers that do not have access to original keratoconic data. The Scheimpflug tomography, ocular biometry and wavefront of 145 keratoconic right eyes were collected. These data were processed using principal component analysis for parameter reduction, followed by a multivariate Gaussian fit that produces a stochastic model for keratoconus (SyntEyes KTC). The output of this model is filtered to remove the occasional incorrect topography patterns by either an automatic or manual procedure. Finally, the output of this keratoconus model is matched to that of the original model for normal eyes using the non-corneal biometry to obtain a description of keratoconus development. The synthetic data generated by the model were found to be significantly equal to the original data (non-parametric Mann-Whitney equivalence test; 145/154 passed). The variability of the synthetic data, however, was often significantly less than that of the original data, especially for the higher order Zernike terms of corneal elevation (non-parametric Levene test; p eyes with incorrect topographies. Interpolation between matched pairs of normal and keratoconic SyntEyes appears to provide an adequate model for keratoconus progression. The synthetic data provided by the proposed keratoconus model closely resembles actual clinical data and may be used for a range of research applications when (sufficient) real data is not available. © 2017 The Authors Ophthalmic & Physiological Optics © 2017 The College of Optometrists.
Modeling and Predicting AD Progression by Regression Analysis of Sequential Clinical Data
Xie, Qing
2016-02-23
Alzheimer\\'s Disease (AD) is currently attracting much attention in elders\\' care. As the increasing availability of massive clinical diagnosis data, especially the medical images of brain scan, it is highly significant to precisely identify and predict the potential AD\\'s progression based on the knowledge in the diagnosis data. In this paper, we follow a novel sequential learning framework to model the disease progression for AD patients\\' care. Different from the conventional approaches using only initial or static diagnosis data to model the disease progression for different durations, we design a score-involved approach and make use of the sequential diagnosis information in different disease stages to jointly simulate the disease progression. The actual clinical scores are utilized in progress to make the prediction more pertinent and reliable. We examined our approach by extensive experiments on the clinical data provided by the Alzheimer\\'s Disease Neuroimaging Initiative (ADNI). The results indicate that the proposed approach is more effective to simulate and predict the disease progression compared with the existing methods.
Modeling and Predicting AD Progression by Regression Analysis of Sequential Clinical Data
Xie, Qing; Wang, Su; Zhu, Jia; Zhang, Xiangliang
2016-01-01
Alzheimer's Disease (AD) is currently attracting much attention in elders' care. As the increasing availability of massive clinical diagnosis data, especially the medical images of brain scan, it is highly significant to precisely identify and predict the potential AD's progression based on the knowledge in the diagnosis data. In this paper, we follow a novel sequential learning framework to model the disease progression for AD patients' care. Different from the conventional approaches using only initial or static diagnosis data to model the disease progression for different durations, we design a score-involved approach and make use of the sequential diagnosis information in different disease stages to jointly simulate the disease progression. The actual clinical scores are utilized in progress to make the prediction more pertinent and reliable. We examined our approach by extensive experiments on the clinical data provided by the Alzheimer's Disease Neuroimaging Initiative (ADNI). The results indicate that the proposed approach is more effective to simulate and predict the disease progression compared with the existing methods.
Jedynak, Bruno M.; Liu, Bo; Lang, Andrew; Gel, Yulia; Prince, Jerry L.
2014-01-01
Understanding the time-dependent changes of biomarkers related to Alzheimer’s disease (AD) is a key to assessing disease progression and to measuring the outcomes of disease-modifying therapies. In this paper, we validate an Alzheimer’s disease progression score model which uses multiple biomarkers to quantify the AD progression of subjects following three assumptions: (1) there is a unique disease progression for all subjects, (2) each subject has a different age of onset and rate of progression, and (3) each biomarker is sigmoidal as a function of disease progression. Fitting the parameters of this model is a challenging problem which we approach using an alternating least squares optimization algorithm. In order to validate this optimization scheme under realistic conditions, we use the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. With the help of Monte Carlo simulations, we show that most of the global parameters of the model are tightly estimated, thus enabling an ordering of the biomarkers that fit the model well, ordered as: the Rey auditory verbal learning test with 30 minutes delay, the sum of the two lateral hippocampal volumes divided by the intra-cranial volume, followed by (the clinical dementia rating sum of boxes score and the mini mental state examination score) in no particular order and lastly the Alzheimer’s disease assessment scale-cognitive subscale. PMID:25444605
Progress in transport modelling of internal transport barrier plasmas in JET
International Nuclear Information System (INIS)
Tala, T.; Bourdelle, C.; Imbeaux, F.; Moreau, D.; Garbet, X.; Joffrin, E.; Laborde, L.; Litaudon, X.; Mazon, D.; Parail, V.; Corrigan, G.; Heading, D.; Crisanti, F.; Mantica, P.; Salmi, A.; Strand, P.; Weiland, J.
2005-01-01
This paper will report on the recent progress in transport modelling of Internal Transport Barrier (ITB) plasmas. Two separate issues will be covered, fully predictive transport modelling of ITBs in the multi-tokamak database, including micro-stability analyses of ITBs, and predictive closed-loop (i.e. real-time control) transport simulations of the q-profile and ITBs. For the first time, the predictive capabilities of the mixed Bohm/GyroBohm and Weiland transport models are investigated with discharges from the ITPA ITB database by fully predictive transport simulations. The predictive transport simulations with the Bohm/GyroBohm model agree very well with experimental results from JET and JT-60U. In order to achieve a good agreement in DIII-D, the stabilisation had to be included into the model, showing the significant role played by the stabilisation in governing the physics of the ITBs. The significant role of the stabilisation is also emphasised by the gyrokinetic analysis. The Weiland transport model shows only limited agreement between the model predictions and experimental results with respect to the formation and location of the ITB. The fully predictive closed-loop simulations with real-time control of the q-profile and ITB show that it is possible to reach various set-point profiles for q and ITB and control them for longer than a current diffusion time in JET using the same real-time control technique as in the experiments. (author)
Reduced order for nuclear reactor model in frequency and time domain
International Nuclear Information System (INIS)
Nugroho, D.H.
1997-01-01
In control system theory, a model can be represented by frequency or time domain. In frequency domain, the model was represented by transfer function. in time domain, the model was represented by state space. for the sake of simplification in computation, it is necessary to reduce the model order. the main aim of this research is to find the best in nuclear reactor model. Model order reduction in frequency domain can be done utilizing pole-zero cancellation method; while in time domain utilizing balanced aggregation method the balanced aggregation method was developed by moore (1981). In this paper, the two kinds of method were applied to reduce a nuclear reactor model which was constructed by neutron dynamics and heat transfer equations. to validate that the model characteristics were not change when model order reduction applied, the response was utilized for full and reduced order. it was shown that the nuclear reactor order model can be reduced from order 8 to 2 order 2 is the best order for nuclear reactor model
Progress in wall turbulence 2 understanding and modelling
Jimenez, Javier; Marusic, Ivan
2016-01-01
This is the proceedings of the ERCOFTAC Workshop on Progress in Wall Turbulence: Understanding and Modelling, that was held in Lille, France from June 18 to 20, 2014. The workshop brought together world specialists of near wall turbulence and stimulated exchanges between them around up-to-date theories, experiments, simulations and numerical models. This book contains a coherent collection of recent results on near wall turbulence including theory, new experiments, DNS, and modeling with RANS, LES.The fact that both physical understanding and modeling by different approaches are addressed by the best specialists in a single workshop is original.
Tabberer, Maggie; Gonzalez-McQuire, Sebastian; Muellerova, Hana; Briggs, Andrew H; Rutten-van Mölken, Maureen P M H; Chambers, Mike; Lomas, David A
2017-05-01
To develop and validate a new conceptual model (CM) of chronic obstructive pulmonary disease (COPD) for use in disease progression and economic modeling. The CM identifies and describes qualitative associations between disease attributes, progression and outcomes. A literature review was performed to identify any published CMs or literature reporting the impact and association of COPD disease attributes with outcomes. After critical analysis of the literature, a Steering Group of experts from the disciplines of health economics, epidemiology and clinical medicine was convened to develop a draft CM, which was refined using a Delphi process. The refined CM was validated by testing for associations between attributes using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). Disease progression attributes included in the final CM were history and occurrence of exacerbations, lung function, exercise capacity, signs and symptoms (cough, sputum, dyspnea), cardiovascular disease comorbidities, 'other' comorbidities (including depression), body composition (body mass index), fibrinogen as a biomarker, smoking and demographic characteristics (age, gender). Mortality and health-related quality of life were determined to be the most relevant final outcome measures for this model, intended to be the foundation of an economic model of COPD. The CM is being used as the foundation for developing a new COPD model of disease progression and to provide a framework for the analysis of patient-level data. The CM is available as a reference for the implementation of further disease progression and economic models.
Mapping of Students’ Learning Progression Based on Mental Model in Magnetic Induction Concepts
Hamid, R.; Pabunga, D. B.
2017-09-01
The progress of student learning in a learning process has not been fully optimally observed by the teacher. The concept being taught is judged only at the end of learning as a product of thinking, and does not assess the mental processes that occur in students’ thinking. Facilitating students’ thinking through new phenomena can reveal students’ variation in thinking as a mental model of a concept, so that students who are assimilative and or accommodative can be identified in achieving their equilibrium of thought as well as an indicator of progressiveness in the students’ thinking stages. This research data is obtained from the written documents and interviews of students who were learned about the concept of magnetic induction through Constructivist Teaching Sequences (CTS) models. The results of this study indicate that facilitating the students’ thinking processes on the concept of magnetic induction contributes to increasing the number of students thinking within the "progressive change" category, and it can be said that the progress of student learning is more progressive after their mental models were facilitated through a new phenomena by teacher.
Group-ICA model order highlights patterns of functional brain connectivity
Directory of Open Access Journals (Sweden)
Ahmed eAbou Elseoud
2011-06-01
Full Text Available Resting-state networks (RSNs can be reliably and reproducibly detected using independent component analysis (ICA at both individual subject and group levels. Altering ICA dimensionality (model order estimation can have a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Recent evidence from several neuroimaging studies suggests that the human brain has a modular hierarchical organization which resembles the hierarchy depicted by different ICA model orders. We hypothesized that functional connectivity between-group differences measured with ICA might be affected by model order selection. We investigated differences in functional connectivity using so-called dual-regression as a function of ICA model order in a group of unmedicated seasonal affective disorder (SAD patients compared to normal healthy controls. The results showed that the detected disease-related differences in functional connectivity alter as a function of ICA model order. The volume of between-group differences altered significantly as a function of ICA model order reaching maximum at model order 70 (which seems to be an optimal point that conveys the largest between-group difference then stabilized afterwards. Our results show that fine-grained RSNs enable better detection of detailed disease-related functional connectivity changes. However, high model orders show an increased risk of false positives that needs to be overcome. Our findings suggest that multilevel ICA exploration of functional connectivity enables optimization of sensitivity to brain disorders.
Brundage, Miles
2015-01-01
Participants in recent discussions of AI-related issues ranging from intelligence explosion to technological unemployment have made diverse claims about the nature, pace, and drivers of progress in AI. However, these theories are rarely specified in enough detail to enable systematic evaluation of their assumptions or to extrapolate progress quantitatively, as is often done with some success in other technological domains. After reviewing relevant literatures and justifying the need for more ...
Progress in modelling agricultural impacts of and adaptations to climate change.
Rötter, R P; Hoffmann, M P; Koch, M; Müller, C
2018-06-01
Modelling is a key tool to explore agricultural impacts of and adaptations to climate change. Here we report recent progress made especially referring to the large project initiatives MACSUR and AgMIP; in particular, in modelling potential crop impacts from field to global using multi-model ensembles. We identify two main fields where further progress is necessary: a more mechanistic understanding of climate impacts and management options for adaptation and mitigation; and focusing on cropping systems and integrative multi-scale assessments instead of single season and crops, especially in complex tropical and neglected but important cropping systems. Stronger linking of experimentation with statistical and eco-physiological crop modelling could facilitate the necessary methodological advances. Copyright © 2018 Elsevier Ltd. All rights reserved.
Modelling T4 cell count as a marker of HIV progression in the ...
African Journals Online (AJOL)
Modelling T4 cell count as a marker of HIV progression in the absence of any defense mechanism. VSM Yadavalli, MMO Labeodan, S Udayabaskaran, N Forche. Abstract. The T4 cell count, which is considered one of the markers of disease progression in an HIV infected individual, is modelled in this paper. The World ...
DEFF Research Database (Denmark)
Kushch, V.I.; Shmegera, S.V.; Mishnaevsky, Leon
2011-01-01
of the multiple inclusion problem by means of complex potentials. The second, finite element model of FRC is based on the cohesive zone model of interface. Simulation of progressive debonding in FRC using the many-fiber models of composite has been performed. The advantageous features and applicability areas...... of both models are discussed. It has been shown that the developed models provide detailed analysis of the progressive debonding phenomena including the interface crack cluster formation, overall stiffness reduction and induced anisotropy of the effective elastic moduli of composite....
Hybrid reduced order modeling for assembly calculations
Energy Technology Data Exchange (ETDEWEB)
Bang, Y.; Abdel-Khalik, H. S. [North Carolina State University, Raleigh, NC (United States); Jessee, M. A.; Mertyurek, U. [Oak Ridge National Laboratory, Oak Ridge, TN (United States)
2013-07-01
While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system. (authors)
Heterogeneous traffic flow modelling using second-order macroscopic continuum model
Mohan, Ranju; Ramadurai, Gitakrishnan
2017-01-01
Modelling heterogeneous traffic flow lacking in lane discipline is one of the emerging research areas in the past few years. The two main challenges in modelling are: capturing the effect of varying size of vehicles, and the lack in lane discipline, both of which together lead to the 'gap filling' behaviour of vehicles. The same section length of the road can be occupied by different types of vehicles at the same time, and the conventional measure of traffic concentration, density (vehicles per lane per unit length), is not a good measure for heterogeneous traffic modelling. First aim of this paper is to have a parsimonious model of heterogeneous traffic that can capture the unique phenomena of gap filling. Second aim is to emphasize the suitability of higher-order models for modelling heterogeneous traffic. Third, the paper aims to suggest area occupancy as concentration measure of heterogeneous traffic lacking in lane discipline. The above mentioned two main challenges of heterogeneous traffic flow are addressed by extending an existing second-order continuum model of traffic flow, using area occupancy for traffic concentration instead of density. The extended model is calibrated and validated with field data from an arterial road in Chennai city, and the results are compared with those from few existing generalized multi-class models.
Van Hasselt, J. G C; Gupta, A.; Hussein, Z.; Beijnen, J. H.; Schellens, J. H M; Huitema, A. D R
2015-01-01
Frameworks that associate cancer dynamic disease progression models with parametric survival models for clinical outcome have recently been proposed to support decision making in early clinical development. Here we developed such a disease progression clinical outcome model for castration-resistant
An epidemic model for the future progression of the current Haiti cholera epidemic
Bertuzzo, E.; Mari, L.; Righetto, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.
2012-04-01
As a major cholera epidemic progresses in Haiti, and the figures of the infection, up to December 2011, climb to 522,000 cases and 7,000 deaths, the development of general models to track and predict the evolution of the outbreak, so as to guide the allocation of medical supplies and staff, is gaining notable urgency. We propose here a spatially explicit epidemic model that accounts for the dynamics of susceptible and infected individuals as well as the redistribution of Vibrio cholera, the causative agent of the disease, among different human communities. In particular, we model two spreading pathways: the advection of pathogens through hydrologic connections and the dissemination due to human mobility described by means of a gravity-like model. To this end the country has been divided into hydrologic units based on drainage directions derived from a digital terrain model. Moreover the population of each unit has been estimated from census data downscaled to 1 km x 1 km resolution via remotely sensed geomorphological information (LandScan project). The model directly accounts for the role of rainfall patterns in driving the seasonality of cholera outbreaks. The two main outbreaks in fact occurred during the rainy seasons (October and May) when extensive floodings severely worsened the sanitation conditions and, in turn, raised the risk of infection. The model capability to reproduce the spatiotemporal features of the epidemic up to date grants robustness to the foreseen future development. To this end, we generate realistic scenario of future precipitation in order to forecast possible epidemic paths up to the end of the 2013. In this context, the duration of acquired immunity, a hotly debated topic in the scientific community, emerges as a controlling factor for progression of the epidemic in the near future. The framework presented here can straightforwardly be used to evaluate the effectiveness of alternative intervention strategies like mass vaccinations
Fractional-order mathematical model of an irrigation main canal pool
Directory of Open Access Journals (Sweden)
Shlomi N. Calderon-Valdez
2015-09-01
Full Text Available In this paper a fractional order model for an irrigation main canal is proposed. It is based on the experiments developed in a laboratory prototype of a hydraulic canal and the application of a direct system identification methodology. The hydraulic processes that take place in this canal are equivalent to those that occur in real main irrigation canals and the results obtained here can therefore be easily extended to real canals. The accuracy of the proposed fractional order model is compared by deriving two other integer-order models of the canal of a complexity similar to that proposed here. The parameters of these three mathematical models have been identified by minimizing the Integral Square Error (ISE performance index existing between the models and the real-time experimental data obtained from the canal prototype. A comparison of the performances of these three models shows that the fractional-order model has the lowest error and therefore the higher accuracy. Experiments showed that our model outperformed the accuracy of the integer-order models by about 25%, which is a significant improvement as regards to capturing the canal dynamics.
Chronic Progressive Neurodegeneration in a transgenic mouse model of Prion disease
Directory of Open Access Journals (Sweden)
Nina Fainstein
2016-11-01
Full Text Available Neurodegenerative diseases present pathologically with progressive structural destruction of neurons and accumulation of mis-folded proteins specific for each condition leading to brain atrophy and functional disability. Many animal models exert deposition of pathogenic protein without accompanying neurodegeneration pattern. The lack of a comprehensive model hinders the efforts to develop treatment. We performed longitudinal quantification of cellular, neuronal and synaptic density, as well as of neurogenesis in brains of mice, mimicking for genetic Creutzfeldt-Jacob disease as compared to age matched wild type mice. Mice exhibited a neurodegenerative process indicated by progressive reduction in cortical neurons and synapses, starting at age of 4-6 months, in accordance with neurologic disability. This was accompanied by significant decrease in subventricular/subependymal zone neurogenesis. Although increased hippocampal neurogenesis was detected in mice, a neurodegenerative process of CA1 and CA3 regions associated with impaired hippocampal-dependent memory function was observed. In conclusion, mice exhibit pathological neurodegeneration concomitant with progressive neurological disease, indicating these mice can serve as a model for neurodegenerative diseases.
Chronic Progressive Neurodegeneration in a Transgenic Mouse Model of Prion Disease.
Fainstein, Nina; Dori, Dvir; Frid, Kati; Fritz, Alexa T; Shapiro, Ilona; Gabizon, Ruth; Ben-Hur, Tamir
2016-01-01
Neurodegenerative diseases present pathologically with progressive structural destruction of neurons and accumulation of mis-folded proteins specific for each condition leading to brain atrophy and functional disability. Many animal models exert deposition of pathogenic proteins without an accompanying neurodegeneration pattern. The lack of a comprehensive model hinders efforts to develop treatment. We performed longitudinal quantification of cellular, neuronal and synaptic density, as well as of neurogenesis in brains of mice mimicking for genetic Creutzfeldt-Jacob disease as compared to age-matched wild-type mice. Mice exhibited a neurodegenerative process of progressive reduction in cortical neurons and synapses starting at age of 4-6 months, in accord with neurologic disability. This was accompanied by significant decrease in subventricular/subependymal zone neurogenesis. Although increased hippocampal neurogenesis was detected in mice, a neurodegenerative process of CA1 and CA3 regions associated with impaired hippocampal-dependent memory function was observed. In conclusion, mice exhibit pathological neurodegeneration concomitant with neurological disease progression, indicating these mice can serve as a model for neurodegenerative diseases.
Fractional-Order Nonlinear Systems Modeling, Analysis and Simulation
Petráš, Ivo
2011-01-01
"Fractional-Order Nonlinear Systems: Modeling, Analysis and Simulation" presents a study of fractional-order chaotic systems accompanied by Matlab programs for simulating their state space trajectories, which are shown in the illustrations in the book. Description of the chaotic systems is clearly presented and their analysis and numerical solution are done in an easy-to-follow manner. Simulink models for the selected fractional-order systems are also presented. The readers will understand the fundamentals of the fractional calculus, how real dynamical systems can be described using fractional derivatives and fractional differential equations, how such equations can be solved, and how to simulate and explore chaotic systems of fractional order. The book addresses to mathematicians, physicists, engineers, and other scientists interested in chaos phenomena or in fractional-order systems. It can be used in courses on dynamical systems, control theory, and applied mathematics at graduate or postgraduate level. ...
A variable-order fractal derivative model for anomalous diffusion
Directory of Open Access Journals (Sweden)
Liu Xiaoting
2017-01-01
Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.
Data-driven models of dominantly-inherited Alzheimer's disease progression.
Oxtoby, Neil P; Young, Alexandra L; Cash, David M; Benzinger, Tammie L S; Fagan, Anne M; Morris, John C; Bateman, Randall J; Fox, Nick C; Schott, Jonathan M; Alexander, Daniel C
2018-03-22
Dominantly-inherited Alzheimer's disease is widely hoped to hold the key to developing interventions for sporadic late onset Alzheimer's disease. We use emerging techniques in generative data-driven disease progression modelling to characterize dominantly-inherited Alzheimer's disease progression with unprecedented resolution, and without relying upon familial estimates of years until symptom onset. We retrospectively analysed biomarker data from the sixth data freeze of the Dominantly Inherited Alzheimer Network observational study, including measures of amyloid proteins and neurofibrillary tangles in the brain, regional brain volumes and cortical thicknesses, brain glucose hypometabolism, and cognitive performance from the Mini-Mental State Examination (all adjusted for age, years of education, sex, and head size, as appropriate). Data included 338 participants with known mutation status (211 mutation carriers in three subtypes: 163 PSEN1, 17 PSEN2, and 31 APP) and a baseline visit (age 19-66; up to four visits each, 1.1 ± 1.9 years in duration; spanning 30 years before, to 21 years after, parental age of symptom onset). We used an event-based model to estimate sequences of biomarker changes from baseline data across disease subtypes (mutation groups), and a differential equation model to estimate biomarker trajectories from longitudinal data (up to 66 mutation carriers, all subtypes combined). The two models concur that biomarker abnormality proceeds as follows: amyloid deposition in cortical then subcortical regions (∼24 ± 11 years before onset); phosphorylated tau (17 ± 8 years), tau and amyloid-β changes in cerebrospinal fluid; neurodegeneration first in the putamen and nucleus accumbens (up to 6 ± 2 years); then cognitive decline (7 ± 6 years), cerebral hypometabolism (4 ± 4 years), and further regional neurodegeneration. Our models predicted symptom onset more accurately than predictions that used familial estimates: root mean squared error of 1
Ordering of diagnostic information in encoded medical images. Accuracy progression
Przelaskowski, A.; Jóźwiak, R.; Krzyżewski, T.; Wróblewska, A.
2008-03-01
A concept of diagnostic accuracy progression for embedded coding of medical images was presented. Implementation of JPEG2000 encoder with a modified PCRD optimization algorithm was realized and initially verified as a tool for accurate medical image streaming. Mean square error as a distortion measure was replaced by other numerical measures to revise quality progression according to diagnostic importance of successively encoded image information. A faster increment of image diagnostic importance during reconstruction of initial packets of code stream was reached. Modified Jasper code was initially tested on a set of mammograms containing clusters of microcalcifications and malignant masses, and other radiograms. Teleradiologic applications were considered as the first area of interests.
Aeroelastic simulation using CFD based reduced order models
International Nuclear Information System (INIS)
Zhang, W.; Ye, Z.; Li, H.; Yang, Q.
2005-01-01
This paper aims at providing an accurate and efficient method for aeroelastic simulation. System identification is used to get the reduced order models of unsteady aerodynamics. Unsteady Euler codes are used to compute the output signals while 3211 multistep input signals are utilized. LS(Least Squares) method is used to estimate the coefficients of the input-output difference model. The reduced order models are then used in place of the unsteady CFD code for aeroelastic simulation. The aeroelastic equations are marched by an improved 4th order Runge-Kutta method that only needs to compute the aerodynamic loads one time at every time step. The computed results agree well with that of the direct coupling CFD/CSD methods. The computational efficiency is improved 1∼2 orders while still retaining the high accuracy. A standard aeroelastic computing example (isogai wing) with S type flutter boundary is computed and analyzed. It is due to the system has more than one neutral points at the Mach range of 0.875∼0.9. (author)
Reverse time migration by Krylov subspace reduced order modeling
Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali
2018-04-01
Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.
Vishik, I. M.
2018-06-01
In the course of seeking the microscopic mechanism of superconductivity in cuprate high temperature superconductors, the pseudogap phase— the very abnormal ‘normal’ state on the hole-doped side— has proven to be as big of a quandary as superconductivity itself. Angle-resolved photoemission spectroscopy (ARPES) is a powerful tool for assessing the momentum-dependent phenomenology of the pseudogap, and recent technological developments have permitted a more detailed understanding. This report reviews recent progress in understanding the relationship between superconductivity and the pseudogap, the Fermi arc phenomena, and the relationship between charge order and pseudogap from the perspective of ARPES measurements.
Finite Progressive Planning for the Assembly Process in Footwear
Reyes, John; Aldás, Darwin; Salazar, Edisson; Armendáriz, Evelyn; Álvarez, Kevin; Núñez, José; García, Mario
2017-06-01
The scheduling of the operations of a manufacturing system is recognized for its efficiency in establishing a characteristic rate of production based on the forecasting of the ending date of an order. However, progressive planning focused on the footwear industries has not been studied in detail, since it is limited by the use of machines and supply according to the demand of the production line, whose development is based on just in time. The study proposes a finite progressive planning model in the area of footwear assembly that begins with analysis of the demand and identification of manufacturing constraints in order to establish an optimal ordering sequence. The results show manufacturing requirements through production orders that automatically determine production shifts per order, through experimentation of scenarios, the 25% increase in productivity indicators and a 31% improvement in efficiency are established. This improvement represents higher benefits for the industrial sector when establishing planning in the workplace.
Estrada, Fernando
2010-01-01
This article describes the argumentative structure of Hayek on the relationship between power to tax and the progressive tax. It is observed throughout its work giving special attention to two works: The Constitution of Liberty (1959) and Law, Legislation and Liberty, vol3; The Political Order of Free People, 1979) Hayek describes one of the arguments most complete information bout SFP progressive tax systems (progressive tax). According to the author the history of the tax progressive system...
A Segmented Signal Progression Model for the Modern Streetcar System
Directory of Open Access Journals (Sweden)
Baojie Wang
2015-01-01
Full Text Available This paper is on the purpose of developing a segmented signal progression model for modern streetcar system. The new method is presented with the following features: (1 the control concept is based on the assumption of only one streetcar line operating along an arterial under a constant headway and no bandwidth demand for streetcar system signal progression; (2 the control unit is defined as a coordinated intersection group associated with several streetcar stations, and the control joints must be streetcar stations; (3 the objective function is built to ensure the two-way streetcar arrival times distributing within the available time of streetcar phase; (4 the available time of streetcar phase is determined by timing schemes, intersection structures, track locations, streetcar speeds, and vehicular accelerations; (5 the streetcar running speed is constant separately whether it is in upstream or downstream route; (6 the streetcar dwell time is preset according to historical data distribution or charging demand. The proposed method is experimentally examined in Hexi New City Streetcar Project in Nanjing, China. In the experimental results, the streetcar system operation and the progression impacts are shown to affect transit and vehicular traffic. The proposed model presents promising outcomes through the design of streetcar system segmented signal progression, in terms of ensuring high streetcar system efficiency and minimizing negative impacts on transit and vehicular traffic.
Algebraic Specifications, Higher-order Types and Set-theoretic Models
DEFF Research Database (Denmark)
Kirchner, Hélène; Mosses, Peter David
2001-01-01
, and power-sets. This paper presents a simple framework for algebraic specifications with higher-order types and set-theoretic models. It may be regarded as the basis for a Horn-clause approximation to the Z framework, and has the advantage of being amenable to prototyping and automated reasoning. Standard......In most algebraic specification frameworks, the type system is restricted to sorts, subsorts, and first-order function types. This is in marked contrast to the so-called model-oriented frameworks, which provide higer-order types, interpreted set-theoretically as Cartesian products, function spaces...... set-theoretic models are considered, and conditions are given for the existence of initial reduct's of such models. Algebraic specifications for various set-theoretic concepts are considered....
Reduced order modeling of flashing two-phase jets
Energy Technology Data Exchange (ETDEWEB)
Gurecky, William, E-mail: william.gurecky@utexas.edu; Schneider, Erich, E-mail: eschneider@mail.utexas.edu; Ballew, Davis, E-mail: davisballew@utexas.edu
2015-12-01
Highlights: • Accident simulation requires ability to quickly predict two-phase flashing jet's damage potential. • A reduced order modeling methodology informed by experimental or computational data is described. • Zone of influence volumes are calculated for jets of various upstream thermodynamic conditions. - Abstract: In the event of a Loss of Coolant Accident (LOCA) in a pressurized water reactor, the escaping coolant produces a highly energetic flashing jet with the potential to damage surrounding structures. In LOCA analysis, the goal is often to evaluate many break scenarios in a Monte Carlo style simulation to evaluate the resilience of a reactor design. Therefore, in order to quickly predict the damage potential of flashing jets, it is of interest to develop a reduced order model that relates the damage potential of a jet to the pressure and temperature upstream of the break and the distance from the break to a given object upon which the jet is impinging. This work presents framework for producing a Reduced Order Model (ROM) that may be informed by measured data, Computational Fluid Dynamics (CFD) simulations, or a combination of both. The model is constructed by performing regression analysis on the pressure field data, allowing the impingement pressure to be quickly reconstructed for any given upstream thermodynamic condition within the range of input data. The model is applicable to both free and fully impinging two-phase flashing jets.
Reduced Order Modeling in General Relativity
Tiglio, Manuel
2014-03-01
Reduced Order Modeling is an emerging yet fast developing filed in gravitational wave physics. The main goals are to enable fast modeling and parameter estimation of any detected signal, along with rapid matched filtering detecting. I will focus on the first two. Some accomplishments include being able to replace, with essentially no lost of physical accuracy, the original models with surrogate ones (which are not effective ones, that is, they do not simplify the physics but go on a very different track, exploiting the particulars of the waveform family under consideration and state of the art dimensional reduction techniques) which are very fast to evaluate. For example, for EOB models they are at least around 3 orders of magnitude faster than solving the original equations, with physically equivalent results. For numerical simulations the speedup is at least 11 orders of magnitude. For parameter estimation our current numbers are about bringing ~100 days for a single SPA inspiral binary neutron star Bayesian parameter estimation analysis to under a day. More recently, it has been shown that the full precessing problem for, say, 200 cycles, can be represented, through some new ideas, by a remarkably compact set of carefully chosen reduced basis waveforms (~10-100, depending on the accuracy requirements). I will highlight what I personally believe are the challenges to face next in this subarea of GW physics and where efforts should be directed. This talk will summarize work in collaboration with: Harbir Antil (GMU), Jonathan Blackman (Caltech), Priscila Canizares (IoA, Cambridge, UK), Sarah Caudill (UWM), Jonathan Gair (IoA. Cambridge. UK), Scott Field (UMD), Chad R. Galley (Caltech), Frank Herrmann (Germany), Han Hestahven (EPFL, Switzerland), Jason Kaye (Brown, Stanford & Courant). Evan Ochsner (UWM), Ricardo Nochetto (UMD), Vivien Raymond (LIGO, Caltech), Rory Smith (LIGO, Caltech) Bela Ssilagyi (Caltech) and MT (UMD & Caltech).
Partial-Order Reduction for GPU Model Checking
Neele, T.; Wijs, A.; Bosnacki, D.; van de Pol, Jan Cornelis; Artho, C; Legay, A.; Peled, D.
2016-01-01
Model checking using GPUs has seen increased popularity over the last years. Because GPUs have a limited amount of memory, only small to medium-sized systems can be verified. For on-the-fly explicit-state model checking, we improve memory efficiency by applying partial-order reduction. We propose
Validity testing of third-order nonlinear models for synchronous generators
Energy Technology Data Exchange (ETDEWEB)
Arjona, M.A. [Division de Estudios de Posgrado e Investigacion, Instituto Tecnologico de La Laguna Torreon, Coah. (Mexico); Escarela-Perez, R. [Universidad Autonoma Metropolitana - Azcapotzalco, Departamento de Energia, Av. San Pablo 180, Col. Reynosa, C.P. 02200 (Mexico); Espinosa-Perez, G. [Division de Estudios Posgrado de la Facultad de Ingenieria Universidad Nacional Autonoma de Mexico (Mexico); Alvarez-Ramirez, J. [Universidad Autonoma Metropolitana -Iztapalapa, Division de Ciencias Basicas e Ingenieria (Mexico)
2009-06-15
Third-order nonlinear models are commonly used in control theory for the analysis of the stability of both open-loop and closed-loop synchronous machines. However, the ability of these models to describe the electrical machine dynamics has not been tested experimentally. This work focuses on this issue by addressing the parameters identification problem for third-order models for synchronous generators. For a third-order model describing the dynamics of power angle {delta}, rotor speed {omega} and quadrature axis transient EMF E{sub q}{sup '}, it is shown that the parameters cannot be identified because of the effects of the unknown initial condition of E{sub q}{sup '}. To avoid this situation, a model that incorporates the measured electrical power dynamics is considered, showing that state measurements guarantee the identification of the model parameters. Data obtained from a 7 kVA lab-scale synchronous generator and from a 150 MVA finite-element simulation were used to show that, at least for the worked examples, the estimated parameters display only moderate variations over the operating region. This suggests that third-order models can suffice to describe the main dynamical features of synchronous generators, and that third-order models can be used to design and tune power system stabilizers and voltage regulators. (author)
Lagrangian generic second order traffic flow models for node
Directory of Open Access Journals (Sweden)
Asma Khelifi
2018-02-01
Full Text Available This study sheds light on higher order macroscopic traffic flow modeling on road networks, thanks to the generic second order models (GSOM family which embeds a myriad of traffic models. It has been demonstrated that such higher order models are easily solved in Lagrangian coordinates which are compatible with both microscopic and macroscopic descriptions. The generalized GSOM model is reformulated in the Lagrangian coordinate system to develop a more efficient numerical method. The difficulty in applying this approach on networks basically resides in dealing with node dynamics. Traffic flow characteristics at node are different from that on homogeneous links. Different geometry features can lead to different critical research issues. For instance, discontinuity in traffic stream can be an important issue for traffic signal operations, while capacity drop may be crucial for lane-merges. The current paper aims to establish and analyze a new adapted node model for macroscopic traffic flow models by applying upstream and downstream boundary conditions on the Lagrangian coordinates in order to perform simulations on networks of roads, and accompanying numerical method. The internal node dynamics between upstream and downstream links are taken into account of the node model. Therefore, a numerical example is provided to underscore the efficiency of this approach. Simulations show that the discretized node model yields accurate results. Additional kinematic waves and contact discontinuities are induced by the variation of the driver attribute.
Multi-skyrmion solutions of a sixth order Skyrme model
International Nuclear Information System (INIS)
Floratos, I.
2001-08-01
In this thesis, we study some of the classical properties of an extension of the Skyrme model defined by adding a sixth order derivative term to the Lagrangian. In chapter 1, we review the physical as well as the mathematical motivation behind the study of the Skyrme model and in chapter 2, we give a brief summary of various extended Skyrme models that have been proposed over the last few years. We then define a new sixth order Skyrme model by introducing a dimensionless parameter λ that denotes the mixing between the two higher order terms, the Skyrme term and the sixth order term. In chapter 3 we compute numerically the multi-skyrmion solutions of this extended model and show that they have the same symmetries with the usual skyrmion solutions. In addition, we analyse the dependence of the energy and radius of these classical solutions with respect to the coupling constant λ. We compare our results with experimental data and determine whether this modified model can provide us with better theoretical predictions than the original one. In chapter 4, we use the rational map ansatz, introduced by Houghton, Manton and Sutcliffe, to approximate minimum energy multi-skyrmion solutions with B ≤ 9 of the SU(2) model and with B ≤ 6 of the SU(3) model. We compare our results with the ones obtained numerically and show that the rational map ansatz works just as well for the generalised model as for the pure Skyrme model, at least for B ≤ 5. In chapter 5, we use a generalisation of the rational map ansatz, introduced by loannidou, Piette and Zakrzewski, to construct analytically some topologically non-trivial solutions of the extended model in SU(3). These solutions are spherically symmetric and some of them can be interpreted as bound states of skyrmions. Finally, we use the same ansatz to construct low energy configurations of the SU(N) sixth order Skyrme model. (author)
Ordering transitions induced by Coulomb interactions
International Nuclear Information System (INIS)
Rovere, M.; Senatore, G.; Tosi, M.P.
1988-11-01
We briefly review recent progress in treating phase transitions to ordered states driven by Coulomb interactions. Wigner crystallization of the one-component plasma, in the degenerate Fermi limit and in the classical limit, is the foremost example and developments in its theory are discussed in some detail. Attention is also given to quasi-twodimensional realizations of the plasma model in the laboratory. The usefulness of these ideas in relation to freezing and ordering transitions is illustrated with reference to alkali metals, elemental and polar semiconductors, and various types of ionic systems (molten salts, colloidal suspensions and astrophysical plasmas). (author). 70 refs, 5 figs
Directory of Open Access Journals (Sweden)
Peter Bacchetti
Full Text Available BACKGROUND: Fibrosis stages from liver biopsies reflect liver damage from hepatitis C infection, but analysis is challenging due to their ordered but non-numeric nature, infrequent measurement, misclassification, and unknown infection times. METHODS: We used a non-Markov multistate model, accounting for misclassification, with multiple imputation of unknown infection times, applied to 1062 participants of whom 159 had multiple biopsies. Odds ratios (OR quantified the estimated effects of covariates on progression risk at any given time. RESULTS: Models estimated that progression risk decreased the more time participants had already spent in the current stage, African American race was protective (OR 0.75, 95% confidence interval 0.60 to 0.95, p = 0.018, and older current age increased risk (OR 1.33 per decade, 95% confidence interval 1.15 to 1.54, p = 0.0002. When controlled for current age, older age at infection did not appear to increase risk (OR 0.92 per decade, 95% confidence interval 0.47 to 1.79, p = 0.80. There was a suggestion that co-infection with human immunodeficiency virus increased risk of progression in the era of highly active antiretroviral treatment beginning in 1996 (OR 2.1, 95% confidence interval 0.97 to 4.4, p = 0.059. Other examined risk factors may influence progression risk, but evidence for or against this was weak due to wide confidence intervals. The main results were essentially unchanged using different assumed misclassification rates or imputation of age of infection. DISCUSSION: The analysis avoided problems inherent in simpler methods, supported the previously suspected protective effect of African American race, and suggested that current age rather than age of infection increases risk. Decreasing risk of progression with longer time already spent in a stage was also previously found for post-transplant progression. This could reflect varying disease activity, with recent progression indicating
Partial Orders and Fully Abstract Models for Concurrency
DEFF Research Database (Denmark)
Engberg, Uffe Henrik
1990-01-01
In this thesis sets of labelled partial orders are employed as fundamental mathematical entities for modelling nondeterministic and concurrent processes thereby obtaining so-called noninterleaving semantics. Based on different closures of sets of labelled partial orders, simple algebraic language...
Directory of Open Access Journals (Sweden)
Renxin Xiao
2016-03-01
Full Text Available In order to properly manage lithium-ion batteries of electric vehicles (EVs, it is essential to build the battery model and estimate the state of charge (SOC. In this paper, the fractional order forms of Thevenin and partnership for a new generation of vehicles (PNGV models are built, of which the model parameters including the fractional orders and the corresponding resistance and capacitance values are simultaneously identified based on genetic algorithm (GA. The relationships between different model parameters and SOC are established and analyzed. The calculation precisions of the fractional order model (FOM and integral order model (IOM are validated and compared under hybrid test cycles. Finally, extended Kalman filter (EKF is employed to estimate the SOC based on different models. The results prove that the FOMs can simulate the output voltage more accurately and the fractional order EKF (FOEKF can estimate the SOC more precisely under dynamic conditions.
Higher-order RANS turbulence models for separated flows
National Aeronautics and Space Administration — Higher-order Reynolds-averaged Navier-Stokes (RANS) models are developed to overcome the shortcomings of second-moment RANS models in predicting separated flows....
Modelling the Progression of Competitive Performance of an Academy's Soccer Teams.
Malcata, Rita M; Hopkins, Will G; Richardson, Scott
2012-01-01
Progression of a team's performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent) with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%). Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%). Aspire experienced a small home-ground advantage of 16% (-5 to 41%), whereas opposition teams experienced 31% (7 to 60%) on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents' scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%), small over two years (15%, -8 to 44%), but unclear over >2 years. In conclusion, the generalized mixed model
Progress in tritium retention and release modeling for ceramic breeders
International Nuclear Information System (INIS)
Raffray, A.R.; Federici, G.; Billone, M.C.; Tanaka, S.
1994-01-01
Tritium behavior in ceramic breeder blankets is a key design issue for this class of blanket because of its impact on safety and fuel self-sufficiency. Over the past 10-15 years, substantial theoretical and experimental efforts have been dedicated world-wide to develop a better understanding of tritium transport in ceramic breeders. Models that are available today seem to cover reasonably well all the key physical transport and trapping mechanisms. They have allowed for reasonable interpretation and reproduction of experimental data and have helped in pointing out deficiencies in material property data base, in providing guidance for future experiments, and in analyzing blanket tritium behavior. This paper highlights the progress in tritium modeling over the last decade. Key tritium transport mechanisms are briefly described along with the more recent and sophisticated models developed to help understand them. Recent experimental data are highlighted and model calibration and validation discussed. Finally, example applications to blanket cases are shown as illustration of progress in the prediction of ceramic breeder blanket tritium inventory
Composite symmetry-protected topological order and effective models
Nietner, A.; Krumnow, C.; Bergholtz, E. J.; Eisert, J.
2017-12-01
Strongly correlated quantum many-body systems at low dimension exhibit a wealth of phenomena, ranging from features of geometric frustration to signatures of symmetry-protected topological order. In suitable descriptions of such systems, it can be helpful to resort to effective models, which focus on the essential degrees of freedom of the given model. In this work, we analyze how to determine the validity of an effective model by demanding it to be in the same phase as the original model. We focus our study on one-dimensional spin-1 /2 systems and explain how nontrivial symmetry-protected topologically ordered (SPT) phases of an effective spin-1 model can arise depending on the couplings in the original Hamiltonian. In this analysis, tensor network methods feature in two ways: on the one hand, we make use of recent techniques for the classification of SPT phases using matrix product states in order to identify the phases in the effective model with those in the underlying physical system, employing Künneth's theorem for cohomology. As an intuitive paradigmatic model we exemplify the developed methodology by investigating the bilayered Δ chain. For strong ferromagnetic interlayer couplings, we find the system to transit into exactly the same phase as an effective spin-1 model. However, for weak but finite coupling strength, we identify a symmetry broken phase differing from this effective spin-1 description. On the other hand, we underpin our argument with a numerical analysis making use of matrix product states.
Optimal inventory management and order book modeling
Baradel, Nicolas
2018-02-16
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.
Heisenberg spin glass experiments and the chiral ordering scenario
International Nuclear Information System (INIS)
Campbell, Ian A.; Petit, Dorothee C.M.C.
2010-01-01
An overview is given of experimental data on Heisenberg spin glass materials so as to make detailed comparisons with numerical results on model Heisenberg spin glasses, with particular reference to the chiral driven ordering transition scenario due to Kawamura and collaborators. On weak anisotropy systems, experiments show critical exponents which are very similar to those estimated numerically for the model Heisenberg chiral ordering transition but which are quite different from those at Ising spin glass transitions. Again on weak anisotropy Heisenberg spin glasses, experimental torque data show well defined in-field transverse ordering transitions up to strong applied fields, in contrast to Ising spin glasses where fields destroy ordering. When samples with stronger anisotropies are studied, critical and in-field behavior tend progressively towards the Ising limit. It can be concluded that the essential physics of laboratory Heisenberg spin glasses mirrors that of model Heisenberg spin glasses, where chiral ordering has been demonstrated numerically. (author)
Interleukin-1 may link helplessness-hopelessness with cancer progression: a proposed model.
Argaman, Miriam; Gidron, Yori; Ariad, Shmuel
2005-01-01
A model of the relations between psychological factors and cancer progression should include brain and systemic components and their link with critical cellular stages in cancer progression. We present a psychoneuroimmunological (PNI) model that links helplessness-hopelessness (HH) with cancer progression via interleukin-1beta (IL-1beta). IL-1beta was elevated in the brain following exposure to inescapable shock, and HH was minimized by antagonizing cerebral IL-1beta. Elevated cerebral IL-1beta increased cancer metastasis in animals. Inescapable shock was associated with systemic elevations of IL-1beta and peripheral IL-1beta was associated with escape from apoptosis, angiogenesis, and metastasis. Involvement of the sympathetic nervous system and the hypothalamic-pituitary-adrenal axis are discussed. Future studies need to identify the role of additional factors in this PNI pathway.
Reduced-order modelling of wind turbines
Elkington, K.; Slootweg, J.G.; Ghandhari, M.; Kling, W.L.; Ackermann, T.
2012-01-01
In this chapter power system dynamics simulation(PSDS) isused to study the dynamics of large-scale power systems. It is necessary to incorporate models of wind turbine generating systems into PSDS software packages in order to analyse the impact of high wind power penetration on electrical power
High-order finite difference solution for 3D nonlinear wave-structure interaction
DEFF Research Database (Denmark)
Ducrozet, Guillaume; Bingham, Harry B.; Engsig-Karup, Allan Peter
2010-01-01
This contribution presents our recent progress on developing an efficient fully-nonlinear potential flow model for simulating 3D wave-wave and wave-structure interaction over arbitrary depths (i.e. in coastal and offshore environment). The model is based on a high-order finite difference scheme O...
Is organizational progress in the EFQM model related to employee satisfaction?
Matthies-Baraibar, Carmen; Arcelay-Salazar, Andoni; Cantero-González, David; Colina-Alonso, Alberto; García-Urbaneja, Marbella; González-Llinares, Rosa María; Letona-Aranburu, Jon; Martínez-Carazo, Catalina; Mateos-Del Pino, Maider; Nuño-Solinís, Roberto; Olaetxea-Urizar, Esther; de la Rica-Giménez, José Antonio; Rodríguez-González, María Angeles; Dabouza-Acebal, Silvia
2014-10-24
To determine whether there is greater employee satisfaction in organisations that have made more progress in implementation of the European Foundation for Quality Management (EFQM) model. A series of cross-sectional studies (one for each assessment cycle) comparing staff satisfaction survey results between groups of healthcare organisations by degree of implementation of the EFQM model (assessed in terms of external recognition of management quality in each organisation). 30 healthcare organisations including hospitals, primary care and mental health providers in Osakidetza, the Basque public health service. Employees of 30 Osakidetza organisations. Progress in implementation of EFQM model. Scores in 9 dimensions of employee satisfaction from questionnaires administered in healthcare organisations in 4 assessment cycles between 2001 and 2010. Comparing satisfaction results in organisations granted Gold or Silver Q Awards and those without this type of external recognition, we found statistically significant differences in the dimensions of training and internal communication. Then, comparing recipients of Gold Q Awards with those with no Q Certification, differences in leadership style and in policy and strategy also emerged as significant. Progress of healthcare organisations in the implementation of the EFQM Excellence Model is associated with increases in their employee satisfaction in dimensions that can be managed at the level of each organisation, while dimensions in which no statistically significant differences were found represent common organisational elements with little scope for self-management.
MODELLING THE PROGRESSION OF COMPETITIVE PERFORMANCE OF AN ACADEMY'S SOCCER TEAMS
Directory of Open Access Journals (Sweden)
Rita M. Malcata
2012-09-01
Full Text Available Progression of a team's performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%. Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%. Aspire experienced a small home-ground advantage of 16% (-5 to 41%, whereas opposition teams experienced 31% (7 to 60% on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents' scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%, small over two years (15%, -8 to 44%, but unclear over >2 years. In conclusion, the generalized
Model order reduction techniques with applications in finite element analysis
Qu, Zu-Qing
2004-01-01
Despite the continued rapid advance in computing speed and memory the increase in the complexity of models used by engineers persists in outpacing them. Even where there is access to the latest hardware, simulations are often extremely computationally intensive and time-consuming when full-blown models are under consideration. The need to reduce the computational cost involved when dealing with high-order/many-degree-of-freedom models can be offset by adroit computation. In this light, model-reduction methods have become a major goal of simulation and modeling research. Model reduction can also ameliorate problems in the correlation of widely used finite-element analyses and test analysis models produced by excessive system complexity. Model Order Reduction Techniques explains and compares such methods focusing mainly on recent work in dynamic condensation techniques: - Compares the effectiveness of static, exact, dynamic, SEREP and iterative-dynamic condensation techniques in producing valid reduced-order mo...
Progress towards localization in the attractive Hubbard model
Morong, W.; Xu, W.; Demarco, B.
2017-04-01
The interplay between fermionic superfluidity and disorder is a topic of long-standing interest that has recently come within reach of ultracold gas experiments. Outstanding questions include the fate of Cooper pairs in a localized superfluid and the effect of disorder on the superfluid transition temperature. We report progress on tackling this problem using a realization of the Hubbard model with attractive interactions. Our system consists of two spin states of fermionic potassium-40 trapped in a cubic optical lattice. Disorder is introduced using an optical speckle potential, and interactions are controlled via a Feshbach resonance. We study the binding and unbinding of Cooper pairs in this system using rf spectroscopy, changes in Tc by measuring the condensate fraction, and transport properties by observing the response to an applied impulse. We will discuss progress towards these measurements.
The second-order decomposition model of nonlinear irregular waves
DEFF Research Database (Denmark)
Yang, Zhi Wen; Bingham, Harry B.; Li, Jin Xuan
2013-01-01
into the first- and the second-order super-harmonic as well as the second-order sub-harmonic components by transferring them into an identical Fourier frequency-space and using a Newton-Raphson iteration method. In order to evaluate the present model, a variety of monochromatic waves and the second...
Transport coefficient computation based on input/output reduced order models
Hurst, Joshua L.
The guiding purpose of this thesis is to address the optimal material design problem when the material description is a molecular dynamics model. The end goal is to obtain a simplified and fast model that captures the property of interest such that it can be used in controller design and optimization. The approach is to examine model reduction analysis and methods to capture a specific property of interest, in this case viscosity, or more generally complex modulus or complex viscosity. This property and other transport coefficients are defined by a input/output relationship and this motivates model reduction techniques that are tailored to preserve input/output behavior. In particular Singular Value Decomposition (SVD) based methods are investigated. First simulation methods are identified that are amenable to systems theory analysis. For viscosity, these models are of the Gosling and Lees-Edwards type. They are high order nonlinear Ordinary Differential Equations (ODEs) that employ Periodic Boundary Conditions. Properties can be calculated from the state trajectories of these ODEs. In this research local linear approximations are rigorously derived and special attention is given to potentials that are evaluated with Periodic Boundary Conditions (PBC). For the Gosling description LTI models are developed from state trajectories but are found to have limited success in capturing the system property, even though it is shown that full order LTI models can be well approximated by reduced order LTI models. For the Lees-Edwards SLLOD type model nonlinear ODEs will be approximated by a Linear Time Varying (LTV) model about some nominal trajectory and both balanced truncation and Proper Orthogonal Decomposition (POD) will be used to assess the plausibility of reduced order models to this system description. An immediate application of the derived LTV models is Quasilinearization or Waveform Relaxation. Quasilinearization is a Newton's method applied to the ODE operator
A parametric model order reduction technique for poroelastic finite element models.
Lappano, Ettore; Polanz, Markus; Desmet, Wim; Mundo, Domenico
2017-10-01
This research presents a parametric model order reduction approach for vibro-acoustic problems in the frequency domain of systems containing poroelastic materials (PEM). The method is applied to the Finite Element (FE) discretization of the weak u-p integral formulation based on the Biot-Allard theory and makes use of reduced basis (RB) methods typically employed for parametric problems. The parametric reduction is obtained rewriting the Biot-Allard FE equations for poroelastic materials using an affine representation of the frequency (therefore allowing for RB methods) and projecting the frequency-dependent PEM system on a global reduced order basis generated with the proper orthogonal decomposition instead of standard modal approaches. This has proven to be better suited to describe the nonlinear frequency dependence and the strong coupling introduced by damping. The methodology presented is tested on two three-dimensional systems: in the first experiment, the surface impedance of a PEM layer sample is calculated and compared with results of the literature; in the second, the reduced order model of a multilayer system coupled to an air cavity is assessed and the results are compared to those of the reference FE model.
X-ray scattering studies of non-equilibrium ordering processes
International Nuclear Information System (INIS)
Nagler, S.E.
1991-01-01
We report on the progress of the project entitled ''X-ray Scattering Studies of Non-Equilibrium Ordering Processes.'' The past year has seen continued progress in the study of kinetic effects in metallic binary alloys and polymers. In addition, work has begun on a low dimensional CDW system: blue bronze. A sample chamber has been constructed to perform small angle neutron scattering measurements on a model quantum system with phase separation: solid He3/He4. Work is continuing on magnetic systems. Planned future experiments include an investigation of crystallization in Rubidium
A model to predict progression in brain-injured patients.
Tommasino, N; Forteza, D; Godino, M; Mizraji, R; Alvarez, I
2014-11-01
The study of brain death (BD) epidemiology and the acute brain injury (ABI) progression profile is important to improve public health programs, organ procurement strategies, and intensive care unit (ICU) protocols. The purpose of this study was to analyze the ABI progression profile among patients admitted to ICUs with a Glasgow Coma Score (GCS) ≤8, as well as establishing a prediction model of probability of death and BD. This was a retrospective analysis of prospective data that included all brain-injured patients with GCS ≤8 admitted to a total of four public and private ICUs in Uruguay (N = 1447). The independent predictor factors of death and BD were studied using logistic regression analysis. A hierarchical model consisting of 2 nested logit regression models was then created. With these models, the probabilities of death, BD, and death by cardiorespiratory arrest were analyzed. In the first regression, we observed that as the GCS decreased and age increased, the probability of death rose. Each additional year of age increased the probability of death by 0.014. In the second model, however, BD risk decreased with each year of age. The presence of swelling, mass effect, and/or space-occupying lesion increased BD risk for the same given GCS. In the presence of injuries compatible with intracranial hypertension, age behaved as a protective factor that reduced the probability of BD. Based on the analysis of the local epidemiology, a model to predict the probability of death and BD can be developed. The organ potential donation of a country, region, or hospital can be predicted on the basis of this model, customizing it to each specific situation.
Low-order aeroelastic models of wind turbines for controller design
DEFF Research Database (Denmark)
Sønderby, Ivan Bergquist
Wind turbine controllers are used to optimize the performance of wind turbines such as to reduce power variations and fatigue and extreme loads on wind turbine components. Accurate tuning and design of modern controllers must be done using low-order models that accurately captures the aeroelastic...... response of the wind turbine. The purpose of this thesis is to investigate the necessary model complexity required in aeroelastic models used for controller design and to analyze and propose methods to design low-order aeroelastic wind turbine models that are suited for model-based control design....... The thesis contains a characterization of the dynamics that influence the open-loop aeroelastic frequency response of a modern wind turbine, based on a high-order aeroelastic wind turbine model. One main finding is that the transfer function from collective pitch to generator speed is affected by two low...
REGIONAL FIRST ORDER PERIODIC AUTOREGRESSIVE MODELS FOR MONTHLY FLOWS
Directory of Open Access Journals (Sweden)
Ceyhun ÖZÇELİK
2008-01-01
Full Text Available First order periodic autoregressive models is of mostly used models in modeling of time dependency of hydrological flow processes. In these models, periodicity of the correlogram is preserved as well as time dependency of processes. However, the parameters of these models, namely, inter-monthly lag-1 autocorrelation coefficients may be often estimated erroneously from short samples, since they are statistics of high order moments. Therefore, to constitute a regional model may be a solution that can produce more reliable and decisive estimates, and derive models and model parameters in any required point of the basin considered. In this study, definitions of homogeneous region for lag-1 autocorrelation coefficients are made; five parametric and non parametric models are proposed to set regional models of lag-1 autocorrelation coefficients. Regional models are applied on 30 stream flow gauging stations in Seyhan and Ceyhan basins, and tested by criteria of relative absolute bias, simple and relative root of mean square errors.
SOLVING FRACTIONAL-ORDER COMPETITIVE LOTKA-VOLTERRA MODEL BY NSFD SCHEMES
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S.ZIBAEI
2016-12-01
Full Text Available In this paper, we introduce fractional-order into a model competitive Lotka- Volterra prey-predator system. We will discuss the stability analysis of this fractional system. The non-standard nite difference (NSFD scheme is implemented to study the dynamic behaviors in the fractional-order Lotka-Volterra system. Proposed non-standard numerical scheme is compared with the forward Euler and fourth order Runge-Kutta methods. Numerical results show that the NSFD approach is easy and accurate for implementing when applied to fractional-order Lotka-Volterra model.
Accelerating transient simulation of linear reduced order models.
Energy Technology Data Exchange (ETDEWEB)
Thornquist, Heidi K.; Mei, Ting; Keiter, Eric Richard; Bond, Brad
2011-10-01
Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to the practical application of MOR methods. In this report we investigate methods for accelerating the simulation of circuits containing ROM blocks using the circuit simulator Xyce.
Progress in integrated energy-economy-environment model system development
International Nuclear Information System (INIS)
Yasukawa, Shigeru; Mankin, Shuichi; Sato, Osamu; Tadokoro, Yoshihiro; Nakano, Yasuyuki; Nagano, Takao
1987-11-01
The Integrated Energy-Economy-Environment Model System has been developed for providing analytical tools for the system analysis and technology assessments in the field of nuclear research and development. This model system consists of the following four model groups. The first model block installs 5 models and can serve to analyze and generate long-term scenarios on economy-energy-environment evolution. The second model block installs 2 models and can serve to analyze the structural transition phenomena in energy-economy-environment interactions. The third model block installs 2 models and can handle power reactor installation strategy problem and long-term fuel cycle analysis. The fourth model block installs 5 models and codes and can treats cost-benefit-risk analysis and assessments. This report describes mainly the progress and the outlines of application of the model system in these years after the first report on the research and development of the model system (JAERI-M 84 - 139). (author)
Higher Order, Hybrid BEM/FEM Methods Applied to Antenna Modeling
Fink, P. W.; Wilton, D. R.; Dobbins, J. A.
2002-01-01
In this presentation, the authors address topics relevant to higher order modeling using hybrid BEM/FEM formulations. The first of these is the limitation on convergence rates imposed by geometric modeling errors in the analysis of scattering by a dielectric sphere. The second topic is the application of an Incomplete LU Threshold (ILUT) preconditioner to solve the linear system resulting from the BEM/FEM formulation. The final tOpic is the application of the higher order BEM/FEM formulation to antenna modeling problems. The authors have previously presented work on the benefits of higher order modeling. To achieve these benefits, special attention is required in the integration of singular and near-singular terms arising in the surface integral equation. Several methods for handling these terms have been presented. It is also well known that achieving he high rates of convergence afforded by higher order bases may als'o require the employment of higher order geometry models. A number of publications have described the use of quadratic elements to model curved surfaces. The authors have shown in an EFIE formulation, applied to scattering by a PEC .sphere, that quadratic order elements may be insufficient to prevent the domination of modeling errors. In fact, on a PEC sphere with radius r = 0.58 Lambda(sub 0), a quartic order geometry representation was required to obtain a convergence benefi.t from quadratic bases when compared to the convergence rate achieved with linear bases. Initial trials indicate that, for a dielectric sphere of the same radius, - requirements on the geometry model are not as severe as for the PEC sphere. The authors will present convergence results for higher order bases as a function of the geometry model order in the hybrid BEM/FEM formulation applied to dielectric spheres. It is well known that the system matrix resulting from the hybrid BEM/FEM formulation is ill -conditioned. For many real applications, a good preconditioner is required
Low order physical models of vertical axis wind turbines
Craig, Anna; Dabiri, John; Koseff, Jeffrey
2016-11-01
In order to examine the ability of low-order physical models of vertical axis wind turbines to accurately reproduce key flow characteristics, experiments were conducted on rotating turbine models, rotating solid cylinders, and stationary porous flat plates (of both uniform and non-uniform porosities). From examination of the patterns of mean flow, the wake turbulence spectra, and several quantitative metrics, it was concluded that the rotating cylinders represent a reasonably accurate analog for the rotating turbines. In contrast, from examination of the patterns of mean flow, it was found that the porous flat plates represent only a limited analog for rotating turbines (for the parameters examined). These findings have implications for both laboratory experiments and numerical simulations, which have previously used analogous low order models in order to reduce experimental/computational costs. NSF GRF and SGF to A.C; ONR N000141211047 and the Gordon and Betty Moore Foundation Grant GBMF2645 to J.D.; and the Bob and Norma Street Environmental Fluid Mechanics Laboratory at Stanford University.
DEFF Research Database (Denmark)
Azarang, Leyla; Scheike, Thomas; de Uña-Álvarez, Jacobo
2017-01-01
In this work, we present direct regression analysis for the transition probabilities in the possibly non-Markov progressive illness–death model. The method is based on binomial regression, where the response is the indicator of the occupancy for the given state along time. Randomly weighted score...
Luján, S; Santamaría, C; Pontones, J L; Ruiz-Cerdá, J L; Trassierra, M; Vera-Donoso, C D; Solsona, E; Jiménez-Cruz, F
2014-12-01
To apply new mathematical models according to Non Muscle Invasive Bladder Carcinoma (NMIBC) biological characteristics and enabling an accurate risk estimation of multiple recurrences and tumor progression. The classical Cox model is not valid for the assessment of this kind of events becausethe time betweenrecurrencesin the same patientmay be stronglycorrelated. These new models for risk estimation of recurrence/progression lead to individualized monitoring and treatment plan. 960 patients with primary NMIBC were enrolled. The median follow-up was 48.1 (3-160) months. Results obtained were validated in 240 patients from other center. Transurethral resection of the bladder (TURB) and random bladder biopsy were performed. Subsequently, adjuvant localized chemotherapy was performed. The variables analyzed were: number and tumor size, age, chemotherapy and histopathology. The endpoints were time to recurrence and time to progression. Cox model and its extensions were used as joint frailty model for multiple recurrence and progression. Model accuracy was calculated using Harrell's concordance index (c-index). 468 (48.8%) patients developed at least one tumor recurrence and tumor progression was reported in 52 (5.4%) patients. Variables for multiple-recurrence risk are: age, grade, number, size, treatment and the number of prior recurrences. All these together with age, stage and grade are the variables for progression risk. Concordance index was 0.64 and 0.85 for multiple recurrence and progression respectively. the high concordance reported besides to the validation process in external source, allow accurate multi-recurrence/progression risk estimation. As consequence, it is possible to schedule a follow-up and treatment individualized plan in new and recurrent NMCB cases. Copyright © 2014 AEU. Published by Elsevier Espana. All rights reserved.
Optimal inventory management and order book modeling
Baradel, Nicolas; Bouchard, Bruno; Evangelista, David; Mounjid, Othmane
2018-01-01
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic
Directory of Open Access Journals (Sweden)
Christer Dalen
2017-10-01
Full Text Available A model reduction technique based on optimization theory is presented, where a possible higher order system/model is approximated with an unstable DIPTD model by using only step response data. The DIPTD model is used to tune PD/PID controllers for the underlying possible higher order system. Numerous examples are used to illustrate the theory, i.e. both linear and nonlinear models. The Pareto Optimal controller is used as a reference controller.
The Ising model coupled to 2d orders
Glaser, Lisa
2018-04-01
In this article we make first steps in coupling matter to causal set theory in the path integral. We explore the case of the Ising model coupled to the 2d discrete Einstein Hilbert action, restricted to the 2d orders. We probe the phase diagram in terms of the Wick rotation parameter β and the Ising coupling j and find that the matter and the causal sets together give rise to an interesting phase structure. The couplings give rise to five different phases. The causal sets take on random or crystalline characteristics as described in Surya (2012 Class. Quantum Grav. 29 132001) and the Ising model can be correlated or uncorrelated on the random orders and correlated, uncorrelated or anti-correlated on the crystalline orders. We find that at least one new phase transition arises, in which the Ising spins push the causal set into the crystalline phase.
Directory of Open Access Journals (Sweden)
Shayoni Ray
Full Text Available Cleft formation during submandibular salivary gland branching morphogenesis is the critical step initiating the growth and development of the complex adult organ. Previous experimental studies indicated requirements for several epithelial cellular processes, such as proliferation, migration, cell-cell adhesion, cell-extracellular matrix (matrix adhesion, and cellular contraction in cleft formation; however, the relative contribution of each of these processes is not fully understood since it is not possible to experimentally manipulate each factor independently. We present here a comprehensive analysis of several cellular parameters regulating cleft progression during branching morphogenesis in the epithelial tissue of an early embryonic salivary gland at a local scale using an on lattice Monte-Carlo simulation model, the Glazier-Graner-Hogeweg model. We utilized measurements from time-lapse images of mouse submandibular gland organ explants to construct a temporally and spatially relevant cell-based 2D model. Our model simulates the effect of cellular proliferation, actomyosin contractility, cell-cell and cell-matrix adhesions on cleft progression, and it was used to test specific hypotheses regarding the function of these parameters in branching morphogenesis. We use innovative features capturing several aspects of cleft morphology and quantitatively analyze clefts formed during functional modification of the cellular parameters. Our simulations predict that a low epithelial mitosis rate and moderate level of actomyosin contractility in the cleft cells promote cleft progression. Raising or lowering levels of contractility and mitosis rate resulted in non-progressive clefts. We also show that lowered cell-cell adhesion in the cleft region and increased cleft cell-matrix adhesions are required for cleft progression. Using a classifier-based analysis, the relative importance of these four contributing cellular factors for effective cleft
Generalized modeling of the fractional-order memcapacitor and its character analysis
Guo, Zhang; Si, Gangquan; Diao, Lijie; Jia, Lixin; Zhang, Yanbin
2018-06-01
Memcapacitor is a new type of memory device generalized from the memristor. This paper proposes a generalized fractional-order memcapacitor model by introducing the fractional calculus into the model. The generalized formulas are studied and the two fractional-order parameter α, β are introduced where α mostly affects the fractional calculus value of charge q within the generalized Ohm's law and β generalizes the state equation which simulates the physical mechanism of a memcapacitor into the fractional sense. This model will be reduced to the conventional memcapacitor as α = 1 , β = 0 and to the conventional memristor as α = 0 , β = 1 . Then the numerical analysis of the fractional-order memcapacitor is studied. And the characteristics and output behaviors of the fractional-order memcapacitor applied with sinusoidal charge are derived. The analysis results have shown that there are four basic v - q and v - i curve patterns when the fractional order α, β respectively equal to 0 or 1, moreover all v - q and v - i curves of the other fractional-order models are transition curves between the four basic patterns.
Latent Partially Ordered Classification Models and Normal Mixtures
Tatsuoka, Curtis; Varadi, Ferenc; Jaeger, Judith
2013-01-01
Latent partially ordered sets (posets) can be employed in modeling cognitive functioning, such as in the analysis of neuropsychological (NP) and educational test data. Posets are cognitively diagnostic in the sense that classification states in these models are associated with detailed profiles of cognitive functioning. These profiles allow for…
Energy Technology Data Exchange (ETDEWEB)
Ihme, Matthias; See, Yee Chee [Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI 48109 (United States)
2010-10-15
An unsteady flamelet/progress variable (UFPV) model has been developed for the prediction of autoignition in turbulent lifted flames. The model is a consistent extension to the steady flamelet/progress variable (SFPV) approach, and employs an unsteady flamelet formulation to describe the transient evolution of all thermochemical quantities during the flame ignition process. In this UFPV model, all thermochemical quantities are parameterized by mixture fraction, reaction progress parameter, and stoichiometric scalar dissipation rate, eliminating the explicit dependence on a flamelet time scale. An a priori study is performed to analyze critical modeling assumptions that are associated with the population of the flamelet state space. For application to LES, the UFPV model is combined with a presumed PDF closure to account for subgrid contributions of mixture fraction and reaction progress variable. The model was applied in LES of a lifted methane/air flame. Additional calculations were performed to quantify the interaction between turbulence and chemistry a posteriori. Simulation results obtained from these calculations are compared with experimental data. Compared to the SFPV results, the unsteady flamelet/progress variable model captures the autoignition process, and good agreement with measurements is obtained for mixture fraction, temperature, and species mass fractions. From the analysis of scatter data and mixture fraction-conditional results it is shown that the turbulence/chemistry interaction delays the ignition process towards lower values of scalar dissipation rate, and a significantly larger region in the flamelet state space is occupied during the ignition process. (author)
The Meaning of Higher-Order Factors in Reflective-Measurement Models
Eid, Michael; Koch, Tobias
2014-01-01
Higher-order factor analysis is a widely used approach for analyzing the structure of a multidimensional test. Whenever first-order factors are correlated researchers are tempted to apply a higher-order factor model. But is this reasonable? What do the higher-order factors measure? What is their meaning? Willoughby, Holochwost, Blanton, and Blair…
Comparing higher order models for the EORTC QLQ-C30
DEFF Research Database (Denmark)
Gundy, Chad M; Fayers, Peter M; Grønvold, Mogens
2012-01-01
To investigate the statistical fit of alternative higher order models for summarizing the health-related quality of life profile generated by the EORTC QLQ-C30 questionnaire.......To investigate the statistical fit of alternative higher order models for summarizing the health-related quality of life profile generated by the EORTC QLQ-C30 questionnaire....
Energy Technology Data Exchange (ETDEWEB)
Napier, Bruce A.; Krupka, Kenneth M.; Fellows, Robert J.; Cataldo, Dominic A.; Valenta, Michelle M.; Gilmore, Tyler J.
2004-12-02
This Annual Progress Report describes the work performed and summarizes some of the key observations to date on the U.S. Nuclear Regulatory Commission’s project Assessment of Food Chain Pathway Parameters in Biosphere Models, which was established to assess and evaluate a number of key parameters used in the food-chain models used in performance assessments of radioactive waste disposal facilities. Section 2 of this report describes activities undertaken to collect samples of soils from three regions of the United States, the Southeast, Northwest, and Southwest, and perform analyses to characterize their physical and chemical properties. Section 3 summarizes information gathered regarding agricultural practices and common and unusual crops grown in each of these three areas. Section 4 describes progress in studying radionuclide uptake in several representative crops from the three soil types in controlled laboratory conditions. Section 5 describes a range of international coordination activities undertaken by Project staff in order to support the underlying data needs of the Project. Section 6 provides a very brief summary of the status of the GENII Version 2 computer program, which is a “client” of the types of data being generated by the Project, and for which the Project will be providing training to the US NRC staff in the coming Fiscal Year. Several appendices provide additional supporting information.
Directory of Open Access Journals (Sweden)
Jackalina M Van Kampen
Full Text Available The development of effective neuroprotective therapies for Parkinson's disease (PD has been severely hindered by the notable lack of an appropriate animal model for preclinical screening. Indeed, most models currently available are either acute in nature or fail to recapitulate all characteristic features of the disease. Here, we present a novel progressive model of PD, with behavioural and cellular features that closely approximate those observed in patients. Chronic exposure to dietary phytosterol glucosides has been found to be neurotoxic. When fed to rats, β-sitosterol β-d-glucoside (BSSG triggers the progressive development of parkinsonism, with clinical signs and histopathology beginning to appear following cessation of exposure to the neurotoxic insult and continuing to develop over several months. Here, we characterize the progressive nature of this model, its non-motor features, the anatomical spread of synucleinopathy, and response to levodopa administration. In Sprague Dawley rats, chronic BSSG feeding for 4 months triggered the progressive development of a parkinsonian phenotype and pathological events that evolved slowly over time, with neuronal loss beginning only after toxin exposure was terminated. At approximately 3 months following initiation of BSSG exposure, animals displayed the early emergence of an olfactory deficit, in the absence of significant dopaminergic nigral cell loss or locomotor deficits. Locomotor deficits developed gradually over time, initially appearing as locomotor asymmetry and developing into akinesia/bradykinesia, which was reversed by levodopa treatment. Late-stage cognitive impairment was observed in the form of spatial working memory deficits, as assessed by the radial arm maze. In addition to the progressive loss of TH+ cells in the substantia nigra, the appearance of proteinase K-resistant intracellular α-synuclein aggregates was also observed to develop progressively, appearing first in the
Progress on HELIAS systems studies
Energy Technology Data Exchange (ETDEWEB)
Warmer, Felix; Beidler, Craig D.; Dinklage, Andreas; Feng, Yuehe; Geiger, Joachim; Schauer, Felix; Turkin, Yuriy; Wolf, Robert; Xanthopoulos, Pavlos [Max-Planck-Institut fuer Plasmaphysik, D-17491 Greifswald (Germany); Kemp, Richard; Knight, Peter; Ward, David [Culham Centre for Fusion Energy, Abingdon, Oxfordshire, OX14 3DB (United Kingdom)
2015-05-01
In order to study and design next-step fusion devices such as DEMO, comprehensive systems codes are commonly employed. For the HELIAS-line, stellarator-specific models have been developed, implemented, and verified within the systems code PROCESS. This systems code ansatz is complemented by self-consistent modeling of plasma scenarios employing a predictive 1-D neoclassical transport code which has been augmented with a model for the edge anomalous transport based on 3-D ITG turbulence simulations. This approach is investigated to ultimately allow one to conduct stellarator system studies, develop design points of HELIAS burning plasma devices, and to facilitate a direct comparison between tokamak and stellarator DEMO and power plant designs. The work reports on the progress towards these goals.
Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States
Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.
2017-01-01
This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.
Declarative Modeling for Production Order Portfolio Scheduling
Directory of Open Access Journals (Sweden)
Banaszak Zbigniew
2014-12-01
Full Text Available A declarative framework enabling to determine conditions as well as to develop decision-making software supporting small- and medium-sized enterprises aimed at unique, multi-project-like and mass customized oriented production is discussed. A set of unique production orders grouped into portfolio orders is considered. Operations executed along different production orders share available resources following a mutual exclusion protocol. A unique product or production batch is completed while following a given activity’s network order. The problem concerns scheduling a newly inserted project portfolio subject to constraints imposed by a multi-project environment The answers sought are: Can a given project portfolio specified by its cost and completion time be completed within the assumed time period in a manufacturing system in hand? Which manufacturing system capability guarantees the completion of a given project portfolio ordered under assumed cost and time constraints? The considered problems regard finding a computationally effective approach aimed at simultaneous routing and allocation as well as batching and scheduling of a newly ordered project portfolio subject to constraints imposed by a multi-project environment. The main objective is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multi-project-like and mass customized oriented production scheduling. Multiple illustrative examples are discussed.
A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression
International Nuclear Information System (INIS)
Dutta-Moscato, Joyeeta; Solovyev, Alexey; Mi, Qi; Nishikawa, Taichiro; Soto-Gutierrez, Alejandro; Fox, Ira J.; Vodovotz, Yoram
2014-01-01
Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl 4 ). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl 4 -treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl 4 -injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant insights into
Lattice Boltzmann model for high-order nonlinear partial differential equations.
Chai, Zhenhua; He, Nanzhong; Guo, Zhaoli; Shi, Baochang
2018-01-01
In this paper, a general lattice Boltzmann (LB) model is proposed for the high-order nonlinear partial differential equation with the form ∂_{t}ϕ+∑_{k=1}^{m}α_{k}∂_{x}^{k}Π_{k}(ϕ)=0 (1≤k≤m≤6), α_{k} are constant coefficients, Π_{k}(ϕ) are some known differential functions of ϕ. As some special cases of the high-order nonlinear partial differential equation, the classical (m)KdV equation, KdV-Burgers equation, K(n,n)-Burgers equation, Kuramoto-Sivashinsky equation, and Kawahara equation can be solved by the present LB model. Compared to the available LB models, the most distinct characteristic of the present model is to introduce some suitable auxiliary moments such that the correct moments of equilibrium distribution function can be achieved. In addition, we also conducted a detailed Chapman-Enskog analysis, and found that the high-order nonlinear partial differential equation can be correctly recovered from the proposed LB model. Finally, a large number of simulations are performed, and it is found that the numerical results agree with the analytical solutions, and usually the present model is also more accurate than the existing LB models [H. Lai and C. Ma, Sci. China Ser. G 52, 1053 (2009)1672-179910.1007/s11433-009-0149-3; H. Lai and C. Ma, Phys. A (Amsterdam) 388, 1405 (2009)PHYADX0378-437110.1016/j.physa.2009.01.005] for high-order nonlinear partial differential equations.
Lattice Boltzmann model for high-order nonlinear partial differential equations
Chai, Zhenhua; He, Nanzhong; Guo, Zhaoli; Shi, Baochang
2018-01-01
In this paper, a general lattice Boltzmann (LB) model is proposed for the high-order nonlinear partial differential equation with the form ∂tϕ +∑k=1mαk∂xkΠk(ϕ ) =0 (1 ≤k ≤m ≤6 ), αk are constant coefficients, Πk(ϕ ) are some known differential functions of ϕ . As some special cases of the high-order nonlinear partial differential equation, the classical (m)KdV equation, KdV-Burgers equation, K (n ,n ) -Burgers equation, Kuramoto-Sivashinsky equation, and Kawahara equation can be solved by the present LB model. Compared to the available LB models, the most distinct characteristic of the present model is to introduce some suitable auxiliary moments such that the correct moments of equilibrium distribution function can be achieved. In addition, we also conducted a detailed Chapman-Enskog analysis, and found that the high-order nonlinear partial differential equation can be correctly recovered from the proposed LB model. Finally, a large number of simulations are performed, and it is found that the numerical results agree with the analytical solutions, and usually the present model is also more accurate than the existing LB models [H. Lai and C. Ma, Sci. China Ser. G 52, 1053 (2009), 10.1007/s11433-009-0149-3; H. Lai and C. Ma, Phys. A (Amsterdam) 388, 1405 (2009), 10.1016/j.physa.2009.01.005] for high-order nonlinear partial differential equations.
Covariant quantization of infinite spin particle models, and higher order gauge theories
International Nuclear Information System (INIS)
Edgren, Ludde; Marnelius, Robert
2006-01-01
Further properties of a recently proposed higher order infinite spin particle model are derived. Infinitely many classically equivalent but different Hamiltonian formulations are shown to exist. This leads to a condition of uniqueness in the quantization process. A consistent covariant quantization is shown to exist. Also a recently proposed supersymmetric version for half-odd integer spins is quantized. A general algorithm to derive gauge invariances of higher order Lagrangians is given and applied to the infinite spin particle model, and to a new higher order model for a spinning particle which is proposed here, as well as to a previously given higher order rigid particle model. The latter two models are also covariantly quantized
Reduced Order Modeling of Combustion Instability in a Gas Turbine Model Combustor
Arnold-Medabalimi, Nicholas; Huang, Cheng; Duraisamy, Karthik
2017-11-01
Hydrocarbon fuel based propulsion systems are expected to remain relevant in aerospace vehicles for the foreseeable future. Design of these devices is complicated by combustion instabilities. The capability to model and predict these effects at reduced computational cost is a requirement for both design and control of these devices. This work focuses on computational studies on a dual swirl model gas turbine combustor in the context of reduced order model development. Full fidelity simulations are performed utilizing URANS and Hybrid RANS-LES with finite rate chemistry. Following this, data decomposition techniques are used to extract a reduced basis representation of the unsteady flow field. These bases are first used to identify sensor locations to guide experimental interrogations and controller feedback. Following this, initial results on developing a control-oriented reduced order model (ROM) will be presented. The capability of the ROM will be further assessed based on different operating conditions and geometric configurations.
Progress report on SYVAC chemical modelling studies during 1984/85
International Nuclear Information System (INIS)
Cross, J.E.; Read, D.; Smith, G.L.; Williams, D.R.
1985-05-01
This report summarises progress made from April 1984 to May 1985 on chemical modelling within the DOE SYVAC project. Three new computer programs; the reaction path codes, PHREEQE and EQ3/6, and the chemical transport simulator CHEMTRN, have been acquired. Their applicability, overall capabilities, ease of use and database requirements are assessed. Coupled approaches to geochemical - hydrological modelling and the use of CHEMTRN is discussed. Modelling has been performed in connection with the ''Dry Run Assessment''. Speciation and solubilities of the actinides were simulated, assuming the vault to be a concrete solution and the geosphere to be represented by Harwell site groundwater analyses. Model verification and validation by collaboration with experimentalists and other modellers is discussed. (author)
Modelling stock order flows with non-homogeneous intensities from high-frequency data
Gorshenin, Andrey K.; Korolev, Victor Yu.; Zeifman, Alexander I.; Shorgin, Sergey Ya.; Chertok, Andrey V.; Evstafyev, Artem I.; Korchagin, Alexander Yu.
2013-10-01
A micro-scale model is proposed for the evolution of such information system as the limit order book in financial markets. Within this model, the flows of orders (claims) are described by doubly stochastic Poisson processes taking account of the stochastic character of intensities of buy and sell orders that determine the price discovery mechanism. The proposed multiplicative model of stochastic intensities makes it possible to analyze the characteristics of the order flows as well as the instantaneous proportion of the forces of buyers and sellers, that is, the imbalance process, without modelling the external information background. The proposed model gives the opportunity to link the micro-scale (high-frequency) dynamics of the limit order book with the macro-scale models of stock price processes of the form of subordinated Wiener processes by means of limit theorems of probability theory and hence, to use the normal variance-mean mixture models of the corresponding heavy-tailed distributions. The approach can be useful in different areas with similar properties (e.g., in plasma physics).
Mechanical model for filament buckling and growth by phase ordering.
Rey, Alejandro D; Abukhdeir, Nasser M
2008-02-05
A mechanical model of open filament shape and growth driven by phase ordering is formulated. For a given phase-ordering driving force, the model output is the filament shape evolution and the filament end-point kinematics. The linearized model for the slope of the filament is the Cahn-Hilliard model of spinodal decomposition, where the buckling corresponds to concentration fluctuations. Two modes are predicted: (i) sequential growth and buckling and (ii) simultaneous buckling and growth. The relation among the maximum buckling rate, filament tension, and matrix viscosity is given. These results contribute to ongoing work in smectic A filament buckling.
A joint frailty-copula model between tumour progression and death for meta-analysis.
Emura, Takeshi; Nakatochi, Masahiro; Murotani, Kenta; Rondeau, Virginie
2017-12-01
Dependent censoring often arises in biomedical studies when time to tumour progression (e.g., relapse of cancer) is censored by an informative terminal event (e.g., death). For meta-analysis combining existing studies, a joint survival model between tumour progression and death has been considered under semicompeting risks, which induces dependence through the study-specific frailty. Our paper here utilizes copulas to generalize the joint frailty model by introducing additional source of dependence arising from intra-subject association between tumour progression and death. The practical value of the new model is particularly evident for meta-analyses in which only a few covariates are consistently measured across studies and hence there exist residual dependence. The covariate effects are formulated through the Cox proportional hazards model, and the baseline hazards are nonparametrically modeled on a basis of splines. The estimator is then obtained by maximizing a penalized log-likelihood function. We also show that the present methodologies are easily modified for the competing risks or recurrent event data, and are generalized to accommodate left-truncation. Simulations are performed to examine the performance of the proposed estimator. The method is applied to a meta-analysis for assessing a recently suggested biomarker CXCL12 for survival in ovarian cancer patients. We implement our proposed methods in R joint.Cox package.
Data-Driven Model Order Reduction for Bayesian Inverse Problems
Cui, Tiangang; Youssef, Marzouk; Willcox, Karen
2014-01-01
One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce
Kernel methods for interpretable machine learning of order parameters
Ponte, Pedro; Melko, Roger G.
2017-11-01
Machine learning is capable of discriminating phases of matter, and finding associated phase transitions, directly from large data sets of raw state configurations. In the context of condensed matter physics, most progress in the field of supervised learning has come from employing neural networks as classifiers. Although very powerful, such algorithms suffer from a lack of interpretability, which is usually desired in scientific applications in order to associate learned features with physical phenomena. In this paper, we explore support vector machines (SVMs), which are a class of supervised kernel methods that provide interpretable decision functions. We find that SVMs can learn the mathematical form of physical discriminators, such as order parameters and Hamiltonian constraints, for a set of two-dimensional spin models: the ferromagnetic Ising model, a conserved-order-parameter Ising model, and the Ising gauge theory. The ability of SVMs to provide interpretable classification highlights their potential for automating feature detection in both synthetic and experimental data sets for condensed matter and other many-body systems.
Discovering biological progression underlying microarray samples.
Directory of Open Access Journals (Sweden)
Peng Qiu
2011-04-01
Full Text Available In biological systems that undergo processes such as differentiation, a clear concept of progression exists. We present a novel computational approach, called Sample Progression Discovery (SPD, to discover patterns of biological progression underlying microarray gene expression data. SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression, and that each sample represents one unknown point along the progression of that process. SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression. We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression, without providing SPD any information of the underlying process. When applied to a cell cycle time series microarray dataset, SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated, yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle. When applied to B-cell differentiation data, SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB. When applied to mouse embryonic stem cell differentiation data, SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes. When applied to a prostate cancer microarray dataset, SPD identified gene modules that reflect a progression consistent with disease stages. SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the
The complex model of risk and progression of AMD estimation
Directory of Open Access Journals (Sweden)
V. S. Akopyan
2012-01-01
Full Text Available Purpose: to develop a method and a statistical model to estimate individual risk of AMD and the risk for progression to advanced AMD using clinical and genetic risk factors.Methods: A statistical risk assessment model was developed using stepwise binary logistic regression analysis. to estimate the population differences in the prevalence of allelic variants of genes and for the development of models adapted to the population of Moscow region genotyping and assessment of the influence of other risk factors was performed in two groups: patients with differ- ent stages of AMD (n = 74, and control group (n = 116. Genetic risk factors included in the study: polymorphisms in the complement system genes (C3 and CFH, genes at 10q26 locus (ARMS2 and HtRA1, polymorphism in the mitochondrial gene Mt-ND2. Clinical risk factors included in the study: age, gender, high body mass index, smoking history.Results: A comprehensive analysis of genetic and clinical risk factors for AMD in the study group was performed. Compiled statis- tical model assessment of individual risk of AMD, the sensitivity of the model — 66.7%, specificity — 78.5%, AUC = 0.76. Risk factors of late AMD, compiled a statistical model describing the probability of late AMD, the sensitivity of the model — 66.7%, specificity — 78.3%, AUC = 0.73. the developed system allows determining the most likely version of the current late AMD: dry or wet.Conclusion: the developed test system and the mathematical algorhythm for determining the risk of AMD, risk of progression to advanced AMD have fair diagnostic informative and promising for use in clinical practice.
Progressive Conversion from B-rep to BSP for Streaming Geometric Modeling.
Bajaj, Chandrajit; Paoluzzi, Alberto; Scorzelli, Giorgio
2006-01-01
We introduce a novel progressive approach to generate a Binary Space Partition (BSP) tree and a convex cell decomposition for any input triangles boundary representation (B-rep), by utilizing a fast calculation of the surface inertia. We also generate a solid model at progressive levels of detail. This approach relies on a variation of standard BSP tree generation, allowing for labeling cells as in, out and fuzzy, and which permits a comprehensive representation of a solid as the Hasse diagram of a cell complex. Our new algorithm is embedded in a streaming computational framework, using four types of dataflow processes that continuously produce, transform, combine or consume subsets of cells depending on their number or input/output stream. A varied collection of geometric modeling techniques are integrated in this streaming framework, including polygonal, spline, solid and heterogeneous modeling with boundary and decompositive representations, Boolean set operations, Cartesian products and adaptive refinement. The real-time B-rep to BSP streaming results we report in this paper are a large step forward in the ultimate unification of rapid conceptual and detailed shape design methodologies.
Modeling and analysis of fractional order DC-DC converter.
Radwan, Ahmed G; Emira, Ahmed A; AbdelAty, Amr M; Azar, Ahmad Taher
2017-07-11
Due to the non-idealities of commercial inductors, the demand for a better model that accurately describe their dynamic response is elevated. So, the fractional order models of Buck, Boost and Buck-Boost DC-DC converters are presented in this paper. The detailed analysis is made for the two most common modes of converter operation: Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). Closed form time domain expressions are derived for inductor currents, voltage gain, average current, conduction time and power efficiency where the effect of the fractional order inductor is found to be strongly present. For example, the peak inductor current at steady state increases with decreasing the inductor order. Advanced Design Systems (ADS) circuit simulations are used to verify the derived formulas, where the fractional order inductor is simulated using Valsa Constant Phase Element (CPE) approximation and Generalized Impedance Converter (GIC). Different simulation results are introduced with good matching to the theoretical formulas for the three DC-DC converter topologies under different fractional orders. A comprehensive comparison with the recently published literature is presented to show the advantages and disadvantages of each approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
In silico ADME-Tox modeling: progress and prospects.
Alqahtani, Saeed
2017-11-01
Although significant progress has been made in high-throughput screening of absorption, distribution, metabolism and excretion, and toxicity (ADME-Tox) properties in drug discovery and development, in silico ADME-Tox prediction continues to play an important role in facilitating the appropriate selection of candidate drugs by pharmaceutical companies prior to expensive clinical trials. Areas covered: This review provides an overview of the available in silico models that have been used to predict the ADME-Tox properties of compounds. It also provides a comprehensive overview and summarization of the latest modeling methods and algorithms available for the prediction of physicochemical characteristics, ADME properties, and drug toxicity issues. Expert opinion: The in silico models currently available have greatly contributed to the knowledge of screening approaches in the early stages of drug discovery and the development process. As the definitive goal of in silico molding is to predict the pharmacokinetics and disposition of compounds in vivo by assembling all kinetic processes within one global model, PBPK models can serve this purpose. However, much work remains to be done in this area to generate more data and input parameters to build more reliable and accurate prediction models.
AN OVERVIEW OF REDUCED ORDER MODELING TECHNIQUES FOR SAFETY APPLICATIONS
Energy Technology Data Exchange (ETDEWEB)
Mandelli, D.; Alfonsi, A.; Talbot, P.; Wang, C.; Maljovec, D.; Smith, C.; Rabiti, C.; Cogliati, J.
2016-10-01
The RISMC project is developing new advanced simulation-based tools to perform Computational Risk Analysis (CRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermal-hydraulic behavior of the reactors primary and secondary systems, but also external event temporal evolution and component/system ageing. Thus, this is not only a multi-physics problem being addressed, but also a multi-scale problem (both spatial, µm-mm-m, and temporal, seconds-hours-years). As part of the RISMC CRA approach, a large amount of computationally-expensive simulation runs may be required. An important aspect is that even though computational power is growing, the overall computational cost of a RISMC analysis using brute-force methods may be not viable for certain cases. A solution that is being evaluated to assist the computational issue is the use of reduced order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RISMC analysis computational cost by decreasing the number of simulation runs; for this analysis improvement we used surrogate models instead of the actual simulation codes. This article focuses on the use of reduced order modeling techniques that can be applied to RISMC analyses in order to generate, analyze, and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (microseconds instead of hours/days).
An exactly solvable model for first- and second-order transitions
International Nuclear Information System (INIS)
Klushin, L I; Skvortsov, A M; Gorbunov, A A
1998-01-01
The possibility of an exact analytical description of first-order and second-order transitions is demonstrated using a specific microscopic model. Predictions using the exactly calculated partition function are compared with those based on the Landau and Yang-Lee approaches. The model employed is an adsorbed polymer chain with an arbitrary number of links and an external force applied to its end, for which the variation of the partition function with the adsorption interaction parameter and the magnitude of the applied force is calculated. In the thermodynamic limit, the system has one isotropic and two anisotropic, ordered phases, each of which is characterized by two order parameters and between which first-order and second-order transitions occur and a bicritical point exists. The Landau free energy is found exactly as a function of each order parameter separately and, near the bicritical point, as a function of both of them simultaneously. An exact analytical formula is found for the distribution of the complex zeros of the partition function in first-order and second-order phase transitions. Hypotheses concerning the way in which the free energy and the positions of the complex zeros scale with the number of particles N in the system are verified. (reviews of topical problems)
Qi, D.; Majda, A.
2017-12-01
A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with
Order Aggressiveness and Order Book Dynamics
Anthony D. Hall; Nikolaus Hautsch
2004-01-01
In this paper, we study the determinants of order aggressiveness and traders' order submission strategy in an open limit order book market. Using order book data from the Australian Stock Exchange, we model traders' aggressiveness in market trading, limit order trading as well as in order cancellations on both sides of the market using a six-dimensional autoregressive intensity model. The information revealed by the open order book plays an important role in explaining the degree of order agg...
The fractional-order modeling and synchronization of electrically coupled neuron systems
Moaddy, K.
2012-11-01
In this paper, we generalize the integer-order cable model of the neuron system into the fractional-order domain, where the long memory dependence of the fractional derivative can be a better fit for the neuron response. Furthermore, the chaotic synchronization with a gap junction of two or multi-coupled-neurons of fractional-order are discussed. The circuit model, fractional-order state equations and the numerical technique are introduced in this paper for individual and multiple coupled neuron systems with different fractional-orders. Various examples are introduced with different fractional orders using the non-standard finite difference scheme together with the Grünwald-Letnikov discretization process which is easily implemented and reliably accurate. © 2011 Elsevier Ltd. All rights reserved.
The fractional-order modeling and synchronization of electrically coupled neuron systems
Moaddy, K.; Radwan, Ahmed G.; Salama, Khaled N.; Momani, Shaher M.; Hashim, Ishak
2012-01-01
In this paper, we generalize the integer-order cable model of the neuron system into the fractional-order domain, where the long memory dependence of the fractional derivative can be a better fit for the neuron response. Furthermore, the chaotic synchronization with a gap junction of two or multi-coupled-neurons of fractional-order are discussed. The circuit model, fractional-order state equations and the numerical technique are introduced in this paper for individual and multiple coupled neuron systems with different fractional-orders. Various examples are introduced with different fractional orders using the non-standard finite difference scheme together with the Grünwald-Letnikov discretization process which is easily implemented and reliably accurate. © 2011 Elsevier Ltd. All rights reserved.
Luo, Gang
2017-01-01
For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic. PMID:29177022
A Reduced-Order Model of Transport Phenomena for Power Plant Simulation
Energy Technology Data Exchange (ETDEWEB)
Paul Cizmas; Brian Richardson; Thomas Brenner; Raymond Fontenot
2009-09-30
A reduced-order model based on proper orthogonal decomposition (POD) has been developed to simulate transient two- and three-dimensional isothermal and non-isothermal flows in a fluidized bed. Reduced-order models of void fraction, gas and solids temperatures, granular energy, and z-direction gas and solids velocity have been added to the previous version of the code. These algorithms are presented and their implementation is discussed. Verification studies are presented for each algorithm. A number of methods to accelerate the computations performed by the reduced-order model are presented. The errors associated with each acceleration method are computed and discussed. Using a combination of acceleration methods, a two-dimensional isothermal simulation using the reduced-order model is shown to be 114 times faster than using the full-order model. In the pursue of achieving the objectives of the project and completing the tasks planned for this program, several unplanned and unforeseen results, methods and studies have been generated. These additional accomplishments are also presented and they include: (1) a study of the effect of snapshot sampling time on the computation of the POD basis functions, (2) an investigation of different strategies for generating the autocorrelation matrix used to find the POD basis functions, (3) the development and implementation of a bubble detection and tracking algorithm based on mathematical morphology, (4) a method for augmenting the proper orthogonal decomposition to better capture flows with discontinuities, such as bubbles, and (5) a mixed reduced-order/full-order model, called point-mode proper orthogonal decomposition, designed to avoid unphysical due to approximation errors. The limitations of the proper orthogonal decomposition method in simulating transient flows with moving discontinuities, such as bubbling flows, are discussed and several methods are proposed to adapt the method for future use.
Reduced-Order Computational Model for Low-Frequency Dynamics of Automobiles
Directory of Open Access Journals (Sweden)
A. Arnoux
2013-01-01
Full Text Available A reduced-order model is constructed to predict, for the low-frequency range, the dynamical responses in the stiff parts of an automobile constituted of stiff and flexible parts. The vehicle has then many elastic modes in this range due to the presence of many flexible parts and equipment. A nonusual reduced-order model is introduced. The family of the elastic modes is not used and is replaced by an adapted vector basis of the admissible space of global displacements. Such a construction requires a decomposition of the domain of the structure in subdomains in order to control the spatial wave length of the global displacements. The fast marching method is used to carry out the subdomain decomposition. A probabilistic model of uncertainties is introduced. The parameters controlling the level of uncertainties are estimated solving a statistical inverse problem. The methodology is validated with a large computational model of an automobile.
Approaches for Reduced Order Modeling of Electrically Actuated von Karman Microplates
Saghir, Shahid
2016-07-25
This article presents and compares different approaches to develop reduced order models for the nonlinear von Karman rectangular microplates actuated by nonlinear electrostatic forces. The reduced-order models aim to investigate the static and dynamic behavior of the plate under small and large actuation forces. A fully clamped microplate is considered. Different types of basis functions are used in conjunction with the Galerkin method to discretize the governing equations. First we investigate the convergence with the number of modes retained in the model. Then for validation purpose, a comparison of the static results is made with the results calculated by a nonlinear finite element model. The linear eigenvalue problem for the plate under the electrostatic force is solved for a wide range of voltages up to pull-in. Results among the various reduced-order modes are compared and are also validated by comparing to results of the finite-element model. Further, the reduced order models are employed to capture the forced dynamic response of the microplate under small and large vibration amplitudes. Comparison of the different approaches are made for this case. Keywords: electrically actuated microplates, static analysis, dynamics of microplates, diaphragm vibration, large amplitude vibrations, nonlinear dynamics
Modelling of electric tree progression due to space charge modified fields
International Nuclear Information System (INIS)
Seralathan, K E; Mahajan, A; Gupta, Nandini
2008-01-01
Tree initiation and growth require localized field enhancement that results in material erosion and formation of tree channels. Tree progression is linked to partial discharges within the tree tubules, characterized by recurrent periods of activity followed by quiescent states. Charge builds up across the non-conducting tree channels during the inactive regime, and discharge follows. In this work, the role of the space charge modified field during the non-discharging regime in deciding the site of subsequent discharges and thereby shaping tree structures is studied. A simple stochastic model was developed, in order to understand the respective effects of charges trapped on the walls of tree tubules, at channel tips, or in the volume of the dielectric. While some charge distributions are seen to arrest tree growth, others encourage axial growth towards the other electrode, and some aid in producing bushy trees clustered around the needle tip. The effect of carbon deposition within tree channels, making them effectively conducting, was also investigated. The insights gained from the simulations were successfully used to explain tree growth in the laboratory under high- and low-field conditions
A new model of progressive pulmonary fibrosis in rats
Energy Technology Data Exchange (ETDEWEB)
Last, J.A.; Gelzleichter, T.R.; Pinkerton, K.E.; Walker, R.M.; Witschi, H. (Univ. of California, Davis (United States))
1993-08-01
Sprague-Dawley rats were exposed for 6 h daily to 0.8 ppm of ozone and 14.4 ppm of nitrogen dioxide. Approximately 7 to 10 wk after the initiation of exposure, animals began to demonstrate respiratory insufficiency and severe weight loss. About half of the rats died between Days 55 and 78 of exposure; no overt ill effects were observed in animals exposed to filtered air, to ozone alone, or to nitrogen dioxide. Biochemical findings in animals exposed to ozone and nitrogen dioxide included increased lung content of DNA, protein, collagen, and elastin, which was about 300% higher than the control values. The collagen-specific crosslink hydroxy-pyridinium, a biomarker for mature collagen in the lung, was decreased by about 40%. These results are consistent with extensive breakdown and remodeling of the lung parenchyma and its associated vasculature. Histopathologic evaluation showed severe fibrosis, alveolar collapse, honeycombing, macrophage and mast cell accumulation, vascular smooth muscle hypertrophy, and other indications of severe progressive interstitial pulmonary fibrosis and end-stage lung disease. This unique animal model of progressive pulmonary fibrosis resembles the final stages of human idiopathic pulmonary fibrosis and should facilitate studying underlying mechanisms and potential therapy of progressive pulmonary fibrosis.
Marginal and Interaction Effects in Ordered Response Models
Debdulal Mallick
2009-01-01
In discrete choice models the marginal effect of a variable of interest that is interacted with another variable differs from the marginal effect of a variable that is not interacted with any variable. The magnitude of the interaction effect is also not equal to the marginal effect of the interaction term. I present consistent estimators of both marginal and interaction effects in ordered response models. This procedure is general and can easily be extended to other discrete choice models. I ...
A delta-rule model of numerical and non-numerical order processing.
Verguts, Tom; Van Opstal, Filip
2014-06-01
Numerical and non-numerical order processing share empirical characteristics (distance effect and semantic congruity), but there are also important differences (in size effect and end effect). At the same time, models and theories of numerical and non-numerical order processing developed largely separately. Currently, we combine insights from 2 earlier models to integrate them in a common framework. We argue that the same learning principle underlies numerical and non-numerical orders, but that environmental features determine the empirical differences. Implications for current theories on order processing are pointed out. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Fractional order creep model for dam concrete considering degree of hydration
Huang, Yaoying; Xiao, Lei; Bao, Tengfei; Liu, Yu
2018-05-01
Concrete is a material that is an intermediate between an ideal solid and an ideal fluid. The creep of concrete is related not only to the loading age and duration, but also to its temperature and temperature history. Fractional order calculus is a powerful tool for solving physical mechanics modeling problems. Using a software element based on the generalized Kelvin model, a fractional order creep model of concrete considering the loading age and duration is established. Then, the hydration rate of cement is considered in terms of the degree of hydration, and the fractional order creep model of concrete considering the degree of hydration is established. Moreover, uniaxial tensile creep tests of dam concrete under different curing temperatures were conducted, and the results were combined with the creep test data and complex optimization method to optimize the parameters of a new creep model. The results show that the fractional tensile creep model based on hydration degree can better describe the tensile creep properties of concrete, and this model involves fewer parameters than the 8-parameter model.
A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression
Energy Technology Data Exchange (ETDEWEB)
Dutta-Moscato, Joyeeta [Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Solovyev, Alexey [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Mathematics, University of Pittsburgh, Pittsburgh, PA (United States); Mi, Qi [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, PA (United States); Nishikawa, Taichiro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Soto-Gutierrez, Alejandro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Pathology, University of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Fox, Ira J. [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Vodovotz, Yoram, E-mail: vodovotzy@upmc.edu [Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States)
2014-05-30
Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl{sub 4}). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl{sub 4}-treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl{sub 4}-injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant
Identification and non-integer order modelling of synchronous machines operating as generator
Directory of Open Access Journals (Sweden)
Szymon Racewicz
2012-09-01
Full Text Available This paper presents an original mathematical model of a synchronous generator using derivatives of fractional order. In contrast to classical models composed of a large number of R-L ladders, it comprises half-order impedances, which enable the accurate description of the electromagnetic induction phenomena in a wide frequency range, while minimizing the order and number of model parameters. The proposed model takes into account the skin eff ect in damper cage bars, the eff ects of eddy currents in rotor solid parts, and the saturation of the machine magnetic circuit. The half-order transfer functions used for modelling these phenomena were verifi ed by simulation of ferromagnetic sheet impedance using the fi nite elements method. The analysed machine’s parameters were identified on the basis of SSFR (StandStill Frequency Response characteristics measured on a gradually magnetised synchronous machine.
Robust simulation of buckled structures using reduced order modeling
International Nuclear Information System (INIS)
Wiebe, R.; Perez, R.A.; Spottswood, S.M.
2016-01-01
Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties. (paper)
Robust simulation of buckled structures using reduced order modeling
Wiebe, R.; Perez, R. A.; Spottswood, S. M.
2016-09-01
Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties.
Mixed-order phase transition in a minimal, diffusion-based spin model.
Fronczak, Agata; Fronczak, Piotr
2016-07-01
In this paper we exactly solve, within the grand canonical ensemble, a minimal spin model with the hybrid phase transition. We call the model diffusion based because its Hamiltonian can be recovered from a simple dynamic procedure, which can be seen as an equilibrium statistical mechanics representation of a biased random walk. We outline the derivation of the phase diagram of the model, in which the triple point has the hallmarks of the hybrid transition: discontinuity in the average magnetization and algebraically diverging susceptibilities. At this point, two second-order transition curves meet in equilibrium with the first-order curve, resulting in a prototypical mixed-order behavior.
International Nuclear Information System (INIS)
Brodin, N. Patrik; Vogelius, Ivan R.; Björk-Eriksson, Thomas; Munck af Rosenschöld, Per; Bentzen, Søren M.
2013-01-01
Purpose: As pediatric medulloblastoma (MB) is a relatively rare disease, it is important to extract the maximum information from trials and cohort studies. Here, a framework was developed for modeling tumor control with multiple modes of failure and time-to-progression for standard-risk MB, using published pattern of failure data. Methods and Materials: Outcome data for standard-risk MB published after 1990 with pattern of relapse information were used to fit a tumor control dose-response model addressing failures in both the high-dose boost volume and the elective craniospinal volume. Estimates of 5-year event-free survival from 2 large randomized MB trials were used to model the time-to-progression distribution. Uncertainty in freedom from progression (FFP) was estimated by Monte Carlo sampling over the statistical uncertainty in input data. Results: The estimated 5-year FFP (95% confidence intervals [CI]) for craniospinal doses of 15, 18, 24, and 36 Gy while maintaining 54 Gy to the posterior fossa was 77% (95% CI, 70%-81%), 78% (95% CI, 73%-81%), 79% (95% CI, 76%-82%), and 80% (95% CI, 77%-84%) respectively. The uncertainty in FFP was considerably larger for craniospinal doses below 18 Gy, reflecting the lack of data in the lower dose range. Conclusions: Estimates of tumor control and time-to-progression for standard-risk MB provides a data-driven setting for hypothesis generation or power calculations for prospective trials, taking the uncertainties into account. The presented methods can also be applied to incorporate further risk-stratification for example based on molecular biomarkers, when the necessary data become available
Directory of Open Access Journals (Sweden)
Kuifen Ma
2017-11-01
Full Text Available Objective(s: Arachidonic Acid/5-lipoxygenase (AA/5-LOX pathway connects lipid metabolism and proinflammatory cytokine, which are both related to the development and progression of nonalcoholic fatty liver disease (NAFLD. Therefore, the present study was designed to investigate the role of AA/5-LOX pathway in progression of NAFLD, and the effect of zileuton, an inhibitor of 5-LOX, in this model. Materials and Methods: Animal model for progression of NAFLD was established via feeding high saturated fat diet (HFD. Liver function, HE staining, NAFLD activity score (NAS were used to evaluate NAFLD progression. We detected the lipid metabolism substrates: free fatty acids (FFA and AA, products: cysteinyl-leukotrienes (CysLTs, and changes in gene and protein level of key enzyme in AA/5-LOX pathway including PLA2 and 5-LOX. Furthermore, we determined whether NAFLD progression pathway was delayed or reversed when zileuton (1-[1-(1-benzothiophen-2-ylethyl]-1-hydroxyurea was administrated. Results: Rat model for progression of NAFLD was well established as analyzed by liver transaminase activities, hematoxylin-eosin (HE staining and NAS. The concentrations of substrates and products in AA/5-LOX pathway were increased with the progression of NAFLD. mRNA and protein expression of PLA2 and 5-LOX were all enhanced. Moreover, administration of zileuton inhibited AA/5-LOX pathway and reversed the increased transamine activities and NAS. Conclusion: AA/5-LOX pathway promotes the progression of NAFLD, which can be reversed by zileuton.
First-order regional seismotectonic model for South Africa
CSIR Research Space (South Africa)
Singh, M
2011-10-01
Full Text Available A first-order seismotectonic model was created for South Africa. This was done using four logical steps: geoscientific data collection, characterisation, assimilation and zonation. Through the definition of subunits of concentrations of earthquake...
Numerical Investigation of Progressive Collapse Resistance for Seismically Designed RC Buildings
Marchiş, Adrian G.; Ioani, Adrian M.
2014-01-01
In this paper the progressive collapse behavior of a reinforced concrete framed building located in different seismic areas from Romania is investigated. The six-storey structure is designed for low (ag = 0.08 g), moderate (ag = 0.16 g) and high (ag = 0.24 g) seismic zone. Based on the GSA (2003) criteria, a nonlinear static analysis is conducted first in order to estimate the progressive collapse resistance of the models. It was shown that all the structures will collapse when subjected to i...
Poole, Matthew L.; Brodtmann, Amy; Darby, David; Vogel, Adam P.
2017-01-01
Purpose: Our purpose was to create a comprehensive review of speech impairment in frontotemporal dementia (FTD), primary progressive aphasia (PPA), and progressive apraxia of speech in order to identify the most effective measures for diagnosis and monitoring, and to elucidate associations between speech and neuroimaging. Method: Speech and…
An Innovative Academic Progression in Nursing Model in New York State.
Markowitz, Marianne; Bastable, Susan B
2017-05-01
The Dual Degree Partnership in Nursing (DDPN) is a unique articulation model created in 2005 between two nursing programs that provides a seamless pathway for students to earn both an associate's degree and a bachelor's degree in nursing while benefiting from the strengths of each program. Archival data has been systematically collected for a decade on admission, progression, retention, satisfaction, graduation, and NCLEX-RN pass rates to measure the reliability, validity, and integrity of this DDPN model for nursing education. The findings demonstrate consistent performance and positive outcomes on all factors measured, which have been benchmarked against available state and national results. This innovative approach to academic progression in nursing is replicable and serves as a prototype to educate more nurses at the baccalaureate level, which directly contributes to the Institute of Medicine's goal of 80% of RNs having a minimum of a bachelor's degree by 2020. [J Nurs Educ. 2017;56(5):266-273.]. Copyright 2017, SLACK Incorporated.
Data-Driven Model Order Reduction for Bayesian Inverse Problems
Cui, Tiangang
2014-01-06
One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce the computational cost of numerical PDE evaluations in this context.
Accessing key steps of human tumor progression in vivo by using an avian embryo model
Hagedorn, Martin; Javerzat, Sophie; Gilges, Delphine; Meyre, Aurélie; de Lafarge, Benjamin; Eichmann, Anne; Bikfalvi, Andreas
2005-02-01
Experimental in vivo tumor models are essential for comprehending the dynamic process of human cancer progression, identifying therapeutic targets, and evaluating antitumor drugs. However, current rodent models are limited by high costs, long experimental duration, variability, restricted accessibility to the tumor, and major ethical concerns. To avoid these shortcomings, we investigated whether tumor growth on the chick chorio-allantoic membrane after human glioblastoma cell grafting would replicate characteristics of the human disease. Avascular tumors consistently formed within 2 days, then progressed through vascular endothelial growth factor receptor 2-dependent angiogenesis, associated with hemorrhage, necrosis, and peritumoral edema. Blocking of vascular endothelial growth factor receptor 2 and platelet-derived growth factor receptor signaling pathways by using small-molecule receptor tyrosine kinase inhibitors abrogated tumor development. Gene regulation during the angiogenic switch was analyzed by oligonucleotide microarrays. Defined sample selection for gene profiling permitted identification of regulated genes whose functions are associated mainly with tumor vascularization and growth. Furthermore, expression of known tumor progression genes identified in the screen (IL-6 and cysteine-rich angiogenic inducer 61) as well as potential regulators (lumican and F-box-only 6) follow similar patterns in patient glioma. The model reliably simulates key features of human glioma growth in a few days and thus could considerably increase the speed and efficacy of research on human tumor progression and preclinical drug screening. angiogenesis | animal model alternatives | glioblastoma
Progress towards an effective model for FeSe from high-accuracy first-principles quantum Monte Carlo
Busemeyer, Brian; Wagner, Lucas K.
While the origin of superconductivity in the iron-based materials is still controversial, the proximity of the superconductivity to magnetic order is suggestive that magnetism may be important. Our previous work has suggested that first-principles Diffusion Monte Carlo (FN-DMC) can capture magnetic properties of iron-based superconductors that density functional theory (DFT) misses, but which are consistent with experiment. We report on the progress of efforts to find simple effective models consistent with the FN-DMC description of the low-lying Hilbert space of the iron-based superconductor, FeSe. We utilize a procedure outlined by Changlani et al.[1], which both produces parameter values and indications of whether the model is a good description of the first-principles Hamiltonian. Using this procedure, we evaluate several models of the magnetic part of the Hilbert space found in the literature, as well as the Hubbard model, and a spin-fermion model. We discuss which interaction parameters are important for this material, and how the material-specific properties give rise to these interactions. U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Scientific Discovery through Advanced Computing (SciDAC) program under Award No. FG02-12ER46875, as well as the NSF Graduate Research Fellowship Program.
Tumour model with intrusive morphology, progressive phenotypical heterogeneity and memory
Atangana, Abdon; Alqahtani, Rubayyi T.
2018-03-01
The model of a tumour, taking into account invasive morphology, progressive phenotypical heterogeneity and also memory, is developed and analyzed in this paper. Three models are investigated: first we consider the model describing the proliferation concentrates in proximity of tumour boundaries, in which the oxygen levels are pronounced. Then we consider the model where the oxygen around the tumour is considered to be unchanged by the vascular system. Finally, we investigate the model of growth of tumours using the concept of non-local operators with the Mittag-Leffler kernel. We provide the numerical solution using the extended 3/8 Simpson method for the new trends of fractional integration for the proliferation concentrates in the proximity of the tumour model. Then we provide the exact solutions of the Gompertz model with three different fractional differentiations involving power law, exponential decay law and the Mittag-Leffler law.
Integrable higher order deformations of Heisenberg supermagnetic model
International Nuclear Information System (INIS)
Guo Jiafeng; Yan Zhaowen; Wang Shikun; Wu Ke; Zhao Weizhong
2009-01-01
The Heisenberg supermagnet model is an integrable supersymmetric system and has a close relationship with the strong electron correlated Hubbard model. In this paper, we investigate the integrable higher order deformations of Heisenberg supermagnet models with two different constraints: (i) S 2 =3S-2I for S is an element of USPL(2/1)/S(U(2)xU(1)) and (ii) S 2 =S for S is an element of USPL(2/1)/S(L(1/1)xU(1)). In terms of the gauge transformation, their corresponding gauge equivalent counterparts are derived.
Next-to-leading order corrections to the valon model
Indian Academy of Sciences (India)
A seminumerical solution to the valon model at next-to-leading order (NLO) in the Laguerre polynomials is presented. We used the valon model to generate the structure of proton with respect to the Laguerre polynomials method. The results are compared with H1 data and other parametrizations.
McNeish, Daniel; Dumas, Denis
2017-01-01
Recent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components-ability, capacity, and availability-where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study-Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.
Low-Order Modeling of Dynamic Stall on Airfoils in Incompressible Flow
Narsipur, Shreyas
Unsteady aerodynamics has been a topic of research since the late 1930's and has increased in popularity among researchers studying dynamic stall in helicopters, insect/bird flight, micro air vehicles, wind-turbine aerodynamics, and ow-energy harvesting devices. Several experimental and computational studies have helped researchers gain a good understanding of the unsteady ow phenomena, but have proved to be expensive and time-intensive for rapid design and analysis purposes. Since the early 1970's, the push to develop low-order models to solve unsteady ow problems has resulted in several semi-empirical models capable of effectively analyzing unsteady aerodynamics in a fraction of the time required by high-order methods. However, due to the various complexities associated with time-dependent flows, several empirical constants and curve fits derived from existing experimental and computational results are required by the semi-empirical models to be an effective analysis tool. The aim of the current work is to develop a low-order model capable of simulating incompressible dynamic-stall type ow problems with a focus on accurately modeling the unsteady ow physics with the aim of reducing empirical dependencies. The lumped-vortex-element (LVE) algorithm is used as the baseline unsteady inviscid model to which augmentations are applied to model unsteady viscous effects. The current research is divided into two phases. The first phase focused on augmentations aimed at modeling pure unsteady trailing-edge boundary-layer separation and stall without leading-edge vortex (LEV) formation. The second phase is targeted at including LEV shedding capabilities to the LVE algorithm and combining with the trailing-edge separation model from phase one to realize a holistic, optimized, and robust low-order dynamic stall model. In phase one, initial augmentations to theory were focused on modeling the effects of steady trailing-edge separation by implementing a non-linear decambering
Exact Sampling and Decoding in High-Order Hidden Markov Models
Carter, S.; Dymetman, M.; Bouchard, G.
2012-01-01
We present a method for exact optimization and sampling from high order Hidden Markov Models (HMMs), which are generally handled by approximation techniques. Motivated by adaptive rejection sampling and heuristic search, we propose a strategy based on sequentially refining a lower-order language
Venus gravity and topography: 60th degree and order model
Konopliv, A. S.; Borderies, N. J.; Chodas, P. W.; Christensen, E. J.; Sjogren, W. L.; Williams, B. G.; Balmino, G.; Barriot, J. P.
1993-01-01
We have combined the most recent Pioneer Venus Orbiter (PVO) and Magellan (MGN) data with the earlier 1978-1982 PVO data set to obtain a new 60th degree and order spherical harmonic gravity model and a 120th degree and order spherical harmonic topography model. Free-air gravity maps are shown over regions where the most marked improvement has been obtained (Ishtar-Terra, Alpha, Bell and Artemis). Gravity versus topography relationships are presented as correlations per degree and axes orientation.
Model order reduction for complex high-tech systems
Lutowska, A.; Hochstenbach, M.E.; Schilders, W.H.A.; Michielsen, B.; Poirier, J.R.
2012-01-01
This paper presents a computationally efficient model order reduction (MOR) technique for interconnected systems. This MOR technique preserves block structures and zero blocks and exploits separate MOR approximations for the individual sub-systems in combination with low rank approximations for the
Gradient models in molecular biophysics: progress, challenges, opportunities
Bardhan, Jaydeep P.
2013-12-01
In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g., molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding nonlocal dielectric response. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain, and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost 40 years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The review concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.
From goal motivation to goal progress: the mediating role of coping in the Self-Concordance Model.
Gaudreau, Patrick; Carraro, Natasha; Miranda, Dave
2012-01-01
The present studies examined the mediating role of self-regulatory mechanisms in the relationship between goal motivation and goal progress in the Self-Concordance Model. First, a systematic review, using meta-analytical path analysis, supported the mediating role of effort and action planning in the positive association between autonomous goal motivation and goal progress. Second, results from two additional empirical studies, using structural equation modeling, lent credence to the mediating role of coping in the relationship between goal motivation and goal progress of university students. Autonomous goal motivation was positively associated with task-oriented coping, which predicted greater goal progress during midterm exams (Study 1, N=702) and at the end of the semester in a different sample (Study 2, N=167). Controlled goal motivation was associated with greater disengagement-oriented coping (Study 1 and Study 2) and lesser use of task-oriented coping (Study 2), which reduced goal progress. These results held up after controlling for perceived stress (Study 2). Our findings highlight the importance of coping in the "inception-to-attainment" goal process because autonomous goal motivation indirectly rather than directly predicts goal progress of university students through their usage of task-oriented coping.
A statistical-thermodynamic model for ordering phenomena in thin film intermetallic structures
International Nuclear Information System (INIS)
Semenova, Olga; Krachler, Regina
2008-01-01
Ordering phenomena in bcc (110) binary thin film intermetallics are studied by a statistical-thermodynamic model. The system is modeled by an Ising approach that includes only nearest-neighbor chemical interactions and is solved in a mean-field approximation. Vacancies and anti-structure atoms are considered on both sublattices. The model describes long-range ordering and simultaneously short-range ordering in the thin film. It is applied to NiAl thin films with B2 structure. Vacancy concentrations, thermodynamic activity profiles and the virtual critical temperature of order-disorder as a function of film composition and thickness are presented. The results point to an important role of vacancies in near-stoichiometric and Ni-rich NiAl thin films
Impact of Physics Parameterization Ordering in a Global Atmosphere Model
Donahue, Aaron S.; Caldwell, Peter M.
2018-02-01
Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.
Glesener, G. B.; Vican, L.
2015-12-01
Physical analog models and demonstrations can be effective educational tools for helping instructors teach abstract concepts in the Earth, planetary, and space sciences. Reducing the learning challenges for students using physical analog models and demonstrations, however, can often increase instructors' workload and budget because the cost and time needed to produce and maintain such curriculum materials is substantial. First, this presentation describes a working model for the Modeling and Educational Demonstrations Laboratory Curriculum Materials Center (MEDL-CMC) to support instructors' use of physical analog models and demonstrations in the science classroom. The working model is based on a combination of instructional resource models developed by the Association of College & Research Libraries and by the Physics Instructional Resource Association. The MEDL-CMC aims to make the curriculum materials available for all science courses and outreach programs within the institution where the MEDL-CMC resides. The sustainability and value of the MEDL-CMC comes from its ability to provide and maintain a variety of physical analog models and demonstrations in a wide range of science disciplines. Second, the presentation then reports on the development, progress, and future of the MEDL-CMC at the University of California Los Angeles (UCLA). Development of the UCLA MEDL-CMC was funded by a grant from UCLA's Office of Instructional Development and is supported by the Department of Earth, Planetary, and Space Sciences. Other UCLA science departments have recently shown interest in the UCLA MEDL-CMC services, and therefore, preparations are currently underway to increase our capacity for providing interdepartmental service. The presentation concludes with recommendations and suggestions for other institutions that wish to start their own MEDL-CMC in order to increase educational effectiveness and decrease instructor workload. We welcome an interuniversity collaboration to
de Punder, Yvonne M R; van Riel, Piet L C M; Fransen, Jaap
2015-03-01
To compare the performance of an extended model and a simplified prognostic model for joint damage in rheumatoid arthritis (RA) based on 3 baseline risk factors: anticyclic citrullinated peptide antibodies (anti-CCP), erosions, and acute-phase reaction. Data were used from the Nijmegen early RA cohort. An extended model and a simplified baseline prediction model were developed to predict joint damage progression between 0 and 3 years. Joint damage progression was assessed using the Ratingen score. In the extended model, prediction factors were positivity for anti-CCP and/or rheumatoid factor, the level of erythrocyte sedimentation rate, and the quantity of erosions. The prediction score was calculated as the sum of the regression coefficients. In the simplified model, the prediction factors were dichotomized and the number of risk factors was counted. Performances of both models were compared using discrimination and calibration. The models were internally validated using bootstrapping. The extended model resulted in a prediction score between 0 and 5.6 with an area under the receiver-operation characteristic (ROC) curve of 0.77 (95% CI 0.72-0.81). The simplified model resulted in a prediction score between 0 and 3. This model had an area under the ROC curve of 0.75 (95% CI 0.70-0.80). In internal validation, the 2 models showed reasonably well the agreement between observed and predicted probabilities for joint damage progression (Hosmer-Lemeshow test p > 0.05 and calibration slope near 1.0). A simple prediction model for joint damage progression in early RA, by only counting the number of risk factors, has adequate performance. This facilitates the translation of the theoretical prognostic models to daily clinical practice.
State reduced order models for the modelling of the thermal behavior of buildings
Energy Technology Data Exchange (ETDEWEB)
Menezo, Christophe; Bouia, Hassan; Roux, Jean-Jacques; Depecker, Patrick [Institute National de Sciences Appliquees de Lyon, Villeurbanne Cedex, (France). Centre de Thermique de Lyon (CETHIL). Equipe Thermique du Batiment]. E-mail: menezo@insa-cethil-etb.insa-lyon.fr; bouia@insa-cethil-etb.insa-lyon.fr; roux@insa-cethil-etb.insa-lyon.fr; depecker@insa-cethil-etb.insa-lyon.fr
2000-07-01
This work is devoted to the field of building physics and related to the reduction of heat conduction models. The aim is to enlarge the model libraries of heat and mass transfer codes through limiting the considerable dimensions reached by the numerical systems during the modelling process of a multizone building. We show that the balanced realization technique, specifically adapted to the coupling of reduced order models with the other thermal phenomena, turns out to be very efficient. (author)
Quo natas, Danio?—Recent Progress in Modeling Cancer in Zebrafish
Directory of Open Access Journals (Sweden)
Stefanie Kirchberger
2017-08-01
Full Text Available Over the last decade, zebrafish has proven to be a powerful model in cancer research. Zebrafish form tumors that histologically and genetically resemble human cancers. The live imaging and cost-effective compound screening possible with zebrafish especially complement classic mouse cancer models. Here, we report recent progress in the field, including genetically engineered zebrafish cancer models, xenotransplantation of human cancer cells into zebrafish, promising approaches toward live investigation of the tumor microenvironment, and identification of therapeutic strategies by performing compound screens on zebrafish cancer models. Given the recent advances in genome editing, personalized zebrafish cancer models are now a realistic possibility. In addition, ongoing automation will soon allow high-throughput compound screening using zebrafish cancer models to be part of preclinical precision medicine approaches.
A model to calculate the progression of the centre of pressure under the foot during gait analysis.
Louey, Melissa Gar Yee; Mudge, Anita; Wojciechowski, Elizabeth; Sangeux, Morgan
2017-09-01
Pedobarography and the centre of pressure (COP) progression is useful to understand foot function. Pedobarography is often unavailable in gait laboratories or completed asynchronously to kinematic and kinetic data collection. This paper presents a model that allows calculation of COP progression synchronously using force plate data. The model is an adjunct to Plug-In-Gait and was applied to 49 typically developing children to create reference COP data. COP progressions were noted to spend 8% of stance behind the ankle joint centre, traverse lateral of the longitudinal axis of the foot through the midfoot for 76% of stance and finishing past the second metatarsal head on the medial side for 16% of stance. It is hoped the model will bridge the information gap for gait laboratories lacking pedobarography during foot assessments and will open up the possibility of retrospective research into COP progression based indices on kinematic data. Copyright © 2017 Elsevier B.V. All rights reserved.
Xiang, Hong-Jun; Zhang, Zhi-Wei; Shi, Zhi-Fei; Li, Hong
2018-04-01
A fully coupled modeling approach is developed for piezoelectric energy harvesters in this work based on the use of available robust finite element packages and efficient reducing order modeling techniques. At first, the harvester is modeled using finite element packages. The dynamic equilibrium equations of harvesters are rebuilt by extracting system matrices from the finite element model using built-in commands without any additional tools. A Krylov subspace-based scheme is then applied to obtain a reduced-order model for improving simulation efficiency but preserving the key features of harvesters. Co-simulation of the reduced-order model with nonlinear energy harvesting circuits is achieved in a system level. Several examples in both cases of harmonic response and transient response analysis are conducted to validate the present approach. The proposed approach allows to improve the simulation efficiency by several orders of magnitude. Moreover, the parameters used in the equivalent circuit model can be conveniently obtained by the proposed eigenvector-based model order reduction technique. More importantly, this work establishes a methodology for modeling of piezoelectric energy harvesters with any complicated mechanical geometries and nonlinear circuits. The input load may be more complex also. The method can be employed by harvester designers to optimal mechanical structures or by circuit designers to develop novel energy harvesting circuits.
Measurements and models for hazardous chemical and mixed wastes. 1998 annual progress report
International Nuclear Information System (INIS)
Holcomb, C.; Louie, B.; Mullins, M.E.; Outcalt, S.L.; Rogers, T.N.; Watts, L.
1998-01-01
'Aqueous waste of various chemical compositions constitutes a significant fraction of the total waste produced by industry in the US. A large quantity of the waste generated by the US chemical process industry is waste water. In addition, the majority of the waste inventory at DoE sites previously used for nuclear weapons production is aqueous waste. Large quantities of additional aqueous waste are expected to be generated during the clean-up of those sites. In order to effectively treat, safely handle, and properly dispose of these wastes, accurate and comprehensive knowledge of basic thermophysical property information is paramount. This knowledge will lead to huge savings by aiding in the design and optimization of treatment and disposal processes. The main objectives of this project are: Develop and validate models that accurately predict the phase equilibria and thermodynamic properties of hazardous aqueous systems necessary for the safe handling and successful design of separation and treatment processes for hazardous chemical and mixed wastes. Accurately measure the phase equilibria and thermodynamic properties of a representative system (water + acetone + isopropyl alcohol + sodium nitrate) over the applicable ranges of temperature, pressure, and composition to provide the pure component, binary, ternary, and quaternary experimental data required for model development. As of May, 1998, nine months into the first year of a three year project, the authors have made significant progress in the database development, have begun testing the models, and have been performance testing the apparatus on the pure components.'
Order aggressiveness and order book dynamics
DEFF Research Database (Denmark)
Hall, Anthony D.; Hautsch, Nikolaus
2006-01-01
In this paper, we study the determinants of order aggressiveness and traders’ order submission strategy in an open limit order book market. Applying an order classification scheme, we model the most aggressive market orders, limit orders as well as cancellations on both sides of the market...... employing a six-dimensional autoregressive conditional intensity model. Using order book data from the Australian Stock Exchange, we find that market depth, the queued volume, the bid-ask spread, recent volatility, as well as recent changes in both the order flow and the price play an important role...... in explaining the determinants of order aggressiveness. Overall, our empirical results broadly confirm theoretical predictions on limit order book trading. However, we also find evidence for behavior that can be attributed to particular liquidity and volatility effects...
Modeling Human Behaviour with Higher Order Logic: Insider Threats
DEFF Research Database (Denmark)
Boender, Jaap; Ivanova, Marieta Georgieva; Kammuller, Florian
2014-01-01
it to the sociological process of logical explanation. As a case study on modeling human behaviour, we present the modeling and analysis of insider threats as a Higher Order Logic theory in Isabelle/HOL. We show how each of the three step process of sociological explanation can be seen in our modeling of insider’s state......, its context within an organisation and the effects on security as outcomes of a theorem proving analysis....
Validation of a RANS transition model using a high-order weighted compact nonlinear scheme
Tu, GuoHua; Deng, XiaoGang; Mao, MeiLiang
2013-04-01
A modified transition model is given based on the shear stress transport (SST) turbulence model and an intermittency transport equation. The energy gradient term in the original model is replaced by flow strain rate to saving computational costs. The model employs local variables only, and then it can be conveniently implemented in modern computational fluid dynamics codes. The fifth-order weighted compact nonlinear scheme and the fourth-order staggered scheme are applied to discrete the governing equations for the purpose of minimizing discretization errors, so as to mitigate the confusion between numerical errors and transition model errors. The high-order package is compared with a second-order TVD method on simulating the transitional flow of a flat plate. Numerical results indicate that the high-order package give better grid convergence property than that of the second-order method. Validation of the transition model is performed for transitional flows ranging from low speed to hypersonic speed.
Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities.
Bardhan, Jaydeep P
2013-12-01
In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.
Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities
Bardhan, Jaydeep P.
2014-01-01
In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics. PMID:25505358
Directory of Open Access Journals (Sweden)
Helen C Johnson
Full Text Available Quantifying rates governing the clearance of Human Papillomavirus (HPV and its progression to clinical disease, together with viral transmissibility and the duration of naturally-acquired immunity, is essential in estimating the impact of vaccination programmes and screening or testing regimes. However, the complex natural history of HPV makes this difficult. We infer the viral transmissibility, rate of waning natural immunity and rates of progression and clearance of infection of 13 high-risk and 2 non-oncogenic HPV types, making use of a number of rich datasets from Sweden. Estimates of viral transmissibility, clearance of initial infection and waning immunity were derived in a Bayesian framework by fitting a susceptible-infectious-recovered-susceptible (SIRS transmission model to age- and type-specific HPV prevalence data from both a cross-sectional study and a randomised controlled trial (RCT of primary HPV screening. The models fitted well, but over-estimated the prevalence of four high-risk types with respect to the data. Three of these types (HPV-33, -35 and -58 are among the most closely related phylogenetically to the most prevalent HPV-16. The fourth (HPV-45 is the most closely related to HPV-18; the second most prevalent type. We suggest that this may be an indicator of cross-immunity. Rates of progression and clearance of clinical lesions were additionally estimated from longitudinal data gathered as part of the same RCT. Our estimates of progression and clearance rates are consistent with the findings of survival analysis studies and we extend the literature by estimating progression and clearance rates for non-16 and non-18 high-risk types. We anticipate that such type-specific estimates will be useful in the parameterisation of further models and in developing our understanding of HPV natural history.
Reduced-order LPV model of flexible wind turbines from high fidelity aeroelastic codes
DEFF Research Database (Denmark)
Adegas, Fabiano Daher; Sønderby, Ivan Bergquist; Hansen, Morten Hartvig
2013-01-01
of high-order linear time invariant (LTI) models. Firstly, the high-order LTI models are locally approximated using modal and balanced truncation and residualization. Then, an appropriate coordinate transformation is applied to allow interpolation of the model matrices between points on the parameter...
Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models
Hooten, Mevin B.; Leeds, William B.; Fiechter, Jerome; Wikle, Christopher K.
2011-01-01
We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.
Progress towards Continental River Dynamics modeling
Yu, Cheng-Wei; Zheng, Xing; Liu, Frank; Maidment, Daivd; Hodges, Ben
2017-04-01
The high-resolution National Water Model (NWM), launched by U.S. National Oceanic and Atmospheric Administration (NOAA) in August 2016, has shown it is possible to provide real-time flow prediction in rivers and streams across the entire continental United States. The next step for continental-scale modeling is moving from reduced physics (e.g. Muskingum-Cunge) to full dynamic modeling with the Saint-Venant equations. The Simulation Program for River Networks (SPRNT) provides a computational approach for the Saint-Venant equations, but obtaining sufficient channel bathymetric data and hydraulic roughness is seen as a critical challenge. However, recent work has shown the Height Above Nearest Drainage (HAND) method can be applied with the National Elevation Dataset (NED) to provide automated estimation of effective channel bathymetry suitable for large-scale hydraulic simulations. The present work examines the use of SPRNT with the National Hydrography Dataset (NHD) and HAND-derived bathymetry for automated generation of rating curves that can be compared to existing data. The approach can, in theory, be applied to every stream reach in the NHD and thus provide flood guidance where none is available. To test this idea we generated 2000+ rating curves in two catchments in Texas and Alabama (USA). Field data from the USGS and flood records from an Austin, Texas flood in May 2015 were used as validation. Large-scale implementation of this idea requires addressing several critical difficulties associated with numerical instabilities, including ill-posed boundary conditions generated in automated model linkages and inconsistencies in the river geometry. A key to future progress is identifying efficient approaches to isolate numerical instability contributors in a large time-space varying solution. This research was supported in part by the National Science Foundation under grant number CCF-1331610.
A simplified parsimonious higher order multivariate Markov chain model
Wang, Chao; Yang, Chuan-sheng
2017-09-01
In this paper, a simplified parsimonious higher-order multivariate Markov chain model (SPHOMMCM) is presented. Moreover, parameter estimation method of TPHOMMCM is give. Numerical experiments shows the effectiveness of TPHOMMCM.
Fundamental Frequency and Model Order Estimation Using Spatial Filtering
DEFF Research Database (Denmark)
Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2014-01-01
extend this procedure to account for inharmonicity using unconstrained model order estimation. The simulations show that beamforming improves the performance of the joint estimates of fundamental frequency and the number of harmonics in low signal to interference (SIR) levels, and an experiment......In signal processing applications of harmonic-structured signals, estimates of the fundamental frequency and number of harmonics are often necessary. In real scenarios, a desired signal is contaminated by different levels of noise and interferers, which complicate the estimation of the signal...... parameters. In this paper, we present an estimation procedure for harmonic-structured signals in situations with strong interference using spatial filtering, or beamforming. We jointly estimate the fundamental frequency and the constrained model order through the output of the beamformers. Besides that, we...
Collaborative Research and Development (CR&D). Task Order 0049: Tribological Modeling
2008-05-01
scratch test for TiN on stainless steel with better substrate mechanical properties. This present study was focused on the study of stress distribution...AFRL-RX-WP-TR-2010-4189 COLLABORATIVE RESEARCH AND DEVELOPMENT (CR&D) Task Order 0049: Tribological Modeling Young Sup Kang Universal...SUBTITLE COLLABORATIVE RESEARCH AND DEVELOPMENT (CR&D) Task Order 0049: Tribological Modeling 5a. CONTRACT NUMBER F33615-03-D-5801-0049 5b
Constructing set-valued fundamental diagrams from jamiton solutions in second order traffic models
Seibold, Benjamin
2013-09-01
Fundamental diagrams of vehicular traiic ow are generally multivalued in the congested ow regime. We show that such set-valued fundamental diagrams can be constructed systematically from simple second order macroscopic traiic models, such as the classical Payne-Whitham model or the inhomogeneous Aw-Rascle-Zhang model. These second order models possess nonlinear traveling wave solutions, called jamitons, and the multi-valued parts in the fundamental diagram correspond precisely to jamiton-dominated solutions. This study shows that transitions from function-valued to set-valued parts in a fundamental diagram arise naturally in well-known second order models. As a particular consequence, these models intrinsically reproduce traiic phases. © American Institute of Mathematical Sciences.
Constructing set-valued fundamental diagrams from jamiton solutions in second order traffic models
Seibold, Benjamin; Flynn, Morris R.; Kasimov, Aslan R.; Rosales, Rodolfo Rubé n
2013-01-01
Fundamental diagrams of vehicular traiic ow are generally multivalued in the congested ow regime. We show that such set-valued fundamental diagrams can be constructed systematically from simple second order macroscopic traiic models, such as the classical Payne-Whitham model or the inhomogeneous Aw-Rascle-Zhang model. These second order models possess nonlinear traveling wave solutions, called jamitons, and the multi-valued parts in the fundamental diagram correspond precisely to jamiton-dominated solutions. This study shows that transitions from function-valued to set-valued parts in a fundamental diagram arise naturally in well-known second order models. As a particular consequence, these models intrinsically reproduce traiic phases. © American Institute of Mathematical Sciences.
Empirical analyses of a choice model that captures ordering among attribute values
DEFF Research Database (Denmark)
Mabit, Stefan Lindhard
2017-01-01
an alternative additionally because it has the highest price. In this paper, we specify a discrete choice model that takes into account the ordering of attribute values across alternatives. This model is used to investigate the effect of attribute value ordering in three case studies related to alternative-fuel...... vehicles, mode choice, and route choice. In our application to choices among alternative-fuel vehicles, we see that especially the price coefficient is sensitive to changes in ordering. The ordering effect is also found in the applications to mode and route choice data where both travel time and cost...
Directory of Open Access Journals (Sweden)
Mao Yu
2009-07-01
Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From
Roşu, M. M.; Tarbă, C. I.; Neagu, C.
2016-11-01
The current models for inventory management are complementary, but together they offer a large pallet of elements for solving complex problems of companies when wanting to establish the optimum economic order quantity for unfinished products, row of materials, goods etc. The main objective of this paper is to elaborate an automated decisional model for the calculus of the economic order quantity taking into account the price regressive rates for the total order quantity. This model has two main objectives: first, to determine the periodicity when to be done the order n or the quantity order q; second, to determine the levels of stock: lighting control, security stock etc. In this way we can provide the answer to two fundamental questions: How much must be ordered? When to Order? In the current practice, the business relationships with its suppliers are based on regressive rates for price. This means that suppliers may grant discounts, from a certain level of quantities ordered. Thus, the unit price of the products is a variable which depends on the order size. So, the most important element for choosing the optimum for the economic order quantity is the total cost for ordering and this cost depends on the following elements: the medium price per units, the stock cost, the ordering cost etc.
Average inactivity time model, associated orderings and reliability properties
Kayid, M.; Izadkhah, S.; Abouammoh, A. M.
2018-02-01
In this paper, we introduce and study a new model called 'average inactivity time model'. This new model is specifically applicable to handle the heterogeneity of the time of the failure of a system in which some inactive items exist. We provide some bounds for the mean average inactivity time of a lifespan unit. In addition, we discuss some dependence structures between the average variable and the mixing variable in the model when original random variable possesses some aging behaviors. Based on the conception of the new model, we introduce and study a new stochastic order. Finally, to illustrate the concept of the model, some interesting reliability problems are reserved.
The confluence model: birth order as a within-family or between-family dynamic?
Zajonc, R B; Sulloway, Frank J
2007-09-01
The confluence model explains birth-order differences in intellectual performance by quantifying the changing dynamics within the family. Wichman, Rodgers, and MacCallum (2006) claimed that these differences are a between-family phenomenon--and hence are not directly related to birth order itself. The study design and analyses presented by Wichman et al. nevertheless suffer from crucial shortcomings, including their use of unfocused tests, which cause statistically significant trends to be overlooked. In addition, Wichman et al. treated birth-order effects as a linear phenomenon thereby ignoring the confluence model's prediction that these two samples may manifest opposing results based on age. This article cites between- and within-family data that demonstrate systematic birth-order effects as predicted by the confluence model. The corpus of evidence invoked here offers strong support for the assumption of the confluence model that birth-order differences in intellectual performance are primarily a within-family phenomenon.
Hui, Zhenyang; Wu, Beiping; Hu, Youjian; Ziggah, Yao Yevenyo
2017-12-01
Obtaining high-precision filtering results from airborne lidar point clouds in complex environments has always been a hot topic. Mathematical morphology was widely used for filtering, owing to its simplicity and high efficiency. However, the morphology-based algorithms are deficient in preserving terrain details. In order to obtain a better filtering effect, this paper proposed an improved progressive morphological filter based on hierarchical radial basis function interpolation (PMHR) to refine the classical progressive morphological filter. PMHR involved two main improvements, namely, automatic setting of self-adaptive thresholds and terrain details preservation, respectively. The performance of PMHR was evaluated using datasets provided by the International Society for Photogrammetry and Remote Sensing. Experimental results show that PMHR achieved good performance under variant terrain features with an average total error of 4.27% and average Kappa coefficient of 84.57%.
A tridiagonal parsimonious higher order multivariate Markov chain model
Wang, Chao; Yang, Chuan-sheng
2017-09-01
In this paper, we present a tridiagonal parsimonious higher-order multivariate Markov chain model (TPHOMMCM). Moreover, estimation method of the parameters in TPHOMMCM is give. Numerical experiments illustrate the effectiveness of TPHOMMCM.
Identification of the reduced order models of a BWR reactor
International Nuclear Information System (INIS)
Hernandez S, A.
2004-01-01
The present work has as objective to analyze the relative stability of a BWR type reactor. It is analyzed that so adaptive it turns out to identify the parameters of a model of reduced order so that this it reproduces a condition of given uncertainty. This will take of a real fact happened in the La Salle plant under certain operation conditions of power and flow of coolant. The parametric identification is carried out by means of an algorithm of recursive least square and an Output Error model (Output Error), measuring the output power of the reactor when the instability is present, and considering that it is produced by a change in the reactivity of the system in the same way that a sign of type step. Also it is carried out an analytic comparison of the relative stability, analyzing two types of answers: the original answer of the uncertainty of the reactor vs. the obtained response identifying the parameters of the model of reduced order, reaching the conclusion that it is very viable to adapt a model of reduced order to study the stability of a reactor, under the only condition to consider that the dynamics of the reactivity is of step type. (Author)
Ordering phenomena and non-equilibrium properties of lattice gas models
International Nuclear Information System (INIS)
Fiig, T.
1994-03-01
This report falls within the general field of ordering processes and non-equilibrium properties of lattice gas models. The theory of diffuse scattering of lattice gas models originating from a random distribution of clusters is considered. We obtain relations between the diffuse part of the structure factor S dif (q), the correlation function C(r), and the size distribution of clusters D(n). For a number of distributions we calculate S dif (q) exactly in one dimension, and discuss the possibility for a Lorentzian and a Lorentzian square lineshape to arise. We discuss the two- and three-dimensional oxygen ordering processes in the high T c superconductor YBa 2 Cu 3 O 6+x based on a simple anisotropic lattice gas model. We calculate the structural phase diagram by Monte Carlo simulation and compared the results with experimental data. The structure factor of the oxygen ordering properties has been calculated in both two and three dimensions by Monte Carlo simulation. We report on results obtained from large scale computations on the Connection Machine, which are in excellent agreement with recent neutron diffraction data. In addition we consider the effect of the diffusive motion of metal-ion dopants on the oxygen ordering properties on YBa 2 Cu 3 O 6+x . The stationary properties of metastability in long-range interaction models are studied by application of a constrained transfer matrix (CTM) formalism. The model considered, which exhibits several metastable states, is an extension of the Blume Capel model to include weak long-range interactions. We show, that the decay rate of the metastable states is closely related to the imaginary part of the equilibrium free-energy density obtained from the CTM formalism. We discuss a class of lattice gas model for dissipative transport in the framework of a Langevin description, which is capable of producing power law spectra for the density fluctuations. We compare with numerical results obtained from simulations of a
Performance of a reduced-order FSI model for flow-induced vocal fold vibration
Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team
2017-11-01
Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.
A MATHEMATICAL MODEL OF CHP 2000 TYPE PROGRESSIVE GEAR
Directory of Open Access Journals (Sweden)
Paweł Lonkwic
2016-12-01
Full Text Available The project of CHP2000 type progressive gear has been presented in the article. The offered solution from its construction point of view differs from the existing solutions due to the application of Belleville springs packets supporting the braking roller cam and achieving a flexible range of the gear loading. The standard concept of the gear loading within a mathematical and a geometrical model has been presented in the article. The proposed solution can be used in the friction lifts with the loading capacity from 8500 up to 20000 N.
Progress and Overview on Neutronics Modelling Development in RTP
International Nuclear Information System (INIS)
Mohamad Hairie Rabir; Muhammad Rawi Mohamed Zin; Julia Abdul Karim
2016-01-01
Reactor calculation and simulation are significantly important to ensure safety and better utilization of a research reactor. The Malaysian PUSPATI TRIGA Reactor (RTP) achieved initial criticality on June 28, 1982. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes. Since early 90s, neutronics modelling were used as part of its routine in-core fuel management activities. The are several computer codes have been used in RTP since then, based on 1D neutron diffusion, 2D neutron diffusion and 3D Monte Carlo neutron transport method. This paper describes current progress and overview on neutronics modelling development in RTP. Several important parameters were analysed such as k_e_f_f, reactivity, neutron flux, power distribution, B_e_f_f, and fission product build-up for the latest core configuration. The developed core neutronics model was validated by means of comparison with experimental and measurement data. Along with the RTP core model, the calculation procedure also developed to establish better prediction capability of RTP behaviour. (author)
A high-order multiscale finite-element method for time-domain acoustic-wave modeling
Gao, Kai; Fu, Shubin; Chung, Eric T.
2018-05-01
Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructs high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss-Lobatto-Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.
HOKF: High Order Kalman Filter for Epilepsy Forecasting Modeling.
Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee
2017-08-01
Epilepsy forecasting has been extensively studied using high-order time series obtained from scalp-recorded electroencephalography (EEG). An accurate seizure prediction system would not only help significantly improve patients' quality of life, but would also facilitate new therapeutic strategies to manage epilepsy. This paper thus proposes an improved Kalman Filter (KF) algorithm to mine seizure forecasts from neural activity by modeling three properties in the high-order EEG time series: noise, temporal smoothness, and tensor structure. The proposed High-Order Kalman Filter (HOKF) is an extension of the standard Kalman filter, for which higher-order modeling is limited. The efficient dynamic of HOKF system preserves the tensor structure of the observations and latent states. As such, the proposed method offers two main advantages: (i) effectiveness with HOKF results in hidden variables that capture major evolving trends suitable to predict neural activity, even in the presence of missing values; and (ii) scalability in that the wall clock time of the HOKF is linear with respect to the number of time-slices of the sequence. The HOKF algorithm is examined in terms of its effectiveness and scalability by conducting forecasting and scalability experiments with a real epilepsy EEG dataset. The results of the simulation demonstrate the superiority of the proposed method over the original Kalman Filter and other existing methods. Copyright © 2017 Elsevier B.V. All rights reserved.
DEFF Research Database (Denmark)
Nielsen, Mette Slot; Glud, Andreas Nørgaard; Møller, Arne
2011-01-01
to discover effective compounds halting PD progression have so far failed in clinical trials, perhaps because current animal models do not imitate the neuropathological progression of PD well enough. We recently established a progressive large animal PD model in Göttingen minipigs based on chronic infusion......Parkinson disease (PD) is a common neurodegenerative disorder, resulting from a progressive dopaminergic neuron loss in the substantia nigra (SN). Alpha-synuclein positive neuronal inclusion bodies and progressive loss of dopaminergic striatal terminals is also well described in PD. Attempts...... the SN were paraffin embedded and immunohistochemically stained for tyrosine hydroxylase (TH) and alpha-synuclein. Stereological examination of the SN showed progressive nigral neuron loss with increased MPTP dosages. Occasional neuronal staining confined to the cytoplasm and cell membrane was observed...
Changes in gene expression and cellular architecture in an ovarian cancer progression model.
Directory of Open Access Journals (Sweden)
Amy L Creekmore
organization and regulation of important downstream signaling events that may be involved in cancer progression. Thus, our MOSE-derived cell model represents a unique model for in depth mechanistic studies of ovarian cancer progression.
A Reduced Order Model to Predict Transient Flows around Straight Bladed Vertical Axis Wind Turbines
Directory of Open Access Journals (Sweden)
Soledad Le Clainche
2018-03-01
Full Text Available We develop a reduced order model to represent the complex flow behaviour around vertical axis wind turbines. First, we simulate vertical axis turbines using an accurate high order discontinuous Galerkin–Fourier Navier–Stokes Large Eddy Simulation solver with sliding meshes and extract flow snapshots in time. Subsequently, we construct a reduced order model based on a high order dynamic mode decomposition approach that selects modes based on flow frequency. We show that only a few modes are necessary to reconstruct the flow behaviour of the original simulation, even for blades rotating in turbulent regimes. Furthermore, we prove that an accurate reduced order model can be constructed using snapshots that do not sample one entire turbine rotation (but only a fraction of it, which reduces the cost of generating the reduced order model. Additionally, we compare the reduced order model based on the high order Navier–Stokes solver to fast 2D simulations (using a Reynolds Averaged Navier–Stokes turbulent model to illustrate the good performance of the proposed methodology.
A fourth order spline collocation approach for a business cycle model
Sayfy, A.; Khoury, S.; Ibdah, H.
2013-10-01
A collocation approach, based on a fourth order cubic B-splines is presented for the numerical solution of a Kaleckian business cycle model formulated by a nonlinear delay differential equation. The equation is approximated and the nonlinearity is handled by employing an iterative scheme arising from Newton's method. It is shown that the model exhibits a conditionally dynamical stable cycle. The fourth-order rate of convergence of the scheme is verified numerically for different special cases.
Unidimensional factor models imply weaker partial correlations than zero-order correlations.
van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J
2018-06-01
In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.
Rijmen, Frank; Jeon, Minjeong; von Davier, Matthias; Rabe-Hesketh, Sophia
2014-01-01
Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the model does not suffer from the curse of…
Raghupathy, Arun; Ghia, Karman; Ghia, Urmila
2008-11-01
Compact Thermal Models (CTM) to represent IC packages has been traditionally developed using the DELPHI-based (DEvelopment of Libraries of PHysical models for an Integrated design) methodology. The drawbacks of this method are presented, and an alternative method is proposed. A reduced-order model that provides the complete thermal information accurately with less computational resources can be effectively used in system level simulations. Proper Orthogonal Decomposition (POD), a statistical method, can be used to reduce the order of the degree of freedom or variables of the computations for such a problem. POD along with the Galerkin projection allows us to create reduced-order models that reproduce the characteristics of the system with a considerable reduction in computational resources while maintaining a high level of accuracy. The goal of this work is to show that this method can be applied to obtain a boundary condition independent reduced-order thermal model for complex components. The methodology is applied to the 1D transient heat equation.
Reduced order dynamic model for polysaccharides molecule attached to an atomic force microscope
International Nuclear Information System (INIS)
Tang Deman; Li Aiqin; Attar, Peter; Dowell, Earl H.
2004-01-01
A dynamic analysis and numerical simulation has been conducted of a polysaccharides molecular structure (a ten (10) single-α-D-glucose molecule chain) connected to a moving atomic force microscope (AFM). Sinusoidal base excitation of the AFM cantilevered beam is considered. First a linearized perturbation model is constructed for the complex polysaccharides molecular structure. Then reduced order (dynamic) models based upon a proper orthogonal decomposition (POD) technique are constructed using global modes for both the linearized perturbation model and for the full nonlinear model. The agreement between the original and reduced order models (ROM/POD) is very good even when only a few global modes are included in the ROM for either the linear case or for the nonlinear case. The computational advantage of the reduced order model is clear from the results presented
Ordering Cost Reduction in Inventory Model with Defective Items and Backorder Price Discount
Directory of Open Access Journals (Sweden)
Karuppuchamy Annadurai
2014-01-01
Full Text Available In the real market, as unsatisfied demands occur, the longer the length of lead time is, the smaller the proportion of backorder would be. In order to make up for the inconvenience and even the losses of royal and patient customers, the supplier may offer a backorder price discount to secure orders during the shortage period. Also, ordering policies determined by conventional inventory models may be inappropriate for the situation in which an arrival lot contains some defective items. To compensate for the inconvenience of backordering and to secure orders, the supplier may offer a price discount on the stockout item. The purpose of this study is to explore a coordinated inventory model including defective arrivals by allowing the backorder price discount and ordering cost as decision variables. There are two inventory models proposed in this paper, one with normally distributed demand and another with distribution free demand. A computer code using the software Matlab 7.0 is developed to find the optimal solution and present numerical examples to illustrate the models. The results in the numerical examples indicate that the savings of the total cost are realized through ordering cost reduction and backorder price discount.
Joint modelling of longitudinal CEA tumour marker progression and survival data on breast cancer
Borges, Ana; Sousa, Inês; Castro, Luis
2017-06-01
This work proposes the use of Biostatistics methods to study breast cancer in patients of Braga's Hospital Senology Unit, located in Portugal. The primary motivation is to contribute to the understanding of the progression of breast cancer, within the Portuguese population, using a more complex statistical model assumptions than the traditional analysis that take into account a possible existence of a serial correlation structure within a same subject observations. We aim to infer which risk factors aect the survival of Braga's Hospital patients, diagnosed with breast tumour. Whilst analysing risk factors that aect a tumour markers used on the surveillance of disease progression the Carcinoembryonic antigen (CEA). As survival and longitudinal processes may be associated, it is important to model these two processes together. Hence, a joint modelling of these two processes to infer on the association of these was conducted. A data set of 540 patients, along with 50 variables, was collected from medical records of the Hospital. A joint model approach was used to analyse these data. Two dierent joint models were applied to the same data set, with dierent parameterizations which give dierent interpretations to model parameters. These were used by convenience as the ones implemented in R software. Results from the two models were compared. Results from joint models, showed that the longitudinal CEA values were signicantly associated with the survival probability of these patients. A comparison between parameter estimates obtained in this analysis and previous independent survival[4] and longitudinal analysis[5][6], lead us to conclude that independent analysis brings up bias parameter estimates. Hence, an assumption of association between the two processes in a joint model of breast cancer data is necessary. Results indicate that the longitudinal progression of CEA is signicantly associated with the probability of survival of these patients. Hence, an assumption of
Universal block diagram based modeling and simulation schemes for fractional-order control systems.
Bai, Lu; Xue, Dingyü
2017-05-08
Universal block diagram based schemes are proposed for modeling and simulating the fractional-order control systems in this paper. A fractional operator block in Simulink is designed to evaluate the fractional-order derivative and integral. Based on the block, the fractional-order control systems with zero initial conditions can be modeled conveniently. For modeling the system with nonzero initial conditions, the auxiliary signal is constructed in the compensation scheme. Since the compensation scheme is very complicated, therefore the integrator chain scheme is further proposed to simplify the modeling procedures. The accuracy and effectiveness of the schemes are assessed in the examples, the computation results testify the block diagram scheme is efficient for all Caputo fractional-order ordinary differential equations (FODEs) of any complexity, including the implicit Caputo FODEs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
38 CFR 21.7653 - Progress, conduct, and attendance.
2010-07-01
... on which the school official who is responsible for determining whether a student is making progress...) Satisfactory pursuit of program. In order to receive educational assistance for pursuit of a program of education, a reservist must maintain satisfactory progress. Progress is unsatisfactory if the reservist does...
Trimming a hazard logic tree with a new model-order-reduction technique
Porter, Keith; Field, Edward; Milner, Kevin R
2017-01-01
The size of the logic tree within the Uniform California Earthquake Rupture Forecast Version 3, Time-Dependent (UCERF3-TD) model can challenge risk analyses of large portfolios. An insurer or catastrophe risk modeler concerned with losses to a California portfolio might have to evaluate a portfolio 57,600 times to estimate risk in light of the hazard possibility space. Which branches of the logic tree matter most, and which can one ignore? We employed two model-order-reduction techniques to simplify the model. We sought a subset of parameters that must vary, and the specific fixed values for the remaining parameters, to produce approximately the same loss distribution as the original model. The techniques are (1) a tornado-diagram approach we employed previously for UCERF2, and (2) an apparently novel probabilistic sensitivity approach that seems better suited to functions of nominal random variables. The new approach produces a reduced-order model with only 60 of the original 57,600 leaves. One can use the results to reduce computational effort in loss analyses by orders of magnitude.
Soepenberg, G.D.; Land, M.J.; Gaalman, G.J.C.
This paper describes the development of a new tool for facilitating the diagnosis of logistic improvement opportunities in make-to-order (MTO) companies. Competitiveness of these companies increasingly imposes needs upon delivery reliability. In order to achieve high delivery reliability, both the
Arslan, Burcu; Taatgen, Niels A.; Verbrugge, Rineke
2017-01-01
The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback “Wrong,” they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children’s failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy. PMID:28293206
Arslan, Burcu; Taatgen, Niels A; Verbrugge, Rineke
2017-01-01
The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.
Anisotropic Third-Order Regularization for Sparse Digital Elevation Models
Lellmann, Jan; Morel, Jean-Michel; Schö nlieb, Carola-Bibiane
2013-01-01
features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE
Zheng, Guo; Wang, Jue; Wang, Lin; Zhou, Muchun; Xin, Yu; Song, Minmin
2017-11-15
The general formulae for second-order moments of Schell-model beams with various correlation functions in atmospheric turbulence are derived and validated by the Bessel-Gaussian Schell-model beams and cosine-Gaussian-correlated Schell-model beams. Our finding shows that the second-order moments of partially coherent Schell-model beams are related to the second-order partial derivatives of source spectral degree of coherence at the origin. The formulae we provide are much more convenient to analyze and research propagation problems in turbulence.
Reduced order modeling in topology optimization of vibroacoustic problems
DEFF Research Database (Denmark)
Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Brunskog, Jonas
2017-01-01
complex 3D parts. The optimization process can therefore become highly time consuming due to the need to solve a large system of equations at each iteration. Projection-based parametric Model Order Reduction (pMOR) methods have successfully been applied for reducing the computational cost of material......There is an interest in introducing topology optimization techniques in the design process of structural-acoustic systems. In topology optimization, the design space must be finely meshed in order to obtain an accurate design, which results in large numbers of degrees of freedom when designing...... or size optimization in large vibroacoustic models; however, new challenges are encountered when dealing with topology optimization. Since a design parameter per element is considered, the total number of design variables becomes very large; this poses a challenge to most existing pMOR techniques, which...
Qi, Di
Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are
Eluru, Naveen; Chakour, Vincent; Chamberlain, Morgan; Miranda-Moreno, Luis F
2013-10-01
Vehicle operating speed measured on roadways is a critical component for a host of analysis in the transportation field including transportation safety, traffic flow modeling, roadway geometric design, vehicle emissions modeling, and road user route decisions. The current research effort contributes to the literature on examining vehicle speed on urban roads methodologically and substantively. In terms of methodology, we formulate a new econometric model framework for examining speed profiles. The proposed model is an ordered response formulation of a fractional split model. The ordered nature of the speed variable allows us to propose an ordered variant of the fractional split model in the literature. The proposed formulation allows us to model the proportion of vehicles traveling in each speed interval for the entire segment of roadway. We extend the model to allow the influence of exogenous variables to vary across the population. Further, we develop a panel mixed version of the fractional split model to account for the influence of site-specific unobserved effects. The paper contributes substantively by estimating the proposed model using a unique dataset from Montreal consisting of weekly speed data (collected in hourly intervals) for about 50 local roads and 70 arterial roads. We estimate separate models for local roads and arterial roads. The model estimation exercise considers a whole host of variables including geometric design attributes, roadway attributes, traffic characteristics and environmental factors. The model results highlight the role of various street characteristics including number of lanes, presence of parking, presence of sidewalks, vertical grade, and bicycle route on vehicle speed proportions. The results also highlight the presence of site-specific unobserved effects influencing the speed distribution. The parameters from the modeling exercise are validated using a hold-out sample not considered for model estimation. The results indicate
Vascular stents: Coupling full 3-D with reduced-order structural models
International Nuclear Information System (INIS)
Avdeev, I; Shams, M
2010-01-01
Self-expanding nitinol stents are used to treat peripheral arterial disease. The peripheral arteries are subjected to a combination of mechanical forces such as compression, torsion, bending, and contraction. Most commercially available peripheral self-expanding stents are composed of a series of sub-millimeter V-shaped struts, which are laser-cut from a nitinol tube and surface-treated for better fatigue performance. The numerical stent models must accurately predict location and distribution of local stresses and strains caused by large arterial deformations. Full 3-D finite element non-linear analysis of an entire stent is computationally expensive to the point of being prohibitive, especially for longer stents. Reduced-order models based on beam or shell elements are fairly accurate in capturing global deformations, but are not very helpful in predicting stent failure. We propose a mixed approach that combines the full 3-D model and reduced-order models. Several global-local, full 3-D/reduced-order finite element models of a peripheral self-expanding stent were validated and compared with experimental data. The kinematic constraint method used to couple various elements together was found to be very efficient and easily applicable to commercial FEA codes. The proposed mixed models can be used to accurately predict stent failure based on realistic (patient-specific), non-linear kinematic behavior of peripheral arteries.
Competing orders in the Hofstadter t -J model
Tu, Wei-Lin; Schindler, Frank; Neupert, Titus; Poilblanc, Didier
2018-01-01
The Hofstadter model describes noninteracting fermions on a lattice in the presence of an external magnetic field. Motivated by the plethora of solid-state phases emerging from electron interactions, we consider an interacting version of the Hofstadter model, including a Hubbard repulsion U . We investigate this model in the large-U limit corresponding to a t -J Hamiltonian with an external (orbital) magnetic field. By using renormalized mean-field theory supplemented by exact diagonalization calculations of small clusters, we find evidence for competing symmetry-breaking phases, exhibiting (possibly coexisting) charge, bond, and superconducting orders. Topological properties of the states are also investigated, and some of our results are compared to related experiments involving ultracold atoms loaded on optical lattices in the presence of a synthetic gauge field.
Anisotropic Third-Order Regularization for Sparse Digital Elevation Models
Lellmann, Jan
2013-01-01
We consider the problem of interpolating a surface based on sparse data such as individual points or level lines. We derive interpolators satisfying a list of desirable properties with an emphasis on preserving the geometry and characteristic features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE and higher-order total variation methods qualitatively and quantitatively on real-world digital elevation data. © 2013 Springer-Verlag.
Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network
Yao, Weigang; Liou, Meng-Sing
2012-01-01
The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis
Testing static tradeoff theiry against pecking order models of capital ...
African Journals Online (AJOL)
We test two models with the purpose of finding the best empirical explanation for corporate financing choice of a cross section of 27 Nigerian quoted companies. The models were developed to represent the Static tradeoff Theory and the Pecking order Theory of capital structure with a view to make comparison between ...
Directory of Open Access Journals (Sweden)
Maja Marijan
2016-02-01
Full Text Available A case study of student’s progress in piano playing was carried out as an empirical research investigating student’s progress in piano performance. The research was outlined as a multiple process carrying out in three phases. The paper discusses the valuation of the training model through the assessment of the student’s level of attainment. The analysis included descriptive statistics for all the variables, and correlations between variables and the level of attainment. Factors that influence the student’s progress in piano playing, student’s individual characteristics (traits,and cognitive abilities, were measured objectively and were related to significant aspect of musical behavior. These items were assessed at the commencement of the student’s tuition program and at the cut-off date set for the study period. Findings confirmed that the change of training model has significant impact on the student’s progress in very short period, in this case three-week research period. Introduction of organized, and intuitive training model influenced cognitive abilities and motor skills, and personality constructs, such as anxiety, motivation, sense of contentment, self confidence, energy and effort. The difference is large enough to permit the conclusion that the proper training model leads to an important progress in student’s piano playing.
Effective high-order solver with thermally perfect gas model for hypersonic heating prediction
International Nuclear Information System (INIS)
Jiang, Zhenhua; Yan, Chao; Yu, Jian; Qu, Feng; Ma, Libin
2016-01-01
Highlights: • Design proper numerical flux for thermally perfect gas. • Line-implicit LUSGS enhances efficiency without extra memory consumption. • Develop unified framework for both second-order MUSCL and fifth-order WENO. • The designed gas model can be applied to much wider temperature range. - Abstract: Effective high-order solver based on the model of thermally perfect gas has been developed for hypersonic heat transfer computation. The technique of polynomial curve fit coupling to thermodynamics equation is suggested to establish the current model and particular attention has been paid to the design of proper numerical flux for thermally perfect gas. We present procedures that unify five-order WENO (Weighted Essentially Non-Oscillatory) scheme in the existing second-order finite volume framework and a line-implicit method that improves the computational efficiency without increasing memory consumption. A variety of hypersonic viscous flows are performed to examine the capability of the resulted high order thermally perfect gas solver. Numerical results demonstrate its superior performance compared to low-order calorically perfect gas method and indicate its potential application to hypersonic heating predictions for real-life problem.
Bayesian Modeling of ChIP-chip Data Through a High-Order Ising Model
Mo, Qianxing; Liang, Faming
2010-01-01
approach to ChIP-chip data through an Ising model with high-order interactions. The proposed method naturally takes into account the intrinsic spatial structure of the data and can be used to analyze data from multiple platforms with different genomic
Correlation effects of third-order perturbation in the extended Hubbard model
International Nuclear Information System (INIS)
Wei, G.Z.; Nie, H.Q.; Li, L.; Zhang, K.Y.
1989-01-01
Using the local approach, a third-order perturbation calculation has been performed to investigate the effects of intra-atomic electron correlation and electron and spin correlation between nearest neighbour sites in the extended Hubbard model. It was found that significant correction of the third order over the second order results and, in comparison with the results of the third-order perturbation where only the intra-atomic electron correlation is included, the influence of the electron and spin correlation between nearest neighbour sites on the correlation energy is non-negligible. 17 refs., 3 figs
Flexible implementation of the Ensemble Model with arbitrary order of moments
Energy Technology Data Exchange (ETDEWEB)
Ackermann, W. [Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder (TEMF), Schlossgartenstrasse 8, D 64289 Darmstadt (Germany)]. E-mail: ackermann@temf.tu-darmstadt.de; Weiland, T. [Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder (TEMF), Schlossgartenstrasse 8, D 64289 Darmstadt (Germany)]. E-mail: thomas.weiland@temf.tu-darmstadt.de
2006-03-01
The Ensemble Model takes advantage of an approach to express the phase space particle distribution function in terms of the first, second and higher order moments instead of considering individual particles. Based on a new flexible implementation, an arbitrary number of orders can be processed and automatically converted into proper update equations for the simulation program V-Code. In this paper the influence of the introduction of higher order moments on the beam dynamics simulation is investigated. The achievable accuracy and the numerical efforts are compared with the ones obtained from the lower order calculations.
Low-order dynamical system model of a fully developed turbulent channel flow
Hamilton, Nicholas; Tutkun, Murat; Cal, Raúl Bayoán
2017-06-01
A reduced order model of a turbulent channel flow is composed from a direct numerical simulation database hosted at the Johns Hopkins University. Snapshot proper orthogonal decomposition (POD) is used to identify the Hilbert space from which the reduced order model is obtained, as the POD basis is defined to capture the optimal energy content by mode. The reduced order model is defined by coupling the evolution of the dynamic POD mode coefficients through their respective time derivative with a least-squares polynomial fit of terms up to third order. Parameters coupling the dynamics of the POD basis are defined in analog to those produced in the classical Galerkin projection. The resulting low-order dynamical system is tested for a range of basis modes demonstrating that the non-linear mode interactions do not lead to a monotonic decrease in error propagation. A basis of five POD modes accounts for 50% of the integrated turbulence kinetic energy but captures only the largest features of the turbulence in the channel flow and is not able to reflect the anticipated flow dynamics. Using five modes, the low-order model is unable to accurately reproduce Reynolds stresses, and the root-mean-square error of the predicted stresses is as great as 30%. Increasing the basis to 28 modes accounts for 90% of the kinetic energy and adds intermediate scales to the dynamical system. The difference between the time derivatives of the random coefficients associated with individual modes and their least-squares fit is amplified in the numerical integration leading to unstable long-time solutions. Periodic recalibration of the dynamical system is undertaken by limiting the integration time to the range of the sampled data and offering the dynamical system new initial conditions. Renewed initial conditions are found by pushing the mode coefficients in the end of the integration time toward a known point along the original trajectories identified through a least-squares projection. Under
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis
2018-01-01
The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Directory of Open Access Journals (Sweden)
Zhong Yi Wan
Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more
Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit
International Nuclear Information System (INIS)
Mandelli, Diego; Smith, Curtis L.; Alfonsi, Andrea; Rabiti, Cristian; Cogliati, Joshua J.; Talbot, Paul W.; Rinaldi, Ivan; Maljovec, Dan; Wang, Bei; Pascucci, Valerio; Zhao, Haihua
2015-01-01
The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.
Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit
Energy Technology Data Exchange (ETDEWEB)
Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Alfonsi, Andrea [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Cogliati, Joshua J. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Talbot, Paul W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rinaldi, Ivan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Maljovec, Dan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Wang, Bei [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pascucci, Valerio [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhao, Haihua [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2015-09-01
The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.
A posteriori model validation for the temporal order of directed functional connectivity maps.
Beltz, Adriene M; Molenaar, Peter C M
2015-01-01
A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data).
A posteriori model validation for the temporal order of directed functional connectivity maps
Directory of Open Access Journals (Sweden)
Adriene M. Beltz
2015-08-01
Full Text Available A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests, and (b to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates and substantive implications (e.g., higher order lags may be common in resting state data.
Using Count Data and Ordered Models in National Forest Recreation Demand Analysis
Simões, Paula; Barata, Eduardo; Cruz, Luis
2013-11-01
This research addresses the need to improve our knowledge on the demand for national forests for recreation and offers an in-depth data analysis supported by the complementary use of count data and ordered models. From a policy-making perspective, while count data models enable the estimation of monetary welfare measures, ordered models allow for the wider use of the database and provide a more flexible analysis of data. The main purpose of this article is to analyse the individual forest recreation demand and to derive a measure of its current use value. To allow a more complete analysis of the forest recreation demand structure the econometric approach supplements the use of count data models with ordered category models using data obtained by means of an on-site survey in the Bussaco National Forest (Portugal). Overall, both models reveal that travel cost and substitute prices are important explanatory variables, visits are a normal good and demographic variables seem to have no influence on demand. In particular, estimated price and income elasticities of demand are quite low. Accordingly, it is possible to argue that travel cost (price) in isolation may be expected to have a low impact on visitation levels.
John Carroll’s Views on Intelligence: Bi-Factor vs. Higher-Order Models
Directory of Open Access Journals (Sweden)
A. Alexander Beaujean
2015-10-01
Full Text Available The development of factor models is inextricably tied to the history of intelligence research. One of the most commonly-cited scholars in the field is John Carroll, whose three-stratum theory of cognitive ability has been one of the most influential models of cognitive ability in the past 20 years. Nonetheless, there is disagreement about how Carroll conceptualized the factors in his model. Some argue that his model is best represented through a higher-order model, while others argue that a bi-factor model is a better representation. Carroll was explicit about what he perceived the best way to represent his model, but his writings are not always easy to understand. In this article, I clarify his position by first describing the details and implications of bi-factor and higher-order models then show that Carroll’s published views are better represented by a bi-factor model.
Model order reduction and sensitivity analysis
Ilievski, Z.
2010-01-01
The electronics industry provides the core technology for numerous industrial innovations. Progress in the area of microelectronics is highlighted by several milestones in chip technology, for example microprocessors and memory chips. The ongoing increase in performance and memory density would not
Post processing of optically recognized text via second order hidden Markov model
Poudel, Srijana
In this thesis, we describe a postprocessing system on Optical Character Recognition(OCR) generated text. Second Order Hidden Markov Model (HMM) approach is used to detect and correct the OCR related errors. The reason for choosing the 2nd order HMM is to keep track of the bigrams so that the model can represent the system more accurately. Based on experiments with training data of 159,733 characters and testing of 5,688 characters, the model was able to correct 43.38 % of the errors with a precision of 75.34 %. However, the precision value indicates that the model introduced some new errors, decreasing the correction percentage to 26.4%.
Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters
Energy Technology Data Exchange (ETDEWEB)
Johnson, Brian B [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Purba, Victor [University of Minnesota; Jafarpour, Saber [University of California Santa-Barbara; Bullo, Francesco [University of California Santa-Barbara; Dhople, Sairaj V. [University of Minnesota
2017-08-21
Next-generation power networks will contain large numbers of grid-connected inverters satisfying a significant fraction of system load. Since each inverter model has a relatively large number of dynamic states, it is impractical to analyze complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model with lumped parameters for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. We show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as any individual inverter in the system. Numerical simulations validate the reduced-order model.
Identification of reduced-order model for an aeroelastic system from flutter test data
Directory of Open Access Journals (Sweden)
Wei Tang
2017-02-01
Full Text Available Recently, flutter active control using linear parameter varying (LPV framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroelastic models. Therefore, the reduced-order model is required by synthesis for avoidance of large computation cost and high-order controller. This paper proposes a new procedure for generation of accurate reduced-order linear time-invariant (LTI models by using system identification from flutter testing data. The proposed approach is in two steps. The well-known poly-reference least squares complex frequency (p-LSCF algorithm is firstly employed for modal parameter identification from frequency response measurement. After parameter identification, the dominant physical modes are determined by clear stabilization diagrams and clustering technique. In the second step, with prior knowledge of physical poles, the improved frequency-domain maximum likelihood (ML estimator is presented for building accurate reduced-order model. Before ML estimation, an improved subspace identification considering the poles constraint is also proposed for initializing the iterative procedure. Finally, the performance of the proposed procedure is validated by real flight flutter test data.
Manipulation and application of orbital ordering
International Nuclear Information System (INIS)
Sheng Zhigao; Sun Yuping
2014-01-01
Under certain conditions, the orbits of the outmost shell electrons in strong correlated materials can be localized in order, which gives birth to so-called orbital ordering. During the construction or destruction of the orbital ordering, strongly correlated materials show fruitful quantum critical phenomena with great potential for future applications. We first present the mechanism for the construction of orbital ordering. Then, some physical properties associated with orbits are discussed. Finally, we emphasize the key points and progress in the research of orbital ordering controlling. (authors)
BAYESIAN PARAMETER ESTIMATION IN A MIXED-ORDER MODEL OF BOD DECAY. (U915590)
We describe a generalized version of the BOD decay model in which the reaction is allowed to assume an order other than one. This is accomplished by making the exponent on BOD concentration a free parameter to be determined by the data. This "mixed-order" model may be ...
DEFF Research Database (Denmark)
Brodin, Nils Patrik; Vogelius, Ivan R.; Bjørk-Eriksson, Thomas
2013-01-01
As pediatric medulloblastoma (MB) is a relatively rare disease, it is important to extract the maximum information from trials and cohort studies. Here, a framework was developed for modeling tumor control with multiple modes of failure and time-to-progression for standard-risk MB, using published...
First Order Fire Effects Model: FOFEM 4.0, user's guide
Elizabeth D. Reinhardt; Robert E. Keane; James K. Brown
1997-01-01
A First Order Fire Effects Model (FOFEM) was developed to predict the direct consequences of prescribed fire and wildfire. FOFEM computes duff and woody fuel consumption, smoke production, and fire-caused tree mortality for most forest and rangeland types in the United States. The model is available as a computer program for PC or Data General computer.
Biomedical Progress Rates as New Parameters for Models of Economic Growth in Developed Countries
Directory of Open Access Journals (Sweden)
Alex Zhavoronkov
2013-11-01
Full Text Available While the doubling of life expectancy in developed countries during the 20th century can be attributed mostly to decreases in child mortality, the trillions of dollars spent on biomedical research by governments, foundations and corporations over the past sixty years are also yielding longevity dividends in both working and retired population. Biomedical progress will likely increase the healthy productive lifespan and the number of years of government support in the old age. In this paper we introduce several new parameters that can be applied to established models of economic growth: the biomedical progress rate, the rate of clinical adoption and the rate of change in retirement age. The biomedical progress rate is comprised of the rejuvenation rate (extending the productive lifespan and the non-rejuvenating rate (extending the lifespan beyond the age at which the net contribution to the economy becomes negative. While staying within the neoclassical economics framework and extending the overlapping generations (OLG growth model and assumptions from the life cycle theory of saving behavior, we provide an example of the relations between these new parameters in the context of demographics, labor, households and the firm.
Biomedical progress rates as new parameters for models of economic growth in developed countries.
Zhavoronkov, Alex; Litovchenko, Maria
2013-11-08
While the doubling of life expectancy in developed countries during the 20th century can be attributed mostly to decreases in child mortality, the trillions of dollars spent on biomedical research by governments, foundations and corporations over the past sixty years are also yielding longevity dividends in both working and retired population. Biomedical progress will likely increase the healthy productive lifespan and the number of years of government support in the old age. In this paper we introduce several new parameters that can be applied to established models of economic growth: the biomedical progress rate, the rate of clinical adoption and the rate of change in retirement age. The biomedical progress rate is comprised of the rejuvenation rate (extending the productive lifespan) and the non-rejuvenating rate (extending the lifespan beyond the age at which the net contribution to the economy becomes negative). While staying within the neoclassical economics framework and extending the overlapping generations (OLG) growth model and assumptions from the life cycle theory of saving behavior, we provide an example of the relations between these new parameters in the context of demographics, labor, households and the firm.
Directory of Open Access Journals (Sweden)
Edyta Mazurek
2014-06-01
Full Text Available Kakwani and Lambert state the three axioms, which should be respected by an equitable tax system. They also proposed a measurement system to evaluate the violations of the axioms. One of the axioms, axiom 2, formulates the progression principle in income tax systems. Vernizzi and Pellegrino improved the alternative index to evaluate violations concerning the progressive command in a tax system. The main aim of this paper is to compare the two indexes in order to evaluate violations of progressive principle in income tax systém using the real data. We also check how the progressivity of taxes and skewness of income distribution affect the measurement of the progressive principle violation.
On the Entropy Based Associative Memory Model with Higher-Order Correlations
Directory of Open Access Journals (Sweden)
Masahiro Nakagawa
2010-01-01
Full Text Available In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model so as to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned conventional dynamics as a special case ignoring the higher-order correlations. According to the introduction of the entropy functional, one may involve higer-order correlation effects between neurons in a self-contained manner without any heuristic coupling coefficients as in the conventional manner. In fact we shall show such higher order coupling tensors are to be uniquely determined in the framework of the entropy based approach. From numerical results, it will be found that the presently proposed novel approach realizes much larger memory capacity than that of the quadratic Lyapunov functional approach, e.g., associatron.
Dietary folate deficiency blocks prostate cancer progression in the TRAMP model.
Bistulfi, Gaia; Foster, Barbara A; Karasik, Ellen; Gillard, Bryan; Miecznikowski, Jeff; Dhiman, Vineet K; Smiraglia, Dominic J
2011-11-01
Dietary folate is essential in all tissues to maintain several metabolite pools and cellular proliferation. Prostate cells, due to specific metabolic characteristics, have increased folate demand to support proliferation and prevent genetic and epigenetic damage. Although several studies have found that dietary folate interventions can affect colon cancer biology in rodent models, its impact on prostate is unknown. The purpose of this study was to determine whether dietary folate manipulation, possibly being of primary importance for prostate epithelial cell metabolism, could significantly affect prostate cancer progression. Strikingly, mild dietary folate depletion arrested prostate cancer progression in 25 of 26 transgenic adenoma of the mouse prostate (TRAMP) mice, in which tumorigenesis is prostate-specific and characteristically aggressive. The significant effect on prostate cancer growth was characterized by size, grade, proliferation, and apoptosis analyses. Folate supplementation had a mild, nonsignificant, beneficial effect on grade. In addition, characterization of folate pools (correlated with serum), metabolite pools (polyamines and nucleotides), genetic and epigenetic damage, and expression of key biosynthetic enzymes in prostate tissue revealed interesting correlations with tumor progression. These findings indicate that prostate cancer is highly sensitive to folate manipulation and suggest that antifolates, paired with current therapeutic strategies, might significantly improve treatment of prostate cancer, the most commonly diagnosed cancer in American men.
Directory of Open Access Journals (Sweden)
Clara ePrats
2016-02-01
Full Text Available The evolution of a tuberculosis (TB infection towards active disease is driven by a combination of factors mostly related to the host response. The equilibrium between control of the bacillary load and the pathology generated is crucial as regards preventing the growth and proliferation of TB lesions. In addition, some experimental evidence suggests an important role of both local endogenous reinfection and the coalescence of neighboring lesions.Herein we propose a mathematical model that captures the essence of these factors by defining three hypotheses: (i lesions grow logistically due to the inflammatory reaction; (ii new lesions can appear as a result of extracellular bacilli or infected macrophages that escape from older lesions; and (iii lesions can merge when they are close enough. This model was implemented in Matlab to simulate the dynamics of several lesions in a 3D space. It was also fitted to available microscopy data from infected C3HeB/FeJ mice, an animal model of active TB that reacts against Mycobacterium tuberculosis with an exaggerated inflammatory response.The results of the simulations show the dynamics observed experimentally, namely an initial increase in the number of lesions followed by oscillations, and an exponential increase in the mean area of the lesions. In addition, further analysis of experimental and simulation results show a strong coincidence of the area distributions of lesions at day 21, thereby highlighting the consistency of the model. Three simulation series removing each one of the hypothesis corroborate their essential role in the dynamics observed.These results demonstrate that three local factors, namely an exaggerated inflammatory response, an endogenous reinfection and a coalescence of lesions, are needed in order to progress towards active TB. The failure of one of these factors stops induction of the disease. This mathematical model may be used as a basis for developing strategies to stop the
Prats, Clara; Vilaplana, Cristina; Valls, Joaquim; Marzo, Elena; Cardona, Pere-Joan; López, Daniel
2016-01-01
The evolution of a tuberculosis (TB) infection toward active disease is driven by a combination of factors mostly related to the host response. The equilibrium between control of the bacillary load and the pathology generated is crucial as regards preventing the growth and proliferation of TB lesions. In addition, some experimental evidence suggests an important role of both local endogenous reinfection and the coalescence of neighboring lesions. Herein we propose a mathematical model that captures the essence of these factors by defining three hypotheses: (i) lesions grow logistically due to the inflammatory reaction; (ii) new lesions can appear as a result of extracellular bacilli or infected macrophages that escape from older lesions; and (iii) lesions can merge when they are close enough. This model was implemented in Matlab to simulate the dynamics of several lesions in a 3D space. It was also fitted to available microscopy data from infected C3HeB/FeJ mice, an animal model of active TB that reacts against Mycobacterium tuberculosis with an exaggerated inflammatory response. The results of the simulations show the dynamics observed experimentally, namely an initial increase in the number of lesions followed by fluctuations, and an exponential increase in the mean area of the lesions. In addition, further analysis of experimental and simulation results show a strong coincidence of the area distributions of lesions at day 21, thereby highlighting the consistency of the model. Three simulation series removing each one of the hypothesis corroborate their essential role in the dynamics observed. These results demonstrate that three local factors, namely an exaggerated inflammatory response, an endogenous reinfection, and a coalescence of lesions, are needed in order to progress toward active TB. The failure of one of these factors stops induction of the disease. This mathematical model may be used as a basis for developing strategies to stop the progression of
Spin model for nontrivial types of magnetic order in inverse-perovskite antiferromagnets
Mochizuki, Masahito; Kobayashi, Masaya; Okabe, Reoya; Yamamoto, Daisuke
2018-02-01
Nontrivial magnetic orders in the inverse-perovskite manganese nitrides are theoretically studied by constructing a classical spin model describing the magnetic anisotropy and frustrated exchange interactions inherent in specific crystal and electronic structures of these materials. With a replica-exchange Monte Carlo technique, a theoretical analysis of this model reproduces the experimentally observed triangular Γ5 g and Γ4 g spin-ordered patterns and the systematic evolution of magnetic orders. Our Rapid Communication solves a 40-year-old problem of nontrivial magnetism for the inverse-perovskite manganese nitrides and provides a firm basis for clarifying the magnetism-driven negative thermal expansion phenomenon discovered in this class of materials.
An Ordered Regression Model to Predict Transit Passengers’ Behavioural Intentions
Energy Technology Data Exchange (ETDEWEB)
Oña, J. de; Oña, R. de; Eboli, L.; Forciniti, C.; Mazzulla, G.
2016-07-01
Passengers’ behavioural intentions after experiencing transit services can be viewed as signals that show if a customer continues to utilise a company’s service. Users’ behavioural intentions can depend on a series of aspects that are difficult to measure directly. More recently, transit passengers’ behavioural intentions have been just considered together with the concepts of service quality and customer satisfaction. Due to the characteristics of the ways for evaluating passengers’ behavioural intentions, service quality and customer satisfaction, we retain that this kind of issue could be analysed also by applying ordered regression models. This work aims to propose just an ordered probit model for analysing service quality factors that can influence passengers’ behavioural intentions towards the use of transit services. The case study is the LRT of Seville (Spain), where a survey was conducted in order to collect the opinions of the passengers about the existing transit service, and to have a measure of the aspects that can influence the intentions of the users to continue using the transit service in the future. (Author)
Magnetic order and Kondo effect in the Anderson-lattice model
International Nuclear Information System (INIS)
Bernhard, B.H.; Aguiar, C.; Kogoutiouk, I.; Coqblin, B.
2007-01-01
The Anderson-lattice model has been extensively developed to account for the properties of many anomalous rare-earth compounds and in particular for the competition between the Kondo effect and an antiferromagnetic (AF) phase in a cubic lattice. Here we apply the higher-order decoupling of the equations of motion for the Green Functions (GF) introduced in [H.G. Luo, S.J. Wang, Phys. Rev. B 62 (2000) 1485]. We obtain an improved description of the phase diagram, where the AF phase subsists in a smaller range of the model parameters. As higher-order GF are included in the chain of equations, we are able to calculate directly the local spin-flip correlation function † ↓ d † ↑ f ↑ d ↓ >. As a further improvement to the previous approximation of [B.H. Bernhard, C. Aguiar, B. Coqblin, Physica B 378-380 (2006) 712], we obtain a reduced range of existence for the AF phase for the symmetric half-filled case and then we discuss the competition between the AF order and the Kondo effect as a function of the band filling
Time-Frequency Analysis Using Warped-Based High-Order Phase Modeling
Directory of Open Access Journals (Sweden)
Ioana Cornel
2005-01-01
Full Text Available The high-order ambiguity function (HAF was introduced for the estimation of polynomial-phase signals (PPS embedded in noise. Since the HAF is a nonlinear operator, it suffers from noise-masking effects and from the appearance of undesired cross-terms when multicomponents PPS are analyzed. In order to improve the performances of the HAF, the multi-lag HAF concept was proposed. Based on this approach, several advanced methods (e.g., product high-order ambiguity function (PHAF have been recently proposed. Nevertheless, performances of these new methods are affected by the error propagation effect which drastically limits the order of the polynomial approximation. This phenomenon acts especially when a high-order polynomial modeling is needed: representation of the digital modulation signals or the acoustic transient signals. This effect is caused by the technique used for polynomial order reduction, common for existing approaches: signal multiplication with the complex conjugated exponentials formed with the estimated coefficients. In this paper, we introduce an alternative method to reduce the polynomial order, based on the successive unitary signal transformation, according to each polynomial order. We will prove that this method reduces considerably the effect of error propagation. Namely, with this order reduction method, the estimation error at a given order will depend only on the performances of the estimation method.
International Nuclear Information System (INIS)
Kolb, E.W.
1991-01-01
In the original proposal, inflation occurred in the process of a strongly first-order phase transition. This model was soon demonstrated to be fatally flawed. Subsequent models for inflation involved phase transitions that were second-order, or perhaps weakly first-order; some even involved no phase transition at all. Recently the possibility of inflation during a strongly first-order phase transition has been reviewed. In this talk I will discuss some models for first-order inflation, and emphasize unique signatures that result if inflation is realized in a first-order transition. Before discussing first-order inflation, I will briefly review some of the history of inflation to demonstrate how first-order inflation differs from other models. (orig.)
Next-to-leading order corrections to the valon model
Indian Academy of Sciences (India)
Next-to-leading order corrections to the valon model. G R BOROUN. ∗ and E ESFANDYARI. Physics Department, Razi University, Kermanshah 67149, Iran. ∗. Corresponding author. E-mail: grboroun@gmail.com; boroun@razi.ac.ir. MS received 17 January 2014; revised 31 October 2014; accepted 21 November 2014.
Progression of renal cell carcinoma is inhibited by genistein and radiation in an orthotopic model
International Nuclear Information System (INIS)
Hillman, Gilda G; Wang, Yu; Che, Mingxin; Raffoul, Julian J; Yudelev, Mark; Kucuk, Omer; Sarkar, Fazlul H
2007-01-01
We have previously reported the potentiation of radiotherapy by the soy isoflavone genistein for prostate cancer using prostate tumor cells in vitro and orthotopic prostate tumor models in vivo. However, when genistein was used as single therapy in animal models, it promoted metastasis to regional para-aortic lymph nodes. To clarify whether these intriguing adverse effects of genistein are intrinsic to the orthotopic prostate tumor model, or these results could also be recapitulated in another model, we used the orthotopic metastatic KCI-18 renal cell carcinoma (RCC) model established in our laboratory. The KCI-18 RCC cell line was generated from a patient with papillary renal cell carcinoma. Following orthotopic renal implantation of KCI-18 RCC cells and serial in vivo kidney passages in nude mice, we have established a reliable and predictable metastatic RCC tumor model. Mice bearing established kidney tumors were treated with genistein combined with kidney tumor irradiation. The effect of the therapy was assessed on the primary tumor and metastases to various organs. In this experimental model, the karyotype and histological characteristics of the human primary tumor are preserved. Tumor cells metastasize from the primary renal tumor to the lungs, liver and mesentery mimicking the progression of RCC in humans. Treatment of established kidney tumors with genistein demonstrated a tendency to stimulate the growth of the primary kidney tumor and increase the incidence of metastasis to the mesentery lining the bowel. In contrast, when given in conjunction with kidney tumor irradiation, genistein significantly inhibited the growth and progression of established kidney tumors. These findings confirm the potentiation of radiotherapy by genistein in the orthotopic RCC model as previously shown in orthotopic models of prostate cancer. Our studies in both RCC and prostate tumor models demonstrate that the combination of genistein with primary tumor irradiation is a more
[RESEARCH PROGRESS OF EXPERIMENTAL ANIMAL MODELS OF AVASCULAR NECROSIS OF FEMORAL HEAD].
Yu, Kaifu; Tan, Hongbo; Xu, Yongqing
2015-12-01
To summarize the current researches and progress on experimental animal models of avascular necrosis of the femoral head. Domestic and internation literature concerning experimental animal models of avascular necrosis of the femoral head was reviewed and analyzed. The methods to prepare the experimental animal models of avascular necrosis of the femoral head can be mainly concluded as traumatic methods (including surgical, physical, and chemical insult), and non-traumatic methods (including steroid, lipopolysaccharide, steroid combined with lipopolysaccharide, steroid combined with horse serum, etc). Each method has both merits and demerits, yet no ideal methods have been developed. There are many methods to prepare the experimental animal models of avascular necrosis of the femoral head, but proper model should be selected based on the aim of research. The establishment of ideal experimental animal models needs further research in future.
Simulation of local instabilities with the use of reduced order models
International Nuclear Information System (INIS)
Dykin, V.; Demaziere, C.; Lange, C.; Hennig, D.
2011-01-01
The development of an advanced reduced order model (ROM) with four heated channels, taking into account local, regional and core-wide oscillations, is described. The ROM contains three sub-models: a neutron-kinetic model (describing neutron transport), a thermal- hydraulic model (describing the coolant flow) and a heat transfer model (describing heat transfer between the fuel and the coolant). All these three models are coupled to each other, using two feedback mechanisms: void feedback and doppler feedback. Each of the sub-models is described by a set of reduced ordinary differential equations, derived from the corresponding time space-dependent partial differential equations by using different types of approximations and mathematical techniques. All three models were developed from past ROMs and, subsequently, were modified in order to fit the purpose of our investigations. One of the novelties of the present ROM is that it takes into account the effect of the first three neutronic modes, namely the fundamental, the first and the second azimuthal modes, as well as the effect of local oscillations on these modes. In order to have a proper representation of both azimuthal modes, a four heated channel ROM was developed. Another modification, compared to earlier work, is the determination of the coupling reactivity coefficients for both void fraction and fuel temperature, which were calculated explicitly by evaluating cross-section perturbations with the help of the SIMULATE-3 and the CORESIM codes. The ROM was thereafter applied to a channel instability event that occurred at the Swedish Forsmark-1 BWR in 1996/1997. The time signals for each of the modes were generated from the ROM and compared with the measurements, performed at the plant. Some qualitative comparison between the ROM and the measurements was made. The results could bear some significance in understanding the instability event and its coupling mechanism to core-wide oscillations. (author)
Reduced order methods for modeling and computational reduction
Rozza, Gianluigi
2014-01-01
This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics. Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This...
A mathematical model for order splitting in a multiple supplier single-item inventory system
DEFF Research Database (Denmark)
Abginehchi, Soheil; Farahani, Reza Zanjirani; Rezapour, Shabnam
2013-01-01
systems. The item acquisition lead times of suppliers are random variables. Backorder is allowed and shortage cost is charged based on not only per unit in shortage but also per time unit. Continuous review (s,Q) policy has been assumed. When the inventory level depletes to a reorder level, the total...... order is split among n suppliers. Since the suppliers have different characteristics, the quantity ordered to different suppliers may be different. The problem is to determine the reorder level and quantity ordered to each supplier so that the expected total cost per time unit, including ordering cost......, procurement cost, inventory holding cost, and shortage cost, is minimized. We also conduct extensive numerical experiments to show the advantages of our model compared with the models in the literature. According to our extensive experiments, the model developed in this paper is the best model...
Higher-order ice-sheet modelling accelerated by multigrid on graphics cards
Brædstrup, Christian; Egholm, David
2013-04-01
Higher-order ice flow modelling is a very computer intensive process owing primarily to the nonlinear influence of the horizontal stress coupling. When applied for simulating long-term glacial landscape evolution, the ice-sheet models must consider very long time series, while both high temporal and spatial resolution is needed to resolve small effects. The use of higher-order and full stokes models have therefore seen very limited usage in this field. However, recent advances in graphics card (GPU) technology for high performance computing have proven extremely efficient in accelerating many large-scale scientific computations. The general purpose GPU (GPGPU) technology is cheap, has a low power consumption and fits into a normal desktop computer. It could therefore provide a powerful tool for many glaciologists working on ice flow models. Our current research focuses on utilising the GPU as a tool in ice-sheet and glacier modelling. To this extent we have implemented the Integrated Second-Order Shallow Ice Approximation (iSOSIA) equations on the device using the finite difference method. To accelerate the computations, the GPU solver uses a non-linear Red-Black Gauss-Seidel iterator coupled with a Full Approximation Scheme (FAS) multigrid setup to further aid convergence. The GPU finite difference implementation provides the inherent parallelization that scales from hundreds to several thousands of cores on newer cards. We demonstrate the efficiency of the GPU multigrid solver using benchmark experiments.
Extreme learning machine for reduced order modeling of turbulent geophysical flows
San, Omer; Maulik, Romit
2018-04-01
We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.
Geometrical aspects of operator ordering terms in gauge invariant quantum models
International Nuclear Information System (INIS)
Houston, P.J.
1990-01-01
Finite-dimensional quantum models with both boson and fermion degrees of freedom, and which have a gauge invariance, are studied here as simple versions of gauge invariant quantum field theories. The configuration space of these finite-dimensional models has the structure of a principal fibre bundle and has defined on it a metric which is invariant under the action of the bundle or gauge group. When the gauge-dependent degrees of freedom are removed, thereby defining the quantum models on the base of the principal fibre bundle, extra operator ordering terms arise. By making use of dimensional reduction methods in removing the gauge dependence, expressions are obtained here for the operator ordering terms which show clearly their dependence on the geometry of the principal fibre bundle structure. (author)
International Nuclear Information System (INIS)
Kolb, E.W.; Chicago Univ., IL
1990-09-01
In the original proposal, inflation occurred in the process of a strongly first-order phase transition. This model was soon demonstrated to be fatally flawed. Subsequent models for inflation involved phase transitions that were second-order, or perhaps weakly first-order; some even involved no phase transition at all. Recently the possibility of inflation during a strongly first-order phase transition has been revived. In this talk I will discuss some models for first-order inflation, and emphasize unique signatures that result in inflation is realized in a first-order transition. Before discussing first-order inflation, I will briefly review some of the history of inflation to demonstrate how first-order inflation differs from other models. 58 refs., 3 figs
Ang, Daniel; Demille, David; Doyle, John; Gabrielse, Gerald; Haefner, Jonathan; Lasner, Zack; Meisenhelder, Cole; Panda, Cristian; West, Adam; West, Elizabeth
2017-04-01
The search for the electron electric dipole moment (eEDM) is a powerful probe of fundamental physics beyond the Standard Model. In 2014, the first generation of the ACME experiment set the most stringent upper limit on the eEDM of |de | < 1 ×10-28 e . cm by means of measuring spin precession in a beam of thorium monoxide. Since then, we have implemented various improvements, such as STIRAP preparation of the experimental H state, rotational cooling, optimized apparatus geometry, and enhanced detection efficency, boosting our signal by a factor of about 400. We have also devised means to reduce the leading systematics we found in the Generation I experiment. We describe the recent progress in taking data using our Generation II apparatus and our ongoing efforts to investigate various systematics. NSF Grant 1404146.
Directory of Open Access Journals (Sweden)
Patrick Aldrin-Kirk
Full Text Available Synucleinopathies, characterized by intracellular aggregation of α-synuclein protein, share a number of features in pathology and disease progression. However, the vulnerable cell population differs significantly between the disorders, despite being caused by the same protein. While the vulnerability of dopamine cells in the substantia nigra to α-synuclein over-expression, and its link to Parkinson's disease, is well studied, animal models recapitulating the cortical degeneration in dementia with Lewy-bodies (DLB are much less mature. The aim of this study was to develop a first rat model of widespread progressive synucleinopathy throughout the forebrain using adeno-associated viral (AAV vector mediated gene delivery. Through bilateral injection of an AAV6 vector expressing human wild-type α-synuclein into the forebrain of neonatal rats, we were able to achieve widespread, robust α-synuclein expression with preferential expression in the frontal cortex. These animals displayed a progressive emergence of hyper-locomotion and dysregulated response to the dopaminergic agonist apomorphine. The animals receiving the α-synuclein vector displayed significant α-synuclein pathology including intra-cellular inclusion bodies, axonal pathology and elevated levels of phosphorylated α-synuclein, accompanied by significant loss of cortical neurons and a progressive reduction in both cortical and striatal ChAT positive interneurons. Furthermore, we found evidence of α-synuclein sequestered by IBA-1 positive microglia, which was coupled with a distinct change in morphology. In areas of most prominent pathology, the total α-synuclein levels were increased to, on average, two-fold, which is similar to the levels observed in patients with SNCA gene triplication, associated with cortical Lewy body pathology. This study provides a novel rat model of progressive cortical synucleinopathy, showing for the first time that cholinergic interneurons are vulnerable
Pairing of parafermions of order 2: seniority model
International Nuclear Information System (INIS)
Nelson, Charles A
2004-01-01
As generalizations of the fermion seniority model, four multi-mode Hamiltonians are considered to investigate some of the consequences of the pairing of parafermions of order 2. Two- and four-particle states are explicitly constructed for H A ≡ -GA†A with A† ≡ 1/2 Σ m>0 c† m c† -m and the distinct H C ≡ -GC†C with C† ≡ 1/2 Σ m>0 c† -m c† m , and for the time-reversal invariant H (-) ≡ -G(A† - C†)(A - C) and H (+) ≡ -G(A† + C†)(A + C), which has no analogue in the fermion case. The spectra and degeneracies are compared with those of the usual fermion seniority model
Ishibashi, Hidetoshi; Minakawa, Eiko N.; Motohashi, Hideyuki H.; Takayama, Osamu; Popiel, H. Akiko; Puentes, Sandra; Owari, Kensuke; Nakatani, Terumi; Nogami, Naotake; Yamamoto, Kazuhiro; Yonekawa, Takahiro; Tanaka, Yoko; Fujita, Naoko; Suzuki, Hikaru; Aizawa, Shu; Nagano, Seiichi; Yamada, Daisuke; Wada, Keiji; Kohsaka, Shinichi
2017-01-01
Abstract Age-associated neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, and the polyglutamine (polyQ) diseases, are becoming prevalent as a consequence of elongation of the human lifespan. Although various rodent models have been developed to study and overcome these diseases, they have limitations in their translational research utility owing to differences from humans in brain structure and function and in drug metabolism. Here, we generated a transgenic marmoset model of the polyQ diseases, showing progressive neurological symptoms including motor impairment. Seven transgenic marmosets were produced by lentiviral introduction of the human ataxin 3 gene with 120 CAG repeats encoding an expanded polyQ stretch. Although all offspring showed no neurological symptoms at birth, three marmosets with higher transgene expression developed neurological symptoms of varying degrees at 3–4 months after birth, followed by gradual decreases in body weight gain, spontaneous activity, and grip strength, indicating time-dependent disease progression. Pathological examinations revealed neurodegeneration and intranuclear polyQ protein inclusions accompanied by gliosis, which recapitulate the neuropathological features of polyQ disease patients. Consistent with neuronal loss in the cerebellum, brain MRI analyses in one living symptomatic marmoset detected enlargement of the fourth ventricle, which suggests cerebellar atrophy. Notably, successful germline transgene transmission was confirmed in the second-generation offspring derived from the symptomatic transgenic marmoset gamete. Because the accumulation of abnormal proteins is a shared pathomechanism among various neurodegenerative diseases, we suggest that this new marmoset model will contribute toward elucidating the pathomechanisms of and developing clinically applicable therapies for neurodegenerative diseases. PMID:28374014
Model for the orientational ordering of the plant microtubule cortical array
Hawkins, Rhoda J.; Tindemans, Simon H.; Mulder, Bela M.
2010-07-01
The plant microtubule cortical array is a striking feature of all growing plant cells. It consists of a more or less homogeneously distributed array of highly aligned microtubules connected to the inner side of the plasma membrane and oriented transversely to the cell growth axis. Here, we formulate a continuum model to describe the origin of orientational order in such confined arrays of dynamical microtubules. The model is based on recent experimental observations that show that a growing cortical microtubule can interact through angle dependent collisions with pre-existing microtubules that can lead either to co-alignment of the growth, retraction through catastrophe induction or crossing over the encountered microtubule. We identify a single control parameter, which is fully determined by the nucleation rate and intrinsic dynamics of individual microtubules. We solve the model analytically in the stationary isotropic phase, discuss the limits of stability of this isotropic phase, and explicitly solve for the ordered stationary states in a simplified version of the model.
McSwiggen, P.L.
1993-01-01
Earlier attempts at solution models for the ternary carbonate system have been unable to adequately accommodate the cation ordering which occurs in some of the carbonate phases. The carbonate solution model of this study combines a Margules type of interaction model with a Bragg-Williams type of ordering model. The ordering model determines the equilibrium state of order for a crystal, from which the cation distribution within the lattice can be obtained. The interaction model addresses the effect that mixing different cation species within a given cation layer has on the total free energy of the system. An ordering model was derived, based on the Bragg-Williams approach; it is applicable to ternary systems involving three cations substituting on two sites, and contains three ordering energy parameters (WCaMg, WCaFe, and WCaMgFe). The solution model of this study involves six Margules-type interaction parameters (W12, W21, W13, W31, W23, and W32). Values for the two sets of energy parameters were calculated from experimental data and from compositional relationships in natural assemblages. ?? 1993 Springer-Verlag.
Utility of low-order linear nuclear-power-plant models in plant diagnostics and control
International Nuclear Information System (INIS)
Tylee, J.L.
1981-01-01
A low-order, linear model of a pressurized water reactor (PWR) plant is described and evaluated. The model consists of 23 linear, first-order difference equations and simulates all subsystems of both the primary and secondary sides of the plant. Comparisons between the calculated model response and available test data show the model to be an adequate representation of the actual plant dynamics. Suggested use for the model in an on-line digital plant diagnostics and control system are presented
Recent progress and modern challenges in applied mathematics, modeling and computational science
Makarov, Roman; Belair, Jacques
2017-01-01
This volume is an excellent resource for professionals in various areas of applications of mathematics, modeling, and computational science. It focuses on recent progress and modern challenges in these areas. The volume provides a balance between fundamental theoretical and applied developments, emphasizing the interdisciplinary nature of modern trends and detailing state-of-the-art achievements in Applied Mathematics, Modeling, and Computational Science. The chapters have been authored by international experts in their respective fields, making this book ideal for researchers in academia, practitioners, and graduate students. It can also serve as a reference in the diverse selected areas of applied mathematics, modelling, and computational sciences, and is ideal for interdisciplinary collaborations.
Sapsis, Themistoklis P; Majda, Andrew J
2013-08-20
A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.
Short-Term Memory for Serial Order: A Recurrent Neural Network Model
Botvinick, Matthew M.; Plaut, David C.
2006-01-01
Despite a century of research, the mechanisms underlying short-term or working memory for serial order remain uncertain. Recent theoretical models have converged on a particular account, based on transient associations between independent item and context representations. In the present article, the authors present an alternative model, according…
Are Quantum Models for Order Effects Quantum?
Moreira, Catarina; Wichert, Andreas
2017-12-01
The application of principles of Quantum Mechanics in areas outside of physics has been getting increasing attention in the scientific community in an emergent disciplined called Quantum Cognition. These principles have been applied to explain paradoxical situations that cannot be easily explained through classical theory. In quantum probability, events are characterised by a superposition state, which is represented by a state vector in a N-dimensional vector space. The probability of an event is given by the squared magnitude of the projection of this superposition state into the desired subspace. This geometric approach is very useful to explain paradoxical findings that involve order effects, but do we really need quantum principles for models that only involve projections? This work has two main goals. First, it is still not clear in the literature if a quantum projection model has any advantage towards a classical projection. We compared both models and concluded that the Quantum Projection model achieves the same results as its classical counterpart, because the quantum interference effects play no role in the computation of the probabilities. Second, it intends to propose an alternative relativistic interpretation for rotation parameters that are involved in both classical and quantum models. In the end, instead of interpreting these parameters as a similarity measure between questions, we propose that they emerge due to the lack of knowledge concerned with a personal basis state and also due to uncertainties towards the state of world and towards the context of the questions.
Recent progress of an integrated implosion code and modeling of element physics
International Nuclear Information System (INIS)
Nagatomo, H.; Takabe, H.; Mima, K.; Ohnishi, N.; Sunahara, A.; Takeda, T.; Nishihara, K.; Nishiguchu, A.; Sawada, K.
2001-01-01
Physics of the inertial fusion is based on a variety of elements such as compressible hydrodynamics, radiation transport, non-ideal equation of state, non-LTE atomic process, and relativistic laser plasma interaction. In addition, implosion process is not in stationary state and fluid dynamics, energy transport and instabilities should be solved simultaneously. In order to study such complex physics, an integrated implosion code including all physics important in the implosion process should be developed. The details of physics elements should be studied and the resultant numerical modeling should be installed in the integrated code so that the implosion can be simulated with available computer within realistic CPU time. Therefore, this task can be basically separated into two parts. One is to integrate all physics elements into a code, which is strongly related to the development of hydrodynamic equation solver. We have developed 2-D integrated implosion code which solves mass, momentum, electron energy, ion energy, equation of states, laser ray-trace, laser absorption radiation, surface tracing and so on. The reasonable results in simulating Rayleigh-Taylor instability and cylindrical implosion are obtained using this code. The other is code development on each element physics and verification of these codes. We had progress in developing a nonlocal electron transport code and 2 and 3 dimension radiation hydrodynamic code. (author)
Integrated model for pricing, delivery time setting, and scheduling in make-to-order environments
Garmdare, Hamid Sattari; Lotfi, M. M.; Honarvar, Mahboobeh
2018-03-01
Usually, in make-to-order environments which work only in response to the customer's orders, manufacturers for maximizing the profits should offer the best price and delivery time for an order considering the existing capacity and the customer's sensitivity to both the factors. In this paper, an integrated approach for pricing, delivery time setting and scheduling of new arrival orders are proposed based on the existing capacity and accepted orders in system. In the problem, the acquired market demands dependent on the price and delivery time of both the manufacturer and its competitors. A mixed-integer non-linear programming model is presented for the problem. After converting to a pure non-linear model, it is validated through a case study. The efficiency of proposed model is confirmed by comparing it to both the literature and the current practice. Finally, sensitivity analysis for the key parameters is carried out.
Modal-based reduced-order model of BWR out-of phase instabilities
International Nuclear Information System (INIS)
Turso, J.A.; Edwards, R.M.; March-Leuba, J.
1995-01-01
For the past 40 yr, reduced-order modeling of boiling water reactor (BWR) dynamic behavior has been accomplished by several researchers. These models have been primarily concerned with providing insight into the so-called corewide neutron flux oscillation, where the power at each radial location in the core oscillates in unison. This is generally considered to be an illustration of the fundamental neutronic mode excited by the core thermal hydraulics. The time dependence of the fundamental mode is typically described by the point-kinetics equations, with one or more delayed-neutron groups. Thermal-hydraulic excitation of the first azimuthal harmonic mode, the so-called out-of-phase (OOP) instability, has been observed in operating BWRs. The temporal behavior of a low-order model of this phenomenon can be characterized using the modal point-kinetics formulation developed in this paper
HIGHLY-ACCURATE MODEL ORDER REDUCTION TECHNIQUE ON A DISCRETE DOMAIN
Directory of Open Access Journals (Sweden)
L. D. Ribeiro
2015-09-01
Full Text Available AbstractIn this work, we present a highly-accurate technique of model order reduction applied to staged processes. The proposed method reduces the dimension of the original system based on null values of moment-weighted sums of heat and mass balance residuals on real stages. To compute these sums of weighted residuals, a discrete form of Gauss-Lobatto quadrature was developed, allowing a high degree of accuracy in these calculations. The locations where the residuals are cancelled vary with time and operating conditions, characterizing a desirable adaptive nature of this technique. Balances related to upstream and downstream devices (such as condenser, reboiler, and feed tray of a distillation column are considered as boundary conditions of the corresponding difference-differential equations system. The chosen number of moments is the dimension of the reduced model being much lower than the dimension of the complete model and does not depend on the size of the original model. Scaling of the discrete independent variable related with the stages was crucial for the computational implementation of the proposed method, avoiding accumulation of round-off errors present even in low-degree polynomial approximations in the original discrete variable. Dynamical simulations of distillation columns were carried out to check the performance of the proposed model order reduction technique. The obtained results show the superiority of the proposed procedure in comparison with the orthogonal collocation method.
The Process-Oriented Simulation (POS) model for common cause failures: recent progress
International Nuclear Information System (INIS)
Berg, H.P.; Goertz, R.; Schimetschka, E.; Kesten, J.
2006-01-01
A common-cause failure (CCF) model based on stochastic simulation has been developed to complement the established approaches and to overcome some of their shortcomings. Reflecting the models proximity to the CCF process it was called Process Oriented Simulation (POS) Model. In recent years, some progress has been made to render the POS model fit for practical applications comprising the development of parameter estimates and a number of test applications in areas where results were already available - especially from CCF benchmarks - and comparison can provide insights in strong and weak points of the different approaches. In this paper, a detailed description of the POS model is provided together with the approach to parameter estimation and representative test applications. It is concluded, that the POS model has a number of strengths - especially the feature to provide reasonable extrapolation to CCF groups with high degrees of redundancy - and thus a considerable potential to complement the insights obtained from existing modeling. (orig.)
Bogosian, Angeliki; Morgan, Myfanwy; Bishop, Felicity L; Day, Fern; Moss-Morris, Rona
2017-03-01
We examined cognitive and behavioural challenges and adaptations for people with progressive multiple sclerosis (MS) and developed a preliminary conceptual model of changes in adjustment over time. Using theoretical sampling, 34 semi-structured interviews were conducted with people with MS. Participants were between 41 and 77 years of age. Thirteen were diagnosed with primary progressive MS and 21 with secondary progressive MS. Data were analysed using a grounded theory approach. Participants described initially bracketing the illness off and carrying on their usual activities but this became problematic as the condition progressed and they employed different adjustment modes to cope with increased disabilities. Some scaled back their activities to live a more comfortable life, others identified new activities or adapted old ones, whereas at times, people disengaged from the adjustment process altogether and resigned to their condition. Relationships with partners, emotional reactions, environment and perception of the environment influenced adjustment, while people were often flexible and shifted among modes. Adjusting to a progressive condition is a fluid process. Future interventions can be tailored to address modifiable factors at different stages of the condition and may involve addressing emotional reactions concealing/revealing the condition and perceptions of the environment.
Probabilistic error bounds for reduced order modeling
Energy Technology Data Exchange (ETDEWEB)
Abdo, M.G.; Wang, C.; Abdel-Khalik, H.S., E-mail: abdo@purdue.edu, E-mail: wang1730@purdue.edu, E-mail: abdelkhalik@purdue.edu [Purdue Univ., School of Nuclear Engineering, West Lafayette, IN (United States)
2015-07-01
Reduced order modeling has proven to be an effective tool when repeated execution of reactor analysis codes is required. ROM operates on the assumption that the intrinsic dimensionality of the associated reactor physics models is sufficiently small when compared to the nominal dimensionality of the input and output data streams. By employing a truncation technique with roots in linear algebra matrix decomposition theory, ROM effectively discards all components of the input and output data that have negligible impact on reactor attributes of interest. This manuscript introduces a mathematical approach to quantify the errors resulting from the discarded ROM components. As supported by numerical experiments, the introduced analysis proves that the contribution of the discarded components could be upper-bounded with an overwhelmingly high probability. The reverse of this statement implies that the ROM algorithm can self-adapt to determine the level of the reduction needed such that the maximum resulting reduction error is below a given tolerance limit that is set by the user. (author)
Multivariable robust adaptive controller using reduced-order model
Directory of Open Access Journals (Sweden)
Wei Wang
1990-04-01
Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.
REDUCED ISOTROPIC CRYSTAL MODEL WITH RESPECT TO THE FOURTH-ORDER ELASTIC MODULI
Directory of Open Access Journals (Sweden)
O. Burlayenko
2018-04-01
Full Text Available Using a reduced isotropic crystal model the relationship between the fourth-order elastic moduli of an isotropic medium and the independent components of the fourth-order elastic moduli tensor of real crystals of various crystal systems is found. To calculate the coefficients of these relations, computer algebra systems Redberry and Mathematica for working with high order tensors in the symbolic and explicit form were used, in light of the overly complex computation. In an isotropic medium, there are four independent fourth order elastic moduli. This is due to the presence of four invariants for an eighth-rank tensor in the three-dimensional space, that has symmetries over the pairs of indices. As an example, the moduli of elasticity of an isotropic medium corresponding to certain crystals of cubic system are given (LiF, NaCl, MgO, CaF2. From the obtained results it can be seen that the reduced isotropic crystal model can be most effectively applied to high-symmetry crystal systems.
An Online Method for Interpolating Linear Parametric Reduced-Order Models
Amsallem, David; Farhat, Charbel
2011-01-01
A two-step online method is proposed for interpolating projection-based linear parametric reduced-order models (ROMs) in order to construct a new ROM for a new set of parameter values. The first step of this method transforms each precomputed ROM into a consistent set of generalized coordinates. The second step interpolates the associated linear operators on their appropriate matrix manifold. Real-time performance is achieved by precomputing inner products between the reduced-order bases underlying the precomputed ROMs. The proposed method is illustrated by applications in mechanical and aeronautical engineering. In particular, its robustness is demonstrated by its ability to handle the case where the sampled parameter set values exhibit a mode veering phenomenon. © 2011 Society for Industrial and Applied Mathematics.
Malekian, Negin; Habibi, Jafar; Zangooei, Mohammad Hossein; Aghakhani, Hojjat
2016-11-01
There are many cells with various phenotypic behaviors in cancer interacting with each other. For example, an apoptotic cell may induce apoptosis in adjacent cells. A living cell can also protect cells from undergoing apoptosis and necrosis. These survival and death signals are propagated through interaction pathways between adjacent cells called gap junctions. The function of these signals depends on the cellular context of the cell receiving them. For instance, a receiver cell experiencing a low level of oxygen may interpret a received survival signal as an apoptosis signal. In this study, we examine the effect of these signals on tumor growth. We make an evolutionary game theory component in order to model the signal propagation through gap junctions. The game payoffs are defined as a function of cellular context. Then, the game theory component is integrated into an agent-based model of tumor growth. After that, the integrated model is applied to ductal carcinoma in situ, a type of early stage breast cancer. Different scenarios are explored to observe the impact of the gap junction communication and parameters of the game theory component on cancer progression. We compare these scenarios by using the Wilcoxon signed-rank test. The Wilcoxon signed-rank test succeeds in proving a significant difference between the tumor growth of the model before and after considering the gap junction communication. The Wilcoxon signed-rank test also proves that the tumor growth significantly depends on the oxygen threshold of turning survival signals into apoptosis. In this study, the gap junction communication is modeled by using evolutionary game theory to illustrate its role at early stage cancers such as ductal carcinoma in situ. This work indicates that the gap junction communication and the oxygen threshold of turning survival signals into apoptosis can notably affect cancer progression. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
New second order Mumford-Shah model based on Γ-convergence approximation for image processing
Duan, Jinming; Lu, Wenqi; Pan, Zhenkuan; Bai, Li
2016-05-01
In this paper, a second order variational model named the Mumford-Shah total generalized variation (MSTGV) is proposed for simultaneously image denoising and segmentation, which combines the original Γ-convergence approximated Mumford-Shah model with the second order total generalized variation (TGV). For image denoising, the proposed MSTGV can eliminate both the staircase artefact associated with the first order total variation and the edge blurring effect associated with the quadratic H1 regularization or the second order bounded Hessian regularization. For image segmentation, the MSTGV can obtain clear and continuous boundaries of objects in the image. To improve computational efficiency, the implementation of the MSTGV does not directly solve its high order nonlinear partial differential equations and instead exploits the efficient split Bregman algorithm. The algorithm benefits from the fast Fourier transform, analytical generalized soft thresholding equation, and Gauss-Seidel iteration. Extensive experiments are conducted to demonstrate the effectiveness and efficiency of the proposed model.
Tracking the Progress of English Language Learners
Murphy, Audrey F.
2009-01-01
Educators need to document progress for English language learners, and the best structures to put into place in order to record their growth. Beginning with the stages of language proficiency, student progress can be tracked through the use of a baseline in all four language strands and the creation of rubrics to monitor performance. Language…
Analysis of credit linked demand in an inventory model with varying ordering cost.
Banu, Ateka; Mondal, Shyamal Kumar
2016-01-01
In this paper, we have considered an economic order quantity model for deteriorating items with two-level trade credit policy in which a delay in payment is offered by a supplier to a retailer and also an another delay in payment is offered by the retailer to his/her all customers. Here, it is proposed that the demand function is dependent on the length of the customer's credit period and also the duration of offering the credit period. In this article, it is considered that the retailer's ordering cost per order depends on the number of replenishment cycles. The objective of this model is to establish a deterministic EOQ model of deteriorating items for the retailer to decide the position of customers credit period and the number of replenishment cycles in finite time horizon such that the retailer gets the maximum profit. Also, the model is explained with the help of some numerical examples.
DEFF Research Database (Denmark)
Lindgård, Per-Anker; Mouritsen, Ole G.
1990-01-01
We discuss central questions in weak, first-order structural transitions by means of a magnetic analog model. A theory including fluctuation effects is developed for the model, showing a dynamical response with softening, fading modes and a growing central peak. The model is also analyzed by a two......-dimensional Monte Carlo simulation, showing clear precursor phenomena near the first-order transition and spontaneous nucleation. The kinetics of the domain growth is studied and found to be exceedingly slow. The results are applicable for martensitic transformations and structural surface...
The lattice Boltzmann model for the second-order Benjamin–Ono equations
International Nuclear Information System (INIS)
Lai, Huilin; Ma, Changfeng
2010-01-01
In this paper, in order to extend the lattice Boltzmann method to deal with more complicated nonlinear equations, we propose a 1D lattice Boltzmann scheme with an amending function for the second-order (1 + 1)-dimensional Benjamin–Ono equation. With the Taylor expansion and the Chapman–Enskog expansion, the governing evolution equation is recovered correctly from the continuous Boltzmann equation. The equilibrium distribution function and the amending function are obtained. Numerical simulations are carried out for the 'good' Boussinesq equation and the 'bad' one to validate the proposed model. It is found that the numerical results agree well with the analytical solutions. The present model can be used to solve more kinds of nonlinear partial differential equations
Leading-order classical Lagrangians for the nonminimal standard-model extension
Reis, J. A. A. S.; Schreck, M.
2018-03-01
In this paper, we derive the general leading-order classical Lagrangian covering all fermion operators of the nonminimal standard-model extension (SME). Such a Lagrangian is considered to be the point-particle analog of the effective field theory description of Lorentz violation that is provided by the SME. At leading order in Lorentz violation, the Lagrangian obtained satisfies the set of five nonlinear equations that govern the map from the field theory to the classical description. This result can be of use for phenomenological studies of classical bodies in gravitational fields.
Numerical Analysis of Fractional Order Epidemic Model of Childhood Diseases
Directory of Open Access Journals (Sweden)
Fazal Haq
2017-01-01
Full Text Available The fractional order Susceptible-Infected-Recovered (SIR epidemic model of childhood disease is considered. Laplace–Adomian Decomposition Method is used to compute an approximate solution of the system of nonlinear fractional differential equations. We obtain the solutions of fractional differential equations in the form of infinite series. The series solution of the proposed model converges rapidly to its exact value. The obtained results are compared with the classical case.
Hall, A.; Munoz-Ruiz, M.; Mattila, J.; Koikkalainen, J.; Tsolaki, M.; Mecocci, P.; Kloszewska, I.; Vellas, B.; Lovestone, S.; Visser, P.J.; Lotjonen, J.; Soininen, H.
2015-01-01
Background: The Disease State Index (DSI) prediction model measures the similarity of patient data to diagnosed stable and progressive mild cognitive impairment (MCI) cases to identify patients who are progressing to Alzheimer's disease. Objectives: We evaluated how well the DSI generalizes across
Vortex network community based reduced-order force model
Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya; Taira, Kunihiko
2017-11-01
We characterize the vortical wake interactions by utilizing network theory and cluster-based approaches, and develop a data-inspired unsteady force model. In the present work, the vortical interaction network is defined by nodes representing vortical elements and the edges quantified by induced velocity measures amongst the vortices. The full vorticity field is reduced to a finite number of vortical clusters based on network community detection algorithm, which serves as a basis for a skeleton network that captures the essence of the wake dynamics. We use this reduced representation of the wake to develop a data-inspired reduced-order force model that can predict unsteady fluid forces on the body. The overall formulation is demonstrated for laminar flows around canonical bluff body wake and stalled flow over an airfoil. We also show the robustness of the present network-based model against noisy data, which motivates applications towards turbulent flows and experimental measurements. Supported by the National Science Foundation (Grant 1632003).
Juvenile myopia progression, risk factors and interventions.
Myrowitz, Elliott H
2012-07-01
The development and progression of early onset myopia is actively being investigated. While myopia is often considered a benign condition it should be considered a public health problem for its visual, quality of life, and economic consequences. Nearly half of the visually impaired population in the world has uncorrected refractive errors, with myopia a high percent of that group. Uncorrected visual acuity should be screened for and treated in order to improve academic performance, career opportunities and socio-economic status. Genetic and environmental factors contribute to the onset and progression of myopia. Twin studies have supported genetic factors and research continues to identify myopia genetic loci. While multiple myopia genetic loci have been identified establishing myopia as a common complex disorder, there is not yet a genetic model explaining myopia progression in populations. Environmental factors include near work, education levels, urban compared to rural location, and time spent outdoors. In this field of study where there continues to be etiology controversies, there is recent agreement that children who spend more time outdoors are less likely to become myopic. Worldwide population studies, some completed and some in progress, with a common protocol are gathering both genetic and environmental cohort data of great value. There have been rapid population changes in prevalence rates supporting an environmental influence. Interventions to prevent juvenile myopia progression include pharmacologic agents, glasses and contact lenses. Pharmacological interventions over 1-2 year trials have shown benefits. Peripheral vision defocus has been found to affect the emmetropization process and may be affected by wearing glasses or contacts. Accommodation accuracy also has been implicated in myopia progression. Further research will aim to assess both the role and interaction of environmental influences and genetic factors.
Jacobian projection reduced-order models for dynamic systems with contact nonlinearities
Gastaldi, Chiara; Zucca, Stefano; Epureanu, Bogdan I.
2018-02-01
In structural dynamics, the prediction of the response of systems with localized nonlinearities, such as friction dampers, is of particular interest. This task becomes especially cumbersome when high-resolution finite element models are used. While state-of-the-art techniques such as Craig-Bampton component mode synthesis are employed to generate reduced order models, the interface (nonlinear) degrees of freedom must still be solved in-full. For this reason, a new generation of specialized techniques capable of reducing linear and nonlinear degrees of freedom alike is emerging. This paper proposes a new technique that exploits spatial correlations in the dynamics to compute a reduction basis. The basis is composed of a set of vectors obtained using the Jacobian of partial derivatives of the contact forces with respect to nodal displacements. These basis vectors correspond to specifically chosen boundary conditions at the contacts over one cycle of vibration. The technique is shown to be effective in the reduction of several models studied using multiple harmonics with a coupled static solution. In addition, this paper addresses another challenge common to all reduction techniques: it presents and validates a novel a posteriori error estimate capable of evaluating the quality of the reduced-order solution without involving a comparison with the full-order solution.
Fan, Qiang; Huang, Zhenyu; Zhang, Bing; Chen, Dayue
2013-02-01
Properties of discontinuities, such as bolt joints and cracks in the waveguide structures, are difficult to evaluate by either analytical or numerical methods due to the complexity and uncertainty of the discontinuities. In this paper, the discontinuity in a Timoshenko beam is modeled with high-order parameters and then these parameters are identified by using reflection coefficients at the discontinuity. The high-order model is composed of several one-order sub-models in series and each sub-model consists of inertia, stiffness and damping components in parallel. The order of the discontinuity model is determined based on the characteristics of the reflection coefficient curve and the accuracy requirement of the dynamic modeling. The model parameters are identified through the least-square fitting iteration method, of which the undetermined model parameters are updated in iteration to fit the dynamic reflection coefficient curve with the wave-based one. By using the spectral super-element method (SSEM), simulation cases, including one-order discontinuities on infinite- and finite-beams and a two-order discontinuity on an infinite beam, were employed to evaluate both the accuracy of the discontinuity model and the effectiveness of the identification method. For practical considerations, effects of measurement noise on the discontinuity parameter identification are investigated by adding different levels of noise to the simulated data. The simulation results were then validated by the corresponding experiments. Both the simulation and experimental results show that (1) the one-order discontinuities can be identified accurately with the maximum errors of 6.8% and 8.7%, respectively; (2) and the high-order discontinuities can be identified with the maximum errors of 15.8% and 16.2%, respectively; and (3) the high-order model can predict the complex discontinuity much more accurately than the one-order discontinuity model.
Basic first-order model theory in Mizar
Directory of Open Access Journals (Sweden)
Marco Bright Caminati
2010-01-01
Full Text Available The author has submitted to Mizar Mathematical Library a series of five articles introducing a framework for the formalization of classical first-order model theory.In them, Goedel's completeness and Lowenheim-Skolem theorems have also been formalized for the countable case, to offer a first application of it and to showcase its utility.This is an overview and commentary on some key aspects of this setup.It features exposition and discussion of a new encoding of basic definitions and theoretical gears needed for the task, remarks about the design strategies and approaches adopted in their implementation, and more general reflections about proof checking induced by the work done.
Protein-induced bilayer Perturbations: Lipid ordering and hydrophobic coupling
DEFF Research Database (Denmark)
Petersen, Frederic Nicolas Rønne; Laursen, Ib; Bohr, Henrik
2009-01-01
The host lipid bilayer is increasingly being recognized as an important non-specific regulator of membrane protein function. Despite considerable progress the interplay between hydrophobic coupling and lipid ordering is still elusive. We use electron spin resonance (ESR) to study the interaction...... between the model protein gramicidin and lipid bilayers of varying thickness. The free energy of the interaction is up to −6 kJ/mol; thus not strongly favored over lipid–lipid interactions. Incorporation of gramicidin results in increased order parameters with increased protein concentration...... and hydrophobic mismatch. Our findings also show that at high protein:lipid ratios the lipids are motionally restricted but not completely immobilized. Both exchange on and off rate values for the lipid ↔ gramicidin interaction are lowest at optimal hydrophobic matching. Hydrophobic mismatch of few Å results...
Directory of Open Access Journals (Sweden)
C.G. Ozoegwu
2016-01-01
Full Text Available The general least squares model for milling process state term is presented. A discrete map for milling stability analysis that is based on the third-order case of the presented general least squares milling state term model is first studied and compared with its third-order counterpart that is based on the interpolation theory. Both numerical rate of convergence and chatter stability results of the two maps are compared using the single degree of freedom (1DOF milling model. The numerical rate of convergence of the presented third-order model is also studied using the two degree of freedom (2DOF milling process model. Comparison gave that stability results from the two maps agree closely but the presented map demonstrated reduction in number of needed calculations leading to about 30% savings in computational time (CT. It is seen in earlier works that accuracy of milling stability analysis using the full-discretization method rises from first-order theory to second-order theory and continues to rise to the third-order theory. The present work confirms this trend. In conclusion, the method presented in this work will enable fast and accurate computation of stability diagrams for use by machinists.
Large-order behavior of nondecoupling effects in the standard model and triviality
International Nuclear Information System (INIS)
Aoki, K.
1994-01-01
We compute some nondecoupling effects in the standard model, such as the ρ parameter, to all orders in the coupling constant expansion. We analyze their large order behavior and explicitly show how they are related to the nonperturbative cutoff dependence of these nondecoupling effects due to the triviality of the theory
Progress in MELCOR development and assessment
International Nuclear Information System (INIS)
Summers, R.M.; Kmetyk, L.N.; Cole, R.K. Jr.; Smith, R.C.; Elsbernd, A.E.; Stuart, D.S.; Thompson, S.L.
1995-01-01
MELCOR models the progression of severe accidents in light water reactor nuclear power plants. Recent efforts in MELCOR development to incorporate CORCON-Mod3 models for core-concrete interactions, new models for advanced reactors, and improvements to several other existing models have resulted in release of MELCOR 1.8.3. In addition, continuing efforts to expand the code assessment database have filled in many of the gaps in phenomenological coverage. Efforts are now under way to develop models for chemical interactions of fission products with structural surfaces and for reactions of iodine in the presence of water, and work is also in progress to improve models for the scrubbing of fission products by water pools, the chemical reactions of boron carbide with steam, and the coupling of flow blockages with the hydrodynamics. Several code assessment analyses are in progress, and more are planned
Earnings progression, human capital and incentives
DEFF Research Database (Denmark)
Frederiksen, Anders
progression by investigating the effects of on-the-job human capital acquisition, explicit short-run incentives and career concern incentives on earnings progression. The model leads to predictions about the incentive structure and the progression in both cross-sectional and individual earnings which...
Topological order in an exactly solvable 3D spin model
International Nuclear Information System (INIS)
Bravyi, Sergey; Leemhuis, Bernhard; Terhal, Barbara M.
2011-01-01
Research highlights: RHtriangle We study exactly solvable spin model with six-qubit nearest neighbor interactions on a 3D face centered cubic lattice. RHtriangle The ground space of the model exhibits topological quantum order. RHtriangle Elementary excitations can be geometrically described as the corners of rectangular-shaped membranes. RHtriangle The ground space can encode 4g qubits where g is the greatest common divisor of the lattice dimensions. RHtriangle Logical operators acting on the encoded qubits are described in terms of closed strings and closed membranes. - Abstract: We study a 3D generalization of the toric code model introduced recently by Chamon. This is an exactly solvable spin model with six-qubit nearest-neighbor interactions on an FCC lattice whose ground space exhibits topological quantum order. The elementary excitations of this model which we call monopoles can be geometrically described as the corners of rectangular-shaped membranes. We prove that the creation of an isolated monopole separated from other monopoles by a distance R requires an operator acting on Ω(R 2 ) qubits. Composite particles that consist of two monopoles (dipoles) and four monopoles (quadrupoles) can be described as end-points of strings. The peculiar feature of the model is that dipole-type strings are rigid, that is, such strings must be aligned with face-diagonals of the lattice. For periodic boundary conditions the ground space can encode 4g qubits where g is the greatest common divisor of the lattice dimensions. We describe a complete set of logical operators acting on the encoded qubits in terms of closed strings and closed membranes.
Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts
Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.
2017-01-01
This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.
White matter lesion progression
DEFF Research Database (Denmark)
Hofer, Edith; Cavalieri, Margherita; Bis, Joshua C
2015-01-01
10 cohorts. To assess the relative contribution of genetic factors to progression of WML, we compared in 7 cohorts risk models including demographics, vascular risk factors plus single-nucleotide polymorphisms that have been shown to be associated cross-sectionally with WML in the current......BACKGROUND AND PURPOSE: White matter lesion (WML) progression on magnetic resonance imaging is related to cognitive decline and stroke, but its determinants besides baseline WML burden are largely unknown. Here, we estimated heritability of WML progression, and sought common genetic variants...... associated with WML progression in elderly participants from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. METHODS: Heritability of WML progression was calculated in the Framingham Heart Study. The genome-wide association study included 7773 elderly participants from...
Directory of Open Access Journals (Sweden)
Salman IJAZ
2018-05-01
Full Text Available In this paper, a methodology has been developed to address the issue of force fighting and to achieve precise position tracking of control surface driven by two dissimilar actuators. The nonlinear dynamics of both actuators are first approximated as fractional order models. Based on the identified models, three fractional order controllers are proposed for the whole system. Two Fractional Order PID (FOPID controllers are dedicated to improving transient response and are designed in a position feedback configuration. In order to synchronize the actuator dynamics, a third fractional order PI controller is designed, which feeds the force compensation signal in position feedback loop of both actuators. Nelder-Mead (N-M optimization technique is employed in order to optimally tune controller parameters based on the proposed performance criteria. To test the proposed controllers according to real flight condition, an external disturbance of higher amplitude that acts as airload is applied directly on the control surface. In addition, a disturbance signal function of system states is applied to check the robustness of proposed controller. Simulation results on nonlinear system model validated the performance of the proposed scheme as compared to optimal PID and high gain PID controllers. Keywords: Aerospace, Fractional order control, Model identification, Nelder-Mead optimization, Robustness
Empirical Reduced-Order Modeling for Boundary Feedback Flow Control
Directory of Open Access Journals (Sweden)
Seddik M. Djouadi
2008-01-01
Full Text Available This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE- based models in general. Specifically, the proper orthogonal decomposition (POD of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA. This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. An H∞ feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.
Energy Technology Data Exchange (ETDEWEB)
Johnson, Brian B [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Purba, Victor [University of Minnesota; Jafarpour, Saber [University of California, Santa Barbara; Bullo, Francesco [University of California, Santa Barbara; Dhople, Sairaj [University of Minnesota
2017-08-31
Given that next-generation infrastructures will contain large numbers of grid-connected inverters and these interfaces will be satisfying a growing fraction of system load, it is imperative to analyze the impacts of power electronics on such systems. However, since each inverter model has a relatively large number of dynamic states, it would be impractical to execute complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. That is, we show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as an individual inverter in the paralleled system. Numerical simulations validate the reduced-order models.
Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun
2016-01-01
The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.
The order of chaos on a Bianch IX cosmological model
Energy Technology Data Exchange (ETDEWEB)
Bugalho, H; da Silva, A R; Ramos, J S
1986-12-01
The purpose of this paper is to analyze the chaotic behavior that can arise on a type-IX cosmological model using methods from dynamic systems theory and symbolic dynamics. Specifically, instead of the Belinski-Khalatnikov-Lifschitz model, we use the iterates of a monotonously increasing map of the circle with a discontinuity, and for the Hamiltonian dynamics of Misner's Mixmaster model we introduce the iterates of a noninvertible map. An equivalence between these two models can easily be brought upon by translating them in symbolic dynamical terms. The resulting symbolic orbits can be inserted in an ordered tree structure set, and so we can present an effective counting and referentation of all period orbits.
Tsuchida, Takuma; Lee, Youngmin A; Fujiwara, Naoto; Ybanez, Maria; Allen, Brittany; Martins, Sebastiao; Fiel, M Isabel; Goossens, Nicolas; Chou, Hsin-I; Hoshida, Yujin; Friedman, Scott L
2018-03-20
Although the majority of patients with nonalcoholic fatty liver disease (NAFLD) have only steatosis without progression, a sizable fraction develop non-alcoholic steatohepatitis (NASH), which can lead to cirrhosis and hepatocellular carcinoma (HCC). Many established diet-induced mouse models for NASH require 24-52 weeks, which makes testing for drug response costly and time consuming. We have sought to establish a murine NASH model with rapid progression of extensive fibrosis and HCC by using a western diet (WD), which is high-fat, high-fructose and high-cholesterol, combined with low dose weekly intraperitoneal carbon tetrachloride (CCl 4 ), which served as an accelerator. C57BL/6J mice were fed a normal chow diet (ND) ± CCl 4 or WD ± CCl 4 for 12 and 24 weeks. Addition of CCl 4 exacerbated histological features of NASH, fibrosis, and tumor development induced by WD, which resulted in stage 3 fibrosis at 12 weeks and HCC development at 24 weeks. Furthermore, whole liver transcriptomic analysis indicated that dysregulated molecular pathways in WD/CCl 4 mice and immunologic features were closely similar to those of human NASH. Our mouse NASH model exhibits rapid progression of advanced fibrosis and HCC, and mimics histological, immunological and transcriptomic features of human NASH, suggesting that it will be a useful experimental tool for preclinical drug testing. A carefully characterized model has been developed in mice that recapitulates the progressive stages of human fatty liver disease, from simple steatosis, to inflammation, fibrosis and cancer. The functional pathways of gene expression and immune abnormalities in this model closely resemble human disease. The ease and reproducibility of this model makes it ideal to study disease pathogenesis and test new treatments. Copyright © 2018 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
Ionization in liquids [annual] progress report, 1993--1994
International Nuclear Information System (INIS)
Bakale, G.
1994-01-01
Progress in 1993--94 was focused on delineating how ions of the model nonpolar spherical solute Buckminsterfullerene interact differently with various nonpolar solvents than does the ellipsoidal fullerene analog C-70, and exposing a variety of new audiences to the electrophilicity-carcinogenicity relationship in order to obtain fresh insight into this relationship that may lead to elucidation of the role of electrons in carcinogenesis and thereby a better understanding of the biological effects of ionizing radiation. To achieve these goals a new collaboration was established with scientists at Oak Ridge National Lab who have unique facilities to characterize fullerene and its radiolytic products
Progress in the improved lattice calculation of direct CP-violation in the Standard Model
Kelly, Christopher
2018-03-01
We discuss the ongoing effort by the RBC & UKQCD collaborations to improve our lattice calculation of the measure of Standard Model direct CP violation, ɛ', with physical kinematics. We present our progress in decreasing the (dominant) statistical error and discuss other related activities aimed at reducing the systematic errors.
Progress towards extreme attitude testing with Magnetic Suspension and Balance Systems
Britcher, Colin P.; Parker, David H.
1988-01-01
Progress is reported in a research effort aimed towards demonstration of the feasibility of suspension and aerodynamic testing of models at high angles of attack in wind tunnel Magnetic Suspension and Balance Systems. Extensive modifications, described in this paper, have been made to the Southampton University suspension system in order to facilitate this work. They include revision of electromagnet configuration, installation of all-new position sensors and expansion of control system programs. An angle of attack range of 0 to 90 deg is expected for axisymmetric models. To date, suspension up to 80 deg angle of attack has been achieved.
International Nuclear Information System (INIS)
Zwingelstein, G.C.
1980-12-01
After a short description of a disturbance analysis system for nuclear plant based on real time dynamic modelling and simulation, a scheme for generating aggregated reduced models of high order systems is presented. This method allows the choice of dominant dynamic modes and its efficiency is illustrated for the case of a 29th order nuclear plant model
Index-aware model order reduction : LTI DAEs in electric networks
Banagaaya, N.; Schilders, W.H.A.; Ali, G.; Tischendorf, C.
2014-01-01
Purpose Model order reduction (MOR) has been widely used in the electric networks but little has been done to reduce higher index differential algebraic equations (DAEs). The paper aims to discuss these issues. Design/methodology/approach Most methods first do an index reduction before reducing a
Magin, Richard L.; Li, Weiguo; Velasco, M. Pilar; Trujillo, Juan; Reiter, David A.; Morgenstern, Ashley; Spencer, Richard G.
2011-01-01
We present a fractional-order extension of the Bloch equations to describe anomalous NMR relaxation phenomena (T1 and T2). The model has solutions in the form of Mittag-Leffler and stretched exponential functions that generalize conventional exponential relaxation. Such functions have been shown by others to be useful for describing dielectric and viscoelastic relaxation in complex, heterogeneous materials. Here, we apply these fractional-order T1 and T2 relaxation models to experiments performed at 9.4 and 11.7 Tesla on type I collagen gels, chondroitin sulfate mixtures, and to bovine nasal cartilage (BNC), a largely isotropic and homogeneous form of cartilage. The results show that the fractional-order analysis captures important features of NMR relaxation that are typically described by multi-exponential decay models. We find that the T2 relaxation of BNC can be described in a unique way by a single fractional-order parameter (α), in contrast to the lack of uniqueness of multi-exponential fits in the realistic setting of a finite signal-to-noise ratio. No anomalous behavior of T1 was observed in BNC. In the single-component gels, for T2 measurements, increasing the concentration of the largest components of cartilage matrix, collagen and chondroitin sulfate, results in a decrease in α, reflecting a more restricted aqueous environment. The quality of the curve fits obtained using Mittag-Leffler and stretched exponential functions are in some cases superior to those obtained using mono- and bi-exponential models. In both gels and BNC, α appears to account for microstructural complexity in the setting of an altered distribution of relaxation times. This work suggests the utility of fractional-order models to describe T2 NMR relaxation processes in biological tissues. PMID:21498095
Modeling 3D PCMI using the Extended Finite Element Method with higher order elements
Energy Technology Data Exchange (ETDEWEB)
Jiang, W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Spencer, Benjamin W. [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2017-03-31
This report documents the recent development to enable XFEM to work with higher order elements. It also demonstrates the application of higher order (quadratic) elements to both 2D and 3D models of PCMI problems, where discrete fractures in the fuel are represented using XFEM. The modeling results demonstrate the ability of the higher order XFEM to accurately capture the effects of a crack on the response in the vicinity of the intersecting surfaces of cracked fuel and cladding, as well as represent smooth responses in the regions away from the crack.
Limit order book and its modeling in terms of Gibbs Grand-Canonical Ensemble
Bicci, Alberto
2016-12-01
In the domain of so called Econophysics some attempts have been already made for applying the theory of thermodynamics and statistical mechanics to economics and financial markets. In this paper a similar approach is made from a different perspective, trying to model the limit order book and price formation process of a given stock by the Grand-Canonical Gibbs Ensemble for the bid and ask orders. The application of the Bose-Einstein statistics to this ensemble allows then to derive the distribution of the sell and buy orders as a function of price. As a consequence we can define in a meaningful way expressions for the temperatures of the ensembles of bid orders and of ask orders, which are a function of minimum bid, maximum ask and closure prices of the stock as well as of the exchanged volume of shares. It is demonstrated that the difference between the ask and bid orders temperatures can be related to the VAO (Volume Accumulation Oscillator), an indicator empirically defined in Technical Analysis of stock markets. Furthermore the derived distributions for aggregate bid and ask orders can be subject to well defined validations against real data, giving a falsifiable character to the model.
Buil-Bruna, Núria; Sahota, Tarjinder; López-Picazo, José-María; Moreno-Jiménez, Marta; Martín-Algarra, Salvador; Ribba, Benjamin; Trocóniz, Iñaki F
2015-06-15
Predictive biomarkers can play a key role in individualized disease monitoring. Unfortunately, the use of biomarkers in clinical settings has thus far been limited. We have previously shown that mechanism-based pharmacokinetic/pharmacodynamic modeling enables integration of nonvalidated biomarker data to provide predictive model-based biomarkers for response classification. The biomarker model we developed incorporates an underlying latent variable (disease) representing (unobserved) tumor size dynamics, which is assumed to drive biomarker production and to be influenced by exposure to treatment. Here, we show that by integrating CT scan data, the population model can be expanded to include patient outcome. Moreover, we show that in conjunction with routine medical monitoring data, the population model can support accurate individual predictions of outcome. Our combined model predicts that a change in disease of 29.2% (relative standard error 20%) between two consecutive CT scans (i.e., 6-8 weeks) gives a probability of disease progression of 50%. We apply this framework to an external dataset containing biomarker data from 22 small cell lung cancer patients (four patients progressing during follow-up). Using only data up until the end of treatment (a total of 137 lactate dehydrogenase and 77 neuron-specific enolase observations), the statistical framework prospectively identified 75% of the individuals as having a predictable outcome in follow-up visits. This included two of the four patients who eventually progressed. In all identified individuals, the model-predicted outcomes matched the observed outcomes. This framework allows at risk patients to be identified early and therapeutic intervention/monitoring to be adjusted individually, which may improve overall patient survival. ©2015 American Association for Cancer Research.
Dynamics of a Fractional Order HIV Infection Model with Specific Functional Response and Cure Rate
Directory of Open Access Journals (Sweden)
Adnane Boukhouima
2017-01-01
Full Text Available We propose a fractional order model in this paper to describe the dynamics of human immunodeficiency virus (HIV infection. In the model, the infection transmission process is modeled by a specific functional response. First, we show that the model is mathematically and biologically well posed. Second, the local and global stabilities of the equilibria are investigated. Finally, some numerical simulations are presented in order to illustrate our theoretical results.
Analysis of a decision model in the context of equilibrium pricing and order book pricing
Wagner, D. C.; Schmitt, T. A.; Schäfer, R.; Guhr, T.; Wolf, D. E.
2014-12-01
An agent-based model for financial markets has to incorporate two aspects: decision making and price formation. We introduce a simple decision model and consider its implications in two different pricing schemes. First, we study its parameter dependence within a supply-demand balance setting. We find realistic behavior in a wide parameter range. Second, we embed our decision model in an order book setting. Here, we observe interesting features which are not present in the equilibrium pricing scheme. In particular, we find a nontrivial behavior of the order book volumes which reminds of a trend switching phenomenon. Thus, the decision making model alone does not realistically represent the trading and the stylized facts. The order book mechanism is crucial.
Roof planes detection via a second-order variational model
Benciolini, Battista; Ruggiero, Valeria; Vitti, Alfonso; Zanetti, Massimo
2018-04-01
The paper describes a unified automatic procedure for the detection of roof planes in gridded height data. The procedure exploits the Blake-Zisserman (BZ) model for segmentation in both 2D and 1D, and aims to detect, to model and to label roof planes. The BZ model relies on the minimization of a functional that depends on first- and second-order derivatives, free discontinuities and free gradient discontinuities. During the minimization, the relative strength of each competitor is controlled by a set of weight parameters. By finding the minimum of the approximated BZ functional, one obtains: (1) an approximation of the data that is smoothed solely within regions of homogeneous gradient, and (2) an explicit detection of the discontinuities and gradient discontinuities of the approximation. Firstly, input data is segmented using the 2D BZ. The maps of data and gradient discontinuities are used to isolate building candidates and planar patches (i.e. regions with homogeneous gradient) that correspond to roof planes. Connected regions that can not be considered as buildings are filtered according to both patch dimension and distribution of the directions of the normals to the boundary. The 1D BZ model is applied to the curvilinear coordinates of boundary points of building candidates in order to reduce the effect of data granularity when the normals are evaluated. In particular, corners are preserved and can be detected by means of gradient discontinuity. Lastly, a total least squares model is applied to estimate the parameters of the plane that best fits the points of each planar patch (orthogonal regression with planar model). Refinement of planar patches is performed by assigning those points that are close to the boundaries to the planar patch for which a given proximity measure assumes the smallest value. The proximity measure is defined to account for the variance of a fitting plane and a weighted distance of a point from the plane. The effectiveness of the
A critical look at the kinetic models of thermoluminescence-II. Non-first order kinetics
International Nuclear Information System (INIS)
Sunta, C M; Ayta, W E F; Chubaci, J F D; Watanabe, S
2005-01-01
Non-first order (FO) kinetics models are of three types; second order (SO), general order (GO) and mixed order (MO). It is shown that all three of these have constraints in their energy level schemes and their applicable parameter values. In nature such restrictions are not expected to exist. The thermoluminescence (TL) glow peaks produced by these models shift their position and change their shape as the trap occupancies change. Such characteristics are very unlike those found in samples of real materials. In these models, in general, retrapping predominates over recombination. It is shown that the quasi-equilibrium (QE) assumption implied in the derivation of the TL equation of these models is quite valid, thus disproving earlier workers' conclusion that QE cannot be held under retrapping dominant conditions. However notwithstanding their validity, they suffer from the shortcomings as stated above and have certain lacunae. For example, the kinetic order (KO) parameter and the pre-exponential factor which are assumed to be the constant parameters of the GO kinetics expression turn out to be variables when this expression is applied to plausible physical models. Further, in glow peak characterization using the GO expression, the quality of fit is found to deteriorate when the best fitted value of KO parameter is different from 1 and 2. This means that the found value of the basic parameter, namely the activation energy, becomes subject to error. In the MO kinetics model, the value of the KO parameter α would change with dose, and thus in this model also, as in the GO model, no single value of KO can be assigned to a given glow peak. The paper discusses TL of real materials having characteristics typically like those of FO kinetics. Theoretically too, a plausible physical model of TL emission produces glow peaks which have characteristics of FO kinetics under a wide variety of parametric combinations. In the background of the above findings, it is suggested that
An image-based model of brain volume biomarker changes in Huntington's disease.
Wijeratne, Peter A; Young, Alexandra L; Oxtoby, Neil P; Marinescu, Razvan V; Firth, Nicholas C; Johnson, Eileanoir B; Mohan, Amrita; Sampaio, Cristina; Scahill, Rachael I; Tabrizi, Sarah J; Alexander, Daniel C
2018-05-01
Determining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine-grained model of temporal progression of Huntington's disease from premanifest through to manifest stages. We employ a probabilistic event-based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track-HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides. The model recovers the following order of detectable changes in brain region volumes: putamen, caudate, pallidum, insula white matter, nonventricular cerebrospinal fluid, amygdala, optic chiasm, third ventricle, posterior insula, and basal forebrain. This ordering is mostly preserved even under cross-validation of the uncertainty in the event sequence. Longitudinal analysis performed using 6 years of follow-up data from baseline confirms efficacy of the model, as subjects consistently move to later stages with time, and significant correlations are observed between the estimated stages and nonimaging phenotypic markers. We used a data-driven method to provide new insight into Huntington's disease progression as well as new power to stage and predict conversion. Our results highlight the potential of disease progression models, such as the event-based model, to provide new insight into Huntington's disease progression and to support fine-grained patient stratification for future precision medicine in Huntington's disease.
Zhai, Yi; Wang, Yan; Wang, Zhaoqi; Liu, Yongji; Zhang, Lin; He, Yuanqing; Chang, Shengjiang
2014-01-01
An achromatic element eliminating only longitudinal chromatic aberration (LCA) while maintaining transverse chromatic aberration (TCA) is established for the eye model, which involves the angle formed by the visual and optical axis. To investigate the impacts of higher-order aberrations on vision, the actual data of higher-order aberrations of human eyes with three typical levels are introduced into the eye model along visual axis. Moreover, three kinds of individual eye models are established to investigate the impacts of higher-order aberrations, chromatic aberration (LCA+TCA), LCA and TCA on vision under the photopic condition, respectively. Results show that for most human eyes, the impact of chromatic aberration on vision is much stronger than that of higher-order aberrations, and the impact of LCA in chromatic aberration dominates. The impact of TCA is approximately equal to that of normal level higher-order aberrations and it can be ignored when LCA exists.
Birth Order and Susceptibility to Peer Modeling Influences in Young Boys
Finley, Gordon E.; Cheyne, James A.
1976-01-01
Susceptibility to peer modeling influences as a function of birth order was studied by examining the data of 390 boys from kindergarten through third grade who previously had participated in moral transgression experiments. (MS)
Progression of regional grey matter atrophy in multiple sclerosis.
Eshaghi, Arman; Marinescu, Razvan V; Young, Alexandra L; Firth, Nicholas C; Prados, Ferran; Jorge Cardoso, M; Tur, Carmen; De Angelis, Floriana; Cawley, Niamh; Brownlee, Wallace J; De Stefano, Nicola; Laura Stromillo, M; Battaglini, Marco; Ruggieri, Serena; Gasperini, Claudio; Filippi, Massimo; Rocca, Maria A; Rovira, Alex; Sastre-Garriga, Jaume; Geurts, Jeroen J G; Vrenken, Hugo; Wottschel, Viktor; Leurs, Cyra E; Uitdehaag, Bernard; Pirpamer, Lukas; Enzinger, Christian; Ourselin, Sebastien; Gandini Wheeler-Kingshott, Claudia A; Chard, Declan; Thompson, Alan J; Barkhof, Frederik; Alexander, Daniel C; Ciccarelli, Olga
2018-06-01
See Stankoff and Louapre (doi:10.1093/brain/awy114) for a scientific commentary on this article.Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset multiple
Progression of regional grey matter atrophy in multiple sclerosis
Marinescu, Razvan V; Young, Alexandra L; Firth, Nicholas C; Jorge Cardoso, M; Tur, Carmen; De Angelis, Floriana; Cawley, Niamh; Brownlee, Wallace J; De Stefano, Nicola; Laura Stromillo, M; Battaglini, Marco; Ruggieri, Serena; Gasperini, Claudio; Filippi, Massimo; Rocca, Maria A; Rovira, Alex; Sastre-Garriga, Jaume; Geurts, Jeroen J G; Vrenken, Hugo; Wottschel, Viktor; Leurs, Cyra E; Uitdehaag, Bernard; Pirpamer, Lukas; Enzinger, Christian; Ourselin, Sebastien; Gandini Wheeler-Kingshott, Claudia A; Chard, Declan; Thompson, Alan J; Barkhof, Frederik; Alexander, Daniel C; Ciccarelli, Olga
2018-01-01
Abstract See Stankoff and Louapre (doi:10.1093/brain/awy114) for a scientific commentary on this article. Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse
Sucharitakul, Kanes; Boily, Marie-Claude; Dimitrov, Dobromir
2018-01-01
Background Many mathematical models have investigated the population-level impact of expanding antiretroviral therapy (ART), using different assumptions about HIV disease progression on ART and among ART dropouts. We evaluated the influence of these assumptions on model projections of the number of infections and deaths prevented by expanded ART. Methods A new dynamic model of HIV transmission among men who have sex with men (MSM) was developed, which incorporated each of four alternative assumptions about disease progression used in previous models: (A) ART slows disease progression; (B) ART halts disease progression; (C) ART reverses disease progression by increasing CD4 count; (D) ART reverses disease progression, but disease progresses rapidly once treatment is stopped. The model was independently calibrated to HIV prevalence and ART coverage data from the United States under each progression assumption in turn. New HIV infections and HIV-related deaths averted over 10 years were compared for fixed ART coverage increases. Results Little absolute difference (ART coverage (varied between 33% and 90%) if ART dropouts reinitiated ART at the same rate as ART-naïve MSM. Larger differences in the predicted fraction of HIV-related deaths averted were observed (up to 15pp). However, if ART dropouts could only reinitiate ART at CD4ART interruption did not affect the fraction of HIV infections averted with expanded ART, unless ART dropouts only re-initiated ART at low CD4 counts. Different disease progression assumptions had a larger influence on the fraction of HIV-related deaths averted with expanded ART. PMID:29554136
Zeng, Xueqiang; Luo, Gang
2017-12-01
Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.
Testing the Processing Hypothesis of word order variation using a probabilistic language model
Bloem, J.
2016-01-01
This work investigates the application of a measure of surprisal to modeling a grammatical variation phenomenon between near-synonymous constructions. We investigate a particular variation phenomenon, word order variation in Dutch two-verb clusters, where it has been established that word order
International Nuclear Information System (INIS)
Harish, V.S.K.V.; Kumar, Arun
2016-01-01
Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.
Arana-Guajardo, Ana; Pérez-Barbosa, Lorena; Vega-Morales, David; Riega-Torres, Janett; Esquivel-Valerio, Jorge; Garza-Elizondo, Mario
2014-01-01
Different prediction rules have been applied to patients with undifferentiated arthritis (UA) to identify those that progress to rheumatoid arthritis (RA). The Leiden Prediction Rule (LPR) has proven useful in different UA cohorts. To apply the LPR to a cohort of patients with UA of northeastern Mexico. We included 47 patients with UA, LPR was applied at baseline. They were evaluated and then classified after one year of follow-up into two groups: those who progressed to RA (according to ACR 1987) and those who did not. 43% of the AI patients developed RA. In the RA group, 56% of patients obtained a score ≤ 6 and only 15% ≥ 8. 70% who did not progress to RA had a score between 6 and ≤ 8. There was no difference in median score of LPR between groups, p=0.940. Most patients who progressed to RA scored less than 6 points in the LPR. Unlike what was observed in other cohorts, the model in our population did not allow us to predict the progression of the disease. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.
Chronic progressive multiple sclerosis
International Nuclear Information System (INIS)
Buffoli, A.; Micheletti, E.; Capra, R.; Mattioli, F.; Marciano', N.
1991-01-01
A long-lasting immunological suppression action seems to be produced by total lymphoid irradiation; some authors emphasize the favorable effect of this treatment on chronic progressive multiple sclerosis. In order to evaluate the actual role of TLI, 6 patients affected with chronic progressive multiple sclerosis were submitted to TLI with shaped and personalized fields at the Istituto del Radio, University of Brescia, Italy. The total dose delivered was 19.8 Gy in 4 weeks, 1.8 Gy/day, 5d/w; a week elapsed between the first and the second irradiation course. Disability according to Kurtzke scale was evaluated, together with blood lymphocyte count and irradiation side-effects, over a mean follow-up period of 20.8 months (range: 13-24). Our findings indicate that: a) disease progression was not markedly reduced by TLI; b) steroid hormones responsivity was restored after irradiation, and c) side-effects were mild and tolerable
Bilinear reduced order approximate model of parabolic distributed solar collectors
Elmetennani, Shahrazed
2015-07-01
This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low dimensional bilinear state representation, enables the reproduction of the heat transfer dynamics along the collector tube for system analysis. Moreover, presented as a reduced order bilinear state space model, the well established control theory for this class of systems can be applied. The approximation efficiency has been proven by several simulation tests, which have been performed considering parameters of the Acurex field with real external working conditions. Model accuracy has been evaluated by comparison to the analytical solution of the hyperbolic distributed model and its semi discretized approximation highlighting the benefits of using the proposed numerical scheme. Furthermore, model sensitivity to the different parameters of the gaussian interpolation has been studied.
Liu, Weihua; Yang, Yi; Wang, Shuqing; Liu, Yang
2014-01-01
Order insertion often occurs in the scheduling process of logistics service supply chain (LSSC), which disturbs normal time scheduling especially in the environment of mass customization logistics service. This study analyses order similarity coefficient and order insertion operation process and then establishes an order insertion scheduling model of LSSC with service capacity and time factors considered. This model aims to minimize the average unit volume operation cost of logistics service integrator and maximize the average satisfaction degree of functional logistics service providers. In order to verify the viability and effectiveness of our model, a specific example is numerically analyzed. Some interesting conclusions are obtained. First, along with the increase of completion time delay coefficient permitted by customers, the possible inserting order volume first increases and then trends to be stable. Second, supply chain performance reaches the best when the volume of inserting order is equal to the surplus volume of the normal operation capacity in mass service process. Third, the larger the normal operation capacity in mass service process is, the bigger the possible inserting order's volume will be. Moreover, compared to increasing the completion time delay coefficient, improving the normal operation capacity of mass service process is more useful.
An efficient numerical progressive diagonalization scheme for the quantum Rabi model revisited
International Nuclear Information System (INIS)
Pan, Feng; Bao, Lina; Dai, Lianrong; Draayer, Jerry P
2017-01-01
An efficient numerical progressive diagonalization scheme for the quantum Rabi model is revisited. The advantage of the scheme lies in the fact that the quantum Rabi model can be solved almost exactly by using the scheme that only involves a finite set of one variable polynomial equations. The scheme is especially efficient for a specified eigenstate of the model, for example, the ground state. Some low-lying level energies of the model for several sets of parameters are calculated, of which one set of the results is compared to that obtained from the Braak’s exact solution proposed recently. It is shown that the derivative of the entanglement measure defined in terms of the reduced von Neumann entropy with respect to the coupling parameter does reach the maximum near the critical point deduced from the classical limit of the Dicke model, which may provide a probe of the critical point of the crossover in finite quantum many-body systems, such as that in the quantum Rabi model. (paper)
A Frank mixture copula family for modeling higher-order correlations of neural spike counts
International Nuclear Information System (INIS)
Onken, Arno; Obermayer, Klaus
2009-01-01
In order to evaluate the importance of higher-order correlations in neural spike count codes, flexible statistical models of dependent multivariate spike counts are required. Copula families, parametric multivariate distributions that represent dependencies, can be applied to construct such models. We introduce the Frank mixture family as a new copula family that has separate parameters for all pairwise and higher-order correlations. In contrast to the Farlie-Gumbel-Morgenstern copula family that shares this property, the Frank mixture copula can model strong correlations. We apply spike count models based on the Frank mixture copula to data generated by a network of leaky integrate-and-fire neurons and compare the goodness of fit to distributions based on the Farlie-Gumbel-Morgenstern family. Finally, we evaluate the importance of using proper single neuron spike count distributions on the Shannon information. We find notable deviations in the entropy that increase with decreasing firing rates. Moreover, we find that the Frank mixture family increases the log likelihood of the fit significantly compared to the Farlie-Gumbel-Morgenstern family. This shows that the Frank mixture copula is a useful tool to assess the importance of higher-order correlations in spike count codes.
Energy Technology Data Exchange (ETDEWEB)
1976-01-01
Progress is reviewed in these areas: nuclear spin-lattice relaxation in ortho-para mixtures of solid deuterium below T/sub lambda/; pulsed NMR experiments of matrix isolated HCl; stimulated Raman scattering in solid hydrogen and nitrogen; and infrared line broadening of matrix isolated molecules. (GHT)
International Nuclear Information System (INIS)
1976-01-01
Progress is reviewed in these areas: nuclear spin-lattice relaxation in ortho-para mixtures of solid deuterium below T/sub lambda/; pulsed NMR experiments of matrix isolated HCl; stimulated Raman scattering in solid hydrogen and nitrogen; and infrared line broadening of matrix isolated molecules
Recent progress of ordered mesoporous silica-supported chiral metallic catalysts
Directory of Open Access Journals (Sweden)
LIU Rui
2013-02-01
Full Text Available Recently,ordered silica-based mesoporous chiral organometallics-functionalized heterogeneous catalysts have attracted extensive research interest due to their excellent properties,such as easy preparation,high activity and convenient recycle.This review mainly summarizesthe generally prepared strategy and the silica-based organometallics-functionalized heterogeneous catalysts reported in the literatures.
Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach
Aguilo, Miguel A.; Warner, James E.
2017-01-01
This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.
Simulation model of a single-server order picking workstation using aggregate process times
Andriansyah, R.; Etman, L.F.P.; Rooda, J.E.; Biles, W.E.; Saltelli, A.; Dini, C.
2009-01-01
In this paper we propose a simulation modeling approach based on aggregate process times for the performance analysis of order picking workstations in automated warehouses with first-in-first-out processing of orders. The aggregate process time distribution is calculated from tote arrival and
Reduced order surrogate modelling (ROSM) of high dimensional deterministic simulations
Mitry, Mina
Often, computationally expensive engineering simulations can prohibit the engineering design process. As a result, designers may turn to a less computationally demanding approximate, or surrogate, model to facilitate their design process. However, owing to the the curse of dimensionality, classical surrogate models become too computationally expensive for high dimensional data. To address this limitation of classical methods, we develop linear and non-linear Reduced Order Surrogate Modelling (ROSM) techniques. Two algorithms are presented, which are based on a combination of linear/kernel principal component analysis and radial basis functions. These algorithms are applied to subsonic and transonic aerodynamic data, as well as a model for a chemical spill in a channel. The results of this thesis show that ROSM can provide a significant computational benefit over classical surrogate modelling, sometimes at the expense of a minor loss in accuracy.
Shi, Jinfei; Zhu, Songqing; Chen, Ruwen
2017-12-01
An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.
Tinder, Teresa L; Subramani, Durai B; Basu, Gargi D; Bradley, Judy M; Schettini, Jorge; Million, Arefayene; Skaar, Todd; Mukherjee, Pinku
2008-09-01
MUC1, a membrane tethered mucin glycoprotein, is overexpressed and aberrantly glycosylated in >80% of human ductal pancreatic adenocarcinoma. However, the role of MUC1 in pancreatic cancer has been elusive, partly due to the lack of an appropriate model. We report the characterization of a novel mouse model that expresses human MUC1 as a self molecule (PDA.MUC1 mice). Pancreatic tumors arise in an appropriate MUC1-tolerant background within an immune-competent host. Significant enhancement in the development of pancreatic intraepithelial preneoplastic lesions and progression to adenocarcinoma is observed in PDA.MUC1 mice, possibly due to increased proliferation. Tumors from PDA.MUC1 mice express higher levels of cyclooxygenase-2 and IDO compared with PDA mice lacking MUC1, especially during early stages of tumor development. The increased proinflammatory milieu correlates with an increased percentage of regulatory T cells and myeloid suppressor cells in the pancreatic tumor and tumor draining lymph nodes. Data shows that during pancreatic cancer progression, MUC1-mediated mechanisms enhance the onset and progression of the disease, which in turn regulate the immune responses. Thus, the mouse model is ideally suited for testing novel chemopreventive and therapeutic strategies against pancreatic cancer.
Tinder, Teresa L.; Subramani, Durai B.; Basu, Gargi D.; Bradley, Judy M.; Schettini, Jorge; Million, Arefayene; Skaar, Todd
2008-01-01
MUC1, a membrane tethered mucin glycoprotein, is overexpressed and aberrantly glycosylated in >80% of human ductal pancreatic adenocarcinoma. However, the role of MUC1 in pancreatic cancer has been elusive, partly due to the lack of an appropriate model. We report the characterization of a novel mouse model that expresses human MUC1 as a self molecule (PDA.MUC1 mice). Pancreatic tumors arise in an appropriate MUC1-tolerant background within an immune competent host. Significant enhancement in the development of pancreatic intraepithelial pre-neoplastic lesions (PanINs) and progression to adenocarcinoma is observed in PDA.MUC1 mice, possibly due to increased proliferation. Tumors from PDA.MUC1 mice express higher levels of cyclooxygenase-2 and indoleamine 2,3, dioxygenase compared to PDA mice lacking MUC1, especially during early stages of tumor development. The increased pro-inflammatory milieu correlates with an increased percentage of regulatory T cells and myeloid suppressor cells in the pancreatic tumor and tumor draining lymph nodes. Data shows that during pancreatic cancer progression, MUC1-mediated mechanisms enhance the onset and progression of the disease which in turn regulate the immune responses. Thus, the mouse model is ideally-suited for testing novel chemopreventive and therapeutic strategies against pancreatic cancer. PMID:18713982
A Study of Enhanced, Higher Order Boussinesq-Type Equations and Their Numerical Modelling
DEFF Research Database (Denmark)
Banijamali, Babak
model is designated for the solution of higher-order Boussinesq-type equations, formulated in terms of the horizontal velocity at an arbitrary depth vector. Various discretisation techniques and grid definitions have been considered in this endeavour, undertaking a detailed analysis of the selected......This project has encompassed efforts in two separate veins: on the one hand, the acquiring of highly accurate model equations of the Boussinesq-type, and on the other hand, the theoretical and practical work in implementing such equations in the form of conventional numerical models, with obvious...... potential for applications to the realm of numerical modelling in coastal engineering. The derivation and analysis of several forms of higher-order in dispersion and non-linearity Boussinesq-type equations have been undertaken, obtaining and investigating the properties of a new and generalised class...
Modelling gas migration in fractured rock. A contribution to the EU's PROGRESS project
International Nuclear Information System (INIS)
Humm, J.; Robinson, P.; Clark, K.
2001-01-01
To assess the performance of a waste repository, it is necessary to be able to predict the rates of gas generation and to understand and evaluate both the way the gas may disperse from the repository and any effects that might be associated with this dispersal. This document describes the modelling work carried out by QuantiSci on behalf of the UK Environment Agency, in conjunction with the CEC PROGRESS Project (Research into Gas Generation and Migration in Radioactive Waste Repository Systems) which has been carried out as part of the European Commission's IV th framework R and D programme. The project was under the PEGASUS (Projects on the Effects of GAS in Underground Storage facilities) umbrella. A review is provided of alternative conceptual models for the migration of gas through an initially water saturated fracture. A range of front or interface tracking methods for computing gas migration through a fracture is described: direct discretisation, marker particle, volume of fluids and level set methods. Volume of fluids methods are identified as the most appropriate approach for models of this sort. Subsequently, a description is given of the development of a model of gas injection into a single fracture in a portion of Borrowdale Volcanic Granite. The theoretical approach for the model is described in detail and the model compared to experimental results obtained for the real fracture. The experimental results of the CEC PROGRESS Project (obtained using Positron Emission Tomography) do not show particularly good agreement with the model results. However, there are strong indications that this is largely the result of uncertainties in the interpretation of the PET results. The experimental results are acknowledged to be extremely hard to interpret and the apparent negative gas thicknesses observed experimentally confirm this fact. Given the clearly critical dependence of the gas migration pathways on the aperture distribution, any discrepancies of this sort
Soft-edged magnet models for higher-order beam-optics map codes
International Nuclear Information System (INIS)
Walstrom, P.L.
2004-01-01
Continuously varying surface and volume source-density distributions are used to model magnetic fields inside of cylindrical volumes. From these distributions, a package of subroutines computes on-axis generalized gradients and their derivatives at arbitrary points on the magnet axis for input to the numerical map-generating subroutines of the Lie-algebraic map code Marylie. In the present version of the package, the magnet menu includes: (1) cylindrical current-sheet or radially thick current distributions with either open boundaries or with a surrounding cylindrical boundary with normal field lines (which models high-permeability iron), (2) Halbach-type permanent multipole magnets, either as sheet magnets or as radially thick magnets, (3) modeling of arbitrary fields inside a cylinder by use of a fictitious current sheet. The subroutines provide on-axis gradients and their z derivatives to essentially arbitrary order, although in the present third- and fifth-order Marylie only the zeroth through sixth derivatives are needed. The formalism is especially useful in beam-optics applications, such as magnetic lenses, where realistic treatment of fringe-field effects is needed
Finite temperature CPN-1 model and long range Neel order
International Nuclear Information System (INIS)
Ichinose, Ikuo; Yamamoto, Hisashi.
1989-09-01
We study in d space-dimensions the finite temperature behavior of long range Neel order (LRNO) in CP N-1 model as a low energy effective field theory of the antiferromagnetic Heisenberg model. For d≤1, or d≤2 at any nonzero temperature, LRNO disappears, in agreement with Mermin-Wagner-Coleman's theorem. For d=3 in the weak coupling region, LRNO exists below the critical temperature T N (Neel temperature). T N decreases as the interlayer coupling becomes relatively weak compared with that within Cu-O layers. (author)
Magnetic ordering of four particle exchange model in BCC 3He
International Nuclear Information System (INIS)
Ishikawa, Koji; Okada, Isamu
1978-01-01
The low temperature magnetic ordering of BCC 3 He within the mean field approximation was studied. A model including four particle exchange interactions was considered. Two types of cyclic quadrupole exchange process, planar and folded, were taken into account. Assuming four sublattices, it was considered to minimize the spin energy with respect to the classical spin vector and to find out four ordered states at the absolute zero point. They are antiferromagnetic (AF), weak ferromagnetic (WF) and two kinds of simple cubic antiferromagnetic states (SCAF). The condition for the existence of each ordered state is given, and the free energies of the ordered states are calculated in the mean field approximation. The transition between AF or SCAF and the paramagnetic states is of the first order. The phase diagram is drawn in the parameter space. The phase diagram was obtained numerically at Hetherington and Willard's value and at its neighbouring values. The difference between the present result and HW's is that of magnetic field direction in the perpendicular simple cubic antiferromagnetic states. The second order transition disappears, and the WF state changes gradually into AF state. With respect to the first order transition, the transition temperature increases with magnetic field. In this case, a critical magnetic field exists. (Kato, T
Directory of Open Access Journals (Sweden)
Rafał Stanisławski
2016-01-01
Full Text Available This paper presents new results on modeling and analysis of dynamics of fractional-order discrete-time linear time-invariant single-input single-output (LTI SISO systems by means of new, two-layer, “fractional-order discrete-time Laguerre filters.” It is interesting that the fractionality of the filters at the upper system dynamics layer is directly projected from the lower Laguerre-based approximation layer for the Grünwald-Letnikov difference. A new stability criterion for discrete-time fractional-order Laguerre-based LTI SISO systems is introduced and supplemented with a stability preservation analysis. Both the stability criterion and the stability preservation analysis bring up rather surprising results, which is illustrated with simulation examples.
Optimizing lengths of confidence intervals: fourth-order efficiency in location models
Klaassen, C.; Venetiaan, S.
2010-01-01
Under regularity conditions the maximum likelihood estimator of the location parameter in a location model is asymptotically efficient among translation equivariant estimators. Additional regularity conditions warrant third- and even fourth-order efficiency, in the sense that no translation
Creixell-Mediante, Ester; Jensen, Jakob S.; Naets, Frank; Brunskog, Jonas; Larsen, Martin
2018-06-01
Finite Element (FE) models of complex structural-acoustic coupled systems can require a large number of degrees of freedom in order to capture their physical behaviour. This is the case in the hearing aid field, where acoustic-mechanical feedback paths are a key factor in the overall system performance and modelling them accurately requires a precise description of the strong interaction between the light-weight parts and the internal and surrounding air over a wide frequency range. Parametric optimization of the FE model can be used to reduce the vibroacoustic feedback in a device during the design phase; however, it requires solving the model iteratively for multiple frequencies at different parameter values, which becomes highly time consuming when the system is large. Parametric Model Order Reduction (pMOR) techniques aim at reducing the computational cost associated with each analysis by projecting the full system into a reduced space. A drawback of most of the existing techniques is that the vector basis of the reduced space is built at an offline phase where the full system must be solved for a large sample of parameter values, which can also become highly time consuming. In this work, we present an adaptive pMOR technique where the construction of the projection basis is embedded in the optimization process and requires fewer full system analyses, while the accuracy of the reduced system is monitored by a cheap error indicator. The performance of the proposed method is evaluated for a 4-parameter optimization of a frequency response for a hearing aid model, evaluated at 300 frequencies, where the objective function evaluations become more than one order of magnitude faster than for the full system.
Reduced-Order Models for Load Management in the Power Grid
Alizadeh, Mahnoosh
In recent years, considerable research efforts have been directed towards designing control schemes that can leverage the inherent flexibility of electricity demand that is not tapped into in today's electricity markets. It is expected that these control schemes will be carried out by for-profit entities referred to as aggregators that operate at the edge of the power grid network. While the aggregator control problem is receiving much attention, more high-level questions of how these aggregators should plan their market participation, interact with the main grid and with each other, remain rather understudied. Answering these questions requires a large-scale model for the aggregate flexibility that can be harnessed from the a population of customers, particularly for residences and small businesses. The contribution of this thesis towards this goal is divided into three parts: In Chapter 3, a reduced-order model for a large population of heterogeneous appliances is provided by clustering load profiles that share similar degrees of freedom together. The use of such reduced-order model for system planning and optimal market decision making requires a foresighted approximation of the number of appliances that will join each cluster. Thus, Chapter 4 provides a systematic framework to generate such forecasts for the case of Electric Vehicles, based on real-world battery charging data. While these two chapters set aside the economic side that is naturally involved with participation in demand response programs and mainly focus on the control problem, Chapter 5 is dedicated to the study of optimal pricing mechanisms in order to recruit heterogeneous customers in a demand response program in which an aggregator can directly manage their appliances' load under their specified preferences. Prices are proportional to the wholesale market savings that can result from each recruitment event.
An isotonic partial credit model for ordering subjects on the basis of their sum scores
Ligtvoet, R.
2012-01-01
In practice, the sum of the item scores is often used as a basis for comparing subjects. For items that have more than two ordered score categories, only the partial credit model (PCM) and special cases of this model imply that the subjects are stochastically ordered on the common latent variable.
Narlikar, Leelavati; Mehta, Nidhi; Galande, Sanjeev; Arjunwadkar, Mihir
2013-01-01
The structural simplicity and ability to capture serial correlations make Markov models a popular modeling choice in several genomic analyses, such as identification of motifs, genes and regulatory elements. A critical, yet relatively unexplored, issue is the determination of the order of the Markov model. Most biological applications use a predetermined order for all data sets indiscriminately. Here, we show the vast variation in the performance of such applications with the order. To identify the ‘optimal’ order, we investigated two model selection criteria: Akaike information criterion and Bayesian information criterion (BIC). The BIC optimal order delivers the best performance for mammalian phylogeny reconstruction and motif discovery. Importantly, this order is different from orders typically used by many tools, suggesting that a simple additional step determining this order can significantly improve results. Further, we describe a novel classification approach based on BIC optimal Markov models to predict functionality of tissue-specific promoters. Our classifier discriminates between promoters active across 12 different tissues with remarkable accuracy, yielding 3 times the precision expected by chance. Application to the metagenomics problem of identifying the taxum from a short DNA fragment yields accuracies at least as high as the more complex mainstream methodologies, while retaining conceptual and computational simplicity. PMID:23267010
Effect of fluoxetine on disease progression in a mouse model of ALS
Koschnitzky, J. E.; Quinlan, K. A.; Lukas, T. J.; Kajtaz, E.; Kocevar, E. J.; Mayers, W. F.; Siddique, T.
2014-01-01
Selective serotonin reuptake inhibitors (SSRIs) and other antidepressants are often prescribed to amyotrophic lateral sclerosis (ALS) patients; however, the impact of these prescriptions on ALS disease progression has not been systematically tested. To determine whether SSRIs impact disease progression, fluoxetine (Prozac, 5 or 10 mg/kg) was administered to mutant superoxide dismutase 1 (SOD1) mice during one of three age ranges: neonatal [postnatal day (P)5–11], adult presymptomatic (P30 to end stage), and adult symptomatic (P70 to end stage). Long-term adult fluoxetine treatment (started at either P30 or P70 and continuing until end stage) had no significant effect on disease progression. In contrast, neonatal fluoxetine treatment (P5-11) had two effects. First, all animals (mutant SOD1G93A and control: nontransgenic and SOD1WT) receiving the highest dose (10 mg/kg) had a sustained decrease in weight from P30 onward. Second, the high-dose SOD1G93A mice reached end stage ∼8 days (∼6% decrease in life span) sooner than vehicle and low-dose animals because of an increased rate of motor impairment. Fluoxetine increases synaptic serotonin (5-HT) levels, which is known to increase spinal motoneuron excitability. We confirmed that 5-HT increases spinal motoneuron excitability during this neonatal time period and therefore hypothesized that antagonizing 5-HT receptors during the same time period would improve disease outcome. However, cyproheptadine (1 or 5 mg/kg), a 5-HT receptor antagonist, had no effect on disease progression. These results show that a brief period of antidepressant treatment during a critical time window (the transition from neonatal to juvenile states) can be detrimental in ALS mouse models. PMID:24598527
Quantifying and modeling birth order effects in autism.
Directory of Open Access Journals (Sweden)
Tychele Turner
Full Text Available Autism is a complex genetic disorder with multiple etiologies whose molecular genetic basis is not fully understood. Although a number of rare mutations and dosage abnormalities are specific to autism, these explain no more than 10% of all cases. The high heritability of autism and low recurrence risk suggests multifactorial inheritance from numerous loci but other factors also intervene to modulate risk. In this study, we examine the effect of birth rank on disease risk which is not expected for purely hereditary genetic models. We analyzed the data from three publicly available autism family collections in the USA for potential birth order effects and studied the statistical properties of three tests to show that adequate power to detect these effects exist. We detect statistically significant, yet varying, patterns of birth order effects across these collections. In multiplex families, we identify V-shaped effects where middle births are at high risk; in simplex families, we demonstrate linear effects where risk increases with each additional birth. Moreover, the birth order effect is gender-dependent in the simplex collection. It is currently unknown whether these patterns arise from ascertainment biases or biological factors. Nevertheless, further investigation of parental age-dependent risks yields patterns similar to those observed and could potentially explain part of the increased risk. A search for genes considering these patterns is likely to increase statistical power and uncover novel molecular etiologies.
Directory of Open Access Journals (Sweden)
Gholamreza Khaje Sarvi
2013-03-01
Full Text Available Implementing Investigations, analyzes and performance measurements in special and qualitative social/cultural arena in our country, needs local and special methodologies. Thus the aim of present article is investigating these issues: the concept of culture, classification of cultural organizations in Islamic Republic of Iran, the Pyramidal structure of cultural hierarchy, the process of development and mutual influences of institutions, reviewing related literature of policy making in cultural issues, compatibility of strategies to existing realities in cultural performance structure, double division in measures and analyzing and elaborating suggested measures in elaborating weighting model and assessment method and investigating progress measures by focusing on Islamic-Iranian pattern of progress and investigating the effects of implementing this pattern plus weighting method and using related measures and studying some university cases which are implemented in three phases in universities and high education centers overall the country. This research has shown a linear model by considering weighting coefficients.
International Nuclear Information System (INIS)
Chalupka, A.; Dirninger, G.
1982-01-01
The progress report describes the scientific work and research results of the institute for radium research and nuclear physics of the Austrian Academy of Sciences for the period of 1981. The progress report covers the subject areas of nuclear theory, nuclear model calculations, experimental nuclear physics and neutron involved reactions, medium energy physics, instrumentation and detectors, evaluation of nuclear data and numerical data processing, dating, applications in medicine, dosimetry and environmental studies. A list of publications of this institute is given. (A.N.)
International Nuclear Information System (INIS)
Chalupka, A.; Wild, E.; Dirninger, G.
1983-01-01
The progress report describes the scientific work and research results of the institute for radium research and nuclear physics of the Austrian Academy of Sciences for the period of 1982. The progress report covers the subject areas of nuclear theory, nuclear model calculations, experimental nuclear physics and neutron involved reactions, medium energy physics, instrumentation and detectors, evaluation of nuclear data and numerical data processing, dating, applications in medicine, dosimetry and environmental studies. A list of publications of this institute is given. (A.N.)
The Effect of Units Lost Due to Deterioration in Fuzzy Economic Order Quantity (FEOQ) Model
M. Pattnaik
2013-01-01
For several decades, the Economic Order Quantity (EOQ) model and its variations have received much attention from researchers. Recently, there has been an investigation into an EOQ model incorporating effect of units lost due to deterioration in infinite planning horizon with crisp decision environment. Accounting for holding and ordering cost, as has traditionally been the case of modeling inventory systems in fuzzy environment are investigated which are not precisely known and defined on a ...
Albaugh, Alex; Head-Gordon, Teresa; Niklasson, Anders M N
2018-02-13
Generalized extended Lagrangian Born-Oppenheimer molecular dynamics (XLBOMD) methods provide a framework for fast iteration-free simulations of models that normally require expensive electronic ground state optimizations prior to the force evaluations at every time step. XLBOMD uses dynamically driven auxiliary degrees of freedom that fluctuate about a variationally optimized ground state of an approximate "shadow" potential which approximates the true reference potential. While the requirements for such shadow potentials are well understood, constructing such potentials in practice has previously been ad hoc, and in this work, we present a systematic development of XLBOMD shadow potentials that match the reference potential to any order. We also introduce a framework for combining friction-like dissipation for the auxiliary degrees of freedom with general-order integration, a combination that was not previously possible. These developments are demonstrated with a simple fluctuating charge model and point induced dipole polarization models.
Two-Stage orders sequencing system for mixed-model assembly
Zemczak, M.; Skolud, B.; Krenczyk, D.
2015-11-01
In the paper, the authors focus on the NP-hard problem of orders sequencing, formulated similarly to Car Sequencing Problem (CSP). The object of the research is the assembly line in an automotive industry company, on which few different models of products, each in a certain number of versions, are assembled on the shared resources, set in a line. Such production type is usually determined as a mixed-model production, and arose from the necessity of manufacturing customized products on the basis of very specific orders from single clients. The producers are nowadays obliged to provide each client the possibility to determine a huge amount of the features of the product they are willing to buy, as the competition in the automotive market is large. Due to the previously mentioned nature of the problem (NP-hard), in the given time period only satisfactory solutions are sought, as the optimal solution method has not yet been found. Most of the researchers that implemented inaccurate methods (e.g. evolutionary algorithms) to solving sequencing problems dropped the research after testing phase, as they were not able to obtain reproducible results, and met problems while determining the quality of the received solutions. Therefore a new approach to solving the problem, presented in this paper as a sequencing system is being developed. The sequencing system consists of a set of determined rules, implemented into computer environment. The system itself works in two stages. First of them is connected with the determination of a place in the storage buffer to which certain production orders should be sent. In the second stage of functioning, precise sets of sequences are determined and evaluated for certain parts of the storage buffer under certain criteria.
A spatially explicit model for the future progression of the current Haiti cholera epidemic
Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.
2011-12-01
As a major cholera epidemic progresses in Haiti, and the figures of the infection, up to July 2011, climb to 385,000 cases and 5,800 deaths, the development of general models to track and predict the evolution of the outbreak, so as to guide the allocation of medical supplies and staff, is gaining notable urgency. We propose here a spatially explicit epidemic model that accounts for the dynamics of susceptible and infected individuals as well as the redistribution of textit{Vibrio cholera}, the causative agent of the disease, among different human communities. In particular, we model two spreading pathways: the advection of pathogens through hydrologic connections and the dissemination due to human mobility described by means of a gravity-like model. To this end the country has been divided into hydrologic units based on drainage directions derived from a digital terrain model. Moreover the population of each unit has been estimated from census data downscaled to 1 km x 1 km resolution via remotely sensed geomorphological information (LandScan texttrademark project). The model directly account for the role of rainfall patterns in driving the seasonality of cholera outbreaks. The two main outbreaks in fact occurred during the rainy seasons (October and May) when extensive floodings severely worsened the sanitation conditions and, in turn, raised the risk of infection. The model capability to reproduce the spatiotemporal features of the epidemic up to date grants robustness to the foreseen future development. In this context, the duration of acquired immunity, a hotly debated topic in the scientific community, emerges as a controlling factor for progression of the epidemic in the near future. The framework presented here can straightforwardly be used to evaluate the effectiveness of alternative intervention strategies like mass vaccinations, clean water supply and educational campaigns, thus emerging as an essential component of the control of future cholera
An efficient flexible-order model for 3D nonlinear water waves
DEFF Research Database (Denmark)
Engsig-Karup, Allan Peter; Bingham, Harry B.; Lindberg, Ole
2009-01-01
The flexible-order, finite difference based fully nonlinear potential flow model described in [H.B. Bingham, H. Zhang, On the accuracy of finite difference solutions for nonlinear water waves, J. Eng. Math. 58 (2007) 211-228] is extended to three dimensions (3D). In order to obtain an optimal......, robustness and energy conservation are presented together with demonstrations of grid independent iteration count and optimal scaling of the solution effort. Calculations are made for 3D nonlinear wave problems for steep nonlinear waves and a shoaling problem which show good agreement with experimental...
A genetic model of progressively partial melting for uranium-bearing granites in south China
International Nuclear Information System (INIS)
Zhai Jianping.
1989-01-01
A genetic model of progressively partial and enrichment mechanism of uranium during partial melting of the sources of material studied and the significance of the genetic model in search of uranium deposits is elaborated. This model accounts better for some geological and geochemical features of uranium-bearing granties and suspects the traditional idea that igneous uranium-bearing granites were formed by fusion of U-rich strata surrounding these granites. Finally this paper points out that the infuence of U-rich strata of wall rocks of granites over uranium-bearing granites depends on variation of water solubility in the magma and assimilation of magma to wall rocks during its ascending and crystallization
A New Model of the Fractional Order Dynamics of the Planetary Gears
Directory of Open Access Journals (Sweden)
Vera Nikolic-Stanojevic
2013-01-01
Full Text Available A theoretical model of planetary gears dynamics is presented. Planetary gears are parametrically excited by the time-varying mesh stiffness that fluctuates as the number of gear tooth pairs in contact changes during gear rotation. In the paper, it has been indicated that even the small disturbance in design realizations of this gear cause nonlinear properties of dynamics which are the source of vibrations and noise in the gear transmission. Dynamic model of the planetary gears with four degrees of freedom is used. Applying the basic principles of analytical mechanics and taking the initial and boundary conditions into consideration, it is possible to obtain the system of equations representing physical meshing process between the two or more gears. This investigation was focused to a new model of the fractional order dynamics of the planetary gear. For this model analytical expressions for the corresponding fractional order modes like one frequency eigen vibrational modes are obtained. For one planetary gear, eigen fractional modes are obtained, and a visualization is presented. By using MathCAD the solution is obtained.
Monalisha Pattnaik
2014-01-01
Background: This model presents the effect of deteriorating items in fuzzy optimal instantaneous replenishment for finite planning horizon. Accounting for holding cost per unit per unit time and ordering cost per order have traditionally been the case of modeling inventory systems in fuzzy environment. These imprecise parameters defined on a bounded interval on the axis of real numbers and the physical characteristics of stocked items dictate the nature of inventory policies implemented ...
Theory and Low-Order Modeling of Unsteady Airfoil Flows
Ramesh, Kiran
Unsteady flow phenomena are prevalent in a wide range of problems in nature and engineering. These include, but are not limited to, aerodynamics of insect flight, dynamic stall in rotorcraft and wind turbines, leading-edge vortices in delta wings, micro-air vehicle (MAV) design, gust handling and flow control. The most significant characteristics of unsteady flows are rapid changes in the circulation of the airfoil, apparent-mass effects, flow separation and the leading-edge vortex (LEV) phenomenon. Although experimental techniques and computational fluid dynamics (CFD) methods have enabled the detailed study of unsteady flows and their underlying features, a reliable and inexpensive loworder method for fast prediction and for use in control and design is still required. In this research, a low-order methodology based on physical principles rather than empirical fitting is proposed. The objective of such an approach is to enable insights into unsteady phenomena while developing approaches to model them. The basis of the low-order model developed here is unsteady thin-airfoil theory. A time-stepping approach is used to solve for the vorticity on an airfoil camberline, allowing for large amplitudes and nonplanar wakes. On comparing lift coefficients from this method against data from CFD and experiments for some unsteady test cases, it is seen that the method predicts well so long as LEV formation does not occur and flow over the airfoil is attached. The formation of leading-edge vortices (LEVs) in unsteady flows is initiated by flow separation and the formation of a shear layer at the airfoil's leading edge. This phenomenon has been observed to have both detrimental (dynamic stall in helicopters) and beneficial (high-lift flight in insects) effects. To predict the formation of LEVs in unsteady flows, a Leading Edge Suction Parameter (LESP) is proposed. This parameter is calculated from inviscid theory and is a measure of the suction at the airfoil's leading edge. It
Progress in the development of the GMM-2 gravity field model for Mars
Lemoine, F. G.; Smith, D. E.; Lerch, F. J.; Zuber, M. T.; Patel, G. B.
1994-01-01
Last year we published the GMM-1 (Goddard Mars Model-1) gravity model for Mars. We have completely re-analyzed the Viking and Mariner 9 tracking data in the development of the new field, designated GMM-2. The model is complete to degree and order 70. Various aspects of the model are discussed.
Efficient response spectrum analysis of a reactor using Model Order Reduction
International Nuclear Information System (INIS)
Oh, Jin Ho; Choi, Jin Bok; Ryu, Jeong Soo
2012-01-01
A response spectrum analysis (RSA) has been widely used to evaluate the structural integrity of various structural components in the nuclear industry. However, solving the large and complex structural systems numerically using the RSA requires a considerable amount of computational resources and time. To overcome this problem, this paper proposes the RSA based on the model order reduction (MOR) technique achieved by applying a projection from a higher order to a lower order space using Krylov subspaces generated by the Arnoldi algorithm. The dynamic characteristics of the final reduced system are almost identical with those of the full system by matching the moments of the reduced system with those of the full system up to the required nth order. It is remarkably efficient in terms of computation time and does not require a global system. Numerical examples demonstrate that the proposed method saves computational costs effectively, and provides a reduced system framework that predicts the accurate responses of a global system
Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.
Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha
2017-09-01
Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.
Teaching Higher Order Thinking in the Introductory MIS Course: A Model-Directed Approach
Wang, Shouhong; Wang, Hai
2011-01-01
One vision of education evolution is to change the modes of thinking of students. Critical thinking, design thinking, and system thinking are higher order thinking paradigms that are specifically pertinent to business education. A model-directed approach to teaching and learning higher order thinking is proposed. An example of application of the…
Energy Technology Data Exchange (ETDEWEB)
Silveira, L.M.; Kamon, M.; Elfadel, I.; White, J. [Massachusetts Inst. of Technology, Cambridge, MA (United States)
1996-12-31
Model order reduction based on Krylov subspace iterative methods has recently emerged as a major tool for compressing the number of states in linear models used for simulating very large physical systems (VLSI circuits, electromagnetic interactions). There are currently two main methods for accomplishing such a compression: one is based on the nonsymmetric look-ahead Lanczos algorithm that gives a numerically stable procedure for finding Pade approximations, while the other is based on a less well characterized Arnoldi algorithm. In this paper, we show that for certain classes of generalized state-space systems, the reduced-order models produced by a coordinate-transformed Arnoldi algorithm inherit the stability of the original system. Complete Proofs of our results will be given in the final paper.
An Isotonic Partial Credit Model for Ordering Subjects on the Basis of Their Sum Scores
Ligtvoet, Rudy
2012-01-01
In practice, the sum of the item scores is often used as a basis for comparing subjects. For items that have more than two ordered score categories, only the partial credit model (PCM) and special cases of this model imply that the subjects are stochastically ordered on the common latent variable. However, the PCM is very restrictive with respect…
Directory of Open Access Journals (Sweden)
Busch Michael P
2007-12-01
Full Text Available Abstract Background Chronic hepatitis C virus infection is prevalent and often causes hepatic fibrosis, which can progress to cirrhosis and cause liver cancer or liver failure. Study of fibrosis progression often relies on imputing the time of infection, often as the reported age of first injection drug use. We sought to examine the accuracy of such imputation and implications for modeling factors that influence progression rates. Methods We analyzed cross-sectional data on hepatitis C antibody status and reported risk factor histories from two large studies, the Women's Interagency HIV Study and the Urban Health Study, using modern survival analysis methods for current status data to model past infection risk year by year. We compared fitted distributions of past infection risk to reported age of first injection drug use. Results Although injection drug use appeared to be a very strong risk factor, models for both studies showed that many subjects had considerable probability of having been infected substantially before or after their reported age of first injection drug use. Persons reporting younger age of first injection drug use were more likely to have been infected after, and persons reporting older age of first injection drug use were more likely to have been infected before. Conclusion In cross-sectional studies of fibrosis progression where date of HCV infection is estimated from risk factor histories, modern methods such as multiple imputation should be used to account for the substantial uncertainty about when infection occurred. The models presented here can provide the inputs needed by such methods. Using reported age of first injection drug use as the time of infection in studies of fibrosis progression is likely to produce a spuriously strong association of younger age of infection with slower rate of progression.
Progressive damage analysis of carbon/epoxy laminates under couple laser and mechanical loading
Directory of Open Access Journals (Sweden)
Wanlei Liu
Full Text Available A multiscale model based bridge theory is proposed for the progressive damage analysis of carbon/epoxy laminates under couple laser and mechanical loading. The ablation model is adopted to calculate ablation temperature changing and ablation surface degradation. The polynomial strengthening model of matrix is used to improve bridging model for reducing parameter input. Stiffness degradation methods of bridging model are also improved in order to analyze the stress redistribution more accurately when the damage occurs. Thermal-mechanical analyses of the composite plate are performed using the ABAQUS/Explicit program with the developed model implemented in the VUMAT. The simulation results show that this model can be used to proclaim the mesoscale damage mechanism of composite laminates under coupled loading. Keywords: Laser irradiation, Multiscale analysis, Bridge model, Thermal-mechanical
DEFF Research Database (Denmark)
Yang, Zhiwen; Liu, Shuxue; Bingham, Harry B.
2013-01-01
, 171–186] is extended to include the second-order dispersive correction. The new formulation is presented in a unified form that includes both progressive and evanescent modes and covers wavemaker configurations of the piston- and flap-type. The second order paddle stroke correction allows for improved...... nonlinear wave generation in the physical wave tank based on target numerical solutions. The performance and efficiency of the new model is first evaluated theoretically based on second order Stokes waves. Due to the complexity of the problem, the proposed method has been truncated at 2D and the treatment...... that the new second-order coupling theory provides an improvement in the quality of nonlinear wave generation when compared to existing techniques....
Twisted quantum double model of topological order with boundaries
Bullivant, Alex; Hu, Yuting; Wan, Yidun
2017-10-01
We generalize the twisted quantum double model of topological orders in two dimensions to the case with boundaries by systematically constructing the boundary Hamiltonians. Given the bulk Hamiltonian defined by a gauge group G and a 3-cocycle in the third cohomology group of G over U (1 ) , a boundary Hamiltonian can be defined by a subgroup K of G and a 2-cochain in the second cochain group of K over U (1 ) . The consistency between the bulk and boundary Hamiltonians is dictated by what we call the Frobenius condition that constrains the 2-cochain given the 3-cocyle. We offer a closed-form formula computing the ground-state degeneracy of the model on a cylinder in terms of the input data only, which can be naturally generalized to surfaces with more boundaries. We also explicitly write down the ground-state wave function of the model on a disk also in terms of the input data only.
Power law-based local search in spider monkey optimisation for lower order system modelling
Sharma, Ajay; Sharma, Harish; Bhargava, Annapurna; Sharma, Nirmala
2017-01-01
The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimisation problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This paper presents a solution for lower order system modelling using spider monkey optimisation (SMO) algorithm to obtain a better approximation for lower order systems and reflects almost original higher order system's characteristics. Further, a local search strategy, namely, power law-based local search is incorporated with SMO. The proposed strategy is named as power law-based local search in SMO (PLSMO). The efficiency, accuracy and reliability of the proposed algorithm is tested over 20 well-known benchmark functions. Then, the PLSMO algorithm is applied to solve the lower order system modelling problem.
Coupled Atmosphere-Wave-Ocean Modeling of Tropical Cyclones: Progress, Challenges, and Ways Forward
Chen, Shuyi
2015-04-01
It has long been recognized that air-sea interaction plays an important role in tropical cyclones (TC) intensity change. However, most current numerical weather prediction (NWP) models are deficient in predicting TC intensity. The extreme high winds, intense rainfall, large ocean waves, and copious sea spray in TCs push the surface-exchange parameters for temperature, water vapor, and momentum into untested regimes. Parameterizations of air-sea fluxes in NWP models are often crude and create "manmade" energy source/sink that does not exist, especially in the absence of a fully interactive ocean in the model. The erroneous surface heat, moisture, and momentum fluxes can cause compounding errors in the model (e.g., precipitation, water vapor, boundary layer properties). The energy source (heat and moisture fluxes from the ocean) and sink (surface friction and wind-induced upper ocean cooling) are critical to TC intensity. However, observations of air-sea fluxes in TCs are very limited, especially in extreme high wind conditions underneath of the eyewall region. The Coupled Boundary Layer Air-Sea Transfer (CBLAST) program was designed to better understand the air-sea interaction, especially in high wind conditions, which included laboratory and coupled model experiments and field campaign in 2003-04 hurricane seasons. Significant progress has been made in better understanding of air-sea exchange coefficients up to 30 m/s, i.e., a leveling off in drag coefficient and relatively invariant exchange coefficient of enthalpy with wind speed. More recently, the Impact of Typhoon on the Ocean in the Pacific (ITOP) field campaign in 2010 has provided an unprecedented data set to study the air-sea fluxes in TCs and their impact on TC structure and intensity. More than 800 GPS dropsondes and 900 AXBTs/AXCTs as well as drifters, floats, and moorings were deployed in TCs, including Typhoons Fanapi and Malakas, and Supertyphoon Megi with a record peak wind speed of more than 80 m
Connection between weighted LPC and higher-order statistics for AR model estimation
Kamp, Y.; Ma, C.
1993-01-01
This paper establishes the relationship between a weighted linear prediction method used for robust analysis of voiced speech and the autoregressive modelling based on higher-order statistics, known as cumulants
Progressive Impairment of Lactate-based Gluconeogenesis in the Huntington's Disease Mouse Model R6/2
DEFF Research Database (Denmark)
Nielsen, Signe Marie Borch; Hasholt, Lis; Nørremølle, Anne
2015-01-01
of impairment of lactate-based hepatic gluconeogenesis in the transgenic HD mouse model R6/2 and determine that the defect manifests very early and progresses in severity with disease development, indicating a potential to explore this defect in a biomarker context. Moreover, R6/2 animals displayed lower blood...
A Hybrid PO - Higher-Order Hierarchical MoM Formulation using Curvilinear Geometry Modeling
DEFF Research Database (Denmark)
Jørgensen, E.; Meincke, Peter; Breinbjerg, Olav
2003-01-01
which implies a very modest memory requirement. Nevertheless, the hierarchical feature of the basis functions maintains the ability to treat small geometrical details efficiently. In addition, the scatterer is modelled with higher-order curved patches which allows accurate modelling of curved surfaces...
An ETP model (exclusion-tolerance-progression for multi drug resistance
Directory of Open Access Journals (Sweden)
Kannan Subburaj
2005-04-01
Full Text Available Abstract Background It is known that sensitivity or resistance of tumor cells to a given chemotherapeutic agent is an acquired characteristic(s, depending on the heterogeneity of the tumor mass subjected to the treatment. The clinical success of a chemotherapeutic regimen depends on the ratio of sensitive to resistant cell populations. Results Based on findings from clinical and experimental studies, a unifying model is proposed to delineate the potential mechanism by which tumor cells progress towards multi drug resistance, resulting in failure of chemotherapy. Conclusion It is suggested that the evolution of multi drug resistance is a developmentally orchestrated event. Identifying stage-specific time windows during this process would help to identify valid therapeutic targets for the effective elimination of malignancy.
Accuracy Analysis of the Zero-Order Hold Model for Digital Pulsewidth Modulation
DEFF Research Database (Denmark)
Ma, Junpeng; Wang, Xiongfei; Blaabjerg, Frede
2018-01-01
This paper analyzes the accuracy of the zero-order hold (ZOH) model for the digital pulsewidth modulator (DPWM) in the s-domain. The s-domain model and the exact z-domain model for the control loop of the single-phase inverter with L-type filter is elaborated for quantifying the deviation...... of the ZOH model for DPWM. The influence of the different computational delay and duty-cycle update modes on this deviation is analyzed in detail. The compensation method for this deviation of the ZOH model is proposed for accurately predicting the stability region of the control system in the s...
Damaging role of neutrophilic infiltration in a mouse model of progressive tuberculosis.
Marzo, Elena; Vilaplana, Cristina; Tapia, Gustavo; Diaz, Jorge; Garcia, Vanessa; Cardona, Pere-Joan
2014-01-01
Tuberculosis was studied using an experimental model based on the C3HeB/FeJ mouse strain, which mimics the liquefaction of caseous necrosis occurring during active disease in immunocompetent adults. Mice were intravenously infected with 2 × 10(4) Colony Forming Units of Mycobacterium tuberculosis and their histopathology, immune response, bacillary load, and survival were evaluated. The effects of the administration of drugs with anti-inflammatory activity were examined, and the C3H/HeN mouse strain was also included for comparative purposes. Massive intra-alveolar neutrophilic infiltration led to rapid granuloma growth and coalescence of lesions into superlesions. A central necrotic area appeared showing progressive cellular destruction, the alveoli cell walls being initially conserved (caseous necrosis) but finally destroyed (liquefactive necrosis). Increasing levels of pro-inflammatory mediators were detected in lungs. C3HeB/FeJ treated with anti-inflammatory drugs and C3H/HeN animals presented lower levels of pro-inflammatory mediators such as TNF-α, IL-17, IL-6 and CXCL5, a lower bacillary load, better histopathology, and increased survival compared with untreated C3HeB/FeJ. The observation of massive neutrophilic infiltration suggests that inflammation may be a key factor in progression towards active tuberculosis. On the basis of our findings, we consider that the C3HeB/FeJ mouse model would be useful for evaluating new therapeutic strategies against human tuberculosis. Copyright © 2013 Elsevier Ltd. All rights reserved.
Frequency-domain reduced order models for gravitational waves from aligned-spin compact binaries
International Nuclear Information System (INIS)
Pürrer, Michael
2014-01-01
Black-hole binary coalescences are one of the most promising sources for the first detection of gravitational waves. Fast and accurate theoretical models of the gravitational radiation emitted from these coalescences are highly important for the detection and extraction of physical parameters. Spinning effective-one-body models for binaries with aligned-spins have been shown to be highly faithful, but are slow to generate and thus have not yet been used for parameter estimation (PE) studies. I provide a frequency-domain singular value decomposition-based surrogate reduced order model that is thousands of times faster for typical system masses and has a faithfulness mismatch of better than ∼0.1% with the original SEOBNRv1 model for advanced LIGO detectors. This model enables PE studies up to signal-to-noise ratios (SNRs) of 20 and even up to 50 for total masses below 50 M ⊙ . This paper discusses various choices for approximations and interpolation over the parameter space that can be made for reduced order models of spinning compact binaries, provides a detailed discussion of errors arising in the construction and assesses the fidelity of such models. (paper)
Directory of Open Access Journals (Sweden)
Xin Lu
2018-03-01
Full Text Available In recent years, the fractional order model has been employed to state of charge (SOC estimation. The non integer differentiation order being expressed as a function of recursive factors defining the fractality of charge distribution on porous electrodes. The battery SOC affects the fractal dimension of charge distribution, therefore the order of the fractional order model varies with the SOC at the same condition. This paper proposes a new method to estimate the SOC. A fractional continuous variable order model is used to characterize the fractal morphology of charge distribution. The order identification results showed that there is a stable monotonic relationship between the fractional order and the SOC after the battery inner electrochemical reaction reaches balanced. This feature makes the proposed model particularly suitable for SOC estimation when the battery is in the resting state. Moreover, a fast iterative method based on the proposed model is introduced for SOC estimation. The experimental results showed that the proposed iterative method can quickly estimate the SOC by several iterations while maintaining high estimation accuracy.
A Predictive Model of Multi-Stage Production Planning for Fixed Time Orders
Directory of Open Access Journals (Sweden)
Kozłowski Edward
2014-09-01
Full Text Available The traditional production planning model based upon a deterministic approach is well described in the literature. Due to the uncertain nature of manufacturing processes, such model can however incorrectly represent actual situations on the shop floor. This study develops a mathematical modeling framework for generating production plans in a multistage manufacturing process. The devised model takes into account the stochastic model for predicting the occurrence of faulty products. The aim of the control model is to determine the number of products which should be manufactured in each planning period to minimize both manufacturing costs and potential financial penalties for failing to fulfill the order completely.
Vanderburgh, Joseph; Sterling, Julie A.
2016-01-01
2D cell culture and preclinical animal models have traditionally been implemented for investigating the underlying cellular mechanisms of human disease progression. However, the increasing significance of 3D versus 2D cell culture has initiated a new era in cell culture research in which 3D in vitro models are emerging as a bridge between traditional 2D cell culture and in vivo animal models. Additive manufacturing (AM, also known as 3D printing), defined as the layer-by-layer fabrication of parts directed by digital information from a 3D computer-aided design (CAD) file, offers the advantages of simultaneous rapid prototyping and biofunctionalization as well as the precise placement of cells and extracellular matrix with high resolution. In this review, we highlight recent advances in 3D printing of tissue engineered constructs (TECs) that recapitulate the physical and cellular properties of the tissue microenvironment for investigating mechanisms of disease progression and for screening drugs. PMID:27169894
Developing and validating a predictive model for stroke progression
Craig, L.E.; Wu, Olivia; Gilmour, H.; Barber, M.; Langhorne, P.
2011-01-01
Background: Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. \\ud \\ud Methods: Two patient cohorts were used for this study – the first cohort formed the trainin...
Daly, Rónán; Edwards, Kieron D.; O'Neill, John S.; Aitken, Stuart; Millar, Andrew J.; Girolami, Mark
Modelling gene regulatory networks in organisms is an important task that has recently become possible due to large scale assays using technologies such as microarrays. In this paper, the circadian clock of Arabidopsis thaliana is modelled by fitting dynamic Bayesian networks to luminescence data gathered from experiments. This work differs from previous modelling attempts by using higher-order dynamic Bayesian networks to explicitly model the time lag between the various genes being expressed. In order to achieve this goal, new techniques in preprocessing the data and in evaluating a learned model are proposed. It is shown that it is possible, to some extent, to model these time delays using a higher-order dynamic Bayesian network.
A 3-D model of tumor progression based on complex automata driven by particle dynamics.
Wcisło, Rafał; Dzwinel, Witold; Yuen, David A; Dudek, Arkadiusz Z
2009-12-01
The dynamics of a growing tumor involving mechanical remodeling of healthy tissue and vasculature is neglected in most of the existing tumor models. This is due to the lack of efficient computational framework allowing for simulation of mechanical interactions. Meanwhile, just these interactions trigger critical changes in tumor growth dynamics and are responsible for its volumetric and directional progression. We describe here a novel 3-D model of tumor growth, which combines particle dynamics with cellular automata concept. The particles represent both tissue cells and fragments of the vascular network. They interact with their closest neighbors via semi-harmonic central forces simulating mechanical resistance of the cell walls. The particle dynamics is governed by both the Newtonian laws of motion and the cellular automata rules. These rules can represent cell life-cycle and other biological interactions involving smaller spatio-temporal scales. We show that our complex automata, particle based model can reproduce realistic 3-D dynamics of the entire system consisting of the tumor, normal tissue cells, blood vessels and blood flow. It can explain phenomena such as the inward cell motion in avascular tumor, stabilization of tumor growth by the external pressure, tumor vascularization due to the process of angiogenesis, trapping of healthy cells by invading tumor, and influence of external (boundary) conditions on the direction of tumor progression. We conclude that the particle model can serve as a general framework for designing advanced multiscale models of tumor dynamics and it is very competitive to the modeling approaches presented before.
DEFF Research Database (Denmark)
Mohanty, Sankhya; Staliulionis, Zygimantas; Shojaee Nasirabadi, Parizad
2016-01-01
the development of rigorous calibrated CFD models as well as simple predictive numerical tools, the current paper tackles the optimization of critical features of a typical two-chamber electronic enclosure. The progressive optimization strategy begins the design parameter selection by initially using simpler...
Directory of Open Access Journals (Sweden)
Godefrooij DA
2017-10-01
Full Text Available Daniel A Godefrooij, Mustapha El Kandoussi, Nienke Soeters, Robert PL Wisse Utrecht Cornea Research Group, Department of Ophthalmology, University Medical Center Utrecht, Utrecht, the Netherlands Purpose: The purpose of this study was to compare the effects of transepithelial crosslinking (trans-CXL versus epithelium-off crosslinking (epi-off CXL for progressive keratoconus with respect to the development of higher order aberrations (HOAs and their effects on visual acuity.Materials and methods: A total of 61 patients were randomized and examined preoperatively and 1, 3, 6, and 12 months postoperatively in an academic referral center. Total corneal HOAs were compared between the two treatment groups using mixed linear modeling. Types of HOAs (coma, trefoil, and spherical aberration that differed between groups were entered in a multivariable analysis to test their effect on uncorrected distance visual acuity (UDVA and corrected distance visual acuity (CDVA.Results: The epi-off CXL group had more flattening in maximal keratometry compared to the trans-CXL group (P=0.02. UDVA did not differ significantly between the groups (P=0.59; however, CDVA was significantly more improved in the trans-CXL group (P=0.02. Horizontal trefoil improved more in the epi-off group compared to the trans-CXL group (P=0.04, whereas the other HOAs were virtually unchanged in both groups. Differences in changes in HOAs between the two groups had no effect on either UCVA (P=0.76 or CDVA (P=0.96.Conclusion: Although HOAs are clinically relevant determinants of vision quality in keratoconus patients, the change in total HOAs post treatment did not differ between the trans-CXL and epi-off CXL groups. Only horizontal trefoil differed significantly post treatment between the trans-CXL and epi-off CXL groups. However, this difference did not independently affect either UDVA or CDVA. Trans-CXL provides no benefit over epi-off CXL regarding visual relevant HOAs. Keywords
Compound waves in a higher order nonlinear model of thermoviscous fluids
DEFF Research Database (Denmark)
Rønne Rasmussen, Anders; Sørensen, Mads Peter; Gaididei, Yuri B.
2016-01-01
A generalized traveling wave ansatz is used to investigate compound shock waves in a higher order nonlinear model of a thermoviscous fluid. The fluid velocity potential is written as a traveling wave plus a linear function of space and time. The latter offers the possibility of predicting...
Basic fibroblast growth factor in an animal model of spontaneous mammary tumor progression.
Kao, Steven; Mo, Jeffrey; Baird, Andrew; Eliceiri, Brian P
2012-06-01
Although basic fibroblast growth factor (FGF2) was the first pro-angiogenic molecule discovered, it has numerous activities on the growth and differentiation of non-vascular cell types. FGF2 is both stimulatory and inhibitory, depending on the cell type evaluated, the experimental design used and the context in which it is tested. Here, we investigated the effects of manipulating endogenous FGF2 on the development of mammary cancer to determine whether its endogenous contribution in vivo is pro- or anti-tumorigenic. Specifically, we examined the effects of FGF2 gene dosing in a cross between a spontaneous breast tumor model (PyVT+ mice) and FGF2-/- (FGF KO) mice. Using these mice, the onset and progression of mammary tumors was determined. As predicted, female FGF2 WT mice developed mammary tumors starting around 60 days after birth and by 80 days, 100% of FGF2 WT female mice had mammary tumors. In contrast, 80% of FGF2 KO female mice had no palpable tumors until nearly three weeks later (85 days) at times when 100% of the WT cohort was tumor positive. All FGF KO mice were tumor-bearing by 115 days. When we compared the onset of mammary tumor development and the tumor progression curves between FGF het and FGF KO mice, we observed a difference, which suggested a gene dosing effect. Analysis of the tumors demonstrated that there were significant differences in tumor size depending on FGF2 status. The delay in tumor onset supports a functional role for FGF2 in mammary tumor progression, but argues against an essential role for FGF2 in overall mammary tumor progression.
Fear Extinction as a Model for Translational Neuroscience: Ten Years of Progress
Milad, Mohammed R.; Quirk, Gregory J.
2016-01-01
The psychology of extinction has been studied for decades. Approximately 10 years ago, however, there began a concerted effort to understand the neural circuits of extinction of fear conditioning, in both animals and humans. Progress during this period has been facilitated by an unusual degree of coordination between rodent and human researchers examining fear extinction. This successful research program could serve as a model for translational research in other areas of behavioral neuroscience. Here we review the major advances and highlight new approaches to understanding and exploiting fear extinction. PMID:22129456
Directory of Open Access Journals (Sweden)
Bin Wang
2016-01-01
Full Text Available This paper studies the application of frequency distributed model for finite time control of a fractional order nonlinear hydroturbine governing system (HGS. Firstly, the mathematical model of HGS with external random disturbances is introduced. Secondly, a novel terminal sliding surface is proposed and its stability to origin is proved based on the frequency distributed model and Lyapunov stability theory. Furthermore, based on finite time stability and sliding mode control theory, a robust control law to ensure the occurrence of the sliding motion in a finite time is designed for stabilization of the fractional order HGS. Finally, simulation results show the effectiveness and robustness of the proposed scheme.
International Nuclear Information System (INIS)
Flisgen, Thomas
2015-01-01
The modeling of large chains of superconducting cavities with couplers is a challenging task in computational electrical engineering. The direct numerical treatment of these structures can easily lead to problems with more than ten million degrees of freedom. Problems of this complexity are typically solved with the help of parallel programs running on supercomputing infrastructures. However, these infrastructures are expensive to purchase, to operate, and to maintain. The aim of this thesis is to introduce and to validate an approach which allows for modeling large structures on a standard workstation. The novel technique is called State-Space Concatenations and is based on the decomposition of the complete structure into individual segments. The radio-frequency properties of the generated segments are described by a set of state-space equations which either emerge from analytical considerations or from numerical discretization schemes. The model order of these equations is reduced using dedicated model order reduction techniques. In a final step, the reduced-order state-space models of the segments are concatenated in accordance with the topology of the complete structure. The concatenation is based on algebraic continuity constraints of electric and magnetic fields on the decomposition planes and results in a compact state-space system of the complete radio-frequency structure. Compared to the original problem, the number of degrees of freedom is drastically reduced, i.e. a problem with more than ten million degrees of freedom can be reduced on a standard workstation to a problem with less than one thousand degrees of freedom. The final state-space system allows for determining frequency-domain transfer functions, field distributions, resonances, and quality factors of the complete structure in a convenient manner. This thesis presents the theory of the state-space concatenation approach and discusses several validation and application examples. The examples
Progress in computational toxicology.
Ekins, Sean
2014-01-01
Computational methods have been widely applied to toxicology across pharmaceutical, consumer product and environmental fields over the past decade. Progress in computational toxicology is now reviewed. A literature review was performed on computational models for hepatotoxicity (e.g. for drug-induced liver injury (DILI)), cardiotoxicity, renal toxicity and genotoxicity. In addition various publications have been highlighted that use machine learning methods. Several computational toxicology model datasets from past publications were used to compare Bayesian and Support Vector Machine (SVM) learning methods. The increasing amounts of data for defined toxicology endpoints have enabled machine learning models that have been increasingly used for predictions. It is shown that across many different models Bayesian and SVM perform similarly based on cross validation data. Considerable progress has been made in computational toxicology in a decade in both model development and availability of larger scale or 'big data' models. The future efforts in toxicology data generation will likely provide us with hundreds of thousands of compounds that are readily accessible for machine learning models. These models will cover relevant chemistry space for pharmaceutical, consumer product and environmental applications. Copyright © 2013 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Dilenko Viktor O.
2016-11-01
Full Text Available The paper presents methods for the accounting of autonomous and induced scientific and technological progress in the Harrod-Domar model of economic dynamics that imply determining the incremental capital/output ratio of the model in the form of special functions of time. As part of the received version of the Harrod-Domar model, on the basis of conditional data there conducted a numerical study of some aspects of the impact of parameters of scientific and technological progress and the initial state of the economy being modeled on peculiarities of corresponding trajectories of its dynamics. A simple economic and mathematical problem of determining an optimal value of investments in the implementation of the induced STP is formulated, and content interpretation of the obtained solution is carried out. Possible directions of development of the obtained results may be associated with the application of the proposed modification of the Harrod-Domar model to build and analyze mathematical models of optimal economic growth in view of the induced STP, as well as with the prospective use of these results to improve dynamic models of the Leontief type in terms of considering innovation processes (scientific and technical progress of various kinds.
Numerical simulation of progressive inlet orifices in boiling water reactor fuel
International Nuclear Information System (INIS)
Lundgren, Sara
2004-07-01
This thesis was carried out at Forsmark Nuclear Power Plant. The power plant in Forsmark consists of three boiling water reactors (BWR) which produce about 17% of Swedish electricity. In a BWR the nuclear reactions are used to boil water inside the reactor vessel. The water works both as a coolant and as a moderator and the resulting steam is used directly to run the turbines. A problem when running a BWR at low flow conditions is the density wave oscillations that might occur to the water flow inside the fuel assemblies. These oscillations arise due to the connection between power and flow rate in a heated channel with two-phase flow. In order to improve the stability performance of the channel an orifice plate is placed at the inlet of each fuel assembly. Today these orifice plates have sharp edges and a constant resistance coefficient. Experimental work has been done with progressive orifices, the edge of which is half-oval in shape. The advantage of progressive orifices is the lower pressure losses with an increase of the Reynolds number, a similar phenomenon that appears in external flow around curved bodies. Since there are high costs associated with experimental generation of high- temperature and high-pressure data, it is of some interest to be able to reproduce and generate data using Computational Fluid Dynamics (CFD). This work deals with the possibility to use the CFD-code Fluent to do numerical simulations of the flow through progressive orifices. The following conclusions may be drawn from the numerical results: All simulations using Reynolds-Averaged Navier-Stokes (RANS) turbulence models, two-dimensional and three-dimensional, capture an abrupt decrease of the resistance coefficient at higher Reynolds numbers. Two-equation models seem to under-predict the critical Reynolds number. The five-equation Reynolds Stress Model (RSM) gives a critical Reynolds number of the same order of magnitude of that measured in experiments. No major differences have
Disturbance estimation of nuclear power plant by using reduced-order model
International Nuclear Information System (INIS)
Tashima, Shin-ichi; Wakabayashi, Jiro
1983-01-01
An estimation method is proposed of multiplex disturbances which occur in a nuclear power plant. The method is composed of two parts: (i) the identification of a simplified model of multi-input and multi-output to describe the related system response, and (ii) the design of a Kalman filter to estimate the multiplex disturbance. Concerning the simplified model, several observed signals are firstly selected as output variables which can well represent the system response caused by the disturbances. A reduced-order model is utilized for designing the disturbance estimator. This is based on the following two considerations. The first is that the disturbance is assumed to be of a quasistatic nature. The other is based on the intuition that there exist a few dominant modes between the disturbances and the selected observed signals and that most of the non-dominant modes which remain may not affect the accuracy of the disturbance estimator. The reduced-order model is furtherly transformed to a single-output model using a linear combination of the output signals, where the standard procedure of the structural identification is evaded. The parameters of the model thus transformed are calculated by the generalized least square method. As for the multiplex disturbance estimator, the Kalman filtering method is applied by compromising the following three items : (a) quick response to disturbance, (b) reduction of estimation error in the presence of observation noises, and (c) the elimination of cross-interference between the disturbances to the plant and the estimates from the Kalman filter. The effectiveness of the proposed method is verified through some computer experiments using a BWR plant simulator. (author)
A Novel Entropy-Based Decoding Algorithm for a Generalized High-Order Discrete Hidden Markov Model
Directory of Open Access Journals (Sweden)
Jason Chin-Tiong Chan
2018-01-01
Full Text Available The optimal state sequence of a generalized High-Order Hidden Markov Model (HHMM is tracked from a given observational sequence using the classical Viterbi algorithm. This classical algorithm is based on maximum likelihood criterion. We introduce an entropy-based Viterbi algorithm for tracking the optimal state sequence of a HHMM. The entropy of a state sequence is a useful quantity, providing a measure of the uncertainty of a HHMM. There will be no uncertainty if there is only one possible optimal state sequence for HHMM. This entropy-based decoding algorithm can be formulated in an extended or a reduction approach. We extend the entropy-based algorithm for computing the optimal state sequence that was developed from a first-order to a generalized HHMM with a single observational sequence. This extended algorithm performs the computation exponentially with respect to the order of HMM. The computational complexity of this extended algorithm is due to the growth of the model parameters. We introduce an efficient entropy-based decoding algorithm that used reduction approach, namely, entropy-based order-transformation forward algorithm (EOTFA to compute the optimal state sequence of any generalized HHMM. This EOTFA algorithm involves a transformation of a generalized high-order HMM into an equivalent first-order HMM and an entropy-based decoding algorithm is developed based on the equivalent first-order HMM. This algorithm performs the computation based on the observational sequence and it requires OTN~2 calculations, where N~ is the number of states in an equivalent first-order model and T is the length of observational sequence.
17 CFR 256.107 - Construction work in progress.
2010-04-01
... UTILITY HOLDING COMPANY ACT OF 1935 Balance Sheet Accounts: Assets and Other Debit Accounts § 256.107 Construction work in progress. This account shall include the total of the balances of work orders for service company property in process of construction. Work orders shall be cleared from this account as soon as...
Energy Technology Data Exchange (ETDEWEB)
Meeks, E.; Chou, C. -P.; Garratt, T.
2013-03-31
Engineering simulations of coal gasifiers are typically performed using computational fluid dynamics (CFD) software, where a 3-D representation of the gasifier equipment is used to model the fluid flow in the gasifier and source terms from the coal gasification process are captured using discrete-phase model source terms. Simulations using this approach can be very time consuming, making it difficult to imbed such models into overall system simulations for plant design and optimization. For such system-level designs, process flowsheet software is typically used, such as Aspen Plus® [1], where each component where each component is modeled using a reduced-order model. For advanced power-generation systems, such as integrated gasifier/gas-turbine combined-cycle systems (IGCC), the critical components determining overall process efficiency and emissions are usually the gasifier and combustor. Providing more accurate and more computationally efficient reduced-order models for these components, then, enables much more effective plant-level design optimization and design for control. Based on the CHEMKIN-PRO and ENERGICO software, we have developed an automated methodology for generating an advanced form of reduced-order model for gasifiers and combustors. The reducedorder model offers representation of key unit operations in flowsheet simulations, while allowing simulation that is fast enough to be used in iterative flowsheet calculations. Using high-fidelity fluiddynamics models as input, Reaction Design’s ENERGICO® [2] software can automatically extract equivalent reactor networks (ERNs) from a CFD solution. For the advanced reduced-order concept, we introduce into the ERN a much more detailed kinetics model than can be included practically in the CFD simulation. The state-of-the-art chemistry solver technology within CHEMKIN-PRO allows that to be accomplished while still maintaining a very fast model turn-around time. In this way, the ERN becomes the basis for
Formal Learning Sequences and Progression in the Studio: A Framework for Digital Design Education
Directory of Open Access Journals (Sweden)
Pontus Wärnestål
2016-02-01
Full Text Available This paper examines how to leverage the design studio learning environment throughout long-term Digital Design education in order to support students to progress from tactical, well-defined, device-centric routine design, to confidently design sustainable solutions for strategic, complex, problems for a wide range of devices and platforms in the digital space. We present a framework derived from literature on design, creativity, and theories on learning that: (a implements a theory of formal learning sequences as a user-centered design process in the studio; and (b describes design challenge progressions in the design studio environment modeled in seven dimensions. The framework can be used as a tool for designing, evaluating, and communicating course progressions within – and between series of – design studio courses. This approach is evaluated by implementing a formal learning sequence framework in a series of design studio courses that progress in an undergraduate design-oriented Informatics program. Reflections from students, teachers, and external clients indicate high student motivation and learning goal achievement, high teacher satisfaction and skill development, and high satisfaction among external clients.
Development and analysis of a twelfth degree and order gravity model for Mars
Christensen, E. J.; Balmino, G.
1979-01-01
Satellite geodesy techniques previously applied to artificial earth satellites have been extended to obtain a high-resolution gravity field for Mars. Two-way Doppler data collected by 10 Deep Space Network (DSN) stations during Mariner 9 and Viking 1 and 2 missions have been processed to obtain a twelfth degree and order spherical harmonic model for the martian gravitational potential. The quality of this model was evaluated by examining the rms residuals within the fit and the ability of the model to predict the spacecraft state beyond the fit. Both indicators show that more data and higher degree and order harmonics will be required to further refine our knowledge of the martian gravity field. The model presented shows much promise, since it resolves local gravity features which correlate highly with the martian topography. An isostatic analysis based on this model, as well as an error analysis, shows rather complete compensation on a global (long wavelength) scale. Though further model refinements are necessary to be certain, local (short wavelength) features such as the shield volcanos in Tharsis appear to be uncompensated. These are interpreted to place some bounds on the internal structure of Mars.
A Progress Review on Soot Experiments and Modeling in the Engine Combustion Network (ECN)
Skeen, Scott A.
2016-04-05
The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.
A Progress Review on Soot Experiments and Modeling in the Engine Combustion Network (ECN)
Skeen, Scott A.; Manin, Julien; Pickett, Lyle M.; Cenker, Emre; Bruneaux, Gilles; Kondo, Katsufumi; Aizawa, Tets; Westlye, Fredrik; Dalen, Kristine; Ivarsson, Anders; Xuan, Tiemin; Garcia-Oliver, Jose M; Pei, Yuanjiang; Som, Sibendu; Hu, Wang; Reitz, Rolf D.; Lucchini, Tommaso; D'Errico, Gianluca; Farrace, Daniele; Pandurangi, Sushant S.; Wright, Yuri M.; Chishty, Muhammad Aqib; Bolla, Michele; Hawkes, Evatt
2016-01-01
The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.
International Nuclear Information System (INIS)
Sutheerawatthana, Pitch; Minato, Takayuki
2010-01-01
The response of a social group is a missing element in the formal impact assessment model. Previous discussion of the involvement of social groups in an intervention has mainly focused on the formation of the intervention. This article discusses the involvement of social groups in a different way. A descriptive model is proposed by incorporating a social group's response into the concept of second- and higher-order effects. The model is developed based on a cause-effect relationship through the observation of phenomena in case studies. The model clarifies the process by which social groups interact with a lower-order effect and then generate a higher-order effect in an iterative manner. This study classifies social groups' responses into three forms-opposing, modifying, and advantage-taking action-and places them in six pathways. The model is expected to be used as an analytical tool for investigating and identifying impacts in the planning stage and as a framework for monitoring social groups' responses during the implementation stage of a policy, plan, program, or project (PPPPs).
Higher-order anisotropies in the blast-wave model: Disentangling flow and density field anisotropies
Energy Technology Data Exchange (ETDEWEB)
Cimerman, Jakub [Czech Technical University in Prague, FNSPE, Prague (Czech Republic); Comenius University, FMPI, Bratislava (Slovakia); Tomasik, Boris [Czech Technical University in Prague, FNSPE, Prague (Czech Republic); Univerzita Mateja Bela, FPV, Banska Bystrica (Slovakia); Csanad, Mate; Loekoes, Sandor [Eoetvoes Lorand University, Budapest (Hungary)
2017-08-15
We formulate a generalisation of the blast-wave model which is suitable for the description of higher-order azimuthal anisotropies of the hadron production. The model includes anisotropy in the density profile as well as an anisotropy in the transverse expansion velocity field. We then study how these two kinds of anisotropies influence the single-particle distributions and the correlation radii of two-particle correlation functions. Particularly we focus on the third-order anisotropy and consideration is given averaging over different orientations of the event plane. (orig.)
Mukhopadhyay, Saumyadip; Abraham, John
2012-07-01
The unsteady flamelet progress variable (UFPV) model has been proposed by Pitsch and Ihme ["An unsteady/flamelet progress variable method for LES of nonpremixed turbulent combustion," AIAA Paper No. 2005-557, 2005] for modeling the averaged/filtered chemistry source terms in Reynolds averaged simulations and large eddy simulations of reacting non-premixed combustion. In the UFPV model, a look-up table of source terms is generated as a function of mixture fraction Z, scalar dissipation rate χ, and progress variable C by solving the unsteady flamelet equations. The assumption is that the unsteady flamelet represents the evolution of the reacting mixing layer in the non-premixed flame. We assess the accuracy of the model in predicting autoignition and flame development in compositionally stratified n-heptane/air mixtures using direct numerical simulations (DNS). The focus in this work is primarily on the assessment of accuracy of the probability density functions (PDFs) employed for obtaining averaged source terms. The performance of commonly employed presumed functions, such as the dirac-delta distribution function, the β distribution function, and statistically most likely distribution (SMLD) approach in approximating the shapes of the PDFs of the reactive and the conserved scalars is evaluated. For unimodal distributions, it is observed that functions that need two-moment information, e.g., the β distribution function and the SMLD approach with two-moment closure, are able to reasonably approximate the actual PDF. As the distribution becomes multimodal, higher moment information is required. Differences are observed between the ignition trends obtained from DNS and those predicted by the look-up table, especially for smaller gradients where the flamelet assumption becomes less applicable. The formulation assumes that the shape of the χ(Z) profile can be modeled by an error function which remains unchanged in the presence of heat release. We show that this
The Nordic Model in a Global Company Situated in Norway. Challenging Institutional Orders?
Directory of Open Access Journals (Sweden)
Elin Kvande
2012-11-01
Full Text Available In this article, we explore the impact of internationalization as organizational processes where institutional actors meet in local contexts and negotiate the institutional order. The internationalization of working life implies that different traditions and practices meet and challenge each other. The focus is on how important elements of the Nordic micro model like cooperation between employees and employers and regulation of working hours are implemented in a global company situated in Norway. In general, it seems that employees and employers cooperate in line with this tradition in the Nordic micro model. Norwegian manager’s practices are described to be in accordance with Scandinavian management traditions, while managers from the United States appear to practice management consistent with the liberal working life model. The findings show a tension-filled clash between two different management practices, which indicates that the Nordic micro model in this field might be under pressure. Manager’s recommendation to the employees was not to become members of the trade union. The absence of trade unions in the organization implies that employees and employers are not cooperating on a collective level. This means that only parts of the regulatory arrangement related to participation and cooperation are implemented. Findings concerning working time and the relation to the institutional order represented by the Norwegian Work Environment Act indicate a clear tension between different institutional traditions in the organization. The company does not respect the Norwegian in working time regulations. These regulations are seen as counterproductive for a company that competes in the international market. This devaluation of the regulations in the Nordic model implies that the institutional order represented in the Nordic micro model is challenged.
Endogenous Technological Progress with Uncertainty and Carbon Abatement Polices
Energy Technology Data Exchange (ETDEWEB)
Cho, G.L. [Korea Energy Economics Institute, Euiwang (Korea)
2001-11-01
Most greenhouse gas abatement policy models tend to neglect a potentially important element that is relevant to the induced technology changes(ITC). These models that incorporate technological change treat such a change as autonomous, that is, unaffected by changes in prices brought about by policy reforms. However, climate change policies can create economic incentives to engage in more extensive R and D oriented toward the discovery of new production techniques that mitigate a reliance on convectional fuels, ultimately resulting in impacts on the policies themselves. In order to investigate the significance of induced technology for the attractiveness of abatement policies, this study develop the multi-sectoral dynamic CGE model by incorporating two characteristics of technological progress: the endogenous growth model with externality of technology in Romer (1986) and Lucas(1988) and the technological changes resulting from profit maximizing investment in R and D in Rebelo(1991) and Jones and Manuelli(1990). Furthermore, technological progress is affected by not only the economical factors but also the political and institutional system that cannot be captured in this model. This study considers such uncertainty in the technological progress as technology shock as in RBC school. This study shows that the presence of ITC implies lower costs of achieving a given abatement target in terms of the reduction cost per ton of carbon and GDP losses. The presence of ITC reduces the GDP losses by 0.9%p{approx}1.5%p compared with the absence of the ITC. As the abatement target is substantially high, R and D is reduced significantly even in the presence of ITC. Therefore, it is necessary to seriously consider the tax recycling for enhancing R and D investment, which minimizes the GDP losses. The reduction cost is highly sensitive to the uncertainty in technological progress. The technology shock leads the reduction cost to widely vary, in terms of standard deviation, 3
Heavy-traffic limits for polling models with exhaustive service and non-FCFS service orders
P. Vis (Petra); R. Bekker (Rene); R.D. van der Mei (Rob)
2015-01-01
htmlabstractWe study cyclic polling models with exhaustive service at each queue under a variety of non-FCFS (first-come-first-served) local service orders, namely last-come-first-served with and without preemption, random-order-of-service, processor sharing, the multi-class priority scheduling with
Fast prediction and evaluation of eccentric inspirals using reduced-order models
Barta, Dániel; Vasúth, Mátyás
2018-06-01
A large number of theoretically predicted waveforms are required by matched-filtering searches for the gravitational-wave signals produced by compact binary coalescence. In order to substantially alleviate the computational burden in gravitational-wave searches and parameter estimation without degrading the signal detectability, we propose a novel reduced-order-model (ROM) approach with applications to adiabatic 3PN-accurate inspiral waveforms of nonspinning sources that evolve on either highly or slightly eccentric orbits. We provide a singular-value decomposition-based reduced-basis method in the frequency domain to generate reduced-order approximations of any gravitational waves with acceptable accuracy and precision within the parameter range of the model. We construct efficient reduced bases comprised of a relatively small number of the most relevant waveforms over three-dimensional parameter-space covered by the template bank (total mass 2.15 M⊙≤M ≤215 M⊙ , mass ratio 0.01 ≤q ≤1 , and initial orbital eccentricity 0 ≤e0≤0.95 ). The ROM is designed to predict signals in the frequency band from 10 Hz to 2 kHz for aLIGO and aVirgo design sensitivity. Beside moderating the data reduction, finer sampling of fiducial templates improves the accuracy of surrogates. Considerable increase in the speedup from several hundreds to thousands can be achieved by evaluating surrogates for low-mass systems especially when combined with high-eccentricity.
Singer, Philipp; Helic, Denis; Taraghi, Behnam; Strohmaier, Markus
2014-01-01
One of the most frequently used models for understanding human navigation on the Web is the Markov chain model, where Web pages are represented as states and hyperlinks as probabilities of navigating from one page to another. Predominantly, human navigation on the Web has been thought to satisfy the memoryless Markov property stating that the next page a user visits only depends on her current page and not on previously visited ones. This idea has found its way in numerous applications such as Google's PageRank algorithm and others. Recently, new studies suggested that human navigation may better be modeled using higher order Markov chain models, i.e., the next page depends on a longer history of past clicks. Yet, this finding is preliminary and does not account for the higher complexity of higher order Markov chain models which is why the memoryless model is still widely used. In this work we thoroughly present a diverse array of advanced inference methods for determining the appropriate Markov chain order. We highlight strengths and weaknesses of each method and apply them for investigating memory and structure of human navigation on the Web. Our experiments reveal that the complexity of higher order models grows faster than their utility, and thus we confirm that the memoryless model represents a quite practical model for human navigation on a page level. However, when we expand our analysis to a topical level, where we abstract away from specific page transitions to transitions between topics, we find that the memoryless assumption is violated and specific regularities can be observed. We report results from experiments with two types of navigational datasets (goal-oriented vs. free form) and observe interesting structural differences that make a strong argument for more contextual studies of human navigation in future work.
Directory of Open Access Journals (Sweden)
Philipp Singer
Full Text Available One of the most frequently used models for understanding human navigation on the Web is the Markov chain model, where Web pages are represented as states and hyperlinks as probabilities of navigating from one page to another. Predominantly, human navigation on the Web has been thought to satisfy the memoryless Markov property stating that the next page a user visits only depends on her current page and not on previously visited ones. This idea has found its way in numerous applications such as Google's PageRank algorithm and others. Recently, new studies suggested that human navigation may better be modeled using higher order Markov chain models, i.e., the next page depends on a longer history of past clicks. Yet, this finding is preliminary and does not account for the higher complexity of higher order Markov chain models which is why the memoryless model is still widely used. In this work we thoroughly present a diverse array of advanced inference methods for determining the appropriate Markov chain order. We highlight strengths and weaknesses of each method and apply them for investigating memory and structure of human navigation on the Web. Our experiments reveal that the complexity of higher order models grows faster than their utility, and thus we confirm that the memoryless model represents a quite practical model for human navigation on a page level. However, when we expand our analysis to a topical level, where we abstract away from specific page transitions to transitions between topics, we find that the memoryless assumption is violated and specific regularities can be observed. We report results from experiments with two types of navigational datasets (goal-oriented vs. free form and observe interesting structural differences that make a strong argument for more contextual studies of human navigation in future work.
Electronic and ionic ordering in condensed matter plasmas
International Nuclear Information System (INIS)
March, N.H.
1981-01-01
Recent progress in treating phase transitions induced by Coulomb interactions is reviewed. This is done by appealing to simple models, and in particular to the one-component plasma, with its quantum-mechanical counterpart jellium. The relevance of the phase transition, to a body-centred-cubic crystal in the classical one-component plasma, to the freezing of liquid metals Na and K is stressed. By generalizing these arguments to a two-component system, regularities in the freezing of the molten alkali halides are understandable. Sublattice disorder in superionics, driven by Coulomb forces, is then discussed. Finally, the ordering of electrons in jellium, in the limit of complete degeneracy, is considered: evidence being presented for the existence of electron liquids in molten Na and K. (author)
The Effect of Units Lost Due to Deterioration in Fuzzy Economic Order Quantity (FEOQ Model
Directory of Open Access Journals (Sweden)
M. Pattnaik
2013-07-01
Full Text Available For several decades, the Economic Order Quantity (EOQ model and its variations have received much attention from researchers. Recently, there has been an investigation into an EOQ model incorporating effect of units lost due to deterioration in infinite planning horizon with crisp decision environment. Accounting for holding and ordering cost, as has traditionally been the case of modeling inventory systems in fuzzy environment are investigated which are not precisely known and defined on a bounded interval of real numbers. The question is how reliable are the EOQ models when items stocked deteriorate one time. This paper introduces Fuzzy Economic Order Quantity (FEOQ model in which it assumes that units lost due to deterioration is included in the objective function to properly model the problem in finite planning horizon. The numerical analysis shows that an appropriate fuzzy policy can benefit the retailer and that is significant, especially for deteriorating items is shown to be superior to that of crisp decision making. A computational algorithm using LINGO 13.0 and MATLAB (R2009a software are developed to find the optimal solution. Sensitivity analysis of the optimal solution is also studied and managerial insights are drawn which shows the influence of key model parameters.
Empirical tight-binding modeling of ordered and disordered semiconductor structures
International Nuclear Information System (INIS)
Mourad, Daniel
2010-01-01
In this thesis, we investigate the electronic and optical properties of pure as well as of substitutionally alloyed II-VI and III-V bulk semiconductors and corresponding semiconductor quantum dots by means of an empirical tight-binding (TB) model. In the case of the alloyed systems of the type A x B 1-x , where A and B are the pure compound semiconductor materials, we study the influence of the disorder by means of several extensions of the TB model with different levels of sophistication. Our methods range from rather simple mean-field approaches (virtual crystal approximation, VCA) over a dynamical mean-field approach (coherent potential approximation, CPA) up to calculations where substitutional disorder is incorporated on a finite ensemble of microscopically distinct configurations. In the first part of this thesis, we cover the necessary fundamentals in order to properly introduce the TB model of our choice, the effective bond-orbital model (EBOM). In this model, one s- and three p-orbitals per spin direction are localized on the sites of the underlying Bravais lattice. The matrix elements between these orbitals are treated as free parameters in order to reproduce the properties of one conduction and three valence bands per spin direction and can then be used in supercell calculations in order to model mixed bulk materials or pure as well as mixed quantum dots. Part II of this thesis deals with unalloyed systems. Here, we use the EBOM in combination with configuration interaction calculations for the investigation of the electronic and optical properties of truncated pyramidal GaN quantum dots embedded in AlN with an underlying zincblende structure. Furthermore, we develop a parametrization of the EBOM for materials with a wurtzite structure, which allows for a fit of one conduction and three valence bands per spin direction throughout the whole Brillouin zone of the hexagonal system. In Part III, we focus on the influence of alloying on the electronic and
Theoretical progress at CNDC theory group
International Nuclear Information System (INIS)
Lu Zhongdao
1993-01-01
In 1992, CNDC (Chinese Nuclear Data Center) theory group has made progress in model study, code making and data calculations for low energy nuclear reaction, intermediate and high energy nuclear reaction. It has also made progress in parameter library establishment. The brief explanations are presented
Fox, Robert J; Thompson, Alan; Baker, David; Baneke, Peer; Brown, Doug; Browne, Paul; Chandraratna, Dhia; Ciccarelli, Olga; Coetzee, Timothy; Comi, Giancarlo; Feinstein, Anthony; Kapoor, Raj; Lee, Karen; Salvetti, Marco; Sharrock, Kersten; Toosy, Ahmed; Zaratin, Paola; Zuidwijk, Kim
2012-11-01
Despite significant progress in the development of therapies for relapsing MS, progressive MS remains comparatively disappointing. Our objective, in this paper, is to review the current challenges in developing therapies for progressive MS and identify key priority areas for research. A collaborative was convened by volunteer and staff leaders from several MS societies with the mission to expedite the development of effective disease-modifying and symptom management therapies for progressive forms of multiple sclerosis. Through a series of scientific and strategic planning meetings, the collaborative identified and developed new perspectives on five key priority areas for research: experimental models, identification and validation of targets and repurposing opportunities, proof-of-concept clinical trial strategies, clinical outcome measures, and symptom management and rehabilitation. Our conclusions, tackling the impediments in developing therapies for progressive MS will require an integrated, multi-disciplinary approach to enable effective translation of research into therapies for progressive MS. Engagement of the MS research community through an international effort is needed to address and fund these research priorities with the ultimate goal of expediting the development of disease-modifying and symptom-relief treatments for progressive MS.
Thompson, Alan; Baker, David; Baneke, Peer; Brown, Doug; Browne, Paul; Chandraratna, Dhia; Ciccarelli, Olga; Coetzee, Timothy; Comi, Giancarlo; Feinstein, Anthony; Kapoor, Raj; Lee, Karen; Salvetti, Marco; Sharrock, Kersten; Toosy, Ahmed; Zaratin, Paola; Zuidwijk, Kim
2012-01-01
Despite significant progress in the development of therapies for relapsing MS, progressive MS remains comparatively disappointing. Our objective, in this paper, is to review the current challenges in developing therapies for progressive MS and identify key priority areas for research. A collaborative was convened by volunteer and staff leaders from several MS societies with the mission to expedite the development of effective disease-modifying and symptom management therapies for progressive forms of multiple sclerosis. Through a series of scientific and strategic planning meetings, the collaborative identified and developed new perspectives on five key priority areas for research: experimental models, identification and validation of targets and repurposing opportunities, proof-of-concept clinical trial strategies, clinical outcome measures, and symptom management and rehabilitation. Our conclusions, tackling the impediments in developing therapies for progressive MS will require an integrated, multi-disciplinary approach to enable effective translation of research into therapies for progressive MS. Engagement of the MS research community through an international effort is needed to address and fund these research priorities with the ultimate goal of expediting the development of disease-modifying and symptom-relief treatments for progressive MS. PMID:22917690
Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.
2012-04-01
Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.
Temporal aggregation in first order cointegrated vector autoregressive models
DEFF Research Database (Denmark)
La Cour, Lisbeth Funding; Milhøj, Anders
We study aggregation - or sample frequencies - of time series, e.g. aggregation from weekly to monthly or quarterly time series. Aggregation usually gives shorter time series but spurious phenomena, in e.g. daily observations, can on the other hand be avoided. An important issue is the effect of ...... of aggregation on the adjustment coefficient in cointegrated systems. We study only first order vector autoregressive processes for n dimensional time series Xt, and we illustrate the theory by a two dimensional and a four dimensional model for prices of various grades of gasoline...
Predictors of third and Higher order births in India
Directory of Open Access Journals (Sweden)
Payal Singh
2015-12-01
Full Text Available Background: Total fertility rate (TFR reflecting population growth is closely related to higher order parity progression. Many Indian states reached replacement level of TFR, but still states constituting nearly 40% population are with TFR ≥ 3. The predictors are the desire of son’s, poor contraceptives practices, younger age at marriage, child loss and shorter birth spacing. Objective: This analysis assessed the degree of relation of 3rd and higher order parity progression with the above mentioned predictors. Material and Methods: State/Union Territories wise proportions of women: progressing to ≥3 births, more sons desire, birth spacing <24 months, adopting modern contraception and median marriage age <18 years along with infant mortality rate (IMR were taken from NFHS-III report. Correlation matrix and stepwise forward multiple regression carried. Significance was seen at 5%. Results: Hindi speaking states constituting 38.92% nation population recorded TFR ≥3. Positive correlation of mothers progressing ≥ 3 births was highest (0.746 with those desiring more sons followed by IMR (0.445; while maximum negative correlation with those practicing modern contraceptives (-0.565 followed by median age at marriage (-0.391. Multiple regression analysis in order identified desire of more sons, practicing modern contraception and shorter birth spacing as the significant predictors and jointly explained 77.9% of the total variation with gain of 15.5% by adding modern contraceptive practice and 8.3% by adding shorter birth spacing. Conclusions: Desire of more sons appeared the most important predictor to progress ≥3 births that is governed by society culture and educational attainment, require attitudinal change. Further, mothers need motivation to practice both spacing and terminal methods once family is complete.
Boghaert, Eline; Radisky, Derek C; Nelson, Celeste M
2014-12-01
Ductal carcinoma in situ (DCIS) is a heterogeneous group of non-invasive lesions of the breast that result from abnormal proliferation of mammary epithelial cells. Pathologists characterize DCIS by four tissue morphologies (micropapillary, cribriform, solid, and comedo), but the underlying mechanisms that distinguish the development and progression of these morphologies are not well understood. Here we explored the conditions leading to the emergence of the different morphologies of DCIS using a two-dimensional multi-cell lattice-based model that incorporates cell proliferation, apoptosis, necrosis, adhesion, and contractility. We found that the relative rates of cell proliferation and apoptosis governed which of the four morphologies emerged. High proliferation and low apoptosis favored the emergence of solid and comedo morphologies. In contrast, low proliferation and high apoptosis led to the micropapillary morphology, whereas high proliferation and high apoptosis led to the cribriform morphology. The natural progression between morphologies cannot be investigated in vivo since lesions are usually surgically removed upon detection; however, our model suggests probable transitions between these morphologies during breast cancer progression. Importantly, cribriform and comedo appear to be the ultimate morphologies of DCIS. Motivated by previous experimental studies demonstrating that tumor cells behave differently depending on where they are located within the mammary duct in vivo or in engineered tissues, we examined the effects of tissue geometry on the progression of DCIS. In agreement with our previous experimental work, we found that cells are more likely to invade from the end of ducts and that this preferential invasion is regulated by cell adhesion and contractility. This model provides additional insight into tumor cell behavior and allows the exploration of phenotypic transitions not easily monitored in vivo.
X-ray scattering studies of non-equilibrium ordering processes
International Nuclear Information System (INIS)
Nagler, S.E.
1990-01-01
We report on the progress of our project entitled ''X-ray Scattering of Non-Equilibrium Ordering Processes.'' During the past year we have made the first synchrotron measurements of ordering in Cu 3 Au have revealed the presence of an intermediate, non-equilibrium ordered state. Preliminary work involving x-ray magnetic scattering has been carried out. Work is continuing in these areas as well as on related problems. 5 refs
Riva, Federico; Agliardi, Federico; Amitrano, David; Crosta, Giovanni B.
2018-01-01
Large alpine rock slopes undergo long-term evolution in paraglacial to postglacial environments. Rock mass weakening and increased permeability associated with the progressive failure of deglaciated slopes promote the development of potentially catastrophic rockslides. We captured the entire life cycle of alpine slopes in one damage-based, time-dependent 2-D model of brittle creep, including deglaciation, damage-dependent fluid occurrence, and rock mass property upscaling. We applied the model to the Spriana rock slope (Central Alps), affected by long-term instability after Last Glacial Maximum and representing an active threat. We simulated the evolution of the slope from glaciated conditions to present day and calibrated the model using site investigation data and available temporal constraints. The model tracks the entire progressive failure path of the slope from deglaciation to rockslide development, without a priori assumptions on shear zone geometry and hydraulic conditions. Complete rockslide differentiation occurs through the transition from dilatant damage to a compacting basal shear zone, accounting for observed hydraulic barrier effects and perched aquifer formation. Our model investigates the mechanical role of deglaciation and damage-controlled fluid distribution in the development of alpine rockslides. The absolute simulated timing of rock slope instability development supports a very long "paraglacial" period of subcritical rock mass damage. After initial damage localization during the Lateglacial, rockslide nucleation initiates soon after the onset of Holocene, whereas full mechanical and hydraulic rockslide differentiation occurs during Mid-Holocene, supporting a key role of long-term damage in the reported occurrence of widespread rockslide clusters of these ages.
Directory of Open Access Journals (Sweden)
Szymszal J.
2013-09-01
Full Text Available It has been found that the area where one can look for significant reserves in the procurement logistics is a rational management of the stock of raw materials. Currently, the main purpose of projects which increase the efficiency of inventory management is to rationalise all the activities in this area, taking into account and minimising at the same time the total inventory costs. The paper presents a method for optimising the inventory level of raw materials under a foundry plant conditions using two different control models. The first model is based on the estimate of an optimal level of the minimum emergency stock of raw materials, giving information about the need for an order to be placed immediately and about the optimal size of consignments ordered after the minimum emergency level has occurred. The second model is based on the estimate of a maximum inventory level of raw materials and an optimal order cycle. Optimisation of the presented models has been based on the previously done selection and use of rational methods for forecasting the time series of the delivery of a chosen auxiliary material (ceramic filters to a casting plant, including forecasting a mean size of the delivered batch of products and its standard deviation.
Defining Higher-Order Turbulent Moment Closures with an Artificial Neural Network and Random Forest
McGibbon, J.; Bretherton, C. S.
2017-12-01
Unresolved turbulent advection and clouds must be parameterized in atmospheric models. Modern higher-order closure schemes depend on analytic moment closure assumptions that diagnose higher-order moments in terms of lower-order ones. These are then tested against Large-Eddy Simulation (LES) higher-order moment relations. However, these relations may not be neatly analytic in nature. Rather than rely on an analytic higher-order moment closure, can we use machine learning on LES data itself to define a higher-order moment closure?We assess the ability of a deep artificial neural network (NN) and random forest (RF) to perform this task using a set of observationally-based LES runs from the MAGIC field campaign. By training on a subset of 12 simulations and testing on remaining simulations, we avoid over-fitting the training data.Performance of the NN and RF will be assessed and compared to the Analytic Double Gaussian 1 (ADG1) closure assumed by Cloudy Layers Unified By Binormals (CLUBB), a higher-order turbulence closure currently used in the Community Atmosphere Model (CAM). We will show that the RF outperforms the NN and the ADG1 closure for the MAGIC cases within this diagnostic framework. Progress and challenges in using a diagnostic machine learning closure within a prognostic cloud and turbulence parameterization will also be discussed.
Ordering Dynamics in Neuron Activity Pattern Model: An Insight to Brain Functionality.
Directory of Open Access Journals (Sweden)
Jasleen Gundh
Full Text Available We study the domain ordering kinetics in d = 2 ferromagnets which corresponds to populated neuron activities with both long-ranged interactions, V(r ∼ r-n and short-ranged interactions. We present the results from comprehensive Monte Carlo (MC simulations for the nonconserved Ising model with n ≥ 2, interaction range considering near and far neighbors. Our model results could represent the long-ranged neuron kinetics (n ≤ 4 in consistent with the same dynamical behaviour of short-ranged case (n ≥ 4 at far below and near criticality. We found that emergence of fast and slow kinetics of long and short ranged case could imitate the formation of connections among near and distant neurons. The calculated characteristic length scale in long-ranged interaction is found to be n independent (L(t ∼ t1/(n-2, whereas short-ranged interaction follows L(t ∼ t1/2 law and approximately preserve universality in domain kinetics. Further, we did the comparative study of phase ordering near the critical temperature which follows different behaviours of domain ordering near and far critical temperature but follows universal scaling law.
Kerfriden, P.; Goury, O.; Rabczuk, T.; Bordas, S.P.A.
2013-01-01
We propose in this paper a reduced order modelling technique based on domain partitioning for parametric problems of fracture. We show that coupling domain decomposition and projection-based model order reduction permits to focus the numerical effort where it is most needed: around the zones where damage propagates. No a priori knowledge of the damage pattern is required, the extraction of the corresponding spatial regions being based solely on algebra. The efficiency of the proposed approach is demonstrated numerically with an example relevant to engineering fracture. PMID:23750055
Interacting gaps model, dynamics of order book, and stock-market fluctuations
Czech Academy of Sciences Publication Activity Database
Svorenčík, A.; Slanina, František
2007-01-01
Roč. 57, - (2007), s. 453-462 ISSN 1434-6028 R&D Projects: GA MŠk 1P04OCP10.001 Institutional research plan: CEZ:AV0Z10100520 Keywords : interacting gaps model * dynamics of order book * stock - market fluctuations Subject RIV: BE - Theoretical Physics Impact factor: 1.356, year: 2007
Progress with lossy compression of data from the Community Earth System Model
Xu, H.; Baker, A.; Hammerling, D.; Li, S.; Clyne, J.
2017-12-01
Climate models, such as the Community Earth System Model (CESM), generate massive quantities of data, particularly when run at high spatial and temporal resolutions. The burden of storage is further exacerbated by creating large ensembles, generating large numbers of variables, outputting at high frequencies, and duplicating data archives (to protect against disk failures). Applying lossy compression methods to CESM datasets is an attractive means of reducing data storage requirements, but ensuring that the loss of information does not negatively impact science objectives is critical. In particular, test methods are needed to evaluate whether critical features (e.g., extreme values and spatial and temporal gradients) have been preserved and to boost scientists' confidence in the lossy compression process. We will provide an overview on our progress in applying lossy compression to CESM output and describe our unique suite of metric tests that evaluate the impact of information loss. Further, we will describe our processes how to choose an appropriate compression algorithm (and its associated parameters) given the diversity of CESM data (e.g., variables may be constant, smooth, change abruptly, contain missing values, or have large ranges). Traditional compression algorithms, such as those used for images, are not necessarily ideally suited for floating-point climate simulation data, and different methods may have different strengths and be more effective for certain types of variables than others. We will discuss our progress towards our ultimate goal of developing an automated multi-method parallel approach for compression of climate data that both maximizes data reduction and minimizes the impact of data loss on science results.
Nuclear theory research. Technical progress report
International Nuclear Information System (INIS)
1982-01-01
Progress is briefly described on the following studies: (1) Dirac phenomenology for deuteron elastic scattering, (2) Dirac wave functions in nuclear distorted wave calculations, (3) impulse approximation for p→p → dπ + reaction above the 3-3 resonance, (4) coherent π production, (5) nuclear potentials from Dirac bound state wavefunctions, (6) nonlocality effects in nuclear reactions, (7) unhappiness factors in DWBA description of (t,p) and (p,t) reactions, (8) absolute normalization of three-nucleon transfer reactions, (9) formulation of a finite-range CCBA computer program, (10) crossing symmetric solutions of the low equations, (11) pion scattering from quark bags, (12) study of the p 11 channel in the delta model, (13) isovector corrections in pion-nucleus scattering, (14) pionic excitation of nuclear giant resonances, and (15) isospin dependence of the second-order pion-nucleus optical potential
A Model-Free Diagnostic for Single-Peakedness of Item Responses Using Ordered Conditional Means
Polak, Marike; De Rooij, Mark; Heiser, Willem J.
2012-01-01
In this article we propose a model-free diagnostic for single-peakedness (unimodality) of item responses. Presuming a unidimensional unfolding scale and a given item ordering, we approximate item response functions of all items based on ordered conditional means (OCM). The proposed OCM methodology is based on Thurstone & Chave's (1929) "criterion…
McSwiggen, P.L.
1993-01-01
The minerals of the ternary carbonate system CaCO3 - MgCO3 - FeCO3 represent a complex series of solid solutions and ordering states. An understanding of those complexities requires a solution model that can both duplicate the subsolidus phase relationships and generate correct values for the activities. Such a solution model must account for the changes in the total energy of the system resulting from a change in the ordering state of the individual constituents. Various ordering models have been applied to binary carbonate systems, but no attempts have previously been made to model the ordering in the ternary system. This study derives a new set of equations that allow for the equilibrium degree of order to be calculated for a system involving three cations mixing on two sites, as in the case of the ternary carbonates. The method is based on the Bragg-Williams approach. From the degree of order, the mole fractions of the three cations in each of the two sites can be determined. Once the site occupancies have been established, a Margules-type mixing model can be used to determine the free energy of mixing in the solid solution and therefore the activities of the various components. ?? 1993 Springer-Verlag.
Venus spherical harmonic gravity model to degree and order 60
Konopliv, Alex S.; Sjogren, William L.
1994-01-01
The Magellan and Pioneer Venus Orbiter radiometric tracking data sets have been combined to produce a 60th degree and order spherical harmonic gravity field. The Magellan data include the high-precision X-band gravity tracking from September 1992 to May 1993 and post-aerobraking data up to January 5, 1994. Gravity models are presented from the application of Kaula's power rule for Venus and an alternative a priori method using surface accelerations. Results are given as vertical gravity acceleration at the reference surface, geoid, vertical Bouguer, and vertical isostatic maps with errors for the vertical gravity and geoid maps included. Correlation of the gravity with topography for the different models is also discussed.
Ordered LOGIT Model approach for the determination of financial distress.
Kinay, B
2010-01-01
Nowadays, as a result of the global competition encountered, numerous companies come up against financial distresses. To predict and take proactive approaches for those problems is quite important. Thus, the prediction of crisis and financial distress is essential in terms of revealing the financial condition of companies. In this study, financial ratios relating to 156 industrial firms that are quoted in the Istanbul Stock Exchange are used and probabilities of financial distress are predicted by means of an ordered logit regression model. By means of Altman's Z Score, the dependent variable is composed by scaling the level of risk. Thus, a model that can compose an early warning system and predict financial distress is proposed.
Najhan Mohd Nagib, Ahmad; Naufal Adnan, Ahmad; Ismail, Azianti; Halim, Nurul Hayati Abdul; Syuhadah Khusaini, Nurul
2016-11-01
The inventory model had been utilized since the early 1900s. The implementation of the inventory management model is generally to ensure that an organisation is able to fulfil customer's demand at the lowest possible cost to improve profitability. This paper focuses on reviewing previous published papers regarding inventory control model mainly in the food and beverage processing industry. The author discusses four inventory models, which are the make-to-stock (MTS), make-to-order (MTO), economic order quantity (EOQ), and hybrid of MTS-MTO models. The issues raised by the researchers on the above techniques as well as the elements need to be considered upon selection have been discussed in this paper. The main objective of the study is to highlight the important role played by these inventory control models in the food and beverage processing industry.
2D model for melt progression through rods and debris
International Nuclear Information System (INIS)
Fichot, F.
2001-01-01
During the degradation of a nuclear core in a severe accident scenario, the high temperatures reached lead to the melting of materials. The formation of liquid mixtures at various elevations is followed by the flow of molten materials through the core. Liquid mixture may flow under several configurations: axial relocation along the rods, horizontal motion over a plane surface such as the core support plate or a blockage of material, 2D relocation through a debris bed, etc.. The two-dimensional relocation of molten material through a porous debris bed, implemented for the simulation of late degradation phases, has opened a new way to the elaboration of the relocation model for the flow of liquid mixture along the rods. It is based on a volume averaging method, where wall friction and capillary effects are taken into account by introducing effective coefficients to characterize the solid matrix (rods, grids, debris, etc.). A local description of the liquid flow is necessary to derive the effective coefficients. Heat transfers are modelled in a similar way. The derivation of the conservation equations for the liquid mixture falling flow (momentum) in two directions (axial and radial-horizontal) and for the heat exchanges (energy) are the main points of this new model for simulating melt progression. In this presentation, the full model for the relocation and solidification of liquid materials through a rod bundle or a debris bed is described. It is implemented in the ICARE/CATHARE code, developed by IPSN in Cadarache. The main improvements and advantages of the new model are: A single formulation for liquid mixture relocation, in 2D, either through a rod bundle or a porous debris bed, Extensions to complex structures (grids, by-pass, etc..), The modeling of relocation of a liquid mixture over plane surfaces. (author)
Bubble nucleation in first-order inflation and other cosmological phase transitions
International Nuclear Information System (INIS)
Turner, M.S.; Weinberg, E.J.; Widrow, L.M.
1992-01-01
We address in some detail the kinematics of bubble nucleation and percolation in first-order cosmological phase transitions, with the primary focus on first-order inflation. We study how a first-order phase transition completes, describe measures of its progress, and compute the distribution of bubble sizes. For example, we find that the typical bubble size in a successful transition is of order 1% to 100% of the Hubble radius, and depends very weakly on the energy scale of the transition. We derive very general conditions that must be satisfied by Γ/H 4 to complete the phase transition (Γ=bubble nucleation rate per unit volume; H=expansion rate; physically, Γ/H 4 corresponds to the volume fraction of space occupied by bubbles nucleated over a Hubble time). In particular, Γ/H 4 must exceed 9/4π to successfully end inflation. To avoid the deleterious effects of bubbles nucleated early during inflation on primordial nucleosynthesis and on the isotropy and spectrum of the cosmic microwave background radiation, during most of inflation Γ/H 4 must be less than order 10 -4 --10 -3 . Our constraints imply that in a successful model of first-order inflation the phase transition must complete over a period of at most a few Hubble times and all but preclude individual bubbles from providing an interesting source of density perturbation. We note, though, that it is just possible for Poisson fluctuations in the number of moderately large-size bubbles to lead to interesting isocurvature perturbations, whose spectrum is not scale invariant. Finally, we analyze in detail several recently proposed models of first-order inflation
Estrada, Marta F; Rebelo, Sofia P; Davies, Emma J; Pinto, Marta T; Pereira, Hugo; Santo, Vítor E; Smalley, Matthew J; Barry, Simon T; Gualda, Emilio J; Alves, Paula M; Anderson, Elizabeth; Brito, Catarina
2016-02-01
3D cell tumour models are generated mainly in non-scalable culture systems, using bioactive scaffolds. Many of these models fail to reflect the complex tumour microenvironment and do not allow long-term monitoring of tumour progression. To overcome these limitations, we have combined alginate microencapsulation with agitation-based culture systems, to recapitulate and monitor key aspects of the tumour microenvironment and disease progression. Aggregates of MCF-7 breast cancer cells were microencapsulated in alginate, either alone or in combination with human fibroblasts, then cultured for 15 days. In co-cultures, the fibroblasts arranged themselves around the tumour aggregates creating distinct epithelial and stromal compartments. The presence of fibroblasts resulted in secretion of pro-inflammatory cytokines and deposition of collagen in the stromal compartment. Tumour cells established cell-cell contacts and polarised around small lumina in the interior of the aggregates. Over the culture period, there was a reduction in oestrogen receptor and membranous E-cadherin alongside loss of cell polarity, increased collective cell migration and enhanced angiogenic potential in co-cultures. These phenotypic alterations, typical of advanced stages of cancer, were not observed in the mono-cultures of MCF-7 cells. The proposed model system constitutes a new tool to study tumour-stroma crosstalk, disease progression and drug resistance mechanisms. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Ullah, Asmat; Chen, Wen; Khan, Mushtaq Ahmad
2017-07-01
This paper introduces a fractional order total variation (FOTV) based model with three different weights in the fractional order derivative definition for multiplicative noise removal purpose. The fractional-order Euler Lagrange equation which is a highly non-linear partial differential equation (PDE) is obtained by the minimization of the energy functional for image restoration. Two numerical schemes namely an iterative scheme based on the dual theory and majorization- minimization algorithm (MMA) are used. To improve the restoration results, we opt for an adaptive parameter selection procedure for the proposed model by applying the trial and error method. We report numerical simulations which show the validity and state of the art performance of the fractional-order model in visual improvement as well as an increase in the peak signal to noise ratio comparing to corresponding methods. Numerical experiments also demonstrate that MMAbased methodology is slightly better than that of an iterative scheme.